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Research Methodology: Cost Benefit Analysis

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About Cost Benefit Analysis

Cost benefit analysis is a systematic process for calculating and comparing benefits and costs of a project. A cost benefit analysis finds, quantifies, and adds all the positive factors (the benefits). Then it identifies, quantifies, and subtracts all the negatives (the costs). The difference between the two indicates whether the planned action is advisable. The real trick to doing a cost benefit analysis well is making sure you include all the costs and all the benefits and properly quantify them.

  • An Introduction to Cost Benefit Analysis San José State University Department of Economics
  • Cost Benefit Analysis Examples of techniques designed to determine the feasibility of a project or plan by quantifying costs and benefits, including external costs and benefits.
  • Benefit-Cost Analysis FEMA

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" cost benefit analysis " OR " benefit cost analysis " OR " costs and cost analysis " OR " cost effectiveness " AND " research methodologies "

Method Demonstrated by IQPs

  • A Cost-Benefit Analysis of a Geothermal Power Plant and Spa Baird, Timothy Brian;Chan, Chun-shek Charles;Kast, Peter Gregory
  • Energy Efficiency in Water Infrastructure Marinelli, Andy; Patenaude, Rachel Lynn; Toomey, Mary Kate
  • Leicester Energy Study Gabrielson, Christopher Daniel; Hanly, Stephen William; Montville, Laura Elizabeth

Books on Cost Benefit Analysis

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How to Do a Cost-Benefit Analysis & Why It’s Important

Woman Working in Finance

  • 05 Sep 2019

Are you unsure whether a particular decision is the best one for your business? Are you questioning whether a proposed project will be worth the effort and resources that will go into making it a success? Are you considering making a change to your business, marketing, or sales strategy, knowing that it might have repercussions throughout your organization?

The way that many businesses, organizations, and entrepreneurs answer these, and other, questions is through business analytics —specifically, by conducting a cost-benefit analysis.

Access your free e-book today.

What Is A Cost-Benefit Analysis?

A cost-benefit analysis is the process of comparing the projected or estimated costs and benefits (or opportunities) associated with a project decision to determine whether it makes sense from a business perspective.

Generally speaking, cost-benefit analysis involves tallying up all costs of a project or decision and subtracting that amount from the total projected benefits of the project or decision. (Sometimes, this value is represented as a ratio.)

If the projected benefits outweigh the costs, you could argue that the decision is a good one to make. If, on the other hand, the costs outweigh the benefits, then a company may want to rethink the decision or project.

There are enormous economic benefits to running these kinds of analyses before making significant organizational decisions. By doing analyses, you can parse out critical information, such as your organization’s value chain or a project’s ROI .

Cost-benefit analysis is a form of data-driven decision-making most often utilized in business, both at established companies and startups . The basic principles and framework can be applied to virtually any decision-making process, whether business-related or otherwise.

Related: 5 Business Analytics Skills for Professionals

Steps of a Cost-Benefit Analysis

1. establish a framework for your analysis.

For your analysis to be as accurate as possible, you must first establish the framework within which you’re conducting it. What, exactly, this framework looks like will depend on the specifics of your organization.

Identify the goals and objectives you’re trying to address with the proposal. What do you need to accomplish to consider the endeavor a success? This can help you identify and understand your costs and benefits, and will be critical in interpreting the results of your analysis.

Similarly, decide what metric you’ll be using to measure and compare the benefits and costs. To accurately compare the two, both your costs and benefits should be measured in the same “common currency.” This doesn’t need to be an actual currency, but it does frequently involve assigning a dollar amount to each potential cost and benefit.

2. Identify Your Costs and Benefits

Your next step is to sit down and compile two separate lists: One of all of the projected costs, and the other of the expected benefits of the proposed project or action.

When tallying costs, you’ll likely begin with direct costs , which include expenses directly related to the production or development of a product or service (or the implementation of a project or business decision). Labor costs, manufacturing costs, materials costs, and inventory costs are all examples of direct costs.

But it’s also important to go beyond the obvious. There are a few additional costs you must account for:

  • Indirect costs: These are typically fixed expenses, such as utilities and rent, that contribute to the overhead of conducting business.
  • Intangible costs: These are any current and future costs that are difficult to measure and quantify. Examples may include decreases in productivity levels while a new business process is rolled out, or reduced customer satisfaction after a change in customer service processes that leads to fewer repeat buys.
  • Opportunity costs: This refers to lost benefits, or opportunities, that arise when a business pursues one product or strategy over another.

Once those individual costs are identified, it’s equally important to understand the possible benefits of the proposed decision or project. Some of those benefits include:

  • Direct: Increased revenue and sales generated from a new product
  • Indirect: Increased customer interest in your business or brand
  • Intangible: Improved employee morale
  • Competitive: Being a first-mover within an industry or vertical

3. Assign a Dollar Amount or Value to Each Cost and Benefit

Once you’ve compiled exhaustive lists of all costs and benefits, you must establish the appropriate monetary units by assigning a dollar amount to each one. If you don’t give all the costs and benefits a value, then it will be difficult to compare them accurately.

Direct costs and benefits will be the easiest to assign a dollar amount to. Indirect and intangible costs and benefits, on the other hand, can be challenging to quantify. That does not mean you shouldn’t try, though; there are many software options and methodologies available for assigning these less-than-obvious values.

4. Tally the Total Value of Benefits and Costs and Compare

Once every cost and benefit has a dollar amount next to it, you can tally up each list and compare the two.

If total benefits outnumber total costs, then there is a business case for you to proceed with the project or decision. If total costs outnumber total benefits, then you may want to reconsider the proposal.

Beyond simply looking at how the total costs and benefits compare, you should also return to the framework established in step one. Does the analysis show you reaching the goals you’ve identified as markers for success, or does it show you falling short?

If the costs outweigh the benefits, ask yourself if there are alternatives to the proposal you haven’t considered. Additionally, you may be able to identify cost reductions that will allow you to reach your goals more affordably while still being effective.

Related: Finance vs. Accounting: What's the Difference?

Pros and Cons of Cost-Benefit Analysis

There are many positive reasons a business or organization might choose to leverage cost-benefit analysis as a part of their decision-making process. There are also several potential disadvantages and limitations that should be considered before relying entirely on a cost-benefit analysis.

Advantages of Cost-Benefit Analysis

A data-driven approach.

Cost-benefit analysis allows an individual or organization to evaluate a decision or potential project free of biases. As such, it offers an agnostic and evidence-based evaluation of your options, which can help your business become more data-driven and logical.

Makes Decisions Simpler

Business decisions are often complex by nature. By reducing a decision to costs versus benefits, the cost-benefit analysis can make this dilemma less complex.

Uncovers Hidden Costs and Benefits

Cost-benefit analysis forces you to outline every potential cost and benefit associated with a project, which can uncover less-than-obvious factors like indirect or intangible costs.

Limitations of Cost-Benefit Analysis

Difficult to predict all variables.

While cost-benefit analysis can help you outline the projected costs and benefits associated with a business decision, it’s challenging to predict all the factors that may impact the outcome. Changes in market demand, material costs, and the global business environment are unpredictable—especially in the long term.

Incorrect Data Can Skew Results

If you’re relying on incomplete or inaccurate data to finish your cost-benefit analysis, the results of the analysis will follow suit.

Better Suited to Short- and Mid-Length Projects

For projects or business decisions that involve longer timeframes, cost-benefit analysis has a greater potential of missing the mark for several reasons. For one, it’s typically more difficult to make accurate predictions the further into the future you go. It’s also possible that long-term forecasts won’t accurately account for variables such as inflation, which can impact the overall accuracy of the analysis.

Removes the Human Element

While a desire to make a profit drives most companies, there are other, non-monetary reasons an organization might decide to pursue a project or decision. In these cases, it can be difficult to reconcile moral or “human” perspectives with the business case.

A Guide to Advancing Your Career with Essentials Business Skills | Access Your Free E-Book | Download Now

In the end, cost-benefit analysis shouldn't be the only business analytics tool or strategy you use in determining how to move your organization into the future. Cost-benefit analysis isn’t the only type of economic analysis you can do to assess your business’s economic state, but a single option at your disposal.

Do you want to take your career to the next level? Download our free Guide to Advancing Your Career with Essential Business Skills to learn how enhancing your business knowledge can help you make an impact on your organization and be competitive in the job market.

This post was updated on July 12, 2022. It was originally published on September 5, 2019.

cost analysis research paper example

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Worked Example in Cost-Benefit Analysis

  • First Online: 29 May 2022

Cite this chapter

cost analysis research paper example

  • Rodrigo Mariño 3  

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This chapter builds upon the previous ones and provides a detailed description of the individual steps in designing a protocol for a cost-benefit analysis (CBA). The chapter starts with a definition of CBA and outlines problems and pitfalls with CBAs. To facilitate the understanding and the practical application of CBA principles and methods, a second part presents a case study of a CBA in oral health. The case study’s methodological framework is structured following a checklist proposed by Splett (The practitioner’s guide to cost-effectiveness analysis of nutrition interventions. https://www.ncemch.org/NCEMCH-publications/NtrnCstEff_Anl.pdf: 1996). Thus, although it is based on a published project, it has been simplified to fit this chapter’s objectives; as such, it may not reflect the complexities of a “real-life” CBA.

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An overview of the methodological aspects and policy implications of willingness-to-pay studies in oral health: a scoping review of existing literature

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Mariño, R. (2022). Worked Example in Cost-Benefit Analysis. In: Zaror, C., Mariño, R. (eds) Introduction to Economic Evaluation in Oral Health Care. Springer, Cham. https://doi.org/10.1007/978-3-030-96289-0_8

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The Official Journal of the Pan-Pacific Association of Input-Output Studies (PAPAIOS)

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Impact and cost–benefit analysis: a unifying approach

  • Pasquale Lucio Scandizzo   ORCID: orcid.org/0000-0002-8824-3589 1  

Journal of Economic Structures volume  10 , Article number:  10 ( 2021 ) Cite this article

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This paper presents a methodology to integrate cost–benefit analysis and SAM-CGE-based impact evaluation. While the two types of analysis have developed in parallel and without a clear connection, there is growing consensus that the two approaches should be integrated for complex investment projects, since their economic evaluation cannot rely solely on the partial equilibrium assumptions of cost–benefit (CB) analysis. Unlike CB analysis, impact evaluation looks at the economy as a complete system of interdependent components (industries, households, investors, government, importers, exporters). By integrating project accounting into a SAM-CGE framework, the methodology developed presents several properties that make it fit to the purpose of providing a reliable assessment of project contribution to the economy.

1 Background

A social accounting matrix (SAM) is an analytical construct that brings together the material input output matrix originally conceived by Leontief, with a consistent framework of transactions across production sectors, factors of production and various classes of economic agents. In the form that has become more popular and was developed first by Stone’s research team in Cambridge, the SAM is the basis of modern national accounting and records transactions across activities, production factors, and the main institutional agents that constitute a modern market economy, namely households, enterprises, government, the financial and the international trade sector. As for the input–output, but in more integrated and value-based fashion, a SAM collects data on inflows and outflows of services by recording receipts and payments using the double accounting principle in a mutually consistent form. By convention, each column of a SAM thus records payments from that account to each other account, while each row records receipts to a specific account from each other account, with total receipts being equal to total expenditures. For this reason, the columns reporting production activities outlays can be interpreted as production processes, whose costs, including factor payments, equal in aggregate the value of production. At the same time, the corresponding rows can be interpreted as the revenues of each activity from all other activities. The SAM records value added formation by accounting for payments from activities to primary production factors (capital and labor) and to the government in the form of indirect taxation. The SAM also accounts for income formation by recording payments from factors of production (value added) to households, government and other institutions, including the financial and the foreign sector, and by accounting for other transactions, including direct taxes, subsidies, interest payments and various types of transfers across institutions. The SAM concept and practice is at the base of the UN national account system (SNA), and in more recent years it has been extended to include environmental flows, such as carbon emissions and ecosystem services of various sort (Burthoo-Barah et al. 2019 ; Scandizzo and Cufari 2019 ; Scandizzo and Ferrarese 2015 ).

While the SAM has been often utilized to evaluate the indirect effects of capital expenditures from investment projects as a demand shock (Scandizzo and Ferrarese 2015 ; Debowicz et al. 2013 ), its use to assess the impact of the investment beyond the activation effects of the construction period, has been limited. The theory and practice of project evaluation has also typically neglected the fact that, while in the construction period a project may be considered as part of the capital formation account, after the construction period, the project is generally a production activity, which is linked to sectors, factors and institutions by a series of transactions that can be accounted for, using the same principles, industrial classification and balancing of all other activities represented in the SAM. For example, the increased demand generated by public investment in a new road during the construction period can be measured as a vector of purchases of capital goods, in analogy and as an implicit part of the investment (capital formation) vector in the SAM. Once completed, however, the road becomes a service producing activity that not only generates increased demand for inputs, but also contributes to revenue formation, increase consumer surpluses and spill over the economy thereby increasing economic activity in the rest of the economy. An investment project, in particular, is characterized by a cash flow, for each year or project life, that can be split into a series of costs and a series of revenues and, as such, conveniently represented in a specific column and row of a SAM. This representation not only provides a convenient way to represent a project in a SAM, but also suggests that SAM production activities can be seen as sets of investment projects at various stages of implementation and are thus subject to variations over time due to the overlapping of projects of different generations. In turn, this twofold consideration on the role of projects as activities and of the activities as overlapping ongoing projects, indicates that a proper SAM accounting should not only aim at accounting for direct responses to final demand changes, but also for the variation of the patterns of transactions (i.e., changes in the SAM coefficients) due to new projects and technologies.

Following Stone’s original interpretation (Stone 1952 ), SAM accounts and coefficients can be considered special cases, respectively, of a transaction and a response matrix for an economy. The response matrix can be more or less complex and may coincide with a linear approximation of a full-fledged computable general equilibrium model (Perali and Scandizzo 2018 ). In the case of an investment project, therefore, while the project cash flow can be directly incorporated in a transaction SAM, its translation into a column and row vector of coefficients require a series of assumptions on the technology and the behavior of the economic agents involved. In the simplest case, the response matrix is a matrix of input output coefficients for the production activities, and of expenditure shares for the behavior of the institutions (households, government, etc.). In the case of a CGE model, the project transaction column contains, for each period of project life, the project payments to the factors of production (including the project net revenues to capital), as well as to activities and institutions. The response (coefficient) column instead in the simplest case embeds the hypothesis that project outlays are fixed proportions of its total cost. Similarly, the project transaction row contains the revenues and possibly the external effects paid to the project by production activities, institutions and the financial sector. For these stakeholders the payments made to project represent costs for goods or services provided by the project, so that in the response matrix, they are converted into coefficients, which in the simplest case are fixed proportions of total costs of their own production. As required for all SAM accounts, project rows and columns of the transaction matrix balance, since the project outlays, which include the net project revenues paid to capital, equal the project inflows or gross revenues with any financial gap filled by the capital formation (i.e., the financing) sector. For example, in the construction period, the outlays will consist of the construction costs, while the balancing inflows will be provided by payments from the capital formation accounts.

More generally, the rows and columns of the SAM as a transaction matrix can be reinterpreted as the twin entries of the cash flow account of an economy for a given period of time. For the production sectors, this means that revenues from product sales are recorded in the row entries and costs in the column entries. The difference between revenues and intermediate costs is value added. This can be considered a result of the production activity (the larger the better, ceteris paribus) and is the basis to compute all welfare measures including GDP. In turn, value added is recorded as a row entry in the accounts of factors of production. Here row entries represent incomes from employment while column entries document payments to factor owners, which in a market economy are households, firms and the government. For institutions, finally, row entries represent incomes from factor ownership, interests and dividends, or transfers of various kind, while column entries are expenditures for goods and services and savings (as purchases of financial assets). Rather than value added, however, the return to capital in the form of gross margins of production are recorded as the difference between sector revenues and sector costs (including cost of intermediates and cost of labor) and are credited to the account of capital as a factor of production.

In sum, while the general practice in input output and SAM-based model has been to consider an investment project as a vector of expenditure shocks, the proper way to analyze it is as a special form of an activity, with its own input output parameters that evolve over time. This type of activity is characterized by a series of cash flows that change over time. At any point in time an investment project can thus be represented in the SAM as a column of cash outflows, including all capital and maintenance costs from intermediates and resulting value added, and as a row of cash inflows, including financing from the government and private savings during the construction phase, and revenues from increased production of goods and services during the operational phase. Since costs and revenues have to balance, financing from the capital formation sector, or directly from the government or other project sponsors must be recorded as one or more row entries in the years where cash outflows are larger than cash inflows (the “construction” period). Vice versa, once the project is operational and inflows become larger than outflows, returns can be credited to capital (as gross business margins) or institutions (government or households).

The benefits from the project, however, are not limited to the remuneration of capital, since other social benefits and costs may also be considered in the economic analysis.

2.1 A SAM-based model for project evaluation

Consider the social accounting matrix equation for a generic scenario:

where X is an n ,1 vector of activity levels for productive sectors, and incomes for factors and institutions and \(Q = I - A\) , the SAM coefficient matrix.

We can consider an investment project as an additional activity and augment the size of the SAM by adding a column and a row of transactions corresponding, respectively, to the outlays and the receipts of the project cash flow. In order for the inflows and outflows to balance, this entails, in particular, accounting, among the receipts, for any financing flow and, among the expenditures, any profits distributed to factors of production and other stakeholders. We can then write two new equilibrium conditions for the situation “without” and “with project” SAM as:

In (2a) and (2b), \(A_{s}\) and \(A_{c}\) are n  + 1, n  + 1, SAM matrices augmented of one column and one row to represent, respectively, the situation without and with the project. The matrix without the project \(A_{s}\) , in particular, can either contain an additional column and row of zeros, for the case of full project additionality, or the data of the cash flow of an alternative project as a counterfactual.

Subtracting Eq. ( 1 ) from Eqs. ( 2a ) and ( 2b ), we obtain, after some manipulation:

As noted in the literature on structural decomposition (e.g., Rose and Casler 1996 ), the two expressions ( 3a ) and ( 3b ) signal an index number problem. In the remainder of this paper, we will assume that the differences between (3a) and (3b) are small enough that they can be ignored or otherwise solved by appropriately averaging the results obtained by separately applying the two equations (Koppany 2017 , p. 619).

Both the \(A_{s}\) and the \(A_{c}\) matrix are singular, but we can decompose them into a non-singular square submatrix of coefficients of endogenous variables and rectangular submatrices of coefficients of exogenous variables:

In (4) \(X_{{ei}}\) and \(X_{{xi}}\) are vectors, respectively, of endogenous and exogenous activity levels and \(A_{{ee,i}} ,~A_{{ex,i,~~~}} A_{{xe,i,~~~}} A_{{xx,i}}\) corresponding submatrices from partitioning of \(A_{i} .~~\) Developing the expression, we can re-write (2) and (3) as follows:

This expression identifies one part of the system ( \(A_{{ex,i}} X_{{xi}} )~\) as a vector of exogenous demand levels and one part (( \(I - A_{{ee,i}} )X_{{ei}} )\) as a corresponding vector of endogenous supply levels necessary to satisfy the direct and indirect demand generated by the exogenous demand levels.

Subtracting the endogenous vector without the project from the one with the project, we obtain:

More synthetically, expression ( 6 ) can be re-written in difference notations as:

Solving for the endogenous variables, we obtain:

Expression ( 8 ) indicates that the variation of the endogenous variables of the model may be the consequence of three different shocks, all filtered through the matrix of multipliers of the endogenous sectors: (i) the autonomous variation of the exogenous variables (capital formation, exports or a specific vector of project expenditures); (ii) the variation of the SAM coefficient submatrix of the transactions within the endogenous accounts, and (iii) the variation of the SAM submatrix of the transactions between the endogenous and the exogenous accounts. Intuitively, the exogenous activities increases aggregate demand through the value chains quantified in the SAM, but may also introduce technological change, and induce a new pattern of transactions, boost or reduce existing connections and create new ones.

If one of the exogenous accounts is a specific investment project, in particular, consider the exogenous variation measured by the project cash flow over a time horizon \(t = 0,1, \ldots ..T\) and the changes in the SAM coefficients due to the changes of the project cash flow every year.

Indicating with the t subscript the time, the term \(A_{{ex,c,t}} \Delta X_{{x,t}} = A_{{ex,c,t}} \left( {X_{{xc,t}} - X_{{xs,t}} } \right)\) is the increase in project expenditure in the t th year, while ( \(\Delta A_{{ex}}^{t} )X_{{xs}}^{t}\) , is the change induced by the project into the counterfactual SAM matrix of the same period without the project. With no competing alternative ( \(X_{{xs,t}} = 0)\) , we have: \(~A_{{ex,c,t}} \Delta X_{{x,t}} = A_{{ex,c,t}} X_{{xc,t}}\) , i.e., the project cash flow. This includes, as all columns of the SAM, the demand increases (with respect to the situation without the project) generated by the expenditures of the project with respect to all sectors. These expenditures include both costs and net benefits of the project such as the payments made to project stakeholders as for example the net margins paid to capital and the other net benefits, accounted in gross terms in a corresponding row of the SAM. The term \(\left( {\Delta A_{{ext}} } \right)X_{{xt}} = (A_{{ext + 1}} - A_{{ext}} )X_{{xs}}^{t}\) represents the structural impact of the technology embodied in the project. This impact may be due to different project requirements in terms of use of intermediate inputs and value added in comparison to existing technologies. Project impact is thus evaluated as the sum of two components, one depending on the change in the scale of the cash flow, and one depending on the change of the weights of the different items of the project transaction vector in a new SAM updated to account for the transactions introduced by each phase of the project.

The present value at rate of discount r of project impact can be directly derived from Eq. ( 8 ):

However, \(A_{{ee,t + 1}}\) will approximately remain constant if the project is small enough, and \(\Delta A_{{eet}} \cong 0\) , so that expression ( 9 ) can be approximated on the basis of the initial SAM for the endogenous accounts:

Expression ( 10 ) allows to estimate the present value of project impact using a single SAM and its variations as the direct and indirect effects of the present values of the project cash flows. In turn these are defined as the sum of two components: (i) the yearly project outlays for a given structure of the interdependencies between the project and the rest of the economy, and (ii) the yearly increases in the same outlays due to the variation of these interdependencies brought about by the changes of project outlays over time.

3.1 Building a project SAM

In the theory of cost–benefit analysis, actual transactions in the form of revenues and expenditures at market prices are associated with the so-called “financial analysis”, which has the purpose to evaluate projects from the point of view of a private subject. In the “economic analysis”, instead, the basis to compute benefits and costs are no longer actual transactions at market prices, but virtual transactions that reflect what consumers or producers gain from market exchanges and other project effects, but not necessarily pay for them. Two typical concepts used to quantify these values are the well-known constructs of consumer and producer surplus.

While definitions can be made more precise by a better specified theoretical context, both consumers and producers surplus have a long history in economics as their definition and initial use is due to Marshall ( 1890 ), one of the founding fathers of microeconomic theory. Consumer surplus can be defined as the excess of willingness to pay for a good or service, compared to what consumers actually pay, while producer surplus can be similarly defined as the excess of the price received compared to producers’ willingness to accept. In both cases, therefore, a measure of the difference between a virtual transaction and an actual one is used as a monetary measure of a real gain. While an increase in household income is matched by an increase in consumer expenditure and/or savings, an increase in consumer surplus does not apparently result in an increase in transactions. However, as shown by Weitzman ( 1988 ), real income, calculated with an appropriate price deflator (a Laspeyres index in case of homothetic preferences), is essentially equivalent to consumer surplus. This implies that any increase in consumer surplus is equivalent to the sum of the increase in income at baseline prices plus a term (of a second order of magnitude) reflecting the fact that real income is also larger because of as concomitant favorable change in relative prices. For example, suppose that the project determines an increase in market supply of a particular good and this determines a corresponding increase in consumer expenditure. This larger expenditure in turn can be decomposed in a consumption saving (i.e., a gain in income) for the quantity consumed without the project (i.e., for those who already consume the good) plus an increase in expenditure due to the fall in price.

In addition to consumer and producers surplus, cost–benefit analysis also takes into account a number of other benefits and costs that are not translated into market transactions, either because they are not the result of market exchanges or because market exchanges do not reflect “true” social values. In other words, these two classes of project effects reflect the so-called “shadow prices”, which differ from market prices of an amount reflecting the components of social values that for various reasons are not internalized by existing markets. Since the important work of Ronald Coase ( 1937 ), these externalities have been recognized as themselves corresponding to virtual (or potential) transactions.

Table 1 shows how benefits and costs of a project can be incorporated in the project row (project receipts) and columns (project outlays). The economic components of project receipts are: (i) revenues from project intermediates; (ii) revenues from consumer purchases; (iii) government subsidies; (iv) debt or equity financing, and (v) exports. The corresponding project costs are: (i) capital and operational costs; (ii) net margins (credited to capital); (iii) consumer incomes, credited to households; (iv) taxes; (v) interests and dividends, and (vi) imports. The project row and column at market prices balance since net margins, i.e., the difference between revenues and costs are included in the project SAM column as a cost for capital. In this way the two sums, respectively, of the column and the row entries for market transactions (the so-called “financial analysis” of the project) equal the project gross revenues, i.e., all receipts. In order to go from financial to economic analysis all the above variables must valued at shadow prices and conform, as indicated in Weitzman ( 1976 ), Eisner ( 1988 ) and Hartwick ( 1990 ) to the notion of Net National Product (NNP), i.e., to an ideal flow measurement of national wealth of a dynamic economy. They can thus also incorporate social welfare effects, externalities and natural capital (last three rows and columns in the matrix) for which market prices are not available (as in Banerjee et al. 2016 ).

3.2 Economic analysis

Tables 2 and 3 show an example of a social accounting matrix incorporating a project cash flow, respectively, in the construction period ( t  = 0), and in the operational period ( t  = 1), with the project cash flow being accounted for as an extra activity and/or institution in the SAM. The cash flow data in the construction period include only capital expenditure (capital goods produced by activities) in the account column and financing from capital formation in the account row. In the operational period, the project account column includes all project costs (capital replacement and operational costs), while the row account contains all project receipts. The value added account is credited in the project column of the payments to labor and capital, including the returns paid as net business margins to project sponsors. These payments amount to the sum of the inflows reported in the row minus all the costs (other than value added) reported in the column. As a consequence, the sum of the column and the sum of the row both amount to the gross revenue component of the project cash flow. In a more detailed account, with value added split between various types of production factors and a capital account, wages would be paid to different types of labor and the net margins from the project would be explicitly credited to capital. On the other hand, while net benefits depend on the return to capital, they also include the indirect effects on the economy which are credited to households, government or other accounts.

As Table 2 shows, in the construction period, the project is assumed to produce no revenues, while its costs are assumed to be 100 monetary units, with payments to activities, production factors (value added), and rest of the world (ROW). These costs are entirely financed from capital formation and give rise, to the extent that they mobilize unemployed resources, to value added increases through indirect effects. Revenues, on the other hand, are collected by the project as listed in the project row in Table 3 . These revenues are collected from various stakeholders who purchase the goods or services provided by the project, including households and government. With no indirect effects, project net (financial) benefits would thus simply be the portion of value added credited to capital net of any charges due to user costs for maintenance.

Project financing is then repaid in the operational period with interests (120 monetary units versus the 100 units borrowed for construction). In this period (Table 3 ), the project is assumed to collect revenues equal to 365 units from all sectors and institutions, with intermediate costs of 20 units from domestic activities and 25 units from imports. The difference between project receipts of 365 and project intermediate costs of 45 is credited for 120 units to the capital formation account and for 200 units to the value added account and add to total project outlays, including loan repayment with interests accrued to capital formation. As a consequence, the value added account in the operation period is the sum of the project direct payments to production factors and indirect taxes to meet operational costs and of the returns to capital obtained from project revenues after paying for intermediate goods and capital formation. The capital formation expenditures include loan repayments, interests, capital depreciation (assumed to be 5% per year) and any expenditure for replacement of capital goods.

The two transaction matrices in Tables 2 and 3 correspond to two coefficient matrices, whose difference is reported in Table 4 .

Assuming as exogenous accounts, in addition to the project, capital formation and the rest of the world, we can now compute the project impact in both periods according to expressions ( 8 ) and ( 9 ).

Table 5 reports the values of the main SAM accounts affected by the project, while Table 6 compares outcome variables with project costs. Multiplier estimates from value added and, considering depreciation charges, for Net National Product (NNP) are around 1 for the construction period and around 1.5 for the operational period, where not only costs but also net revenues from the project are taken into account.

4 Discussion

In this paper, I have presented a methodology to integrate cost–benefit analysis in the impact evaluation performed on the basis of social accounting principles (SAM or SAM-based models). The integration requires simply a recasting of the economic and/or financial data used in the discounted cash flow analysis in the format used in the SAM accounts and involves a simple reclassification of costs and revenues according to the statistical system used in the SAM (Eisner 1988 ). The methodology generalizes the use of multipliers to evaluate the short-term impact of investment projects, which is typically used alongside cost–benefit analysis, but without a clear relation with both its theoretical principles and practical applications. Unlike the simple multiplier method, by integrating project accounting in the SAM, it allows an exhaustive analysis of impact on revenues, costs and financing, thus providing a clear picture of the project contribution to both demand and supply both in the project construction and operational periods. By integrating in a consistent accounting framework value added formation and economic benefits and costs, this method also allows making full use of the information provided by the sector and the distributional details of investment cash flows through the entire project life.

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Scandizzo, P.L. Impact and cost–benefit analysis: a unifying approach. Economic Structures 10 , 10 (2021). https://doi.org/10.1186/s40008-021-00240-w

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Cost-Benefit Analysis: A Quick Guide with Examples and Templates

ProjectManager

When managing a project, many key decisions are required. Project managers strive to control costs while getting the highest return on investment and other benefits for their business or organization. A cost-benefit analysis (CBA) is just what they need to help them do that. Before we explain how to do a cost-benefit analysis, let’s briefly define what it is.

What Is a Cost-Benefit Analysis?

A cost-benefit analysis (CBA) is a process that’s used to estimate the costs and benefits of projects or investments to determine their profitability for an organization. A CBA is a versatile method that’s often used for business administration, project management and public policy decisions. An effective CBA evaluates the following costs and benefits:

  • Direct costs
  • Indirect costs
  • Intangible costs
  • Opportunity costs
  • Costs of potential risks
  • Total benefits
  • Net benefits

These project costs and benefits are then assigned a monetary value and used to determine the cost-benefit ratio. However, a cost-benefit analysis might also involve other calculations such as return on investment (ROI), internal rate of return (IRR), net present value (NPV) and the payback period (PBP).

Cost-Benefit Analysis Template

Use this Excel template to put what you’ve learned into practice. This free cost-benefit analysis template helps you identify quanitative costs and benefits, as well as qualitative costs and benefits, so you can appreciate the full impact of your project. Download yours today.

cost-benefit analysis template for Excel

The Purpose of Cost-Benefit Analysis

The purpose of cost-benefit analysis is to have a systemic approach to figure out the pluses and minuses of various business or project proposals. The cost-benefit analysis gives you options and offers the best project budgeting approach to achieve your goal while saving on investment costs.

When to Do a Cost-Benefit Analysis

Cost-benefit analysis is a technique that helps decision-makers choose the best investment opportunities in different scenarios. Here are some of the most common applications for a cost-benefit analysis in project management.

Cost Benefit Analysis & Feasibility Studies

A feasibility study determines whether a project or business initiative is feasible by determining whether it meets technical, economic, legal and market criteria.

Cost Benefit Analysis & Business Requirements Documents

A cost-benefit analysis should be included in a business requirements document , a document that explains what a project entails and what it requires for its successful completion.

Cost Benefit Analysis & Government Projects

Government projects also require conducting a cost-benefit analysis. However, in these types of projects, decision-makers must not only focus on financial gain, but rather think about the impact projects have on the communities and external stakeholders who might benefit from them.

Keeping track of project costs is easier with project management software. For example, ProjectManager has a sheet view, which is exactly like a Gantt but without a visual timeline. You can switch back and forth from the Gantt to the sheet view when you want to just look at your costs in a spreadsheet. You can add as many columns as you like and filter the sheet to capture only the relevant data. Keeping track of your costs and benefits is what makes a successful project. Get started for free today.

Track costs in real time with ProjectManager

How to Do a Cost-Benefit Analysis

According to the Economist , CBA has been around for a long time. In 1772, Benjamin Franklin wrote of its use. But the concept of CBA as we know it dates to Jules Dupuit, a French engineer, who outlined the process in an article in 1848.

Since then, the CBA process has greatly evolved. Let’s go through this checklist to learn how to do a basic cost-benefit analysis using the cost-benefit ratio and present value formulas:

1. What Are the Project Goals and Objectives?

Create a business case for your project and state its goals and objectives.

2. Review Historical Data

Before you can know if a project proposal might be valuable, you need to compare it to similar past projects to see which is the best path forward. Check their success metrics such as their return on investment, internal rate of return, payback period and benefit-cost ratio.

3. Who Are the Stakeholders?

List all stakeholders in the project. They’re the ones affected by the costs and benefits. Describe which of them are decision-makers.

4. What Are the Project Costs and Benefits?

Estimate the future value of your project costs and benefits and think about all the non-financial benefits that a project proposal might bring

The process can be greatly improved with project management software. ProjectManager has one-click reporting that lets you can create eight different project reports. Get data on project status, variance and more. Reports can be easily shared as PDFs or printed out for stakeholders. Filter any report to display only the data you need at the time.

cost analysis research paper example

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Cost Benefit Analysis Template

Use this free Cost Benefit Analysis Template for Excel to manage your projects better.

5. Define a Project Timeframe

Look over the costs and benefits of the project, assign them a monetary value and map them over a relevant time period. It’s important to understand that the cost-benefit ratio formula factors in the number of periods in which the project is expected to generate benefits.

6. What Is the Rate of Return?

As explained above, the rate of return is used to calculate the present values of your project’s costs and benefits, which are needed to find the cost-benefit ratio.

What Is the Cost-Benefit Ratio?

The cost-benefit ratio, or benefit-cost ratio, is the mathematical relation between the costs and financial benefits of a project. The cost-benefit ratio compares the present value of the estimated costs and benefits of a project or investment.

Cost-Benefit Ratio Formula

This is a simplified version of the cost-benefit ratio formula.

Cost-Benefit Ratio= Sum of Present Value Benefits / Sum of Present Value Costs

Here’s how you should interpret the result of the cost-benefit ratio formula.

  • If the result is less than 1: The benefit-cost ratio is negative, therefore the project isn’t a good investment as its expected costs exceed the benefits.
  • If the result is greater than 1: The cost-benefit ratio is positive, which means the project will generate financial benefits for the organization and it’s a good investment. The larger the number, the most benefits it’ll generate.

Present Value Formula

The present value of a project’s benefits and costs is calculated with the present value formula (PV).

PV = FV/(1+r)^n

  • FV: Future value
  • r= Rate of return
  • n= Number of periods

We’ll apply these formulas in the cost-benefit analysis example below. Our free cost-benefit analysis template can help you gather the information you need for the cost-benefit ratio analysis.

Cost-Benefit Analysis Example

Now let’s put the formulas reviewed above into practice. For our cost-benefit analysis example, we’ll think about a residential construction project, the renovation of an apartment complex. After using project cost estimation methods and evaluating past-project data, the apartment management company concludes that:

  • The project costs are $65,000. They’re paid upfront, so it’s not necessary to calculate their present value
  • The project is expected to generate $100,000 in profit for the next 3 years
  • The rate of return based on inflation data is 2%

Next, we’ll need to calculate the present value of the benefits expected to be earned in the future using the present value formula:

PV= ($100,000 / (1 + 0.02)^1) + ($100,000 / (1 + 0.02)^2) + ($100,000 / (1 + 0.02)^3)=$288,000

Now we need to use this cost value to find the cost-benefit ratio. Here’s how it would be calculated in this case:

Cost-Benefit Ratio: 288,000/65,000= 4.43

Since we obtained a positive benefit-cost ratio, we can conclude that the project will be profitable for this company. This result implies that the project will generate about $4,43 dollars per each $1 spent to cover expenses .

This is a simple cost-benefit analysis that relies on the cost-benefit ratio to establish the profitability of this project. In other scenarios, you might also need to calculate the return on investment (ROI), internal rate of return (IRR), net present value (NPV) and the payback period (PBP). In addition, it’s advisable to conduct a sensitivity analysis to evaluate different scenarios and how those affect your cost-benefit analysis.

Capture all the costs and benefits with project management software. But unlike many apps with inferior to-do lists, ProjectManager has a list view that is dynamic. It adds priority and customized tags you can assign team members to own each item. Our online tool automatically tracks the percentage complete for each item in real time. All the data you collect in our list view is visible throughout the tool. Regardless of the view, they all update live and they’re ready for you to utilize.

task list view from ProjectManager, with expanded item showing greater detail

How Accurate Is Cost-Benefit Analysis?

How accurate is CBA? The short answer is it’s as accurate as the data you put into the process. The more accurate your estimates, the more accurate your results.

Some inaccuracies are caused by the following:

  • Relying too heavily on data collected from past projects, especially when those projects differ in function, size, etc., from the one you’re working on
  • Using subjective impressions when you’re making your assessment
  • Improperly using heuristics (problem-solving employing a practical method that is not guaranteed) to get the cost of intangibles
  • Confirmation bias or only using data that backs up what you want to find

Cost-Benefit Analysis Limitations

Cost-benefit analysis is best suited to smaller to mid-sized projects that don’t take too long to complete. In these cases, the analysis can help decision-makers optimize the benefit-cost ratio of their projects.

However, large projects that go on for a long time can be problematic in terms of CBA. There are outside factors, such as inflation, interest rates, etc., that impact the accuracy of the analysis. In those cases, calculating the net present value, time value of money, discount rates and other metrics can be complicated for most project managers .

There are other methods that complement CBA in assessing larger projects, such as NPV and IRR. Overall, though, the use of CBA is a crucial step in determining if any project is worth pursuing.

Templates to Help With Your Cost-Benefit Analysis

As you work to calculate the cost-benefit analysis of your project, you can get help from some of the free project management templates we offer on our site. We have dozens of free templates that assist every phase of the project life cycle. For cost-benefit analysis, use these three.

RACI Matrix Template

One of the steps when executing a cost-benefit analysis includes identifying project stakeholders. You need to list those stakeholders, but our free RACI matrix template takes that one step further by outlining who needs to know what. RACI is an acronym for responsible, accountable, consulted and informed. By filling out this template, you’ll organize your team and stakeholders and keep everyone on the same page.

Project Budget Template

You can’t do a cost-benefit analysis without outlining all your expenses first. That’s where our free project budget template comes in. It helps you capture all the expenses related to your project from labor costs, consultant fees, the price of raw materials, software licenses and travel. There’s even space to capture other line items, such as telephone charges, rental space, office equipment, admin and insurance. A thorough budget makes for a more accurate cost analysis.

Project Risk Register Template

You have your stakeholders identified and your budget outlined, but there’s always the unknown to consider. You can’t leave that up to chance: you must manage risk, which is why our free project risk register is so essential. Use it to outline inherent project risks. There are places to list the description of the risk, its impact, the level of risk and who’s responsible for it. By maintaining a risk register, you can control the project variables and make a better cost-benefit analysis.

Make Any Project Profitable With ProjectManager

No matter how great your return on investment might be on paper, a lot of that value can evaporate with poor execution of your project. ProjectManager is award-winning project management software with the tools you need to realize the potential of your project. First, you need an airtight plan.

Planning on Gantt Charts

Our online Gantt charts have features to plan your projects and organize your tasks, so they lead to a successful final deliverable. If things change, and they will, the Gantt is easy to edit, so you can pivot quickly.

A screenshot of a gantt chart in ProjectManager

Resource Management Tools

Another snag that can waylay a project is your resources. ProjectManager has resource management tools that track your materials, supplies and your most valuable resource: the project team. If they’re overworked, morale erodes and production suffers.

The workload page on ProjectManager is color-coded to show who is working on what and gives you the tools to reassign to keep the workload balanced and the team productive.

resource management tools in ProjectManager

Real-Time Cost Tracking

The surest way to kill any project is for it to bleed money. ProjectManager lets you set a budget for your project from the start. This figure is then reflected in reports and in the charts and graphs of the real-time dashboard , so you’re always aware of how costs are impacting your project. ProjectManager has the features you need to lead your project to profitability.

ProjectManager’s dashboard view, which shows six key metrics on a project

Cost benefits analysis is a data-driven process and requires project management software robust enough to digest and distribute the information. ProjectManager is online project management software with tools, such as a real-time dashboard, that can collect, filter and share your results in easy-to-understand graphs and charts. Try it today with this free 30-day trial.

Click here to browse ProjectManager's free templates

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Cost Analysis – Definition, Methods, & Free Business Essays

🔝 top-10 cost analysis examples, ✅ cost analysis definition, 📒 methods of cost analysis, 📝 cost analysis research paper examples, 💡 essay ideas on cost analysis, 👍 good cost analysis essay examples to write about, 🎓 simple research paper examples with cost analysis, ✍️ cost analysis essay examples for college, 🏆 best cost analysis research titles.

If you want to learn about cost analysis, you’ve come to the right place. In this article, we’ll explain what cost analysis is and explore various methods of conducting it. Keep reading to find out more!

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We aim to provide a clear and straightforward cost analysis definition to help you better understand this complex subject.

What Is a Cost Analysis?

Cost analysis is a process used to measure financial expenses. It’s a critical component of strategic planning for any organization. The goal is to calculate the budget and identify methods to optimize or reduce costs. There are 3 primary methods of analysis: cost allocation, cost-benefit analysis, and cost-effectiveness analysis. Cost allocation and cost-benefit analysis rely on more limited information resources, while cost-effectiveness analysis can evaluate a wide range of data in different formats.

How to Do a Cost Analysis

To conduct a cost analysis, you first need to classify expenses into fixed and variable categories. Fixed costs remain constant, while variable costs depend on the level of business activity. Next, determine the significance of different types of costs, their behavior, and what conditions affect them. It’s helpful to use spreadsheets, charts, and tables to organize the data. Remember that the specific steps for conducting a cost analysis will depend on the type of analysis you choose, so be sure to select the appropriate method for your needs.

If you are studying business or economics, you’ve probably asked yourself: what is a cost-benefit analysis? Is it different from cost-effectiveness? And how does cost allocation fit into all of it? Well, let’s figure it out together!

Here, you will find a breakdown of the three most common cost analysis methods.

Cost Allocation

Cost allocation is part of the management accounting and reporting framework that helps organizations make better decisions by determining the actual cost of their service units or products. It considers all the accompanying costs, including supply chains , to ensure accurate calculation. The goal of cost allocation can vary depending on the organization’s objectives.

The cost allocation method can be grouped into 2 categories: product-related (such as services, manufacturing, and marketing) and structural-related (such as departments, units, or teams). A company needs to have proper budgeting systems, data collection, and recording to conduct accurate cost allocation for services. Quality information is essential to ensure precise calculation.

Cost Benefit Analysis

The cost-benefit analysis quantifies the costs and benefits of a project, decision, or program . It helps determine if the selected project is optimal and lucrative. A specific time frame is chosen for the analysis to get information about planned costs and projected benefits.

For instance, a construction company may use cost-benefit analysis to compare costs and benefits when deciding to start construction. The analysis aims to show the profitability or failure of the project. Ideally, expenditures should increase the financial opportunity of the business, but the economic profit should exceed them to ensure success.

Cost Effectiveness Analysis

Cost-effectiveness analysis is a method for comparing multiple solutions or projects in economic terms to identify the most effective one . The goal is to balance costs and outcomes to maximize efficiency.

For instance, a company might compare the cost-effectiveness of two projects to determine which will provide the best return on investment . This method also enables consideration of non-monetary factors, such as student graduation rates in the education industry.

To summarize, cost analysis is a helpful tool for anyone who needs to organize their finances: entrepreneurs, students, companies, or families. Cost analysis can help you make informed decisions about your expenses and financial goals. To learn more, check out some great essay samples on this topic!

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Cost-Benefit Analysis and the Evaluation of the Effects of Corruption on Public Projects

Chapter 15 in Handbook of Research on Cost-benefit Analysis, (ed.) Robert J. Brent, Edward Elgar Publishing, 2009; ISBN: 9781847200693

26 Pages Posted: 22 Sep 2018

Robert J Brent

Fordham University

Date Written: July 22, 2009

Cost–benefit analysis (CBA) is the basis for rational economic decision making, whether it is for the government or individuals. If benefits are greater than costs, then a project or activity should be expanded. If costs are greater than the benefits, the project or activity should be contracted. And if benefits equal costs, the existing scale of operations is optimal. A social CBA obtains its measurement principles concerning the benefits and costs from applied welfare economics. Its main purpose is to incorporate considerations into public expenditure decision making that caused private market decision making to fail to produce optimally (due to the existence of externalities) or produce at all (pure public goods). However, these corrections for market failure lead only to potential gains. Once the public sector is involved there is also the potential for government failure. Public officials may have an agenda that is different from social welfare maximization. In particular, if these public officials are corrupt and try to maximize bribes which they keep for themselves, then this reality needs to be included as part of the cost–benefit evaluation. The Executive Board of the World Bank defined corruption in 1997 as: ‘The use of public office for private gain’. This definition is also the one used by Bardhan (1997) in his survey of corruption and development.

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Department of Economics 441 E Fordham Road Bronx, NY 10458 United States 718 817 4058 (Phone)

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  • Published: 05 September 2018

Cost-benefit analysis of vaccination: a comparative analysis of eight approaches for valuing changes to mortality and morbidity risks

  • Minah Park 1 ,
  • Mark Jit 1 , 2 , 3   na1 &
  • Joseph T. Wu 1   na1  

BMC Medicine volume  16 , Article number:  139 ( 2018 ) Cite this article

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There is increasing interest in estimating the broader benefits of public health interventions beyond those captured in traditional cost-utility analyses. Cost-benefit analysis (CBA) in principle offers a way to capture such benefits, but a wide variety of methods have been used to monetise benefits in CBAs.

To understand the implications of different CBA approaches for capturing and monetising benefits and their potential impact on public health decision-making, we conducted a CBA of human papillomavirus (HPV) vaccination in the United Kingdom using eight methods for monetising health and economic benefits, valuing productivity loss using either (1) the human capital or (2) the friction cost method, including the value of unpaid work in (3) human capital or (4) friction cost approaches, (5) adjusting for hard-to-fill vacancies in the labour market, (6) using the value of a statistical life, (7) monetising quality-adjusted life years and (8) including both productivity losses and monetised quality-adjusted life years. A previously described transmission dynamic model was used to project the impact of vaccination on cervical cancer outcomes. Probabilistic sensitivity analysis was conducted to capture uncertainty in epidemiologic and economic parameters.

Total benefits of vaccination varied by more than 20-fold (£0.6–12.4 billion) across the approaches. The threshold vaccine cost (maximum vaccine cost at which HPV vaccination has a benefit-to-cost ratio above one) ranged from £69 (95% CI £56–£84) to £1417 (£1291–£1541).

Conclusions

Applying different approaches to monetise benefits in CBA can lead to widely varying outcomes on public health interventions such as vaccination. Use of CBA to inform priority setting in public health will require greater convergence around appropriate methodology to achieve consistency and comparability across different studies.

Peer Review reports

Health economic evaluations are used to inform medical procurement and reimbursement decisions by public and private healthcare providers. The most popular form of health economic evaluation is cost-effectiveness analysis (CEA), which often presents the ratio of the incremental cost of an intervention (from the perspective of either the healthcare provider or society) to the incremental health benefits of an intervention. A review conducted for the Bill & Melinda Gates Foundation of health economic evaluations of interventions related to malaria, tuberculosis, HIV/AIDS and vaccination in low- and middle-income countries found that, of 204 studies published in 2000–2013, 202 (99%) were CEAs [ 1 ].

Economic evaluations of large public health interventions such as new vaccination programmes attract particularly intense debates because of the high absolute costs (and potentially large benefits) involved [ 2 ]. A major focus of such debates has been about whether current economic evaluation techniques capture the full scope and value of these public health programmes. For instance, several reviews have found that vaccines may have broad, long-term societal consequences that are not always captured in CEAs [ 3 , 4 ], although many of these benefits can, in principle, be monetised and included in CEA based on a broader societal perspective as recommended by the US Second Panel on Cost-Effectiveness in Health and Medicine [ 5 , 6 ]. Such broader, non-health benefits of an intervention include effects on future productivity and consumption, social services, educational achievement and other societal impacts.

Several economists have instead proposed the use of cost-benefit analysis (CBA) [ 7 , 8 ]. The term CBA is often informally used to refer to any analysis used in decision-making that compares the expected costs and benefits (both in monetary terms) of an investment. In principle, to be regarded as complete, a CBA should capture all benefits due to an intervention, valuing them either at their market value or at the level of consumption that individuals are willing to forego to obtain them. Hence, it has its conceptual roots in welfare economics, which quantifies social welfare in terms of individuals’ willingness-to-pay (WTP) to increase welfare. By using a consistent, directly comparable metric to value all outcomes, CBA allows comparison with non-health interventions. A recent analysis estimated that the return on investment (a form of economic analysis that uses the same economic assumptions as CBA) for vaccines in low- and middle-income countries was comparable or superior to that for non-health interventions such as road safety [ 3 ].

The methodology for CEA has been well established, with the perspective or range of costs admissible in a CEA usually prescribed by ‘reference cases’ produced by particular health authorities. In CEAs, the perspective on costs can be narrow (costs and cost offsets falling to healthcare providers alone, as recommended by the National Institute for Health and Care Excellence (NICE) in the UK) [ 9 ] or broad (all costs and cost offsets falling on society, as recommended by the World Health Organization (WHO)) [ 10 ]. NICE’s recommendation to take a narrow perspective when estimating costs is reasonable given that its evaluations are intended to promote the most efficient use of available resources allocated to the NHS (or publicly funded health sectors) in particular [ 11 ]. Conversely, the WHO Guide to Cost-Effectiveness Analysis [ 10 ] explicitly recommended all costs and health effects to be valued from the societal perspective, because there are always opportunity costs in every decision we make, such that all costs and resources used for a chosen health intervention (regardless of who paid them) could have been used for other purposes in society, including non-health consumption. The guide further argued that the so-called ‘decision-maker’s approach’ taking such a narrow perspective is not consistent with WHO’s concern that governments should strive to maximise not only the overall health but also wellbeing of societies. The Second Panel on Cost-Effectiveness in Health and Medicine, composed of experts and leaders in the field of health economics, has also provided two reference cases for healthcare sector and societal perspectives, respectively, in their recent report. The Panel recommended that CEAs are undertaken based on both perspectives to improve the quality and comparability of CEAs [ 5 ].

Each of these approaches also affects the threshold by which an option with a particular cost-effectiveness ratio is deemed cost-effective. The CEA threshold is often determined based on one of the following: (1) the opportunity cost of new spending at the margin of a budget limit, (2) a multiple of GDP per capita, usually based on human capital arguments (although they have also been justified based on WTP) or (3) preference elicitation (based on WTP) [ 12 ]. Using a decision-maker’s perspective and assuming that the decision-maker has control over a budget with the objective of maximising health, the threshold should arguably be set based on the opportunity cost of new spending at the margin of the decision-maker’s budget. From a societal perspective, the threshold should arguably instead be set based on either the human capital value of improved health, or by preference elicitation (based on WTP) of societal willingness to improve health.

In contrast, there is less detail around CBA methodology in health. While there exists guidance on conducting CBAs for government policies [ 13 , 14 , 15 ], it generally is not as precise as ‘reference cases’ available for CEAs that specify the exact economic assumptions to be used in pharmacoeconomic evaluations. This is likely because CBA has not been used as extensively as CEA for informing decisions on specific healthcare resource allocation. While CBA is used to evaluate a broader range of public sector initiatives across multiple sectors, CEA guidelines are generally used in the health sector only.

Given the increasing interest in using CBA to evaluate the value of vaccinations and other major public health programmes (as in part evidenced by the Bill & Melinda Gates Foundation’s recent efforts to develop a reference case for CBA), it is important to understand the implications of different approaches for capturing and monetising benefits. To this effect, we conducted a CBA of human papillomavirus (HPV) vaccination as a case study. HPV vaccination is a major public health investment that has been the topic of numerous CEAs with a total of more than 60 studies identified across a number of systematic reviews [ 16 , 17 , 18 ]. Indeed, vaccination in general has been subject to numerous studies assessing costs and benefits based on various monetisation methods [ 3 , 19 , 20 , 21 , 22 ]. For the current study, we applied eight different approaches to monetise benefits of HPV vaccination and compared the results.

We conducted a CBA of HPV vaccination in the UK. HPV is the aetiological agent of a number of cancers and other diseases such as anogenital warts. Cervical cancer has the highest global burden among the HPV-related fraction of these cancers [ 23 ]. In particular, around 70% of cervical cancers are caused by HPV-16 and HPV-18. We have chosen this example as a large public health investment with a well-established model of HPV vaccine impact used for national decision-making, so that our focus in this study could be on the methodology of CBA rather than on the modelling of HPV epidemiology. For simplicity, we focus only on the value of vaccination in preventing cervical cancer due to HPV-16 and HPV-18.

The decision to introduce HPV vaccination in the UK was informed by a CEA that incorporated an epidemiological model of HPV transmission [ 24 ] to assess the impact of routine female adolescent two-dose vaccination on cervical cancer burden over a time horizon of 100 years. We adopted the same epidemiological model but used it as input for CBA. We assumed that (1) vaccination is given annually to 12-year-old girls at 80% coverage, with a catch-up campaign in the first year to age 16, and that (2) the vaccine provides lifelong protection against HPV-16 and HPV-18 without cross protection against other HPV types. Costs and benefits were discounted at 3.5% per annum. For the probability sensitivity analysis, we used Latin hypercube sampling to generate 1000 scenarios that encompass the uncertainties in epidemiologic and economic parameters.

The outcome in our CBA was threshold vaccine cost (TVC), which we defined as the maximum vaccine cost per person (including the administration cost) at which HPV vaccination has a benefit-to-cost ratio above one (i.e. the vaccination programme is cost-beneficial) (Additional file 1 ). The direct benefits of vaccination included all medical cost avoided due to reduced screening for and treatment of cervical cancer and pre-cancerous lesions (Additional file  2 : Table S1).

We applied two conceptually different approaches to monetise benefits (lost production and WTP) to examine the impact of varying methods on the results. Estimates of WTP were derived from stated or revealed preference studies while lost production were measured using the human capital and friction cost methods as summarised in Table  1 .

Lost production: Conventional production-based approaches

While conventional CBA generally assumes that individuals are the best judges of their own welfare (i.e. consumer sovereignty) and that monetary values should reflect individual willingness to exchange consumption for the outcomes of concern (e.g. [ 25 ], p. 30), lost production has also been commonly used in the CBA literature to value health [ 26 , 27 , 28 , 29 , 30 , 31 ]. Under these approaches, productivity loss averted due to reduction in morbidity and mortality were incorporated as indirect benefits of vaccination in terms of the wider economic effects of health as human capital (rather than its intrinsic value).

We considered the two most commonly used production-based approaches, namely the human capital (HC) and friction cost (FC) methods. From the perspective of affected individuals, the HC method assumes that production loss incurred by sick or deceased workers is irreplaceable. The duration of productivity loss for a sick worker was therefore assumed to be the same as the entire duration of disease treatment, whereas productivity loss due to premature death was estimated by assuming an average retirement age of 65. Specifically, production loss was measured with a cumulative sum of income lost over the duration of illness (morbidity) and the number of years lost due to premature death (mortality) using age-specific employment rates and mean personal incomes retrieved from the UK Office for National Statistics [ 32 , 33 ].

In contrast, the FC method takes the employer perspective and assumes that there always exists some level of involuntary unemployment and hence a sick or deceased worker is replaceable by an otherwise unemployed worker [ 34 ]. As such, the FC method only accounts for productivity loss during the friction period, which is defined as the time between the first day of absence of a sick or deceased worker and the last day of training for a replaced worker. According to the 2015 UK Recruitment Trends Report [ 35 ] based on responses from major UK recruitment agencies, the average time to fill a vacancy (i.e. time between announcing a job and finding a successful applicant) ranged from 6 to 44 days in 2014. The average time in training for a new employee of 6.8 days was derived from the UK Employer Skills Survey 2015 [ 36 ]. As the friction period largely depends on the type of job (e.g. longer friction period for jobs requiring higher-level knowledge and skills) and economic or labour market conditions, it was difficult to find all the necessary data needed to estimate the friction period. We assumed that the sum of (1) the time period between the start of absence by a sick employee and the first day of job announcement and (2) the time period between the acceptance of job offer and the first day of training of a new employee to be approximately 3 to 5 weeks in total based on Koopmanschap’s study [ 34 ]. The friction period in the UK was estimated to be approximately 34 to 86 days. In addition to productivity loss incurred over the friction period, we considered additional administrative costs related to hiring (£2610) [ 36 ] and training (£5433) [ 37 ] a new worker for all mortality and long-term morbidity cases (i.e. treatment time > friction period).

The conventional production-based approaches account for productivity loss from individuals with the paid jobs only and thus disregard homemakers who comprise a substantial proportion of cervical cancer cases (mean age 45, interquartile range 27–59) [ 38 ]. As indicated in one of WHO’s guidelines on CBA, the economic value of unpaid work, such as homemaking and caring, is undervalued using this approach [ 39 ]. As such, we also considered modified versions of the conventional production-based methods (HC-M and FC-M) in which paid labour and homemakers within the same age group were assumed to have the same economic productivity. The assumption is in line with the UK’s recent effort in recognising the value of unpaid work at home and its contribution to the economy, by providing it with a monetary value equivalent to the average wages of those who are paid to do those tasks [ 40 ]. The proportion of homemakers in each age group was approximated based on the Office for National Statistics employment statistics [ 13 ].

Lost production: a new production-based approach

The conventional production-based approach has the advantage that it uses relatively objective and quantifiable measures (e.g. wage rates) compared to a WTP-based approach. However, the theoretical framework of neither the HC nor the FC method is completely sound, because (1) the HC method’s underlying assumption of full employment is often considered unrealistic and (2) the friction period of the FC method largely varies across occupations, times and countries. In order to address both issues, we examined how easily job vacancies could actually be filled within the ‘normal’ friction period in the current UK labour market.

We considered a new approach for estimating productivity loss by interpolating between the HC and FC methods (HC/FC). Under this approach, productivity loss was a weighted average of that under the two methods where the weight for HC corresponded to the proportion of jobs that are unlikely to be filled within the friction period in the current labour market. We estimated this weight based on recent statistics on ‘hard-to-fill vacancies’ (HtFV) from the UK Commission’s Employer Skills Survey 2015 (Additional file  3 : Table S2) [ 36 ]. HtFV refer to vacancies that are difficult to fill due to skill-related (e.g. lack of qualified applicants) or non-skill-related reasons (e.g. low pay offered for the post). It was noted that there is a major gender difference in occupational employment in the UK [ 41 ], with women historically dominating employment in jobs such as leisure and caring while men dominating in construction industry, for example. To take into account the gender difference in occupational employment and largely varying proportions of HtFV by industry sector [ 36 ], we calculated the weighted proportion of HtFV for women to be used in the analysis. We compiled two recent UK employment statistics that provide (1) the distribution of female workforce [ 42 ] and (2) the proportion of HtFV in 13 industry sectors categorised according to the Standard Industrial Classification [ 36 ]. The distribution of females in the workforce largely varied by industry sector, ranging from 0.6% in agriculture to 22% in health and social work, while the proportion of HtFV (regardless of gender) ranged from 23% in education to 43% in construction.

WTP: the value of a statistical life (VSL) approach

Under this approach, the monetary values of both pecuniary (e.g. avoided medical expenses) and non-pecuniary (e.g. pain and suffering associated with the disease) benefits are presumed to be encapsulated by VSL estimates given that individuals’ WTP takes into account the impact of mortality risk reductions on their wellbeing in every aspect. The VSL estimates are used to value mortality risk reductions and obtained via (1) revealed preferences (VSL-RP) based on labour-market or hedonic wage studies; or (2) stated preferences (VSL-SP) based on contingent valuation studies [ 8 ]. While the VSL generally does not address morbidity associated with non-fatal cases, it has been suggested that VSL-RP may as well include the value of the associated morbidity risk though it is likely to be minimal (6–25%) compared to the value of the fatality risk [ 43 ]. As for the VSL-SP, there has been mixed evidence regarding the morbidity premium (or cancer premium) to take into account the effects of morbidity associated with the fatality in the VSL estimate [ 44 , 45 , 46 ]. This highlights a key advantage of the VSL approach over the HC or FC methods that do not take into account the intrinsic value of health gains. We considered seven different VSL estimates derived from three individual studies (labelled as ‘Lang’, ’Viscusi’ and ‘Gayer 1–2’ in Fig.  1 ) and three normative national and international guidance (‘UKHSE’, ‘USDoT’ and ‘OECD’) (Additional file  4 : Table S3). For VSL-RP, we selected (1) a VSL estimate currently in use by the US Department of Transportation (‘USDoT’) [ 47 ], which is very similar to that adopted by the US Department of Health and Human Services [ 14 ] and the US Environmental Protection Agency [ 15 ], as well as the estimated means from a meta-regression analysis, which adjusted for publication bias [ 48 ], and (2) a range of VSL for cancer risk reduction estimated based on hedonic housing prices in the US (‘Gayer 1–2’) [ 49 ]. For VSL-SP, we selected VSL estimates from (1) a WTP study conducted among cervical cancer patients in Taiwan (‘Lang’) [ 50 ], (2) a recent systematic review of VSL focusing on a ‘cancer premium’ (‘Viscusi’) [ 45 ], (3) recommendation of the UK Health and Safety Executive (‘UKHSE’) [ 13 ], and (4) OECD guidelines for EU-27 countries (‘OECD’) [ 44 ]. All VSL estimates were converted to the current UK currency based on the OECD guideline [ 44 ]. To convert VSL values varying across countries and over time to the UK 2015 value, we used the benefit transfer method with income adjustments. For example, to approximate VSL used by the US Department of Transportation, we used purchasing power parity (PPP)-adjusted GDP per capita in the following equation:

figure 1

Direct and indirect benefits of two-dose HPV vaccination in the UK (top) and threshold vaccine cost (TVC) estimates (bottom) under different cost-benefit analysis (CBA) approaches

Here, PPP-adjusted GDP per capita for both the UK and the US were extracted from the World Bank [ 51 ]. To convert the VSL (in USD) estimated from the above equation to the UK currency, we used PPP-adjusted exchange rates from OECD Statistics [ 52 ]. To update VSL values across different years (e.g. 2000 to 2015), we used the average Consumer Price Index and Real Income in the UK as follows:

Data on Consumer Price Index and Real Incomes across different years were available at the UK Office for National Statistics website [ 53 ]. After the adjustment, the selected VSL estimates ranged from £1.1 million to £7.2 million. Each adjusted VSL estimate was then multiplied by the projected number of cervical cancer deaths prevented from vaccination.

WTP: the quality-adjusted life-year (QALY) monetisation (QM) approach

Under this approach, the health outcome in conventional cost-utility analyses, namely QALY, was monetised using individual WTP for an additional QALY gained. Based on a study that assessed WTP for the respondent’s own additional QALY gained (WTP sel ) in the UK [ 54 ], we applied £23,000 to the discounted QALY gained. Our QM approach with a £23,000/QALY WTP is analogous to NICE’s cost-effectiveness reference case, which has a cost-effectiveness threshold of £20,000–£30,000/QALY [ 9 ], although our approach is based on individual rather than societal WTP arguments. Hence, it would be expected that the net present value of an intervention using our QM approach would correspond to its net monetary benefit evaluated using NICE’s reference case.

Integration of production-based and QM approaches

Under these approaches, productivity loss from production-based approaches and monetised QALYs gained were both included when estimating the economic benefit of vaccination (e.g. HC/QM when HC is integrated with QM) to capture both the intrinsic and the instrumental value of better health. Such analyses are analogous to cost-utility analyses using a societal perspective.

Future deaths averted were discounted at 3.5% per annum back to the reference year, i.e. the year in which the vaccination programme is initiated. Subsequently, the value attached to averted mortality was discounted further, depending on the method used. For production-based (HC and FC) and QM approaches, the productivity loss and QALYs lost for each year of life lost due to premature death was discounted back to the year of death. For the VSL-based approaches (VSL-RP and VSL-SP), the same value was ascribed to a prevented death regardless of the age of the woman or the number of life years averted, as has been standard practice for public policy analyses [ 55 ].

Among all CBA methods considered, the WTP-based approach using the VSL yielded the highest TVC estimates. Specifically, the median TVC estimates ranged from £206 (interquartile range: £187–£223) to £939 (£855–£1021) under VSL-SP and £734 (£669–£798) to £1417 (£1291–£1541) under VSL-RP, which correspond to approximately 78.6% and 541% of the TVC estimated under the standard QM method (£262), respectively (Fig. 1 ). When the QM approach was integrated with the production-based approaches, the TVC estimates ranged from £268 (£244–£293) with FC/QM to £373 (£345–£407) with HC/QM and remained lower than that estimated under the VSL method.

Under the production-based approach, the direct benefit was £0.54 billion (£0.44 billion to £0.66 billion). The mean UK female employment rate used to measure the indirect benefits in terms of averted productivity loss was 36.9% for those aged 16–19 and 64.7–77.6% for those aged 20–64. The indirect benefits varied 9-fold across different monetisation methods utilising the production-based approach, at £33 million in FC, £37 million in FC-M, £946 million in HC, £1.1 billion in HC-M, and £324 million in HC/FC (Fig. 1 ). Consequently, the FC method resulted in the lowest TVC estimate of £69 (£56–£84), which is only 26% of the TVC estimated under the QM. When integrated with the QM method, the total indirect benefits increased by nearly 53-fold (£1.7 billion) and 2-fold (£2.6 billion) for the FC and HC methods, respectively. Similarly, with homemakers (around 8.9%–13.9% across the different age groups in 2015) included in the calculation of productivity loss under the modified production-based approaches, the TVC estimate increased by 1–2% (from £56–£84 to £57–£85) and 8–10% (from £157–£195 to £172–£211) under the FC and HC method, respectively (Additional file  5 : Table S4).

Point estimates and error bars indicate medians and interquartile ranges across 1000 scenarios randomly generated. Benefits under the VSL approaches cannot be decomposed into direct and indirect components. VSL estimates used in Gayer–1 and –2 were derived from the same study using different level of cancer risk [ 49 ].

The proportion of HtFV varied by industry sector, ranging from 23% in education (in which 16% of women work) to 43% in construction (in which fewer than 2% of women work). Considering the gender difference and varying proportions of HtFV across different establishments, we estimated that the overall proportion of HtFV among the female workforce in the UK was 31% (Additional file  3 : Table S2). That is, we estimated that 69% of all vacancies would be filled with a replaced worker within the friction period. The resulting TVC estimate was £101 (£88–£118) under HC/FC, which was 56% lower and 11% higher than that under HC and FC, respectively. Relative changes in TVC were similar when homemakers were included in the calculation of productivity loss.

We found that the economic benefits of vaccination against HPV-16 and HPV-18 in the UK could vary by as much as 20-fold depending on the method used to monetise benefits. In particular, two-dose HPV vaccination in the UK was found to be not cost-beneficial under the HC approach and all FC-related approaches except when integrated with QM.

Our results suggest that using different approaches to monetise benefits can lead to divergent conclusions about the value of vaccination. Our TVC estimates for a vaccine against cervical cancer in the UK ranged over an order of magnitude (£69–£1417) depending on the method used to value the benefits of cervical cancer prevention. The TVC estimate was lowest (£69–£191) when benefits were valued in terms of productivity loss averted due to ill health and premature mortality, particularly if the friction cost method was used, and highest (£206–£1417) when VSL methodology was used. When an individual WTP for an additional QALY gained was used instead, the TVC estimates (£262–£373) were generally higher than that obtained by valuing productivity gains but lower than that obtained using VSL methods.

Our finding that measuring benefits based on WTP estimates (e.g. the VSL and QM approaches) yields larger benefit estimates than measuring benefits based on lost production (e.g. HC and FC) is unsurprising – this is likely because the former includes both financial (e.g. medical expenses and losses in future earnings) and non-financial (e.g. avoided pain and suffering) benefits of the intervention, whereas the latter solely focuses on lost production [ 56 , 57 ]. The finding that the FC method yields much smaller benefit estimates than the HC method is likewise intuitive, because the FC method only takes into account temporary losses during the friction period while the HC method assumes lifetime losses during the entire period affected by morbidity and mortality.

Each of the methods used has advantages and limitations. Production-based approaches for valuing health gains have been criticised for not being consistent with the theoretical foundations of CBA in welfare economics, as they focus on changes in productivity rather than measuring overall welfare. Similarly, QALY-based approaches do not fit naturally within the conceptual framework of welfare economics, because they measure changes in health rather than overall welfare. The approach that most directly reflects the principles of welfare economics is to estimate the consumption that affected individuals are willing to trade-off to avoid morbidity or mortality [ 27 , 58 , 59 ].

Valuing benefits based on averted productivity loss has the advantage of being based on an easily measurable quantity (market income). However, for diseases such as cancer, which tend to cause long-term work absences, the difference in outcome between the production-based approaches can be large. In our study, productivity loss estimates under the HC approach were 29 times higher than that under the FC approach. Similarly, Oliva et al. [ 60 ] found that the annual productivity cost of mortality due to cervical cancer in Spain was €21.7 million based on HC and €0.39 million with FC (56-fold difference). Advocates of the FC method argue that there is always some level of involuntary unemployment, so the HC method overestimates the societal cost of long-term illness or death by measuring the ‘potential’ productivity loss over the entire period of absenteeism beyond the friction period [ 34 ]. The FC method purports to measure the ‘actual’ productivity loss to society from an employer’s perspective by considering the time and related costs (e.g. hiring and training costs) needed to fully restore production levels with a replacement worker.

Both conventional production-based methods have been criticised for valuing life purely in terms of marketable productive capacity and not providing an explicit value for the health gains themselves (i.e. ignoring the additional value of avoided suffering, leisure time and unpaid labour) [ 61 ]. The concern is that this may lead to prioritising interventions that primarily benefit high-wage earners over low-wage earners and those doing unpaid labour (e.g. caregiving and housework). In our analysis, we have accounted for unpaid labour by employing the modified versions (namely HC-M and FC-M) and estimate that the TVC for HPV vaccination increases by 22% with the HC and 2% with the FC method if all females are included in productivity loss calculations (data not shown here), rather than those in the paid labour force only. It should be noted, however, that the market value approach that we used measures unpaid household work based on the population average wage, which differs from the conventional method of valuing household based on the average wage of a paid household worker or carer.

Measuring lost production by using wage rates raises a number of methodological questions, including (1) whether or not to assume full employment (we capture this uncertainty by showing results using both HC, which assumes full employment and competitive labour markets, and FC, which does not make these assumptions), (2) whether the economic value of lost productivity is best captured by the employer perspective (so measured in pre-tax wages including fringe benefits and indirect costs) or employee perspective (so measured in post-tax wages), and (3) how to capture labour market constraints on how much work an individual does, since there may be requirements to work a fixed number of hours [ 62 ]. For example, Bockstael et al. [ 63 ] found that individuals who are required to work a fixed number of hours valued the opportunity cost of time approximately 3.5-fold more than the wage rate, whereas those with flexible working hours valued it similarly to their wage rate.

We proposed an alternative production-based method that may be used instead of established methods, as it strikes a balance between the two approaches in terms of assumptions about unemployment. Weighting the outputs from the two methods according to the proportion of HtFV should theoretically give estimates closer to the actual productivity loss due to ill-health.

An alternative approach is the VSL method. The VSL reflects the marginal rate of substitution between money (or income) and mortality risk and infers the value of the consumption of market goods that individuals are willing to forgo to achieve a reduced risk of premature death [ 8 ]. Hence, VSL can be seen as a direct application of the welfarist principle of consumer sovereignty. Consistent with the conceptual framework for CBA, VSL estimates are highly context specific. In practice, however, researchers often rely on the averages across country populations (or even extrapolations from other countries), which can potentially cause under- or overestimations of the result. Furthermore, there are few VSL estimates from low- or middle-income countries. VSL estimates for cancer are particularly divergent, with debates around the existence and magnitude of a ‘cancer premium’ that inflates the VSL for a cancer death in comparison to a death from an acute fatality to incorporate the latency and morbidity period of cancer. For instance, Viscusi et al. [ 45 ] suggested the use of 1.21 for cancer premium, the US Environmental Protection Agency, the European Commission and several studies recommend a cancer premium of 1.5 [ 46 , 64 , 65 ], and the UK’s Health and Safety Executive doubles the VSL (or the value of preventing a statistical fatality) estimates of accidental death to derive a VSL estimate for cancer [ 13 ]. We understand that there are concerns about transferring VSL between countries with different healthcare systems, income levels and cultural values that may affect mortality risk valuation. Nevertheless, we have used VSL estimates derived from other countries also for the following reasons: (1) there is disagreement and inconsistency with the use of a ‘cancer premium’ when applying a standard VSL to cancer studies and (2) there were few studies reporting cancer-specific VSLs at the time of the study, none of which was from the UK. To minimise such effects, we have adjusted for different income levels and costs between the countries using the ‘unit transfer with income adjustments’ method.

A third approach is to monetise individual WTP for an additional QALY gained. It offers policymakers the flexibility to incorporate additional units for the value of non-health outcomes not captured in measures such as QALYs, as well as to compare outcomes with non-health interventions. In practice, monetised QALYs has been used by government agencies such as the US Department of Health and Human Services [ 14 ] and US Food and Drug Administration for regulatory analyses [ 66 ]. However, there is still an on-going debate around the use of monetised QALYs in healthcare decision-making among health economists. During the meeting organised by the US National Institutes of Health in 2010, for example, it was argued that QALYs should not be monetised since this approach lacks theoretical and empirical support [ 67 ]. It should also be noted that adding productivity costs to monetised QALYs may lead to double counting, as there remains uncertainty about whether productivity loss has been fully captured in QALY measures [ 5 , 6 ].

Hence, a key challenge to using CBA for priority setting around public health interventions is the great variety in the way benefits can be monetised and the relative lack of detail on normative guidance about the appropriate methodology to use.

In principle, CBA offers the opportunity to capture many benefits of public health interventions such as vaccination that may not naturally fit into a CEA framework. Other approaches, such as cost-consequences analysis and multiple criteria decision analysis, also admit a wider range of outcomes, but do not offer a straightforward way to synthesise multiple outcomes into a single measure. Wider use of CBA to evaluate public health interventions will require greater convergence around the appropriate methodology to use in order to achieve consistency and comparability across different studies. Ultimately, discussions around appropriate methodology for CBA could help us better understand what we actually value about health.

Abbreviations

cost-benefit analysis

cost-effectiveness analysis

friction cost

modified friction cost method

human capital

modified human capital method

human papillomavirus

hard-to-fill vacancies

National Institute for Health and Care Excellence

purchasing power parity

quality-adjusted life-year

monetisation of QALYs

threshold vaccine cost

value of a statistical life

VSL based on revealed preference

VSL based on stated preference

World Health Organization

willingness-to-pay

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This study was supported by a commissioned grant (HSK-17-E15) from the Health and Medical Research Fund from the Government of the Hong Kong Special Administrative Region and Award Number U54GM088558 from the National Institute of General Medical Sciences. MJ was supported by the National Institute for Health Research Health Protection Research Units (NIHR HPRUs) in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England (PHE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences, the National Institutes of Health, the National Health Service, the NIHR, the Department of Health, or PHE.

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The epidemiological outputs generated from the HPV transmission dynamic model and used in the current study are available from the corresponding author on reasonable request. All other data generated or analysed during this study are included in this published article (and its supplementary information files).

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Mark Jit and Joseph T. Wu contributed equally to this work.

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Minah Park, Mark Jit & Joseph T. Wu

Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK

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MJ and JTW designed and conceived the study. MP collected and analysed the data. All authors contributed to interpreting the results and drafting the manuscript. All authors read and approved the final version before submission.

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Additional files

Additional file 1:.

Supplementary Text. Summary of the literature review and descriptions on the methodology used for calculating conventional and modified production-based approaches

Additional file 2:

Table S1. Summary of cost and QALY parameters used in the model

Additional file 3:

Table S2. Distribution of women in workforce and the proportion of hard-to-fill vacancies across industry sectors

Additional file 4:

Table S3. List of selected value of a statistical life (VSL) estimates included in the analysis

Additional file 5:

Table S4. Threshold vaccine cost (TVCs) based on different methods of monetising benefits

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Park, M., Jit, M. & Wu, J.T. Cost-benefit analysis of vaccination: a comparative analysis of eight approaches for valuing changes to mortality and morbidity risks. BMC Med 16 , 139 (2018). https://doi.org/10.1186/s12916-018-1130-7

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Cost-benefit analysis (CBA) is a method for assessing the economic efficiency of public policies through the systematic measurement of social costs and social benefits. When economic efficiency is the only relevant social goal, CBA provides an appropriate decision rule: choose the policy, or set of policies, that maximizes net social benefits. Although the conceptual foundations of CBA continue to be refined, most of the basic concepts were in place when it was explicitly introduced in the 1930s to evaluate water resource projects in the USA. Advances in empirical research methods, especially with respect to the measurement of the benefits of goods not traded in markets, have steadily expanded the plausible range of application of CBA.

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Get 10% off with 24start discount code, 1. foundations of cost–benefit analysis.

CBA is concerned primarily with efficiency in the allocation of resources. As such, it follows directly from the body of neoclassical economic theory (or resource allocation theory). Yet whereas the main body of neoclassical theory deals with the nature of private decisions by households and firms, CBA focuses on public decisions. It sets forth the requirements for any public decision, or policy, to be efficient; that is, for the policy to contribute to an ‘improvement’ in the allocation of economic resources. CBA seeks to answer the question: will an alteration in the current pattern of resource allocation improve efficiency in the use of national resources? Insofar as CBA is directed at allocative efficiency, it can be viewed as an attempt to replicate for the public sector the decisions that would be made if private markets worked satisfactorily. In private markets, no explicit attention is given to social goals such as equity. Indeed, private markets tend to respond to actual demands and resource constraints, where demand is partly a reflection of the distribution of income, and economists do not generally regard private markets as operating unsatisfactorily simply because they fail to produce goods for people who cannot afford to pay for them. Similarly, the focus of cost–benefit analysis is on allocative efficiency, and implies that public sector decisions should be guided by these same demand (not desire) and resource cost considerations. It is presumed that if there are concerns about the acceptability of the income distribution that gives rise to the pattern of demands, or to the impact of the policy’s benefits and costs on the income distribution, these concerns will be taken into account through other policies with explicitly redistributive goals.

As with the neoclassical theory that guides market analysis, CBA rests on the analytical underpinnings of modern welfare economics. Modern welfare economics shares the utilitarian presumption that aggregating the wellbeing (utilities) of the individuals who make up society is a valid measure of social wellbeing. CBA provides a basis for inferring changes in utilities, which are unobservable, from economic choices and outcomes, which are observable. These outcomes, especially if they are revealed in markets, express the value of changes in utilities in terms of a money metric. At one level, then, CBA can be thought of as the accounting protocol of welfare economics for measuring in terms of a money metric the changes in utilities caused by changes in public policy.

The principle of Pareto efficiency lies at the heart of welfare economics. An allocation of goods is Pareto-efficient if there exist no alternative allocations that make at least someone better off without making anyone else worse off. The intuitive appeal of Pareto efficiency is obvious: one would have to be malevolent to oppose a reallocation that betters the situation of someone without harming anyone else.

Although the Pareto criterion seems unobjectionable as a basis for judging the relative desirability of public policies, it would be largely useless as the basis for choice because policies without some losers are extremely rare in the real world. This limitation of the Pareto criterion prompted efforts to develop a normative welfare criterion with more general applicability to actual decisions. A more serviceable criterion for CBA arose out of proposals by Nicholas Kaldor and J. R. Hicks: a change in the allocation of resources should be regarded as increasing welfare if either the Pareto criterion is met or the persons who have gained by the reallocation could compensate those who have been harmed by it so as to leave everyone at least as well off as they would have been without the reallocation. Any resource allocation that meets this criterion is said to be a ‘potential Pareto improvement.’ This criterion expands the set of situations and policies about which statements may be made as to whether economic welfare has been increased, decreased, or left unchanged.

In resting on this criterion, CBA becomes an accounting protocol that enables the analyst to determine whether a reallocation has the potential to be Pareto improving. As a decision rule, this criterion seeks the greatest potential Pareto improvement by choosing projects that maximize the excess of social benefits over social costs.

CBA gained a distinct identity in the 1930s as a formal technique for systematically measuring benefits and costs of flood control projects sponsored by the US federal government (for an overview, see Steiner 1974). As the scope of governments grew, and economists gained influence as policy analysts, the use of CBA expanded well beyond the evaluation of public works projects. In the USA, for example, Executive Order 12291 (February 17, 1981) requires that federal regulatory agencies subject proposed regulations with estimated costs of over $100 million to CBA. Continuing advances in empirical research methods further expand its range of application. Natural resource economists, for instance, use survey methods to estimate benefits necessary for applying CBA to environmental policies.

2. Social Benefits And Costs: Concepts And Measurement

2.1 the with without principle of evaluation.

The evaluation of public projects in terms of the potential Pareto improvement principle requires that analysts determine if the value of the output in the economy with the proposed project would be greater than the value of the economy’s output without the project. Note that this comparison must be made ex ante (based on the prediction of results). It therefore requires the prediction of the future under two scenarios: one with the project and one without it. This with without principle is important for defining and measuring both social benefits and social costs.

Although CBA is forward looking, its application often requires analysts to draw on past experience as a basis for prediction. In such cases, the outcome of a similar policy previously implemented is observed but the counterfactual—what would have occurred with-out it—is not. Analysts must infer the counterfactual in order to make the with without comparison. For example, in order to assess the social costs and benefits of an existing irrigation project, analysts must infer the value of crops and environmental quality that would have been produced without the project for comparison with those observed to occur with it. This ex post CBA (based on actual results) could then be used as an empirical basis for predicting the social costs and benefits for an ex ante CBA of a proposed irrigation project with similar features.

2.2 A Comprehensive Framework: Standing

Costs and benefits in CBA derive from the preferences of the individuals who make up society. But what defines society? And are all preferences legitimate? These questions have come to be known as issues of ‘standing’ (Whittington and MacRae 1986). Recognizing that the citizens of a country share a common constitution, which sets out values and rules for making collective choices, and participate in the same national economy, most analysts define society at the national level. The evaluation of social benefits andu social costs requires that the protocol for the analysis be a comprehensive one in which all of the adverse and beneficial effects of the policy are tabulated, regardless of who in the society is harmed or helped by them. It follows that all effects accruing to national citizens (or perhaps residents) be counted.

Comprehensively taking account of effects accruing to all those with standing means that CBA differs from financial analysis. Considering only the revenue flows to government agencies is generally inadequate be-cause it does not take account of all the impacts of policies on citizens. It also means that analysts working for sub-national governments should resist pressures to ignore national costs and benefits that accrue outside of their jurisdictions. For example, a city may view a grant from the central government as only a benefit, while from the social perspective it involves an offsetting national cost.

An accounting that accepted all preferences as legitimate would be too broad. For example, most observers would not view the pleasure that psycho-paths get from physically assaulting people as an appropriate part of the utilitarian calculus. Where to draw the line between legitimate and illegitimate preferences, however, is sometimes difficult. One approach is to rely on the existing legal framework for guidance (Zerbe 1998), yet doing so assumes that existing laws are moral.

2.3 The Concept Of Social Benefits: Willingness To Pay

The fundamental concept for guiding the measurement of social benefits is the aggregate willingness to pay of those with standing for the impacts of a policy. The analyst wishes to know the maximum amounts individuals would be willing to pay for policy impacts that they view as beneficial, and the minimum amounts individuals would be willing to accept as compensation for policy impacts that they view as harmful. In other words, the analyst would like to know how much each individual’s wealth would have to be adjusted in conjunction with the policy change so that the individual’s utility remained unchanged. The algebraic sum of these wealth adjustments for all individuals measures the social value of the impacts of the policy in terms of dollars. Although some theoretical caveats apply (Blackorby and Donaldson 1985), policies with larger positive sums have larger social benefits.

Note that the amounts that people are willing to pay to obtain a policy’s impacts depends on their levels of wealth. For example, provision of a public good, such as improved environmental quality, may convey the same physical effect on all people. However, people with more wealth would be willing to pay more for this benefit than those who are poorer. An obvious implication of the dependence of individuals’ willing-ness to pay on their levels of wealth is that the aggregate willingness of a society to pay for a policy impact depends on the distribution of wealth among its members. Thus, the social benefits used in CBA are contingent upon the particular distribution of wealth that exists in the society.

2.4 Categories Of Social Benefits: Active And Passive Use

The impacts of public policies can be divided into two broad categories. In the first category are impacts that change observable behaviors of individuals. These behavioral changes are labeled ‘active use.’ For ex-ample, preserving a wilderness area may facilitate birdwatching, an observable behavior. Any such behavior provides at least the possibility of making an inference about willingness to pay through its observation.

Many policies also produce impacts that are valued by people without changing observable behaviors. The realization of these values is labeled ‘passive use.’ Analysts have found it useful to identify three distinct categories of passive use.

First, a policy may have an ‘option value’ (Weisbrod 1964). People may value a good because they anticipate the possibility of using it in the future. Only when they actually use it, if ever, will their behavior be observable. For example, a person may be willing to pay something now to preserve a national park in Alaska with the hope of visiting it someday. The person’s circumstances, however, may never allow the visit to be made.

Second, a policy may have ‘existence value’ (Krutilla 1967). People may value a good even if they never anticipate actively using it. For example, a person may be willing to pay to preserve a wildlife habitat that would be completely closed to the public. One motivation for the willingness to pay may be a belief in the intrinsic value of the natural order. Another motivation may be altruism: a desire to make the good available either to the current generation, or to bequeath it to future generations.

Third, a policy may have a ‘donor value’ (Hochman and Rodgers 1969). People may be willing to pay something for a policy that distributes goods in a way they view as desirable. The motivation may be altruistic, say in providing more to those who otherwise would be consuming less. It may also be motivated by values of equality or fairness. The inclusion of donor values integrates individual preferences over the distribution of wealth into the efficiency framework, broadening it substantially from a normative perspective. While some studies have attempted to attach explicit weights to benefits and costs depending on the characteristics of who bears them, most analysts suggest an alternative approach—namely that the distributional consequences of a proposed resource reallocation be displayed as a supplement to the cost–benefit calculation based purely on efficiency. Such a display enables decision-makers to perceive fully the distributive implications of the proposals being discussed.

2.5 The Measurement Of Social Benefits

How can willingness to pay be measured? It would be ideal if analysts could elicit willingness-to-pay amounts directly from individuals through structured conversations. If securing this information from all citizens were too costly or impossible, surveys of population samples could be used as the basis for estimating aggregate willingness to pay for the population. This approach, called ‘contingent valuation,’ is conceptually attractive because it potentially allows the analyst to elicit a willingness-to-pay amount for impacts that involve both active and passive use.

The use of contingent valuation to measure willing-ness to pay has become increasingly common, especially in the evaluation of environmental policies (Bateman and Willis 2000). A blue ribbon panel convened by the US National Oceanic and Atmospheric Administration concluded that contingent valuation could be a reasonable basis for estimating passive use values in natural resource damage assessment (Arrow et al. 1993).

Nevertheless, the use of contingent valuation re-mains controversial. One source of concern is the cognitive demands that it places on respondents in terms of understanding the policy being valued. Unless respondents understand what is being valued, and believe their answers to be consequential in influencing the policy choice, they cannot be expected to give meaningful answers to serve as the basis for an inference about the willingness to pay of the entire population. Considerable research, mainly by environmental economists, is contributing to the craft of designing effective questionnaires for contingent valuation. Another source of concern is the fear that respondents will answer strategically in the sense of giving false answers that they believe will lead to a better outcome for themselves than would result from truthful answers. Both theory and evidence suggest that giving respondents referendum-type questions about public goods minimizes the dangers of strategic responses. That is, rather than directly asking a respondent to state her willingness to pay, she is given a random dollar amount and asked if she would vote for the policy if it would cost her that amount in higher taxes or increased costs for other goods. An estimate of mean or median willingness to pay for the sampled population can be inferred statistically from sample responses.

The conceptual and practical problems in conducting contingent valuations commonly lead analysts to estimate willingness-to-pay amounts through inferences from observation of the behavior of individuals, especially in markets. Demand analysis plays an especially important role in such estimation. A per-son’s demand schedule for a good tells how much of a good the person wishes to purchase as a function of the price of the good, holding all other prices and the person’s utility constant. The height of the demand schedule at each level of consumption gives the person’s willingness to pay for an additional unit of consumption. The difference between the willingness to pay for this unit and the amount that the consumer actually pays is its ‘consumer surplus.’ Adding up the surpluses for each of the units consumed gives the total consumer surplus that accrues to the person from participation in the market or experiencing services produced by the public sector.

If a policy measure either satisfies a demand that has not been met, or changes the price of a good or service that a person is already consuming, the consumer surplus of the person will be changed. This change is the person’s willingness to pay for the impact of the policy measure. (Graphically, the consumer surplus is the area under the demand schedule but above the market price from zero units to the number of units actually purchased.) If the good or service produced by the public sector is a private good, in that it does not generate external, or spillover, costs or benefits, then the market demand schedule for the good (that is, the horizontal sum of all the individuals’ demand schedules) provides the basis for estimating changes in consumer surplus, and hence changes in the aggregate willingness to pay of individuals for the effects of the policy.

The market demand schedule must be estimated from observed price and quantity data. The standard econometric procedures result in the direct estimation not of the demand schedule described above, which holds the utilities of individuals constant (the Hicksian or compensated demand schedule), but of one that holds their incomes constant (the Marshallian or market demand schedule). Quite often these demand schedules are sufficiently similar so that measuring consumer surplus in terms of the market demand schedules provides good approximations of the aggregate of individuals’ willingness-to-pay amounts (Willig 1976).

Estimation of willingness to pay is more difficult when policy impacts do not correspond to changes in markets for traded goods. For example, though most people would be willing to pay positive amounts for improvements in environmental quality, there is no market for this public good. People may convey information about their willingness to pay for changes in environmental quality, however, by their action in other markets. So, for instance, housing values may change to reflect changes in levels of noise pollution near airports, thereby providing a so-called ‘shadow’ price for quiet. In general, shadow prices refer to inferences of marginal social value when it is not revealed through market prices.

This approach is based on what is called the ‘hedonic price model,’ which provides a theoretical basis for statistically isolating the independent effects of the various characteristics of a product on price. It has been used extensively to estimate the benefits of air quality improvements and health risk reductions from wage and housing value variation. An important use of the hedonic price model in CBA has been to estimate the ‘value of life,’ defined as the amount that people are willing to pay for reductions in the risks of death that they face (see Viscusi 1993). Analysts can take advantage of prior research to find estimates of relevant shadow prices (Boardman et al. 1997). For example, a large number of studies conducted across a number of countries suggest that commuters value reductions in their travel times at between 40 and 50 percent of their after-tax wage rate (Waters 1996).

2.6 The Concept Of Social Costs: Opportunity Costs

The implementation of policies usually requires the use of economic inputs that could be used to produce other things. CBA uses the concept of ‘opportunity cost’ to value these particular policy impacts. The opportunity cost of an input is the value of the goods and services that the input would have produced in its best alternative use. This value is just the willingness to pay for these goods and services on the part of those who would have consumed them if they had been produced.

Opportunity cost may or may not correspond to the accounting cost of inputs used to implement policies. If purchasing the input in a competitive market does not alter the price in the market, then opportunity cost and accounting cost are identical. For example, buying books for a local reading project is unlikely to affect prices so that the purchase cost of the books represents their opportunity cost. If purchasing the input in a competitive market increases the market price, then opportunity cost will be less than the accounting cost based on the post-purchase price. For example, buying concrete for a dam in a local market may drive up the price of concrete, as the marginal costs of producing concrete increase. However, some of the payments at the higher price will be to more efficient suppliers with lower marginal costs. These payments in excess of marginal costs, called ‘rents,’ are simply transfers from the project budget to the efficient suppliers and therefore do not contribute to opportunity cost. The opportunity cost of inputs purchased in noncompetitive markets may be larger, smaller, or equal to their accounting cost. For example, the opportunity cost of the time of people compelled to serve on juries may be larger or smaller than the legally set payments they receive from the court.

2.7 The Measurement Of Social Costs

The problems encountered in measuring social opportunity costs are very similar to those confronted in measuring social benefits. A commonly encountered problem in CBA is the measurement of the opportunity cost of unemployed labor. The conceptually correct measure is the value of the forgone leisure to each worker. The accounting cost of the project is certainly an overestimation of the opportunity cost of otherwise unemployed labor. Alternatively, zero is probably an underestimation of the opportunity cost. Rarely do analysts have enough information about the value of the forgone leisure to estimate the conceptually correct opportunity cost for unemployed labor so they usually use some fraction of accounting cost as an approximation (Haveman and Krutilla 1968).

Another commonly encountered problem in CBA is the appropriate measurement of the opportunity cost of government revenues. Standard practice is to treat a dollar of accounting cost raised through taxation as the equivalent of a dollar of opportunity cost. Raising revenue through taxes, however, usually involves inefficiencies, or ‘deadweight losses,’ that reduce social welfare. The amount by which the social cost of a dollar of tax revenue exceeds its nominal value is called its excess marginal burden. Expenditures funded by tax increases, and revenues allowing tax reductions, should be adjusted by the marginal excess burden of the relevant tax. A number of estimates of marginal excess burden have been made for various components of the US tax system (Jorgenson and Yun 1990).

An appropriate accounting of opportunity costs helps clarify when the inclusion of so-called secondary benefits is correct (Haveman and Weisbrod 1975). The primary benefits of a project derive from its direct effects. For example, the primary benefit of stocking a lake with game fish is to increase the supply of fishing days. The improved fishing might very well have secondary effects, such as the construction of a nearby hotel. It is usually incorrect to attribute any benefits to the secondary effects because they involve offsetting opportunity costs—the hotel requires resources that could have been used to build it elsewhere. Such secondary effects may involve benefits, however, if they use otherwise unemployed resources such as labor. In such cases, the benefits produced may not be fully offset by opportunity costs. A final point on opportunity cost: resources already expended have zero opportunity cost if they are no longer available for other uses. These previously expended resources are known as ‘sunk costs.’ Because it is forward looking, CBA ignores sunk costs.

3. Timing Of Costs And Benefits: Discounting

The social benefits and costs generated by a public program often extend over long periods. Because waiting is costly, the amount that people value a dollar of benefits or costs in the future is less than if that value were obtained in the present. In an ideal economy, markets for lending and borrowing funds (also known as capital markets) balance the preferences of lenders who require a payment for giving up use of their funds (hence, delaying consumption) and the preferences of borrowers who invest in projects with future payoffs. In this situation, the market interest rate that is the outcome of this balancing serves as the basis for adjusting costs and benefits occurring in the future to make them commensurate with costs and benefits occurring in the present. This adjustment for time is called discounting. In particular, if r is the annual market interest rate, then a dollar of cost or benefit that will be realized after N years in the future would have a present value of 1/(1+ r) N . Maximizing the present value of net benefits would maximize potential Pareto efficiency.

This simple solution results if capital markets are competitive and not restricted or distorted, for example because of taxes on savings (consumption) or on the returns from investment. When such distortions exist, the solution becomes more complicated. Such taxes insert wedges between the marginal valuation of funds by lenders and borrowers. With such wedges, it is not clear which of the values is appropriate for discounting: the before-tax rate of return of borrowers who invest (the marginal rate of return on private investment), or the after-tax return faced by lenders (the marginal rate of pure time preference). Another distortion is general price inflation. Market interest rates reflect expectations about inflation. They correspond to projections of costs and benefits in inflated (nominal) dollars. When costs and benefits are projected in terms of current (real) dollars, typically the most convenient method, nominal discount rates must be converted to real discount rates.

Although some controversy remains, most analysts do seem to agree that the social discount rate should reflect the fact that both consumption and investment are foregone when the public sector uses resources. Thinking of the discounting problem in terms of shadow price of capital provides a way of taking account of these effects (Bradford 1975, Boardman and Greenberg 1998). It involves using the marginal rate of return on private investment to convert any foregone investment to the stream of future consumption that it would have produced. The consumption equivalents of foregone investment are then added to any foregone consumption to express all resource costs in terms of consumption, which can then be appropriately discounted using the marginal rate of social time preference.

4. Accounting For Uncertainty

As CBA involves prediction, it can rarely be done with certainty. The standard approach to dealing with uncertainty is to estimate expected net benefits. The first step is to convert the problem from one of uncertainty to one of risk by assuming a plausible distribution of benefits. The second step involves finding the expected value, basically the weighted average, over this distribution. Third, society is assumed to be risk-neutral, so that the expected values can be treated as commensurate with certain values. For example, a project with certain opportunity costs of $15 million and a 20 percent chance of yielding $5 million in benefits and an 80 percent chance of yielding $20 million in benefits would have expected benefits of $17 million and expected net benefits of $2 million.

The calculation of expected net benefits, however, does not fully take account of individual preferences for risk. Individuals may not be willing to trade certain amounts for expected values of the same magnitude. In such cases, the appropriate measure of benefits is ‘option price,’ the individual’s willingness to pay for the particular distribution of outcomes associated with a policy (Graham 1981). As individuals are generally risk averse, policies that reduce risk generally have option prices larger than expected benefits. The difference, ‘option value,’ is a premium individuals are willing to pay for the reduced risk. As option price can only be elicited through contingent valuation surveys, it is rarely estimated. Unfortunately, relatively little progress has been made in the theoretical determination of the magnitude or even sign of option value. For policies involving substantial risks, especially if the risks are social in the sense that everyone realizes the same outcome, the use of expected benefits may introduce substantial error into CBA. Even when the policy being evaluated is not inherently risky, analysts may be uncertain about their predictions of its costs and benefits. It is common, therefore, for analysts to test how sensitive their estimates of costs and benefits are to particular assumptions. This process, called ‘sensitivity analysis,’ typically involves changing the assumed values of a few key parameters to see how net benefits change.

5. The Maximum Net Benefits Rule

Assuming that all of the costs and benefits of a policy have been correctly measured, discounted, adjusted for uncertainty, and aggregated, positive net benefits indicate that the policy is potentially Pareto improving: the excess of benefits over costs would permit the policy to be implemented in conjunction with a set of compensatory transfers such that at least someone would be better off without anyone being worse off. Thus selecting policies on the basis of positive net benefits, the Kaldor-Hicks criterion discussed above, guarantees that adopted policies are potentially, but not necessarily actually, Pareto-improving.

The rule can be stated as follows: choose from among all possible policies those that offer the largest sum of net benefits. In the special case of mutually exclusive policies, the one with the largest net benefits should be selected. In the special case of completely independent policies, all those with positive net benefits should be selected. Note that this rule says nothing about a benefit–cost ratio, which is a common calculation made by CBA analysts. The use of a benefit– cost ratio criterion is appropriate only if the policies are independent of each other, in which case the set of projects with benefit–cost ratios greater than one corresponds to the rule of adopting policies with positive net benefits.

6. Further Reading

A number of textbook-length treatments of CBA are available for those wishing to explore it in much more depth (Boardman et al. 2001; Dinwiddy and Teal 1996, Zerbe and Divily 1994, Gramlich 1990, Sugden and Williams 1978).

Bibliography:

  • Arrow K, Solow R, Portney P, Leamer E, Radner R, Schuman H 1993 Report of the NOAA Panel on contingent valuation. Federal Register 58: 4601–14
  • Bateman I J, Willis K G (eds.) 2000 Valuing Environmental PBibliography: Theory and Practice of the Contingent Valuation Method in the US, EC, and De eloping Countries. Oxford University Press, Oxford, UK
  • Blackorby C, Donaldson D 1985 Consumers’ surpluses and consistent cost–benefit tests. Social Choice and Welfare 1: 251–62
  • Boardman A E, Greenberg D H 1998 Discounting and the social discount rate. In: Thompson F, Green M T (eds.) Handbook of Public Finance. Marcel Dekker, New York
  • Boardman A E, Greenberg D H, Vining A R, Weimer D L 2001 Cost–Benefit Analysis: Concepts and Practice. Prentice-Hall, Upper Saddle River, NJ
  • Boardman A E, Greenberg D H, Vining A R, Weimer D L 1997 Plug-in shadow price estimates for policy analysis. Annals of Regional Science 31: 299–324
  • Bradford D F 1975 Constraints on government investment opportunities and the choice of discount rate. American Economic Review 65: 887–99
  • Dinwiddy C, Teal F 1996 Principles of Cost–Benefit Analysis for De eloping Countries. Cambridge University Press, New York
  • Graham D A 1981 Cost–benefit analysis under uncertainty. American Economic Review 71: 715–25
  • Gramlich E M 1990 A Guide to Benefit–Cost Analysis. Prentice Hall, Upper Saddle River, NJ
  • Haveman R H, Krutilla J V 1968 Unemployment, Idle Capacity, and the Evaluation of Public Expenditures. Johns Hopkins University Press, Baltimore, MD
  • Haveman R H, Weisbrod B A 1975 Defining benefits of public programs: some guidance for policy analysts. Policy Analysis 1: 169–96
  • Hochman H M, Rodgers J D 1969 Pareto optimal redistribution. American Economic Review 59: 542–57
  • Jorgenson D W, Yun K Y 1990 Tax reform and US economic growth. Journal of Political Economy 98: S151–93
  • Krutilla J V 1967 Conservation reconsidered. American Economic Review 57: 777–86
  • Steiner P O 1974 Public expenditure budgeting. In: Blinder A S, Solow R M, Break G F, Steiner P O, Netzer D (eds.) The Economics of Public Finance. Brookings Institute, Washington, DC
  • Sugden R, Williams A H 1978 The Principles of Practical Cost–Benefit Analysis. Oxford University Press, New York
  • Viscusi W K 1993 The value of risks to life and health. Journal of Economic Literature 31: 1912–46
  • Waters W G 1996 Values of travel time savings in road transport project evaluation. In: Hensher D et al. (ed.) World Transport Research. Elsevier, New York, Vol. 3
  • Weisbrod B 1964 Collective consumption services of individual consumption goods. Quarterly Journal of Economics 78: 71–7
  • Whittington D, MacRae D 1986 The issue of standing in cost–benefit analysis. Journal of Policy Analysis and Management 5: 665–82
  • Willig R D 1976 Consumer’s surplus without apology. American Economic Review 66: 589–97
  • Zerbe R O 1998 Is cost–benefit analysis legal? Three rules. Journal of Policy Analysis and Management 17(419): 56
  • Zerbe R O, Divily D D 1994 Benefit–Cost Analysis in Theory and Practice. HarperCollins, New York

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Cost-Benefit Analysis versus Cost-Effectiveness Analysis from a Societal Perspective in Healthcare

Cost-effectiveness analysis (CEA) is the main way that economic evaluations are carried out in the health care field. However, CEA has limited validity in deciding whether any health care evaluation is socially worthwhile and hence justifies funding. Cost-Benefit Analysis (CBA) is the economic evaluation method that should be used to help decide what to invest in when the objective is to record the impact on everyone in society. Cost-utility analysis (CUA), which has its roots in CEA, can be converted into CBA under certain circumstances that are not general. In this article, the strengths and weaknesses of CEA relative to CBA are analyzed in stages, starting in its most classical form and then proceeding via CUA to end up as CBA. The analysis takes place mainly in the context of five actual dementia interventions that have already been found to pass a CBA test. The CBA data is recast into CEA and CUA terms in tabular form in order that the contrast been CEA and CBA is most transparent. We find that how much of the fixed budget that is used up to fund other alternatives determines how much is left over to fund the particular intervention one is evaluating.

1. Introduction

Using cost-effectiveness analysis (CEA) in healthcare, by finding the intervention which produces a specific outcome at the lowest cost, may be useful when the perspective is limited to a hospital, healthcare provider, government agency or other healthcare institutional setting, especially when a budget has been provided to fund the least cost interventions. But, when the perspective is social, meaning everyone in society, whether they be family members, third parties or taxpayers is involved, and a budget has not been allocated, a CEA is completely insufficient for deciding priorities as to which interventions, if any, should be funded. In this context, cost-benefit analysis (CBA) is the more relevant economic evaluation method.

The purpose of this paper is to explain precisely why, and how, CBA is the more relevant evaluation method when one is taking a societal perspective in healthcare when evaluating interventions (For a CBA text that focuses solely on the field of heath care, see [ 1 ]). This will be carried out mainly in the context of evaluating five new interventions for reducing dementia symptoms. The new dementia interventions involved are: years of education (a dropout prevention program), Medicare eligibility (the extra services it provides), hearing aids (over a lifetime), vision correction (over a lifetime), and avoiding living in a nursing home (as residing in a nursing home increases dementia symptoms). What made these five interventions “new” was not that the medical literature was unaware of them; rather it was because they were recently fully evaluated using CBA, and newly shown to be worthwhile financing, see [ 2 ].

For the five dementia interventions we will be highlighting, estimation of benefits and costs were carried out using a large, national panel data set from the National Alzheimer’s Coordinating Center (NACC) (Alzheimer’s is the main category of dementia experienced throughout the US. In our NACC data used for making the economic evaluation calculations presented in this article, we cover all categories of dementia). However, in order that the contrast between using CEA and CBA be fully transparent, some of the data used for the CBA evaluations will be recast also into CEA terms.

The outline of the paper is as follows. We start the analysis by viewing CEA as a method of economic evaluation in its classical form, which involves covering mutually exclusive interventions with, and without, a budget constraint. Then we move on to the more general form of CEA which is called cost-utility analysis (CUA). CUA can be viewed as CEA, but it also can be converted into a CBA with one extension. This leads the analysis to CBA proper which, unlike CEA, can be applied to any type of healthcare intervention to assess whether it is socially worthwhile. In the discussion section, some of the background wider issues concerning CEA and dementia interventions are presented. We close with the summary and conclusions.

2. Cost-Effectiveness Analysis

2.1. cost-effectiveness analysis with a budget constraint.

Here we will present the findings of the evaluations of the five new dementia interventions using the CEA methodology. We will assume that the institutional setting involves the US government, say Medicare or Medicaid is making the expenditure decisions (Of the five dementia interventions, only education, Medicare eligibility, and avoiding nursing homes actually involved government involvement).

The starting point for a CEA is to define the effect unit that is to be costed for each of the interventions. For the five new dementia interventions, the effect was the reduction in dementia symptoms as measured by the Clinical Dementia Rating (CDR) scale, known as the CDR ® Dementia Staging Instrument , created by Washington University (The CDR is a measure of dementia severity used globally that is based primarily on a neurological exam and informant reporting, see [ 3 ]. A CDR was administered to each NACC participant at each visit by a clinician. There are six domains in the CDR: memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care. Each domain is assessed using a 0 to 3 interval (none, mild, moderate and severe) with a questionable response being scored as 0.5. The CDR-SB (the CDR sum of boxes) is the aggregate score across all six domains and this has a range of 0 to 18. It is important to understand that using dementia symptoms as the effect is basing cognitive impairment on a behavioral definition of dementia (interfering with activities of daily living) rather than the medical definition, which relies on brain pathology (for example fibers and plaques for Alzheimer’s). At this time, there are no interventions that can alter brain pathology, but there does already exist interventions that can reduce dementia symptoms.

To obtain the effect from any intervention, resources have to be allocated and they have to be costed. In CEA the costing is usually related just to the institution undertaking the financing, which is called the private costs. Although the costing for the CBA’s of the new dementia interventions was wider than this, we will assume, just for simplicity, that the CBA costs were the relevant ones for the CEA (We will relax this assumption when we deal with externalities when the analysis switches to social CBA).

Dividing these cost estimates by the outcome effects produces the cost-effectiveness ratios for each intervention. CEA proceeds by ranking each intervention from the lowest to the highest ratio. Table 1 shows how CEA would rank the five new dementia interventions. On the basis of this ranking of the five interventions, education would be the most cost-effective, and avoiding living in a nursing home would be judged the least-cost-effective.

Cost-Effectiveness of Various Dementia Interventions.

InterventionEffect: Reduction in Dementia SymptomsCosts per PersonCost-Effectiveness Ratio
Education0.3459USD 1400USD 4047
Corrective Lenses0.1858USD 765USD 4117
Medicare Eligibility0.9182USD 6540USD 7123
Hearing Aids0.7251USD 8498USD 11,719
Avoiding Nursing Homes3.2367USD 54,545 *USD 16,892

* The benefit and cost figures for nursing homes in [ 2 ] were in population terms. To convert them into per-person terms, one needs to divide by 1.1 million, the approximate number of older adults in Medicaid-financed nursing homes. The total costs of living in nursing homes in the CBA (which was the difference between total benefits of USD 1.93 trillion and the benefits without the nursing home cost savings, which was USD 1.87 trillion) was equal to USD 0.06 trillion. Dividing this sum by 1.1 million produces a cost per person of USD 54,545.

As to the issue of which interventions, if any, would actually be funded, the budget constraint needs to be specified, which involves knowing the amounts available to the government to devote to the interventions. We will consider three possible budget limits: $10,000, $20,000 or $70,000 per person. For a budget of $10,000, the government would only approve education, corrective lenses and Medicare eligibility, as the cumulative sum totals $8705. For a budget of $20,000, hearing aids would be added (making the total $17,2037). For a budget of $70,000 not even avoiding nursing homes, which has by far the largest effect, would be approved, as the total cost with this intervention added would amount to $71,748.

It is clear from this application of the CEA method to the new dementia interventions that the decision-maker who specified how large the budget for the institution was going to be, was effectively determining which interventions were worthwhile for that institution and therefore were going to be carried out. The fundamental weakness of CEA is that this budget decision would be made in advance of knowing what interventions were available, and what the costs and effects are likely to be of the interventions that were available.

2.2. Cost-Effectiveness Analysis without a Budget Constraint

In the absence of a pre-specified budget constraint, the main role of CEA as an intervention evaluation method is to indicate which dementia interventions can be eliminated from consideration and therefore not to be financed. There are two categories of interventions that can be eliminated.

The first category contains any interventions that are not effective. For example, take the case of placing an older adult for skilled nursing care in the custody of a nursing home. In the case of the interventions listed in Table 1 , if under consideration is living in a nursing home (that is, not avoiding residing in a nursing home), Table 1 informs the decision-maker that residing in a nursing home actually increases dementia symptoms by 3.3267 points. This intervention would be counterproductive and so should be eliminated from consideration. In the process, one does not experience the increased dementia symptoms and one obtains a cost saving of $54,545. It is because of this effect gain and the avoidance of incurring costs, that avoiding living in a nursing home becomes a productive intervention and can be included in Table 1 .

The second category of intervention that can be eliminated involves an effect gain, or a cost saving from an intervention not listed, but involves some variation of the ones listed. The listed ones are not mutually exclusive as both hearing aids and corrective lenses can both be approved (The listed ones must also be not repeatable, or else one can just fund one intervention over and over again if that is the one that is the most cost-effective). However, if a variation of a listed intervention is the new intervention being evaluated, then the new intervention is mutually exclusive, as both the listed and the new intervention cannot both take place at the same time. In this case, the cost-effectiveness of the particular listed intervention becomes the benchmark for deciding the fate of the new intervention. Thus, for example, consider instead of purchasing five sets of hearing aids over a lifetime, which is what the hearing aid intervention listed in Table 1 involved, one is now evaluating instead purchasing six hearing aids over one’s lifetime. If this sixth set costs more than $8498, yet does not produce greater effects, then it can safely be eliminated as it is dominated by the existing listed intervention (More generally, for mutually exclusive interventions where the new intervention has both a different cost and effect than an existing intervention, the CEA must be decided on the basis of the incremental cost-effectiveness ratios rather than average cost-effectiveness ratios that we have been using. See [ 4 ]).

As we have just seen, CEA without a budget constraint can be useful by eliminating some interventions that are not effective, and are dominated by variations of the listed interventions. However, the decision-maker still does not know with CEA whether any of the listed interventions in Table 1 are worthwhile funding.

2.3. Cost-Utility Analysis as Cost-Effectiveness Analysis

From the perspective of CEA, Cost-Utility Analysis (CUA) is a CEA that involves the most general health care outcome, which is a Quality Adjusted Life Year (QALY). A QALY is the product of the number of life-years affected (LY) and the quality of any one life year (QoL). In principle, every health care intervention that one can think of, that has an effect, must affect either the quantity or quality (or both) of a person’s life, and that is why it is the most general effect to use in a CEA.

Three of the new interventions listed in Table 1 had CBAs that used data that can be expressed in units of QALYs. In Table 2 we present the three QALY effects, and combine them with the costs from Table 1 , to form the cost-utility ratio which is the cost-effectiveness ratio in a CUA.

Cost-Utility Analysis of Various Dementia Interventions.

InterventionEffect: Increase in QALYsCosts per PersonCost-Utility Ratio
Corrective Lenses0.1012 *USD 765USD 7559
Hearing Aids0.6785 **USD 8498USD 12,525
Avoiding Nursing Homes3.4282USD 54,545 USD 15,911

* The outcome measure in [ 2 ] for corrective lenses was in terms of mortality and the reduction was 0.0044. Multiplying this mortality reduction by a life expectancy of 23 years produces the equivalent QALY increase of 0.1012. ** The outcome measure in [ 2 ] for hearing aids was in terms of the quality of a life year and the reduction was 0.0295. Multiplying this quality of life increase by a life expectancy of 23 years produces the equivalent QALY increase of 0.6785.

What is interesting about the alternative cost-effectiveness ratios in Table 2 is that the ratios with QALYs as the measure of effect is much higher than when dementia symptoms were the measure of effect. This confirms the obvious point that CEA ratios very much depend on the specific effect measure it uses. Thus, CEA’s applicability is not general unless it is in the form of a CUA.

What is not so obvious is that an intervention’s chances of being approved is very much dependent on what other interventions are not being evaluated. Not appearing in Table 2 are the education and Medicare interventions, because QALY information was not available for these two interventions. Without consideration of these two interventions, Table 2 reveals that avoiding nursing homes would now be approved if the budget were USD 70,000 (as the total cost of the three interventions would be USD 63,808) while before it was rejected. Even with CEA in the form of a CUA, assigning a budget in advance of knowing which interventions will be evaluated, and actually funded, is not a rational economic evaluation method.

When no budget constraint has been assigned, to use CUA for decision-making purposes, CUA league tables are often referred to. These tables rank from lowest to highest, in terms of their cost per QALY, a host of interventions appearing in the literature. These tables are then used for comparison with the particular intervention one is evaluating using CUA, which in our case relates to dementia. Table 3 gives an abbreviated league table that appeared in [ 5 ] (The interventions in Mason et al.’s (1993) table are valued in 1990 UK pounds. To facilitate comparison with the US dementia interventions used in this article, which were mainly in 2000 dollars, the UK 1990 GBP value was raised to its 2000 GBP equivalent, using the consumer price index, and then converted to USD using the official foreign exchange rate. Thus, the conversion involved multiplying the GBP amount by 2.1818).

Cost-Utility Analysis of Various Non-Dementia Interventions.

InterventionCost-Utility Ratio
Cholesterol Testing and Diet TherapyUSD 480
Hip ReplacementUSD 2545
Kidney TransplantUSD 10,276
Home HaemodialysisUSD 37,658
Erythropoietin Treatment for Anaemia in Dialysis Patients USD 118,616

Comparing the cost-utility ratios in Table 2 with those in Table 3 , we would conclude that none of the three new dementia interventions was as cost-effective as cholesterol testing and diet therapy, which had the lowest cost-utility ratio of all listed by [ 5 ]. However, all three dementia interventions were more cost-effective than Erythropoietin Treatment. Clearly, it matters which intervention in the league table you are using for comparison purposes. Mason et al. are right to point out that for league tables to be valid, they need to be standardized, such that the same measures of utility, cost and discount rate, are used to calculate the cost-utility ratios. But, standardization does not solve the problem of knowing which intervention in the league table is to be used as the benchmark. Just as important is the fact that even when a benchmark intervention has been identified in the CUA league table, one still does not know whether that benchmark is worthwhile or not. A CBA of the benchmark intervention first needs to be undertaken, in order to know whether being more cost-effective than the benchmark justifies funding the intervention.

3. Cost-Benefit Analysis

The definition of a benefit is an effect that is valued in monetary terms. Because it is expressed in monetary terms, it is then commensurate with the costs, which are almost always measured in monetary terms (For an exception, where costs and benefits are both expressed in non-monetary terms ((time is the numeraire), see the CBA of the 55-mph speed limit in [ 6 ]). It is therefore now possible to compare directly the benefits and costs to see which is greater. If, and only if, the benefits exceed the costs, that is, the difference (called the net-benefits) is positive, then the intervention is worthwhile from the institutional perspective. If the costs and benefits relate to everyone who lives in society, which means that they are social benefits and social costs, then any positive net-benefits indicate that the intervention is socially worthwhile.

3.1. Cost-Utility Analysis as Cost-Benefit Analysis

The effect in a CUA is a QALY (Thus, a QALY is in each individual’s utility function. The social utility is then simply the sum of each individual’s utility function, which is the total number of QALYs for everyone from an intervention). To be designated as a benefit, the QALY must be valued, that is, given a price. In CUA that purports to be a CBA, the price is treated as a constant and is determined independently from the circumstances of the intervention being evaluated. The CUA constant price is a threshold price, usually set at the national level. It is the minimum price assigned to the QALYs in order for the intervention to be judged worthwhile (mainly by others). Often the threshold price is based on some multiple of per capita national income. Ref. [ 7 ] surveyed the literature on the threshold value and suggested a QALY price between USD 100,000 and USD 150,000.

As an example of a CUA used as a CBA, refer to [ 8 ] evaluation of Cholinesterase Inhibitors and Memantine medicines for those with Alzheimer’s dementia. Their results appear in Table 4 . They used the upper limit of USD 150,000 from Neumann et al. as their threshold QALY price. All four monotherapies were found to be socially worthwhile (have positive net-benefits). Since the interventions were mutually exclusive, of the four monotherapies, only Donepezil would have been chosen to be funded.

Net Benefits of Various Dementia FDA-approved medicine interventions.

InterventionBenefits per Person Costs per PersonNet-Benefits per Person
Rivastigmine Oral MonotherapyUSD 131,400USD 58,277USD 73,123
Galantamine MonotherapyUSD 144,150USD 60,793USD 83,357
Memantine MonotherapyUSD 194,100USD 48,728USD 145,372
Donepezil MonotherapyUSD 241,350USD 48,176USD 193,174

1 The benefit figures in this column were constructed by taking the QALY estimates for each intervention from [ 8 ]’s Table 1 , and multiplying them by the threshold value of USD 150,000 per QALY.

It is important to understand that the price of a QALY in CBA is primarily meant to be what a person is willing to pay (WTP) for that QALY. This implies that there are two fundamental weaknesses of using a single threshold price to convert a CUA into a CBA. The first weakness, as pointed out by [ 9 ], is that it applies a constant price to a QALY. This is a drawback because in economics a demand curve is drawn based on the principle of diminishing marginal utility. This implies that the price that a person is WTP to pay for a QALY decreases as the more QALYS one consumes increases. Johannesson’s point is relevant to the interventions in Table 4 because Donepezil’s total of 1.6 QALYs was greater than for any of the other interventions. If one QALY is valued at $150,000, but the second QALY is valued at only USD 50,000, then the 0.6 additional QALYs is valued at 0.6 of $50,000 and not 0.6 of USD 150,000 as in Table 4 . The Donepezil Monotherapy benefits would be downsized to $180,000, making the net benefits become $131,824, which is now lower than for Memantine Monotherapy. Priorities could be altered if the assumption of a constant price is invalid.

The other weakness of CUA using a threshold price as the price of a QALY is that it is not based on a person’s WTP. One of [ 7 ]’s justification for the $150,000 threshold came from the World Health Organization’s suggestion that the threshold should be two to three times per capita income, which was around $54,000 in 2014. Using national income as a benchmark is a human capital justification and this is not at all based on an individual’s preferences (The human capital approach used for valuation in CBA in health care assumes that the value of one’s life is the foregone output that society no longer receives because the person dies. The value placed on this foregone output in national income accounting is the price that others place on the products, not what the person whose life is at stake values his or her life).

3.2. CBA Not Based on CUA

Whether one selects Donepezil Monotherapy or Memantine Monotherapy from the list of the mutually exclusive rivals in Table 4 , its social value does not then need to be compared with any other intervention to be justified. The net-benefits are positive and this is the only prerequisite. This is the criterion for any dementia intervention using CBA to be determined to be socially worthwhile. This means that any type of effect that is valid for an intervention can be used in a CBA and it is not necessary that dementia symptoms be standardized in any way as in Table 1 and Table 2 . The effect can be anything that provides value for an individual and society.

In the top part of Table 5 we supply the net-benefits from the CBAs of the five new interventions. Because the effects can be anything that the evaluator considers relevant, the Table is not restricted to the three evaluations that appeared in Table 2 that relied for effects on QALYs (consisting of corrective lenses, hearing aids and avoiding living in nursing homes). Added is education and Medicare eligibility which used the independent living cost savings of reducing dementia symptoms as the effect to be evaluated as in Table 1 . It is true that with different measures of effects, the method used for the pricing of effects would be different. But, the point is that if the valuation method used is valid, because it is based on individual preferences, then any intervention with positive net-benefits is worthwhile irrespective of which other alternative interventions are available (providing that they are not mutually exclusive).

Net Benefits of Various Dementia Interventions.

InterventionBenefits per PersonCosts per PersonNet-Benefits per Person
Education$5500$1400$4100
Corrective Lenses$14,249$765$13,484
Medicare Eligibility$9338$6540$2798
Hearing Aids$248,425$8498$239,927
Avoiding Nursing Homes$1700,000($54,545) $1754,545
Preventing Elder Abuse$50,000$7500$42,500
Cognitive Rehabilitation$8875$942$7933

The pricing method used for the corrective lenses, hearing aids and avoiding nursing homes interventions was based on the Value of a Statistical Life (VSL) literature. Individual preferences are involved in this method because individuals are willing to trade off a specific probability of dying on the job for the extra salaries that are paid per year to compensate for incurring that extra risk. If a person is willing to accept $5000 as compensation for a one-in-thousand chance of dying, then a thousand times $5000, that is $5 million, is what a thousand times greater risk would be worth, statistically speaking. This simply means that, if a population of 1000 persons are working with a one-in-thousand risk of dying, one should expect, on average, one person would be dying for that $5 million aggregate compensation (The $5 million amount was based on [ 10 ]).

The pricing method for the education and Medicare eligibility interventions was in terms of the savings by the effect of reducing dementia symptoms increasing the chances of independent living. When a person can transfer to independent living, caregivers do not have to give up their time and resources looking after the person with dementia. This is true for the government as well as for private citizens as Medicare expenses can go down when people’s dementia symptoms are reduced.

At the bottom part of Table 5 are added two other dementia interventions that did not rely on the NACC data, but illustrate how widespread and multidimensional any dementia intervention can be. Firstly, there is reductions in elder abuse. People take advantage of persons with dementia resulting in psychological, financial and physical elder abuse. This abuse is something that people are WTP to avoid. Using the willingness to prosecute as a measure of this WTP, a benefit amount of between $40,000 to $50,000 was estimated, varying with the type of abuse. By reducing dementia symptoms, one is reducing the extent of elder abuse. Subtracting the cost of $7500 involved with facilitating the prosecution of the abusers, the net-benefits of reducing the dementia symptoms were calculated to be $42,500 (See [ 2 ], chapter 8).

The second intervention added to the bottom part of Table 5 was cognitive rehabilitation. Even when dementia symptoms cannot be reduced directly, the consequences of a person’s dementia symptoms can be mitigated, especially for the benefit of a dementia person’s caregiver. Cognitive Rehabilitation, in the form of the Tailored Activity Program (TAP)—see [ 11 ]—involves an individual specific intervention whereby an occupational therapist comes to a caregiver house, finds out what dementia behavior needs changing, and trains the dementia person to adapt his/her behavior to reduce the caregiver’s time spent “doing things” or spent “on duty” for the person with dementia. Since time saved by the caregiver can be given a monetary value using labor market valuations, for example, by using the federal minimum wage rate, the benefits of the TAP were straight-forward to estimate. The time saving benefits were put at $8875. The occupational therapist’s time spent traveling to the caregiver’s house, and training the dementia patient and caregiver, was estimated to be $942. Subtracting these costs from the benefits made the net-benefits positive at $7933 (See [ 2 ], chapter 9).

The role of Table 5 is to demonstrate the fact that there already exist many dementia interventions that have been evaluated using CBA and found to be socially worthwhile. Many different methods have been employed to put a price on the effect that was found to be the one most relevant by the evaluator of the intervention.

3.3. Social CBA

To be a social evaluation, the outcome measure for the CBA cannot be specific to the healthcare institutional setting. The outcome measure must consist of the effects on everyone in society. Similarly, on the costs side, the costs of everyone affected by the intervention must be summed, including those who incur the funding for the intervention. The relevant economic concept here is that on an externality, where one person’s activities affects some other person and this effect is unpriced. Therefore, pricing of the effects on others should be an integral part of a social CBA. If the patient is considered the first party, and the physician or hospital supplying the service to the patient is the second party, then the externality involves the effect on third parties.

In health care, the third party is often the person accompanying the patient to receive the service. The full cost is not just what is charged by the healthcare provider, it is the transport costs and the value of the time given up by the person accompanying the patient. The full benefit is also wider than the gain to the patient, as the friend or family member receives satisfaction when the patient ‘s functioning improves. This externality was explicitly priced in the context of the cognitive rehabilitation intervention referred to in Table 5 . The value of the caregiver’s time saved by the TAP constituted the net-benefits of the intervention.

In all the CBAs of the new interventions, the effect was the reduction in dementia symptoms that they produced for the patient, and this led to benefits in terms of either cost savings from increased independent living, or from the value of the QALYs. It is important to understand that when a dementia patient’s symptoms are reduced, this will also mean that the dementia symptoms of the caregiver are also likely to be reduced. This is because the spouses of people with dementia are six times more likely to develop dementia than for persons whose spouses have not experienced dementia [ 12 ]. As a result, any reductions in symptoms by the dementia patient will generate external benefits that need to be added to the direct benefits accruing to the dementia patient.

Therefore, all the net-benefit figures for the new interventions in Table 5 must be interpreted to be conservative under-estimates of how socially worthwhile they actually are. The cost-savings from the greater independent living for the caregivers, and the value of the QALYs that they receive externally by the patient’s reduction in symptoms, must be added to the net-benefits of all the new dementia interventions.

Our conclusion that the net-benefits of dementia economic evaluations would likely be higher when externalities are included is supported by the literature. In a survey of 63 CUAs of Alzheimer interventions by [ 13 ], for 33 of them they were able to compare CEA ratios with and without externalities. Of these, 28 (85%) had CEA ratios that were either more favorable, or cost-saving, when externalities were included. The main externalities related to informal caregivers in terms of costs (time savings) and QALYs increases they received. For the subset of CUAs that used a threshold price, and thus were converted into CBAs, 21 (64%) of them that did include externalities did not cross the threshold to make the net-benefits negative (The threshold prices they used to value the QALYs were $50,000, $100,00 and $150,000).

4. Discussion

4.1. health evaluation nomenclature.

Although the previous sections have tried to draw a clear line of demarcation line between CEA and CUA, and CUA and CBA, and even CBA from an individual perspective and CBA from a social perspective, the healthcare literature is not careful to label its published work distinctly. One has to actually read a published paper to know whether it is a CEA, or a CUA, or a CBA. The title of the evaluation paper may not be at all informative. For example, even the Yunusa et al. paper, which we analyzed in this article, that applied a QALY price threshold to its CUA results to convert them into CBAs, did not entitle their paper a CUA or a CBA, but instead called it a CEA.

4.2. CEA as Cost-Minimization

CEA is most valid, and therefore most useful, if it operates in the context of a fixed quantity of an effect. A CEA would then be a Cost-Minimization (CM) analysis. The outcome of the CEA would identify what combination of resources for an intervention would produce a given effect quantity for the lowest cost. Once this has been determined, CBA can take over and see whether the value of the given effect is greater than the minimum cost combination. As soon as CEA departs from CM by considering also differences in the quantity of effects, and compares this to its differences in costs, it loses its validity. For example, antiretroviral drugs for HIV were the least cost-effective of a number of interventions for HIV in Sub-Saharan Africa [ 14 ]; but, when the effect for ARVs was priced to form the benefits, the benefits for this least cost-effective alternative were greater than the costs [ 15 ].

4.3. CBA and Dementia Interventions

Best practice in CBA is to use a person’s WTP as the price of the effect to estimate the benefits (Costs are usually measured by market prices, with this occasionally adjusted for the extra utility loss to taxpayers for financing the intervention by taxation and other externalities (see [ 1 ], part II). For example, for the US at the federal level [ 16 ], taxes have on average an extra utility loss of 0.245 per dollar of taxes raised (averaged over all the elasticity possibilities), making a total loss of 1.245. Thus, for any government intervention that is funded by taxes, the costs must be multiplied by 1.245 to form the social costs. Similarly, for any intervention that provides tax savings, the savings must be multiplied by 1.245 to obtain its social value. In the case of Medicare eligibility, all the costs and benefits are in terms of funds involving the government. Thus, the net-benefits of $1,754,545 in Table 5 would be $2,184,409 when the gain in utility from the tax savings is included). This method can be employed for CBAs in healthcare generally, but can be problematic for CBAs of dementia interventions, seeing that WTP to pay depends on ability to pay, and persons with dementia are rarely engaged in paid employment. For the new interventions, the CBAs relied on more indirect WTP measures.

For the education and Medicare eligibility interventions, it was the external benefits that were estimated. The reduction in dementia symptoms led to the older persons being able to shift back to independent living, which produced cost-savings for caregivers and the government.

For the hearing aids, corrective lenses and avoiding nursing homes interventions, the reduction in dementia symptoms generated QALYs which was priced by using the VSL, which is a WTP measure. Although the older persons were not working at the time of the evaluation, the VSL estimates were based on the risk of dying/ extra salary choices by the older persons when they were last working (the VSL amounts used were related to persons aged 62). For the quantity of life years part of a QALY, it was the life expectancy of the older persons that was applied. For the quality of life part of a QALY, it was the dementia person’s stated preferences that were used, as measured by the Geriatric Depression Scale (GDS). In the NACC data set, 95 percent of the patients were judged by trained clinicians to be mentally capable of completing the GDS. Thus, for the GDS, it made sense to use the preferences of dementia patients to help estimate the benefits for these three new interventions. Whenever an economic evaluation uses a person’s preferences to estimate the benefits, it incorporates one of the central value judgments of CBA, which is to honor consumer sovereignty, that is, individuals are regarded to be the best judges of their own welfare.

5. Summary and Conclusions

In this article the aim was to highlight the strengths and weaknesses of CEA from a societal perspective as a method of economic evaluation in healthcare. This was carried out in the context of a common, single area of application related to dementia interventions. We started off with a narrow focus, where the effect to be evaluated was restricted just to interventions in terms of dementia symptoms. We then broadened the outcome to consider a comprehensive measure, that of a QALY, that can be adopted for the evaluation of any type of healthcare intervention. Using a QALY converts the CEA into a CUA. Finally, from the perspective of a CBA, which supplies the most valid and general method to use for an economic evaluation, one is not at all limited in the type of effect one employs as long as the effect can be priced.

The applications which we used throughout the analysis concentrated mainly on the interventions that were newly evaluated using CBA and found to be socially worthwhile. These were years of education, Medicare eligibility, hearing aids, corrective lenses, and avoiding living in a nursing home. The data used for these evaluations were recast in order that they could be viewed separately as CEAs, CUAs and CBAs. This enabled the contrast between CEA, CUA and CBA to be fully appreciated. For the CUA part of the analysis, we expanded the range of dementia applications to include FDA-approved medicines. This provided a bridge between CUA and CBA, as not only were QALYs used as the effect of the evaluations, they could also be priced and, in the process, form a special type of CBA. This was because a priced effect is what defines a benefit.

What limited the scope of CUAs from the perspective of CBA generally was that they used a single threshold price that was the same irrespective of the preference of the persons who were actually receiving the benefits of the interventions. When the price of effects was not restricted to a single, threshold price, different methods for estimating the benefits could be employed and this allowed the effects for an intervention to be varied as well. Thus, the list of worthwhile dementia interventions was expanded even further to include the prevention of elder abuse and the provision of cognitive rehabilitation. For CBA evaluations, many different pricing methods can be employed and the two methods we highlighted in this article was in terms of cost savings and the value of a statistical life (Note that although a single VSL amount is adopted, which was Aldy and Viscusi’s $5 million, this does not mean that the valuation of a life is a single price for everyone to whom it is to be applied. This is because, for persons at different ages, the remaining life years varies and this make the valuation of a life year individual specific).

When the effect for the CEA is not a QALY, as when the outcome was considered narrowly to be just the reduction in dementia symptoms, CEA would not be able to be compared with any other healthcare intervention that was not related to dementia. Choices by individuals and by the government in economics are always dependent on opportunity costs. If one does not value alternatives to identify the next best alternative, the opportunity cost of an intervention cannot be determined.

Even when CEA’s contribution in the literature was considered greatest, that is, when non-mutually exclusive interventions were considered, and a budget constraint had been assigned, as an economic evaluation method its role is still very limited, as it is always dependent on the particular alternatives that were identified for comparison purposes. This was because how much of the fixed budget that is used up to finance other alternatives always determines how much is left over to fund the particular intervention one is evaluating. No matter how socially worthwhile an intervention may be, if there are no funds left over to finance it, the intervention will not be approved.

The very existence of a budget constraint can be questioned because it predetermines that something will be funded, even without knowing if any intervention for a specific purpose like dementia was socially worthwhile. More generally, the problem with CEA was that even when funds were available, and an intervention was found to be the most cost-effective one, one still had not accumulated enough evidence to conclude that this low-cost intervention should be approved. An intervention can be cost-effective and not socially worthwhile; or it can be the least cost-effective intervention yet, none-the-less, be socially worthwhile.

On the other hand, whether a budget constraint has been specified (or not) does not limit the use of CBA in any way. When a budget constraint exists, CBA chooses the one with the higher benefit-cost ratio. Without a budget constraint, CBA chooses any alternative with positive net-benefits, as this indicates that this intervention is socially worthwhile.

The other main limitation of CEA relates to its practice. In the economic evaluation literature, it is the costs and effects on the first and second parties to the intervention that are primarily considered. The effects on third parties are usually excluded (This exclusion exists even though there was the recommendation in [ 17 ] that states: “All cost-effectiveness analyses should report 2 reference case analyses: one based on a health care sector perspective and another based on a societal perspective”). We emphasized that to be a social evaluation of an intervention, it is the costs and effects on everyone that have be estimated. Externalities need to be included to ensure that it at least becomes a social CEA evaluation. In the context of dementia interventions, it was mainly the costs and effects of the caregivers of the persons with dementia that was the externality that needed to be included.

The main policy prescription that follows from the analysis in this paper is that, when an evaluation is carried out for an intervention in the healthcare field that involves public expenditures, CBA needs to be used as the evaluation method and not CEA. This is because only CBA ensures that outputs will be valued in monetary terms, and therefore made comparable to the costs, to see which is larger, and thereby determine whether the expenditure is socially worthwhile or not. Also, only a CBA provides a social perspective by including the effects on everyone affected by an intervention both directly and indirectly.

Funding Statement

This research received no external funding.

Conflicts of Interest

The author declares no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Cost-Benefit Analysis, Research Paper Example

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Introduction

In an effort to improve water quality in the Ottawa River, the City of Ottawa is considering options to reduce combined sewer overflows (CSO’s) into the river. Therefore, this issue would appear to present a classic case in which cost-benefit analysis should be used to determine which option maximizes net benefits. It appears the older pipes in the city are combined with the storm water runoff in one pipe which is not able to handle the capacity. When the heavy rain comes the treatment facility cannot handle the load from the older and newer neighborhoods. In order to prevent overflow into the homes of the neighborhoods the overflow is sent into the Ottawa River. Hence, the water quality is severely damaged. The city plans to spend between $40 billion to $2.2 million to eliminate this pollution overflow problem. It is obvious the representation of the adequacy of the elimination of the problems will be in proportion to the amount of money invested. Hence, a cost-benefit analysis would be in the best interest of the city to determine which avenue to determine which option maximizes net benefits. For the purposes of this long term essay I will provide the city with three options or recommendations ranking each with the maximum net benefit proposed. Further I will recommend according to the cost-benefit analysis how it is recommended that the city proceed to eliminate the overflow into the Ottawa River which will in turn take care of the over capacity issue at the water treatment plant. Reducing sewerage discharge will be relied upon non-market methods to estimate monetary values.

“Using the EVRI and the benefits transfer approach appropriately will yield significant time and cost savings as compared to the time and resource intensive process of designing, testing and implementing a new valuation study. Beyond its role in facilitating defensible benefits transfers, the EVRI can assist in the design of new valuation studies since it contains concise, detailed and easily accessed information about the methods and approaches taken in existing valuation studies. In the long run, the EVRI will illustrate the gaps in the body of valuation research with respect to environmental goods and services and different parts of the world.” (“Environmental Value Reference Inventory”). The six basis categories of study for a proper economic evaluation study are:

  • “The study reference which includes the basis bibliographic information.” (“EVRI”).
  • “The study are and population characteristics which includes the basic information of the site location and the population of the site data.” (“EVRI”).
  • “The study methods which include the technical methods to conduct the studies including the specific techniques used to arrive at the data.” (“EVRI”).
  • “The estimated values which include the monetary values as well as the specific units of measures used to arrive at the data of the study.” (“EVRI”)
  • Any alternative summary language which includes the study in various languages such as French, English and Spanish. Some studies are also provided in Dutch and Russian.

Estimations

 

 

 

 

 

Petrie Island  –      West Beach Petrie Island –      East Beaches Petrie Island –      East Bay Britannia Beach Mooney’s Bay Beach Westboro Beach  
TOTAL # of Beach Visitors 11,000 22,000 22,500 12,000 90,000 30,000  
Existing Condition              
Beach closures in 2009 30 20 10 5 10 30  
Benefit lost due to closures in current $ 30,000 42,000 25,000 34,000 70,000 85,000  
Option A              
Expected Beach Closures in 2014 3 3 3 2 3 3  
Benefit lost due to closures in current $ 25000 55000 26000 13000 29000 45000  
               
Option B              
Expected Beach Closures in 2015 1 1 2 1 1 1  
Benefit lost due to closures in current $ 18000 33000 45000 16000 66000 22000  
               
Option C              
Expected Beach Closures in 2060 1 0 1 0 0 0  
Benefit lost due to closures in current $ 0 0 0 0 0 0  
Improvement from Existing Condition

(Benefit for Option C)

             

A discount ratio of 2.5% was used to make the following calculations for cost analysis:

Present Value of Benefit-Cost under Option A

The PV was calculated as follows:

PV = R 0 + R 1 /(1+r) + R 2 /(1+r) 2 +….+ R T /(1+r) T

PV = (Return in Tth period)/(1+r) T

PV for benefit A = Return after 5 years/ (1+0.03) 5

After plugging in the values above here are the results

PV for benefit A = 3.67458.987/(1+0.03) 5

PV for benefit A = $2.278569 million

Option A – PV of Cost = 15 + 15/(1+0.03) +  15/(1+0.03) 2 + 15/(1+0.03) 3 15/(1+0.03) 4

Option A – PV of Cost = $61.8567436 million

Benefit-Cost Ratio =1.98865490/46.60517865

A- Benefit-Cost Ratio = 0.0768906

Present Value of Benefit-Cost under from Option B

PV for benefit B = Return after 5 years/ (1+0.03) 6

PV for benefit B = 254789.729/(1+0.03) 6

PV for benefit B = $4.77867789 million

Assuming that the cost is evenly spread over the six years of implementation, cost per year comes to be $42.8 million (2010-2015).

Option B – PV of Cost = 41.9 + 33.9 /(1+0.03) +  41.9 /(1+0.03) 2 + 41.9 /(1+0.03) 3 + 33.9 /(1+0.03) 4 + 41.9 /(1+0.03) 5

Option B – PV of Cost = 135.2576699 million

B- Benefit-Cost Ratio = 3.14517627 /139.1931549 = 0.039353990

Present Value of Benefit-Cost under Option C

PV for benefit C = Return after 50 years/ (1+0.03) 50

PV for benefit C = 3782640.786/(1+0.03) 50

PV for benefit C = $636,864.6738

Assuming that the cost of $3.8 billion is evenly spread over the fifty years of implementation, cost per year comes to be $41 million (2010-2060).

Option C – PV of Cost = 37+ 44/(1+0.03) +  37/(1+0.03) 2 + 37/(1+0.03) 3 + 37/(1+0.03) 4 +….+ 37/(1+0.03) 50

Let x = 1/(1.03) = 1.01

Using Geometric series summation:

Option C – PV of Cost = 39(1-x (n+1) )/(1-x)

Option C – PV of Cost = 39(1-0.97 (50+1) )/(1-0.97)

Option C – PV of Cost = 1.286079896 billion

C- Benefit-Cost Ratio = 612,864.2289/1166.072905 = 0.000762177

Ranking of options with respect to Benefit-Cost Ratio

Option Benefit-Cost Ratio Rank
A 0.047871559 1
B 0.018753982
C 0.000692162

The Project and Projected Cost-Benefit Analysis

The EVRI and Ottawa River Commission proposed over seventeen different combinations that could reduce the E-coli contamination/pollution in the river by nearly 70%. Following are the three proposals that are likely to be most efficient and successful according to ecologists and economist considering technical applications and cost effective analysis provided by the EVRI in combination of the Environmental Protection Agency.

This proposal entails upgrading the already existing operations through new regulators and the use of automated controls to keep the sewerage control at a constant flow to make water treatment more efficient and effective in the longevity.

The initiative is to reduce storm water overflows that lead to producing surcharge overflows. This system can be used in collaboration with Project 1. Project 1 and Project 5 will cost less than Project 3 and appear to be a more viable technically advanced source for permanent elimination of pollution and over flowage.

The goal is to achieve regulatory compliance issues so that the overflows are controlled during summer months to prevent beach closures due to pollution issues. Not totally sufficient for other seasons of the year because of concentration on the summer months. Only used as a storage area rather than a permanent elimination of pollution.

Discussion of the Cost-Analysis Rankings

Since the original piping and sewer system of the City of Ottawa, Canada was built with a one system piping to handle all waters, sewerage and storm waters there was a need to make separation of the sewerage system. There has since been a separate system of sanitary pipelines to handle the sewerage and storm waters. The problem is that only approximately 63% of the city has undergone such change due to various reasons including costs, inability to make changes due to residency, etc. Government regulations have since required the City of Ottowa to meet certain guidelines according to the of the Environment’s Procedure F-5-5. The most important factor to consider when meeting these guidelines is controlling the amount of overflows into the rivers.

Once Real Time Control (ORAP Project 1) is put in place the City of Ottawa is expected to be in full compliance of the new policy .  Project 3 and 5 present a goal to bring the cities sewerage and non-compliance issue fully into compliance with the numeric criterion set by the province of Canada. This allows a maximum of two overflow events during the swimming season, during the average year.

The following represents the anticipated implementation time for each ranked scenario:

Time to implement programs of cost-benefit analysis plan

Project 1 would entail the combination of an automated sewerage plant and some storage facilities for overflow. Underground storage tanks would be built in order to hold polluted sewerage until it could be treated and then discharged into the rivers. This would prevent overflow into the rivers whilst housing temporary sewer holdings for the sewerage and rain overflow. This would severely prevent beach closure due to pollution. Because forecasters predict a 35% increase in precipitation in the coming year there is a need to do something with this overflow. The bare minimum requirements should be accomplished in time for the upcoming precipitation but there is a long way to accomplish this goal.

Project 5 offers an approximate 45,000 m3 storage facility for sewer system and the overflow to prevent overflows during the wet weather periods of the year. The anticipated storage areas would be sufficient to allow the sewer separation and real time controls to take care of the control of the storm water during the heavy rainfall precipitation months in Canada. Once the waters are sufficiently treated at the sewer systems they can be safely returned back into the Ottawa River. This storage would facilitate the compliance of no more than two overflows per annual year. These storage tanks would be larger than the storage tanks in proposed Project 1. However the combination of Project 1 and Project 5 would facilitate a stronger elimination of sewer problems and overflows to the river due to the technological advances of treating the water and providing overflow protection. The use of advanced automated controls would aid in this development along with the larger storage tanks implemented underground. The disadvantage of this plan is that it does not address the issues of the downtown piping which is over one hundred years old. Some alternative plan needs to be incorporated to tackle this issue; however this will be a costly measure that will take many years to accomplish. The City needs a temporary fix and a short term plan such as a two to five year permanent plan to establish permanent compliance according to policies of the government.

Project 3 is a long term plan that incorporates the neighborhoods and subdivision revisions of piping and sewerage revamping in order to establish new boundaries for elimination of sewerage and overflow problems. This being the most costly plan with the longest time frame of over thirty years is not the most plausible means to help the City of Ottawa with their immediate needs. Some of the anticipated options to consider when revamping the system are:

  • Disconnecting the sewer lines in the city
  • Installation of new sewer lateral lines to homes in the city including streets
  • Sump pumps in the basements are not available for use in all areas
  • Including the use of centrifuges to remove sediment before discharging water into the river

Eventually when completed this would eliminate all overflow issues but there might still be a problem with E-coli unless the water treatment plants are technically advanced such as automation devices. Because this project would take years to complete, there would be a need for a temporary solution where monies would have to be invested in order to accommodate the residents and look towards a future permanent goal. There would be a cost-analysis procured to estimate the return on the investment since the anticipated cost is much greater than the costs associated with the combination of Project 1 and Project 3.

It is in my opinion that a combination of Project 1 and Project 3 would serve the same purpose at a lower cost-analysis and the net return would be much greater in a very lesser period of time hence benefiting the community as well as the residents.

Issues to Consider When Making the Decision

My chosen strategy shows there is much work to be accomplished. Achieving the goals set out here requires the collective support of private and public sectors, voluntary organizations, labor, research centers and academic institutions. “Success depends on the people of Ottawa, who have the skills, resources and creativity to achieve these goals. Ottawa’s leading economic partners include The Ottawa Partnership (TOP), economic agencies (OCRI, OLSC, and OTCA), chambers of commerce, business improvement areas, Ottawa Federation of Agriculture, business and professional associations including cluster groups, and educational institutions. These economic partners already have a track record of collaboration, often with City involvement. Their successful partnerships will be the foundation for new collaborative ventures.” (“Economic Strategy, 2010).

The plan will be implemented with the help of the business, research and planning committees. In any case the goal of the city will be to implement a plan that will be most effective whilst considering the costs associated with such implementation.

The city plans to makes its strategies open to the public to review regularly and ad input. This will be accomplished through monthly meetings and public facilitation of onsite collaboration between engineers and workers. Supervisors plan to take input from the technical advisors.

“The next step is development of tactical plans to implement the Economic Strategy . The progress of all Ottawa 20/20 plans will be assessed every year in a Report Card that will be based on quantitative and qualitative indicators. This will allow all stakeholders to keep a watchful eye on the cumulative effects of change. It will also allow us to determine whether public spending is serving real needs and achieving the desired results. The Ottawa 20/20 plans will be reviewed every five years to assess whether amendments are necessary.” (“Economic Strategy, 2010”).

The city plans to monitor its progress against the progress of other cities that have implemented similar plans and ensure they are on track with the time frame and quality of the work accomplished. They are very positive for accountability of the project.

“Evaluate progress in improving business climate, promoting the rural economy and supporting knowledge and skills development, and by benchmarking Ottawa’s status against similar cities nationally and internationally.” (“Economic Strategy, 2010”).

Performance indicators for data sources will be used to monitor progress Here are the possible indicators:

  • Prosperity: Lower employment rates in the city. Improvements in wages per person and household income. Shareholders should expect healthy returns.
  • Equity/disparity: The gap between the rich and poor should reduce. (based on average household income). “Increase in equity-opportunity, community quality and participation-regardless of where people live. Reduction in the employment gap between foreign-trained professionals and Canadian-born and trained professionals.” (“Economic Strategy, 2010”).
  • Sustainability: The city hopes to employ better educated workers and hopes to make the bottom line larger for the profitability of the city and it’s employed.
  • Quality of life: Health care and affordability of housing should improve in the city.

The City of Ottawa’s Economic Vision

It is the goal of the Economic Strategy to achieve improved opulence for Ottawa through fair and prosperous growth. Prosperity is created through the incorporation of high quality jobs, increased communal and financial equity, and increased investment in the basics that support our economy: people, place and knowledge. The City of Ottawa plans to use its new tools of vision to create a more prosperous and advantageous community for all.

These plans will depend on the public sector, politicians, community hospitals, volunteer organizations as well as universities in and near the city.

Consultants gave rise to the following positive strategies to make this plan happen:

  • “Invest in people and place”
  • “Share knowledge and ideas”
  • “Link innovation to the marketplace”
  • “Strengthen industry clusters and entrepreneurship”
  • “Promote Ottawa to the world” (“Economic Strategy, 2010”).

Ottawa hopes to become ever so competitive in the local community as well as global world and to further attract and retain high-value jobs and companies; to enhance the quality of life of its residents and improve the environment.  Following is a preliminary list from the plan they want to put into action:

Immediate Priority Actions

There is an immediate need to implement the following into the Economic Strategy.

Strategic Direction 1: Invest in people and place

  • There is an immediate need to increase two way communications between businesses, politicians and the residents of the community. [See policy 1.]
  • There is a need to implement a regimented visitation plan where anyone can monitor the progress of the plan. [See policy 1.]
  • Implement the Talent Plan recommendations. [See policies 2, 3 and 7.]

Strategic Direction 2: Share knowledge and ideas

  • There is an immediate need to implement the Broadband Recommendations. [See policies 11, 12 and 13.]

Strategic Direction 3: Link innovation to the marketplace

  • There should be a collaborative plan to link research and technology. [See policy 14.]
  • The incubation capacity should be regularly reviewed and accessed. [See policy 15.]
  • Take a look at business marketing plans and create a way for individual businesses to create their own effective marketing plans with minimal assistance. [See policy 17.]

Strategic Direction 4: Strengthen industry clusters and entrepreneurship

  • Establish and support industry clusters and ensure they are properly maintained. [See policy 18.]
  • Capture more revenue for the local economy by looking at probable supply-chain linkages between the industry clusters and local businesses, and between urban and rural businesses. [See policy 20.]
  • Strengthen vitality of Main Street through use of business retention methods. [See policy 20.]

Strategic Direction 5: Promote Ottawa to the world

  • Promote tourism through domestic and international marketing schemes. [See policies 23 and 25.]
  • Ottawa Congress Center should gain more support from the city and the politicians because of its potential to bring revenue to the city.  [See policy 24.]

Through the use of various technical proposals and the support of the city, politicians, universities, volunteer agencies, etc Ottawa can change its image from a rural city into a new developing suburban city and possible international marketing city with just a few changes. The first issue on the agenda is taking care of the sewerage and overflow issues with regards to rainwater and storm causing over flowage. Next the community must collaborate its efforts and come together to promote the city to where it can be a contender in Canada. There is no need for the city to stay behind times with technology and the essentials such as sewerage and overflow. Change is made through progressive means of communities coming together. Support is gained through marketing schemes and bringing together the people that are most influential in the city. Numbers are important when wanting to make change happen. Change does not come overnight but it can come with preservation and determination. Let’s make Ottawa at the top of its caliber-make change happen!

Environmental Value Reference Inventory (2010) Retrieved April 25, 2010 from, https://www.evri.ca/Other/AboutEVRI.aspx#00

The Environmental Valuation Reference Inventory (EVRI) was developed by P. De Civita, F. Filion and J. Frehs of Environment Canada

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Research on investment evaluation of highway projects based on system dynamics model

  • Yonghua Liu 1 , 
  • Hao Deng 1 , 
  • Hanqi Gao 1 ,  ,  , 
  • 1. Faculty of Transportation Engineering, Kunming University of Science and Technology, Yunnan Kunming 650504, China
  • 2. Yunnan Transportation Research Institute Co., Kunming 650011, China
  • Received: 24 March 2024 Revised: 02 May 2024 Accepted: 27 May 2024 Published: 21 June 2024

MSC : 91-10

  • Full Text(HTML)
  • Download PDF

Aiming at the deficiencies presented by the traditional methods of highway project investment evaluation, the proposed highway investment evaluation method was based on system dynamics. First, we constructed an evaluation index system from profitability, solvency, and risk resistance and clarified the positive and negative causality within the investment evaluation system of highway projects; second, we determined the boundaries of the system dynamics model and divided it into six sub-systems, namely, income, cash flow, investment evaluation, profit, cost, investment and financing, and liabilities; and then, we established the system dynamics model of highway investment evaluation based on the sub-systems. The model made up for the limitations of the traditional discounted cash flow method; finally, taking the China's Yunnan Province an Expressway project as an example, using VENSIM software simulation, we get the evaluation results of the system dynamics model and make a comparative analysis with the discounted cash flow method, which showed that the calculation inaccuracies of the NPV and other financial indicators were in a reasonable range, and the evaluation method had strong operability and practicability. The system dynamics investment evaluation model provided a systematic, intuitive, whole-process investment evaluation method, which provided a theoretical basis for the analysis and decision-making of the investment effect of highway projects.

  • transportation economics ,
  • investment appraisal ,
  • system dynamics ,
  • discounted cash flow approach

Citation: Yonghua Liu, Hao Deng, Hanqi Gao, Wei Ni. Research on investment evaluation of highway projects based on system dynamics model[J]. AIMS Mathematics, 2024, 9(8): 20326-20349. doi: 10.3934/math.2024989

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[1]
[2] , (2016), 1−161. --> Editorial Board of China Journal of Highway, Review of Academic Research on Transportation Engineering in China 2016, , (2016), 1−161.
[3] , 2019, 77−78. --> H. Huang, Discussion of the national toll road statistical bulletin from a financial perspective, , 2019, 77−78.
[4] , (2024), 4161−4177. https://doi.org/10.3934/math.2024204 --> Y. H. Liu, R. K. Duan, K. Shen, Q. X. Luan, H. Q. Gao, H. Deng, An investigation into the determinants of satisfaction concerning varied toll policies on highways using the random forest model, , (2024), 4161−4177. https://doi.org/10.3934/math.2024204 doi:
[5] , (2021), 446−467. https://doi.org/10.1080/09654313.2020.1742665 --> T. Machiels, T. Compernolle, T. Coppens, Real option applications in megaproject planning: Trends, relevance and research gaps: A literature review, , (2021), 446−467. https://doi.org/10.1080/09654313.2020.1742665 doi:
[6] , (2017), 7−11. --> X. Y. Cai, G. G. Zhou, Option value analysis of revenue adjustment in operation period of toll road PPP project, , (2017), 7−11.
[7] , (2015), 1104−1110. --> Y. Wang, L. Ma, J. Bai, Evaluation of financial risk control of large-scale international projects based on neural network, , (2015), 1104−1110.
[8] , (2019), 9−16. --> L. Li, An empirical study on the rational selection of comprehensive line solution diagram and calculation period for economic evaluation of construction projects, , (2019), 9−16.
[9] , (2017), 124−127. --> X. Liu, R. X. Zhou, Y. Zhan, Research on project investment evaluation index based on interval number, , (2017), 124−127.
[10] , (2014), 83−105. https://doi.org/10.1080/21680566.2014.916236 --> S. P. Shepherd, A review of system dynamics models applied in transportation, , (2014), 83−105. https://doi.org/10.1080/21680566.2014.916236 doi:
[11] , (2017), 57−61. --> Q. N. Liu, Y. W. Wang, M. L. Yao, J. Li, Research on the evolution and simulation of operational risk of PPP project based on system dynamics, , (2017), 57−61.
[12] , (2020), 765−771. --> Z. Y. Zhao, S. Fan, T. Dai, Application of system dynamics model for value-for-money evaluation of PPP projects, J. Huaqiao Univ. , (2020), 765−771.
[13] , 2019,171−176. --> C. C. Xue, J. K. Zhou, System dynamics modeling and analysis of PPP project performance–A highway as an example, , 2019,171−176.
[14] , (2024), 1227−1247. https://doi.org/10.3934/math.2024061 --> W. Xu, J. J. Liu, J. M. Li, H. Wang, Q. T. Xiao, A novel hybrid intelligent model for molten iron temperature forecasting based on machine learning, , (2024), 1227−1247. https://doi.org/10.3934/math.2024061 doi:
[15] , (2018), 2980−2987. --> F. L. Feng, N. Yu, Research on pack back transportation tariff based on system dynamics and logit model, , (2018), 2980−2987.
[16] , (2024), 78−89. --> P. D. Chao, L. Y. Zhou, Y. F. Kang, Simulation analysis of transportation restructuring policy based on system dynamics, , (2024), 78−89.
[17] , (2022), 81−88. --> Z. W. Wang, Z. Y. Xiang, X. Liu, Research on urban traffic congestion management strategy based on system dynamics model, J. Changsha Univ. , (2022), 81−88.
[18] , (2023), 103978. https://doi.org/10.1016/j.trd.2023.103978 --> R. Pokharel, E. J. Miller, K. Chapple, Modeling car dependency and policies towards sustainable mobility: A system dynamics approach, , (2023), 103978. https://doi.org/10.1016/j.trd.2023.103978 doi:
[19] , (2023), 103013. https://doi.org/10.1016/j.tre.2022.103013 --> X. F. Lai, Z. X. Chen, X. Wang, C. H. Chiu, Risk propagation and mitigation mechanisms of disruption and trade risks for a global production network, , (2023), 103013. https://doi.org/10.1016/j.tre.2022.103013 doi:
[20] , China Planning Press, 2010. --> Institute of Standards and Quotas, Ministry of Housing and Urban-Rural Development, Institute of Planning and Research, Ministry of Transportation, , China Planning Press, 2010.
[21]
  • This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ -->

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  • Figure 2.1. Causal feedback loops for major factors
  • Figure 2.2. Flow chart of the investment appraisal system for highway projects
  • Figure 3.1. Project toll revenue simulation
  • Figure 3.2. Simulation of total project income
  • Figure 3.3. Simulation of project operating costs
  • Figure 3.4. Simulation of project financial costs
  • Figure 3.5. Simulation of total project costs and expenses
  • Figure 3.6. Total project costs and expenses vs. total revenue
  • Figure 3.7. Simulation of project net profit
  • Figure 3.8. Simulation of project cash inflows and outflows
  • Figure 3.9. Project net cash flow after tax
  • Figure 3.10. Simulation of the cumulative after-tax net present value of the project
  • Figure 3.11. Simulation of project ROA, ROI, and ROE
  • Figure 3.12. Project ICR simulation
  • Figure 3.13. Project DSCR simulation
  • Figure 3.14. Project LOAR simulation
  • Figure 3.15. Sensitivity analysis of toll revenue
  • Figure 3.16. Operating cost sensitivity analysis
  • Figure 3.17. Mixed-factor sensitivity analysis
  • Figure 3.18. Cumulative NPV simulation for extended toll periods
  • Figure 3.19. After-tax net cash flow inaccuracy analysis
  • Figure 3.20. Cumulative after-tax NPV inaccuracy analysis
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