scholarly journals Appropriate Discounting for Benefit-Cost Analysis

2011 ◽  
Vol 2 (2) ◽  
pp. 1-20 ◽  
Author(s):  
David F. Burgess ◽  
Richard O. Zerbe
Keyword(s):  
Cost Analysis ◽  
Discount Rate ◽  
Cost Of Capital ◽  
Hyperbolic Discounting ◽  
Ease Of Use ◽  
Benefit Cost Analysis ◽  
The Social ◽  
Net Benefits ◽  
Benefit Cost

In order to be sensible about what discount rate to use one must be clear about its purpose. We suggest that its purpose is to help select those projects that will contribute more net benefits than some other discount rate. This approach, which is after all the foundation for benefit-cost analysis, helps to reconcile different suggested procedures for determining the discount rate. We suggest that the social opportunity cost of capital (SOC) is superior to other suggested approaches in its generality and its ease of use. We use the SOC to determine a range of real rates that vary between 6% and 8%. We suggest that approaches based on determination of preferences, which result in hyperbolic discounting, are less appropriate and less useful.

Accounting for the Distribution of Benefits and Costs in Benefit–Cost Analysis

2020 ◽  
pp. 1-21
Author(s):  
James K. Hammitt
Keyword(s):  
Cost Analysis ◽  
Decision Makers ◽  
Policy Choice ◽  
Alternative Evaluation ◽  
Benefit Cost Analysis ◽  
Transfer Programs ◽  
Net Benefits ◽  
Benefit Cost ◽  
Benefits And Costs

Abstract Benefit–cost analysis (BCA) is often viewed as measuring the efficiency of a policy independent of the distribution of its consequences. The role of distributional effects on policy choice is disputed; either: (a) the policy that maximizes net benefits should be selected and distributional concerns should be addressed through other measures, such as tax and transfer programs or (b) BCA should be supplemented with distributional analysis and decision-makers should weigh efficiency and distribution in policy choice. The separation of efficiency and distribution is misleading. The measure of efficiency depends on the numéraire chosen for the analysis, whether monetary values or some other good (unless individuals have the same rates of substitution between them). The choice of numéraire is not neutral; it can affect the ranking of policies by calculated net benefits. Alternative evaluation methods, such as BCA using a different numéraire, weighted BCA, or a social welfare function (SWF), may better integrate concerns about distribution and efficiency. The most appropriate numéraire, distributional weights, or SWFs cannot be measured or statistically estimated; it is a normative choice.

Benefit-Cost Analysis for Financial Regulation

2013 ◽  
Vol 103 (3) ◽  
pp. 393-397 ◽  
Author(s):  
Eric Posner ◽  
E. Glen Weyl
Keyword(s):  
Cost Analysis ◽  
Financial Markets ◽  
Financial Regulation ◽  
Allocative Efficiency ◽  
Social Value ◽  
Wall Street ◽  
Benefit Cost Analysis ◽  
The Social ◽  
Benefit Cost ◽  
Rule Making

Calls for benefit-cost analysis in rule-making, based on the Dodd-Frank Wall Street Reform Act, have revealed a paucity of work on allocative efficiency in financial markets. We propose three principles to help fill this gap. First, we highlight the need for quantifying the statistical cost of a crisis to trade off the risk of a crisis against loss of growth during good times. Second, we propose a framework quantifying the social value of price discovery, and highlighting which arbitrages are over- and under-supplied from a social perspective. Finally, we distinguish between insurance benefits and gambling-facilitation harms of market completion.

scholarly journals The Social Cost of Carbon, Greenhouse Gas Policies, and Politicized Benefit/Cost Analysis

2018 ◽  
Vol 6 (1) ◽  
pp. 59-76
Author(s):  
Benjamin Zycher
Keyword(s):  
Cost Analysis ◽  
Social Cost ◽  
Climate Impacts ◽  
Cost Calculation ◽  
Substantial Part ◽  
Social Cost Of Carbon ◽  
Benefit Cost Analysis ◽  
Climate Policies ◽  
The Social ◽  
Benefit Cost

Benefit/cost analysis can be a powerful tool for examination of proposed (or alternative) public policies, but, unsurprisingly, decisionmakers’ policy preferences can drive the analysis, rather than the reverse. That is the reality with respect to the Obama Administration computation of the social cost of carbon, a crucial parameter underlying the quantitative analysis of its proposed climate policies, now being reversed in substantial part by the Trump Administration. The Obama analysis of the social cost of carbon suffered from four central problems: the use of global benefits in the benefit/cost calculation, the failure to apply a 7% discount rate as required by Office of Management and Budget guidelines, the conflation of climate and GDP effects of climate policies, and the inclusion of non-climate effects of climate policies as co-benefits, as a tool with which to overcome the trivial temperature and other climate impacts of those policies. Moreover, the Obama analysis included in its “market failure” analysis the fuel price parameter that market forces are likely to incorporate fully. This Article suggests that policymakers and other interested parties would be wise to concentrate on the analytic minutia underlying policy proposals because policy analysis cannot be separated from politics.

scholarly journals Benefit–Cost Analysis of an Innovative Program for Self-Sufficiency and Homeownership

2019 ◽  
Vol 43 (1-2) ◽  
pp. 3-40
Author(s):  
George C. Galster ◽  
Anna Maria Santiago ◽  
Richard J. Smith ◽  
Joffre Leroux
Keyword(s):  
Cost Analysis ◽  
Home Ownership ◽  
Social Benefit ◽  
Model Specification ◽  
Parameter Estimates ◽  
Housing Subsidy ◽  
Benefit Cost Analysis ◽  
Quasi Experimental ◽  
Net Benefits ◽  
Benefit Cost

Background: Federal policy has increasingly sought to build financial capability, earnings, and assets of subsidized housing recipients. Objective: We conduct a benefit–cost analysis of the Denver Housing Authority’s (DHA) innovative Home Ownership Program (HOP), which incentivizes participants to increase earnings, build wealth, and purchase homes. Research design, subjects, and measures: In assessing HOP participant benefits (earnings, home-buying, and positive exits from DHA), we use parameter estimates from quasi-experimental methods (i.e., propensity score matching) that permit drawing causal inferences of program impacts. Impact estimates are robust to alternate model specification and mostly insensitive to omitted variable bias found in the social sciences. We deploy a comprehensive accounting framework, distinguishing benefits and costs accruing to program participants, nonparticipants (other citizens, taxpayers, and governments), and society as a whole. We use Monte Carlo simulation techniques to approximate distributions of benefit and cost parameters, thereby ascertaining how reliably participation in HOP yielded net benefits compared to if families had continued to receive housing assistance during the same period. Results: We estimate a net social benefit from HOP of US$6,015 per participant. The simulated standard deviation was only a third of this value and 99.9% of simulations returned positive net social benefits. Conclusion: We conclude with a high degree of statistical confidence that HOP produced substantial net benefits to society as a whole, program participants, and nonparticipants alike. HOP offers strong potential for poverty alleviation among housing subsidy recipients and should be replicated.

Developing Theoretical Foundations of DfM

2000 ◽  
Author(s):  
Jami J. Shah ◽  
Paul K. Wright
Keyword(s):  
Cost Analysis ◽  
Computational Cost ◽  
Ease Of Use ◽  
Value Engineering ◽  
Benefit Cost Analysis ◽  
Trade Offs ◽  
Function Domain ◽  
Market Factors ◽  
Benefit Cost ◽  
Theoretical Foundations

Abstract This work is motivated by a desire to put DfM on solid theoretical foundations. The paper evaluates measures of manufacturability and classes of DfM methods and frameworks independent of the specific manufacturing processes. Criteria used in evaluation include theoretical foundation, accuracy, flexibility in choosing utility/objective function, domain independence, ease of use, level and extent of information required, computational cost, ability to incorporate uncertainty and market factors. We introduce a DfM approach based on Benefit/Cost analysis. All design utilities are lumped into a single “Design Benefit (RD)”, all manufacturability factors into another parameter “Manufacturing Rating (RM)”, and then techniques of benefit-cost analysis and value engineering are used to make decisions about design improvements. Use of overall and marginal DfM ratings allows trade-offs to be made. Any set of desired objectives can be used for computing the ratings. It is also possible to incorporate design or manufacturing constraints.

Sign in / Sign up

Export Citation Format

Share Document