Cost-benefit analysis and cost-effectiveness analysis are two approaches that sound the same, operate similarly, have similar goals, and are often referred to interchangeably. Despite what these two techniques have in common, they are indeed two distinct techniques that ask different questions and have different approaches to evaluating the efficiency of a program.
At the most fundamental level, cost-benefit analysis and cost-effectiveness analysis are centered on two different questions. While cost-benefit analysis asks whether the economic benefits outweigh the economic costs of a given policy, cost-effectiveness analysis is focused on the question of how much it costs to get a certain amount of output from a policy. Formulas to calculate the two are listed below.
Cost-benefit = Benefits ($) - Costs ($) (AKA “net benefits”)
OR
Cost-benefit = Benefits ($) / Costs ($) (AKA “benefit ratio”)
Cost-effectiveness = Costs ($) / Outcome
Let’s put this into practice. Say an analyst is conducting a policy analysis on a proposal to expand a school district’s preschool education program by opening free slots for children from low-income families. What would this analysis look like if it focused on cost-benefit outcomes versus cost-effectiveness outcomes?
A cost-benefit analysis would attempt to collate all the benefits of the program such as future labor market earnings benefits for participants, improved health benefits, reductions in crime, and reduction in future social spending, and compare that to program costs and other costs of the program, for instance the potential for increased public-sector spending on higher education. The analyst would then convert all these benefits to dollar figures and then estimate the dollar value of benefits compared to costs as a ratio or difference depending on client needs.
A cost-effectiveness analysis, on the other hand, would focus on a given outcome and see how much spending is needed to bring about that outcome. For instance, if the preschool program was focused on trying to increase high school graduation rates, an analyst could estimate how much would need to be spent on the program, given what we know about how preschool participation impacts high school graduation rates, in order to cause one new person to graduate who would not otherwise. This cost could then be measured against other interventions to improve high school graduation rates to assess how cost-effective opening preschool slots is for improving graduation rates compared to other options the school district may have.
Looking at this example, you can start to see some of the advantages and disadvantages of using one technique versus the other. Cost-benefit analysis is usually considered a more comprehensive analytical technique since the process of monetization (converting all costs and benefits to dollars figures) converts all costs and benefits into a common currency, namely economic benefit.
The drawback of monetization is that it can sometimes fail to give information to policymakers that is all that useful for them. Policymakers are usually interested in outcomes besides economic efficiency, making cost-benefit analysis at best only partially informative to them. Thus, cost-effectiveness analysis can be a good tool for zeroing in on one outcome and comparing alternatives of greater or less cost-effectiveness against one another. The drawback of this strategy, of course, is that it can set you up to leave out “side benefits” that policymakers may also be interested in. For instance, more preschool slots may not be the most cost-effective way to improve graduation rates, but maybe a policymaker would be willing to choose a less cost-effective graduation rate improving program if it had future earnings and crime reduction benefits that other programs didn’t.
Overall, both approaches are powerful tools for a policy analyst, and need to be deployed strategically depending on the client and the project. Because after all, these methodologies are only tools, which means they’re only as good as they are useful for their purpose, which is generating better information for more informed policymaking.