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Economic Rates of Return

Accountability and transparency are key principles of MCC’s evidence-based approach to reducing poverty through economic growth. Economic Rates of Return (ERRs) provide a single metric showing how a project’s economic benefits compare to its costs. MCC requires that its projects' ERRs pass a 10 percent hurdle rate to be considered for investment. MCC makes all ERR analyses available via interactive, downloadable spreadsheets. These spreadsheets are unique to a project or activity as defined within a compact, or to a set of closely related interventions with the same benefit stream.

Each spreadsheet includes:

  • A description of the project, including its economic rationale;
  • The expected impacts, including detailed cost and benefit estimates;
  • A tool allowing users to modify key assumptions and study the effects of those modifications on the project’s returns.
Some familiarity with cost-benefit analysis is essential to using these spreadsheets.

What is an Economic Rate of Return (ERR)?

An ERR provides a convenient metric, produced from a cost-benefit analysis, that compares the economic costs and benefits of a program. In MCC’s cost-benefit analyses, the costs of a project include all necessary economic costs—financial expenses covered by MCC and other parties, as well as opportunity costs of non-financial resources expended. Benefits include the increased income of a country’s population or the increased value-added generated by producers (firms and households) that can be attributed to the proposed project. [Value-added is defined as the value of gross production (or sales) minus the cost of intermediate inputs produced (and purchased from) outside the firm.]

Calculating ERRs

MCC’s methodology for cost-benefit analysis, which produces an ERR metric, is best described as micro-economic growth analysis, which captures the expected increases in local incomes. This analysis includes income or value-added that is expected to be generated through environmental and social improvements, such as the effect of clean water on health outcomes for improved female educational attainment on incomes. However, it does not incorporate the non-income related value of environmental and social improvements, given MCC’s mission.

Every ERR calculation considers two scenarios:

  • The expected outcome with the project; and
  • The expected outcome without the project.

Scenario 1: Expected Outcome with Project

This scenario reflects the increases in income or value-added generated by the proposed program, as well as the full costs related to the program.

Scenario 2: Expected Outcome without Project

The second scenario, called the counterfactual, reflects an estimate of what is likely to happen in the future if the project does not take place. While this may be considered a "status quo" scenario, the estimation of future economic outcomes without the project also accounts for dynamic trends. For example, a growing economy would be expected to continue on its recent (or projected) growth trajectory without the project, and private investments would likely be made.  In other cases, investments could be expected to decline in the counterfactual, for example if electrical outages would be expected to increase without the project.

Economic analysis compares the difference in incomes or value-added between the two scenarios, factoring in the timing of accrued costs and benefits. Since the value of a benefit accruing to people sooner is greater than the value of the same benefit accruing later, benefits and costs are discounted over time. The ERR is expressed in percentage terms and represents the rate at which benefits equal costs after discounting. Investments meeting MCC’s hurdle ERR of 10 percent, a common discount factor for development projects, are those for which benefits are at least as high as costs after adjusting for the time value of money. Projects that are likely to generate larger increases in household incomes per dollar invested will have higher ERRs.

MCC models incorporate the best information available at the time regarding core parameters. Nonetheless, projections of future economic activity for both scenarios must account for uncertainty. MCC conducts sensitivity analysis on its ERRs using a range of plausible values on the major variables that drive the results. ERRs represent MCC’s best estimate of the expected economic returns of the project, while the sensitivity analysis captures the potential range of those outcomes.

Pre-Investment Cost-Benefit Analysis and Closeout ERRs

Conducting cost-benefit analysis of a proposed MCC project prior to investment decision entails making a forecast of its likely economic impact and its costs. The resulting ERR provides a measure of its cost-benefit relationship to inform investment decisions. MCC’s pre-investment ERRs represent the agency's best estimate given the data and evidence available at that stage.

In addition to producing these ex-ante ERRs, MCC began computing revised ERRs upon compact closeout in 2011, called “closeout ERRs.” These ERRs provide an estimate of a project’s cost-benefit relationship based upon the information available at the time of closeout, when MCC’s costs and some indicators of benefits are known. Closeout ERRs are still forecasts, given that for many projects benefits do not start until after compact closeout, and these benefits can continue for 20 years or more. Moreover, impact evaluation findings, which provide a measure of the degree of any project impact to date, are typically not available at the time of closeout ERR estimation. Closeout ERRs are thus distinct from an ERR based on measured benefits resulting from the MCC’s projects (see “Evaluation-Based ERRs” below).

Evaluation-Based ERRs

All MCC projects are independently evaluated, and these independent evaluations often include evaluation-based ERRs. Independently calculated ERRs complement the closeout ERRs that MCC calculates at the end of the compact. Because independent evaluations occur two to five years after compact closure, evaluation-based ERRs offer an updated assessment of a project’s costs and benefits post-compact. These ERRs still rely on forecasts for the later portion of MCC’s CBA evaluation horizon, which spans 20 years. Nonetheless, independent evaluation-based ERRs complete the accountability loop in a way that is rare among donors. Two examples are below.

Results of the Mozambique Farmer Income Support Project

MCC’s Farmer Income Support Project (FISP) was designed to reduce damage to the incomes of 1.7 million Mozambican farmers due to Coconut Lethal Yellowing Disease (CLYD). This was to be accomplished through (i) short term surveillance, control and mitigation services, prompt eradication of diseased palms, and replanting with the less susceptible Mozambican Green Tall coconut variety, and (ii) Technical advisory services to introduce crop diversification options. Based on estimated benefits to farmers’ incomes and the costs of the program, MCC originally forecast a project economic rate of return of 25.1 percent.

An independent evaluation of the FISP project’s impacts found that cutting trees and burning tree stumps in epidemic areas did reduce CLYD prevalence though not to the degree originally forecast, resulting in lower-than-expected productivity impacts. Likewise, alternative crop uptake in endemic areas was lower than expected, likely due to insufficient input and output market linkages. The resulting updated, evaluation-based ERR estimate was 16.8 percent. Greater detail on the evaluation and lessons learned are available in MCC’s public Evaluation Catalog.

Results of the Nicaragua Transportation Project

MCC’s Nicaragua Transportation Project was designed to stimulate economic development and improve access to markets and social services by reducing transportation costs. It upgraded and rehabilitated 68 kilometers of roads, consisting of two secondary roads and a trunk road. MCC originally forecast an economic return from the project of 13.2 percent based on reduced vehicle operating costs and travel time savings for road users, including new users expected to travel on the road due to improved road conditions resulting from the project.

The independent evaluation of this project estimated actual impacts using data from two years after the roads were completed. It found that the road roughness, a key indicator of transport costs, decreased 80 percent on average, and traffic increased 12 percent on average over the two years to 3,062 vehicles per day. At the same time, the capital costs for the road works came in on average 2.2 times those estimated prior to implementation. Given this balance of measured benefits and costs, the resulting evaluation-based ERR fell to 2.1 percent, primarily due to these higher costs. (Benefits were roughly consistent with ex-ante estimates.) Greater detail on the evaluation and lessons learned are available in MCC’s public Evaluation Catalog, and recently published Principles into Practice: Lessons from MCC’s Investments in Roads.

Other Inputs to Investment Decisions

Although economic returns are a key decision variable for MCC, the agency takes many factors into consideration when making its decisions to approve compact investments. MCC expects that programs will generate adequate benefit streams to justify the investment of resources. MCC also conducts a Beneficiary Analysis to assess whether its investments will deliver benefits to the poor. At the same time, MCC values country ownership and places a premium on supporting initiatives that enjoy broad support in the country and that are developed through a consultative process. It also examines whether the program proposal is consistent with MCC policies and guidelines on gender, the environment, and procurement procedures, among others. Finally, MCC analyzes each investment to determine its sustainability—i.e., the degree to which benefits are likely to be sustained, or the degree to which costs (including potential environmental costs) may grow.

These spreadsheets provide a window into the assessment of economic impact used by MCC in its consideration of a proposed project. MCC understands that key parameters will change over time, and project design may be revised during implementation. When project designs or model parameters change significantly, MCC may revise these models; updated information will be posted here as it becomes available.

What the spreadsheet data represent:

  • An overall impact estimate. The spreadsheets provide MCC’s best pre-investment estimate of the likely economic impact of the project and form the basis for monitoring and evaluation efforts.
  • Estimated benefits. The spreadsheets estimate the expected increases in either incomes or value-added of individuals, households, firms or sectors of economic activity.
  • A counterfactual scenario. Potential benefits are compared against what is likely to happen without the project (e.g., a growing economy would be expected to continue growing, even without the project).
  • A snapshot in time. The spreadsheets reflect the best data available to MCC at the time the project was approved for investment.

What the spreadsheet data do not represent:

  • The sole reason for an investment decision. Although ERRs are an integral part of MCC’s decision-making process, other factors are considered when MCC decides whether to undertake a project.
  • A detailed beneficiary analysisThe ERR spreadsheets portray the overall economic impact of a project rather than apportioning the income gains along various demographic dimensions.
  • Up-to-the-minute information for projects in implementation. Many of the parameters that are used in these pre-investment estimates change over time, so ERRs may not reflect the actual implementation experience. When project designs or model parameters change significantly, MCC may revise these models; updated information will be posted as it becomes available.

Country Spreadsheets

Country Program Spreadsheet
Armenia Compact
Benin Compact
Burkina Faso Compact
Cabo Verde Compact
Cabo Verde Compact II
El Salvador Compact
Georgia Compact
Georgia Compact II
Ghana Compact
Honduras Compact
Indonesia Compact
Jordan Compact
Lesotho Compact
Madagascar Compact
Malawi Compact
Mali Compact
Moldova Compact
Mongolia Compact
Morocco Compact
Mozambique Compact
Namibia Compact
Nicaragua Compact
Philippines Compact
Senegal Compact
Tanzania Compact
Vanuatu Compact
Zambia Compact