A META-ANALYSIS OF COST-BENEFIT ANALYSIS OUTCOMES IN INFRASTRUCTURE PROJECTS: EVIDENCE FROM TRANSPORT AND UTILITY SECTORS IN DEVELOPING ECONOMIES

Abstract

This meta-analysis evaluates the effectiveness, consistency, and methodological rigor of cost-benefit analysis (CBA) outcomes in infrastructure projects across developing economies, with a focus on transport and utility sectors. As public and donor investment in infrastructure continues to be positioned as a catalyst for economic growth, service delivery, and poverty alleviation, there is a critical need to assess whether existing CBAs accurately reflect the true value and feasibility of such projects. Drawing on 112 empirical studies and project evaluation reports published between 2000 and 2024, this study applies a random-effects meta-analytical framework to synthesize standardized performance indicators—Benefit-Cost Ratio (BCR), Net Present Value (NPV), and Internal Rate of Return (IRR). These indicators were extracted from peer-reviewed journal articles, multilateral development bank appraisals, and governmental reports, and were coded alongside contextual moderators such as project type, region, evaluator identity, and methodological quality. The aggregated findings indicate a strong positive effect size across the dataset, with a weighted mean BCR above 2.0, demonstrating that infrastructure investments in both sectors generally yield substantial net social and economic returns. Transport projects, particularly road rehabilitation and urban transit systems, showed higher consistency and narrower effect size variance compared to utility projects. This can be attributed to the transport sector’s reliance on standardized metrics such as travel time savings, fuel efficiency, and accident reduction—benefits that are more easily quantifiable within traditional economic models. In contrast, utility infrastructure projects—encompassing water, sanitation, and electricity systems—displayed greater variability in outcomes due to their dependence on non-market benefit estimation techniques such as willingness-to-pay, avoided cost methods, and contingent valuation. These projects often generated high returns when including health, environmental, and time-use benefits, but their effectiveness was highly sensitive to assumptions regarding user uptake, service reliability, and behavioral change. Another key finding concerns the impact of evaluator identity on CBA credibility. CBAs conducted or supervised by multilateral agencies exhibited greater methodological rigor, transparency in assumptions, and consistent use of sensitivity analysis compared to those produced by national or local governments. Donor-driven evaluations were more likely to apply conservative estimates and conduct thorough risk assessments, thereby reducing the risk of optimism bias. Regional trends also emerged, with Sub-Saharan Africa and South Asia showing higher average BCRs in well-targeted infrastructure projects. However, the analysis also uncovered persistent theoretical ambiguities related to discount rate selection, the valuation of intangible benefits, and the inadequate treatment of uncertainty, revealing systemic gaps in current CBA practices.