Kenya<sup>85</sup> considers a behavioral economics model in which some farmers are patient and others procrastinate, to rationalize low investment in fertilizer in the face of high returns to its use. A study of microfinance in Thailand<sup>86</sup> uses a structural model of entrepreneurship to explain why credit provision can have highly heterogenous impacts on subsequent investment. A later RCT of a microfinance program in India confirms precisely this pattern of response across beneficiaries.<sup>87</sup>

- **Structural modeling also enables researchers to predict the impact of hypothetical policies that have yet to be implemented.** A study<sup>88</sup> of Mexico’s celebrated PROGRESA conditional cash transfer program uses a dynamic decision‐making model to show that an alternative subsidy scheme could generate greater schooling impact at similar cost to the existing program.  In the Thailand microfinance study, a counterfactual policy of providing credit explicitly tied to investment is found to substantially outperform the actual policy of unconditional credit provision.

- **Finally, a tight link to theory can allow researchers to go beyond cost‐benefit analysis and make quantitative welfare statements, identifying winners and losers from a policy (or a range of alternative policies) and the magnitudes of these gains or losses.** In the Kenya study, the authors use the structural model to show that small and time‐limited fertilizer subsidies can lead to higher social welfare compared to heavy subsidies or no subsidies at all.  The Thai study shows that large‐ scale credit provision is not a cost‐effective policy on average; although some households value the added liquidity substantially more than it costs to provide, many more value it very little.

The World Bank, as well as many governments and large NGOs, now insist on evaluations – often in the form of RCTs – wherever feasible. Many World Bank researchers regularly use these methods and a specialized unit named DIME was set up to facilitate impact evaluations within World Bank projects. However, not all development policies or programs can be evaluated with RCTs. For example, policies that affect the whole of the economy or an entire market, like a minimum wage regulation, are not amenable to RCTs. To identify causal effects of market‐level policies, researchers rely on non‐experimental methods such as difference‐in‐differences – e.g., comparing employment changes in border‐counties across lines of U.S. states with and without minimum wage hikes – and regression‐discontinuity – e.g., comparing employment rates among individuals just below the age threshold to qualify for the minimum wage in Denmark to those just above it.<sup>89</sup> In the developing country context, a difference‐in‐differences strategy was used to study the labor market consequences of a massive school construction program in Indonesia by comparing cohorts that would

> 85 Duflo, E., M. Kremer, and J. Robinson. 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya." _American Economic Review_ , 101 (6):2350‐90.

> 86 Kaboski, J., and R. Townsend, 2011. "A Structural Evaluation of a Large‐Scale Quasi‐Experimental Microfinance Initiative." _Econometrica_ , 79: 1357‐1406.

> 87 Banerjee, A., E. Duflo, R. Glennerster, and C. Kinnan. 2015. "The Miracle of Microfinance? Evidence from a Randomized Evaluation." _American Economic Journal: Applied Economics,_ 7 (1): 22‐53.

> 88 Todd, P., and K. Wolpin. 2006. "Assessing the Impact of a School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility." _American Economic Review_ , 96 (5): 1384‐1417.

> 89 Card, D., and A. Krueger, 1994. "Minimum Wages and Employment: A Case Study of the Fast‐Food Industry in New Jersey and Pennsylvania," American Economic Review 84(4): 772‐793 and Kreiner, C., D. Reck, and P. Skov. Forthcoming. "Do Lower Minimum Wages for Young Workers Raise Their Employment? Evidence from a Danish Discontinuity" _Review of Economics and Statistics_ .

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