Rough Guide to Impact Evaluation of Environmental and Development Programs
By Subhrendu K Pattanayak
This paper is a “rough guide” for evaluation of programs, projects and policies in the environment and development arena.
First, a general overview of the what, how, and why of program evaluation, with particular emphasis on the role of control groups, pre and post measurement, and covariate data to define counterfactual scenarios (including formal definition of all terms) are provided.
Second, a detailed review with examples of the four main methods for evaluation – randomized experiments, natural experiments, matching methods, and panel-based DID estimators with a description of the pros and cons of each method is given.
Finally, the econometric evaluations within the broader context is placed– how can we move beyond estimation of average treatment effects; what do we do under time, resource and data constraints; and when and where should we rely on theory-based evaluations.
Keywords: evaluation, environment, development area, econometric, natural and quasi experiments, resource, data constraints, data, theory, DID estimators, south asia,
URL: http://d.repec.org/n?u=RePEc:ess:wpaper:id:2187&r=dev
This paper is a “rough guide” for evaluation of programs, projects and policies in the environment and development arena.
First, a general overview of the what, how, and why of program evaluation, with particular emphasis on the role of control groups, pre and post measurement, and covariate data to define counterfactual scenarios (including formal definition of all terms) are provided.
Second, a detailed review with examples of the four main methods for evaluation – randomized experiments, natural experiments, matching methods, and panel-based DID estimators with a description of the pros and cons of each method is given.
Finally, the econometric evaluations within the broader context is placed– how can we move beyond estimation of average treatment effects; what do we do under time, resource and data constraints; and when and where should we rely on theory-based evaluations.
Keywords: evaluation, environment, development area, econometric, natural and quasi experiments, resource, data constraints, data, theory, DID estimators, south asia,
URL: http://d.repec.org/n?u=RePEc:ess:wpaper:id:2187&r=dev