Abstract
A government sets up a scheme for extending microcredit to farmers; or builds an irrigation canal; or provides free textbooks to 10-year-olds; or introduces supplemental nutrition for pregnant mothers; or strengthens the social security net with a food-for-work program.
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Notes
- 1.
“Program for the Expansion of Educational Coverage.”
- 2.
Note that \( Y_i^{\rm{T}} = {Y_i}{I_{{{T_i} = 1}}} \)where \( {I_{\rm{A}}} \)denotes the indicator function of an event (1 if A occurs, 0 if not). We also have \( Y_i^{\rm{C}} = {Y_i}{I_{{{T_i} = 0}}}. \)
- 3.
We have that \( {G^{\rm{ATE}}} = E({Y_i}{I_{{{T_i} = 1}}}) - E({Y_i}{I_{{{T_i} = 0}}}) \)since \( {G^{\rm{ATE}}} = E(({Y_i}{I_{{{T_i} = 1}}} - {Y_i}{I_{{{T_i} = 0}}}){I_{{{T_i} = 1}}} + E(({Y_i}{I_{{{T_i} = 1}}} - {Y_i}{I_{{{T_i} = 0}}}){I_{{{T_i} = 0}}} \)by the definition of conditional expectations.
- 4.
To see this, consider an extreme case where all men borrow and no women borrow, so that gender perfectly predicts whether one will borrow. But then it will be impossible to match a borrower with an “otherwise identical” nonborrower.
- 5.
An earlier version of the model had used regional, rather than provincial, dummy variables in the propensity score equation; when it did not show adequate balance we revised the model, mainly by using the (more numerous) provincial dummy variables.
- 6.
This variable was instrumented using a dummy variable that indicated whether the area was covered by the piso firmeprogram; the rationale for and use of instrumental variables is discussed further below.
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A growing number of impact evaluations are now available on the Web, and can serve as templates for new evaluations; for a useful list, see http://www.worldbank.org/poverty (and follow links Impact Evaluation and then Selected Evaluations).
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Haughton, D., Haughton, J. (2011). Impact Evaluation. In: Living Standards Analytics. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0385-2_12
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