APPENDIX 3: Exercises
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c. Specifically, are households that got agricultural extension poorer? Richer? Larger? Are they more reliant on farm income? 3. Next, let us assume that agricultural extension was provided randomly, once other variables are held constant, and then ask what effect the program had. a. Create dummy variables for each district (“thana”). The tab thana, gen(than) command will do this nicely. b. Run a regression of per capita income (or consumption or farm income) on the agextend, individual variables (such as gender, age, education, family size), and district dummy variables. The coefficient on the agextend variable measures the impact of the program. You will probably want to run a few regressions, one for each output variable (such as income per capita) that is of interest. c. Are the effects measured in 3(b) larger or smaller than in 2? 4. Finally, let us run a propensity score analysis. The idea is first to create a “propensity score” that measures the probability that a household will get agricultural extension; and then to use this score to match each “treated” household (that is, a household that gets agricultural extension) with an untreated household that is otherwise similar (that is, has a similar propensity score). Here is how it might work: a. From within Stata, use the search command to find “pscore” and “attnd” and download the relevant *.ado files. This is mainly an issue of following the instructions. b. Estimate the propensity score equation. This will look something like this: pscore agextend sexhead ... [other variables, including district dummies] ... , pscore(fhat1) comsup c. Now make the comparison, using nearest-neighbor matching, using attnd xxx agextend, pscore(fhat1) comsup where xxx refers to the outcome variable (for example, consumption per capita) that is of interest.
Notes 1. These commands were substantially revised in Stata version 8, and the syntax differs significantly from earlier versions of Stata. 2. A calorie is the energy required to heat one gram of water by one degree Celsius. A Calorie is 1,000 calories.
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