Section_7_Spring2008 - Panel Data Review and Implementation...

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Panel Data Review and Implementation in Stata Econ 142 Spring 2008 Raymundo M. Campos-Vazquez March 5, 2008 Contents 1 Instrumental Variables 1 2 Panel Data 1 2.1 Dummy Variable Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Within Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.3 First-Di/erence Transformation . . . . . . . . . . . . . . . . . . . . . . . . . 4 1 Instrumental Variables ° Stata: Check the command ivreg. ° Notation: ivreg y (x=z) where y is the dependent variable, x the endogenous variable and z the instrument. 2 Panel Data Panel data is a challenging, confusing and exciting topic. Please read carefully the Chapters in the book on Panel Data. The big picture: we are interested in the causal e/ect of X on Y. Suppose we have the following model: Y st = ° + ±X st + " st (1) 1
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± is the causal e/ect if E [ " sj j X st ] = 0 for all j and t , or that X is "strictly exogenous" : For example, if we are trying to estimate the e/ects of welfare programs on labor supply across states and years, or the e/ects of immigration on natives°wages, or the e/ect of cigarette prices on cigarette consumption, we may think that there are some permanent di/erences across states. Regression (1) is comparing Alabama and California, and similarly across states. In the same way, if we have data for 1990 and 2000, regression (1) is comparing Alabama in 1990 with California in 2000. Does this make sense?
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