截面和面板數(shù)據(jù)分析課件5(復(fù)旦大學(xué)陸銘張晏)-預(yù)覽頁(yè)
【正文】 fferenced Equation ? Methods: (AR(1)) ? Zero Assumption: ? Steps: ? First, we estimate () by pooled OLS and obtain the residuals, ? Then, we run the regression again with r?i,t1 as an additional explanatory variable. ? The coefficient on r?i,t1 is an estimate of , and so we can use the usual t statistic on r?i,t1 to test H0: 0. Correct for the AR(1) Serial Correlation ? Unfortunately, standard packages that perform AR(1) corrections for time series regressions will not work. Standard CochraneOrcutt or PraisWinsten methods will treat the observations as if they followed an AR(1) process across i and t。 marital status。 fchnge。 region ? dependent variable: fertility rates。 ? To control certain unobserved Characteristic of cross sections。 Analysis of Cross Section and Panel Data Yan Zhang School of Economics, Fudan University CCER, Fudan University Introductory Econometrics A Modern Approach Yan Zhang School of Economics, Fudan University CCER, Fudan University Analysis of Cross Section and Panel Data Part 3. Some Advanced Topics Chap 13. Pooling Cross Sections across Time ? Data Structure ? Pooled Cross Section。 ? Similar to a standard cross section, except that we often need to account for secular differences in the variables across the time. Panel or Longitudinal Data ? The same cross sectional members。 religion。 none of the slope estimates will change. ? Chow Test: ? What happens if we interact all independent variables with y85 in equation ()? Policy Analysis with Pooled Cross Sections ? natural experiments: occurs when some exogenous event—often a change in government policy— changes the environment in which individuals, families, firms, or cities operate. ? control group: not affected by the policychange ? treatment group: thought to be affected by the policy change. ? Methods: ? to control for systematic differences between the control and treatment groups, we need two years of data, one before the policy change and one after the change. ? the differenceindifferences estimator: Example Effects of Worker Compensation Laws on Duration ? : Kentucky raised the cap on weekly earnings that were covered by workers’ pensation. ? Problem: its effects on duration ? influenced: highine worker ? control group (low) and treatment group (high) ? Meyer, Viscusi and Durbin (1995) ? ? log(durat)。 gender。 drawback: ? Heterogeneity bias: Therefore, even if we assume that the idiosyncratic error uit is uncorrelated with xit, pooled OLS is biased and inconsistent if ai and xit are correlated. ? In most applications, the main reason for collecting panel data is to allow for the unobserved effect, ai, to be correlated with the explanatory . ? firstdifferenced equation FirstDifferenced Equation ? ? Key assumptions: ? strict exogeneity: dui is uncorrelated with dxi. ? firstdifferenced estimator ? dxi must have some variation across i. ? () satisfies the homoskedasticity assumption. . Sleeping vs. Working ? ? Differencing with More than Two Time periods ? Data Structure (fixed effect a
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