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in this presentation i will talk about panel data models the outline of this presentation will be to talk about panel data setup and variations and then we will talk about different estimators the pull down less model estimator the first differences estimator the fixed effector the within estimator dummy variable regressions with fixed effects the random effects estimator and then well finish up with the hausmann test for deciding between fixed effects versus random effects so when we have panel data its because we have panel data variables so we would distinguish between three types of panel data variables the first type is the varying regressors x i t and examples could be annual income for a person monthly food expenditures here we have the variable and then i and t which means that this variable varies for the individual and over time then we would have time invariant regressors where x i t would be equal to x i for all t variables such as gender race or education now its possi
