G3e14 - Chapter 14 Introduction to panel data Overview...

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Chapter 14 Introduction to panel data Overview Increasingly, researchers are now using panel data where possible in preference to cross-sectional data. One major reason is that dynamics may be explored with panel data in a way that is seldom possible with cross- sectional data. Another is that panel data offer the possibility of a solution to the pervasive problem of omitted variable bias. A further reason is that panel data sets often contain very large numbers of observations and the quality of the data is high. This chapter describes Learning outcomes After working through the corresponding chapter in the text, studying the corresponding slideshows, and doing the starred exercises in the text and the additional exercises in this guide, you should be able to: explain the differences between panel data, cross-sectional data, and time series data explain what the benefits that can be obtained using panel data explain the differences between OLS pooled regressions, fixed effects regressions, and random effects regressions explain the potential advantages of the fixed effects model over pooled OLS explain the differences between the within-groups, first differences, and least squares dummy variables variants of the fixed effects model explain the assumptions required for the use of the random effects model explain the advantages of the random effects model over the fixed effects model when the assumptions are valid explain how to use a Durbin–Wu–Hausman test to determine whether the random effects model may be used instead of the fixed effects model Additional exercises A14.1 The NLSY2000 data set contains the following data for a sample of 2,427 males and 2,392 females for the years 1980–2000: weight in pounds, years of schooling, age, marital status in the form of a dummy variable MARRIED defined to be 1 if the respondent was married, 0 if single, and height in inches. Hypothesizing that weight is influenced by schooling, age, marital status, and height, the following regressions were performed for males and females separately: (1) an ordinary least squares (OLS) regression pooling the observations (2) a within-groups fixed effects regression (3) a random effects regression The results of these regressions are shown in the table. Standard errors are given in parentheses. October 2007
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2 Males Females OLS FE RE OLS FE RE Years of schooling –0.98 (0.09) –0.02 (0.23) –0.45 (0.16) –1.95 (0.12) –0.60 (0.27) –1.25 (0.18) Age 1.61 (0.04) 1.64 (0.02) 1.65 (0.02) 2.03 (0.05) 1.66 (0.03) 1.72 (0.03) Married 3.70 (0.48) 2.92 (0.33) 3.00 (0.32) –8.27 (0.59) 3.08 (0.46) 1.98 (0.44) Height 5.07 (0.08) dropped 4.95 (0.18) 3.48 (0.10) dropped 3.38 (0.21) constant –209.52 (5.39) dropped –209.81 (12.88) –105.90 (6.62) dropped –107.61 (13.43) R 2 0.27 0.17 n 17,299 17,299 17,299 13,160 13,160 13,160 DWH χ 2 (3) 7.22 92.94 (a) Explain why height is excluded from the FE regression. (b)
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This note was uploaded on 05/26/2010 for the course ECON 301 taught by Professor Öcal during the Spring '10 term at Middle East Technical University.

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G3e14 - Chapter 14 Introduction to panel data Overview...

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