Econometric Analysis of Panel Data Introduction Panel Data

Econometric Analysis of Panel Data • Introduction – Panel Data Definition • • Unbalanced Panel Balanced Panel: Short Panel: Long Panel: – Panel Data Analysis • Unobserved Heterogeneity • Cross Section and Time Series Correlation • Using Stata (stata_intro)

Introduction • Panel Data – Definition (Wikipedia Encyclopedia) – Examples of Panel Datasets • Panel Study of Income Dynamics (PSID) • Penn World Table (PWT) • Panel Data Analysis – A Primer for Panel Data Analysis (Yaffee)

Using Stata • Declare Panel Data and Variables – xtset (or tsset) – xttab • Panel Data Analysis: xt commands – xtdes – xtsum – xtdata – xtline • Panel Data Regression – xtreg

Using Stata • Hypothesis Testing – xthausman – xttest 0 • Advanced Topics – xtregar – xthtaylor (Hausman-Taylor Estimator) – xtivreg (Instrumental Variables Estimation) – xtabond (Arellano-Bond Estimator)

Example: Investment Demand • Grunfeld and Griliches [1960] – i = 10 firms: GM, CH, GE, WE, US, AF, DM, GY, UN, IBM; t = 20 years: 1935 -1954 – Iit = Gross investment – Fit = Market value – Cit = Value of the stock of plant and equipment

Example: International Comparison of Economic Growth • R. Summers and A. Heston, "The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950 -1988, " Quarterly Journal of Economics 106, 1991, 327 -368. • G. Mankiw, D. Romer, and D. Weil, "A Contribution to the Empirics of Economic Growth, “ Quarterly Journal of Economics 107, 1992, 407 -437.

Example: International Comparison of Economic Growth • • • yit = Real per capita GDP si = Average saving rate (over 1960 -1985) ni = Average population growth rate (over 1960 -1985) g+d = 5% COMi = 1 if communist, 0 otherwise OPECi =1 if OPEC, 0 otherwise

Example: Returns to Schooling • Cornwell and Rupert Data, 595 Individuals, 7 Years • These data were analyzed in Cornwell, C. and Rupert, P. , "Efficient Estimation with Panel Data: An Empirical Comparison of Instrumental Variable Estimators, " Journal of Applied Econometrics, 3, 1988, pp. 149 -155. See Baltagi, page 122 for further analysis.

Example: Returns to Schooling • LWAGE = log of wage = dependent variable in regressions • EXP = work experience WKS = weeks worked OCC = occupation, 1 if blue collar, IND = 1 if manufacturing industry SOUTH = 1 if resides in south SMSA = 1 if resides in a city (SMSA) MS = 1 if married FEM = 1 if female UNION = 1 if wage set by union contract ED = years of education BLK = 1 if individual is black

Example: Wage Equation • Koop and Tobias [2004] • The data is available in two parts: – Part 1: Time-Variant Data (17, 919 obs. ) • • • id= Person id (ranging from 1 to 2178) ed = Education lwage = Log of hourly wage pexp = Potential experience trend = Time trend

Example: Wage Equation – Part 2: Time-Invariant Data (2178 individuals) • • • ability = Time invariant ability medu = Mother’s education fedu= Father’s education d = Dummy variable for residence in a broken home siblings = Number of siblings.

Example: U. S. Productivity • Munnell [1988] Productivity Data 48 Continental U. S. States, 17 Years: 19701986 – – – – – STATE = State name, ST ABB=State abbreviation, YR =Year, 1970, . . . , 1986, PCAP =Public capital, HWY =Highway capital, WATER =Water utility capital, UTIL =Utility capital, PC =Private capital, GSP =Gross state product, EMP =Employment,