Econometrics-I-17

Econometrics-I-17 - Applied Econometrics William Greene...

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Applied Econometrics William Greene Department of Economics Stern School of Business
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Applied Econometrics 17. Linear Models for Panel Data
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Panel Data Sets Longitudinal data National longitudinal survey of youth (NLSY) British household panel survey (BHPS) Panel Study of Income Dynamics (PSID) German Socioeconomic Panel (GSOEP) Agricultural Resource Management Survey (ARMS) Cross section time series Grunfeld’s investment data Penn world tables Financial data by firm, year r it  – r ft  =  β i (r mt   -  r ft )  +   ε it , i = 1,…,many; t=1,…many Exchange rate data, essentially infinite T, large N Effects:  β i β  + v i
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Terms of Art Cross sectional vs. time series variation -  ( history: consumption function studies ) Heterogeneity Group effects (individual effects) Fixed effects and/or random effects Substantive differences?    Is it possible to tell them apart in observed data? 
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Panel Data Rotating panels: Spanish household survey Spanish income study ( http://www.cemfi.es/~albarran/0008r.pdf ) Efficiency analysis: “Efficiency measurement in  rotating panel data,” Heshmati, A,  Applied  Economics , 30, 1998, pp. 919-930 Hierarchical (nested) data sets: Student  outcome, by year, district, school, teacher
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Nested Panel Data Antweiler, W., Nested Random Effects…”  Journal of Econometrics, 101, 2001, 295-313 2 1 2 c,s,t 3 c,t 4 8 9 , , , Sulfide concentration(year,country,station=t,c,s) + (logGDP/km ) + log(K/L) β β β   . .. +  log( Pr ) c t c s t c s s Communist Oil ice t v w + β + β + β + ε + +
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Balanced and Unbalanced Panels Distinction A notation to help with mechanics             z i,t , i = 1,…,N;  t = 1,…,T i The role of the assumption  Mathematical and notational convenience: Balanced, NT Unbalanced: Is the fixed T i  assumption ever necessary?  SUR  models.   N i i=1 T
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Benefits of Panel Data Time and individual variation in behavior  unobservable in cross sections or aggregate  time series Observable and unobservable individual  heterogeneity Rich hierarchical structures Dynamics in economic behavior
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Unobserved individual effects in regression:  E[y it  |  x it , c i ] Notation:   Linear specification: Fixed Effects:  E[c i  |  X i  ] = g( X i ); effects are correlated with  included variables. Common: Cov[ x it ,c i ] ≠ 0 Random Effects: E[c i  |  X i  ] = μ; effects are uncorrelated with  included variables.  If  X i  contains a constant term, μ=0 WLOG.  Common: Cov[ x it ,c i ] = 0 , but E[c i  |  X i  ] = μ is needed for the full  model it it i it
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This note was uploaded on 11/23/2011 for the course ECON B30.3351 taught by Professor Professorw.greene during the Spring '10 term at NYU.

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Econometrics-I-17 - Applied Econometrics William Greene...

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