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Panel Models in Sociological Research

Panel Models in Sociological Research. Janet H. Van Cleave Yale University. Panel Data. Cross-sectional time series data Number of observations over time Usually large number of units Individuals Households Institutions Governments Between or within units. Panel Data.

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Panel Models in Sociological Research

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  1. Panel Models in Sociological Research Janet H. Van Cleave Yale University

  2. Panel Data • Cross-sectional time series data • Number of observations over time • Usually large number of units • Individuals • Households • Institutions • Governments • Between or within units

  3. Panel Data • One restriction in panel data is exogeneity • Error term uncorrelated with current, future and past values of error term • Period effects are common to all units

  4. Panel Data • Independent variables • Time variant • Education, Marital status, number of children, interest rates • Time Invariant • Unobserved unit effects • Race, Gender • Errors • Transitory • Varies over time and units • Dependent variable • Wages, Employment

  5. Panel Data • Random Effects • Yit = α + ∑ β1xkit + uit • Assume unobserved unit effect α is uncorrelated with independent variable • Fixed Effects (Within Effects) • Yit = ∑ β1xkit + uit • Allows for arbitrary correlation between α and the independent variable • Between Group Effects • Ignores any information within individuals

  6. Panel Data • Key issue concerns subject • Is the unobserved unit effect correlated with independent variables? • Random effects model • Is not allowed to be correlated • Fixed effects • Unobserved unit effect can correlate • Random effects model vs. Fixed effects model?

  7. Panel Data • Benefits of random vs. fixed effects • Fixed effects model • Allows for arbitrary correlation between unobserved unit effect and independent variable • Within dimension of data • Random effects model • Use when unobserved unit effect is not correlated with independent variable • Combines between and within dimensions of data

  8. Panel Data • Hausman Test • Test for null hypothesis • α (unobservered effect) and xkit (independent variable) uncorrelated • Significant difference indicates null hypothesis is unlikely • Unlikely that α and xkit are uncorrelated • Use Fixed Effects • Non significant difference • Supports that α and xkit are uncorrelated • Cannot reject null hypothesis • Use Random Effects model

  9. Example: Wage Penalty for Motherhood • Purpose • Is there a wage penalty for motherhood • Data: Pooled 1982-1993 waves of the National Longitudinal Survey of Youth • Persons interviewed annually • Two observations for each person Budig & England (2001) American Sociological Review, 66, 204-225

  10. Example: Wage Penalty • Dependent variable: Natural log of hourly wage • Unit of analysis: person-years • Independent variables • Time variant • Total number of children (dummy variable) • Marital status (dummy variable) • Education • Years of full-time and parttime seniority • Job characteristics • Quality of Employment Survey (Continuous variables) Budig & England (2001) American Sociological Review, 66, 204-225

  11. Example: Wage Penalty • Fixed Independent Variables • Time invariant • Years and persons • Unchanging aspects of persons • Life cycle plans • Tastes for affluence • Future orientation • Unmeasured human capital Budig & England (2001) American Sociological Review, 66, 204-225

  12. Example: Wage Penalty • Two types of unobservable data • Time-invariant unit specific unobservable • Represent permanent properties of mothers (i.e.unit effects) • Cognitive effects, preference from previous socialization • Time-varying unit specific unobservables • Transitory and idosyncratic forces acting upon mothers • i.e. employer discrimination Budig & England (2001) American Sociological Review, 66, 204-225

  13. Example: Wage Penalty • Statistical Model • Fixed effects regression model • Fixed effects for years and persons • Hausman test conducted to assess whether random-effects model vs. fixed effects • Showed need for fixed-effects models • Best controlled for unobserved heterogeneity of mothers in study Budig & England (2001) American Sociological Review, 66, 204-225

  14. Wage Penalty: Results • Wage penalty for each child is 7 percent • Penalties larger for married women • Reduced experience partly explains • Controlling for human capital variables reduces child penalty 36% (7% to 5%) • Unexplained penalty • Decreased productivity • Discrimination by employers Budig & England (2001) American Sociological Review, 66, 204-225

  15. Benefits of Fixed-Effects Model • Fixed Effects • Within-group estimator avoids heterogeneity bias • Controls for “between group” variation • Does not depend on the random effects assumption

  16. Regression Models for Panel Data

  17. Summary • Panel Studies for observational data common • Use for analytical problems • Individuals • Institutions • Corporations • Use when unobserved unit effect correlated with independent variable

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