Earnings Mobility and Measurement Error: A Pseudo-Panel Approach

The degree of mobility in incomes is often seen as an important measure of the equality of opportunity in a society and of the flexibility and freedom of its labor market. But estimation of mobility using panel data is biased by the presence of measurement error and non-random attrition from the panel. This paper shows that dynamic pseudo-panel methods can be used to consistently estimate measures of absolute and conditional mobility in the presence of non-classical measurement errors. These methods are applied to data on earnings from a Mexican quarterly rotating panel. Absolute mobility in earnings is found to be very low in Mexico, suggesting that the high level of inequality found in the cross-section will persist over time. However, the paper finds conditional mobility to be high, so that households are able to recover quickly from earnings shocks. These findings suggest a role for policies which address underlying inequalities in earnings opportunities.

[1]  P. Gottschalk.  Inequality, Income Growth, and Mobility: The Basic Facts , 1997 .

[2]  S. Jenkins,et al.  How Much Income Mobility Is There in Britain , 1998 .

[3]  Bob Baulch,et al.  Economic mobility and poverty dynamics in developing countries , 2000 .

[4]  David J. McKenzie,et al.  Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity , 2005 .

[5]  D. McKenzie.  How do Households Cope with Aggregate Shocks? Evidence from the Mexican Peso Crisis , 2003 .

[6]  Sukamdi,et al.  Indonesian living standards : before and after the financial crisis , 2004 .

[7]  D. McKenzie.  Asymptotic theory for heterogeneous dynamic pseudo-panels , 2004 .

[8]  Efe A. Ok,et al.  The measurement of income mobility : an introduction to the literature, February, 1996 , 1996 .

[9]  Angus Deaton.  Panel data from time series of cross-sections , 1985 .

[10]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[11]  M. Lokshin,et al.  Household Income Dynamics in Two Transition Economies , 2004 .

[12]  Erzo F. P. Luttmer.  Measuring Economic Mobility and Inequality: Disentangling Real Events from Noisy Data , 2002 .

[13]  Rolf Aaberge,et al.  Income Inequality and Income Mobility in the Scandinavian Countries Compared to the United States , 2002 .

[14]  T. Piketty,et al.  Theories of persistent inequality and intergenerational mobility , 2000 .

[15]  Nazrul Islam,et al.  Growth Empirics: A Panel Data Approach , 1995 .

[16]  C. Barrett,et al.  The economics of poverty traps and persistent poverty: An asset-based approach , 2006 .

[17]  R. Moffitt.  Identification and estimation of dynamic models with a time series of repeated cross-sections , 1993 .

[18]  The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right? , 1991 .

[19]  David J. McKenzie,et al.  Consumption Growth in a Booming Economy: Taiwan 1976-96 , 2001 .

[20]  D. McKenzie.  Indonesian Living Standards: Before and After the Financial Crisis , 2005 .

[21]  Marno Verbeek,et al.  Estimating Dynamic Models from Repeated Cross-Sections , 2002 .

[22]  Enrico Spolaore,et al.  On the Evaluation of Economic Mobility , 2001 .

[23]  James P. Smith,et al.  Lost but Not Forgotten: Attrition and Follow-up in the Indonesia Family Life Survey , 2001 .

[24]  M. Collado.  Estimating dynamic models from time series of independent cross-sections , 1997 .

[25]  Paul J. Devereux,et al.  Improved Errors-in-Variables Estimators for Grouped Data , 2007 .

[26]  D. McKenzie.  Estimation of AR(1) models with unequally spaced pseudo-panels , 2001 .

[27]  Yoosoon Chang,et al.  Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency , 2002 .

[28]  M. Arellano,et al.  A NOTE ON THE ANDERSON-HSIAO ESTIMATOR FOR PANEL DATA , 1989 .

[29]  Bob Baulch,et al.  Simulating the impact of policy upon chronic and transitory poverty in rural Pakistan , 2000 .

[30]  P. Glewwe,et al.  Economic Mobility in Vietnam in the 1990s , 2002 .

[31]  Paul L. Cichello,et al.  For Richer or for Poorer? Evidence from Indonesia, South Africa, Spain, and Venezuela , 2003 .

[32]  Gary S. Fields,et al.  U.S. Earnings Mobility: Comparing Survey-Based and Administrative-Based Estimates , 2006 .

[33]  John Bound,et al.  Measurement error in survey data , 2001 .

[34]  John Bound,et al.  The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right? , 1988, Journal of Labor Economics.