Measurement Error and Its Impact on Estimates of Income and Consumption Dynamics

71 Pages Posted: 21 Nov 2008 Last revised: 23 Mar 2009

See all articles by Nayoung Lee

Nayoung Lee

University of Southern California

Date Written: March 2009

Abstract

This paper uses data from the Korean Labor and Income Panel Study (KLIPS) to examine whether measurement error in income and consumption has the potential to generate biases for studies on income and consumption dynamics. A first-differenced dynamic panel model is estimated with lagged income and consumption as internal instruments and the household head's satisfaction with their household income as an external instrument. This study suggests that there is substantial time-varying measurement error in reported income and consumption, leading to a bias towards zero in the estimates of income and consumption dynamics. Time-invariant measurement error and unobserved heterogeneity are also found to be important and to lead to upward biases in the estimated coefficients, offsetting the effect of time-varying measurement error. The standard deviation of time-varying measurement error is as large as the standard deviation of the equation error for both income and consumption dynamics. This result also supports the view that time-varying measurement error exists in reported income and consumption and has a substantial magnitude.

Interestingly, the standard deviation of time-varying measurement error, as well as that of the equation error, is much larger in the model for the income dynamics than that for consumption dynamics. This result suggests that time-varying measurement error is more prevalent and varies more across households in income than in consumption and also indicates that households smooth their consumption relative to their income in the face of shocks.

Keywords: C81, I32, O15

JEL Classification: measurement error, income dynamics, consumption dynamics

Suggested Citation

Lee, Nayoung, Measurement Error and Its Impact on Estimates of Income and Consumption Dynamics (March 2009). Available at SSRN: https://ssrn.com/abstract=1299330 or http://dx.doi.org/10.2139/ssrn.1299330

Nayoung Lee (Contact Author)

University of Southern California ( email )

2250 Alcazar Street
Los Angeles, CA 90089
United States

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