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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.
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.
Do individuals keep the same place on the earnings scale, or is there a great deal of mobility? This volume discusses the empirical studies of this issue.
This paper develops a framework for the quantitative analysis of individual income dynamics, mobility and welfare. Individual income is assumed to follow a stochastic process with two (unobserved) components, an i.i.d. component representing measurement error or transitory income shocks and an AR(1) component representing persistent changes in income. We use a tractable consumption-saving model with labor income risk and incomplete markets to relate income dynamics to consumption and welfare, and derive analytical expressions for income mobility and welfare as a function of the various parameters of the underlying income process. The empirical application of our framework using data on individual incomes from Mexico provides striking results. Much of measured income mobility is driven by measurement error or transitory income shocks and therefore (almost) welfare-neutral. A smaller part of measured income mobility is due to either welfare-reducing income risk or welfare-enhancing catching-up of low-income individuals with high-income individuals, both of which have economically significant effects on social welfare. Decomposing mobility into its fundamental components is thus seen to be crucial from the standpoint of welfare evaluation.