Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework

By M. Arellano, Richard Blundell, S. Bonhomme. Social Science Research Network, 2015

219 citations recorded by the source corpus.

We develop a new quantile-based panel data framework to study the nature of income persistence and the transmission of income shocks to consumption. Log-earnings are the sum of a general Markovian persistent component and a transitory innovation. The persistence of past shocks to earnings is allowed to vary according to the size and sign of the current shock. Consumption is modeled as an age-dependent nonlinear function of assets and the two earnings components. We establish the nonparametric identification of the nonlinear earnings process and the consumption policy rule. Exploiting the enhanced consumption and asset data in recent waves of the Panel Study of Income Dynamics, we find nonlinear persistence and conditional skewness to be key features of the earnings process. We show that the impact of earnings shocks varies substantially across earnings histories, and that this nonlinearity drives heterogeneous consumption responses. The transmission of shocks is found to vary systematically with assets.

Subfields: Accounting, Demography, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/7874ce8583c1784fe19ee4c6245822f3f2c0efde

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Citations in the corpus

Nonlinear Panel Data Estimation via Quantile Regressions (2015, methodology): “Arellano et al. (2015) use a quantile-based approach to document nonlinear relationships between earnings shocks to households and their lifetime profiles of earnings and consumption.”
Saving and Wealth Inequality (2017, unknown): “Yet, Arellano et al. (2015) find that the persistence of earnings innovations depends both on age and previous earnings level, Geweke and Keane (2000) and Bonhomme and Robin (2009) document that innovations to earnings are not Gaussian, Meghir and Pistaferri (1998) and Blundell et al. (2015) show…”