Earnings, consumption and lifecycle choices

By C. Meghir, Luigi Pistaferri. 2010

236 citations recorded by the source corpus.

We discuss recent developments in the literature that studies how the dynamics of earnings and wages affect consumption choices over the life cycle. We start by analyzing the theoretical impact of income changes on consumption - highlighting the role of persistence, information, size and insurability of changes in economic resources. We next examine the empirical contributions, distinguishing between papers that use only income data and those that use both income and consumption data. The latter do this for two purposes. First, one can make explicit assumptions about the structure of credit and insurance markets and identify the income process or the information set of the individuals. Second, one can assume that the income process or the amount of information that consumers have are known and tests the implications of the theory. In general there is an identification issue that is only recently being addressed, with better data or better "experiments". We conclude with a discussion of the literature that endogenize people's earnings and therefore change the nature of risk faced by households.

Subfields: Accounting, Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/bc2507a300ea244be7e74bf3691b5c03b78c8604

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Citations in the corpus

Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework (2015, background): “k=0 aQklφk(ηi,t−1, ageit) ) fi(η T i ; θ)dη T i ] , (23)”
Learning by working in big cities (2017, unknown): “THE INTERACTION BETWEEN ABILITY AND THE LEARNING BENEFITS OF BIGGER CITIES earnings proﬁles across workers, which has crucial implications for income dynamics and choices made over the life cycle (see Meghir and Pistaferri, 2011, for a review).”
On-the-Job Search and Precautionary Savings (2013, background): “The wage moments are sufficient to identify the variances in a reduced form model of income dynamics with a permanent and transitory shock, where the variance of the permanent shock is time varying (see Meghir and Pistaferri 2011 for details).”
Heterogeneous Income Profiles and Lifecycle Bias in Intergenerational Mobility Estimation (2016, methodology): “8 A variation of the model that relies on the same intuition has been presented in Lee and Solon (2009). But as the classical errors-in-variables model, the GEiV model depends critically on assumption (5), as also noted by HS.”
Labor Income Dynamics and the Insurance from Taxes, Transfers, and the Family (2014, unknown): “The relatively small scale of the available U.S. panel surveys has forced researchers to rely on simple models that impose economically implausible restrictions (see the discussions in Baker and Solon, 2003; Meghir and Pistaferri, 2011).”
Knowledge of Future Job Loss and Implications for Unemployment Insurance (2017, unknown): “This is compounded by the problem that consumption expenditure is generally measured with error (Zeldes (1989); Meghir and Pistaferri (2011)).”
Optimal Tax Progressivity: An Analytical Framework (2014, unknown): “C = λH1−τ , and the production technology simplifies toY = H, implyingG = gH. Taking the fiscal variables (λ, g, τ) as given, the optimal choices for the representative agent ar logHRA (τ) = 1 1 + σ log(1− τ), (18) logCRA (g, τ) = log λ (g, τ) + 1− τ 1 + σ log(1− τ).”
Consumption Inequality and Family Labor Supply (2014, background): “Since age-specic cells are quite small given the size of our data set, however, we restrict the age-variation to stages of the life cycle (30-37, 38-42, 43-47, 48-52, 53-57).”
A Schumpeterian Model of Top Income Inequality (2014, unknown): “Meghir and Pistaferri (2011) survey this literature, highlighting prominent examples such as MaCurdy (1982), Abowd and Card (1989), Topel and Ward (1992), Baker and Solon (2003), and Meghir and Pistaferri (2004).”