Life Cycle Models: Micro to Macro

I have studied extensively life cycle model and their estimation with micro data. I have looked at models of labor supply, durable purchases, housing, different preference specifications and so on. Recently I have used estimated life cycle models to reverse engineer individual perceptions of future events.

I list here some of my papers and current projects.

Working Papers

Temptation and Commitment: Understanding Hand-to-Mouth Behavior
with A. Kovacs and P. Moran (October 2020, NBER Working Paper No. 27944)

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Abstract: This paper presents a model of consumption behavior that explains the presence of ‘wealthy hand-to-mouth’ consumers using a mechanism that differs from those analyzed previously. We show that a two-asset model with temptation preferences generates a demand for commitment and thus illiquidity, leading to hand-to-mouth behavior even when liquid assets deliver higher returns than illiquid assets. This model fits other features of the data, such as the fact that the Marginal Propensity to Consume declines only slowly with shock size. Moreover, temptation and commitment have important policy implications: we show that housing subsidies and mandatory mortgage amortization increase household savings.


(S)cars in the great recession
with K. Larkin, M. Ravn, and M. Padula (Forthcoming 2022, Econometrica)

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Abstract: US households’ consumption and car purchases collapsed during the Great Recession, for reasons that are still poorly understood. In this paper we use the Consumer Expenditure Survey to derive cohort and business cycle decompositions of consumption profiles. When decomposing the car expenditure data into its extensive and intensive margins, we find that the intensive margin contracted sharply in the Great Recession, a finding in stark contrast to conventional wisdom and to the experience of prior recessions. We interpret the evidence through the prism of a very rich life-cycle model where individuals are subject to idiosyncratic uninsurable income shocks, aggregate income shocks, wealth shocks, and credit shocks. We show that, because of their salience and the transaction costs, cars are particularly sensitive to changes in the perception of fu- ture expected income and its variability. We find that on top of a large aggregate income shock, life-cycle income profile shocks and wealth shocks are important determinants of consumption choices during the Great Recession.

Euler Equations, Subjective Expectations and Income Shocks
with A. Kovacs and K. Molnar (June 2019, Economica)

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Abstract: In this paper, we make three substantive contributions. First, we use elicited subjective income expectations to identify the levels of permanent and transitory income shocks in a lifecycle framework. Second, we use these shocks to assess whether households’ consumption is insulated from them. Third, we use the shock data to estimate an Euler equation for consumption. We find that households are able to smooth transitory shocks, but adjust their consumption in response to permanent shocks, albeit not fully. The estimates of the Euler equation parameters with and without expectational errors are similar, which is consistent with rational expectations. We break new ground by combining data on subjective expectations about future income from the Michigan Survey with microdata on actual income from the Consumer Expenditure Survey.

Aggregating Elasticities: Intensive and Extensive Margins of Women’s Labour Supply
with H. Low, P. Levell, and V. Sanchez Marcos (November 2018, Econometrica)

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Abstract: We show that there is substantial heterogeneity in women’s labor supply elasticities at the micro level and highlight the implications for aggregate behavior. We consider both intertemporal and intratemporal choices, and identify intensive and extensive responses in a consistent life-cycle framework, using US CEX data. Heterogeneity is due to observables, such as age, wealth, hours worked, and the wage level, as well as to unobservable tastes for leisure: the median Marshallian elasticity for hours worked is 0.18, with corresponding Hicksian elasticity of 0.54 and Frisch elasticity of 0.87. At the 90th percentile, these values are 0.79, 1.16, and 1.92. Responses at the extensive margin explain about 54% of the total labor supply response for women under 30, although this declines with age. Aggregate elasticities are higher in recessions, and increase with the length of the recession. The heterogeneity at the micro level means that the aggregate labor supply elasticity is not a structural parameter: any aggregate elasticity will depend on the demographic structure of the economy as well as the distribution of wealth and the particular point in the business cycle.

Work in Progress

The Life Cycle Model
with G. Weber and H. Low (Book in Progress)

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Abstract: Available soon.