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• W1502956075 abstract "The importance of idiosyncratic labor income risk for individuals’ economic choices and, hence, for allocations and welfare is hard to overstate. The literature that relies on incomplete markets/heterogeneous agent models is not only vast, but is also continuing to expand at a rapid pace. Not surprisingly, a crucial ingredient in this research is the precise nature of income risk that researchers feed into their models. This demand for reliable information has led to the development of an active empirical literature that estimates stochastic processes for individual (labor) earnings, going back to the early seminal contributions by Lillard and Willis (1978), MaCurdy (1982), and Abowd and Card (1989), and more recent contributions by Meghir and Pistaferri (2004), Heathcote, Storesletten, and Violante (2008), Guvenen (2009), and Altonji, Smith, and Vidangos (2010). Although these studies have made important contributions to our understanding of idiosyncratic income risk, an important shortcoming is that they rely on very noisy survey data, with small sample sizes—most commonly, the Panel Study of Income Dynamics (PSID). The goal of this paper is to shed new light on income risk by using—for the first time—a panel dataset on labor earnings obtained from administrative records that has three key advantages: (i) very large sample size with a long average time span (7 to 20 times the size of PSID samples used in the existing literature), (ii) minimal measurement error, (iii) no top-coding.1 First, as I elaborate in the data description below, the smallest sample we use has about 188,000 observations on approximately 19,000 individuals (compared to 10,000 to 35,000 observations on 500 to 2000 individuals, in most existing work). Furthermore, what is also critical is that more than half of all individuals in our sample (ie., 10,000+ individuals) are observed for 15 years or more, which is about 10 times larger than the number of individuals observed for the same duration in PSID. As discussed in Guvenen (2009), a long time dimension is essential for constructing higherorder autocovariances, which are critical for identification between alternative income processes. Unfortunately, due to attrition, in most survey data sets few individuals are observed for 15 to 20 years, which has been an important obstacle for precise empirical identification in existing work." @default.
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• W1502956075 date "2010-01-01" @default.
• W1502956075 modified "2023-09-26" @default.
• W1502956075 title "Idiosyncratic Income Risk Estimated From IRS Administrative Wage Data" @default.
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