Economists routinely propose models in which current decisions depend on expectations of future variables. For instance, theories of intertemporal choice with incomplete markets posit that people react to expected income.
When the strong assumptions that lead to certainty equivalence are relaxed, theory also predicts that people respond to higher moments of the distribution of future income (Kimball, 1990). The relevant moments are those of the subjective income distribution conditional on information available at the time the decisions are made.
Only under the extreme hypothesis of complete markets the measurement of individual income risk is not an issue. But when idiosyncratic shocks matter, measuring microeconomic uncertainty becomes a crucial issue in applied econometrics and in calibration of general and partial equilibrium models. In a recent survey, Browning, Hansen and Heckman (1999) argue that calibrating economic models with imperfect insurance “requires a measure of the magnitude of microeconomic uncertainty, and how that uncertainty evolves over the business cycle [...]. This introduces the possibility of additional sources of heterogeneity because different economic agents may confront fundamentally different risks”.
These remarks have implications for many areas of research. Measuring individual uncertainty is crucial when trying to determine the importance of precautionary saving. Individual uncertainty affects the width of the inaction band in Ss models of durable demand and housing investment. Income risk can lead prudent individuals to demand a higher risk premium on risky assets, affects portfolio choice and the demand for insurance against insurable risks. More generally, income risk can impact labor supply, education and occupation choice, job search, and many other economic decisions.
Two approaches have emerged in the literature to extract moments of the distribution of future income from observable variables. One relies on panel data and infers expectations and possibly higher moments of the individual distribution from past income realizations. To be valid, this method requires assuming that individuals condition on the same set of variables to form expectations, that the individuals and the econometrician have the same information set and that the econometrician knows the stochastic process that generates individual expectations. It is an unhappy feature of applied economics that implausible assumptions and procedures get accepted for lack of sound alternatives.
A second strand of literature has recently proposed to rely on survey questions, not retrospective data, to elicit information on the conditional distribution of future income. The main advantage of survey questions over inference based on realizations is that they do not require the econometrician to know the variables that individuals consider in forming their expectations.
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