NBER Publications by Hamish Low

This paper provides a life-cycle framework for weighing up the insurance value of disability benefits against the incentive cost. Within this framework, we estimate the life-cycle risks that individuals face in the US, as well as the parameters governing the disability insurance program, using indirect inference and longitudinal data on consumption, disability status, disability insurance receipt, and wages. We use our estimates to characterize the economic effects of disability programs and to consider how policy reforms would affect behaviour and standard measures of household welfare. Because of high levels of false rejections associated with the screening problem, average household welfare increases as the program becomes less strict, despite the worsening incentives that this implies....

We specify a structural life-cycle model of consumption, labour supply and job mobility in an economy with search frictions that allows us to distinguish between different sources of risk and to estimate their effects. The sources of risk are shocks to productivity, job destruction, the process of job arrival when employed and unemployed and match level heterogeneity. In contrast to simpler models that attribute all income fluctuations to shocks, our framework disentangles variability due to shocks from variability due to the responses to these shocks. Estimates of productivity risk, once we control for employment risk and for individual labour supply choices, are substantially lower than estimates that attribute all wage variation to productivity risk. Increases in productivity risk impos...

In this paper we consider conditions under which the estimation of a log-linearized Euler equation for consumption yields consistent estimates of the preference parameters. When utility is isoelastic and a sample covering a long time period is available, consistent estimates are obtained from the log-linearized Euler equation when the innovations to the conditional variance of consumption growth are uncorrelated with the instruments typically used in estimation. We perform a Montecarlo experiment, consisting in solving and simulating a simple life cycle model under uncertainty, and show that in most situations, the estimates obtained from the log-linearized equation are not systematically biased. This is true even when we introduce heteroscedasticity in the process generating income. The o...