In this paper we explore the impact of imperfectly competitive input markets on production function estimation. First order profit maximizing conditions are altered when frictions in input markets cause the elasticity of input supply to the firm to be finite. A consequence of this is that the...

We study asset-tested unemployment insurance in an incomplete markets model with moral hazard during job search. Asset testing has two counteracting effects on welfare. On the one hand, it improves consumption insurance by introducing state contingent transfers to agents most in need. On the...

Estimates of Frisch labor-supply elasticities are biased in the presence of borrowing constraints. We show that this estimation bias is less pronounced for secondary than for primary earners. The reason is that, in households with two earners and joint borrowing constraints, wage-rate...

This paper quantitatively determines the asset limit in income support programs which minimizes consumption volatility in a lifecycle model with incomplete markets and idiosyncratic earnings risk. An asset limit allows allocating transfers to those households with the highest utility gains from...

We use the Italian Survey of Household Income and Wealth, a rather unique dataset with a long time dimension of panel information on consumption, income and wealth, to structurally estimate a buffer-stock saving model. We exploit the information contained in the joint dynamics of income,...

In this paper, we document that households’ consumption expenditures depend on their expected earnings - even after controlling for realized earnings and wealth. To explain this evidence, we develop and structurally estimate a standard-incomplete markets model in which rational households...

This paper develops a macroeconomic model that combines an incomplete-markets overlapping-generations economy with a job ladder featuring sequential wage bargaining, endogenous search effort of employed and non-employed workers, and differences in match quality. The calibrated model offers a...

This paper performs a comparative analysis of estimation as well as of out-of-sample forecasting results of more than 20 estimators common in the panel data literature using the data on migration to Germany from 18 source countries in the period 1967-2001. Our results suggest that the choice of...

This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS. The methods are suitable for the high-dimensional setting where the number of...

The maximum likelihood estimator for the regression coefficients, β, in a panel binary response model with fixed effects can be severely biased if N is large and T is small, a consequence of the incidental parameters problem. This has led to the development of conditional maximum likelihood...