We estimate a principal-agent model of moral hazard with longitudinal data on firms and managerial compensation over two disjoint periods spanning 60 years to investigate increased value and variability in managerial compensation. We find exogenous growth in firm size largely explains these secular trends in compensation. In our framework, exogenous firm size works through two channels. First, conflicts of interest between shareholders and managers are magnified in large firms, so optimal compensation plans are now more closely linked to insider wealth. Second, the market for managers has become more differentiated, increasing the premium paid to managers of large versus small firms.

Government procurement contracts rarely have many bids, often only one. Motivated by the institutional features of federal procurement, this article develops a principal-agent model where a buyer seeks sellers at a cost and negotiates contract terms with them. The model is identified and estimated with data on IT and telecommunications contracts. We find the benefits of drawing additional sellers are significantly reduced because the procurement agency can extract informational rents from sellers. Another factor explaining the small number of bids is that sellers are relatively homogeneous, conditional on observed project attributes. Administrative hurdles and corruption appear to play very limited roles.

This paper develops a generalized Roy model with human capital accumulation, moral hazard, and career concerns. We identify and estimate the model with a large panel that matches data on publicly listed firms to information on their executives. The structural estimates obtained are used to decompose the firm‐size pay gap. We find that although total compensation and incentive pay increase with firm size, certainty‐equivalent pay decreases with firm size. In larger firms, and for more highly ranked executives, weaker signal quality about effort results in higher risk premiums. This risk premium accounts for roughly 80 percent of the firm‐size gap in total compensation. Larger firms are also willing to pay more than smaller ones to attract executives. Finally, the estimated coefficients on human capital accumulation from formal education and experience gained from different firms are individually significant, but their collective effect on firm‐size pay differentials nets out.

This paper develops a new method for estimating the structural parameters of (discrete choice) dynamic programming problems. The method reduces the computational burden of estimating such models. We show the valuation functions characterizing the expected future utility associated with the choices often can be represented as an easily computed function of the state variables, structural parameters, and the probabilities of choosing alternative actions for states which are feasible in the future. Under certain conditions, nonparametric estimators of these probabilities can be formed from sample information on the relative frequencies of observed choices using observations with the same (or similar) state variables. Substituting the estimators for the true conditional choice probabilities in formulating optimal decision rules, we establish the consistency and asymptotic normality of the resulting structural parameter estimators. To illustrate our new method, we estimate a dynamic model of parental contraceptive choice and fertility using data from the National Fertility Survey.

We adapt the expectation–maximization algorithm to incorporate unobserved heterogeneity into conditional choice probability (CCP) estimators of dynamic discrete choice problems. The unobserved heterogeneity can be time-invariant or follow a Markov chain. By developing a class of problems where the difference in future value terms depends on a few conditional choice probabilities, we extend the class of dynamic optimization problems where CCP estimators provide a computationally cheap alternative to full solution methods. Monte Carlo results confirm that our algorithms perform quite well, both in terms of computational time and in the precision of the parameter estimates.

We provide empirical restrictions of a model of optimal order submissions in a limit order market. A trader's optimal order submission depends on the trader's valuation for the asset and the trade-offs between order prices, execution probabilities and picking off risks. The optimal order submission strategy is a monotone function of a trader's valuation for the asset. We test the monotonicity restriction in a sample of order submissions and their realized outcomes from the Stockholm Stock Exchange. We do not reject the monotonicity restriction for buy orders or sell orders considered separately, but reject the monotonicity restriction for buy and sell orders considered jointly.

This paper examines household fertility and female labor supply over the life cycle. We investigate how maternal time inputs, market expenditures on offspring, as well as the benefits they yield their parents, vary with ages of offspring, and influence female labor supply and contraceptive behavior. Our econometric framework combines a female labor supply model and a contraceptive choice index function. It also accounts for the fact that conceptions are not perfectly controllable events. Using longitudinal data on married couples from the Panel Study of Income Dynamics, we estimate these equations and test alternative specifications of the technologies governing chld care. Our findings suggest that while parents cannot perfectly control conceptions, variations in child care costs do affect the life cycle spacing of births. Furthermore, our results demonstrate the gains of modelling the linkages between female labor supply and fertility behavior at the household level.

We present a method to estimate the gains from trade in limit‐order markets and provide empirical evidence that the limit‐order market is a good market design. Using observations on order submissions and execution and cancellation histories, we estimate both the distribution of traders' unobserved valuations for the stock and latent trader arrival rates. We use the resulting estimates to compute the current gains from trade, the gains from trade in a perfectly liquid market, and the gains from trade with a monopoly liquidity supplier. The current gains are 90% of the maximum gains and 150% of the monopolist gains.