This paper empirically investigates how sentences to be assigned at trial impact plea bargaining. The analysis is based on the model of bargaining with asymmetric information by Bebchuk, 1984. I provide conditions for the nonparametric identification of the model, propose a consistent nonparametric estimator, and implement it using data on criminal cases from North Carolina. Employing the estimated model, I evaluate how different sentencing reforms affect the outcome of criminal cases. My results indicate that lower mandatory minimum sentences could greatly reduce the total amount of incarceration time assigned by the courts, but may increase conviction rates. In contrast, the broader use of non‐incarceration sentences for less serious crimes reduces the number of incarceration convictions, but has a very small effect over the total assigned incarceration time. I also consider the effects of a ban on plea bargains. Depending on the case characteristics, over 20 percent of the defendants who currently receive incarceration sentences would be acquitted if plea bargains were forbidden.

This paper develops a search-theoretic model of technological change to explain why both patenting and the growth of productivity have remained roughly constant while research employment in the United States has increased by a factor of six over the past four decades. In the model, researchers sample from probability distributions determining the efficiency of potential new production techniques. Technological breakthroughs, resulting in patents, become increasingly hard to find as the level of technology advances. Given certain restrictions on the search distributions, the equilibrium of the model replicates the U.S. time-series pattern of research, patenting, and productivity.

On presente une definition formelle de l'identification dans un contexte non parametrique sur la base des travaux de Koopmans et Reiersol (1950)

[A dynamic model of insider trading with sequential auctions, structured to resemble a sequential equilibrium, is used to examine the informational content of prices, the liquidity characteristics of a speculative market, and the value of private information to an insider. The model has three kinds of traders: a single risk neutral insider, random noise traders, and competitive risk neutral market makers. The insider makes positive profits by exploiting his monopoly power optimally in a dynamic context, where noise trading provides camouflage which conceals his trading from market makers. As the time interval between auctions goes to zero, a limiting model of continuous trading is obtained. In this equilibrium, prices follow Brownian motion, the depth of the market is constant over time, and all private information is incorporated into prices by the end of trading.]

This paper develops a general theory of the aggregate implications of (S, s) inventory policies. It is shown that (S, s) policies add to the variability of demand, with the variance of orders exceeding the variance of sales. Overall, the (S, s) theory contradicts the widely held notion that retail inventories act as a buffer, protecting manufacturers from fluctuating sales. In 1951, Arrow, Harris, and Marschak [3] introduced the (S, s) form of inventory policy. The policies are designed for retailers of finished goods, who face economies of scale when placing orders with their suppliers. To pursue an (S, s) inventory policy, the retailer establishes a lower stock point s, and an upper stock point S. No order is placed until inventories fall to s or below, whereupon they are restored to the maximum of S. A general proof of the optimality of these (S, s) inventory policies was provided by Scarf [13]. At the microeconomic level, the model has been extensively investigated. Formulae are available to compute optimal policies (e.g., Ehrhardt [6]), and these policies are xidely used in industry (e.g., Schwartz (ed.) [14]). In addition, the model has been extended to increasingly complex demand environments (e.g., Karlin and Fabens [11]). In contrast, little is known about the macroeconomic implications of (S, s) policies. Several recent papers have begun to correct this deficiency. Akerlof has suggested that pursuit of constant threshold money holding policies of the (S, s) variety might be responsible for the observed low short-run income elasticity of the demand for money (Akerlof [1] and Akerlof and Milbourne [2]). In the operations research literature, Ehrhardt, Schultz, and Wagner [7] analyzed the demand environment of a wholesaler supplying several retailers. They required that the distinct retailers have independent sales, ruling out the analysis of common factors in sales. Finally, simulation results of Blinder [4] suggested a role for the (S, s) model in understanding retail sector inventories. However the theoretical difficulties with the model remained unresolved. Blinder commented: If firms have a technology that makes the S, s rule optimal, aggregation across firms is inherently difficult. Indeed it is precisely this difficulty which has prevented the S, s model from being used in empirical work to date (Blinder [4, p. 459]). In this paper we present a general theory of the aggregate implications of (S, s) policies. Our central finding is that (S, s) policies add to the variability of demand, with the variance of orders exceeding the variance of sales. This result holds even in the presence of common factors in retail sales. In addition, a close connection

Institutional and Behavioral Economics, Labor and Human Capital

Economic theorists have interpreted the "efficient markets hypothesis" to assert that equilibrium asset prices reveal all decision-relevant information in the market. This paper establishes conditions on investors' utility functions of future wealth which are necessary for the efficient markets hypothesis to be satisfied and be robust to slight perturbations of endowments and the joint distribution of current information and future asset values. The main result states that over the relevant range of future wealth values, there are three possible cases: (i) all investors are risk-neutral; (ii) modulo a change in the wealth origin, each investor has constant relative risk aversion with the same constant for all investors; or (iii) all investors have constant absolute risk aversion.