Knowledge that Transforms

We use data from an agricultural labour market in which workers receive both time- and piece-rate wages and shift frequently among employers and tasks, to assess the roles of comparative advantage, information problems and preferences in determining the allocation of workers. The estimates which impose minimal structure not implied by economic theory are consistent with a one-factor productivity model, and indicate that information asymmetries are present but workers are sorted according to comparative advantage. In particular, the disproportionate presence of female workers in weeding activities is due not to worker or employer preferences but to comparative advantage and statistical discrimination.

A general model of community formation and human capital accumulation with social spillovers and decentralized school funding is used to analyse the causes of economic segregation and its consequences for equity and efficiency. Significant polarization arises from minor differences in endowments, preferences or access to capital markets. This makes income inequality more persistent across generations, but the same need not be true for wealth. Equilibrium stratification tends to be excessive, resulting in low aggregate surplus. Whether state equalization of school resources can remedy these problems hinges on how purchased, social and family inputs interact in education and in mobility decisions.

We study a positive theory of stagnation and growth aimed at understanding the large variations in growth outcomes across actual economies. The theory points to the fundamental role played by vested interests in determining policies which are key to the growth process: some agents seek to prevent the adoption of new technologies. We develop a model of technology adoption, and show how technological innovation may sow the seeds of its own destruction. In particular, we find that the equilibrium is characterized by a long cycle of stagnation and growth. Over this cycle, incumbent innovators have sufficient political influence that new technologies are prohibited, and only as these incumbents are phased out of the economy will new innovation occur. In formalizing our theory we make a methodological contribution by characterizing dynamic voting equilibria in which voters must forecast the effects of different current policies on future prices and policy outcomes.

This paper explores the effect of policy variability (or frequency of regime switching) on economic growth and welfare. We study a one-sector growth model where investment can be subsidized at either a positive rate or not subsidized at all. We find that the lack of persistence in policies per se need not be welfare reducing and that it is likely to decrease growth. Higher variability implies more frequent changes in consumption and investment. But, by creating a stronger intertemporal link across regimes, variability reduces the fluctuation in investment rates, thus decreasing the magnitude of changes in consumption and increasing welfare.

Convergence to a full-information equilibrium (FIE) in the presence of persistent shocks and asymmetric information about an unknown payoff-relevant parameter θ is established in a classical infinite-horizon partial equilibrium linear model. It is found that, under the usual stability assumptions on the autoregressive process of shocks, convergence occurs at the rate n−1/2, where n is the number of rounds of trade, and that the asymptotic variance of the discrepancy of the full-information price and the market price is independent of the degree of autocorrelation of the shocks. This is so even though the speed of learning θ from prices becomes arbitrarily slow as autocorrelation approaches a unit root level. It follows then that learning the unknown parameter θ and convergence of the equilibrium process to the FIE are not equivalent. Moreover, allowing for non-stationary processes of shocks, the distinction takes a more stark form. Learning θ is neither necessary nor sufficient for convergence to the FIE. When the process of shocks has a unit root, convergence to the FIE occurs but θ can not be learned. When the process is sufficiently explosive and there is a positive mass of perfectly informed agents, θ is learned quickly but convergence to the FIE does not occur.

Do the implications for business cycle issues change when we switch from studying infinitely-lived, representative-agent models to more sophisticated demographic structures with finitely lived agents? This article addresses that question by using a large, overlapping-generations model that is calibrated to U.S. demographic properties, microeconomic evidence, and National Income and Product Accounts. The finding is that the answers obtained are basically the same for the two kinds of models. The article also explores the relative volatility of hours across age groups, an issue that cannot be addressed by using the infinitely-lived, representative-agent abstraction.

To what extent can agents' learning and incomplete information about the "true" underlying model generating stock returns explain findings of excess volatility and predictability of returns in the stock market? In this paper we analyse two models of recursive learning in the stock market when dividends follow a (trend-)stationary autoregressive process. The asymptotic convergence properties of the models are characterized and we decompose the variation in stock prices into rational expectations and recursive learning components with different rates of convergence. A present-value learning rule is found to generate substantial excess volatility in stock prices even in very large samples, and also seems capable of explaining the positive correlation between stock returns and the lagged dividend yield. Self-referential learning, where agents' learning affect the law of motion of the process they are estimating, is shown to generate some additional volatility in stock prices, though of a magnitude much smaller than present value learning

Investment is characterized by costly reversibility when a firm can purchase capital at a given price and sell capital at a lower price. We solve for the optimal investment of a firm that faces costly reversibility under uncertainty and we extend the Jorgensonian concept of the user cost of capital to this case. We define and calculate cU and cL as the user costs of capital associated with the purchase and sale of capital, respectively. Optimality requires the firm to purchase and sell capital as needed to keep the marginal revenue product of capital in the closed interval [cL, cU). This prescription encompasses the case of irreversible investment as well as the standard neoclassical case of costlessly reversible investment.

Consumption data generally indicates that consumption risk is not perfectly diversified across individuals. This paper considers if and when imperfect diversification is a feature of efficient allocations in a symmetric information environment without commitment. It shows that if individuals are sufficiently patient, imperfect diversification is always sub-optimal in the long run; however, if individuals are not so patient, imperfect diversification is always optimal. The paper goes on to demonstrate that the way that history matters in an efficient allocation in a symmetric-information/no-commitment environment can be used to distinguish lack of commitment from other possible rationalizations of imperfect risk sharing, such as efficiency in the presence of asymmetric information.

The authors study a multilateral bargaining procedure that extends A. Rubinstein's (1982) alternating offer game to the case of n players. The procedure captures the notion of consistency in the sense familiar in cooperative game theory and they use it to establish links to the axiomatic theory of bargaining. Copyright 1996 by The Review of Economic Studies Limited.