We analyze the theoretical foundations of the efficient market hypothesis by stressing the efficient use of information and its effect upon price volatility. The “random walk” hypothesis assumes that price volatility is exogenous and unexplained. Randomness means that a knowledge of the past cannot help to predict the future. We accept the view that randomness appears because information is incomplete. The larger the subset of information available and known, the less emphasis one must place upon the generic term randomness. We construct a general and well accepted intertemporal price determination model, and show that price volatility reflects the output of a higher order dynamic system with an underlying stochastic foundation. Our analysis is used to explain the learning process and the efficient use of information in our archetype model. We estimate a general unrestricted system for financial and agricultural markets to see which specifications we can reject. What emerges is that a system very close to our archetype model is consistent with the evidence. We obtain an equation for price volatility which looks a lot like the GARCH equation. The price variability is a serially correlated variable which is affected by the Bayesian error, and the Bayesian error is a serially correlated variable which is affected by the noisiness of the system. In this manner we have explained some of the determinants of what has been called the “randomness” of price changes.

Wages are positively related to firm size. This relation was discovered by Henry L. Moore (1911) and later confirmed by, among others, Charles Brown and James Medoff (1989). The wage premium associated with working at a larger firm or plant is ubiquitous, but its magnitude varies across countries and over time. The reason for a size-related wage premium is harder to pin down. Paying supernormal wages to deter shirking, thereby saving monitoring costs, seems plausible, but a closer examination has led us to reject this explanation (Oi and Idson, 1999). At a big firm, the workplace is safer, and fringes are superior, so that these factors cannot be the source of a positive premium. It must be something else such as work effort. The theory that we advance is that employees at larger firms are more productive and hence command higher wages in a competitive labor market. The shape of the size–wage relation depends on technology, worker preferences, and working conditions other than size. It will change over time and across occupations.

Random utility models (RUMs) are used in the literature to model consumer choices from among a discrete set of alternatives, and they typically impose a constant marginal utility of income on individual preferences. This assumption is driven partially by the difficulty of constructing welfare estimates in models with nonlinear income effects. Recently, McFadden (1995) developed an algorithm for computing these welfare impacts using a Monte Carlo Markov chain simulator for generalized extreme-value variates. This paper investigates the empirical consequences of nonlinear RUMs in the case of sportfishing modal choice, while refining and contrasting the available methods for welfare estimation.

This paper examines segregation in American cities from 1890 to 1990. We divide the century into three time periods. From 1890 to 1940, ghettos were born as blacks migrated to urban areas and cities developed vast expanses filled with nearly exclusively black housing. From 1940 to 1970, black migration continued and ghettos expanded. Since 1970, there has been a decline in segregation as blacks have moved to suburban areas and central cities have become less segregated. Across all of these time periods there is a strong positive relation between urban population or density and segregation. We then examine why segregation has varied so much over time. We find evidence that the mechanism sustaining segregation has changed. In the mid-20th century taken by whites to exclude blacks from their neighborhoods. By 1990, these legal barriers enforcing segregation had been replaced by decentralized racism, where whites pay more than blacks to live in predominantly white areas.

Economists have long suggested that nominal product prices are changed infrequently because of fixed costs. In such a setting, optimal price adjustment should depend on the state of the economy. Yet, while widely discussed, statedependent pricing has proved difficult to incorporate into macroeconomic models. This paper develops a new, tractable theoretical state-dependent pricing framework. We use it to study how optimal pricing depends on the persistence of monetary shocks, the elasticities of labor supply and goods demand, and the interest sensitivity of money demand.

This study compares the pre‐ and postprivatization financial and operating performance of 85 companies from 28 industrialized countries that were privatized through public share offerings for the period from 1990 through 1996. We document significant increases in profitability, output, operating efficiency, and dividend payments—and significant decreases in leverage ratios—for our full sample of firms after privatization, and for most subsamples examined. Capital expenditures increase significantly in absolute terms, but not relative to sales. Employment declines, but insignificantly. Combined with results from two previous, directly comparable studies, these findings strongly suggest that privatization yields significant performance improvements.

This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. Our approach employs series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. We derive consistency and asymptotic normality results for our estimator, including optimal convergence rates. Finally we present an empirical example, based on the relationship between the hourly wage rate and annual hours worked, which illustrates the utility of our approach.

Philip J. Lee, Stephen L. Taylor, Terry S. Walter, IPO Underpricing Explanations: Implications from Investor Application and Allocation Schedules, The Journal of Financial and Quantitative Analysis, Vol. 34, No. 4 (Dec., 1999), pp. 425-444

We examine the effect of discount rate changes on stock market returns, volatility, and trading volume using intraday data. Equity returns generally respond negatively and significantly to the unexpected announcements; however, the effect of expected changes on equity returns is insignificant. Furthermore, our results indicate that equity prices respond to announcements within the trading period/hour after the information release. An indication of a return reversal is too small to cover the full transaction costs. Unexpected discount rate changes also contribute to higher market volatility although the volatility is short-lived. Similarly, unexpected changes in discount rates induce larger trading volume while expected changes do not. Abnormal trading volume occurs only in period t. Our results also support the notion that unexpected changes in the discount rates impact market returns irrespective of the Federal Reserve operating procedures.

This paper examines the roles played by innovations identified from a simple four-variable VAR characterized by cointegration. Using knowledge of cointegration rank and “textbook” relations that link macroeconomic aggregates, we identify distinct “real” and “nominal” innovations that dictate the long-run behavior of the model. We also examine the explanatory power of transitory innovations that are orthogonal to these permanent shocks. One of the permanent shocks displays all the characteristics of a technology or “supply” innovation, while one of the transitory innovations—identified by imposing short-run price rigid-ity—is interpretable as a “demand” side impulse. The permanent nominal shock bears the imprint of an innovation in aggregate inflation expectations. Historical decomposition and comparison with variables that are external to the model reveals the relative importance of the shocks at various episodes.