Conventional tests of the predictability of stock returns could be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional t-test leads to invalid inference and an efficient test of predictability that corrects this problem. Although the conventional t-test is invalid for the dividend–price and smoothed earnings–price ratios, our test finds evidence for predictability. We also find evidence for predictability with the short rate and the long-short yield spread, for which the conventional t-test leads to valid inference.

This paper derives a concept of aggregate real income for a competitive economy in general equilibrium consisting of heterogeneous infinitely lived people and relates it to current and future consumption possibilities. An important characteristic of our measure of income, which we call Real Income, is that deflation is carried out using a consumption deflator rather than any price index of output. We suggest that it may be inappropriate to regard capital gains as income. We also present a coherent treatment of the effects of changes to the terms of trade on Real Income and explain the implications of this for resource-exporting economies.

We study the extent to which U. S. urban development is sprawling and what determines differences in sprawl across space. Using remote-sensing data to track the evolution of land use on a grid of 8.7 billion 30 × 30 meter cells, we measure sprawl as the amount of undeveloped land surrounding an average urban dwelling. The extent of sprawl remained roughly unchanged between 1976 and 1992, although it varied dramatically across metropolitan areas. Ground water availability, temperate climate, rugged terrain, decentralized employment, early public transport infrastructure, uncertainty about metropolitan growth, and unincorporated land in the urban fringe all increase sprawl.

This paper provides a new approach to forecasting time series that are subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks occurring over the forecast horizon, taking account of the size and duration of past breaks (if any) by means of a hierarchical hidden Markov chain model. Predictions are formed by integrating over the parameters from the meta-distribution that characterizes the stochastic break-point process. In an application to U.S. Treasury bill rates, we find that the method leads to better out-of-sample forecasts than a range of alternative methods.

In 2003 the federal-state Medicaid program provided prescription drug coverage to more than 50 million people. To determine the price that it will pay for each drug, Medicaid uses the average private sector price. When Medicaid is a large part of the demand for a drug, this creates an incentive for its maker to increase prices for other health care consumers. Using drug utilization and expenditure data for the top 200 drugs in 1997 and in 2002, we investigate the relationship between the Medicaid market share (MMS) and the average price of a prescription. Our estimates imply that a 10-percentage-point increase in the MMS is associated with a 7 to 10 percent increase in the average price of a prescription. In addition, the Medicaid rules increase a firm's incentive to introduce new versions of a drug in order to raise price. We find empirical evidence that firms producing newer drugs with larger sales to Medicaid are more likely to introduce new versions. Taken together, our findings suggest that government procurement rules can alter equilibrium price and product proliferation in the private sector.

We construct an index of firms' external finance constraints via generalized method of moments (GMM) estimation of an investment Euler equation. Unlike the commonly used KZ index, ours is consistent with firm characteristics associated with external finance constraints. Constrained firms' returns move together, suggesting the existence of a financial constraints factor. This factor earns a positive but insignificant average return. Much of the variation in this factor cannot be explained by the Fama--French and momentum factors. Cross-sectional regressions of returns on our index and other firm characteristics show that constrained firms earn higher returns and that the financial-constraints effect dominates the size effect.

We study the effects of a change in financial aid policy introduced by an anonymous university in 1998. Prior to that time, the university's financial aid packages for low-income students consisted of grants, loans, and campus jobs. After the change, the entire loan portion of the package for low-income students was replaced with grants. We find the program increased the likelihood of matriculation by low-income students by approximately 3 percentage points, although the effect is not statistically significant. The effect among low-income minority students was between 8 and 10 percentage points and statistically significant at the 10% level.

We study the effects of a change in financial aid policy introduced by a Northeastern university in 1998. Prior to that time, the university s financial aid packages for low income students consisted of grants, loans, and campus jobs. After the change, the entire loan portion of the package for low-income students was replaced with grants. We find the program increased the likelihood of matriculation by low-income students by about 3 percentage points, although the effect is not statistically significant. The effect among low-income minority students was about twice that size and statistically significant at the 10 percent level.

The neoclassical growth model is used to identify the short‐run effects of neutral technology shocks, which affect the production of all goods homogeneously, and investment‐specific shocks, which affect only investment goods. The real equipment price, crucial for identifying the investment shocks, experiences an abrupt increase in its average rate of decline in 1982, so the analysis is based on a split sample. On the basis of the preferred specification, the two technology shocks account for 73 percent of hours’ and 44 percent of output’s business cycle variation before 1982, and 38 percent and 80 percent afterward. The shocks also account for more than 40 percent of hours’ and 58 percent of output’s forecast errors over a three‐ to eight‐year horizon in both samples. The majority of these effects are driven by the investment shocks.