As patent applications increase, and the range of patentable technologies increases, the length of time it takes for an invention to go through the examination process at the U.S. Patent Office has increased. Concerns over the distributional effects of these changes have been expressed during policy debates. We use data on U.S. patent applications and grants to ask who is affected by longer grant lags. We augment this analysis with interviews of patent examiners, leading to a better understanding of the examination process. Our analysis finds that differences across technology are most important. These differences do not erode over time, suggesting that learning effects alone will not reduce grant lags. Inventor characteristics have statistically significant effects, but the magnitudes are small.

This article examines the relationship between Research & Development (R&D) funding and the production of knowledge by academic chemists. Using articles published, either raw counts or adjusted for quality, we find a strong, positive causal effect of funding on knowledge production. This effect is similar across subsets of universities, suggesting a relatively efficient allocation of R&D funds. Finally, we document a rapid acceleration in the rate at which chemical knowledge was produced in the late 1990s and early 2000s relative to the financial and human resources devoted to its production.

Abstract. Several widely used tests for a changing mean exhibit nonmonotonic power in finite samples due to "incorrect" estimation of nuisance parameters under the alternative. In this paper, we study the issue of nonmonotonic power in testing for changing mean. We investigate the asymptotic power properties of the tests using a new framework where alternatives are characterized as having "large" changes. The asymptotic analysis provides a theoretical explanation to the power problem. Modified tests that have monotonic power against a wide range of alternatives of structural change are proposed. Instead of estimating the nuisance parameters based on ordinary least squares residuals, the proposed tests use modified estimators based on nonparametric regression residuals. It is shown that tests based on the modified long-run variance estimator provide an improved rate of divergence of the tests under the alternative of a change in mean. Tests for structural breaks based on such an estimator are able to remain consistent while still retaining the same asymptotic distribution under the null hypothesis of constant mean.

This study compares two alternative regression specifications for sizing hedge positions and measuring hedge effectiveness: a simple regression on price changes and an error correction model (ECM). We show that, when the prices of the hedged item and the hedging instrument are cointegrated, both specifications yield similar results which depend on the hedge horizon (i.e., the time frame for measuring price changes). In particular, the estimated hedge ratio and regression R 2 will both be small when price changes are measured over short intervals, but as the hedge horizon is lengthened both measures will converge toward one. These results imply that, when prices are cointegrated, a longer hedge horizon will yield an optimal hedge ratio closer to one, while at the same time enhancing the ability to qualify for hedge accounting.The Financial Accounting Standards Board (FASB) has recently released an exposure draft that, if enacted, would lower the requirement from "highly" effective to "reasonably" effective. It is not clear whether or how this change would affect the current practice of requiring the regression R 2 statistic to be at least 0.80. 4 Levy and Sarnat (1984) and Marmer (1986) discuss various drawbacks to the textbook approach. Schneeweis (1981, 1982) and Dale (1981) debate use of a simple regression on price levels versus price changes.

The impacts of two recent changes in US patent policy depend on the length of time it takes for an invention to go through the examination process. Concerns over the distributional effects of these changes were expressed during policy debates. We use data on U.S. patent applications and grants to determine the factors influencing the length of the patent examination process. We augment this analysis with interviews of patent examiners, leading to a better understanding of the examination process. Our analysis finds that differences across technology are most important. Inventor characteristics have statistically significant effects, but the magnitudes are small.