Relationship of direct nursing care hours to DRG and severity of illness

Great variation in nursing resource use is documented within DRGs. Much of this variation may be explained by patient severity of illness. Variance in nursing resource use within DRGs can be reduced by using a severity of illness instrument to score patients.     

Copyright Damages and Statistics

This paper discusses the statistical issues that arise in conducting an economic damages analysis in the context of a litigation matter involving copyrights. Calculating damages in copyright cases turns out to be a natural application for econometric modelling methods. Surprisingly, elementary statistical issues can be a source of significant debate between the experts in such matters. In this paper, we present a case study and illustrate how issues such as interpretation of p -values and what "rejection of the null hypothesis" really "means" in such matters.     

Improved estimation of portfolio value‐at‐risk under copula models with mixed marginals

Portfolio value‐at‐risk (PVAR) is widely used in practice, but recent criticisms have focused on risks arising from biased PVAR estimates due to model specification errors and other problems. The PVAR estimation method proposed in this article combines generalized Pareto distribution tails with the empirical density function to model the marginal distributions for each asset in the portfolio, and a copula model is used to form a joint distribution from the fitted marginals. The copula–mixed distribution (CMX) approach converges in probability to the true marginal return distribution but is based on weaker assumptions that may be appropriate for the returns data found in practice. CMX is used to estimate the joint distribution of log returns for the Taiwan Stock Exchange (TSE) index and the associated futures contracts on SGX and TAIFEX. The PVAR estimates for various hedge portfolios are computed from the fitted CMX model, and backtesting diagnostics indicate that CMX outperforms the alternative PVAR estimators. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:997–1018, 2006     

Regulatory Monitoring and the Impact of Bank Holding Company Dividend Changes on Equity Returns

This paper examines the impact of announcements of dividend changes by bank holding companies (BHCs) on equity returns. Many empirical studies of dividend behavior reveal positive market responses to dividend increases, which have been interpreted as confirmation of the signalling theory of dividend behavior. These studies typically focus on “large” changes, however. We argue that BHCs allow for a stronger test of signalling theory because regulatory monitors, in effect, “certify” dividend signals. Consequently, even “small” dividend increases should result in positive abnormal equity returns. Using the event study methodology, our results generally confirm this hypothesis for a sample covering the period 1973–1987.     

PRINCIPAL AND AGENCY TRADES BY STOCKBROKERS ARE COMPLEMENTARY: THE WELFARE EFFECTS OF DEREGULATING AGENCY TRADING AND BANNING PRINCIPAL TRADES

This paper models the demand for stockbrokers' services in Australia, consisting of two related services, agency trades and principal trades. The relationship between agency and principal trades is estimated. The results indicate that the two services are complements rather than substitutes. Using unique accounting information, a model of agency and principal trading activities is estimated to determine the welfare effects of (i) deregulating brokerage commissions and (ii) a ban on principal trading by brokers. The results show a sizeable welfare gain to investors (amounting to about 60% of the gross revenue of brokers) stemming from deregulation of the minimum charge for agency trades. The loss in profitability by brokers due to deregulation is also computed and shown to be negligible. The results also show that due to complementarity, a ban on principal trading, even with deregulation of agency trading, can impose an arbitrarily high cost on investors which could, in principle, offset the gains from agency deregulation.     

Technology Transfer and Learning

Despite the fact that international technology transfer has been widely studied its management still encounters many difficulties. To fully understand the issues that are relevant to the process of transferring production technology, it is necessary to determine the important factors that influence this process. Learning curves are often used as a means of determining the time required to become familiar with a transferred technology. The cases discussed in this paper have all employed learning curves, which were established at the outset of the transfer process and which turned out to be incorrect. As a consequence the envisaged efficiencies were not obtained. This phenomenon is partly due to the fact that when technology is transferred to a relatively inexperienced 'destination company', the curve is established based on the circumstances of the 'source company'. The case study findings lead to the conclusion that to establish a realistic curve a more comprehensive method is required than simply basing anticipated performance on that achieved at the source company.     

A Cross‐national Comparison of R&D Expenditure Decisions: Tax Incentives and Financial Constraints*

We provide evidence on the impact of tax incentives and financial constraints on corporate R&D expenditure decisions. We contribute to extant research by comparing R&D expenditures in the United States and Canada, thereby exploiting the differences in the two countries' R&D tax credit mechanisms and generally accepted accounting principles. The two tax incentive mechanism designs are consistent with differing views of the degree of financial constraints faced by firms in these economies. Our sample also allows us to explore the effects of capitalizing R&D on Canadian firms. Employing a matched design, we document relations between tax credit incentives and R&D spending consistent with both Canadian and U.S. public companies responding as though they are not financially constrained. We estimate that the Canadian credit system induces, on average, $1.30 of additional R&D spending per dollar of taxes forgone while the U.S. system induces, on average, $2.96 of additional spending. We also find that firms that capitalize R&D costs in Canada spend, on average, 18 percent more on R&D. Collectively, this evidence is important to the ongoing debates in both countries concerning the appropriate design of incentives for R&D and is consistent with the assumptions found in the U.S. tax credit system, but not those found in the Canadian system.