Are differences in firm size transitory or permanent?

An Erratum for this article has been published in Journal of Applied Econometrics 18(2) 2003, 249 Previous empirical work on corporate growth rates using cross‐section or short‐panel econometric techniques suggests that growth rates are random but that some degree of mean reversion exists. This means that size differences between firms are transitory. Another, more natural way to explore the long‐run distribution of firm sizes is to examine data on the growth of particular firms over long periods of time. Using a sample of 147 UK firms observed continually for more than 30 years, our conclusions are that growth rates are highly variable over time and that differences in growth rates between firms do not persist for very long. Further, firms show no tendency to converge to either a common size or to a pattern of stable size differences over time. These results are compared and contrasted with standard approaches that suggest that firms reach and maintain stable positions in a skewed size distribution. Copyright © 2002 John Wiley & Sons, Ltd.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

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.     

Long- and short-term interest rates in 19 countries: Tests of cointegration and parameter instability

This paper examines the long-run relationship between short-term and long-term interest rates (both nominal and real) in 19 countries, and explores the possibility that the relationship is statistically stable using Lc, MeanF, and SupF statistics suggested by Hansen [1992]. Empirical results obtained from various cointegration techniques (Johansen, Phillips and Hansen, Stock and Watson, and Park) and quarterly data (1973–1998) show considerable support for the expectations hypothesis in all countries (except the United Kingdom). In a majority of cases, it is also found that a stable relationship exists between the short-term and long-term interest rates.     

ON ESTIMATING STOCK MARKET VOLATILITY: AN EXPLORATORY APPROACH

Traditional methods of estimating market volatility use daily return observations from a stock index to calculate monthly variance. We break with tradition and estimate stock market volatility using the daily, cross-sectional standard deviation of returns for all firms trading on the New York Stock Exchange and the American Stock Exchange. We find a significantly positive relation between risk and return. Market volatility is estimated to be about half the volatility level previously reported. The intraday, cross-sectional market volatility measure provides findings consistent with risk-return theory.     

The effect of spot and futures trading on stock index market volatility: A nonparametric approach

This article provides empirical evidence on the intraday relation between spot volatility and trading volume in the Spanish stock index futures market. GARCH methodology is used to estimate spot volatility. We analyze the potential relation between spot and futures trading volume and spot volatility by estimating the corresponding conditional density functions as proposed in Quah (1997). Our results reveal no significant link between those variables. Similar findings arise when expected and unexpected volume is considered. Our results suggest that derivative market is not a force behind episodes of significant spot jump volatility. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:841–858, 2003     

MANAGING VENDOR INVENTORY IN A DUAL LEVEL DISTRIBUTION SYSTEM

Collaborative arrangements among members of the supply chain have received a great deal of interest in recent years as a means of reducing costs. One such arrangement is vendor managed inventory (VMI). VMI allows the vendor to make decisions concerning the quantity and timing of deliveries to the retailer. Such an arrangement offers the potential of a more efficient supply chain by removing the negative effects of retail ordering policies. A thorough review of the literature was conducted to identify factors likely to impact the performance of a VMI partnership. Computer simulation was used to study the effects of these factors from both the vendor's and retailer's perspectives. The results lend insight into the performance of VMI and guidance for managers as to the environments in which VMI is most effective.