MNE competitiveness: A scenario-driven technology transfer construct

To compete effectively, multi-national enterprises (MNEs) must establish market presence in their global rivals' home courts and/or profit sanctuaries. Technology transfer is often used as a means toward that end. The technology adoption decisions of an aggressor MNE and a defender MNE are investigated in a model that features indirect moves and changes in strategy through technology transfer. Each firm may adopt a strategy that incorporates the transfer of high technology or appropriate technology. The strategic decision situation is modelled as a closed-loop sequential equilibrium in discrete time. In contrast to results in the technology adoption literature, the aggressor MNE may successfully transfer technology first, to be imitated later by the defender MNE. This and several other scenarios emerge from the model which, by incorporating the cost of social adjustment and risks involved in technology transfer, ties technology to the competitive interaction of MNEs and specifies conditions for creating competitive advantage through technology, both locally and worldwide.     

THE DETERMINANTS OF ILLEGAL DRUG USE

An extensive set of self-reported survey data exists on illegal drug use. The survey data show that drug use is quite frequent among the younger adult population, relatively infrequent among those of high-school age, and rare among middle-aged and older adults. Drug use varies by occupational category in ways that are difficult to rationalize. This study utilizes a model in which an individual's time is allocated among labor, non-drug consumption, leisure, and drug use, where the individual is cognizant of the effect of drug use on his wages. The study analyzes comparative static results and then uses data from the National Longitudinal Survey of Youth to estimate a probit model of the individual decision to use drugs. The findings of the study are that non-economic factors dominate the decision for both harder drugs and drugs more broadly defined. One must consider this finding tentative, however, since usable drug price data were not available.     

Cointegration Vector Estimation by Panel DOLS and Long‐run Money Demand*

We study the panel dynamic ordinary least square (DOLS) estimator of a homogeneous cointegration vector for a balanced panel of N individuals observed over T time periods. Allowable heterogeneity across individuals include individual‐specific time trends, individual‐specific fixed effects and time‐specific effects. The estimator is fully parametric, computationally convenient, and more precise than the single equation estimator. For fixed N as T→∞, the estimator converges to a function of Brownian motions and the Wald statistic for testing a set of s linear constraints has a limiting χ²(s) distribution. The estimator also has a Gaussian sequential limit distribution that is obtained first by letting T→∞ and then letting N→∞. In a series of Monte‐Carlo experiments, we find that the asymptotic distribution theory provides a reasonably close approximation to the exact finite sample distribution. We use panel DOLS to estimate coefficients of the long‐run money demand function from a panel of 19 countries with annual observations that span from 1957 to 1996. The estimated income elasticity is 1.08 (asymptotic s.e. = 0.26) and the estimated interest rate semi‐elasticity is ?0.02 (asymptotic s.e. = 0.01).     

Regional integration: an empirical assessment of Russia

Using a statistical model of commodity trade, we quantify the evolution of regional economic integration within Russia during 1995–1999, and explore potential determinants of this evolution. Our integration measure exhibits rich regional variation that, when aggregated to the national level, fluctuates substantially over time. In accounting for this behavior, we draw in part on theoretical models that emphasize the potential role of openness to international trade and regional disparities in income in threatening economic integration. Controlling for a host of additional regional- and national-level variables, we find a strong negative correspondence between openness to international trade and internal economic integration.     

The Determinants of Enterprise Risk Management: Evidence From the Appointment of Chief Risk Officers

Enterprise risk management (ERM) has captured the attention of risk management professionals and academics worldwide. Unlike the traditional "silo-based" approach to corporate risk management, ERM enables firms to benefit from an integrated approach to managing risk that shifts the focus of the risk management function from primarily defensive to increasingly offensive and strategic. Despite the heightened interest in ERM, little empirical research has been conducted on the topic. This study provides an initial attempt at identifying the determinants of ERM adoption. We construct a sample of firms that have signaled their use of ERM by appointing a Chief Risk Officer (CRO) who is charged with the responsibility of implementing and managing the ERM program. We use a logistic regression framework to compare these firms to a size- and industry-matched control sample. While our results suggest a general absence of differences in the financial and ownership characteristics of sample and control firms, we find that firms with greater financial leverage are more likely to appoint a CRO. This finding is consistent with the hypothesis that firms appoint CROs to reduce information asymmetry regarding the firm's current and expected risk profile.     

MEASURING HEDGE EFFECTIVENESS FOR FAS 133 COMPLIANCE

Financial Accounting Standard (FAS) 133 requires business entities to document their anticipation of hedge effectiveness in order to qualify for hedge accounting treatment of gains and losses from financial derivatives. In the absence of specific guidelines, the accounting industry has espoused the "80–125" rule for determining hedge effectiveness. But the authors observe that meaningful assessment of anticipated hedge effectiveness must consider two distinct aspects of a firm's hedging strategy: (1) the strength of the hedging relationship, which is determined by the choice of the hedging instrument; and (2) the position taken in the hedging instrument relative to the holdings of the hedged item. They take both aspects of hedging into consideration in developing alternative measures of hedge effectiveness and distinguishing between the potential and attained effectiveness of a particular hedge. This approach enables the user to evaluate the relative merits of alternative hedging strategies to support risk management decisions, and also to document a selected hedging strategy's anticipated effectiveness for purposes of compliance with FAS 133. While the authors endorse a fairly broad interpretation of hedge effectiveness, their approach can also be used in the narrower context of an "80–125" rule.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.