A large factor model for forecasting macroeconomic variables in South Africa

This paper uses large Factor Models (FMs), which accommodate a large cross-section of macroeconomic time series for forecasting the per capita growth rate, inflation, and the nominal short-term interest rate for the South African economy. The FMs used in this study contain 267 quarterly series observed over the period 1980Q1-2006Q4. The results, based on the RMSEs of one- to four-quarter-ahead out-of-sample forecasts from 2001Q1 to 2006Q4, indicate that the FMs tend to outperform alternative models such as an unrestricted VAR, Bayesian VARs (BVARs) and a typical New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model in forecasting the three variables under consideration, hence indicating the blessings of dimensionality.     

Export channel design: The use of foreign distributors and agents

Because many manufacturers are unable to integrate vertically into global distribution, the nonintegrated market entry modes of foreign distributor and agent are frequently used. Unfortunately, little is known about choosing efficiently between distributor and agent because research has only partially examined the importance of transaction and production costs in determining institutional arrangements. To specify efficient channel design, this article develops and tests hypotheses linking the characteristics of export exchange to the cost-minimizing mode of export channel governance. Based on a sample of 269 manufacturers, results suggest that market diversity, type of transaction-specific asset, and production cost economies all affect the choice between foreign-based agents and distributors. The article concludes with the implications of these results for export management and future export research. He received his Ph.D. from Michigan State University. His research interests include distribution strategy and international marketing. He has published in theJournal of Marketing, European Journal of Marketing, Journal of International Business Studies, Journal of Business Research, Industrial Marketing Management, andJournal of Advertising. He serves on the editorial review boards of various professional journals including theJournal of Marketing and theJournal of Business Research. She received her Ph.D. from the University of Maryland. Her research interests include buyer-seller relationships and business-to-business marketing. She has published in theJournal of Business Research, Industrial Marketing Management, Journal of Global Marketing, and in the proceedings of various professional conferences.     

Tax evasion and financial repression

Using a simple overlapping generations framework, calibrated to four Southern European countries, we analyze the relationship between tax evasion, determined endogenously, and financial repression. We show that higher degree of tax evasion within a country, resulting from a higher level of corruption and a lower penalty rate, yields higher degrees of financial repression as a social optimum. However, a higher degree of tax evasion, due to a lower tax rate, reduces the severity of the financial restriction.     

Leveraging Information Across Categories

Companies are collecting increasing amounts of information about their customers. This effort is based on the assumption that more information is better and that this information can be leveraged to predict customers' behavior in a variety of situations and product categories. For example, information about a customer's purchase behavior in one category can be helpful in predicting his potential behavior in a related category, which in turn could help a firm in its cross-selling efforts. In this paper, we present a model to better understand and predict a consumer's purchases and preferences when we may have limited or no information about him in one or more product categories. Conceptually this involves leveraging information from purchases of other consumers in multiple categories as well as partial information (e.g., purchase in one of the categories) of the target consumer. Our approach builds on the pioneering work of (Rossi et al. (1996)) who demonstrate the value of purchase information in the context of a single product category. We present results from an extensive simulation as well as an application on scanner panel data. Our simulation shows many interesting and somewhat surprising results. Specifically, we find that compared to a single-category analysis, a cross-category analysis does not lead to any significant improvement in data likelihood in most cases. Therefore, the single-category analysis of (Rossi et al. (1996)) is even more powerful than previously thought. However, we also find that a cross-category analysis does improve parameter recovery in many situations as compared to a single-category analysis. It is in these conditions that retailers can use cross-category information to better implement micro marketing programs. We demonstrate the transfer of information across categories in an application of two grocery products—Breakfast Foods and Table Syrup. In spite of a reasonable correlation (0.21) in the price parameter across these two categories, our simulation guidelines predict very little benefit of cross-category analysis over single-category analysis. Our empirical results confirm this prediction.     

Misspecified polynomial detrending

This letter shows that substantial errors result in linear detrending of the data when a linear trend is inappropriate. These errors increase without bound with increasing sample size! Also, the reliability of the linear trend is overstated.     

On a Morgenstern-type bivariate gamma distribution

Summary In this paper a Morgenstern-type bivariate gamma distribution has been studied. Its moment generating function has been derived. The distribution of the product and quotient are derived in terms of the modified Bessel function. The results for the independent case follow as special cases. Further the regression function has been analysed, in terms of its deviation from linear regression function.This research was initiated while the first author was a U.N. Consultant under the Statistical Training Program for Africa, visiting the University of Ghana.     

Comparison of SML and GMM estimators for the random coefficient logit model using aggregate data

A simulated maximum likelihood (SML) estimator for the random coefficient logit model using aggregate data is found to be more efficient than the widely used generalized method of moments estimator (GMM) of Berry et?al. (Econometrica 63:841?C890, 1995). In particular, the SML estimator is better than the GMM estimator in recovery of heterogeneity parameters which are often of central interest in marketing research. With the GMM estimator, the analyst must determine what moment conditions to use for parameter identification, especially the heterogeneity parameters. With the SML estimator, the moment conditions are automatically determined as the gradients of the log-likelihood function, and these are the most efficient ones if the model is correctly specified. Another limitation of the GMM estimator is that the product market shares must be strictly positive while the SML estimator can handle zero market share observations. Properties of the SML and GMM estimators are demonstrated in simulated data and in data from the US photographic film market.     

A Fireside Chat with Raj Gupta: What It Takes to Create Long‐Term Value

The chairman of two public companies (and former chair and CEO of Rohm and Haas) draws on his experience as a director of five private and 15 public companies in discussing the challenges and opportunities facing today's corporate boards. Perhaps the most formidable challenge is the pace of technological change, which is making business models ‘in all industries and countries’ obsolete and forcing companies to adapt much more quickly than in the past. Along with the risk of obsolescence is the increase in ‘reputational risk’ associated with an ‘information age’ in which companies are forced to monitor the nearly continuous flow of fact, hearsay, and outright fabrication. The author recommends that public company boards adopt a new ‘partnership’ model. Besides ensuring an ‘ethical tone at the top,’ corporate directors should aim to become partners with the senior management team by playing more active roles in strategic planning, risk management, and the design of performance evaluation and incentive pay systems. In the most striking departure from current practice, the author urges directors to seize the opportunity created by the ‘reconcentration’ of ownership of U.S. public companies by actively engaging large institutional investors in a strategic dialogue about the companies' strengths and vulnerabilities. In so doing, proactive directors can help their management teams preempt shareholder activists and create long‐run value by creating a more effective two‐way channel of communication, one with the potential to give management more confidence when undertaking large strategic investments with longer‐run payoffs.