Gains from Corporate Multinationalism: Evidence from the China Experience

This paper examines the valuation impact of U.S. multinational corporations' expansion into the Peoples Republic of China (PRC during 1979 to 1987. The market response to the announcement of a firm's initial entry into the PRC is found to be positive and statistically significant, suggesting that expansion into China was a value-enhancing activity. Equity joint venture modes of entry are found to result in greater shareholder gains than nonequity expansion modes. The influence of degree of multinationality, market share, growth, and technology-related variables on the size of shareholder gains is also analyzed.     

A structural model of sales-force compensation dynamics: Estimation and field implementation

We present an empirical framework to analyze real-world sales-force compensation schemes, and report on a multi-million dollar, multi-year project involving a large contact lens manufacturer at the US, where the model was used to improve sales-force contracts. The model is built on agency theory, and solved using numerical dynamic programming techniques. The model is flexible enough to handle quotas and bonuses, output-based commission schemes, as well as “ratcheting” of compensation based on past performance, all of which are ubiquitous in actual contracts. The model explicitly incorporates the dynamics induced by these aspects in agent behavior. We apply the model to a rich dataset that comprises the complete details of sales and compensation plans for the firm’s US sales-force. We use the model to evaluate profit-improving, theoretically-preferred changes to the extant compensation scheme. These recommendations were then implemented at the focal firm. Agent behavior and output under the new compensation plan is found to change as predicted. The new plan resulted in a 9% improvement in overall revenues, which translates to about $12 million incremental revenues annually, indicating the success of the field-implementation. The results bear out the face validity of dynamic agency theory for real-world compensation design. More generally, our results fit into a growing literature that illustrates that dynamic programming-based solutions, when combined with structural empirical specifications of behavior, can help significantly improve marketing decision-making, and firms’ profitability.     

Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables

This article proposes using an expanded form of the Johnson S_U family as a way to approximate nonnormal distributions in regression models. The distribution is one of the few that allows modeling heteroskedasticity and autocorrelation. The technique is evaluated with Monte Carlo simulation and illustrated through an empirical model of the West Texas cotton basis. Given nonnormality, this technique can substantially reduce the variance of slope parameter estimates relative to least squares procedures.     

Return Linkages between Dual Listings under Arbitrage Restrictions: A Study of Indian Stocks and Their London Global Depositary Receipts

We examine the linkages between returns on Indian global depositary receipts (GDRs) in London and their underlying stocks in India. GDR returns are sensitive to returns observed earlier in India. This sensitivity is more pronounced for more liquid GDRs. Although arbitrage is not feasible for GDRs that sell at a premium, these GDRs are, nevertheless, sensitive to Indian returns. The sensitivity is greater for GDRs selling at a discount, where costly arbitrage is feasible. GDR returns have a significant but small effect on subsequent returns of the underlying stocks, with more liquid GDRs having a slightly greater impact.     

An augmented P-star model of Indian inflation

ABSTRACT

An augmented P-Star model is estimated and tested to identify the drivers of inflation in India. The model includes monetary and non-monetary factors, demand-pull and cost-push factors, and domestic as well as foreign factors. The results show that inflation in India is driven by a combination of monetary factors and non-monetary factors, some of which affect inflation on the supply side while others operate on the demand side. It turns out, however, that inflation in India is determined more by domestic rather than foreign factors.     

Tracking technology trajectory through regression modelling: a retrospective techno-analysis

A significant number of studies have been conducted to forecast the expanding market and evaluate new generation smartphone technologies. However, no such study has been witnessed so far that could forecast the release time of these technologies. The purpose of the paper is to test the forecasting capabilities of stepwise regression in forecasting the smartphones commercialisation time. This technique predicts the release time of smartphones released in 2006 (belonging to the second generation of smartphones) and 2007 (belonging to the third generation of smartphones). The stepwise regression approach based on 12 year data set from 1994 to 2005 determines whether it provides a superior fitting and forecasting performance. The validation approach applied for the first- and second-generation smartphones will benefit future researchers and practitioners in understanding that a regression model developed on the basis of one generation may not give accurate results for the next generation, owing to the fact that technological developments are multi-folded.     

Exploiting Mobile Technology for Achieving Supply Chain Integration in Indian Retail

For decades supply chain coordination has been subject to research interest, and technology has been seen as an agent that accelerates this process. In developing countries, with far-flung markets and unorganized distribution networks, using technology for improving supply chain performances and accessing information is not an easy task. The research was directed to understand if mobile technology is being used by downstream supply chain partners for information sharing and thus improving supply chain performances. Findings suggest that supply chain integration with suppliers and customers is done through extensive use of mobile networks.     

Robust firm pricing with panel data

Firms often have imperfect information about demand for their products. We develop an integrated econometric and theoretical framework to model firm demand assessment and subsequent pricing decisions with limited information. We introduce a panel data discrete choice model whose realistic assumptions about consumer behavior deliver partially identified preferences and thus generate ambiguity in the firm pricing problem. We use the minimax-regret criterion as a decision-making rule for firms facing this ambiguity. We illustrate the framework’s benefits relative to the most common discrete choice analysis approach through simulations and empirical examples with field data.     

Assessing and forecasting technology dynamics in smartphones: a TFDEA approach

Over the last 20 years, the smartphone technologies at the device level have undergone tremendous change. This paper puts forward a framework to characterise, assess and forecast the smartphone technologies at the device level. The study assesses and forecasts the technological advancement observed in smartphones using technology forecasting using data envelopment analysis with an objective to evaluate the technological rate of change in the device. A quarterly data set comprising 31 quarters from 2007 to 2014 was analysed for smartphone releases in a particular price range. For the validation purpose, the analysis was designed to set the point of forecasting somewhere in 2012 using the data set between 2007 and 2012, so as to forecast the technologies thereon till 2014. The results indicate that the rate of technological change in smartphones is accelerating.     

Crop-Yield Distributions Revisited

This article revisits the issue of crop-yield distributions using improved model specifications, estimation, and testing procedures that address the concerns raised in recent literature, which could have invalidated previous findings of yield nonnormality. It concludes that some aggregate and farm-level yield distributions are nonnormal, kurtotic, and right or left skewed, depending on the circumstances. The advantages of utilizing nonnormal versus normal probability distribution function models, and the consequences of incorrectly assuming crop-yield normality are explored.