Management Risk Incentives and the Readability of Corporate Disclosures

Managers with higher risk incentives (greater options vega) issue less readable disclosures. Firms in the top quartile of vega file annual reports that are about 15.4% more voluminous than those in the bottom quartile. The effect of vega on obfuscation remains after controlling for firm risk, operating complexities, accounting and auditor choices, chief executive officer changes, and an exogenous shock to option compensation. This effect is tempered by higher institutional ownership, lower management entrenchment, and greater analyst following. Obfuscation benefits managers by increasing return volatility (option value) and allowing greater earnings management. These findings document a new link between options and disclosure transparency.     

Managerial risk-taking incentives and non-GAAP earnings disclosures

We investigate the association between risk-taking incentives provided by stock-based compensation arrangements and non-GAAP financial disclosures. Controlling for compensation to stock price sensitivity, we find that managers with higher compensation to stock volatility sensitivity (vega) are more likely to be associated with voluntary non-GAAP earnings information disclosures. In addition, higher-vega managers are found to be associated with more frequent and less opportunistic non-GAAP earnings information disclosures. Robust to alternative specifications and estimations, our findings suggest that compensation arrangements can encourage managers to make more, higher-quality voluntary non-GAAP disclosures.     

The effects of standardized tax rates,average tax rates,and the distribution of income on tax progressivity

This study examines the changes in US individual income tax progressivity over the 1986–2003 period using the indexes developed by [Kakwani, N.C., 1976. Measurement of tax progressivity: An international comparison. Economic Journal 87(March), 71–80]. Although progressivity over this time frame has generally been studied in the literature, we provide additional insights by decomposing the changes in index values to account for the effects of concurrent changes in the standardized tax rates, average tax rates, and the income distribution. The decomposition should prove to be particularly useful when different summary indexes lead to conflicting conclusions about progressivity changes, as is often the case. From a policy standpoint, we show that it is the standardized tax rates, a derivative of the legislated tax rates, which need to be monitored and managed to offset the negative progressivity effects of increasing before-tax income inequality.     

Modeling Dependencies in Brand Choice Outcomes Across Complementary Categories

We build an econometric model of a household's contemporaneous brand choice outcomes in complementary product categories. This model explicitly captures cross-category dependencies in brand choice outcomes of a household. Such dependencies have not been modeled in existing multi-category demand models.Our model accommodates cross-category dependencies that arise on account of three component effects: (1) complementarity due to the additional utility that a household derives from the joint purchase of brands in complementary categories, (2) marketing spillovers due to the effects of brands’ prices in one category affecting the households’ latent utilities for brands in the complementary category, (3) unobserved dependencies due to correlations in households’ latent utilities for brands across categories.We estimate our proposed multi-category brand choice model using scanner panel data on cake mix and frosting categories. We find that complementarity accounts for the vast majority of the estimated cross-category effects in demand. We also find that as much as 55 percent of the total retail profit impact of price promotions arise on account of brand-level (focus of our study), as opposed to category-level (focus of previous studies), dependencies in household demand. Finally, we propose an easily interpretable visual representation – Largess and Free-Ride Plot – of cross-category price elasticities that summarizes the differential abilities of brands to influence, or be influenced by, brands in the complementary category.     

The Indirect Impact of Price Deals on Households’ Purchase Decisions Through the Formation of Expected Future Prices

We examine the indirect impact of price deals, which occurs through the formation of expected future prices, on households’ purchase decisions. Two competing learning processes of households’ formation of expected future deals that lead to opposite predictions are proposed. Under a deal-probability learning process, a current deal on a brand raises households’ expectations of a deal on the same brand in the immediate future, while under a deal-timing learning process, a current deal on a brand lowers households’ expectations of a deal on the same brand. We embed each learning specification within a comprehensive econometric framework that simultaneously examines three purchase decisions – incidence, brand choice and quantity – at the household level, while explicitly correcting for two sources of selectivity bias in discrete quantity outcomes. We estimate the proposed model using scanner panel data on paper towels, and find that (1) the deal-probability learning process better describes how households incorporate the deal information into the formation of future price expectations compared to the deal-timing learning process; (2) the indirect impact of price deals is greater for brand-loyals than for brand-switchers; (3) the indirect impact of price deals is greater for larger families, heavy users, less educated and less employed households, and infrequent shoppers. We also show that ignoring the indirect impact of price deals severely overstates the sales effects.     

Too close to be similar: Product and price competition in retail gasoline markets

We examine how product and pricing decisions of retail gasoline stations depend on local market demographics and the degree of competitive intensity in the market. We are able to shed light on the observed empirical phenomenon that proximate gasoline stations price very similarly in some markets, but very differently in other markets. Our analysis of product design and price competition between firms integrates two critical dimensions of heterogeneity across consumers: Consumers differ in their locations and in their travel costs, as in models of horizontal differentiation. They also differ in their relative preference or valuations for product quality dimensions, in terms of the offered station services (such as pay-at-pump, number of service bays or other added services), as in models of vertical differentiation. We find that the degree of local competitive intensity and the dispersion in consumer incomes are sufficient to explain variations in the product and pricing choices of competing firms. Closely located retailers who face sufficient income dispersion across consumers in a local market may differentiate on product design and pricing strategies. In contrast, retailers that are farther apart from each other may adopt similar product design and pricing strategies if the market is relatively homogeneous on income. Using empirical survey data on prices and station characteristics gathered across 724 gasoline stations in the St. Louis metropolitan area, and employing a multivariate logit model that predicts the joint probability of stations within a local market differentiating on product design and pricing strategies as a function of market demographics and local competitive intensity, we find strong support for the central implications of the theory.

To Price Discriminate or Not: Product Choice and the Selection Bias Problem

In this paper, we investigate a gasoline station's incentive to price-discriminate by selling full-service gasoline as well as self-service gasoline. Unlike previous research, we explicitly model a firm's incentive to price discriminate by choosing to be either single-product or multi-product as a function of market and station characteristics. This allows us to make two contributions to research in the area: First, we highlight the importance of accounting for self-selectivity considerations that can arise in an empirical analysis of price discrimination that is based on market data. Second, we are able to show how the product and pricing choices of firms depend upon the market characteristics.Using cross-sectional survey data on prices, station and market characteristics for 198 gasoline stations in the Greater Saint Louis area, we estimate a switching regression model of station decisions. Specifically, we employ a binary probit framework that models a station's decision to price-discriminate through the choice of the station-type as a function of market and station characteristics. We then estimate conditional linear regressions with self-selectivity corrections for the station's choice of prices. We show that incorrect inferences about the incentive to price discriminate and about the differences in the prices charged between single-product and multi-product stations would result if the endogeneity in the choice of the station-type were ignored in the estimation. The empirical analysis shows that a larger income spread in the market implies a greater likelihood of the gasoline station being multi-product. In addition, we have support for the various within firm and across firm price differentials as predicted by the theory of price discrimination.     

Structural Applications of the Discrete Choice Model

A growing body of empirical literature uses structurally-derived economic models to study the nature of competition and to measure explicitly the economic impact of strategic policies. While several approaches have been proposed, the discrete choice demand system has experienced wide usage. The heterogeneous, or mixed, logit in particular has been widely applied due to its parsimonious structure and its ability to capture flexibly substitution patterns for a large number of differentiated products.We outline the derivation of the heterogeneous logit demand system. We then present a number of applications of such models to various data sources. Finally, we conclude with a discussion of directions for future research in this area.     

Interorganizational processes in buyer–supplier dyads: An information intensity perspective

In an increasingly global business environment, organizations interact with partners, suppliers and customers who are geographically spread and exchange information regularly. Without a robust information technology infrastructure, the speed and effectiveness of this information exchange is limited. Business-to-business (B2B) electronic business applications are a class of interorganizational information systems (IOIS) that facilitate such information exchange arising out of interorganizational processes (IOPs). The success of any e-business initiative depends on the successful implementation and the actual use of such IOIS. This study uses the concept of information intensity (II) to identify the information sharing requirements arising from IOPs, thus presenting opportunities for B2B Web site use, with specific reference to organization-specific customer-facing and supplier-facing IOIS. We use data from four buyer–supplier dyads, eight medium- to large-scale organizations in the Indian context and identify a generic set of dominant IOPs in buyer–supplier interactions. Through these we present the sources of II in IOPs along three dimensions – complexity, uncertainty and ambiguity which influence the feature set in the IOISs. We conclude with implications for IOIS design, implementation and use.