Characterization of the Walrasian equilibria of the assignment model

We study the assignment model where a collection of indivisible goods are sold to a set of buyers who want to buy at most one good. We characterize the extreme and interior points of the set of Walrasian equilibrium price vectors for this model. Our characterizations are in terms of demand sets of buyers. Using these characterizations, we also give a unique characterization of the minimum and the maximum Walrasian equilibrium price vectors. Also, necessary and sufficient conditions are given under which the interior of the set of Walrasian equilibrium price vectors is non-empty. Several of the results are derived by interpreting Walrasian equilibrium price vectors as potential functions of an appropriate directed graph.     

Risk premia in forward foreign exchange rates: a comparison of signal extraction and regression methods

We investigate possible presence of time-varying risk premia in forward pound, yen, and Euro monthly exchange rates versus the US dollar over the last two decades. We study this issue using regression techniques and separately using a signal plus noise model. Our models account for time-varying volatility and non-normality in the observed series. Our regression model rejects the hypothesis that the forward rate is an unbiased predictor of future spot exchange rate, indicating the existence of time-varying risk premium under rational expectations. Our signal plus noise model reveals a time-varying risk premium component in yen and Euro. The same model provides evidence for the presence of risk premium in pound over a shorter sample period, though not over the entire sample. We conclude that risk premia exist, although we may fail to detect these for some currencies over specific time periods.     

Jumps in cross‐sectional rank and expected returns: a mixture model

We propose a new nonlinear time series model of expected returns based on the dynamics of the cross‐sectional rank of realized returns. We model the joint dynamics of a sharp jump in the cross‐sectional rank and the asset return by analyzing (1) the marginal probability distribution of a jump in the cross‐sectional rank within the context of a duration model, and (2) the probability distribution of the asset return conditional on a jump, for which we specify different dynamics depending upon whether or not a jump has taken place. As a result, the expected returns are generated by a mixture of normal distributions weighted by the probability of jumping. The model is estimated for the weekly returns of the constituents of the SP500 index from 1990 to 2000, and its performance is assessed in an out‐of‐sample exercise from 2001 to 2005. Based on the one‐step‐ahead forecast of the mixture model we propose a trading rule, which is evaluated according to several forecast evaluation criteria and compared to 18 alternative trading rules. We find that the proposed trading strategy is the dominant rule by providing superior risk‐adjusted mean trading returns and accurate value‐at‐risk forecasts. Copyright © 2008 John Wiley & Sons, Ltd.     

Securities laws in the host countries and the capital structure of US multinationals

We examine whether securities laws in the host countries influence the capital structure choice of United States (US) multinational corporations. We develop firm-level global indices to classify each corporation in terms of its exposure to the security laws that govern the rights of security holders in the countries where it has subsidiaries. The results show that the use of long-term debt is positively related to the firm's global standing in terms of common law legal origin, burden of proof, investor protection, disclosure requirements, and public enforcement. The securities laws in a country affect the capital structure of multinational corporations that has subsidiaries in that country.     

Markov-switching model selection using Kullback–Leibler divergence

In Markov-switching regression models, we use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. Specifically, we derive a new information criterion, Markov switching criterion (MSC), which is an estimate of KL divergence. MSC imposes an appropriate penalty to mitigate the over-retention of states in the Markov chain, and it performs well in Monte Carlo studies with single and multiple states, small and large samples, and low and high noise. We illustrate the usefulness of MSC via applications to the U.S. business cycle and to media advertising.     

The core of some location games

An important problem in Location Theory is that of assigning plants to locations in an optimal manner. In the context of this problem, recognizing interplant transportation costs, Koopmans and Beckmann (1957) introduced the Quadratic Assignment Problem (QAP). It is shown in this paper that when the QAP is formulated as a cooperative location game, its core may be empty. By contrast, the core of the game corresponding to thelinear assignment problem (where transportation costs are disregarded) is assured to be non-empty. Some conditions under which the core is non-empty are discussed.I am grateful to two anonymous referees of this journal for their comments.     

Optimal univariate inflation forecasting with symmetric stable shocks

Monthly inflation in the United States indicates non-normality in the form of either occasional big shocks or marked changes in the level of the series. We develop a univariate state space model with symmetric stable shocks for this series. The non-Gaussian model is estimated by the Sorenson–Alspach filtering algorithm. Even after removing conditional heteroscedasticity, normality is rejected in favour of a stable distribution with exponent 1·83. Our model can be used for forecasting future inflation, and to simulate historical inflation forecasts conditional on the history of inflation. Relative to the Gaussian model, the stable model accounts for outliers and level shifts better, provides tighter estimates of trend inflation, and gives more realistic assessment of uncertainty during confusing episodes. © 1998 John Wiley & Sons, Ltd.     

A Hierarchical Marketing Communications Model of Online and Offline Media Synergies

We propose a new hierarchical model of online and offline advertising. This model incorporates within-media synergies and cross-media synergies and allows higher-order interactions among various media. We derive the optimal spending on each medium and the optimal total budget. We also develop three hypotheses on the effects of within- and across-media synergies on both the total budget and its allocation. We estimate media effectiveness as well as the within- and cross-media synergies of offline (television, print, and radio) and online (banners and search) ads using market data for a car brand. We show that both types of synergies —within-media (i.e., intra-offline) and cross-media (online-offline)— exist. We show how within- and cross-media synergies boost the total media budget and online spending due to synergies of the online media with various offline media.     

Can the small dairy farm remain competitive in US agriculture?

Smaller dairy farms in the US are observed to have higher costs than larger farms, and whether those higher costs are due to technology or inefficiency has implications for policy to address the small farm. If high cost of production on smaller farms is due to a higher cost frontier, then to make small farms competitive would require research to devise and design technology that is suitable for small farms. If instead high cost is due to inefficiency, then educational approaches are needed to ensure small dairy farms use technology efficiently. To determine the cause of higher costs on small farms, the cost of milk production by farm size was decomposed into frontier and efficiency components with a stochastic cost curve using data on USA dairy farms. Although the frontier cost of production decreases with farm size, that cost reduction is not as pronounced as a cost curve that includes inefficiency. The higher cost of production on many smaller farms is caused by inefficiency rather than technology.