LIQUIDITY AND ASSET PRICING UNDER THE THREE‐MOMENT CAPM PARADIGM

We examine whether the use of the three‐moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four‐factor model based on Fama–French and Pástor–Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ.     

Exchange rate volatility and its impact on the transaction costs of covered interest rate parity

This paper provides empirical evidence on the linkage between foreign exchange market volatility and daily 90-day covered interest rate parity (CIP) conditions of the three major exchange rates against the US dollar (US$). Markov regime shifting models were utilized to generate time series of volatility regime probabilities and these were used to explain the first and second moments of the daily deviations from and the transaction cost bands around the covered parity conditions. We find a significant positive relationship between the deviations and the regime probabilities, indicating an increasing probability of higher volatility state being associated with rising deviations (both first and second moments) from the parity condition. Similar positive relationship is found for the transaction bands. Rising (falling) probabilities of high (low) volatility regimes increased the first and second moments of the bands. Furthermore, we find a higher volatility state combined with a US$ depreciation is associated with significantly higher volatility in the daily deviations than an appreciation. Also, US$ depreciation is associated with widening transaction bands. This suggests that the level of market uncertainty was higher when the US$ was depreciating.     

Capital structure around the world: The roles of firm- and country-specific determinants

We analyze the importance of firm-specific and country-specific factors in the leverage choice of firms from 42 countries around the world. Our analysis yields two new results. First, we find that firm-specific determinants of leverage differ across countries, while prior studies implicitly assume equal impact of these determinants. Second, although we concur with the conventional direct impact of country-specific factors on the capital structure of firms, we show that there is an indirect impact because country-specific factors also influence the roles of firm-specific determinants of leverage.     

Characterizations of negative multinomial distributions based on conditional distributions

In this paper characterizations of negative multinomial distributions based on conditional distributions have been studied.     

Remote control and maintenance outsourcing networks and its applications in supply chain management

The paper analyzes the impact of e-business technologies on maintenance management and supply chain operations. The aim of this work is to investigate the network organization level of supply chains in case of remote maintenance application and to understand how maintenance policies are coupled with information technology (IT) solutions. To this purpose two literature reviews are presented: firstly, on the supply chain and network integration, and then on the evolution of maintenance using information technology. Following this, the paper present four specific industrial case-studies of eMRO network organisation. They have been chosen as reference models from a set of practical applications and pilot tests performed by the authors in different production sectors in the last 5 years. Technology complexity environments, maintenance outsourcing level, and supply chain integration context are discussed for each case-studies with particular regards to the profitable forms of collaboration provided by the introduction of IT and the Web. This analysis work toward the development of a framework useful to: (1) classify different e-maintenance systems and understand the relationships between the different members of the network, and (2) identify the variables which can influence the introduction and development of the systems.     

Nonlinearities and heterogeneity in environmental quality: An empirical analysis of deforestation

We use a panel data set of 59 developing countries over the 1972–1994 period to study the deforestation process. Relying on both parametric and semiparametric models, we examine nonlinearities and heterogeneity in the deforestation process. We first study the existence of an Environmental Kuznets Curve (EKC) and then analyze determinants of deforestation. Our data sample provides no evidence of an EKC. We also find that political institution failures may worsen the deforestation process in developing countries.     

Distribution Dynamics of CO<Subscript>2</Subscript> Emissions

This paper uses nonparametric methods to examine the convergence in CO₂ emissions per capita on a sample of 100 countries for the period 1966–1996. Industrial countries show a convergence pattern. However, there is little evidence of convergence for the whole sample.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Estimating the gravity model when zero trade flows are frequent and economically determined

ABSTRACT

Since the 1950s, we have known that the presence of zero-valued dependent variables can seriously bias econometric estimates whether the zeros are included or excluded. Yet the widely-used gravity model is frequently estimated on samples that include large fractions of zeros. An influential paper by Santos Silva and Tenreyro – based on simulations that include no economically-determined zeros – concludes that the bias problems resulting from zeros and those resulting from heteroscedasticity and nonlinearity can be solved using the Poisson Pseudo-Maximum-Likelihood (PPML) model including the zero values. This paper begins by adapting the Santos Silva and Tenreyro experimental design to include economically-determined zeros to see whether this conclusion continues to hold. With this design, it finds that alternative estimators have lower bias than PPML. Changing to a Monte Carlo design that replicates the much-higher real-world frequency of predicted values near zero restores the finding of lower bias with the PPML estimator. The results highlight the need for very careful design of Monte Carlo experiments when evaluating alternative estimators of the gravity model.