Exact Bayesian modeling for bivariate Poisson data and extensions

Bivariate count data arise in several different disciplines (epidemiology, marketing, sports statistics just to name a few) and the bivariate Poisson distribution being a generalization of the Poisson distribution plays an important role in modelling such data. In the present paper we present a Bayesian estimation approach for the parameters of the bivariate Poisson model and provide the posterior distributions in closed forms. It is shown that the joint posterior distributions are finite mixtures of conditionally independent gamma distributions for which their full form can be easily deduced by a recursively updating scheme. Thus, the need of applying computationally demanding MCMC schemes for Bayesian inference in such models will be removed, since direct sampling from the posterior will become available, even in cases where the posterior distribution of functions of the parameters is not available in closed form. In addition, we define a class of prior distributions that possess an interesting conjugacy property which extends the typical notion of conjugacy, in the sense that both prior and posteriors belong to the same family of finite mixture models but with different number of components. Extension to certain other models including multivariate models or models with other marginal distributions are discussed.     

Optimal design of supply chain networks under uncertain transient demand variations

We consider a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production facilities with shared production resources, warehouses, distribution centers and customer zones and operating under time varying demand uncertainty. Uncertainty is captured in terms of a number of likely scenarios possible to materialize during the lifetime of the network. The problem is formulated as a mixed-integer linear programming problem and solved to global optimality using standard branch-and-bound techniques. A case study concerned with the establishment of Europe-wide supply chain is used to illustrate the applicability and efficiency of the proposed approach. The results obtained provide a good indication of the value of having a model that takes into account the complex interactions that exist in such networks and the effect of inventory levels to the design and operation.     

Information systems,inter-functional collaboration and innovation in Taiwanese high-tech manufacturing firms

This article investigates whether (1) cross-functional integration within a firm and the use of information systems (IS) that support information sharing with external parties can enhance integration across the supply chain and wider networks and (2) whether collaboration with customers, suppliers and other external parties leads to increased supply chain performance in terms of new product development and introduction of new processes. Data from a high-quality survey carried out in Taiwan in 2009 were used, and appropriate econometric models were applied. Results show that the adoption of IS that enhance information sharing is vital not only for the effective communication with suppliers and with wider network members, but their adoption also has a direct effect across a firm's innovative effort. Cross-functional integration appears to matter only for the introduction of an innovative process. Collaboration with customers and suppliers affected a product's design and its overall features and functionality, respectively.     

Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components

Statistics and Computing - Recent work on overfitting Bayesian mixtures of distributions offers a powerful framework for clustering multivariate data using a latent Gaussian model which resembles...     

Adaptive likelihood estimator of conditional variance function

Modelling volatility in the form of conditional variance function has been a popular method mainly due to its application in financial risk management. Among others, we distinguish the parametric GARCH models and the nonparametric local polynomial approximation using weighted least squares or gaussian likelihood function. We introduce an alternative likelihood estimate of conditional variance and we show that substitution of the error density with its estimate yields similar asymptotic properties, that is, the proposed estimate is adaptive to the error distribution. Theoretical comparison with existing estimates reveals substantial gains in efficiency, especially if error distribution has fatter tails than Gaussian distribution. Simulated data confirm the theoretical findings while an empirical example demonstrates the gains of the proposed estimate.     

A behavioral portfolio approach to multiple job holdings

In this paper we present an alternative explanation of multiple job holdings. It is based on a behavioral portfolio approach using prospect theory. Multiple job holdings is often a result of economic hardship but also because of peer comparisons. Workers may decide to take on a risky job like self-employment and engage into new ventures but also hold on to a safe employment in order to stay as close as possible to their reference level. While multiple job holdings might be the case for some, many others might decide to keep on working only at a safe job and do not engage into new risky ventures. This paper presents a behavioral economics model to explain such decisions. We find that the decision to hold multiple jobs depends on the degree of loss aversion, the value of the reference level and on the expected return in the risky venture. The worker will not seek for a risky job if she has an income reference level equal to what she can earn from a safe job. At any other reference level, the worker will seek new ventures provided she is compensated with a higher expected wage and is sufficiently loss averse.     

Foreign Direct Investment and Trade Openness: The Case of Developing Economies

This paper examines the importance of trade openness for attracting Foreign Direct Investment (FDI) inflows, using a sample of 36 developing economies for the period 1990–2008. It provides a direct test of causality between FDI inflows, trade openness and other key variables in developing regions of the world: Latin America, Asia, Africa, CIS (Commonwealth of Independent States) and Eastern Europe. Trade openness is measured by using eight different indicators. The main empirical findings of the panel regression analysis reveal that in the long run, trade openness contributes positively to the inflow of FDI in developing economies.     

How do Greek banking institutions react after significant events?—A DEA approach

The efficiency of Greek commercial banks is considered through the period 1995–2003 using the data envelopment analysis technique. Two approaches are used to measure efficiency: one using financial ratios as outputs only and the other viewing banks as credit generation and transaction institutions. The empirical results are used to examine the reaction of banking institutions after significant events such as M&As, privatizations and the crisis of the Athens Stock Exchange in 1999. In most cases performance deteriorates for the next 1 to 2 years, while increases thereafter, forming specific patterns of efficiency. In the last part we introduce an index to measure the management's efficiency through a process of change. The results suggest that the Greek banking sector operated efficiently on average during the destabilization periods. The contribution of the article is that it comprises the first study which examines empirically the performance behavior of banking institutions within the scope of change management theory.     

Does research and development expenditure impact innovation? Evidence from the European Union countries

This study empirically investigates the relationship between innovation and Research & Development expenditure in European Union countries over the period 1995–2014. The findings of the empirical analysis show that there is a co-integration relationship between innovation and R&D. The results also reveal the existence of a positive and significant effect of business, public and higher education R&D on innovation. Business R&D is the sector with the highest positive effect on innovation. The results indicate that EU should strengthen the cooperation between business, public and higher education R&D through the encouragement of partnerships between the private sector, R&D and innovation system.