Consistent estimation in the bilinear multivariate errors-in-variables model

A bilinear multivariate errors-in-variables model is considered. It corresponds to an overdetermined set of linear equations AXB=C, A∈ℝ^m×n, B∈ℝ^p×q, in which the data A, B, C are perturbed by errors. The total least squares estimator is inconsistent in this case.  An adjusted least squares estimator is constructed, which converges to the true value X, as m →∞, q →∞. A small sample modification of the estimator is presented, which is more stable for small m and q and is asymptotically equivalent to the adjusted least squares estimator. The theoretical results are confirmed by a simulation study. Acknowledgements. We thank two anonymous reviewers for their suggestions and corrections.? A. Kukush is supported by a postdoctoral research fellowship of the Belgian office for Scientific, Technical and Cultural Affairs, promoting Scientific and Technical Collaboration with Central and Eastern Europe.? S. Van Huffel is a full professor with the Katholieke Universiteit Leuven.? I. Markovsky is a research assistant with the Katholieke Universiteit Leuven.? This paper presents research results of the Belgian Programme on Interuniversity Poles of Attraction (IUAP V-22), initiated by the Belgian State, Prime Minister's Office – Federal Office for Scientific, Technical and Cultural Affairs of the Concerted Research Action (GOA) projects of the Flemish Government MEFISTO-666 (Mathematical Engineering for Information and Communication Systems Technology), of the IDO/99/03 project (K.U. Leuven) “Predictive computer models for medical classification problems using patient data and expert knowledge”, of the FWO projects G.0078.01, G.0200.00, and G0.0270.02.? The scientific responsibility is assumed by its authors.     

Relative importance of scheduled macroeconomic news for stock market investors

This paper investigates the relative importance of scheduled U.S. macroeconomic news releases for stock valuation. The study focuses on 11 macroeconomic announcements selected on the basis of the previous literature and the Bureau of Labor Statistics classifications of major economic indicators. The paper shows that five out of the 11 announcements have significant influence on stock valuation. These are the Employment Report, NAPM (manufacturing), Producer Price Index, Import and Export Price Indices, and Employment Cost Index. Of these six announcements, the Employment Report and NAPM (manufacturing) exert the greatest influence. The time of the announcement, measured by days from the beginning of the month to the release day, has a moderating impact on the relationship between macroeconomic announcements and its importance.     

The reversal of large stock price declines: The case of large firms

This paper examines the long-run reversal pattern for a sample of large U.S. firms that experienced significant stock price declines of more than 20 percent during a specific month. The results from the analysis are largely consistent with the overreaction hypothesis and significantly greater in magnitude than those reported by previous studies. Six and 12 months after their initial price decline, the stocks of large firms earn approximately 4 and 12 percent in excess of what was expected, respectively. However, the magnitude and trend of that reversal differs substantially across industries. Technology stocks experience the largest and strongest reversal pattern followed by manufacturing stocks, while service industry stocks exhibit a clear downward drift that lasts up to three years and can be described as investorunderreaction to the large price drop.     

The impact of purchasing power parity on auto foreign trade

In this study, the validity of the assumption saying that the import and export are a function of prices as in the classical, neo-classical approaches is studied within the framework of the import and export of automobile vehicles between 1997 and 2003 in Turkey and the EU countries which are automobile manufacturers. The price here is considered as the purchasing power parity. The effect of the purchasing power parity on the automobile import and export is determined by using classical models with constant coefficients, and fixed and random effects models with constant slope coefficients and a constant term differing according to units and/or time. The models comprise balanced linear panel data models. The likelihood ratio test and F-test are used in the selection of fixed effects and classical models; and the Lagrange multiplier test is used in the selection of random effects and classical models. As for the selection of fixed and random effects models, the Hausman test is used. As a result of these tests, the fixed effects models covering both individual and time effects are selected as the most appropriate import and export models.