International marketing research, in most cases, involves at least two levels (e.g., firms within countries) that make the hierarchical linear modeling (HLM) a suitable data analysis technique. Due to its robustness, the use of HLM in the international business (IB) research has increased...

The size and power properties of several tests of equal Mean Square Prediction Errors (MSPE) and of Forecast Encompassing (FE) are evaluated, using Monte Carlo simulations, in the context of nested dynamic regression models. The highest size-adjusted power is achieved by the F-type test of...

This paper examines financial market data to assess the likelihood of Renminbi appreciation and its implications for Chinese financial markets, given the continuing volatility of the exchange rate between the US Dollar and the Japanese Yen. Using VAR and Bayesian VAR estimation, we find that the...

The paper considers the problem of selecting one of two not necessarily nested competing regression models based on comparative evaluations of their abilities in each of two different issues: The first pertains to viewing the problem as a “best-fitting” model determination problem in the...

Recent research suggests that regional hydrologic and economic implications should be considered before adopting policies encouraging efficient irrigation technology. Investigating regional effects of irrigation efficiency investments relies on predicting how farmers will adopt irrigation...

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the...

This paper compares the goods and characteristics models of the consumer within a non-parametric revealed preference framework. Of primary interest is to make a comparison on the basis of predictive success that takes into account dimension reduction. This allows us to nonparametrically identify...