Disaggregating entrepreneurial orientation: the non-linear impact of innovativeness, proactiveness and risk-taking on SME performance

Previous studies have generally established a positive relationship between aggregated measures of entrepreneurial orientation (EO) and firm performance. However, there are theoretical reasons suggesting that three dimensions of EO (innovativeness, proactiveness, and risk-taking) may possess differential relationships with performance in smaller firms. This study utilizes a sample consisting of 1,668 small-to-medium sized enterprises (SMEs) in nine countries across 13 different industries to provide a finer-grained analysis of the EO-performance relationship. Specifically, we theorize and test a non-monotonic influence of innovativeness, proactiveness, and risk-taking on SME performance. Innovativeness and proactiveness displayed predominantly positive U-shaped relationships with SME performance. Risk-taking, however, displayed a predominantly negative U-shaped relationship with SME performance. Further, individualism was found to positively moderate the relationships between innovativeness-performance and proactiveness-performance. Taken together, these results suggest that differential relationships exist between three dimensions of EO and SME performance, with important theoretical implications for future EO research.     

Do country risk and financial uncertainty matter for energy commodity futures?

Using an instrumental variable quantile regression technique, this paper assesses whether country risk and financial uncertainty exert an impact on energy commodity futures prices under different commodity conditional return distributions over the period from January 1994 to July 2017. We also discuss whether the correlations change with different dimensions of country risk, that is economic, financial, and political. The results reveal that country risk and financial stress do have a significant impact on energy commodity returns of futures contracts with different maturities, but their direction, intensity, and significance differ, caused by the distinct market situations and divergent channels of country risk.     

A note on estimating the minimum extended Gini hedge ratio

The extended Gini coefficient, Γ, is a measure of dispersion with strong theoretical merit for use in futures hedging. Yitzhaki (1982, 1983) provides conditions under which a two-parameter framework using the mean and Γ of portfolio returns yields an efficient set consistent with second-order stochastic dominance. Unlike mean-variance theory, the mean-Γ framework requires no particular return distribution or utility function to yield this conclusion. However, Γ must be computed iteratively making it less convenient to use than variance. Shalit (1995) offers a solution to the computation problem by suggesting an instrumental variables (IV) slope estimator, β^IV, as the basis for the minimum extended Gini hedge ratio where the instruments are based on the empirical distribution function (edf) of futures prices. However, the validity of employing the IV slope coefficient as the basis for the minimum extended Gini hedge ratio requires the questionable assumption that the rankings of futures prices to be the same as those for the profits of the hedged portfolio. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19:101–113, 1999