PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

Economic design of one-sided screening procedures based on a correlated variable with all parameters unknown

Summary Economic design of one-sided screening procedures for improving outgoing product quality based on a screening variable is considered for the case with all parameters unknown. It is assumed that the performance and screening variables are jointly normally distributed and that costs are incurred by screening inspection, acceptance of an imperfect item, and disposition of a rejected one. A method for finding optimal cutoff value based on the predictive distribution is presented.     

Modelling the inflation process in transition economies: Empirical comparison of Poland, Hungary and Czech Republic

This paper starts from the observation that inflation in transition economies appears to be persistently high and volatile and attempts to provide some empirical characterisation of the inflation process in three such transition economies: Poland, Hungary and Czech Republic. We first consider the role of monetary growth as a major causal factor for inflation in these economies, and argue that the evidence provides rather weak support for the causal relationship. We then propose a transition economy cost-plus model and estimate this using the equilibrium-correction modelling (ECM) strategy augmented by introduction of a number of transitory factors and changes in the internal structure of the real economy which we believe may have had a significant impact on inflation in these economies. We show that this approach enables us to account for long-run inflation in these economies from the early 1980s to the present despite the turbulence of the latter part of the sample period. Our results support wage and exchange rate based inflation policies.     

韩国企业对中国直接投资的实情分析和决定因素

文章通过对韩国企业对中国直接投资的实情分析,考察不同规模企业的特征,并依 据投资国的国内因素分析了对中国直接投资的决定因素。     

MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.     

The Influence of Environmental Pressures, Diversification Strategy, and Union/Nonunion Setting on Employee Participation

This study tests the hypotheses that environment, diversification strategy, and union/nonunion setting affect the number and variety of employee participation programs. A survey of large U.S. manufacturing firms measured the implementation of employee participation programs. Regression results suggest that environmental pressures exert a direct effect on participation in union settings. However, in nonunion settings, environment and diversification strategy both correlated directly with participation. These results suggest that unions could potentially affect participation program implementation.     

制度变迁对中国汽车工业增长贡献的实证分析

中国汽车工业增长是粗放型的，技术的贡献极低，而制度变迁贡献的潜力非常大。为此，一方面，要加快汽车工业的技术创新进程；另一方面，要深化汽车工业领域的市场化的制度变迁进程，以推动汽车工业走上高效、集约武增长之路。     

Is unemployment good for the environment?

Environmental quality is a public good, potentially impacted by everybody. Individual level pro-environmental behavior affects environmental quality in the aggregate. Therefore, it is important to understand what causes individual’s pro-environmental behaviors to change. We quantify the causal effect of one determinant, unemployment, using an EU-27 population representative Eurobarometer survey. Drawing on results from the theory of the private provision of public goods, and recognizing that unemployment decreases income and the opportunity cost of time, we formulate testable predictions that unemployment will decrease the extent of pro-environmental behaviors that require monetary contributions and increase the extent of pro-environmental behaviors that mainly require time/effort. Instrumental variables regressions provide empirical evidence to support these hypotheses. Changes in the unemployment rate within a sub-national region provide the exogenous variation needed to identify the causal effect. Several supplemental questions on the survey provide evidence that environmental issues lose saliency and economic issues gain saliency when one becomes unemployed, suggesting that interested parties may wish to emphasize cost savings of pro-environmental behavior rather than environmental benefits during times of increased unemployment.     

A saddlepoint approximation to the distribution of the sum of independent non‐identically uniform random variables

Calculating the probability of the corresponding significance point is important for finite sample sizes. However, it is difficult to evaluate this probability when the sample sizes are moderate to large. Under these circumstances, consideration of a more accurate approximation for the distribution function is extremely important. Herein, we performed a saddlepoint approximation in the upper tails for the distribution of the sum of independent non‐identically uniform random variables under finite sample sizes. Saddlepoint approximation results were compared with those for a normal approximation. Additionally, the order of errors of the saddlepoint approximation was derived. © 2014 The Authors. Statistica Neerlandica © 2014 VVS.