Information in Tender Offers With a Large Shareholder

We study takeovers of firms whose ownership structure is a mixture of minority block‐holders and small shareholders. We show that the combination of dispersed private information on the side of small shareholders and the presence of a large shareholder can facilitate profitable takeovers. Furthermore, our analysis implies that even if some model of takeovers predicts a profit for the raider, for example, due to private benefits, the profit will be underestimated unless the large shareholder and the dispersion of information among the small shareholders are modeled.     

Model Selection and Shrinkage: An Overview

This special issue is concerned with model selection and shrinkage estimators. This Introduction gives an overview of the papers published in this special issue.     

Oracle Inequalities for Convex Loss Functions with Nonlinear Targets

This article considers penalized empirical loss minimization of convex loss functions with unknown target functions. Using the elastic net penalty, of which the Least Absolute Shrinkage and Selection Operator (Lasso) is a special case, we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target is linear, this inequality also provides an upper bound of the estimation error of the estimated parameter vector. Next, we use the non-asymptotic results to show that the excess loss of our estimator is asymptotically of the same order as that of the oracle. If the target is linear, we give sufficient conditions for consistency of the estimated parameter vector. We briefly discuss how a thresholded version of our estimator can be used to perform consistent variable selection. We give two examples of loss functions covered by our framework.     

Within inequality characteristics and adaptation of immigrants in the United States

Until recently, in works of literature, the assimilation of immigrants had been viewed as an individualistic rather than a community-based process. However, Hatton and Leigh (2011) showed that immigrants integrate to their host country as communities, not as individuals; hence, group characteristics play as much of a role as individual characteristics in terms of adaptation. This paper introduces another dimension to the immigrant adaptation proxies that reflect community-based characteristics. The fundamental assertion of this paper is that inequality can be used as a proxy of adaptation within immigrant groups. Immigrant groups that exhibit income and education distributions similar to those of the natives can be regarded as well-adapted groups, while those who exhibit vastly different distributions should be considered to be groups with limited adaptation. Using the American Community Survey (ACS) 2010 cohort, this paper presents the initial findings of the within-group inequality of immigrants. Then, a cross-sectional regression analysis is employed to analyze the determinants of inequality across these immigrant groups. The results suggest that immigrant community-based characteristics, such as average income, education, and number of years that the immigrants have spent in the US, can indeed explain most of the variation in inequality.     

Functions of Concordance and Dependence with Related Measures

Some functions that serve as building blocks for construction of a wider range of modes of concordance and dependence are pointed. We probe into interplays of such modes. From the standpoint of their conformity to stochastic dominance ordering of distributions within a Fréchet class, all such derived modes display some parallelism under certain conditions. We finally suggest a novel numeric measure of dependence that covers similar existing measures in literature.     

A Locally Optimal Seasonal Unit-Root Test

This article proposes a locally best invariant test of the null hypothesis of seasonal stationarity against the alternative of seasonal unit roots at all or individual seasonal frequencies. An asymptotic distribution theory is derived and the finite-sample properties of the test are examined in a Monte Carlo simulation. My test is also compared with the Canova and Hansen test. The proposed test is superior to the Canova and Hansen test in terms of both size and power.     

Comparison of ANOVA-F and ANOM tests with regard to type I error rate and test power

A Monte Carlo simulation was conducted to compare the type I error rate and test power of the analysis of means (ANOM) test to the one-way analysis of variance F-test (ANOVA-F). Simulation results showed that as long as the homogeneity of the variance assumption was satisfied, regardless of the shape of the distribution, number of group and the combination of observations, both ANOVA-F and ANOM test have displayed similar type I error rates. However, both tests have been negatively affected from the heterogeneity of the variances. This case became more obvious when the variance ratios increased. The test power values of both tests changed with respect to the effect size (Δ), variance ratio and sample size combinations. As long as the variances are homogeneous, ANOVA-F and ANOM test have similar powers except unbalanced cases. Under unbalanced conditions, the ANOVA-F was observed to be powerful than the ANOM-test. On the other hand, an increase in total number of observations caused the power values of ANOVA-F and ANOM test approach to each other. The relations between effect size (Δ) and the variance ratios affected the test power, especially when the sample sizes are not equal. As ANOVA-F has become to be superior in some of the experimental conditions being considered, ANOM is superior in the others. However, generally, when the populations with large mean have larger variances as well, ANOM test has been seen to be superior. On the other hand, when the populations with large mean have small variances, generally, ANOVA-F has observed to be superior. The situation became clearer when the number of the groups is 4 or 5.     

Big Data and Performance: What Can Management Research Tell us?

The special issue focuses on the theory and evidence linking the use of Big Data related technologies by businesses with their performance. Here we connect the papers accepted for the special issue to the overarching theme of Big Data as an emerging concept within the business management literature. We present two prominent case studies examining the use Big Data technologies on performance and strategy, followed by a discussion on how themes around Big Data and Performance may be examined from a theoretical perspective. Finally, based on a synthesis of papers in the current issue, we discuss the emerging issues and trends within the academic literature, relevant for future research.     

Fiscal harmonization in view of the Euro adoption: Economic implications for Poland

In this paper, we investigate the ex ante effects of fiscal policy harmonization that might be necessary for the adoption of the common currency on economic growth in Poland using a neoclassical dynamic two-sector general equilibrium model. We study two fiscal policy scenarios. In the first one, we adjust all taxes to German and EU-27 levels, respectively, while in the second one, we change only consumption taxes to German and EU-27 levels. We find that in the first scenario, the current Polish taxes yield the highest rate of growth due to lower capital taxation. However, in the second scenario, German and EU-27 taxes yield the highest rate of growth due to the lower consumption tax on capital-intensive good. From a policy perspective, our results suggest that fiscal policy with lower taxes on capital and capital-intensive goods can generate a higher rate of growth in the long-run. In the case of fiscal harmonization, our findings propose adopting only German or EU-27 consumption tax structure into the Polish tax system.