Victim or Victimizer: Firm Responses to Government Corruption

What is the relationship between government corruption and firm performance? To address this question, I conduct a review of articles published in the leading management journals on government‐business interactions pertaining to rent‐seeking activities and integrate findings from the fields of international business, social issues in management, public organization, institutional change, and corporate political activity. I find that while much empirical work corroborates the earlier findings suggesting a corrosive impact of government corruption on firm performance in general, management research also points to the heterogeneous impact of government corruption on individual firm performance, driven by the strategic activities conducted by firms in response to corruption. I propose an integrative model of firm strategy vis‐à‐vis corruption that predicts the activity choice of the firm as predicated by its organizational structure, political resources, industry regulation, and surrounding political and social institutions.     

Statistical tests for multiple forecast comparison

We consider a multivariate version of the Diebold–Mariano test for equal predictive ability of three or more forecasting models. The Wald-type test, $S$, which has a null distribution that is asymptotically chi-squared, is shown to be generally invariant with respect to the ordering of the models being compared. Finite-sample corrections for the test are also developed. Monte Carlo simulations indicate that $S$ has reasonable size properties in large samples but tends to be oversized in moderate samples. The finite-sample correction succeeds in correcting for size, but only partially. For the size-adjusted tests, power increases with sample size, as expected. It is speculated that further finite-sample improvements can be achieved using Hotelling’s $T^2$ or bootstrap critical values.     

Liquidity Crises and Corporate Cash Holdings in Chile

This paper addresses the heterogonous effects of adverse liquidity shocks on corporate cash holdings in an emerging market. We use a large panel dataset with quarterly financial information for Chilean firms during the period 1996–2009. We find three main results. First, liquidity crises have had a negative and economically significant effect on cash holdings, but mainly for small firms; medium‐sized and large firms have not been affected by liquidity crises. Second, liquidity crises reduce the ability of firms to adjust to optimal cash holdings. Finally, medium‐sized firms are less able to adjust cash holdings compared to small and large firms.     

Trade Openness and Spatial Inequality in Emerging Countries

Abstract

Emerging world countries have experienced over the last two decades a significant change in their trade patterns. Bold trade reforms have been followed by rapid rises in international trade levels. However, despite these radical changes, we know remarkably little about how changes in trade patterns are affecting the evolution of regional inequality in the developing world. This paper addresses the link between trade openness and spatial inequality across 22 emerging countries over the period between 1990 and 2006. Our findings show that changes in international trade bring about a significant rise in within-country inequality across the developing world and that this impact is greatest in the poorest countries. This result is robust to the inclusion of a number of control variables, and to changes in the specification of the sample and in the measure used to quantify the level of regional disparities. Consequently, the increase in trade exposure across the emerging world, while possibly benefiting the countries involved in the process in aggregate terms, is generating winning and losing regions.     

Quantitative narrative analysis software options compared: PC-ACE and CAQDAS (ATLAS.ti, MAXqda, and NVivo)

This paper shows how to carry out quantitative narrative analysis (QNA) with different text analysis software (PC-ACE, Program for Computer-Assisted Coding of Events, and various CAQDAS programs, Computer-Assisted Qualitative Data Analysis Software: ATLAS.ti, MAXQDA, and NVivo). QNA is a methodological approach to narrative texts that exploits invariant properties of narrative (namely, a “story grammar”, based on actors, actions, and their attributes) to make a statistical analysis of words possible. In comparing PC-ACE and CAQDAS, the paper leads the reader through the steps involved in setting up a grammar, in data entry, and in data query. A careful comparison of limits and possibilities of the two types of software will allow the reader interested in QNA to make an informed choice between a full implementation of QNA in a specialized but unknown software (PC-ACE) and a limited implementation in any of the widely used and popular CAQDAS programs.     

High involvement work practices and firm performance

During the past two decades the chain of three links organizational strategy – human resources practices – organizational performance has been deeply analysed. However, the mediator role of organizational structure in the first link of this chain remains relatively uninvestigated. In this article we analyse a model of relationships among organizational strategy, organizational structure, human resources practices, and organizational performance. Through a structural equation methodology applied to a sample of 183 Spanish companies, we will try to confirm that organizations with differentiation strategies are more likely to implement high involvement work practices. As a novelty we will introduce organizational structure as a mediator of this relationship. For that we will use the construct control mechanisms (centralization, formalization and socialization). Further, we will analyse the effect on firm performance of these proposed relationships among differentiation strategy, control mechanisms and high involvement work practices.     

Multidimensional configurations of the organizational climate construct

This study describes the creation and validation of a multidimensional model which assesses the level of employee satisfaction based on international theoretical models. It utilizes data collected from a sample of 518 public and private company employees during the year 2009 in the city/state of São Paulo, Brazil. In the first stage of the study, 15 independent dimensions were theoretically obtained. In the second stage, five different multiple dimensions were confirmed using structure equation modeling (SEM) technique, thus characterizing general configurations of the organizational climate construct denominated motivation, management philosophy, leadership, people management and nature of work. It is hoped that the model can contribute by enhancing managerial best practices of an organization by attending a major demand for those listed on stock markets, since these companies must periodically provide information on job satisfaction of their employees to maintain or achieve higher levels of corporate governance.     

Beta-product dependent Pitman–Yor processes for Bayesian inference

Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process mixture approach and define a new class of multivariate dependent Pitman–Yor processes (DPY). The proposed DPY are represented in terms of vectors of stick-breaking processes which determine dependent clustering structures in the time series. We follow a hierarchical specification of the DPY base measure to account for various degrees of information pooling across the series. We discuss some theoretical properties of the DPY and use them to define Bayesian non-parametric repeated measurement and vector autoregressive models. We provide efficient Monte Carlo Markov Chain algorithms for posterior computation of the proposed models and illustrate the effectiveness of the method with a simulation study and an application to the United States and the European Union business cycle.     

Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency

This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi:10.1007/s11123-012-0303-1, 2012) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the log-likelihood function of the model using results from the closed-skew normal distribution. Our Monte Carlo analysis shows that MLE is more efficient and less biased than the multi-step KLH estimator. Moreover, we obtain closed-form expressions for the posterior expected values of the random effects, used to estimate short-run and long-run (in)efficiency as well as random-firm effects. The model is general enough to nest most of the currently used panel SF models; hence, its appropriateness can be tested. This is exemplified by analyzing empirical results from three different applications.