Identifying Changes in Mean,Seasonality, Persistence and Volatility for G7 and Euro Area Inflation*

We propose an iterative decomposition that tests and accounts for multiple structural breaks in the mean, seasonality, dynamics and conditional volatility, while also accounting for outliers. Considering each component separately within each iteration leads to greater flexibility compared with joint procedures. Monte Carlo analysis shows the procedure performs well. Applied to monthly CPI inflation in G7 countries and the Euro area, we uncover mean and seasonality breaks for all countries and, allowing for these, changes in persistence are generally also indicated. Further, volatility reductions are widespread in the early to mid 1980s, with some countries exhibiting increases from 1999 onwards.     

Real-time macroeconomic forecasting with leading indicators: An empirical comparison

This paper demonstrates that the Conference Board’s Composite Leading Index (CLI) has significant real-time predictive ability for Industrial Production (IP) growth rates at horizons from one to six months ahead over the period 1989-2009. A popular but unrealistic analysis, which combines real-time data for CLI and final vintage data for IP as predictor variables, obscures the actual predictive content of the CLI, in the sense that in that case, the improvements in forecast accuracy relative to a univariate AR model are not significant. The CLI appears to be less useful for forecasting growth rates of the Conference Board’s Composite Coincident Index (CCI) in real time, as a univariate AR model performs better. This result is mostly due to its disappointing performance during the first five years of the forecast period. The CLI may not be the best way of exploiting the information contained in the underlying individual leading indicator variables. The use of principal components instead of CLI leads to more accurate real-time forecasts for both IP and CCI growth rates.     

Do I Hear the Whistle…? A First Attempt to Measure Four Forms of Employee Silence and Their Correlates

Silence in organizations refers to a state in which employees refrain from calling attention to issues at work such as illegal or immoral practices or developments that violate personal, moral, or legal standards. While Morrison and Milliken (Acad Manag Rev 25:706–725, 2000) discussed how organizational silence as a top-down organizational level phenomenon can cause employees to remain silent, a bottom-up perspective—that is, how employee motives contribute to the occurrence and maintenance of silence in organizations—has not yet been given much research attention. In this paper, we argue that this perspective is a meaningful complementation of the existing literature and that it is sensible to conceptualize distinct forms of employee silence (Pinder and Harlos, Research in personnel and human resources management. JAI Press, Greenwich, 2001; van Dyne et al., J Manag Stud 40:1359–1392, 2003). Drawing on past research and theory we conceptualize four forms of employee silence, namely quiescent, acquiescent, prosocial, and opportunistic silence. We present scales to assess the four forms and provide empirical tests for their distinctiveness and patterns of relationships to various correlates and potential antecedents and consequences.     

The determinants of Norwegian exporters’ foreign exchange risk management

Abstract

This paper examines foreign exchange (FX) hedging by Norwegian exporting firms to provide empirical evidence on the determinants of the hedging decision. The paper contributes to prior studies by, first, focusing on exporters to ensure that the companies in the sample have FX exposure, thereby allowing a more rigorous test of the theoretical determinants of hedging, and, secondly, in contrast to most previous studies that have focused on FX external hedging instruments, the use of both internal and external instruments is examined. Univariate, multivariate and multinominal analyses all provide evidence consistent with the firm value maximization hypotheses of underinvestment and risk aversion. Also, the following characteristics of firms—size, extent of internationalization and liquidity—are found to be related to the decision to hedge FX risk. However, the evidence on the links between the firm characteristics and the decision to hedge is not consistent across internal and external FX hedgers, and also varies for individual hedging instruments. Therefore it is argued that the empirical evidence on the theoretical determinants cannot be generalized to cover the full range of FX hedging strategies (which includes internal hedging instruments). Unlike empirical studies for other countries the evidence for Norwegian firms does not support the hypothesis that the avoidance of financial distress and the need to resort to external capital markets is a significant determinant of the hedging decision. Whilst the evidence suggests that country-specific factors may play a role in determining the use of FX hedging, it does not imply that the different policies adopted are necessarily inconsistent with the firm value maximization hypothesis.     

Similarity-Based Spatial Methods to Estimate Shelf Space Elasticities

A retailer may allocate shelf space to brands based on factors, unobservable to researchers, which also determine sales. As a consequence, both sales and shelf space are endogenous in historical data, and this leads to inconsistent estimates of shelf space elasticities based on OLS. To obtain valid estimates of shelf space elasticities for allocation decisions, we propose an approach that incorporates the spatial correlation between shelf space and the error term resulting from store-, consumer- and competitor characteristics. The empirical results suggest that our model based on a single cross section of stores corrects for endogeneity and provides valid shelf space elasticities. We also obtain superior predictions compared to several benchmark models. With the same cross section and two observations over time, the alternative methods we use provide comparable shelf space elasticity estimates. However, our proposed method is still superior in the sense that its estimates have somewhat smaller standard errors.     

Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy*

Nonlinear time series models have become fashionable tools to describe and forecast a variety of economic time series. A closer look at reported empirical studies, however, reveals that these models apparently fit well in‐sample, but rarely show a substantial improvement in out‐of‐sample forecasts, at least over linear models. One of the many possible reasons for this finding is the use of inappropriate model selection criteria and forecast evaluation criteria. In this paper we therefore propose a novel criterion, which we believe does more justice to the very nature of nonlinear models. Simulations show that this criterion outperforms those criteria currently in use, in the sense that the true nonlinear model is more often found to perform better in out‐of‐sample forecasting than a benchmark linear model. An empirical illustration for US GDP emphasizes its relevance.     

Forecasting aggregates using panels of nonlinear time series

Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine whether forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As many macroeconomic variables have nonlinear properties, we specifically focus on panels of nonlinear time series. We discuss the representation of such models, parameter estimation and a method for generating forecasts. We illustrate the usefulness of our approach for simulated data and for the US coincident index, making use of state-specific component series.     

The Effects of Following Islam in Decisions about Taboo Products

This study tests the role of consumers’ religious motivation (intrinsic and extrinsic) in their decision making regarding the consumption of a prohibited brand or product category because of a religious declaration called Fatwa. Despite numerous studies on the effects of religion in consumers’ marketplace behaviors, little is known of about consumers’ decision making under a religious ruling like Fatwa. A Fatwa is a decree issued by religious scholars for Muslim communities. A survey based on the Theory of Planned Behavior asked young adult Muslims about their responses to a brand, and two product categories that were subject to Fatwa. The data concerning the respondents’ decision making were analyzed using structural equation modeling to test hypotheses based on the available literature. The analyses found that the respondents’ motivation in following Islamic teachings had the greatest effects in their deciding to smoke, listen to contentious popular music, but was not relevant for buying the Coca Cola brand. The results are discussed in terms of the study's theoretical contributions, managerial implications, and future research.     

Recognizing the benefits of diversity: When and how does diversity increase group performance?

Diversity does not only bring positive consequences. It has often been recognized that heterogeneity in teams can reduce intra-group cohesiveness, and that it can lead to conflicts and misunderstandings which, in turn, can lower employee satisfaction, citizenship behaviors and increase turnover. On the other hand, there is also evidence for performance-increasing effects of diversity because it can improve creativity and innovation through the team members' greater variety of perspectives. Little is known, however, about the conditions and the psychological mechanisms required for increasing group performance under diverse settings. Answers to research questions such as how and when diversity influences performance at work are still limited. The purpose of the paper is to provide theoretical answers to these questions by proposing a model of managing diversity which draws on social psychology theories. The model brings a new perspective by identifying the process of learning from one another's identity within a group. This process underlies two different levels of mechanisms (individual and group level). The model proposes that when these social psychological mechanisms are activated, diversity will lead to an increase in group performance. The model also suggests that collective identity is salient and when psychological safety climate are the psychological conditions that activate these mechanisms.