Talent or Not? Employee Reactions to Talent Identification

In this article, we examine the effect of talent identification on employee attitudes. Building on social exchange theory, we analyze the association between employees' perceptions about whether or not they have been formally identified as “talent” and the following attitudinal outcomes: commitment to increasing performance demands, building skills, and supporting strategic priorities; identification with the unit and the multinational enterprise; and turnover intentions. Our analyses of 769 managers and professionals in nine Nordic multinational corporations reveal a number of differences between employees who perceive that they have been identified as “talent” and those who either perceive that they have not been identified or do not know whether they have been identified. We found only limited differences between the two latter categories.     

Limit theory for panel data models with cross sectional dependence and sequential exogeneity

The paper derives a general Central Limit Theorem (CLT) and asymptotic distributions for sample moments related to panel data models with large n$n$. The results allow for the data to be cross sectionally dependent, while at the same time allowing the regressors to be only sequentially rather than strictly exogenous. The setup is sufficiently general to accommodate situations where cross sectional dependence stems from spatial interactions and/or from the presence of common factors. The latter leads to the need for random norming. The limit theorem for sample moments is derived by showing that the moment conditions can be recast such that a martingale difference array central limit theorem can be applied. We prove such a central limit theorem by first extending results for stable convergence in Hall and Heyde (1980) to non-nested martingale arrays relevant for our applications. We illustrate our result by establishing a generalized estimation theory for GMM estimators of a fixed effect panel model without imposing i.i.d. or strict exogeneity conditions. We also discuss a class of Maximum Likelihood (ML) estimators that can be analyzed using our CLT.     

Central limit theorems and uniform laws of large numbers for arrays of random fields

Over the last decades, spatial-interaction models have been increasingly used in economics. However, the development of a sufficiently general asymptotic theory for nonlinear spatial models has been hampered by a lack of relevant central limit theorems (CLTs), uniform laws of large numbers (ULLNs) and pointwise laws of large numbers (LLNs). These limit theorems form the essential building blocks towards developing the asymptotic theory of M-estimators, including maximum likelihood and generalized method of moments estimators. The paper establishes a CLT, ULLN, and LLN for spatial processes or random fields that should be applicable to a broad range of data processes.     

The people behind the scenes: Episodic volunteering at fundraising events

Nonprofit organizations (NPOs) have become increasingly dependent on episodic volunteers (EVs), those that would help carry out an event with little training and expectation to commit to future events. Despite its importance to the survival of NPOs, the use of EVs with respect to fundraising has received little research focus. Furthermore, none of the existing studies identified examined how fundraising EVs differ from other EVs. This study seeks to contribute to our understanding of fundraising EVs using a global perspective. Data were generated using surveys distributed in seven countries, tallying more than 4,000 respondents. Variables included demographic characteristics, previous donation and volunteer history, motives, mode of volunteering, and overall experience. The data were analyzed by applying between-group (logistic regression on participation) and within-group analysis (ordered logistic regression on willingness to participate in the future). Data were further analyzed by examining differences by country. We found that country, gender, religion, income, employment, history of donations, mode of volunteering, and several motives, both intrinsic and extrinsic, were significant in the logistic regression analysis of participation in fundraising episodic volunteering. The ordered logistic analysis unexpectedly found that the only predictors to foster a willingness to engage again were the responsiveness of the event team and a desire to fulfill spiritual satisfaction. In recruiting and selecting EVs for fundraising events, NPOs should consider previous or current donors and those with regular volunteering experience and they should market volunteer opportunities towards those in search of spiritual fulfillment and meaning. Moreover, NPOs should prioritize quick and clear communication with fundraising EVs in order to foster a willingness to volunteer again. Lastly, NPOs should regularly assess for country-specific factors and contexts that may affect episodic volunteering in fundraising events. Our paper illustrates who fundraising EVs are, their motives, how they choose to volunteer, and what contributes to their willingness to volunteer again. Given the limited research on fundraising EVs, this study serves to help lay the foundation of research for this unique subgroup. Our aim was to not only address the dearth of literature but serve as a springboard for future research on fundraising EVs.     

Team autonomy,organizational commitment and company performance – a study in the retail trade

The study focuses on the relationship between perceived team autonomy and company performance through highlighting organizational commitment as a mediating factor in this relationship. Data collected in 2007 came from 25 small-sized companies in the retail trade, covering both the employer and employee levels (n = 369). This study aims to shed light on the following questions: first, is team autonomy associated with organizational commitment and company performance? Second, does commitment mediate the relationship between team autonomy and company performance? Results indicated that team autonomy was both directly and indirectly positively associated with company performance. Furthermore, organizational commitment partially mediated the relationship between team autonomy and company performance. Theoretical and practical implications of these findings are discussed.     

Spousal Complementarity in Home Production

A bstract .   Economists have increasingly recognized the growing role of married women in the labor market by treating the labor supply decisions of married couples as joint decisions. However, they have yet to apply the same reasoning to home production. We build a more complete model of household time allocation that consists of a system of simultaneous equations estimating hours of labor supply and home production. Using data on white couples from Wave XXV of the Panel Study of Income Dynamics, we find that working wives act as if their husbands are substitutes for home production while other wives do not. Husbands' responses to their wives' behavior depends upon whether children are present.     

Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.     

Productivity Dispersion and Measurement Error

Several reasons have been put forward to explain the high dispersion of productivity across establishments: quality of management, different input usage and market distortions, to name but a few. Although it is acknowledged that a sizable portion of productivity dispersion may also be due to measurement error, little research has been devoted to identifying how much they contribute. We outline a novel procedure for identifying the role of measurement error in explaining the empirical dispersion of productivity across establishments. The starting point of our framework is the errors-in-variable model consisting of a measurement equation and a structural equation for latent productivity. We estimate the variance of the measurement error and subsequently estimate the variance of the latent productivity variable, which is not contaminated by measurement error. Using Norwegian data on the manufacture of food products, we find that about one percent of the measured dispersion stems from measurement error.