The value of commuting time in an empirical on-the-job search model – an application based on moments from two samples

This article estimates the Value of Commuting Time (VOCT) among Swedish males in an empirical on-the-job search model. It uses a large sample of employee-establishment linked data obtained from administrative registers. The sample lacks information on mode choice for the journey to work. We therefore estimate a mode choice model on another sample and use this model to link the administrative data to the relevant set of travel times, costs and distances. The VOCT is found to be 1.8 times the net hourly wage rate in the sample. The relatively high estimate results from a high VOCT among cohabiting men.     

The efficiency of the Scandinavian banking sector – a wavelet quantile regression analysis

In this article, the Scandinavian housing financing market is analysed in order to determine whether the interest rate price-discovery processes of Denmark, Norway and Sweden are efficient. Based on wavelet quantile regression analysis, we find systematic positive asymmetric price transmission (APT) inefficiencies. We conclude that there is a very high propensity for mortgage lenders to directly increase its customers’ mortgage interest rates subsequently to an increase in its borrowing costs. However, after a corresponding borrowing cost decrease, the same mortgage lenders are very slow to decrease its customers’ mortgage rates. These positive coefficients for so-called APT effects are found in all Scandinavian countries, even if the coefficients for Norway were not statistically significant. Wavelet quantile regression analysis, with a focus on the relevant higher percentiles, is easily motivated since the mortgage rates are adjusted very infrequently. Moreover, wavelet decomposition allows a robust analysis at different time frequency scales, while simultaneously controlling for nonstationary trends, autocorrelation and structural breaks. Except for the still positive but yet insignificant and inconclusive coefficients for Norway, the result is very clear-cut. Regardless of which wavelet scaling decomposition or quantile coefficient that is studied – positive APT effects are clearly identified and confirmed on the Scandinavian mortgage market.     

Extrinsic Cues and Consumer Judgments of Food Product Introductions: The Case of Pangasius in Norway

In this article, the authors explore how the extrinsic cues corporate social responsibility, endorsement, and country of origin affect consumer evaluations of product quality, value, and expected product popularity for frozen Pangasius filets, a farmed fish product just recently introduced into the Norwegian market. The effects of these three variables are tested on purchase intentions. By means of a 2?×?2?×?2 factorial experiment in combination with survey data, the authors find that the three extrinsic cues under study had different effects on the evaluative variables. Furthermore, these variables all had positive and significant effects on purchase intentions. Hence, the general conclusion is that importers of new food products like Pangasius can benefit from focusing on extrinsic cues when the intrinsic cues are hard to evaluate or are unknown. Through the indirect effect on purchase intentions, extrinsic cues play an important role when consumers judge unfamiliar and new products.     

Commoditization in Food Retailing: Is Differentiation a Futile Strategy?

This article addresses commoditization in food retailing whereby competition has a tendency to lead to a continuous addition of new but similar products in a category. This often results in products that are more homogeneous and may make it more difficult for firms to gain unique market positions. In light of this development, we ask whether product differentiation is a futile strategy in food products marketing. We also address how consumers perceive and react to the seemingly ever-increasing number of similar products. These questions are explored through insights from relevant literature and a small-scale study of a seemingly highly differentiated category—smoked salmon—sold at the flagship store of an upmarket UK supermarket chain. It was concluded that no product attributes could be described as truly innovative, unique, or difficult to imitate. Implications are highlighted and discussed.     

The evolving domain of entrepreneurship research

Research on entrepreneurship has flourished in recent years and is evolving rapidly. This article explores the history of entrepreneurship research, how the research domain has evolved, and its current status as an academic field. The need to concretize these issues stems partly from a general interest in defining the current research domain and partly from the more specific tasks confronting the prize committee of the Global Award for Entrepreneurship Research. Entrepreneurship has developed in many sub-fields within several disciplines—primarily economics, management/business administration, sociology, psychology, economic and cultural anthropology, business history, strategy, marketing, finance, and geography—representing a variety of research traditions, perspectives, and methods. We present an analytical framework that organizes our thinking about the domain of entrepreneurship research by specifying elements, levels of analysis, and the process/context. An overview is provided of where the field stands today and how it is positioned relative to the existing disciplines and new research fields upon which it draws. Areas needed for future progress are highlighted, particularly the need for a rigorous dynamic theory of entrepreneurship that relates entrepreneurial activity to economic growth and human welfare. Moreover, applied work based on more careful design as well as on theoretical models yielding more credible and robust estimates seems also highly warranted.     

Regularized conditional estimators of unit inefficiency in stochastic frontier analysis,with application to electricity distribution market

In stochastic frontier analysis, the conventional estimation of unit inefficiency is based on the mean/mode of the inefficiency, conditioned on the composite error. It is known that the conditional mean of inefficiency shrinks towards the mean rather than towards the unit inefficiency. In this paper, we analytically prove that the conditional mode cannot accurately estimate unit inefficiency, either. We propose regularized estimators of unit inefficiency that restrict the unit inefficiency estimators to satisfy some a priori assumptions, and derive the closed form regularized conditional mode estimators for the three most commonly used inefficiency densities. Extensive simulations show that, under common empirical situations, e.g., regarding sample size and signal-to-noise ratio, the regularized estimators outperform the conventional (unregularized) estimators when the inefficiency is greater than its mean/mode. Based on real data from the electricity distribution sector in Sweden, we demonstrate that the conventional conditional estimators and our regularized conditional estimators provide substantially different results for highly inefficient companies.

     

An asset protection scheme for banks exposed to troubled loan portfolios

We examine a specific portfolio credit derivative, an Asset Protection Scheme (APS), and its applicability as a discretionary regulatory tool to reduce asymmetric information and help restore the capital base of troubled banks. The APS can be a fair-valued contract with an appropriate structure of incentives. We apply two alternative multivariate structural default risk models: the classical Gaussian Merton model and a model based on Normal Inverse Gaussian processes. Using a data set on annual farm level data from 1996 to 2009, we use the Danish agricultural sector as a case study and price an APS on an agricultural loan portfolio. We compute the economic capital for this loan portfolio with and without an APS. Moreover, we illustrate how model risk in the form of parameter uncertainty is reduced when an APS is attached to the loan portfolio.     

Does best practice HRM only work for intrinsically motivated employees?

The purpose of this study was to explore the relationships between perception of multiple best practice HRM and employee outcomes. Four cross-sectional surveys from different Norwegian service organizations of a total of 838 employees showed that several relationships between perceived empowerment and perceived information sharing and employee outcomes were moderated by intrinsic motivation. Implications for practice and directions for future research are discussed.     

Antecedents and Employee Outcomes of Line Managers' Perceptions of Enabling HR Practices

To learn more about the role of line managers in the implementation of HR practices, we propose and test a model of line managers' perceptions of enabling HR practices on the one hand and employee outcomes on the other. In a field study of 89 line managers and 631 employees, we observed that the relationship between line managers' perceptions of enabling HR practices and employees' intrinsic motivation, affective organizational commitment, and turnover intention was mediated by employees' perceived supervisor support. Line managers' perceptions of enabling HR practices, in turn, were predicted by line managers' perceived quality of the HR training they received. Theoretical and practical implications and directions for future research are discussed.     

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.