The Adjusted Big Mac Methodology: A Clarification

The Economist's adjusted Big Mac index takes GDP into account in currency valuation, but the methodology is not explained. We show that the key to understanding the methodology is to distinguish between a currency's bilateral valuation (versus a specific currency) and the currency's overall valuation (versus a “basket” of a large number of currencies). Also, the adjusted Big Mac estimates of intrinsic foreign exchange (FX) rates have been better forecasts of actual FX changes than those of the original “raw” Big Mac index.     

Customer and Supplier Portfolios: Can Credit Risks be Managed Through Supply Chain Relationships?

While supply chain risk has been the subject of an ever‐increasing amount of research attention, the importance of credit risk has been less studied, at least by supply chain researchers. Yet, there may be risks inherent within a firm's portfolios of supply chain relationships that are manifested in the credit risk of a firm. Moreover, portfolio characteristics may serve as a signal to the external market regarding these risks. While customer and supplier portfolio characteristics may impact the firm's exposure to risks, the specific issue of how portfolio characteristics relate to credit risk has rarely been examined by supply chain scholars. This research bridges extant works in supply chain management and finance to relate supply chain characteristics to a critical reputational outcome, namely credit ratings. In this research, we utilize a sample of firms that recently underwent an initial public offering to empirically examine the theoretical predictions of Resource Dependence Theory regarding the relationships between different supply chain portfolio characteristics and credit risk.     

Occupations,fields of study and returns to education

This paper considers several possible channels behind the well‐documented effect of education on earnings. The first channel is that education makes workers more productive on a given task, as in a conventional human capital framework. The second channel is based on the idea that education helps workers get assigned to higher‐paying occupations where output is more sensitive to skill. A third and final channel is that workers are more productive and earn more when they are matched to a job related to their field of study. Using data from the 2005 National Graduate Survey and the 2006 Canadian Census, I find that channels two and three account for close to half of the conventionally measured return to education. The results indicate that the return to education varies greatly depending on occupation, field of study and the match between these two factors.     

Do we understand each other? Toward a simulated empathy theory for entrepreneurship

Entrepreneurs often face the daunting task of predicting consumer demand before it exists—what consumers will want if and when the entrepreneur might make it available to them. Such alertness and judgment require an entrepreneur's vicarious imagination—the supposition of what a value experience would be like for another—such as empathy. Prevailing theories of empathy, however, are ill-suited for entrepreneurship theory as they are defined as and focused on an emotion-matching process. We propose that empathy be understood instead as a vicarious mental simulation of another's experience that, when accurate, produces similar emotions but also similar experiential knowledge. According to our ‘simulated empathy theory,’ empathy is a rational imagination process, intentional and knowledge-based. We connect this empathy process to contemporary entrepreneurship theory, namely opportunity recognition and evaluation processes. We also revise the concept of empathic accuracy accordingly, and derive therefrom some practical implications regarding how entrepreneurs can increase their empathic accuracy and, thereby, their chances of success.     

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.