Endorse or Not to Endorse: Understanding the Determinants of Newspapers’ Likelihood of Making Political Recommendations

This article investigates the determinants of newspapers’ provision for political opinion. I empirically examine the role of newspapers’ political preferences and market competition on newspapers’ decision to make endorsements. Regression results suggest that market competition turns newspapers more likely to make endorsements. Results from a simple model show that newspapers’ ideology determine their endorsements, making partisan papers more likely to make political recommendations and endorse challengers than non‐partisan newspapers.     

A Comparison of EPI Sampling, Probability Sampling, and Compact Segment Sampling Methods for Micro and Small Enterprises

Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to draw samples from a census of businesses and non-businesses in the Tshwane Municipality of South Africa, using three different sampling methods: the traditional probability sampling method, the compact segment sampling method, and the World Health Organization's Expanded Programme on Immunization (EPI) sampling method. Three mechanisms by which the methods could differ are tested, the proximity selection of respondents, the at-home selection of respondents, and the use of inaccurate probability weights. The results highlight the importance of revisits and accurate probability weights, but the lesser effect of proximity selection on the samples' statistical properties.     

A panel data approach to economic forecasting: The bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zero-mean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.     

Are Liberated Companies a Concrete Application of Sen’s Capability Approach?

Journal of Business Ethics - The capability approach (CA) developed by Amartya Sen focuses on the enhancement of people’s capabilities, i.e. their real freedom to choose a life course they...