Institutional Impediments to Voluntary Ethics Measurement Systems

In this paper, we argue that calls for widespread implementation of ethics measurement systems would be better informed by institutional economic analysis. Specifically, we assert that proponents of such systems must first recognize and understand the institutions that potentially impede such efforts. We identify two potential institutional impediments to measuring ethics and social responsibility. First, we suggest that neoclassical economics, supported by traditional business education and legal precedent, serves to reinforce the notion that shareholders are the primary corporate constituency group. Such an emphasis on the needs of shareholders severely hinders implementation of measurement systems that address the needs of multiple stakeholder groups. Second, we argue that the threat of litigation may constrain corporate managers from measuring and considering ethics and corporate social responsibility matters. In particular, managers may be reluctant to quantify various ethical concerns if the resulting measurements could be used as evidence against the corporation in a lawsuit.     

Field Experiments in a Course on Behavioral Economics: Nudging Students Around Campus

In experiential education, the student learns through experience by observing a concept or phenomenon and applying this knowledge in a real-world context. A research project conducted by undergraduate students at a U.S. private liberal arts college is described in this article. The project provided opportunity for students to think about their decision-making processes, compare them to existing literature, and apply this knowledge in examining their own hypotheses through primary data collection on campus. While the research design's simplicity ensured that the project could be completed in time for a final grade and sacrificed lecture material in favor of feedback opportunities, this behavioral field experiment was a rewarding experience because of students’ enthusiasm and their ability to defend and think critically of their own ideas.     

Lifting the hood of supply and demand for trademarks of start-ups: Partial observability estimates

This paper estimates simultaneously the supply and the demand determinants of the trademark adoption decision made by start-ups. We use a partial observability econometric model, as non-adoption is unobserved. Estimation is by maximum likelihood using the partial observability bivariate probit (POBP) model for an unbalanced longitudinal panel of surviving US start-ups (2004–2011). Our model is shown to provide a good explanation of supply and demand determinants of trademark adoption. For example, size, incorporation and expenditure on R&D are important on the supply side; and copyrights, licensing out and being in a high knowledge information sector are important on the demand side.     

Decision support for firm performance by real options analytics

This paper develops a real options decision support tool for raising the performance of the firm. It shows how entrepreneurs can use our intuitive tool quickly to assess the nature and type of action required for improved performance. This exploits our estimated econometric relationship between precipitators of entrepreneurial opportunities, time until exercise, and firm performance. Our 3D chromaticity plots show how staging investments, investment time, and firm performance support entrepreneurial decisions to embed, or to expedite, investments. Speedy entrepreneurial action is securely supported with this tool, without expertise in econometric estimation or in formulae for real options valuation.     

Nowcasting South African gross domestic product using a suite of statistical models

Given lags in the release of data, a central bank must ‘nowcast’ current gross domestic product (GDP) using available quarterly or higher frequency data to understand the current state of economic activity. This paper uses various statistical modelling techniques to draw on a large number of series to nowcast South African GDP. We also show that GDP volatility has increased markedly over the last 5 years, making GDP forecasting more difficult. We show that all the models developed, as well as the Reserve Bank's official forecasts, have tended to overestimate GDP growth over this period. However, several of the statistical nowcasting models we present in this paper provide competitive nowcasts relative to the official Reserve Bank and market analysts' nowcasts.     

A Sticky Information Phillips Curve for South Africa

Mankiw and Reis propose the Sticky Information Phillips Curve (SIPC) as an alternative to the standard New Keynesian Phillips Curve to address empirical shortcomings in the latter. A SIPC for South Africa is estimated, and we find estimates of information updating probability between 0.69 and 0.81, somewhat higher than suggested by methods using micro‐evidence. Because the estimation requires data on expectations of current period inflation and output gap conditional on sequences of earlier period information sets, we provide a detailed analysis of the impact on our estimates of alternative proxies available in South Africa.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

Tipping the scale? The workings of monetary policy through trade

The monetary policy entails demand‐augmenting and diverting effects, and its impact on the trade balance—and on other countries—depends on the magnitude of these opposing effects. Using U.S. data and a sign‐restricted structural vector autoregressive identification, we investigate the importance of these effects. Overall, the results indicate that a monetary loosening (tightening) leads to a strengthening (weakening) of the overall trade balance, indicating that demand diversion dominates. The paper also explores changes in the effects following the global financial crisis, reflecting the impaired monetary transmission mechanism.     

Risk analysis of new maize technology in Zaire: a portfolio approach

Risk associated with the adoption of new maize technology and the impact of mandatory cotton production on traditional farmers in the Kasai Oriental Region of Zaire are evaluated within a portfolio context using a quadratic programming model. Seasonal net returns for farm plans including four levels of maize technology in combination with staple food crops are evaluated, with and without mandatory cotton production. The results indicate that cropping systems that include new maize technology are risk-efficient relative to local maize varieties while mandatory cotton production is not risk-efficient at the prevalent price and yield levels in the farming system.     

The Learning Transfer System Inventory (LTSI) translated into French: internal structure and predictive validity

The Learning Transfer System Inventory (LTSI, Holton et al., 2000 ) considers 16 factors likely to influence the transfer of training to the workplace. The purpose of this study is to translate the Learning Transfer System Inventory into French and to examine (1) the internal structure of the translated instrument; and (2) its predictive validity. The Learning Transfer System Inventory was administered to 328 participants from six companies during the week following the end of a training program. The transfer questionnaire was filled in by 106 of those participants 1–3 months later. The results showed that a principal component analysis reveals a factor structure very similar to the original structure: the 16 original factors are replicated. Second, seven factors display statistically significant correlations with transfer: learner readiness, motivation to transfer, transfer design, opportunity to use, transfer‐performance expectations, performance‐outcomes expectations and performance self‐efficacy. Comparisons with four similar previous studies allow us to draw directions for future research on the instrument.