A Machine Learning Analysis of the Recent Environmental and Resource Economics Literature

We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in different topics and the changing emphasis on topics in different journals. The most prevalent topics in environmental and resource economics research in this period are growth and sustainable development and theory and methodology. Topics on climate change and energy economics have emerged with the strongest upward trends. When we look at our results across journals, we see that journals have different topical profiles and that many topics mainly appear in one or a few selected journals. Further investigation reveal latent semantic structures across research themes that only the insider would be aware.

     

Do foreign exchange forecasters apply asymmetric loss functions? Evidence from three major exchange rates

This article investigates which type of loss function is consistent with the hypothesis that major exchange rate forecasts, i.e. the euro, the British pound, and the Japanese yen vis-à-vis the US dollar, are rational. We apply a comprehensive data set, which also allows us to examine different forecast horizons and heterogeneity of forecasters.     

The Joint Effect of Ethical Idealism and Trait Skepticism on Auditors’ Fraud Detection

Journal of Business Ethics - Although regulators have identified ethical lapses as a key factor contributing to auditors’ failure to detect their clients’ fraudulent financial reporting...     

In Pursuit of Happiness: Disentangling Sustainable Consumption,Consumer Alienation,and Social Desirability

Journal of Consumer Policy - This study makes a novel attempt to disentangle the complex relationships between making sustainable purchasing choices and happiness, while also considering the key...     

Neuer Nachholfaktor der Rentenversicherung im Geflecht von Schutz- und Niveauschutzklausel

Wirtschaftsdienst - Im Zuge der Einführung der Niveauschutzklausel in der gesetzlichen Rentenversicherung hat man den Nachholfaktor außer Kraft gesetzt. Um diese unbefriedigende Situation...     

The process of entrepreneurial action at the base of the pyramid in developing countries: a case of vegetable farmers in Benin

The assumption that entrepreneurship is a critical factor in expanding employment, creating wealth and contributing to poverty alleviation at the base of the pyramid (BoP) in developing countries has led to the development of many initiatives to strengthen the entrepreneurial activities of poor people. Despite the fact that entrepreneurship is seen as a strategy in combatting poverty, the process that leads to entrepreneurial action in a BoP context is still unclear. In this paper, we illustrate the possibilities a multi-layered perspective offers to understand the complexity of entrepreneurship in poverty settings. Based on five focus group discussions and 36 in-depth interviews with vegetable farmers in Benin, we examined the entrepreneurship of poor people. We learned that entrepreneurial action is the nexus of individual and exogenous factors in complex relationships. Based on this, we elaborate on the characteristics of the process model of entrepreneurial action. We provide a process-based view of entrepreneurship at the BoP, suggesting a need for consistency between individual, behavioural strategies and contextual elements. We discuss the implications of our findings for BoP practice and provide a framing perspective that we hope will encourage a greater focus on the complexity of entrepreneurship phenomenon.     

Bayesian Inference in Spatial Sample Selection Models

In this study, we consider Bayesian methods for the estimation of a sample selection model with spatially correlated disturbance terms. We design a set of Markov chain Monte Carlo algorithms based on the method of data augmentation. The natural parameterization for the covariance structure of our model involves an unidentified parameter that complicates posterior analysis. The unidentified parameter – the variance of the disturbance term in the selection equation – is handled in different ways in these algorithms to achieve identification for other parameters. The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study and an empirical application.     

The Role of Ideas in Understanding Industrial Relations Policy Change in Liberal Market Economies

This paper analyzes the uneven processes underpinning industrial relations policy liberalization in New Zealand, Australia, the UK, and Ireland. Drawing upon 140 elite interviews and building upon ideational comparative political theories, the paper highlights the role of ideas in the policy change process. It identifies how particular ideas can be used to construct policy problems, how these ideas can gain legitimacy through battles with competing ideas, and how policy legacies can influence whether ideas take root. The findings from the comparative case analysis expose a critical difference between “positive legacies” and “negative legacies” to account for different liberalization trajectories.     

Good global citizen? ASEAN’s image building in the United Nations

ABSTRACT

Based on role theory, the article examines the images that ASEAN member governments project of their organization. It rests on a discourse analysis of 198 speeches in the United Nations General Assembly between 1998 and 2017. Findings suggest that ASEAN does not figure as a top priority for delegates and that an overarching ASEAN role conception is missing. However, their addresses reveal parameters on which a collective role conception can be built. Individual ASEAN countries undertake great efforts to project themselves as ‘good global citizens,’ a role conception that could also be applied to ASEAN.     

Forecast-error-based estimation of forecast uncertainty when the horizon is increased

Past forecast errors are employed frequently in the estimation of the unconditional forecast uncertainty, and several institutions have increased their forecast horizons in recent times. This work addresses the question of how forecast-error-based estimation can be performed if there are very few errors available for the new forecast horizons. It extends the results of Knüppel (2014) in order to relax the condition on the data structure that is required for the SUR estimator to be independent of unknown quantities. It turns out that the SUR estimator of the forecast uncertainty, which estimates the forecast uncertainty for all horizons jointly, tends to deliver large efficiency gains relative to the OLS estimator (i.e., the sample mean of the squared forecast errors for each individual horizon) in the case of increased forecast horizons. The SUR estimator is applied to the forecast errors of the Bank of England, the US Survey of Professional Forecasters, and the FOMC.