Doorsteps Toward Political and Economic Openness: Testing the North-Wallis-Weingast Transition Framework

In this paper, we test the theoretical framework developed by North, Wallis, and Weingast (2009), who posit that limited-access societies need to meet three doorstep conditions before they can transit into open-access societies: (1) establishment of rule of law among elites, (2) adoption of perpetually existing organizations, and (3) political control of the military. We identify indicators reflecting these doorsteps and econometrically test their relationships with specific political and economic variables. We broadly confirm the logic behind the doorsteps as necessary conditions in the transition to open-access societies. The doorsteps influence economic and political processes, as well as each other, with varying intensities.     

Appeals in Korean Magazine Advertising: A Content Analysis and Cross-Cultural Comparison

This paper examines the economic, advertising industry, cultural, and product factors influencing the use of emotional and rational appeals in advertising for South Korea and the U.S. Content analysis of 600 Korean magazine advertisements shows that emotional appeals predominate in headlines, but rational appeals are more common overall and in the illustrations. Compared to results from 403 U.S. advertisements, Korean magazine advertising uses more emotional appeals, though differences vary across product types and executional method. Implications for advertising practice and future research are discussed.     

Applying the method of simulated moments to estimate a small agent-based asset pricing model

The paper takes a recent agent-based asset pricing model by Manzan and Westerhoff from the literature and applies the method of simulated moments to estimate its six parameters. In selecting the moments, the focus is on the fat tails and autocorrelation patterns of the daily returns of several stock market indices and foreign exchange rates. It is argued that it may be meaningful to abandon the econometrically optimal weighting matrix in the objective function and instead invoke the moments' t-statistics in an intuitively appealing way. This modification gives rise to estimations whose moment matching, given the model's parsimony, can be largely considered to be satisfactory. Also the parameter estimates across different markets make good economic sense.     

WHITHER CONSUMER PROTECTION IN FINANCIAL MARKETS? LESSONS FROM THE FINANCIAL CRISIS OF 1857

Consumer protection regulation has not prevented a collapse of trust in financial markets. Theories underlying regulatory intervention require review. In the financial crisis of 1857, firms rather than public authorities restored consumer confidence. Future regulatory regimes may permit greater scope for market-based design of consumer protection measures.     

A new stock-price bubble with stochastically deflating trajectories

We propose a new, rational stock-price bubble that is able to generate recurringly explosive and stochastically deflating trajectories. Our flexible bubble process entails stock-price volatility dynamics that are consistent with real-world data. To demonstrate this, we fit our bubble specification to NASDAQ data and analyse the volatility dynamics.     

Effort maximization in asymmetric contest games with heterogeneous contestants

Contest rules are set up by administrators who frequently have discretionary power in specifying the details of these rules, i.e., they can bias the contest rules toward specific contestants in order to further their prime objective. We derive the optimal bias of the contest rule for a contest administrator, who is interested in maximizing the total efforts expended in the contest. The solution is obtained in closed form for a widely used class of n-person contest games. Setting the optimal bias has important implications: (i) there is never exclusion of strong players, instead there is (endogenously induced) inclusion of weak contestants; (ii) the contest administrator will optimally level the playing field by encouraging weak contestants, but he will not equalize the contestants’ chances unless they are identical; and (iii) at least three contestants will be active in equilibrium of the optimal contest, irrespective of heterogeneity.     

Antecedents, consequences, and mediating effects of perceived moral intensity and personal moral philosophies

This study uses responses from a survey of marketing professionals in a structural equation model linking antecedents and consequences of two dimensions of personal moral philosophies (idealism and relativism) and perceived moral intensity (PMI). Mixed support is found for hypothesized effects of gender, religiosity, education, experience, salary, and corporate ethical values on idealism and relativism. Idealism increases and relativism decreases PMI in four ethical scenarios. PMI increases perceptions of ethical problems, which reduce intentions to act unethically. The study tests whether relationships between variables, revealing that PMI has direct as well as indirect effects on intentions. Intentions are also influenced by gender: women have more ethical intentions than men, on average, and this effect is not mediated by other variables in the model. Anusorn Singhapakdi is an associate professor of marketing at Old Dominion University. He has also served on the marketing faculty at Lamar University, Texas, and at Thammasat University, Thailand. His papers on topics in marketing ethics and social responsibility have been published in theJournal of the Academy of Marketing Science, Journal of Business Ethics, Journal of Business Research, Journal of Macromarketing, Journal of Public Policy & Marketing, and various other journals and proceedings. Scott J. Vitell is the Phil B. Hardin Professor of Marketing at the University of Mississippi. He received his Ph.D. in marketing from Texas Tech University. His work has previously appeared in theJournal of the Academy of Marketing Science, Journal of Business Research, Journal of Macromarketing, Journal of Business Ethics, Research in Marketing, International Marketing Review, and in other journals and proceedings. George R. Franke is an associate professor and Reese Phifer Fellow of Marketing at the University of Alabama. His research interests include ethics, public policy, advertising, and research methodology. His publications have received best-paper awards from theJournal of Advertising, Journal of Marketing Research, American Marketing Association, and Southern Marketing Association.     

Technology for the People? Humanity as a Compass for the Digital Transformation

How do we define what technology is for humans? One perspective suggests that it is a tool enabling the use of valuable resources such as time, food, health and mobility. One could say that in its cultural history, humanity has developed a wide range of artefacts which enable the effective utilisation of these resources for the fulfilment of physiological, but also psychological, needs. This paper explores how this perspective may be used as an orientation for future technological innovation. Hence, the goal is to provide an accessible discussion of such a psychological perspective on technology development that could pave the way towards a truly human-centred digital transformation.

     

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.