Factors Influencing Young Consumers’ Acceptance of Genetically Modified Food in India

We analyzed the determinants of acceptance of genetically modified food (GMF) by using the probit model. In this study, we found that around 41% of the students are willing to buy GMF, and acceptance of GMF is less in female respondents than male respondents. The findings indicate that in India, benefit perception of GMF outweighed the risk perception. We also found that respondents’ trust in international organizations for truthful information has a positive and significant influence on acceptance of GMF.     

Fast Kernel Smoothing of Point Patterns on a Large Network using Two‐dimensional Convolution

We propose a computationally efficient and statistically principled method for kernel smoothing of point pattern data on a linear network. The point locations, and the network itself, are convolved with a two‐dimensional kernel and then combined into an intensity function on the network. This can be computed rapidly using the fast Fourier transform, even on large networks and for large bandwidths, and is robust against errors in network geometry. The estimator is consistent, and its statistical efficiency is only slightly suboptimal. We discuss bias, variance, asymptotics, bandwidth selection, variance estimation, relative risk estimation and adaptive smoothing. The methods are used to analyse spatially varying frequency of traffic accidents in Western Australia and the relative risk of different types of traffic accidents in Medellín, Colombia.     

THE ECONOMICS OF COUNTERTERRORISM: A SURVEY

We provide a review of theoretical and empirical contributions on the economic analysis of terrorism and counterterrorism. We argue that simple rational‐choice models of terrorist behavior – in the form of cost‐benefit models – already provide a well‐founded theoretical framework for the study of terrorism and counterterrorism. We also hint at their limitations which relate to the failure of accounting for the dynamics between terrorism and counterterrorism that may produce unintended second‐order effects as well as for the costs associated with counterterrorism and its international dimension. We reevaluate previously proposed counterterrorism strategies accordingly. Finally, in the light of our findings, we discuss interesting areas of future research.     

Communication in financial markets with several informed traders

This paper investigates the incentives for informed traders in financial markets to reveal their information truthfully to the public. In the model, a subset of traders receive noisy signals about the value of a risky asset. The signals are composed of a directional component (“high” vs. “low”) as well as a precision component that represents the quality of the directional component. Between trading periods, the informed agents make public announcements to the uninformed traders. With a sufficiently large number of informed traders, an equilibrium exists in which the directional components are credibly revealed, but not the precision components. Even though the informed traders retain some of their rivate information, the post-communication estimate of the asset value converges in probability to the full-information estimate as the number of informed traders increases. The paper is based on a chapter of my Ph.D. thesis at the University of Western Ontario and was circulated previously under the title “Public Communication Devices in Financial Markets.” I thank my dissertation committee Arthur Robson, Hari Govindan, and Al Slivinski for their guidance and support. I also thank Murali Agastya, Roland Benabou, Philippe Grégoire, Rick Harbaugh, Mike Peters, an anonymous referee and an associate editor, and seminar participants at various universities and conferences at which this paper was presented.