How limiting deceptive practices harms consumers

There are two competing sellers of an experience good, one offers high quality, one low. The low‐quality seller can engage in deceptive advertising, potentially fooling a buyer into thinking the product is better than it is. Although deceptive advertising might seem to harm the buyer, we show that he could be better off when the low‐quality seller can engage in deceptive advertising than not. We characterize the optimal deterrence rule that a regulatory agency seeking to punish deceptive practices should adopt. We show that greater protection against deceptive practices does not necessarily improve the buyer welfare.     

Taking Actively Advantage of MNCs’ Presence

In this paper, not only do we posit that the presence of a multinational corporation may entail significant benefits for the host economy and local firms’ performance, but also that these benefits can be actively sought and dynamically reinforced by local firms through the development of intense, embedded customer–supplier relationships. Building on the relational view, we argue that this may happen through the commitment of resources to relation-specific investments. Our hypotheses find support in a sample of SMEs suppliers of ST Microelectronics, the fourth largest producer of microelectronic components in the world. We show that by making relation-specific investments, local firms can grow quantitatively and qualitatively, improve their innovativeness, and acquire new clients.     

Identification of monetary policy in SVAR models: a data-oriented perspective

In the literature using short-run timing restrictions to identify monetary policy shocks in vector-auto-regressions (VAR) there is a debate on whether (i) contemporaneous real activity and prices or (ii) only data typically observed with high frequency should be assumed to be in the information set of the central bank when the interest rate decision is taken. This paper applies graphical modeling theory, a data-based tool, in a small-scale VAR of the US economy to shed light on this issue. Results corroborate the second type of assumption.     

Narrow Replication of ‘A Spatio‐Temporal Model of House Prices in the Usa’ Using R

I narrowly replicate Holly et al.'s (Journal of Econometrics 2010; 158 (1): 160–173) analysis of the housing market in the USA, using the open source R software instead of the original ad hoc GAUSS routines. Their main findings are confirmed and most results are matched exactly. Attention is given to providing a self‐contained and fully reproducible analysis, exclusively using user‐level features available in the public domain. Copyright © 2014 John Wiley & Sons, Ltd.     

Expropriation risk and discounting

This paper focuses on time preference and individual measures of expropriation risk. We use survey data on Italian households and on the 50+ population in eleven European countries. The surveys provide measures of discount rate and proxies for expropriation due to criminal offenses. We show that impatience increases with expropriation risk.     

Migration,Friendship Ties,and Cultural Assimilation

We study immigrant assimilation by analyzing whether friendship with natives is a measure of cultural assimilation, and by investigating the formation of social ties. Using the German Socio‐Economic Panel, we find that immigrants with a German friend are more similar to natives than those without German friends, along several important dimensions, including concerns about the economy, an interest in politics, and a host of policy issues. Turning to friendship acquisition, we find that becoming employed, time spent in the host country, the birth of a child, residential mobility, and additional education acquired in the host country are significant drivers of social network variation.     

Machine learning,artificial neural networks and social research

Quality & Quantity - Machine learning (ML), and particularly algorithms based on artificial neural networks (ANNs), constitute a field of research lying at the intersection of different...