Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Correcting for the Missing Rich: An Application to Wealth Survey Data

It is a well‐known criticism that if the distribution of wealth is highly concentrated, survey data are hardly reliable when it comes to analyzing the richest parts of society. This paper addresses this criticism by providing a general rationale of the underlying methodological problem as well as by proposing a specific methodological approach tailored to correcting the arising bias. We illustrate the latter approach by using Austrian data from the Household Finance and Consumption Survey. Specifically, we identify suitable parameter combinations by using a series of maximum‐likelihood estimates and appropriate goodness‐of‐fit tests to avoid arbitrariness with respect to the fitting of the Pareto distribution. Our results suggest that the alleged non‐observation bias is considerable, accounting for about one quarter of total net wealth in the case of Austria. The method developed in this paper can easily be applied to other countries where survey data on wealth are available.     

The more others care,the more you share? – Social contagion as a stardom trigger of social media superstars –

Emerging superstars on social media platforms reshape the media landscape. This research analyses social contagion as a stardom trigger of social media superstars (SMS). We argue that in addition to serving as a quality indicator, the number of observed consumers of SMS performances also indicates the suitability of discussing the SMS performances with others. We experimentally manipulated the number of previous views of a YouTube video and find that a high number of previous views significantly increases the perceived quality and the video’s discussion suitability even when holding all objective video characteristics constant. We discuss implications for aspiring SMS and (online) marketers.     

Changes in Global Trade Patterns and Women's Employment in Manufacturing, 1995–2011

This study investigates the feminization and defeminization trends in manufacturing employment in thirty countries from 1995 to 2011. Utilizing two separate methods, structural decomposition analysis (SDA) and factor content analysis (FCA), the study identifies the major industries and trade partners behind the structural shifts in trade that have induced changes in employment and thus in the rates of women’s employment. The findings highlight that, as a general trend, defeminization in manufacturing has persisted in the Global North, led by a negative trade impact in low-technology industries. In the Global South, feminization and defeminization trends are not as straightforward. Despite positive changes in women’s share of employment in medium-high- and high-technology industries, negative gender bias effects of trade changes are found particularly in high-technology industries, where occupations are notably gendered.     

Are we nice(r) to nice(r) people?—An experimental analysis

We experimentally investigate whether individuals can reliably detect cooperators (the nice(r) people) in an anonymous decision environment involving “connected games.” Participants can condition their choices in an asymmetric prisoners’ dilemma and a trust game on past individual (their partner’s donation share to a self-selected charity) and social (whether their partner belongs to a group with high or low average donations) information. Thus, the two measures of niceness are the individual donation share in the donation task, and the cooperativeness of one’s choice in the two games. We find that high donors achieve a higher-than-average expected payoff by cooperating predominantly with other high donors. Group affiliation proved to be irrelevant. Electronic Supplementary Material Supplementary material is available in the online version of this article at . JEL Classification C91, C72, D3     

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.     

Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE,DSGE‐VAR,and VAR Models

The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marzginalization, for any subset of the observables in linear Gaussian state‐space models. We compare macroeconomic density forecasts for the euro area of a DSGE model to those of a DSGE‐VAR, a BVAR and a multivariate random walk over 1999:Q1–2011:Q4. While the BVAR generally provides superior forecasts, its performance deteriorates substantially with the onset of the Great Recession. This is particularly notable for longer‐horizon real GDP forecasts, where the DSGE and DSGE‐VAR models perform better. Copyright © 2016 John Wiley & Sons, Ltd.     

Fare Thee Well? An Analysis of Buyout Funds’ Exit Strategies

This paper analyzes exit strategies of buyout funds in portfolio companies following initial public offerings (IPOs). We use a data set of 222 buyout‐backed IPOs in the United States from 1999 to 2008, including hand‐collected data about each exit process, to draw a detailed roadmap of buyout investors’ divestment processes. Using this data, we document the timing and aggressiveness of the exit strategies, and analyze to which degree a multitude of possible determinants influence the choice of a given exit strategy. Our results indicate that buyout funds remain invested in their portfolio companies for a substantial period of time after the IPO, and that the choice of a given exit strategy depends not only upon the characteristics of each respective portfolio company, but also on the financial success of the deal from the perspective of the buyout investor.