What Drives the Creation of New Businesses? A Panel-Data Analysis for EU Countries

Our article aims to identify the key factors that affect the establishment of new businesses in 18 developed and emerging member countries in the European Union over the period 2003–2015. Using panel-data estimation techniques, we alternatively assess the effects of some macroeconomic, demographic, individual, and business environment-related factors on the dynamics of new firm creation, proxied by the rates of nascent entrepreneurship and entrepreneurial intentions. The results show that macroeconomic and demographic variables are the most significant determinants, followed by the individual characteristics of potential entrepreneurs and of the business environment. In addition, the sovereign debt crisis in Europe in 2010 positively affected entrepreneurship through increased support for new firms by individual country governments and the European Union.     

When do jumps matter for portfolio optimization?

We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on quantities known only in the true model. We apply our method to a calibrated affine model. Our findings are threefold: Jumps matter more, i.e. our approximation is less accurate, if (i) the expected jump size or (ii) the jump intensity is large. Fixing the average impact of jumps, we find that (iii) rare, but severe jumps matter more than frequent, but small jumps.     

Dynamic factor Value-at-Risk for large heteroskedastic portfolios

We propose a methodology that can efficiently measure the Value-at-Risk (VaR) of large portfolios with time-varying volatility and correlations by bringing together the established historical simulation framework and recent contributions to the dynamic factor models literature. We find that the proposed methodology performs well relative to widely used VaR methodologies, and is a significant improvement from a computational point of view.     

Does the trust game measure trust?

Could altruism explain observed choices in the standard trust game? With dominant altruism, trustors would give more to poor trustees. However, we find trustors to give no more to poor than to rich trustees, confirming trust as the dominant motivation for “trust like” choices.     

Comovement of Exchange Rates: A Wavelet Analysis

In this article we investigate the behavior of exchange rates in Central and Eastern European countries. The results strongly indicate that interactions between exchange rates have different characteristics at different timescales. Our results show that CEE exchange rates are nearly perfectly integrated in the short and medium run, since the returns obtained in any of the CEE foreign exchange market can almost be explained by the overall performance in the other CEE markets. The discrepancies between CEE exchange rates are small, but increase within three to six months and that means in the long run the integration of foreign exchange markets is weak.     

Discussant Comments on Papers by Andrew Joskow,Daniel Rubinfeld,and Janusz Ordover and Margaret Guerin-Calvert

Review of Industrial Organization -     

Analyzing user sentiment in social media: Implications for online marketing strategy

This article examines restaurant customers’ online activity following visits to restaurants. Differences in customers’ opinions based on gender and location are discussed. Sentiment analysis was used to analyze customers’ social media behavior in terms of liking, rating, and reviewing restaurants. User‐generated reviews and comments about experiences influence potential customers’ decisions. The results of this study show that gender and location of customers influence restaurant ratings. This article shows that sentiment analysis (using Natural Language Toolkit and TextBlob) can help marketers by providing a useful tool for big data analysis. Sentiment analysis can be used to interpret customer behavior and highlight how presales, sales, and after‐sales strategies can be improved.     

Multimodality in GARCH regression models

It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. Maximum likelihood estimates at the local and global modes are investigated and turn out to be qualitatively different, leading to different model-based forecast intervals. In the simpler GARCH(p,q) regression model, we derive analytical conditions for bimodality of the corresponding likelihood. In that case, the likelihood is symmetrical around a local minimum. We propose a solution to avoid this bimodality.     

Corruption and Banking Stability: Evidence from Emerging Economies

This article investigates the effect of corruption on banking stability using data from banks in emerging markets. The analysis first reveals that a lower level of corruption had a positive impact on bank stability and is associated with fewer credit losses and with more moderate credit growth. It then highlights the importance of bank and country characteristics in identifying the asymmetric effects of corruption on bank stability. Our evidence suggests that stability of banks that are acting in a country that has not adopted a corporate governance code or is not a member of the European Union is affected more by the corruption. Also, in countries with higher levels of corruption banks could increase their stability if they implement rigorous corporate governance practices.