Understanding Interactions in Social Networks and Committees

While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

Two Studies on the Interplay between Social Preferences and Individual Biological Features

Biological features and social preferences have been studied separately as factors influencing human strategic behaviour. We run two studies in order to explore the interplay between these two sets of factors. In the first study, we investigate to what extent social preferences may have some biological underpinnings. We use simple one-shot distribution experiments to attribute subjects one out of four types of social preferences: Self-interested (SI), Competitive (C), Inequality averse (IA) and Efficiency-seeking (ES). We then investigate whether these four groups display differences in their levels of facial Fluctuating Asymmetry (FA) and in proxies for exposure to testosterone during phoetal development and puberty. We observe that development-related biological features and social preferences are relatively independent. In the second study, we compare the relative weight of these two set of factors by studying how they affect subjects’ behaviour in the Ultimatum Game (UG). We find differences in offers made and rejection rates across the four social preference groups. The effect of social preferences is stronger than the effect of biological features even though the latter is significant. We also report a novel link between facial masculinity (a proxy for exposure to testosterone during puberty) and rejection rates in the UG. Our results suggest that biological features influence behaviour both directly and through their relation with the type of social preferences that individuals hold.

Human capital, social mobility and the skill premium

This paper develops a dynamic general equilibrium model to highlight the role of human capital accumulation of agents differentiated by skill type in the joint determination of social mobility and the skill premium. We first show that our model captures the empirical co-movement of the skill premium, the relative supply of skilled to unskilled workers and aggregate output in the U.S. data from 1970-2000. We next show that endogenous social mobility and human capital accumulation are key channels through which the effects of capital tax cuts and increases in public spending on both pre- and post-college education are transmitted. In particular, social mobility creates additional incentives for the agents which enhance the beneficial effects of policy reforms. Moreover, the dynamics of human capital accumulation imply that, post reform, the skill premium is higher in the short- to medium-run than in the long-run.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.