Capabilities and Functionings: The Role of Social Capital for Accessing New Capabilities

This paper connects two relatively recent streams of research in social science: the capabilities approach and the literature on social capital. The aim is to show that these are strictly connected in a dynamic process linking functionings and capabilities through social capital. The ability to attain new capabilities is enhanced by the possession of social capital; hence investing in its accumulation allows individuals to improve their welfare. Furthermore, new capabilities allow the individual to create new connections and access new networks, accruing his or her stock of social capital and opening the door to the possibility of attaining new capabilities. The paper hypothesizes that a dynamic spiral interweaves social capital, capabilities and functionings.     

Identifying the Independent Sources of Consumption Variation

By representing a system of budget shares as an approximate factor model we determine its rank, i.e. the number of common functional forms or factors, and we estimate a base of the factor space by means of approximate principal components. We assume that the extracted factors span the same space of basic Engel curves representing the fundamental forces driving consumers' behaviour. We identify these curves by imposing statistical independence and by studying their dependence on total expenditure using local linear regressions. We prove consistency of the estimates. Using data from the UK Family Expenditure Survey from 1977 to 2006, we find strong evidence of two common factors and mixed evidence of a third factor. These are identified as decreasing, increasing, and almost constant Engel curves. The household consumption behaviour is therefore driven by two factors respectively related to necessities (e.g. food), luxuries (e.g. vehicles), and in some cases by a third factor related to goods to which is allocated the same percentage of total budget both by rich and poor households (e.g. housing). Copyright © 2015 John Wiley & Sons, Ltd.     

Supporting the free and competitive market in China and India: Differences and evolution over time

This paper analyzes the support to market competition by Indian and Chinese citizens. In particular, I study the individual preferences with respect to some characteristics of a free and competitive market. The paper aims at establishing whether preferences in these countries are different and their evolution over the time. This is an important issue, as the economic literature shows that people's preferences and policies tend to go hand in hand. This means that the analysis of today's preferences and their evolution over time can be useful to forecast tomorrow's policies. The main findings of this paper are that Indians and Chinese are different in supporting competition. The Chinese express preferences that are more in line with a free and competitive market than Indians do. The detected time path reveals that this support has been decreasing over time during the last two decades. The two populations appear to be in favour of a capitalistic, but strictly regulated market. This can mean that the future economic policies of these Asian giants will tend to this direction. Apparently there are no risks for some form of capitalism, but it is likely the two countries will not adopt completely free and competitive market institutions.     

Non‐Fundamentalness in Structural Econometric Models: A Review

Current economic theory typically assumes that all the macroeconomic variables belonging to a given economy are driven by a small number of structural shocks. As recently argued, apart from negligible cases, the structural shocks can be recovered if the information set contains current and past values of a large, potentially infinite, set of macroeconomic variables. However, the usual practice of estimating small size causal Vector AutoRegressions can be extremely misleading as in many cases such models could fully recover the structural shocks only if future values of the few variables considered were observable. In other words, the structural shocks may be non‐fundamental with respect to the small dimensional vector used in current macroeconomic practice. By reviewing a recent strand of econometric literature, we show that, as a solution, econometricians should enlarge the space of observations, and thus consider models able to handle very large panels of related time series. Among several alternatives, we review dynamic factor models together with their economic interpretation, and we show how non‐fundamentalness is non‐generic in this framework. Finally, using a factor model, we provide new empirical evidence on the effect of technology shocks on labour productivity and hours worked.     

Bootstrap prediction intervals for autoregressions: some alternatives

A new method is proposed to obtain interval forecasts for autoregressive models taking into account the variability due to the estimation of the order and the parameters. The procedure improves that introduced by Masarotto (1990), allows a substantial reduction of the variance of the predictive distribution percentile estimators and should thus be considered as a useful alternative to the classic Box and Jenkins interval forecast. The method uses the bootstrap technique and is distribution-free. An empirical application is considered.     

Geopolitical risks and stock market dynamics of the BRICS

This paper examines the effect of geopolitical uncertainty on return and volatility dynamics in the BRICS stock markets via nonparametric causality-in-quantiles tests. The effect of geopolitical risks (GPRs) is found to be heterogeneous across the BRICS stock markets, suggesting that news regarding geopolitical tensions do not affect return dynamics in these markets in a uniform way. GPRs are generally found to impact stock market volatility measures rather than returns, and often at return quantiles below the median, indicating the role of GPRs as a driver of bad volatility in these markets. While Russia bears the greatest risk exposure to GPRs in terms of both return and volatility, India is found to be the most resilient BRICS nation in the group. Noting that geopolitical shocks and in particular terrorist incidents are largely unanticipated, our findings underscore the importance of a strong financial sector that can help return the market to stability and an open economy that allows local investors to diversify country-specific risks in their portfolios.     

Health Systems and Health Reform in Europe

The organisation of health care differs widely across Europe. Access to services, financing schemes, incentives for better care, and administrative efficiency are challenges that are being dealt with in a variety of ways. Are insurance-based systems the best solution for balancing resources and services or are national health funds preferable? Does the introduction of competition fulfil high hopes for better service at lower costs? What are the relative advantages and drawbacks of central and local management of health care?     

International trade and macroeconomic dynamics with labor market frictions

This paper studies how labor market frictions affect the consequences of trade integration in a two-country dynamic stochastic general equilibrium model with heterogeneous firms and endogenous producer entry. Two main results emerge. First, trade integration is beneficial for welfare by inducing higher productivity, but unemployment can temporarily rise during the transitional adjustment. Labor market rigidities reduce gains from trade, even though they can mitigate short-run employment losses. Second, consistent with the data, the model predicts that stronger trade linkages lead to increased business cycle synchronization. The strength of this effect, however, depends on the labor market characteristics of the integrating partners.     

A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering

We introduce a new factor model for log volatilities that considers contributions, and performs dimensionality reduction, at a global level through the market, and at a local level through clusters and their interactions. We do not assume a-priori the number of clusters in the data, instead using the Directed Bubble Hierarchical Tree algorithm to fix the number of factors. We use the factor model to study how the log volatility contributes to volatility clustering, quantifying the strength of the volatility clustering using a new nonparametric integrated proxy. Indeed finding a link between volatility and volatility clustering, we find that a global analysis reveals that only the market contributes to the volatility clustering. A local analysis reveals that for some clusters, the cluster itself contributes statistically to the volatility clustering effect. This is significantly advantageous over other factor models, since it offers a way of selecting factors in a statistical way, whilst also keeping economically relevant factors. Finally, we show that the log volatility factor model explains a similar amount of memory to a principal components analysis factor model and an exploratory factor model.