Which Domestic Firms Benefit from FDI? Evidence from Selected African Countries

The existing literature on the effects of FDI inflows on domestic firms' performance offers ambiguous evidence. Macro‐level studies suggest that the characteristics of inward FDI and the ‘absorptive capacity’ of the host economy matter in determining the sign (or the mere existence) of these effects. Studies based on micro‐level data have so far mostly focused on finding a nexus between FDI inflows and the productivity of domestic firms, suggesting that the effects might be highly heterogeneous. This article, using a recent firm‐level survey conducted by UNIDO in 19 sub‐Saharan African countries, explores the channels through which multinational enterprises may exert an impact on local firms: products’ market, input availability and costs, access to finance and export opportunities, and analyses the strategic reactions of domestic firms induced by the presence of foreign affiliates.     

Constrained vs unconstrained labor supply: the economics of dual job holding

This paper develops a unified model of dual and unitary job holding based on a Stone-Geary utility function. The model incorporates both constrained and unconstrained labor supply. Panel data methods are adapted to accommodate unobserved heterogeneity and multinomial selection into six mutually exclusive labor supply regimes. We estimate the wage and income elasticities arising from selection and unobserved heterogeneity as well as from the Stone-Geary Slutsky equations. The labor supply model is estimated with data from the British Household Panel Survey 1991–2008. Among dual job holders, our study finds that the Stone-Geary income and wage elasticities are much larger for labor supply to the second job compared with the main job. When the effects of selection and unobserved heterogeneity are taken account of, the magnitudes of these elasticities on the second job tend to be significantly reduced.     

The younger, the better? Age-related differences in academic performance at university

In this paper, we investigate differences in academic performance among students of different ages within the same cohorts using a unique database of students at Bocconi University. Our data allow to control for potential selection effects as well as for differences in cognitive ability, as measured by an attitudinal entry test. Contrary to most of the existing evidence for younger pupils, we document that at the undergraduate level, youngest students perform better compared with their oldest peers. This finding is only partly explained by differences in cognitive ability and rather seems to be associated with differences in social activities.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.     

Splines for financial volatility

Summary.  We propose a flexible generalized auto-regressive conditional heteroscedasticity type of model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B -splines of lagged observations and volatilities. Estimation of such a B -spline basis expansion is constructed within the likelihood framework for non-Gaussian observations. As the dimension of the B -spline basis is large, i.e. many parameters, we use regularized and sparse model fitting with a boosting algorithm. Our method is computationally attractive and feasible for large dimensions. We demonstrate its strong predictive potential for financial volatility on simulated and real data, and also in comparison with other approaches, and we present some supporting asymptotic arguments.     

The Italian Labour Force Survey to estimate fertility

The own-children method (OCM) applied to the Italian Labour Force Survey (ILFS) is an alternative way to give information on fertility for the years before the survey. By deriving children information and the population at risk on the basis of parents’ characteristics, a large-scale dataset for fertility analysis in Italy becomes available, also to reconstruct event histories. The quality assessment provided by comparing the total fertility rate (TFR) calculated on ILFS with the official regional and national TFRs by ISTAT gives us usable outcomes.     

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.

     

Hybrid social and news media protest events: from #MarchinMarch to #BusttheBudget in Australia

Public protest events are now both social media and news media events. They are deeply entangled, with news media actors – such as journalists or news organisations – directly participating in the protest by tweeting about the event using the protest hashtag; and social media actors sharing news items published online by professional news agencies. Protesters have always deployed tactics to engage the media and use news media agencies’ resources to amplify their reach, with the dual aim of mobilising new supporters and adding their voice to public, mediatised debate. When protest moves between a physical space and a virtual space, the interactions between protesters and media stop being asynchronous or post hoc and turn instantaneous. In this new media-protest ecosystem, traditional media are still relevant sources of information and legitimacy, yet this dynamic is increasingly underpinned by a hybrid interdependency between traditional news and social media sources. In this paper we focus on an anti-austerity government movement that arose in Australia in early 2014 and was mobilised as a series of social media driven, connective action protest events. We show that there is a complex symbiotic interdependency between the movement and the traditional media for recognition and amplification of initial protest events, but that over time as media interest wanes, the movements’ network becomes disconnected and momentum is lost. This suggests that the active role traditional media play in protest events is being underestimated in the current research agenda on connective action.