Combined Density Nowcasting in an Uncertain Economic Environment

We introduce a combined density nowcasting (CDN) approach to dynamic factor models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features to provide more accurate and complete density nowcasts. The combination weights are latent random variables that depend on past nowcasting performance and other learning mechanisms. The combined density scheme is incorporated in a Bayesian sequential Monte Carlo method which rebalances the set of nowcasted densities in each period using updated information on the time-varying weights. Experiments with simulated data show that CDN works particularly well in a situation of early data releases with relatively large data uncertainty and model incompleteness. Empirical results, based on U.S. real-time data of 120 monthly variables, indicate that CDN gives more accurate density nowcasts of U.S. GDP growth than a model selection strategy and other combination strategies throughout the quarter with relatively large gains for the two first months of the quarter. CDN also provides informative signals on model incompleteness during recent recessions. Focusing on the tails, CDN delivers probabilities of negative growth, that provide good signals for calling recessions and ending economic slumps in real time.     

Aggregate age-at-marriage patterns from individual mate-search heuristics

The distribution of age at first marriage shows well-known strong regularities across many countries and recent historical periods. We accounted for these patterns by developing agent-based models that simulate the aggregate behavior of individuals who are searching for marriage partners. Past models assumed fully rational agents with complete knowledge of the marriage market; our simulated agents used psychologically plausible simple heuristic mate search rules that adjust aspiration levels on the basis of a sequence of encounters with potential partners. Substantial individual variation must be included in the models to account for the demographically observed age-at-marriage patterns.     

A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments

A multi-stratum design is a useful tool for industrial experimentation, where factors that have levels which are harder to set than others, due to time or cost constraints, are frequently included. The number of different levels of hardness to set defines the number of strata that should be used. The simplest case is the split-plot design, which includes two strata and two sets of factors defined by their level of hardness-to-set. In this paper, we propose a novel computational algorithm which can be used to construct optimal multi-stratum designs for any number of strata and up to six optimality criteria simultaneously. Our algorithm allows the study of the entire Pareto front of the optimization problem and the selection of the designs representing the desired trade-off between the competing objectives. We apply our algorithm to several real case scenarios and we show that the efficiencies of the designs obtained present experimenters with several good options according to their objectives.     

The new ‘twice migrants’: motivations,experiences and disillusionments of Italian-Bangladeshis relocating to London

Taking our cue from an earlier study of East African Asians who ‘onward-migrated’ to the UK in the 1960s and 1970s, this paper looks at the more recent phenomenon of Bangladeshi immigrants in Italy who are onward-migrating to London. We seek to answer three questions. First, why does this migration occur? Second, how does the ethnic group we call ‘Italian-Bangladeshis’ narrate their working lives in London and to what extent do they feel ‘at home’ there? Third, what are the gaps between their expectations held before the move and the actual social and economic conditions they encounter in London? Empirical evidence comes from 40 in-depth interviews with Italian-Bangladeshis who have already onward-migrated or plan to. Most Italian-Bangladeshis move to London to escape socially limiting factory work in Italy, to invest in the educational future of their children, and to join the largest Bangladeshi community outside of their home country. In London, they describe feeling more ‘at home’ than in Italy, due to the size and multiple facilities of the Bangladeshi community, their lack of ‘visibility’ and of racialisation, and the greater sense of religious freedom. But their onward-migration experience has its more negative sides: the inability to access more than low-paid casual work in London’s service economy, the cost of housing, and the difficulty of making social contacts beyond their ethnic community, especially with those they regard as ‘natives’, i.e. ‘white’ British.     

Emigration and Immigration in Italy: Recent Trends

ABSTRACT: During the eighties Italy has evolved into being a receiver of immigration. However, the existence of large Italian communities abroad, and the persistence of exit migratory flows (although amply compensated by re-entry flows) show that the connotation of Italy as a country of emigration still persists. This paper points out the differing composition of present immigration flows to Italy compared to those of Italian migratory flows towards the more industrially advanced European countries over the past decades. The labour forces that constitute these present day immigration flows often possess medium to high educational qualifications, and are more frequently absorbed into the tertiary and agricultural markets, rather than the industrial sector. These immigrants rarely have regular, unionized occupations, and satisfy a demand for precarious, unstable labour which is in expansion in Italy, as in other countries. Furthermore, these immigration flows are directed not only towards those regions with high employment rates, but also to those with high unemployment rates. Thus, the implications are that the character of present day emigration can only be clearly understood by taking into account the highly segmented aspect of the labour market.