Dispositifs d’intermédiation marchande et politique des marchés. La modernisation du marché des fruits et légumes en France, 1950-1980

As this study of experiments with organizing the fruit and vegetable market from the 1950s till the end of the 1970s shows, there were alternatives to the principle of distribution, for instance: the modernization of traditional wholesale marketplaces (carreau) or the establishment of veilings (marchés au cadran) controlled by producers. After exposing the rationale underlying each of these arrangements, the empirical conditions are examined for actually modernizing markets. Attention is drawn to the factors that weigh on players in the market, in particular the tensions, on the one hand, between homogenization and concentration and, on the other hand, the singularity of products and transactions.     

Too risk averse to purchase insurance?

This paper suggests a new explanation for the low level of annuitization, which is valid even if one assumes perfect markets. We show that, as soon there is a positive bequest motive, sufficiently risk averse individuals should not purchase annuities. A model calibration accounting for lifetime risk aversion generates a significantly smaller willingness-to-pay for annuities than the one generated by a standard time-additive model. Moreover, the calibration predicts that riskless savings finance one third of consumption, in line with empirical findings.     

Arrangements for market intermediation and policies. Modernizing the fruit and vegetable market in France, 1950–1980

This article studies experiments in organizing the fruit and vegetable market from the 1950s till the late 1970s. It shows that there were alternatives to the principle of distribution, e.g. modernizing traditional wholesale markets (carreau) or setting up producer controlled veilings (marchés au cadran, or “clock auctions”). After exposing the rationale underlying each of these models, the empirical conditions are examined for actually implementing change. Attention is drawn to the factors that weigh on social actors in the market, in particular the tension between homogenization and concentration on the one hand, and, on the other hand, the uniqueness of products and transactions.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Bootstrap Prediction Intervals for Factor Models

We propose bootstrap prediction intervals for an observation h periods into the future and its conditional mean. We assume that these forecasts are made using a set of factors extracted from a large panel of variables. Because we treat these factors as latent, our forecasts depend both on estimated factors and estimated regression coefficients. Under regularity conditions, asymptotic intervals have been shown to be valid under Gaussianity of the innovations. The bootstrap allows us to relax this assumption and to construct valid prediction intervals under more general conditions. Moreover, even under Gaussianity, the bootstrap leads to more accurate intervals in cases where the cross-sectional dimension is relatively small as it reduces the bias of the ordinary least-squares (OLS) estimator.     

MULTIREGIONAL FIRMS AND REGION SWITCHING IN THE U.S. MANUFACTURING SECTOR

I use data on U.S. manufacturing establishments to study the spatial reallocation of resources that takes place within surviving firms as they open and close establishments in different regions. To motivate the empirical analysis, I extend existing models of industry dynamics to include production‐location decisions within firms. Consistent with the theory, the empirical results show that only a fraction of firms make the same product in multiple regions, that multiregional firms are larger and more productive on average compared to single‐region firms, and that “region switching” is pervasive among multiregional firms and correlated with changes in firm and firm‐region characteristics. (JEL L2, F12, F23)     

Trust among recent immigrants in Canada: levels,roots and implications for immigrant integration

ABSTRACT

Generalised trust promotes social interactions and may well be a crucial component of immigrant integration. Recent immigrants in particular are likely to be viewed by themselves and others as ‘outsiders’ who are unfamiliar with the expectations and norms that structure day-to-day social interactions in the host country. This study relies on a unique combination of three sources of data all derived from World Values Surveys to examine levels of trust, and its sources, among newcomers in one country with a large immigrant population, Canada. The evidence indicates that recent immigrants to Canada make a clear distinction between trust in other people in general, and trust in Canadians in particular: the former is grounded in pre-migration cultural influences, while the latter is grounded in immigrants’ experiences in the new host country. Moreover, the evidence suggests trust in Canadians is a crucial component of immigrant integration.