IMMIGRATION,JOBS, AND EMPLOYMENT PROTECTION: EVIDENCE FROM EUROPE BEFORE AND DURING THE GREAT RECESSION

In this paper we analyze the impact of immigrants on the type and quantity of native jobs. We use data on 15 Western European countries during the 1996–2010 period. We find that immigrants, by taking manual‐routine type of occupations pushed natives towards more “complex” (abstract and communication) jobs. This job upgrade was associated to a 0.7% increase in native wages for a doubling of the immigrants' share. These results are robust to the use of an IV strategy based on past settlement of immigrants across European countries. The job upgrade slowed but did not come to a halt during the Great Recession. We also document the labor market flows behind it: the complexity of jobs offered to new native hires was higher relative to the complexity of lost jobs. Finally, we find evidence that such reallocation was larger in countries with more flexible labor laws.     

SALES AND COLLUSION IN A MARKET WITH STORAGE

Sales are a widespread and well‐known phenomenon documented in several product markets. This paper presents a novel rationale for sales that does not rely on consumer heterogeneity, or on any form of randomness to explain such periodic price fluctuations. The analysis is carried out in the context of a simple repeated price competition model, and establishes that firms must periodically reduce prices in order to sustain collusion when goods are storable and the market is large. The largest equilibrium profits are characterized at any market size. A trade‐off between the size of the industry and its profits arises. Sales foster collusion, by magnifying the inter‐temporal links in consumers' decisions.     

Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection

In this paper, we describe a series of laboratory experiments that implement specific examples of a general network structure. Specifically, actions are either strategic substitutes or strategic complements, and participants have either complete or incomplete information about the structure of a random network. Since economic environments typically have a considerable degree of complementarity or substitutability, this framework applies to a wide variety of settings. We examine behavior and equilibrium selection. The degree of equilibrium play is striking, in particular with incomplete information. Behavior closely resembles the theoretical equilibrium whenever this is unique; when there are multiple equilibria, general features of networks, such as connectivity, clustering, and the degree of the players, help to predict informed behavior in the lab. People appear to be strongly attracted to maximizing aggregate payoffs (social efficiency), but there are forces that moderate this attraction: (1) people seem content with (in the aggregate) capturing only the lion's share of the efficient profits in exchange for reduced exposure to loss, and (2) uncertainty about the network structure makes it considerably more difficult to coordinate on a demanding, but efficient, equilibrium that is typically implemented with complete information.     

Semi-parametric forecasts of the implied volatility surface using regression trees

We present a new semi-parametric model for the prediction of implied volatility surfaces that can be estimated using machine learning algorithms. Given a reasonable starting model, a boosting algorithm based on regression trees sequentially minimizes generalized residuals computed as differences between observed and estimated implied volatilities. To overcome the poor predictive power of existing models, we include a grid in the region of interest, and implement a cross-validation strategy to find an optimal stopping value for the boosting procedure. Back testing the out-of-sample performance on a large data set of implied volatilities from S&P 500 options, we provide empirical evidence of the strong predictive power of our model.     

Penalized likelihood inference in extreme value analyses

Models for extreme values are usually based on detailed asymptotic argument, for which strong ergodic assumptions such as stationarity, or prescribed perturbations from stationarity, are required. In most applications of extreme value modelling such assumptions are not satisfied, but the type of departure from stationarity is either unknown or complex, making asymptotic calculations unfeasible. This has led to various approaches in which standard extreme value models are used as building blocks for conditional or local behaviour of processes, with more general statistical techniques being used at the modelling stage to handle the non-stationarity. This paper presents another approach in this direction based on penalized likelihood. There are some advantages to this particular approach: the method has a simple interpretation; computations for estimation are relatively straightforward using standard algorithms; and a simple reinterpretation of the model enables broader inferences, such as confidence intervals, to be obtained using MCMC methodology. Methodological details together with applications to both athletics and environmental data are given.     

EXTERNAL AIDS FOR SOCIAL MEMORY

Collective or social memories are not just a way for accumulating and preserving but also for sharing and developing knowledge. Indeed, as knowledge is made explicit and elaborated by a community, it enriches the local culture and the current practices, becoming a basis for communication and learning. This paper addresses the concept of 'social memory' in a specific 'community of practice': teachers and students of primary schools. The work is developed within HIPS1 (Hyper Interaction within Physical Space), a three-year (1997-2000) research project funded by the European Commission within the I 3 (I-Cube) Programme. HIPS is a hand-held location-aware tourist guide that delivers information related to the surrounding space mainly reacting to the physical movements of visitors (Benelli et al . 1999). The guide is designed to minimize the boundary between the physical space and the related information through a number of situated and contextual-aware interaction mechanisms. In the paper we present a specific application of HIPS as tool to support the creation of a social memory. First, we illustrate the theoretical framework, the cultural psychology (Vygotsky 1978), which we adopted to design the tool as an external aid for social memory. Afterwards we describe the user study and the design process that resulted in the development of an early prototype. The conclusions are a reflection about the use of new technology to open new learning opportunities for students.     

Parsimonious periodic autoregressive models for time series with evolving trend and seasonality

Statistics and Computing - This paper proposes an extension of Periodic AutoRegressive (PAR) modelling for time series with evolving features. The large scale of modern datasets, in fact, implies...     

A Well-Being Indicator for the Italian Provinces

Social Indicators Research - In recent years, a significant number of papers has been published providing alternative measures of progress and well-being to Gross Domestic Product. Most of these...     

A note on the decidability of de Finetti's coherence

To check the de Finetti coherence of a putative probability assigned to a classA of events, we must know the possible combinations of truth values (constituents) of any finite class of events inA. Even for a very simple, finite,A this can be impossible. In this case the notion of DF coherence cannot be applied to some or all the putative probabilities on this class of events.