Mixtures of t-distributions for finance and forecasting

We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. Particularly desirable for econometric applications are closed-form expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-of-sample, than density forecasts obtained using normal or standard t-distributions. In the second application, we replicate the option-pricing exercise of Abadir and Rockinger [Density functionals, with an option-pricing application. Econometric Theory 19, 778–811.] and obtain comparably good results, while gaining analytical tractability.     

Visible moves and invisible bodies: the case of teleworking in an Italian call centre

Popular images of teleworkers' autonomy, such as 'the electronic cottage', give unrealistic pictures of the control exercised over teleworkers, particularly when these are call centre operators and highly integrated information and communication technology systems facilitate pervasive forms of control. However, this study of Italian home-located call centre operators demonstrates that extensive and multifaceted monitoring practices cannot 'solve' the controversial issue of control.     

Core and equilibria in coalitional asymmetric information economies

We study coalitional economies under uncertainty and asymmetric information, assuming a finitely additive measure space of agents and finitely many possible states of nature. We introduce a suitable core notion showing that it is equivalent to Walrasian expectations equilibria. The finitely additive approach proposed in the paper permits also asymmetric information economy with countably many agents, rather than requiring only a continuum. Moreover, it allows us to overcome well-known criticisms related to the interpretation of individual private core notions.     

Economies with informational asymmetries and limited vetoer coalitions

With reference to a model of coalitional economies with asymmetric information, we consider different possible restrictions on the set of blocking coalitions. We provide suitable price systems decentralizing allocations in the corresponding enlarged core.     

Is your open-innovation successful? The mediating role of a firm's organizational and social context

Open firms are not equally successful. This is because, in order to benefit from external sources of knowledge, firms must be able to absorb such knowledge. The paper outlines a firm's context as a set of organizational and social features, which may be considered absorptive capacity antecedents. It explores the mediating role of such antecedents in the relationship – hitherto insufficiently researched – between the degree of openness and innovative performance. The use of a methodology combining both direct interviews and survey of Italian firms has allowed us to confirm the supposed mediating role. We also identify different modes for companies to open up their innovation process and, for each of them, the antecedents that are consistent with choices regarding the degree of openness.     

Theory-coherent forecasting

We consider a method for producing multivariate density forecasts that satisfy moment restrictions implied by economic theory, such as Euler conditions. The method starts from a base forecast that might not satisfy the theoretical restrictions and forces it to satisfy the moment conditions using exponential tilting. Although exponential tilting has been considered before in a Bayesian context (Robertson et al. 2005), our main contributions are: (1) to adapt the method to a classical inferential context with out-of-sample evaluation objectives and parameter estimation uncertainty; and (2) to formally discuss the conditions under which the method delivers improvements in forecast accuracy. An empirical illustration which incorporates Euler conditions into forecasts produced by Bayesian vector autoregressions shows that the improvements in accuracy can be sizable and significant.