Temporal aggregation of cyclical models with business cycle applications

This paper focuses on temporal aggregation of the cyclical component model as introduced by Harvey (1989). More specifically, it provides the properties of the aggregate process for any generic period of aggregation. As a consequence, the exact link between aggregate and disaggregate parameters can be easily derived. The cyclical model is important due to its relevance in the analysis of business cycle. Given this, two empirical applications are presented in order to compare the estimated parameters of the quarterly models for German and US gross domestic products with those of the corresponding models aggregated to annual frequency.     

On the use of area-wide models in the Euro-zone

This paper investigates the legitimacy of using area-wide models in predicting aggregate variables in the Euro-area. We aim to compare the performance of area-wide versus national specific models for modeling money demand when using different aggregation schemes. A generalized Grunfeld and Griliches criterion and the Vuong test are used to discriminate between competitive models. Results show that the use of different aggregation methods is not irrelevant. In fact, due to the volatility of the exchange rates, the aggregate models fit better than the disaggregate whenever we employ ECU exchange rates. However, for fixed exchange rates expressed in Euro, the disaggregate models outperform the aggregate ones. This paper was written during my visiting research period at the Department of Economics, University of Southampton. I wish to thank John Aldrich, Jan Podivinsky, Grayham Mizon and Akos Valentinyi. Financial support of the Universita degli Studi “Roma Tre” and the Marie Curie fellowship (HPMT-CT-2001-00353) are gratefully acknowledged.     

Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)

Among the many tools suited to detect local clusters in group-level data, Kulldorff–Nagarwalla’s spatial scan statistic gained wide popularity (Kulldorff and Nagarwalla in Stat Med 14(8):799–810, 1995). The underlying assumptions needed for making statistical inference feasible are quite strong, as counts in spatial units are assumed to be independent Poisson distributed random variables. Unfortunately, outcomes in spatial units are often not independent of each other, and risk estimates of areas that are close to each other will tend to be positively correlated as they share a number of spatially varying characteristics. We therefore introduce a Bayesian model-based algorithm for cluster detection in the presence of spatially autocorrelated relative risks. Our approach has been made possible by the recent development of new numerical methods based on integrated nested Laplace approximation, by which we can directly compute very accurate approximations of posterior marginals within short computational time (Rue et al. in JRSS B 71(2):319–392, 2009). Simulated data and a case study show that the performance of our method is at least comparable to that of Kulldorff–Nagarwalla’s statistic.     

Let's meet up! The role of relational goods in promoting cooperation

The present paper draws on data collected through a Traveler's Dilemma experiment where the possibility of consuming relational goods is introduced by allowing (or forcing) agents to meet after the experiment. It enriches the literature on social distance by comparing the effect of its reduction when it is a voluntary subject's choice and when it is compulsory.We show that the existing interpretations of the effect of social distance reduction cannot explain the differences in agents’ behavior across our experimental treatments. This allows us to give to the theory of social distance an original interpretation based on the concept of relational goods where the possibility to consume relational goods promotes non-selfish behavior.     

Narratives of the Future Affect Fertility: Evidence from a Laboratory Experiment

European Journal of Population - In recent years, fertility rates have declined in most wealthy countries. This phenomenon has largely been explained by focusing on the rise of economic...     

The Role of Blended Value Accounting in the Evaluation of Socio-Economic Impact of Social Enterprises

Social enterprise has become a key phenomenon in providing public services in many developed countries. The debate on the evaluation of the socio-economic impact generated by this kind of organization has gone hand in hand with the growth of social entrepreneurship. This study provides an exploratory analysis of the emerging practice of measuring the socio-economic impact of social enterprises using the theoretic construct called “Blended Value Accounting” (BVA). Among the models and tools proposed by BVA, we examine in particular the Social Return on Investment (SROI)—an instrument of causal contribution analysis—conducting a literature review on its application to the evaluation of socio-economic impact of social enterprises and on its implications for BVA. Finally, we reach a conclusion as to the role that these tools of mixed accounting and assessment might play—particularly the one examined—with respect to the positivist, critical, and interpretative theories of accounting, thus identifying the areas for further research.     

On Stalnaker's Notion of Strong Rationalizability and Nash Equilibrium in Perfect Information Games

Counterexamples to two results by Stalnaker (Theory and Decision, 1994) are given and a corrected version of one of the two results is proved. Stalnaker's proposed results are: (1) if at the true state of an epistemic model of a perfect information game there is common belief in the rationality of every player and common belief that no player has false beliefs (he calls this joint condition strong rationalizability), then the true (or actual) strategy profile is path equivalent to a Nash equilibrium; (2) in a normal-form game a strategy profile is strongly rationalizable if and only if it belongs to C , the set of profiles that survive the iterative deletion of inferior profiles.     

Web-Based Accountability Practices in Non-profit Organizations: The Case of National Museums

Stakeholder theory posits that accountability systems depend on the strength and the number of their stakeholders. This paper aims to analyze the empirical validity of stakeholder theory, focusing on accountability systems in the museum sector. Based on Wikipedia resources, we have selected all of the “National Museums” (134 museums) in the major developed countries: Australia, Canada, France, Germany, Italy, the United Kingdom, and the US. After we control for type of activity (art or other), cost per visitor and country, the results of an OLS multivariate model show that size of the museum, which is assumed to represent the strength and number of stakeholders, and the amount of funds received, which represents the power of a particularly salient category of stakeholders (donors), are the two main determinants of the accountability level. We conclude that accountability, in the absence of shareholders, is driven by the number and the power of different stakeholders, validating the stakeholder theory.     

CLASS SIZE AND CLASS HETEROGENEITY

We study how class size and class composition affect the academic and labor market performance of college students, two crucial policy questions given the secular increase in college enrollment. Our identification strategy relies on the random assignment of students to teaching classes. We find that a one standard deviation increase in class‐size results in a 0.1 standard deviation deterioration of the average grade. Further, the effect is heterogeneous as it is stronger for males and lower income students. Also, the effects of class composition in terms of gender and ability appear to be inverse U‐shaped. Finally, a reduction of 20 students (one standard deviation) in one’s class size has a positive effect on monthly wages of about €80 ($115) or 6% over the average.