CONSUMER CREDIT: EVIDENCE FROM ITALIAN MICRO DATA

In this paper we analyse unique data on credit applications received by the leading provider of consumer credit in Italy (Findomestic). The data set covers a five‐year period (1995–1999) during which the consumer credit market rapidly expanded in Italy and a new law (the usury law) came into force that set a limit on interest rates charged to consumers. We compute behavioural changes by controlling for changes in the observable characteristics of the Findomestic clientele and argue that, under suitable identifying assumptions, these changes can be given a structural interpretation. If the usury shock is assumed to have affected credit supply but not credit demand—that is, if the usury law had a differential impact on the supply of various types of credit but a uniform impact on demand—then we can identify and estimate a demand equation. Our key finding is that demand is interest‐rate elastic, particularly in the more affluent North. (JEL: D14, E21, G21)     

Simultaneous Wavelet Deconvolution in Periodic Setting

Abstract.  The paper proposes a method of deconvolution in a periodic setting which combines two important ideas, the fast wavelet and Fourier transform-based estimation procedure of Johnstone et al . [ J. Roy. Statist. Soc. Ser. B 66 (2004) 547] and the multichannel system technique proposed by Casey and Walnut [ SIAM Rev . 36 (1994) 537]. An unknown function is estimated by a wavelet series where the empirical wavelet coefficients are filtered in an adapting non-linear fashion. It is shown theoretically that the estimator achieves optimal convergence rate in a wide range of Besov spaces. The procedure allows to reduce the ill-posedness of the problem especially in the case of non-smooth blurring functions such as boxcar functions: it is proved that additions of extra channels improve convergence rate of the estimator. Theoretical study is supplemented by an extensive set of small-sample simulation experiments demonstrating high-quality performance of the proposed method.     

Paradoxes of Modernization: The new agrarian question and the peasant movement in Mexico

The clauses of this [social] contract are so determined by the nature of the act that the slightest modification would make them vain and ineffective; so that, although they have perhaps never been formally set forth, they are everywhere the same and everywhere tacitly admitted and recognized, until, on the violation of the social compact, each regains his original rights and resumes his natural liberty, while losing the conventional liberty in favour of which he renounced it.     

Bivariate Semi-Markov Process for Counterparty Credit Risk

We consider the problem of constructing an appropriate multivariate model to study counterparty credit risk in the credit rating migration problem. For this financial problem different multivariate Markov chain models were proposed. However, the Markovian assumption may be inappropriate for the study of the dynamics of credit ratings, which typically show non Markovian-like behavior. In this article, we develop a semi-Markov approach to study the counterparty credit risk by defining a new multivariate semi-Markov chain model. Methods are given for computing the transition probabilities, reliability functions and the price of a risky Credit Default Swap.     

Stochastic Differential Mixed-Effects Models

Abstract.  Stochastic differential equations have been shown useful in describing random continuous time processes. Biomedical experiments often imply repeated measurements on a series of experimental units and differences between units can be represented by incorporating random effects into the model. When both system noise and random effects are considered, stochastic differential mixed-effects models ensue. This class of models enables the simultaneous representation of randomness in the dynamics of the phenomena being considered and variability between experimental units, thus providing a powerful modelling tool with immediate applications in biomedicine and pharmacokinetic/pharmacodynamic studies. In most cases the likelihood function is not available, and thus maximum likelihood estimation of the unknown parameters is not possible. Here we propose a computationally fast approximated maximum likelihood procedure for the estimation of the non-random parameters and the random effects. The method is evaluated on simulations from some famous diffusion processes and on real data sets.     

A Procedural Evaluation of an Analytic-Deliberative Process: The Columbia River Comprehensive Impact Assessment

The U.S. Department of Energy's Columbia River Comprehensive Impact Assessment (CRCIA) was an ambitious attempt to direct its cleanup of the Hanford Nuclear Reservation toward the most significant risks to the Columbia River resulting from past plutonium production. DOE's approach was uncommonly open, including tribal, regulatory agency, and other Hanford interest group representatives on the board that was to develop the assessment approach. The CRCIA process had attributes of the "analytic-deliberative" process for risk assessment recommended by the National Research Council. Nevertheless, differences between the DOE and other participants over what was meant by the term "comprehensive" in the group's charge, coupled with differing perceptions of the likely effectiveness of remediation efforts in reducing risks, were never resolved. The CRCIA effort became increasingly fragmented and the role its products were to play in influencing future clean-up decisions increasingly ambiguous. A procedural evaluation of the CRCIA process, based on Thomas Webler's procedural normative model of public participation, reveals numerous instances in which theoretical-normative discourse disconnects occurred. These had negative implications for both the basic procedural dimensions of Webler's model-fairness and competence. Tribal and other interest group representatives lacked the technical resources necessary to make or challenge what philosopher Jurgens Habermas terms cognitive validity claims, while DOE and its contractors did not challenge normative claims made by tribal representatives. The results are cautionary for implementation of the analytic-deliberative process. They highlight the importance of bringing rigor to the evaluation of the quality of the deliberation component of risk characterization via the analytic-deliberative process, as well as to the analytic component.     

Performance of Robust GCV and Modified GCV for Spline Smoothing

Abstract. While it is a popular selection criterion for spline smoothing, generalized cross‐validation (GCV) occasionally yields severely undersmoothed estimates. Two extensions of GCV called robust GCV (RGCV) and modified GCV have been proposed as more stable criteria. Each involves a parameter that must be chosen, but the only guidance has come from simulation results. We investigate the performance of the criteria analytically. In most studies, the mean square prediction error is the only loss function considered. Here, we use both the prediction error and a stronger Sobolev norm error, which provides a better measure of the quality of the estimate. A geometric approach is used to analyse the superior small‐sample stability of RGCV compared to GCV. In addition, by deriving the asymptotic inefficiency for both the prediction error and the Sobolev error, we find intervals for the parameters of RGCV and modified GCV for which the criteria have optimal performance.