EstimatingJ (>1) quarterly time series in fulfilling annual and quarterly constraints

This paper addresses the problem of joint disaggregating a group of time series when their temporal aggregation values and their contemporaneous aggregation are known and when a number of related series in the desired frequency are available. The focus is on temporal distribution of annual series. This problem was treated before by other authors but they did not solve the problem of spurious steps which usually emerge in this framework. Proposed here is the simplest hypothesis congruent with reality that solves this difficulty. An algorithm is proposed to use these hypotheses in empirical works.     

An Exponential Family of Lorenz Curves

A new method for building parametric-functional families of Lorenz curves, generated from an initial Lorenz curve (which satisfies some regularity conditions), is presented. The method is applied to the exponential family since they use the exponential Lorenz curves as their generating curves. Several properties of these families are analyzed, including the population function, inequality measures, and Lorenz orderings. Finally, an application is presented for data from various countries. The family is shown to perform well in fitting the data across countries. The results are very robust across data sources.     

On Terms of Trade and Capital Accumulation

This paper studies, within an OLG general equilibrium framework, the role of relative factor intensities in determining the relationship between the terms of trade and the capital stock. It shows that a diversified production equilibrium can be characterized by a positive association between these two variables if the investment sector is more labor-intensive and sector technologies are relatively dissimilar. Therefore, capital accumulation and terms-of-trade improvements do not require an import sector growing faster than the export sector when the latter is more capital-intensive. Large Stolper–Samuelson effects on factor incomes drive the results.     

A non-parametric test for independence based on symbolic dynamics

In the present paper we propose a powerful, yet simple, non-parametric test for independence based on symbolic dynamic analysis. The absence of dependences in the unknown underlying data generating process is studied via symbolic dynamics. This is possible due to the ordering property of real numbers on an interval. Interestingly, the test is closely related to entropy concepts. Apart from being correctly sized, the new test is powerful for realistic finite data sets, and it is easy to use as one does not need to select any free parameter, which sharply contrasts with other tests of independence. In addition, the test is robust in the presence of noise which is one of the most typical cases when dealing with economic time series.     

On rankings and top choices in random utility models with dependent utilities

Different aggregate preference orders based on rankings and top choices have been defined in the literature to describe preferences among items in a fixed set of alternatives. A useful tool in this framework is constituted by random utility models, where the utility of each alternative, or object, is represented by a random variable, indexed by the object, which, for example, can capture the variability of preferences over a population. Applications are derived in diverse research fields, including computer science, management science and reliability. Recently, some stochastic ordering conditions have been provided for comparing alternatives by means of some aggregate preference orders in the case of independent random utility variables by Joe (Math Soc Sci 43:391–404, 2002). In this paper we provide new conditions, based on some joint stochastic orderings, for aggregate preference orders among the alternatives in the case of dependent random utilities. We also provide some examples of application in different research fields.      

Multiple safety net regulators and agency problems in the EU: Is Prompt Corrective Action partly the solution?

Prompt Corrective Action (PCA) provides a more efficient mechanism for dealing with problem banks operating in more than one European country. In a PCA framework, a bank's losses are likely to be substantially reduced. This reduction in the losses to deposit insurance and governments will improve the problem of allocating those losses across the various insurance schemes and make it less likely that any deposit insurer will renege on its obligations in a cross-border banking crisis. This paper presents a stylized mechanism aimed at dealing with the cross-border agency problems that arise in supervising and resolving cross-border banking groups in the European Union (EU). The authors assume that PCA policies have been implemented by the national supervisors and explore the institutional changes needed in Europe if PCA is to be effective as an incentive compatible mechanism. The paper identifies these changes starting with enhancements in the availability of information on banking groups to supervisors. Next, the paper considers the collective decision making by supervisors with authority to make discretionary decisions within the PCA framework as soon as a bank of a cross-border banking group falls below the minimum capital standard. Finally, the paper analyzes the coordination measures that should be implemented if PCA requires the bank to be resolved.     

Successive Sampling to Estimate Quantiles with P-Auxiliary Variables

The successive sampling is a known technique that can be used in longitudinal surveys to estimate population parameters and measurements of difference or change of a study variable. The paper discusses the estimation of quantiles for the current occasion based on sampling in two successive occasions and using p-auxiliary variables obtained of the previous occasion. A multivariate ratio estimator from the matched portion is used to provide the optimum estimate of a quantile by weighting the estimates inversely to derived optimum weights. Its properties are studied under large–sample approximation and the expressions of the variances are established. The behavior of these asymptotic variances is analyzed on the basis of data from natural populations. A simulation study is also used to measure the precision of the proposed estimator.