Francisco Rodríguez Fernández

The Finance-Growth Nexus A Regional Perspective

Recent cross-country studies suggest that finance and economic growth are significantly related. The characteristics and geographical scope of this relationship have become central to explain differences in economic development and financial exclusion. Two concepts are highly relevant in this context. First, financial deepening, which involves the development of traditional and non-traditional financial services in these territories. Second, bank dependence, which makes households and firms rely heavily on banks. Employing dynamic causality and panel data techniques on a sample of Spanish banks during 1993-9 we find that at a regional level, economic growth predicted financial deepening in this period. Regarding bank dependence, the bank-lending specialization appears to be a key issue in financing firms and households compared to other bank specializations.

Saving computational effort in genetic programming by means of plagues

A new technique for saving computing resources when using genetic programming is presented in this work. Instead of directly fighting bloat

An MPI-based tool for distributed genetic programming

the main factor explaining the large computational cost required for the evaluation of generations - by acting on individuals, we apply a new operator to the whole population: the plague. By removing some individuals every generation, we compensate for the increase in size of individuals, thus saving computing time when looking for solutions.

Genetic tuning of a laser pointer environment control device system for handicapped people with fuzzy systems

We present an environment for distributed genetic programming using MPI. Genetic programming is a stochastic evolutionary learning methodology that can greatly benefit from parallel/distributed implementations. We describe the distributed system, as well as a user-friendly graphical interface to the tool. The usefulness of the distributed setting is demonstrated by the results obtained to date on several difficult problems, two of which are described in the text.

The Role of Interchange Fees in Two-Sided Markets: An Empirical Investigation on Payment Cards

In this paper we present a new approach for laser-based environment device control systems by laser pointer for handicapped people. The paper proposes the design of a Fuzzy Rule Base System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs, i.e., the detection of a false laser spot (since this could lead to dangerous situations). To this end, Genetic Fuzzy Systems have also been employed for improving the laser spot system detection thus reducing the system false offs, that is the main objective in this problem. The system presented in this paper, using a Fuzzy Rule Base System adjusted by a Genetic Algorithm, shows a better success rate, and the most important thing, the not desired false offs are completely avoided.

Multiobjective RBFNNs designer for function approximation: an application for mineral reduction

We study the impact of reductions in interchange fees on payment card services. We find that consumer and merchant acceptance and transaction volumes increased when interchange fees were reduced. Our results suggest that a 10% reduction in the rate of decline per quarter in the average interchange fee by an acquirer resulted in a rate of increase in merchant acceptance per quarter of up to 1.4%. In addition, a 10% increase in the rate of interaction of merchant acceptance and the total number of cards increased the rate of quarterly issuer transaction volumes up to 1.7%.

The Effects of Bank Market Power in Short-Term and Long-Term Firm Credit Availability and Investment

Radial Basis Function Neural Networks (RBFNNs) are well known because, among other applications, they present a good performance when approximating functions. The function approximation problem arises in the construction of a control system to optimize the process of the mineral reduction. In order to regulate the temperature of the ovens and other parameters, it is necessary a module to predict the final concentration of mineral that will be obtained from the source materials. This module can be formed by an RBFNN that predicts the output and by the algorithm that designs the RBFNN dynamically as more data is obtained. The design of RBFNNs is a very complex task where many parameters have to be determined, therefore, a genetic algorithm that determines all of them has been developed. This algorithm provides satisfactory results since the networks it generates are able to predict quite precisely the final concentration of mineral.

Cooperative and decomposable approaches on royal road functions: overcoming the random mutation hill-climber

ABSTRACT This article investigates the short-term and long-term effects of bank market power on the availability of credit for companies, and on firm investment. Our results suggest that an increase in bank market power reduces firms’ credit availability and investment in the short-term, but firm investment recovers in the long-term. The economic significance of these relationships is found to be larger for SMEs than for other (larger) firms.

An artificial life approach to dense stereo disparity

Traditionally, evolutionary algorithms (EAs) encode each individual as a possible solution to the whole problem. As a natural extension to standard EAs, problem decomposition emerged for addressing complex problems. Although many problem decomposition methods rely on dividing the main problem in several less complex sub-problems, launching independent populations (species) to solve each of them, there are also other problem decomposition approaches that require a single population. Parisian approach [1] (often called Individual Evolution) and Gene Fragment Competition (GFC) [5] are two single-population problem decomposition approaches, where the problem can be decomposed in smaller sub-problems, so that they can be evaluated individually reducing the size of the search space. In order to evaluate both Parisian approach and Gene Fragment Competion on problem solving, we aim to use the so called Royal Road functions [3]. We take advantage of the modular and hierarchical structure of the Royal Road test functions to adapt them to both Individual Evolution and Gene Fragment Competition. It is our claim that these functions may serve in the theoretical studies of singlepopulation problem decomposable approaches, such as the Parisian and Gene Fragment Competition, since the landscape can be varied in a number of ways, and the global optimum and all possible fitness values are known in advance. Besides presenting a comparison between a standard genetic algorithm and both Individual Evolution and Gene Fragment Competion on several instances of the Royal Road functions, it is also presented a comparison between these single-population problem decomposition approaches and the results of a previous study made by Ochoa et al. about multi-population co-evolutionary approaches to the same Royal Road functions [4]. One final comparison was

The Single Euro Payment Area (SEPA): Implementation in Spain

This article presents an adaptive approach to improving the infection algorithm that we have used to solve the dense stereo matching problem. The algorithm presented here incorporates two different epidemic automata along a single execution of the infection algorithm. The new algorithm attempts to provide a general behavior of guessing the best correspondence between a pair of images. Our aim is to provide a new strategy inspired by evolutionary computation, which combines the behaviors of both automata into a single correspondence problem. The new algorithm will decide which automata will be used based on the transmission of information and mutation, as well as the attributes, texture, and geometry, of the input images. This article gives details about how the rules used in the infection algorithm are coded. Finally, we show experiments with a real stereo pair, as well as with a standard test bed, to show how the infection algorithm works.