A proposal for a new specification for a conditionally heteroskedastic variance model: the Quadratic Moving-Average Conditional Heteroskedasticity and an application to the D. Mark-U.S. dollar Exchange Rate

Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

Aplicaciones Single Program Multiple Data (SPMD) en ambientes distribuidos

Un reto al ejecutar las aplicaciones en un cluster es lograr mejorar las prestaciones utilizando los recursos de manera eficiente, y este reto es mayor al utilizar un ambiente distribuido. Teniendo en cuenta este reto, se proponen un conjunto de reglas para realizar el cómputo en cada uno de los nodos, basado en el análisis de cómputo y comunicaciones de las aplicaciones, se analiza un esquema de mapping de celdas y un método para planificar el orden de ejecución, tomando en consideración la ejecución por prioridad, donde las celdas de fronteras tienen una mayor prioridad con respecto a las celdas internas. En la experimentación se muestra el solapamiento del computo interno con las comunicaciones de las celdas fronteras, obteniendo resultados donde el Speedup aumenta y los niveles de eficiencia se mantienen por encima de un 85%, finalmente se obtiene ganancias de los tiempos de ejecución, concluyendo que si se puede diseñar un esquemas de solapamiento que permita que la ejecución de las aplicaciones SPMD en un cluster se hagan de forma eficiente.

The Electoral Determinants of Collective Remittances: The Mexican 3x1 Program for Migrants

The 3x1 Program for Migrants is a matching grant scheme that seeks to direct the money sent by migrant organizations abroad to the provision of public and social infrastructure, and to productive projects in migrants’ communities of origin. To do so, the municipal, state, and federal administrations match the amount sent by hometown associations by 3 to 1. This opens the door to the political manipulation of the program. We explore the impact of a particular facet of Mexican political life on the operation of the 3x1: its recent democratization and the increasing political competition at the municipal level. Relying on the literature on redistributive politics, we posit that an increasing number of effective parties in elections may have two different effects. On the one hand, the need to cater to more heterogeneous constituencies may increase the provision of public projects. On the other hand, since smaller coalitions are needed to win elections under tighter competition, fewer public and more private (clientelistic) projects could be awarded. Using a unique dataset on the 3x1 Program for Migrants for over 2,400 municipalities in the period 2002 through 2007, we find a lower provision of public goods in electorally competitive jurisdictions. Thus, we remain sceptical about the program success in promoting public goods in politically competitive locations with high migration levels.

Including the workload effect in the parallel program signature

Performance prediction and application behavior modeling have been the subject of exten- sive research that aim to estimate applications performance with an acceptable precision. A novel approach to predict the performance of parallel applications is based in the con- cept of Parallel Application Signatures that consists in extract an application most relevant parts (phases) and the number of times they repeat (weights). Executing these phases in a target machine and multiplying its exeuction time by its weight an estimation of the application total execution time can be made. One of the problems is that the performance of an application depends on the program workload. Every type of workload affects differently how an application performs in a given system and so affects the signature execution time. Since the workloads used in most scientific parallel applications have dimensions and data ranges well known and the behavior of these applications are mostly deterministic, a model of how the programs workload affect its performance can be obtained. We create a new methodology to model how a program’s workload affect the parallel application signature. Using regression analysis we are able to generalize each phase time execution and weight function to predict an application performance in a target system for any type of workload within predefined range. We validate our methodology using a synthetic program, benchmarks applications and well known real scientific applications.

Creació de taules d'una base de dades relacional a partir del diagrama de classes d'anàlisi d'UML

És ben sabut que les úniques etapes del cicle de vida del programari que necessàriament s'han d'especificar són les de recollida de requisits i l'anàlisi o l'especificació del programari. La resta (disseny, implementació i prova) es pot generar d'una manera més o menys automàtica a partir de l'anàlisi. En aquest PFC hem volgut estudiar la viabilitat de la construcció automàtica de codi SQL a partir de diagrames de classes d'anàlisi UML. S'ha estès l'eina de modelatge UML Poseidon amb un connector, de manera que amb una interfície molt simple es pot obtenir molt ràpidament l'esquema bàsic d'una base de dades, incloent-hi les taules, les seves columnes, claus rimàries i foranes, i també els disparadors (i les claus úniques) necessaris per a garantir les restriccions de cardinalitat de les associacions.

FGF signaling controls caudal hindbrain specification through Ras-ERK1/2 pathway

Background: During early steps of embryonic development the hindbrain undergoes a regionalization process along the anterior-posterior (AP) axis that leads to a metameric organization in a series of rhombomeres (r). Refinement of the AP identities within the hindbrain requires the establishment of local signaling centers, which emit signals that pattern territories in their vicinity. Previous results demonstrated that the transcription factor vHnf1 confers caudal identity to the hindbrain inducing Krox20 in r5 and MafB/Kreisler in r5 and r6, through FGF signaling [1].Results: We show that in the chick hindbrain, Fgf3 is transcriptionally activated as early as 30 min after mvHnf1 electroporation, suggesting that it is a direct target of this transcription factor. We also analyzed the expression profiles of FGF activity readouts, such as MKP3 and Pea3, and showed that both are expressed within the hindbrain at early stages of embryonic development. In addition, MKP3 is induced upon overexpression of mFgf3 or mvHnf1 in the hindbrain, confirming vHnf1 is upstream FGF signaling. Finally, we addressed the question of which of the FGF-responding intracellular pathways were active and involved in the regulation of Krox20 and MafB in the hindbrain. While Ras-ERK1/2 activity is necessary for MKP3, Krox20 and MafB induction, PI3K-Akt is not involved in that process.Conclusion: Based on these observations we propose that vHnf1 acts directly through FGF3, and promotes caudal hindbrain identity by activating MafB and Krox20 via the Ras-ERK1/2 intracellular pathway.

Panel index VAR models: Specification, Estimation, Testing and Leading Indicators

This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

A comment on the Nash program and the theory of implementation

The mechanisms in the Nash program for cooperative games are madecompatible with the framework of the theory of implementation. This is donethrough a reinterpretation of the characteristic function that avoids feasibilityproblems, thereby allowing an analysis that focuses exclusively on the payoff space. In this framework, we show that the core is the only majorcooperative solution that is Maskin monotonic. Thus, implementation of mostcooperative solutions must rely on refinements of the Nash equilibrium concept(like most papers in the Nash program do). Finally, the mechanisms in theNash program are adapted into the model.

Invariance and randomness in the Nash program for coalitional games

By introducing physical outcomes in coalitional games we note that coalitional games and social choice problems are equivalent (implying that so are the theory of implementation and the Nash program). This facilitates the understanding of the role of invariance and randomness in the Nash program. Also, the extent to which mechanisms in the Nash program perform ``real implementation'' is examined.

The impact of interest-rate subsidies on long-term household debt: Evidence from a large program

The responsiveness of long-term household debt to the interest rate is acrucial parameter for assessing the effectiveness of public policies aimedat promoting specific types of saving. This paper estimates the effect ofa reform of Credito Bonificado, a large program in Portugal that subsidizedmortgage interest rates, on long-term household debt. The reform establisheda ceiling in the price of the house that could be financed through theprogram, and provides plausibly exogenous variation in incentives. Usinga unique dataset of matched household survey data and administrative recordsof debt, we document a large decrease in the probability of signing a newloan after the removal of the subsidy.

Female labour supply in Spain: The importance of behavioural assumptions and unobserved heterogeneity specification

We estimate four models of female labour supply using a Spanish sampleof married women from 1994, taking into account the complete form of theindividual s budget set. The models differ in the hypotheses relating tothe presence of optimisation errors and/or the way non-workers contributeto the likelihood function. According to the results, the effects of wagesand non-labour income on the labour supply of Spanish married women dependon the specification used. The model which has both preference andoptimisation errors and allows for both voluntarily and involuntarilyunemployed females desiring to participate seems to better fit the evidencefor Spanish married women.

An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Improving college access and success for low-income students: Evidence from a large need-based grant program

Using comprehensive administrative data on France's single largest financialaid program, this paper provides new evidence on the impact of large-scaleneed-based grant programs on the college enrollment decisions, persistenceand graduation rates of low-income students. We exploit sharp discontinuitiesin the grant eligibility formula to identify the impact of aid on student outcomesat different levels of study. We find that eligibility for an annual cashallowance of 1,500 euros increases college enrollment rates by up to 5 percentagepoints. Moreover, we show that need-based grants have positive effectson student persistence and degree completion.