Estimation of random coefficients logit demand models: an application to the Brazilian fixed income fund market

Estimation of demand and supply in differentiated products markets is a central issue in Empirical Industrial Organization and has been used to study the effects of taxes, merges, introduction of new goods, market power, among others. Logit and Random Coefficients Logit are examples of demand models used to study these effects. For the supply side it is generally supposed a Nash equilibrium in prices. This work presents a detailed discussion of these models of demand and supply as well as the procedure for estimation. Lastly, is made an application to the Brazilian fixed income fund market.

The hierarchical model of branch planning with random coefficients

We consider the management branch model where the random resources of the subsystem are given by the exponential distributions. The determinate equivalent is a block structure problem of quadratic programming. It is solved effectively by means of the decomposition method, which is based on iterative aggregation. The aggregation problem of the upper level is resolved analytically. This overcomes all difficulties concerning the large dimension of the main problem.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Estresse e acidentes de trabalho: Estudo Pró-Saúde

Esta tese tem o objetivo geral de investigar a associação entre estresse e acidentes no trabalho em funcionários técnico-administrativos efetivos de uma universidade pública no Rio de Janeiro por meio de modelos multiníveis. Para alcançar tal objetivo, a tese foi distribuída em dois artigos. O primeiro artigo investiga a associação entre estresse e acidentes no trabalho considerando componentes hierárquicos da estrutura dos dados por meio de modelos multiníveis com funcionários no primeiro nível agrupados em setores de trabalho no segundo nível. O segundo artigo investiga o comportamento dos coeficientes fixos e aleatórios dos modelos multiníveis com classificação cruzada entre setores de trabalho e grupos ocupacionais em relação aos modelos multiníveis que consideram apenas componentes hierárquicos dos setores de trabalho, ignorando o ajuste dos grupos ocupacionais. O estresse psicossocial no trabalho foi abordado a partir das relações entre alta demanda psicológica e baixo controle do processo laboral, Estas dimensões foram captadas por meio da versão resumida da escala Karasek, que também contém informações sobre o apoio social no trabalho. Dimensões isoladas do estresse no trabalho (demanda e controle), razão entre demanda psicológica e controle do trabalho (Razão D/C) e o apoio social no trabalho foram mensurados no nível individual e nos setores de trabalho. De modo geral, os resultados destacam a demanda psicológica mensurada no nível individual como um importante fator associado à ocorrência de acidentes de trabalho. O apoio social no trabalho, mensurado no nível individual e no setor de trabalho, apresentou associação inversa à prevalência de acidentes de trabalho, sendo, no setor, acentuada entre as mulheres. Os resultados também mostram que os parâmetros fixos dos modelos com e sem classificação cruzada foram semelhantes e que, de modo geral, os erros padrões (EP) foram um pouco maiores nos modelos com classificação cruzada, apesar deste comportamento do EP não ter sido observado quando relacionado aos coeficientes fixos das variáveis agregadas no setor de trabalho. A maior distinção entre as duas abordagens foi observada em relação aos coeficientes aleatórios relacionados aos setores de trabalho, que alteraram substancialmente após ajustar o efeito da ocupação por meio dos modelos com classificação cruzada. Este estudo reforça a importância de características psicossociais na ocorrência de acidentes de trabalho e contribui para o conhecimento dessas relações a partir de abordagens analíticas que refinam a captação da estrutura de dependência dos indivíduos em seu ambiente de trabalho. Sugere-se a realização de outros estudos com metodologia similar, que permitam aprofundar o conhecimento sobre estresse e acidentes no trabalho.

Determinants and effects of central bank independence reforms

This thesis consists of four empirically oriented papers on central bank independence (CBI) reforms.    Paper [1] is an investigation of why politicians around the world have chosen to give up power to independent central banks, thereby reducing their ability to control the economy. A new data-set, including the possible occurrence of CBI-reforms in 132 countries during 1980-2005, was collected. Politicians in non-OECD countries were more likely to delegate power to independent central banks if their country had been characterized by high variability in inflation and if they faced a high probability of being replaced. No such effects were found for OECD countries.    Paper [2], using a difference-in-difference approach, studies whether CBI reform matters for inflation performance. The analysis is based on a dataset including the possible occurrence of CBI-reforms in 132 countries during the period of 1980-2005. CBI reform is found to have contributed to bringing down inflation in high-inflation countries, but it seems unrelated to inflation performance in low-inflation countries.    Paper [3] investigates whether CBI-reforms are important in reducing inflation and maintaining price stability, using a random-effects random-coefficients model to account for heterogeneity in the effects of CBI-reforms on inflation. CBI-reforms are found to have reduced inflation on average by 3.31 percent, but the effect is only present when countries with historically high inflation rates are included in the sample. Countries with more modest inflation rates have achieved low inflation without institutional reforms that grant central banks more independence, thus undermining the time-inconsistency theory case for CBI. There is furthermore no evidence that CBI-reforms have contributed to lower inflation variability    Paper [4] studies the relationship between CBI and a suggested trade-off between price variability and output variability using data on CBI-levels, and data the on implementation dates of CBI-reforms. The results question the existence of such a trade-off, but indicate that there may still be potential gains in stabilization policy from CBI-reforms.

Affine processes, arbitrage-Free Term structures of legendre polynomials,and option pricing

Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

Bias from ignoring price dispersion in demand estimation

Consumers often pay different prices for the same product bought in the same store at the same time. However, the demand estimation literature has ignored that fact using, instead, aggregate measures such as the “list” or average price. In this paper we show that this will lead to biased price coefficients. Furthermore, we perform simple comparative statics simulation exercises for the logit and random coefficient models. In the “list” price case we find that the bias is larger when discounts are higher, proportion of consumers facing discount prices is higher and when consumers are more unwilling to buy the product so that they almost only do it when facing discount. In the average price case we find that the bias is larger when discounts are higher, proportion of consumers that have access to discount are similar to the ones that do not have access and when consumers willingness to buy is very dependent on idiosyncratic shocks. Also bias is less problematic in the average price case in markets with a lot of bargain deals, so that prices are as good as individual. We conclude by proposing ways that the econometrician can reduce this bias using different information that he may have available.

Econometric models of financial risks

The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in the borrower's decision to default or prepay on his mortgage by estimating a multinomial logit model with borrower-specific random coefficients.

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

Stochastic choice analysis of tourism destinations

The analysis of tourist destination choice, defined by intra-country administrative units and by product types “coastal/inland and village/city”, permits the characterisation of tourist flow behaviour, which is fundamental for public planning and business management. In this study, we analyse the determinant factors of tourist destination choice, proposing various research hypotheses relative to the impact of destination attributes and the personal characteristics of tourists. The methodology applied estimates Nested and Random Coefficients Multinomial Logit Models, which allow control over possible correlations among different destinations. The empirical application is realised in Spain on a sample of 3,781 individuals and allows us to conclude that prices, distance to the destination and personal motivations are determinants in destination choice.

The negative effects of failed service recoveries

Research has shown that more than half of attempted recovery efforts fail, producing a ‘double deviation’ effect. Surprisingly, these double deviation effects have received little attention in marketing literature. This paper examines what happens after these critical encounters, which behavior or set of behaviors the customers are prone to follow and how customers’ perceptions of the firm’s recovery efforts influence these behaviors. For the analysis of choice of the type of response (complaining, exit, complaining and exit, and no-switching), we estimate multinomial Logit models with random coefficients (RCL). The results of our study show that magnitude of service failure, explanations, apologies, perceived justice, angry and frustration felt by the customer, and satisfaction with service recovery have a significant effect on customers’ choice of the type of response. Implications from the findings are offered.

Factors that determine the level of commitment of our teaching staff when the implementation of continuous evaluation system takes place

Comunicación presentada en CIDUI 2010, Congreso Internacional Docencia Universitaria e Innovación, Barcelona, 30 junio-2 julio 2010.

Willingness Towards Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.

Fostering Teaching Staff's Engagement in Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.

Methylomic and Transcriptomic Insights Linking Air Pollution and Atherosclerosis

Thesis (Ph.D.)--University of Washington, 2016-06