Temporal aggregation and bandwidth selection in estimating long memory

This paper reinterprets results of Ohanissian et al (2003) to show the asymptotic equivalence of temporally aggregating series and using less bandwidth in estimating long memory by Geweke and Porter-Hudak’s (1983) estimator, provided that the same number of periodogram ordinates is used in both cases. This equivalence is in the sense that their joint distribution is asymptotically normal with common mean and variance and unity correlation. Furthermore, I prove that the same applies to the estimator of Robinson (1995). Monte Carlo simulations show that this asymptotic equivalence is a good approximation in finite samples. Moreover, a real example with the daily US Dollar/French Franc exchange rate series is provided.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

Trabalho móvel: em trânsito por aeroportos e aviões

Argumenta-se na contemporaneidade que o trabalho adquiriu a possibilidade de ser realizado “a qualquer hora e em qualquer lugar” e que, particularmente, pode ser realizado em movimento, enquanto a pessoa que trabalha desloca-se de um lugar a outro. Este estudo investiga esse último, o trabalho móvel; em especial, aquele que envolve o uso de tecnologias de informação e comunicação e realizado enquanto a pessoa que trabalha desloca-se por meio do sistema de transporte aéreo. Este projeto explora, especificamente, o desempenho de espaço-tempos de trabalho em terminais de aeroportos e em aviões. Para tanto, adota a abordagem teórico-metodológica Teoria Ator-Rede que considera o social um movimento de associações entre elementos heterogêneos e os espaço-tempos, incluindo aqueles de trabalho, efeitos de modos como humanos e não humanos relacionam-se entre si. A estratégia metodológica envolveu uma combinação de observação de campo, auto-observação e entrevistas com pessoas que vivem a experiência do trabalho móvel. A coleta de dados compreendeu: (a) horas de observação de pessoas e situações, em alguns terminais de aeroportos no Brasil e em voos entre a cidade de São Paulo e outras capitais do país, e (b) entrevistas semiestruturadas com pessoas que, com certa frequência, deslocam-se para trabalhar por meio do sistema de transporte aéreo. Como resultado, este estudo contribui para as análises sobre o fenômeno do trabalho móvel, realizado em aeroportos e aviões, e destaca: os atores envolvidos, bem como os agentes que levam esses atores a agir; a quantidade de objetos ativos na manifestação do fenômeno; e as controvérsias envolvidas com o tema. Além disso, aponta elementos empíricos (i) que revelam lugares em que os fenômenos de trabalho móvel se manifestam esporadicamente, de modo disperso, como “bolhas”, e (ii) que se contrapõem à ideia que é possível trabalhar “a qualquer hora e em qualquer lugar”. As contribuições deste estudo ecoam resultados de pesquisas desenvolvidas sobre trabalho móvel, assim como apresentam particularidades, como a metáfora da bolha, amplificações de aspectos pouco presentes nos textos sobre o tema e elementos peculiares do trabalho móvel investigado no espaço-tempo da pesquisa

On the welfare costs of business-cycle fluctuations and economic-growth variation in the 20th century

Lucas (1987) has shown a surprising result in business-cycle research: the welfare cost of business cycles are very small. Our paper has several original contributions. First, in computing welfare costs, we propose a novel setup that separates the effects of uncertainty stemming from business-cycle fluctuations and economic-growth variation. Second, we extend the sample from which to compute the moments of consumption: the whole of the literature chose primarily to work with post-WWII data. For this period, actual consumption is already a result of counter-cyclical policies, and is potentially smoother than what it otherwise have been in their absence. So, we employ also pre-WWII data. Third, we take an econometric approach and compute explicitly the asymptotic standard deviation of welfare costs using the Delta Method. Estimates of welfare costs show major differences for the pre-WWII and the post-WWII era. They can reach up to 15 times for reasonable parameter values -β=0.985, and ∅=5. For example, in the pre-WWII period (1901-1941), welfare cost estimates are 0.31% of consumption if we consider only permanent shocks and 0.61% of consumption if we consider only transitory shocks. In comparison, the post-WWII era is much quieter: welfare costs of economic growth are 0.11% and welfare costs of business cycles are 0.037% - the latter being very close to the estimate in Lucas (0.040%). Estimates of marginal welfare costs are roughly twice the size of the total welfare costs. For the pre-WWII era, marginal welfare costs of economic-growth and business- cycle fluctuations are respectively 0.63% and 1.17% of per-capita consumption. The same figures for the post-WWII era are, respectively, 0.21% and 0.07% of per-capita consumption.

On the welfare costs of business-cycle fluctuations and economic-growth variation in the 20th century

Lucas(1987) has shown a surprising result in business-cycle research: the welfare cost of business cycles are very small. Our paper has several original contributions. First, in computing welfare costs, we propose a novel setup that separates the effects of uncertainty stemming from business-cycle uctuations and economic-growth variation. Second, we extend the sample from which to compute the moments of consumption: the whole of the literature chose primarily to work with post-WWII data. For this period, actual consumption is already a result of counter-cyclical policies, and is potentially smoother than what it otherwise have been in their absence. So, we employ also pre-WWII data. Third, we take an econometric approach and compute explicitly the asymptotic standard deviation of welfare costs using the Delta Method. Estimates of welfare costs show major diferences for the pre-WWII and the post-WWII era. They can reach up to 15 times for reasonable parameter values = 0:985, and = 5. For example, in the pre-WWII period (1901-1941), welfare cost estimates are 0.31% of consumption if we consider only permanent shocks and 0.61% of consumption if we consider only transitory shocks. In comparison, the post-WWII era is much quieter: welfare costs of economic growth are 0.11% and welfare costs of business cycles are 0.037% the latter being very close to the estimate in Lucas (0.040%). Estimates of marginal welfare costs are roughly twice the size of the total welfare costs. For the pre-WWII era, marginal welfare costs of economic-growth and business-cycle uctuations are respectively 0.63% and 1.17% of per-capita consumption. The same gures for the post-WWII era are, respectively, 0.21% and 0.07% of per-capita consumption.

Essays on Spatial Econometrics

Esta dissertação concentra-se nos processos estocásticos espaciais definidos em um reticulado, os chamados modelos do tipo Cliff & Ord. Minha contribuição nesta tese consiste em utilizar aproximações de Edgeworth e saddlepoint para investigar as propriedades em amostras finitas do teste para detectar a presença de dependência espacial em modelos SAR (autoregressivo espacial), e propor uma nova classe de modelos econométricos espaciais na qual os parâmetros que afetam a estrutura da média são distintos dos parâmetros presentes na estrutura da variância do processo. Isto permite uma interpretação mais clara dos parâmetros do modelo, além de generalizar uma proposta de taxonomia feita por Anselin (2003). Eu proponho um estimador para os parâmetros do modelo e derivo a distribuição assintótica do estimador. O modelo sugerido na dissertação fornece uma interpretação interessante ao modelo SARAR, bastante comum na literatura. A investigação das propriedades em amostras finitas dos testes expande com relação a literatura permitindo que a matriz de vizinhança do processo espacial seja uma função não-linear do parâmetro de dependência espacial. A utilização de aproximações ao invés de simulações (mais comum na literatura), permite uma maneira fácil de comparar as propriedades dos testes com diferentes matrizes de vizinhança e corrigir o tamanho ao comparar a potência dos testes. Eu obtenho teste invariante ótimo que é também localmente uniformemente mais potente (LUMPI). Construo o envelope de potência para o teste LUMPI e mostro que ele é virtualmente UMP, pois a potência do teste está muito próxima ao envelope (considerando as estruturas espaciais definidas na dissertação). Eu sugiro um procedimento prático para construir um teste que tem boa potência em uma gama de situações onde talvez o teste LUMPI não tenha boas propriedades. Eu concluo que a potência do teste aumenta com o tamanho da amostra e com o parâmetro de dependência espacial (o que está de acordo com a literatura). Entretanto, disputo a visão consensual que a potência do teste diminui a medida que a matriz de vizinhança fica mais densa. Isto reflete um erro de medida comum na literatura, pois a distância estatística entre a hipótese nula e a alternativa varia muito com a estrutura da matriz. Fazendo a correção, concluo que a potência do teste aumenta com a distância da alternativa à nula, como esperado.

A (semi-)parametric functional coefficient autoregressive conditional duration model

In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.

The finite-sample size of the BDS test for GARCH standardized residuals

This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation, even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. Nonethe-less, the estimated response surfaces can provide not only a measure of the size distortion, but also more adequate critical values for the BDS test in small samples.

Non- parametric specification tests for conditional duration models

This paper deals with the estimation and testing of conditional duration models by looking at the density and baseline hazard rate functions. More precisely, we foeus on the distance between the parametric density (or hazard rate) function implied by the duration process and its non-parametric estimate. Asymptotic justification is derived using the functional delta method for fixed and gamma kernels, whereas finite sample properties are investigated through Monte Carlo simulations. Finally, we show the practical usefulness of such testing procedures by carrying out an empirical assessment of whether autoregressive conditional duration models are appropriate to oIs for modelling price durations of stocks traded at the New York Stock Exchange.

Multivariate unit root tests

A new multivariate test for the detection ofunit roots is proposed. Use is made ofthe possible correlations between the disturbances of difIerent series, and constrained and unconstrained SURE estimators are employed. The corresponding asymptotic distributions, for the case oftwo series, are obtained and a table with criticai vaIues is generated. Some simulations indivate that the procedure performs better than the existing alternatives.

Inequality treatment effects

This paper presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this paper are those that capture summarized distributional effects of the treatment. In particular, the focus is on the impact of the treatment calculated by differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here inequality treatment effects. The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the reweighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are.computed. Calculations of semiparametric effciency bounds for inequality treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper.

Modelos dinâmicos não lineares e aplicações de quadratura gaussiana

We propose mo deIs to analyze animal growlh data wilh lhe aim of eslimating and predicting quanlities of Liological and economical interest such as the maturing rate and asymptotic weight. lt is also studied lhe effect of environmenlal facLors of relevant influence in the growlh processo The models considered in this paper are based on an extension and specialization of the dynamic hierarchical model (Gamerman " Migon, 1993) lo a non-Iinear growlh curve sdLillg, where some of the growth curve parameters are considered cxchangeable among lhe unils. The inferencc for thcse models are appruximale conjugale analysis Lascd on Taylor series cxpallsiulIs aliei linear Bayes procedures.

Efficient semiparametric estimation of quantile treatment effects

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.

Sustainable silvopastoral systems: theory and a practical case

Muitas transformações são esperadas por causa das mudanças do clima, especialmente das atividades agrícolas realizadas nos trópicos. Esta tese centra-se em dois aspectos. O primeiro deles é o de reunir o conhecimento de sistemas silvipastoris; este ponto de vista estabelece a importância de solos tropicais e sua gestão adequada de acordo com as normas ambientais e sustentáveis. A segunda parte da tese é a aplicação desses princípios em um caso específico: a fazenda "El Paraíso". O objetivo central ou problema a resolver da segunda parte é propor um projeto para melhorar as atividades de produção de carne e, ao mesmo tempo, ajudar a preservar e melhorar o meio ambiente e especialmente os ecossistemas tropicais. A metodologia utilizada na tese foi buscar e analisar informações sobre o assunto. Depois disso, a investigação experimental e de campo foi realizada para levantar o projeto que combinaria as duas partes da obra. No final, com a informação recolhida uma proposta de projeto foi feita. O objetivo era propor a transformação dos processos de produção na fazenda selecionada. Logo de desenvolver e apresentar o projeto, foram analisadas as possibilidades de implementação do projeto. A conclusão do estudo foi o de apresentar e discutir três cenários possíveis após a implementação. Finalmente, a conclusão geral apresenta as realizações, as oportunidades e possíveis expansões futuras do projeto.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.