Nonparametric specification tests for conditional duration models

This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the distance between the parametric density and hazard rate functions implied by the duration process and their non-parametric estimates. We derive the asymptotic justification using the functional delta method for fixed and gamma kernels, and then investigate the finite-sample properties through Monte Carlo simulations. Although our tests display some size distortion, bootstrapping suffices to correct the size without compromising their excellent power. We show the practical usefulness of such testing procedures for the estimation of intraday volatility patterns.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE transactions data, with special attention to IBM price durations. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE price duration data on the IBM stock. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

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.

Dealing with Tyranny: International Sanctions and Autocrats’ Duration

This paper enquires into whether economic sanctions are effective in destabilizing authoritarian rulers. We argue that this effect is mediated by the type of authoritarian regime against which sanctions are imposed. Thus, personalist regimes and monarchies, which are more dependent on aid and resource rents to maintain their patronage networks, are more likely to be affected by sanctions. In contrast, single-party and military regimes are able to maintain (and even increase) their tax revenues and to reallocate their expenditures and so increase their levels of cooptation. Data on sanction episodes, authoritarian rulers and regimes covering the period 1946–2000 have allowed us to test our hypotheses. To do so, duration models have been run, and the results confirm that personalist autocrats are more vulnerable to foreign pressure. Concretely, the analysis of the modes of exit reveals that sanctions increase the likelihood of an irregular change of ruler, such as a coup. Sanctions are basically ineffective when targeting single-party or military regimes.

The Determinants of Urban (Un)employment Duration: Evidence from Barcelona

This paper analyses the likelihood of leaving and joining employment in an urban area. Estimates show that individual, firm, regulatory and macroeconomic factors a ffect urban (un)employment duration in di fferent degrees. Also, national and urban (un)employment seem to share a common baseline hazard and similar macroeconomic and regulatory drivers. Individual characteristics are the only source of di fference we can identify between national and urban (un)employment duration. Keywords: Duration Models, Urban (Un)employment. JEL Classi fication: J64, R23.

A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.

Employment, turnover and career progress

The severe economic downturn that followed the Global Financial Crisis of 2007 was accompanied by major fluctuations in the labour market. During the Great Recession the rate of job destruction was such that, by 2013, active population was at levels of 1999; employment levels were at an historical minimum; and the unemployment rate soared to 17,5%. This chapter inspects the dynamics behind the aggregate fl uctuations in the labour market and studies the determinants of mobility within (promotions) and between fi rms, and whether these have changed during crisis, using Portuguese (LEED) data. During crisis women became more likely to make between- rm moves with short gaps of unemployment and less likely to find a new job after a long gap or to make a job-to-non-employment transition. More educated workers are less likely to experience between fi rm job mobility, both before and during crisis, and became less likely to make job-to-non-employment transitions during crisis. Young workers are the group that most suffered from crisis: they became less likely to make job-to-job transitions and their hazard of experiencing a transition into unemployment shoot up.

How binding are legal limits? Transitions from temporary to permanent work in Spain

This paper studies the duration pattern of xed-term contracts and the determinantsof their conversion into permanent ones in Spain, where the share of xed-termemployment is the highest in Europe. We estimate a duration model for temporaryemployment, with competing risks of terminating into permanent employment versusalternative states, and exible duration dependence. We nd that conversion rates aregenerally below 10%. Our estimated conversion rates roughly increase with tenure,with a pronounced spike at the legal limit, when there is no legal way to retain theworker on a temporary contract. We argue that estimated di¤erences in conversionrates across categories of workers can stem from di¤erences in worker outside optionsand thus the power to credibly threat to quit temporary jobs.

Sector-Specific on-the-Job Training: Evidence from U.S. Data.

Using data from the National Longitudinal Survey of Youth (NLSY), we re-examine the effect of formal on-the-job training on mobility patterns of young American workers. By employing parametric duration models, we evaluate the economic impact of training on productive time with an employer. Confirming previous studies, we find a positive and statistically significant impact of formal on-the-job training on tenure with the employer providing the training. However, the expected net duration of the time spent in the training program is generally not significantly increased. We proceed to document and analyze intra-sectoral and cross-sectoral mobility patterns in order to infer whether training provides firm-specific, industry-specific, or general human capital. The econometric analysis rejects a sequential model of job separation in favor of a competing risks specification. We find significant evidence for the industry-specificity of training. The probability of sectoral mobility upon job separation decreases with training received in the current industry, whether with the last employer or previous employers, and employment attachment increases with on-the-job training. These results are robust to a number of variations on the base model.

Les modèles vectoriels et multiplicatifs avec erreurs non-négatives de séries chronologiques.

L'objectif du présent mémoire vise à présenter des modèles de séries chronologiques multivariés impliquant des vecteurs aléatoires dont chaque composante est non-négative. Nous considérons les modèles vMEM (modèles vectoriels et multiplicatifs avec erreurs non-négatives) présentés par Cipollini, Engle et Gallo (2006) et Cipollini et Gallo (2010). Ces modèles représentent une généralisation au cas multivarié des modèles MEM introduits par Engle (2002). Ces modèles trouvent notamment des applications avec les séries chronologiques financières. Les modèles vMEM permettent de modéliser des séries chronologiques impliquant des volumes d'actif, des durées, des variances conditionnelles, pour ne citer que ces applications. Il est également possible de faire une modélisation conjointe et d'étudier les dynamiques présentes entre les séries chronologiques formant le système étudié. Afin de modéliser des séries chronologiques multivariées à composantes non-négatives, plusieurs spécifications du terme d'erreur vectoriel ont été proposées dans la littérature. Une première approche consiste à considérer l'utilisation de vecteurs aléatoires dont la distribution du terme d'erreur est telle que chaque composante est non-négative. Cependant, trouver une distribution multivariée suffisamment souple définie sur le support positif est plutôt difficile, au moins avec les applications citées précédemment. Comme indiqué par Cipollini, Engle et Gallo (2006), un candidat possible est une distribution gamma multivariée, qui impose cependant des restrictions sévères sur les corrélations contemporaines entre les variables. Compte tenu que les possibilités sont limitées, une approche possible est d'utiliser la théorie des copules. Ainsi, selon cette approche, des distributions marginales (ou marges) peuvent être spécifiées, dont les distributions en cause ont des supports non-négatifs, et une fonction de copule permet de tenir compte de la dépendance entre les composantes. Une technique d'estimation possible est la méthode du maximum de vraisemblance. Une approche alternative est la méthode des moments généralisés (GMM). Cette dernière méthode présente l'avantage d'être semi-paramétrique dans le sens que contrairement à l'approche imposant une loi multivariée, il n'est pas nécessaire de spécifier une distribution multivariée pour le terme d'erreur. De manière générale, l'estimation des modèles vMEM est compliquée. Les algorithmes existants doivent tenir compte du grand nombre de paramètres et de la nature élaborée de la fonction de vraisemblance. Dans le cas de l'estimation par la méthode GMM, le système à résoudre nécessite également l'utilisation de solveurs pour systèmes non-linéaires. Dans ce mémoire, beaucoup d'énergies ont été consacrées à l'élaboration de code informatique (dans le langage R) pour estimer les différents paramètres du modèle. Dans le premier chapitre, nous définissons les processus stationnaires, les processus autorégressifs, les processus autorégressifs conditionnellement hétéroscédastiques (ARCH) et les processus ARCH généralisés (GARCH). Nous présentons aussi les modèles de durées ACD et les modèles MEM. Dans le deuxième chapitre, nous présentons la théorie des copules nécessaire pour notre travail, dans le cadre des modèles vectoriels et multiplicatifs avec erreurs non-négatives vMEM. Nous discutons également des méthodes possibles d'estimation. Dans le troisième chapitre, nous discutons les résultats des simulations pour plusieurs méthodes d'estimation. Dans le dernier chapitre, des applications sur des séries financières sont présentées. Le code R est fourni dans une annexe. Une conclusion complète ce mémoire.

Uso de modelos econométricos en aseguramiento de portafolios

El aseguramiento de portafolio trae consigo unos costos de transacción asociados que son reconocidos por la teoría financiera pero que no han sido objeto de estudio de muchas aproximaciones empíricas. Mediante modelos econométricos de series de tiempo se puede pronosticar el número de rebalanceos necesarios para mantener un portafolio asegurado, así como el tiempo que debe transcurrir entre cada uno de estos. Para tal fin se usan modelos de Datos de Cuenta de Poisson Autorregresivos (ACP) modificados para captar las características de la serie y modelos de Duración Autorregresivos (ACD). Los modelos capturan la autocorrelación de las series y pronostican adecuadamente el costo de transacción asociado a los rebalanceos.

Determinantes de la deserción universitaria en la Facultad de Economía de la Universidad del Rosario

Este trabajo analiza el problema de la deserción estudiantil en la Facultad de Economía de la Universidad del Rosario, a través del estudio de los factores individuales, académicos y socioeconómicos que implican el riesgo de desertar. Con este objetivo, se utiliza el análisis de modelos de duración. Específi camente, se estima un modelo de riesgo proporcional de tiempo discreto con y sin heterogeneidad observada (Prentice- Gloeckler, 1978 y Meyer, 1980). Los resultados muestran que los estudiantes de sexo masculino, la vinculación de los estudiantes al mercado laboral y los estudiantes provenientes de otras regiones, tienen el mayor riesgo de deserción. Además, la edad del estudiante incrementa el riesgo, sin embargo, su efecto decrece marginalmente al aumentar la edad. Palabras clave: deserción estudiantil, modelos de duración, riesgo proporcional. Clasifi cación JEL: C41, C13, I21.

Custos de ajustamento e a dinâmica da estrutura de capital em empresas brasileiras

Diversos estudos de Finanças Corporativas consideram os custos associados aos ajustes da estrutura de capital das empresas irrelevantes tanto na forma quanto em magnitude. Este estudo analisou empiricamente a influência dos custos de ajustamento na dinâmica dos ajustes da estrutura de capital de empresas brasileiras de capital aberto no período de 1999 a 2007. A alavancagem foi abordada sob três diferentes cenários, considerando a presença de custos fixos, custos proporcionais e por uma composição de custos fixos e proporcionais através de simulações utilizando um modelo reduzido da estrutura de capital. Em seguida a análise não paramétrica da amostra revelou que as empresas apresentam um comportamento dinâmico em suas decisões de financiamento para o ajuste da estruturas de capital, mas que não se revelou contínuo. A utilização de um modelo de duration mostrou-se adequado para mensurar o intervalo de tempo entre os ajustes da estrutura de capital das empresas. Os resultados são extremamente relevantes e suportam a teoria de um comportamento de rebalanceamento dinâmico pelas empresas de suas estruturas de capital em torno de um intervalo ótimo. Entretanto os ajustes não ocorrem de forma imediata e a persistência de choques à estrutura de capital deve-se em sua maior parte aos custos associados aos ajustes do que a uma possível indiferença à estrutura de capital. . Este trabalho constitui-se como pioneiro no mercado brasileiro acerca dos custos de ajustamento da estrutura de capital e abre espaço para a discussão do comportamento ótimo em torno da estrutura de capital de empresas nacionais.

A utilização de modelos de duração para gerenciar risco de crédito

Os modelos hazard, também conhecidos por modelos de tempo até a falência ou duração, são empregados para determinar quais variáveis independentes têm maior poder explicativo na previsão de falência de empresas. Consistem em uma abordagem alternativa aos modelos binários logit e probit, e à análise discriminante. Os modelos de duração deveriam ser mais eficientes que modelos de alternativas discretas, pois levam em consideração o tempo de sobrevivência para estimar a probabilidade instantânea de falência de um conjunto de observações sobre uma variável independente. Os modelos de alternativa discreta tipicamente ignoram a informação de tempo até a falência, e fornecem apenas a estimativa de falhar em um dado intervalo de tempo. A questão discutida neste trabalho é como utilizar modelos hazard para projetar taxas de inadimplência e construir matrizes de migração condicionadas ao estado da economia. Conceitualmente, o modelo é bastante análogo às taxas históricas de inadimplência e mortalidade utilizadas na literatura de crédito. O Modelo Semiparamétrico Proporcional de Cox é testado em empresas brasileiras não pertencentes ao setor financeiro, e observa-se que a probabilidade de inadimplência diminui sensivelmente após o terceiro ano da emissão do empréstimo. Observa-se também que a média e o desvio-padrão das probabilidades de inadimplência são afetados pelos ciclos econômicos. É discutido como o Modelo Proporcional de Cox pode ser incorporado aos quatro modelos mais famosos de gestão de risco .de crédito da atualidade: CreditRisk +, KMV, CreditPortfolio View e CreditMetrics, e as melhorias resultantes dessa incorporação