Conditional mean functions of non-linear models of US output

We compare a number of models of post War US output growth in terms of the degree and pattern of non-linearity they impart to the conditional mean, where we condition on either the previous period's growth rate, or the previous two periods' growth rates. The conditional means are estimated non-parametrically using a nearest-neighbour technique on data simulated from the models. In this way, we condense the complex, dynamic, responses that may be present in to graphical displays of the implied conditional mean.

Forecasting exchange rate volatility using conditional variance models selected by information criteria

This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

Tests of conditional asset pricing models in the brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

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.

A conditional likelihood ratio test for structural models

This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

Conditional and transgenic mouse models as tools to study the role of TGFbeta, BMP signaling in skeletal development

Die TGFbeta/BMP Signaltransduktionskaskade ist wichtig für viele Entwicklungsprozesse fast aller embryonaler sowie extraembryonaler Gewebe und sie ist ebenso essentiell bei der Aufrechterhaltung der Homöostase im adulten Organismus. In vielen Mausmodellen und Zellkulturversuchen wurde gezeigt, dass Liganden dieses Signalweges in verschiedene Stadien der Knorpel- und Knochenentwicklung involviert sind. BMPs sind beispielsweise maßgeblich an der frühen Kondensation und Bildung des Knorpels und später an Proliferation und Hypertrophie der Chondrozyten beteiligt. BMPs können ektopisch Knochenbildung auslösen und das Expressionsmuster der Liganden und spezifischen Rezeptoren in der Wachstumsfuge lässt auf eine wichtige Rolle der BMPs in der Wachstumsfuge schließen. Der gezielte knock out der BMP-Rezeptoren Bmpr1a und Bmpr1b in proliferierenden Chondrozyten führt zur Ausbildung einer generellen Chondrodysplasie. Smad1, Smad5 und Smad8 sind die Mediatoren der BMP-Signalkaskade. Im Rahmen der vorliegenden Arbeit sollte die Rolle und Funktion der Smad1- und Smad5-Proteine in der Wachstumsfuge untersucht werden. Hierzu wurden konditionale Smad1-knock out-Mäuse mit einer transgenen Mauslinie gekreuzt, die die Cre-Rekombinase spezifisch in proliferierenden Chondrozyten exprimiert. Diese Mäuse wurden mit und ohne heterozygotem Smad5-Hintergrund charakterisiert. Bei einem knock out von Smad1 allein konnte ein leichte Verkürzung der Wachstumsfuge beobachtet werden, wobei prähypertrophe und hypertrophe Zone gleichermaßen betroffen waren. Dieser Phänotyp war verstärkt in Mäusen mit zusätzlichem heterozygotem Smad5-Hintergrund. Eine Verringerung der Proliferationsrate konnte zusammen mit einer verminderten Ihh-Expression nachgewiesen werden. Zusätzlich konnte anhand von Röntgenaufnahmen eine Dysorganisation der nasalen Region und ein fehlendes nasales Septum beobachtet werden. Produktion und Mineralisation der extrazellulären Matrix waren nicht beeinträchtigt. Um die Rolle der BMP- und TGFbeta-Signalkaskaden während der endochondralen Ossifikation zu vergleichen, wurden transgene Mäuse generiert, in denen die TGFbeta-Signalkaskade spezifisch in proliferierenden Chondrozyten gestört war. Zwei Mauslinien, die ähnliche Phänotypen zeigten, wurden untersucht. Esl1 ist ein TGFbeta-bindendes Protein, von dem man annimmt, dass es die TGFbeta-Signalkaskade inhibieren kann. Esl1-knock out-Mäuse sind kleiner als Wildtypmäuse und die Überexpression von Esl1 in proliferierenden Chondrozyten führt zu einer Verlängerung der Wachstumsfuge und einer verstärkten Proliferationsrate. Knorpelmarker, wie Col2a1 und Sox9 sind in diesen Mäusen herunterreguliert, während Col10a1 und Ihh als Marker für die hypertrophe und prähypertrophe Zone herunterreguliert waren. Dies führt zu der Annahme, dass mehr Zellen in die terminale Differenzierung eintreten. Bei transgenen Mäusen, in denen ein dominant-negativer (dn) TGFbeta-Rezeptor in proliferierenden Chondrozyten überexprimiert wurde, konnte eine verlängerte prähypertrophe Zone, eine erhöhte Ihh-Expression, sowie eine verstärkte Proliferationsrate beobachtet werden. Zusätzlich konnte in homozygoten Tieren ein craniofacialer Phänotyp beschrieben werden, der zu Problemen bei der Nahrungsaufnahme und damit zu einer starken Wachstumsbeeinträchtigung führte. Die BMP- und TGFbeta-Signalkaskaden haben möglicherweise antagonistische Effekte in der Wachstumsfuge. Während der Ausfall von BMP in proliferierenden Chondrozyten aufgrund einer gesunkenen Proliferationsrate zu einer Verkürzung der Wachstumsfuge führte, kann man in Mäusen mit einer Störung der TGFbeta-Signalkaskade eine verstärkte Proliferation in einer daher verlängerten Wachstumsfuge beobachten. Ein weiteres Ziel dieser Arbeit war die Generation einer transgenen Mauslinie, die die Cre-Rekombinase spezifisch in hypertrophen Chondrozyten exprimiert. Promoterstudien mit transgenen Mäusen weisen darauf hin, dass ein putatives AP1-Element, etwa 4 kb vor dem ersten Exon des Col10a1 gelegen, wichtig für die spezifische Expression in hypertrophen Chondrozyten ist. Ein Konstrukt, dass vier Kopien dieses Elements und den basalen Promoter enthält, wurde benutzt, um die Cre-Rekombinase spezifisch zu exprimieren. Diese Mauslinie befindet sich in der Testphase und erste Daten deuten auf eine spezifische Expression der Cre-Rekombinase in hypertrophen Chondrozyten hin.

On the Behaviour of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models

In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion (AIC) have been used, based either on the marginal or on the conditional distribution. We show that the marginal AIC is no longer an asymptotically unbiased estimator of the Akaike information, and in fact favours smaller models without random effects. For the conditional AIC, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that leads to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional AIC, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

Postnatal Notch1 activation induces T‑cell malignancy in conditional and inducible mouse models

The Notch1 signaling pathway is essential for hematopoietic development. However, the effects of postnatal activation of Notch1 signaling on hematopoietic system is not yet fully understood. We previously generated ZEG‑IC‑Notch1 transgenic mice that have a floxed β‑geo/stop signal between a CMV promoter and intracellular domain of Notch1 (IC‑Notch1). Constitutively active IC‑Notch1 is silent until the introduction of Cre recombinase. In this study, endothelial/hematopoietic specific expression of IC‑Notch1 in double transgenic ZEG‑IC‑Notch1/Tie2‑Cre embryos induced embryonic lethality at E9.5 with defects in vascular system but not in hematopoietic system. Inducible IC‑Notch1 expression in adult mice was achieved by using tetracycline regulated Cre system. The ZEG‑IC‑Notch1/Tie2‑tTA/tet‑O‑Cre triple transgenic mice survived embryonic development when maintained on tetracycline. Post‑natal withdrawal of tetracycline induced expression of IC‑Notch1 transgene in hematopoietic cells of adult mice. The triple transgenic mice displayed extensive T‑cell infiltration in multiple organs and T‑cell malignancy of lymph nodes. In addition, the protein levels of p53 and alternative reading frame (ARF) were decreased in lymphoma‑like neoplasms from the triple transgenic mice while their mRNA expression remained unchanged, suggesting that IC‑Notch1 might repress ARF‑p53 pathway by a post‑transcriptional mechanism. This study demonstrated that activation of constitutive Notch1 signaling after embryonic development alters adult hematopoiesis and induces T‑cell malignancy.

Bayesian estimation in generalized autoregressive conditional heteroskedasticity models

Esta tesis doctoral nace con el propósito de entender, analizar y sobre todo modelizar el comportamiento estadístico de las series financieras. En este sentido, se puede afirmar que los modelos que mejor recogen las especiales características de estas series son los modelos de heterocedasticidad condicionada en tiempo discreto,si los intervalos de tiempo en los que se recogen los datos lo permiten, y en tiempo continuo si tenemos datos diarios o datos intradía. Con esta finalidad, en esta tesis se proponen distintos estimadores bayesianos para la estimación de los parámetros de los modelos GARCH en tiempo discreto (Bollerslev (1986)) y COGARCH en tiempo continuo (Kluppelberg et al. (2004)). En el capítulo 1 se introducen las características de las series financieras y se presentan los modelos ARCH, GARCH y COGARCH, así como sus principales propiedades. Mandelbrot (1963) destacó que las series financieras no presentan estacionariedad y que sus incrementos no presentan autocorrelación, aunque sus cuadrados sí están correlacionados. Señaló también que la volatilidad que presentan no es constante y que aparecen clusters de volatilidad. Observó la falta de normalidad de las series financieras, debida principalmente a su comportamiento leptocúrtico, y también destacó los efectos estacionales que presentan las series, analizando como se ven afectadas por la época del año o el día de la semana. Posteriormente Black (1976) completó la lista de características especiales incluyendo los denominados leverage effects relacionados con como las fluctuaciones positivas y negativas de los precios de los activos afectan a la volatilidad de las series de forma distinta.