Добірка наукової літератури з теми "Weak instrument"

This dissertation is intended to provide a statistical foundation for the IV models and shed lights on a number of issues related to the IV method. The first chapter shows that the theoretical Instrumental Variable model can be derived by reparameterization of a well-specified statistical model defined on the joint distribution of the involved random variables as the actual (local) data generation process. This reveals the covariance structure of the error terms of the usual theory-driven instrumental variable model. The revealed covariance structure of the IV model have important implications, particularly, for designing simulation studies. Monte Carlo simulations are used to reexamine the Nelson and Startz (1990a) findings regarding the performance of IV estimators when the instruments are weak. The results from the simulation exercises indicate that the sampling distribution of ^Î _IV is concentrated around ^Î _OLS. The second chapter considers the underlying joint distribution function of the instrumental variable (IV) model and presents an alternative definition for the exogenous and relevant instruments. The paper extracts a system of independent and orthogonal equations that covers up a non-orthogonal structural model and argues that the estimated IV regression is well-specified if the underlying system of equations is well-specified. It proposes a new instrument relevancy measure that does not suffer from the first-stage <i>R²</i> deficiencies. Third chapter argues the application of the IV method in estimation of models with omitted variable. The paper considers the implicit parametrization of statistical models and presents five conditions for an appropriate instruments. Two of them are empirically measurable and can be tested. This improves the literature by adding one more objective criterion for the selection of instruments. This chapter applies the IV method to estimate the rate of return to education in Iran. It argues that the education of two cohorts of Iranians was delayed or cut short by the Cultural Revolution. Therefore, the Cultural Revolution, as an exogenous shock to the supply of education, establishes the year of birth as the exogenous and relevant instrument for education. Using the standard Mincerian earnings function with control for experience, ethnicity, location of residence and sector of employment, the instrumental variable estimate of the return to schooling is equal to 5.6&#37;. The estimation results indicate that the Iranian labor market values degrees more than years of schooling.<br>Ph. D.

Instrumental Variable (IV) methods are widely used in the analysis of economic data when the explanatory variable of interest is endogenous and so OLS estimation of the model is biased. However, if the instruments used do not strongly predict the endogenous variable being instrumented then the IV estimator will also give biased results. Weak Instrument Asymptotic theory can be used to model the strength of the instruments in Two-Stage Least Squares (2SLS) IV models and critical values have been developed to test for Weak Instruments in models with one time period. In the first part of this thesis I extend Weak Instrument Asymptotics to a model with multiple endogenous variables where the instruments available can strongly predict each of the endogenous variables separately but correlation between the endogenous variables means that they cannot be jointly predicted and so the overall strength of the instruments in the model is weak. I develop a partial F-statistic to test for 'Weak Instruments of this form and show that this test has the correct size using currently existing critical values for testing for Weak Instruments. I then extend the Weak Instrument Asymptotics to Panel Data models with multiple time periods, and one endogenous variable. I show that it is no longer possible to use the F -statistic to test for Weak Instruments but it is possible to use the Effective F-statistic developed by Olea and Pflueger (2013) with appropriately clustered standard errors to test for 'Weak Instruments in Pallel Data models. Finally, I extend this analysis to look a AR(l) panel data models and show that it is possible to control the strcngth of the instruments asymptotically by changing the persistence of the autoregressive process. I also show the Effective F-statistic has the correct size in these AR(l) models.

Submitted by Lucas Pimentel Vilela (lvilela@fgvmail.br) on 2013-10-07T17:22:14Z No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)<br>Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2013-10-08T21:33:30Z (GMT) No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2013-10-14T14:44:28Z (GMT) No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)<br>Made available in DSpace on 2013-10-14T14:45:02Z (GMT). No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5) Previous issue date: 2013-09-17<br>This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).<br>Esta dissertação trata do problema de inferência na presença de identificação fraca em modelos de regresso com variáveis instrumentais. Mais especificamente em testes de hipóteses com relação ao parâmetro da variável endógena quando os instrumentos são fracos. O principal foco é nos testes condicionais unilaterais baseados nas estatísticas de razão de máxima verossimilhança, score e Wald. Resultados teóricos e numéricos mostram que o teste t condicional unilateral baseado no estimador de mínimos quadrados em dois estágios tem uma boa performance mesmo na presença de instrumentos fracamente correlacionados com a variável endógena. A abordagem condicional corrige uniformemente o tamanho do teste t e quando a estatística F populacional é tão pequena quanto dois, o poder do teste é próximo ao power envelope tanto de testes similares quanto de não similares. Tal resultado é surpreendente visto a má performance dos testes t’s condicionais bilaterais relatada em (6, Andrews, Moreira and Stock (2007)). Dado esse resultado aparentemente contra intuitivo, apresentamos novos testes t’s condicionals bilaterais que são aproximadamente não viesados e performam, em alguns casos, tão bem quanto o teste condicional baseado na estatística de razão de verossimilhança de ( 19 , Moreira (2003)).

(I A Few-Cluster-Robust Test for Weak Instruments) - ABSTRACT - In the usual IV regression models, the quality of estimation and inference dra- matically depends on the relevance of the set of instruments. To test such condition, most empiricists rely on the first-stage F-statistic as suggested by Stock and Yogo (2005a). However, this method is not valid for clustered data, especially when there are few clusters. Recently, weak instrument-robust methods for inference have been proposed, but none of them deals with the latter case. In this paper, we propose a simple method to perform inference which is robust both to the presence of weak instruments and few clusters in the case of a single endogenous regressor. (II Sharing or gambling over losses?) - ABSTRACT - This paper investigates experimentally whether individuals prefer to share an exogenous loss in a deterministic way or to gamble over it. In particular, in some scenarios subjects face an equal allocation of the loss, in others a social lottery with an equal chance to suffer it entirely. The loss is implemented after the endowment is earned. We find that the loss domain does not affect subjects' behavior directly, but it decreases their probability to play in a competitive way.

<p>Two new specification tests for overidentifying restrictions proposed by Hahn and Hausman (2002:b) are here tested and compared to the classical Sargan test. Power properties are found to be very similar in overall performance, while Sargan generally has better size than the new tests. Also, size is distorted for one of the new tests, thus a tendency to reject prevails. In addition, sometimes severe bias is found which affects the tests’ performances, something that differs from earlier studies.</p>

Les amas de galaxies sont des outils cosmologiques et astrophysiques essentiels, car ce sont les objets les plus grands et les plus massifs gravitationnellement liées dans l'Univers. L'étude de leur fonction de masse, de leur fonction de corrélation et des relations d'échelle entre leur masse et différentes observables nous permettent de tester les prévisions des modèles cosmologique et les scenarii de formation des structures. Ils sont aussi d'intéressants laboratoires pour l'étude de la formation et de l'évolution des galaxies, et de leur interactions avec le milieu qui les entourent, dans d’environnements denses. Pour y parvenir, estimer précisément leur masse revêt une importance fondamentale. J’ai étudié la précision de la richesse optique calculée par l’algorithme de détection d’amas RedGOLD (Licitra et al. 2016) en tant que mass proxy, en utilisant des mesures de lentilles gravitationnelles (weak lensing) et des observations en rayon X. J’ai mesuré les masses cumulées d’un échantillon de 1323 amas de galaxies dans le CFHTLS et NGVS à 0.2<br>Galaxy clusters are essential cosmological and astrophysical tools, since they represent the largest and most massive gravitationally bound structures in the Universe. Through the study of their mass function, of their correlation function, and of the scaling relations between their mass and different observables, we can probe the predictions of cosmological models and structure formation scenarios. They are also interesting laboratories that allow us to study galaxy formation and evolution, and their interactions with the intra-cluster medium, in dense environments. For all of these goals, an accurate estimate of cluster masses is of fundamental importance. I studied the accuracy of the optical richness obtained by the RedGOLD cluster detection algorithm (Licitra et al. 2016) as a mass proxy, using weak lensing and X-ray mass measurements. I measured stacked weak lensing cluster masses for a sample of 1323 galaxy clusters in the CFHTLS W1 and in the NGVS at 0.2