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Author: Firmin Doko Tchatoka
Publisher:
ISBN: 9782893827032
Category :
Languages : en
Pages :
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Book Description
Author: Firmin Doko Tchatoka
Publisher:
ISBN: 9782893827032
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Firmin Doko Tchakota
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Juan Jose Dolado
Publisher:
ISBN:
Category :
Languages : en
Pages : 29
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Book Description
A common practice in empirical work is to estimate the conditional mean of a variable y on another variable x, ignoring its marginal density. Weak exogeneity of x for the parameters of interest in the conditional mean ensures valid inference. Available weak exogeneity tests correspond to a Gaussian-linear environment. However, there are some variables, typically related to financial marked-point processes, where non-Gaussian distributions and nonlinear means are much more appropriate assumptions. We propose two tests for weak exogeneity when the density is not necessarily Gaussian but belongs to the the family of exponential densities, and the conditional and marginal means are nonlinear. Both tests exploit dependencies (lack of free variation), under the alternative hypotesis, among parameters in both means. To illustrate this testing procedure, we analyze the relationship between trade size and trade durations for four stocks traded at NYSE. The null hypothesis of weak exogeneity is often rejected, questioning therefore some results in the literature which rely on separate estimation of each density.
Author: Alexander Chudik
Publisher: Emerald Group Publishing
ISBN: 1802620656
Category : Business & Economics
Languages : en
Pages : 376
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Book Description
The collection of chapters in Volume 43 Part B of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
Author: Jean-Pierre Urbain
Publisher: Springer Science & Business Media
ISBN: 3642957064
Category : Business & Economics
Languages : en
Pages : 201
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Book Description
In the recent years, the study of cointegrated time series and the use of error correction models have become extremely popular in the econometric literature. This book provides an analysis of the notion of (weak) exogeneity, which is necessary to sustain valid inference in sub-systems, inthe framework of error correction models (ECMs). In many practical situations, the applied econometrician wants to introduce "structure" on his/her model in order to get economically meaningful coefficients. For thispurpose, ECMs in structural form provide an appealing framework, allowing the researcher to introduce (theoretically motivated) identification restrictions on the long run relationships. In this case, the validity of the inference will depend on a number of conditions which are investigated here. In particular,we point out that orthogonality tests, often used to test for weak exogeneity or for general misspecification, behave poorly in finite samples and are often not very useful in cointegrated systems.
Author: Katarzyna Bech
Publisher:
ISBN:
Category :
Languages : en
Pages : 38
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Book Description
This paper presents new approaches to testing for exogeneity in non-parametric models with discrete regressors and instruments. Our interest is in learning about an unknown structural (conditional mean) function. An interesting feature of these models is that under endogeneity the identifying power of a discrete instrument depends on the number of support points of the instruments relative to that of the regressors, a result driven by the discreteness of the variables. Observing that the simple nonparametric additive error model can be interpreted as a linear regression, we present two test-statistics. For the point identifying model, the test is an adapted version of the standard Wu-Hausman approach. This extends the work of Blundell and Horowitz (2007) to the case of discrete regressors and instruments. For the set identifying model, the Wu-Hausman approach is not available. In this case the test-statistic is derived from a constrained minimization problem. The asymptotic distributions of the test-statistics are derived under the null and fixed and local alternatives. The tests are shown to be consistent, and a simulation study reveals that the proposed tests have satisfactory finite-sample properties.
Author: Mehmet Caner
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper analyzes near exogeneity and weak identification in Generalized Empirical Likelihood Estimators. Near exogeneity and weak identification are related to the exogeneity and relevance of the instruments, respectively. These two issues are important from an applied perspective, such as empirical growth theory and labor economics. In the case of empirical growth and institutional economics literature a small number of moments/instruments are used in studies. First, we analyze the limit behavior of estimators and tests under fixed number of weak moments and near exogeneity. We show that Anderson-Rubin (1949) and Kleibergen (2002) type of tests' limits change when there is small correlation between the instruments and the structural equation error. The new limits are obtained under the null hypothesis at the true vale of the parameter. The test statistics are no longer asymptotically pivotal in the joint case of near exogeneity and weak instruments compared to the weak identification case. We also show that when used with the x2 critical values, which are not valid in the case of near exogeneity and weak instruments, the tests show very large size distortions. This is an important warning to applied researchers who may use these tests without taking into account the near exogeneity problem. We try subsampling and delete-d jackknife methods to recover asymptotic limits. Both of these methods are inconsistent. However, we show that the asymptotic limit of delete-d jackknife is arbitrarily close to true limit and only slightly liberal. In simulations, exponential tilting based tests with delete-d jackknife method have good size compared to the others. Then we develop the limits of estimators and tests under many weak moments with near exogeneity. The results are different from the fixed moments case. Estimators are consistent, and test limits are simple, noncentral x2.
Author: Enrique Moral-Benito
Publisher:
ISBN:
Category :
Languages : en
Pages : 23
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Book Description
For reason of empirical tractability, analysis of cointegrated economic time series is often developed in a partial setting, in which a subset of variables is explicitly modeled conditional on the rest. This approach yields valid inference only if the conditioning variables are weakly exogenous for the parameters of interest. This paper proposes a new test of weak exogeneity in panel cointegration models. The test has a limiting Gumbel distribution that is obtained by first letting the time dimension of the panel go to infinity and then letting its cross-sectional dimension go to infinity.The paper evaluates the accuracy of the asymptotic approximation in finite samples via simulation experiments. Finally, as an empirical illustration, the paper reports tests of weak exogeneity of disposable income and wealth in an aggregate consumption equation.
Author: Purevdorj Tuvaandorj
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"This thesis makes contributions to weak identification, modelselection and hypothesis testing in econometrics. It consists of thefollowing essays.In Chapter 1, we study likelihood-basedinference in models with possible identification failure. The results relyheavily on the properties of the mapping from structural parameters togeneralized reduced-form parameters (which are identified by construction).We establish an asymptotic chi-square bound on the likelihood ratio (LR)statistic for testing restrictions on the possibly unidentified structuralparameters with degrees of freedom equal to the dimension of the reducedform parameter vector through which the tested parameters enter thelikelihood function. We also propose pivotal C(alpha)-type statisticsthat are robust to potential identification failure and are flexible inincorporating a wide class of estimators of the (strongly identified)nuisance parameters. Furthermore, we develop a generalized version of theclassical Anderson-Rubin (AR)-type statistic in linear simultaneousequations and an identification-robust pretest-based inference procedure.In Chapter 2, we study the invariance properties of various test criteria which have been proposed for hypothesis testing in the context of incompletely specified models, such asmodels which are formulated in terms of estimating functions (Godambe, 1960, Ann. Math. Stat.) or moment conditions and are estimated bygeneralized method of moments (GMM) procedures (Hansen, 1982, Econometrica), and models estimated by pseudo-likelihood (Gourieroux,Monfort and Trognon, 1984, Econometrica) and M-estimation methods.The invariance properties considered include invariance to (possiblynonlinear) hypothesis reformulations and reparameterizations. The teststatistics examined include Wald-type, LR-type, LM-type, score-type, and C(alpha)-type criteria. In Chapter 3, we propose generalized C(alpha) tests for testing linear and nonlinear parameterrestrictions in models specified by estimating functions. The asymptotic distribution of theproposed statistic is established under weak regularity conditions. We show that earlierC(alpha)-type statistics are included as special cases. The problem of testing hypotheses fixinga subvector of the complete parameter vector of the model is discussed in detail. In Chapter 4, we consider conditional distribution and conditional density functionalsin the space of generalized functions. We obtain the limit of the kernel estimators for weakly dependent data, evenunder non-differentiability of the distribution function; the limit Gaussian process is characterizedas a stochastic random functional (random generalized function) on the suitablefunction space. An alternative simple to compute estimator based on the empirical distribution function is proposed for the generalized random functional. For test statistics based on this estimator, limit properties are established.Chapter 5, considers the issue of selecting the number of regressors and the numberof structural breaks in multivariate regression models in the possible presence of multiplestructural changes. We develop a modified Akaike's information criterion (AIC), amodified Mallows' Cp criterion and a modified Bayesian information criterion (BIC). Thepenalty terms in these criteria are shown to be different from the usual terms." --
Author: Christian Homburg
Publisher: Springer
ISBN: 9783319574110
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
In this handbook, internationally renowned scholars outline the current state-of-the-art of quantitative and qualitative market research. They discuss focal approaches to market research and guide students and practitioners in their real-life applications. Aspects covered include topics on data-related issues, methods, and applications. Data-related topics comprise chapters on experimental design, survey research methods, international market research, panel data fusion, and endogeneity. Method-oriented chapters look at a wide variety of data analysis methods relevant for market research, including chapters on regression, structural equation modeling (SEM), conjoint analysis, and text analysis. Application chapters focus on specific topics relevant for market research such as customer satisfaction, customer retention modeling, return on marketing, and return on price promotions. Each chapter is written by an expert in the field. The presentation of the material seeks to improve the intuitive and technical understanding of the methods covered.
