EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book Efficient Estimation of the Semiparametric Spatial Autoregressive Model

Download or read book Efficient Estimation of the Semiparametric Spatial Autoregressive Model written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Efficient Estimation of the Semiparametric Spatial Autoregressive Model

Download or read book Efficient Estimation of the Semiparametric Spatial Autoregressive Model written by and published by . This book was released on 2008 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing nonstochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series nonparametric estimates of the score function are employed in adaptive estimates of parameters of interest. These estimates are as efficient as ones based on a correct form, in particular they are more efficient than pseudo-Gaussian maximum likelihood estimates at non-Gaussian distributions. Two different adaptive estimates are considered. One entails a stringent condition on the spatial weight matrix, and is suitable only when observations have substantially many quot;neighboursquot;. The other adaptive estimate relaxes this requirement, at the expense of alternative conditions and possible computational expense. A Monte Carlo study of finite sample performance is included.

Book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer Valued Ar P  Models

Download or read book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer Valued Ar P Models written by Feike C. Drost and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on the nonnegative integers, called an immigration or innovation distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to belong to a parametric family. This paper instead considers a more realistic semiparametric INAR(p) model where there are essentially no restrictions on the innovation distribution. We provide an (semiparametrically) efficient estimator of both the autoregression parameters and the innovation distribution.

Book Efficient and Adaptive Estimation for Semiparametric Models

Download or read book Efficient and Adaptive Estimation for Semiparametric Models written by Peter J. Bickel and published by Springer. This book was released on 1998-06-01 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with estimation in situations in which there is believed to be enough information to model parametrically some, but not all of the features of a data set. Such models have arisen in a wide context in recent years, and involve new nonlinear estimation procedures. Statistical models of this type are directly applicable to fields such as economics, epidemiology, and astronomy.

Book The Oxford Handbook of Panel Data

Download or read book The Oxford Handbook of Panel Data written by Badi Hani Baltagi and published by . This book was released on 2015 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.

Book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer valued AR p  Models

Download or read book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer valued AR p Models written by Feike Cornelis Drost and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Spatial AutoRegression  SAR  Model

Download or read book Spatial AutoRegression SAR Model written by Baris M. Kazar and published by Springer Science & Business Media. This book was released on 2012-03-02 with total page 81 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and approximate spatial autoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function. The second part of the book introduces theory on SAR model solutions. The third part of the book applies parallel processing techniques to the exact SAR model solutions. Parallel formulations of the SAR model parameter estimation procedure based on ML theory are probed using data parallelism with load-balancing techniques. Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led the book to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the fourth and fifth parts of the book, two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials are presented. Experiments show that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy. In the last part of the book, we developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term, which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter for all of the approximate SAR model solutions.

Book Handbook of Spatial Analysis in the Social Sciences

Download or read book Handbook of Spatial Analysis in the Social Sciences written by Sergio J. Rey and published by Edward Elgar Publishing. This book was released on 2022-11-18 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing an authoritative assessment of the current landscape of spatial analysis in the social sciences, this cutting-edge Handbook covers the full range of standard and emerging methods across the social science domain areas in which these methods are typically applied. Accessible and comprehensive, it expertly answers the key questions regarding the dynamic intersection of spatial analysis and the social sciences.

Book Semiparametric Estimation of Censored Spatial Autoregressive Models

Download or read book Semiparametric Estimation of Censored Spatial Autoregressive Models written by Tadao Hoshino and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This study considers the estimation of spatial autoregressive models with censored dependent variables, where the spatial autocorrelation exists within the uncensored latent dependent variables. The estimator proposed in this paper is semiparametric, in the sense that the error distribution is not parametrically specified and can be heteroscedastic. Under a median restriction, we show that the proposed estimator is consistent and asymptotically normally distributed. As an empirical illustration, we investigate the determinants of the risk of assault and other violent crimes including injury in the Tokyo metropolitan area.

Book Efficient Maximum Likelihood Estimation of Spatial Autoregressive Models with Normal But Heteroskedastic Disturbances

Download or read book Efficient Maximum Likelihood Estimation of Spatial Autoregressive Models with Normal But Heteroskedastic Disturbances written by Takahisa Yokoi and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Likelihood functions of spatial autoregressive models with normal but heteroskedastic disturbances have been already derived [Anselin (1988, ch.6)]. But there is no implementation for maximum likelihood estimation of these likelihood functions in general (heteroskedastic disturbances) cases. This is the reason why less efficient IV-based methods, 'robust 2-SLS' estimation for example, must be applied when disturbance terms may be heteroskedastic. In this paper, we develop a new computer program for maximum likelihood estimation and confirm the efficiency of our estimator in heteroskedastic disturbance cases using Monte Carlo simulations.

Book Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models

Download or read book Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models written by Emir Malikov and published by . This book was released on 2017 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in which unknown coefficients are permitted to be nonparametric functions of some contextual variables to allow for potential nonlinearities and parameter heterogeneity in the spatial relationship. Unlike other semiparametric spatial dependence models, ours permits the spatial autoregressive parameter to meaningfully vary across units and thus allows the identification of a neighborhood-specific spatial dependence measure conditional on the vector of contextual variables. We propose several (locally) nonparametric GMM estimators for our model. The developed two-stage estimators incorporate both the linear and quadratic orthogonality conditions and are capable of accommodating a variety of data generating processes, including the instance of a pure spatially autoregressive semiparametric model with no relevant regressors as well as multiple partially linear specifications. All proposed estimators are shown to be consistent and asymptotically normal. We also contribute to the literature by putting forward two test statistics to test for parameter constancy in our model. Both tests are consistent.

Book Issues in General Economic Research and Application  2011 Edition

Download or read book Issues in General Economic Research and Application 2011 Edition written by and published by ScholarlyEditions. This book was released on 2012-01-09 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in General Economic Research and Application: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about General Economic Research and Application. The editors have built Issues in General Economic Research and Application: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about General Economic Research and Application in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in General Economic Research and Application: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Book The Palgrave Companion to LSE Economics

Download or read book The Palgrave Companion to LSE Economics written by Robert A. Cord and published by Springer. This book was released on 2019-01-18 with total page 949 pages. Available in PDF, EPUB and Kindle. Book excerpt: The London School of Economics (LSE) has been and continues to be one of the most important global centres for economics. With six chapters on themes in LSE economics and 29 chapters on the lives and work of LSE economists, this volume shows how economics became established at the School, how it produced some of the world’s best-known economists, including Lionel Robbins and Bill Phillips, plus Nobel Prize winners, such as Friedrich Hayek, John Hicks and Christopher Pissarides, and how it remains a global force for the very best in teaching and research in economics. With original contributions from a stellar cast, this volume provides economists – especially those interested in macroeconomics and the history of economic thought – with the first in-depth analysis of LSE economics.

Book GMM Estimation of Spatial Autoregressive Models with Moving Average Disturbances

Download or read book GMM Estimation of Spatial Autoregressive Models with Moving Average Disturbances written by Osman Dogan and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we introduce the one-step generalized method of moments (GMM) estimation methods considered in Lee (2007a) and Liu, Lee, and Bollinger (2010) to spatial models that impose a spatial moving average process for the disturbance term. First, we determine the set of best linear and quadratic moment functions for GMM estimation. Second, we show that the optimal GMM estimator (GMME) formulated from this set is the most efficient estimator within the class of GMMEs formulated from the set of linear and quadratic moment functions. Our analytical results show that the one-step GMME can be more efficient than the quasi maximum likelihood (QMLE), when the disturbance term is simply i.i.d. With an extensive Monte Carlo study, we compare its finite sample properties against the MLE, the QMLE and the estimators suggested in Fingleton (2008a).

Book Efficient Estimation of Spatial Econometric Interaction Models for Sparse OD Matrices

Download or read book Efficient Estimation of Spatial Econometric Interaction Models for Sparse OD Matrices written by Lukas Dargel and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: