Search results for: estimation-of-spatial-panels

Estimation of Spatial Panels

Author : Lung-fei Lee
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Estimation of Spatial Panels provides some recent developments on the specification and estimation of spatial panel models.

Generalized Moments Estimation for Spatial Panel Data

Author : Viliam Druska
File Size : 82.52 MB
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Estimation and Inference in Heterogeneous Spatial Panel Data Models with a Multifactor Error Structure

Author : Jia Chen
File Size : 64.85 MB
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GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors

Author : Pavel Čížek
File Size : 57.99 MB
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Advances in Spatial Econometrics

Author : Luc Anselin
File Size : 56.67 MB
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World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.

Spatial Econometrics

Author : J. Paul Elhorst
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​This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted.

The Econometric Analysis of Non Stationary Spatial Panel Data

Author : Michael Beenstock
File Size : 68.71 MB
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This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.

The Oxford Handbook of Panel Data

Author : Badi Hani Baltagi
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Panel data econometrics has evolved rapidly over the past three decades. The field is of both theoretical and practical importance, and methods to deal with micro- and macroeconomic panel data are in high demand from practitioners. Applications in finance, development, trade, marketing, health, labor, and consumer economics attest to the usefulness of these methods in applied economics. THis book is a comprehensive source on panel data. It contains 20 chapters edited by Professor Badi Baltagi--one of the leading econometricians in the area of panel data econometrics--and authored by renowned experts in the field. The chapters are divided into two sections. Part I examines new developments in theory. It includes panel cointegration, dynamic panel data models, incidental parameters and dynamic panel modeling, and panel data models for discrete choice. The chapters in Part II target applications of panel data, including health, labor, marketing, trade, productivity and macro applications in panels.

Handbook of Applied Spatial Analysis

Author : Manfred M. Fischer
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The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.

Productivity and Efficiency Analysis

Author : William H. Greene
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This proceedings volume examines the state-of-the art of productivity and efficiency analysis and adds to the existing research by bringing together a selection of the best papers from the 8th North American Productivity Workshop (NAPW). It also aims to analyze world-wide perspectives on challenges that local economies and institutions may face when changes in productivity are observed. The volume comprises of seventeen papers that deal with productivity measurement, productivity growth, dynamics of productivity change, measures of labor productivity, measures of technical efficiency in different sectors, frontier analysis, measures of performance, industry instability and spillover effects. These papers are relevant to academia, but also to public and private sectors in terms of the challenges firms, financial institutions, governments and individuals may face when dealing with economic and education related activities that lead to increase or decrease of productivity. The North American Productivity Workshop brings together academic scholars and practitioners in the field of productivity and efficiency analysis from all over the world. It is a four day conference exploring topics related to productivity, production theory and efficiency measurement in economics, management science, operations research, public administration, and related fields. The papers in this volume also address general topics as health, energy, finance, agriculture, utilities, and economic dev elopment, among others. The editors are comprised of the 2014 local organizers, program committee members, and celebrated guest conference speakers.

Modelling Spatial Housing Markets

Author : Geoffrey Meen
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Spatial fixity is one of the characteristics that distinguishes housing from most other goods and services in the economy. In general, housing cannot be moved from one part of the country to another in response to shortages or excesses in particular areas. The modelling of housing markets and the interlinkages between markets at different spatial levels - international, national, regional and urban - are the main themes of this book. A second major theme is disaggregation, not only in terms of space, but also between households. The book argues that aggregate time-series models of housing markets of the type widely used in Britain and also in other countries in the past have become less relevant in a world of increasing income dispersion. Typically, aggregate relationships will break down, except under special conditions. We can no longer assume that traditional location or tenure patterns, for example, will continue in the future. The book has four main components. First, it discusses trends in housing markets both internationally and within nations. Second, the book develops theoretical housing models at each spatial scale, starting with national models, moving down to the regional level and, then, to urban models. Third, the book provides empirical estimates of the models and, finally, the models are used for policy analysis. Analysis ranges over a wide variety of topics, including explanations for differing international house price trends, the causes of housing cycles, the role of credit markets, regional housing market interactions and the role of housing in urban/suburban population drift.

Spatial Econometrics

Author : Giuseppe Arbia
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This book bridges the gap between economic theory and spatial econometric techniques. It is accessible to those with only a basic statistical background and no prior knowledge of spatial econometric methods. It provides a comprehensive treatment of the topic, motivating the reader with examples and analysis. The volume provides a rigorous treatment of the basic spatial linear model, and it discusses the violations of the classical regression assumptions that occur when dealing with spatial data.

Cross Sectional Dependence in Spatial Econometric Models

Author : Stefan Klotz
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This book is concerned with spatial dependence in econometric models, offering a work of reference to the applied researcher. In economics, spatial aspects are usually somewhat disregarded, which - as is shown and quantified here - may seriously impair research results. It presents the basic tool kit of treating cross sectional dependence, which typically occurs between spatial observations. The methods are introduced as straightforward enhancement of standard econometric models and methods, placing emphasis on the practical aspects of their features.

Statistical Analysis of Spatial and Spatio Temporal Point Patterns Third Edition

Author : Peter J. Diggle
File Size : 41.52 MB
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Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author’s website.

Maximum Likelihood Estimation and Lagrange Multiplier Tests for Panel Seemingly Unrelated Regressions with Spatial Lag and Spatial Errors An Application to Hedonic Housing Prices in Paris

Author : Badi H. Baltagi
File Size : 87.47 MB
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Spatial Correlations in Panel Data

Author : John Christopher Driscoll
File Size : 37.53 MB
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Estimation of Multiequation Cross section Models in the Presence of Spatial Autocorrelation

Author : Alexandre Carvalho
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Problem description; Spatial generalized method of moments; Monte Carlo simulations; Application to municipality growth in Brazil.

Panel Data Econometrics with R

Author : Yves Croissant
File Size : 66.87 MB
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1 Introduction 5 1.1 Panel data econometrics: a gentle introduction 5 1.1.1 Eliminating unobserved components 6 1.2 R for econometric computing 11 1.2.1 The modus operandi of R 12 1.2.2 Data management 13 1.3 plm for the casual R user 14 1.3.1 R for the matrix language user 14 1.3.2 R for the user of econometric packages 16 1.4 plm for the procient R user 18 1.4.1 Reproducibile econometric work 18 1.4.2 Object-orientation for the user 19 1.5 plm for the R developer 20 1.5.1 Object orientation for development 21 1.6 Notations 24 2 The error component model 31 2.1 Notations and hypotheses 31 2.1.1 Notations 31 2.1.2 Some useful transformations 32 2.1.3 Hypotheses concerning the errors 34 2.2 Ordinary least squares estimators 36 2.2.1 Ordinary least squares on the raw data: the pooling model 36 2.2.2 The between estimator 38 2.2.3 The within estimator 39 2.3 The generalized least squares estimator 44 2.3.1 Presentation of the gls estimator 44 2.3.2 Estimation of the variances of the components of the error 46 2.4 Comparison of the estimators 51 2.4.1 Relations between the estimators 51 2.4.2 Comparison of the variances 52 2.4.3 Fixed vs random eects 53 2.4.4 Some simple linear model examples 55 2.5 The two-ways error components model 60 2.5.1 Error components in the two-ways model 60 2.5.2 Fixed and random eects models 61 2.6 Estimation of a wage equation 62 3 Advanced error components models 67 3.1 Unbalanced panels 67 3.1.1 Individual eects model 67 3.1.2 Two-ways error component model 69 3.1.3 Estimation of the components of the error variance 73 3.2 Seemingly unrelated regression equations 80 3.2.1 Introduction 80 3.2.2 Constrained least squares 81 3.2.3 Inter-equations correlation 82 3.2.4 SUR with panel data 83 3.3 The maximum likelihood estimator 88 3.3.1 Derivation of the likelihood function 89 3.3.2 Computation of the estimator 90 3.4 The nested error components model 92 3.4.1 Presentation of the model 92 3.4.2 Estimation of the variance of the error components 93 4 Tests on error component models 101 4.1 Tests on individual and/of time eects 102 4.1.1 F tests 102 4.1.2 Breusch-Pagan tests 102 4.2 Tests for correlated eects 107 4.2.1 The Mundlak approach 108 4.2.2 Hausman's test 109 4.2.3 Chamberlain's approach 110 4.3 Tests for serial correlation 115 4.3.1 Unobserved eects test 116 4.3.2 Score test of serial correlation and/or individual eects 117 4.3.3 Likelihood Ratio tests for ar(1) and individual eects 120 4.3.4 Applying traditional serial correlation tests to panel data 122 4.3.5 Wald tests for serial correlation 124 4.4 Tests for cross-sectional dependence 126 4.4.1 Pairwise correlation coe-cients 126 4.4.2 cd -type tests for cross-sectional dependence 127 4.4.3 Testing cross-sectional dependence in a pseries 129 5 Robust inference and estimation 133 5.1 Robust inference 133 5.1.1 Robust covariance estimators 134 5.1.2 plm and generic sandwich estimators 145 5.1.3 Robust testing of linear hypotheses 150 5.2 Unrestricted generalized least squares 154 5.2.1 General feasible generalized least squares 155 5.2.2 Applied examples 160 6 Endogeneity 167 6.1 Introduction 167 6.2 The instrumental variables estimator 168 6.2.1 Generalities about the instrumental variables estimator 168 6.2.2 The within instrumental variables estimator 170 6.3 Error components instrumental variables estimator 173 6.3.1 The general model 173 6.3.2 Special cases of the general model 176 6.4 Estimation of a system of equations 186 6.4.1 The three stage least squares estimator 186 6.4.2 The error components three stage least squares estimator 188 6.5 More empirical examples 191 7 Estimation of a dynamic model 193 7.1 Dynamic model and endogeneity 195 7.1.1 The bias of the ols estimator 195 7.1.2 The within estimator 197 7.1.3 Consistent estimation methods for dynamic models 198 7.2 gmm estimation of the dierenced model 201 7.2.1 Instrumental variables

Estimating spatial basis risk in rainfall index insurance

Author : Ceballos, Francisco
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This paper develops a novel methodology to estimate the degree of spatial basis risk for an arbitrary rainfall index insurance instrument. It relies on a widelyused stochastic rainfall generator, extendedto accommodate nontraditional dependence patterns—in particular spatial upper-tail dependence in rainfall—through a copula function. The methodology is applied to a recentlylaunched index product insuring against excess rainfall in Uruguay. The model is first calibrated using historical daily rainfall data from the national network of weather stations, complemented with a unique,high-resolution dataset from a dense network of 34 automatic weather stations around the study area. The degree of downside spatial basis risk is then estimated by Monte Carlo simulations and the results are linked to both a theoretical model of the demand for index insurance and to farmers’ perceptions about the product.

Spatial Econometrics

Author : Harry Kelejian
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Spatial Econometrics provides a modern, powerful and flexible skillset to early career researchers interested in entering this rapidly expanding discipline. It articulates the principles and current practice of modern spatial econometrics and spatial statistics, combining rigorous depth of presentation with unusual depth of coverage. Introducing and formalizing the principles of, and ‘need’ for, models which define spatial interactions, the book provides a comprehensive framework for almost every major facet of modern science. Subjects covered at length include spatial regression models, weighting matrices, estimation procedures and the complications associated with their use. The work particularly focuses on models of uncertainty and estimation under various complications relating to model specifications, data problems, tests of hypotheses, along with systems and panel data extensions which are covered in exhaustive detail. Extensions discussing pre-test procedures and Bayesian methodologies are provided at length. Throughout, direct applications of spatial models are described in detail, with copious illustrative empirical examples demonstrating how readers might implement spatial analysis in research projects. Designed as a textbook and reference companion, every chapter concludes with a set of questions for formal or self--study. Finally, the book includes extensive supplementing information in a large sample theory in the R programming language that supports early career econometricians interested in the implementation of statistical procedures covered. Combines advanced theoretical foundations with cutting-edge computational developments in R Builds from solid foundations, to more sophisticated extensions that are intended to jumpstart research careers in spatial econometrics Written by two of the most accomplished and extensively published econometricians working in the discipline Describes fundamental principles intuitively, but without sacrificing rigor Provides empirical illustrations for many spatial methods across diverse field Emphasizes a modern treatment of the field using the generalized method of moments (GMM) approach Explores sophisticated modern research methodologies, including pre-test procedures and Bayesian data analysis