Asymptotic Properties of Full Information Estimators in Dynamic Autoregressive Simultaneous Equations Models PDF Download
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Author: Phoebus James Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Author: Phoebus James Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Author: Rand Corporation
Publisher:
ISBN:
Category :
Languages : en
Pages : 35
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Book Description
Author: Phoebus J. Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 19
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Book Description
Author: Kai Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 196
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Book Description
Databases with cross-sectional interdependent variables have highlighted the need for new data analysis techniques to model interdependence patterns cross-sectional units. Among various models to describe the interdependence, spatial autoregressive models (SAR) have attracted much attention. The theory and practice of single dependent variable SAR have been well established. Although a large number of economic theories may concern about interrelations among several economic variables, econometric studies regarding multivariate and simultaneous equations SAR models are limited. This dissertation is filling in this gap. This dissertation is composed of two chapters, the first chapter focuses on models with cross-sectional data, while the second chapter is on models in panel data which incorporates both intertemporal dynamics and spatial interdependence. The first chapter investigates a simultaneous equations spatial autoregressive model which incorporates simultaneity effects, own-variable spatial lags and cross-variable spatial lags as explanatory variables, and allows for correlation between disturbances across equations. In exposition, this chapter also discusses a multivariate spatial autoregressive model that can be treated as a reduced form of the simultaneous equations model. For a multivariate model, we provide identification conditions in terms of the existence of instruments for spatial lags and regularities of the weight matrix structure. Rank conditions and order conditions are provided for identification of structural parameters in the simultaneous equations model. In this chapter we study parameter spaces, the parameter identification, asymptotic properties of the quasi-maximum likelihood estimation, and computational issues. Monte Carlo experiments illustrate the advantages of the QML, broader applicability and efficiency, compared to instrumental variables based estimation methods in the existing literature. The second chapter introduces multivariate and simultaneous equations dynamic panel spatial autoregressive models in the cases of stability and spatial cointegration. A spatial unit is assumed to depend on its lagged term, and to respond to its neighbours' or peers' behaviour in the current period (spatial lags), and in the previous period (space-time lags). The disturbances in the model are specified with time fixed effects and individual fixed effects in addition to idiosyncratic disturbances. This chapter investigates identification for the model with simultaneous effects, time dynamic effects, and spatial effects. In the estimation of stable and spatially cointegrated models, we investigate QMLE and establish asymptotic properties of the estimator. Convergence rates of parameters may change depending on variables being stable or unstable. We analyze asymptotic biases and suggest bias-corrected estimates. We also study a robust estimation method which can be applied to stable case, spatial cointergration case and some spatial explosion cases. We apply the model to study the grain market integration using a unique historical dataset of rice and wheat prices of 65 cities in 49 years in Yangtze River Basin. The empirical result shows that rice and wheat prices are spatially cointegrated across cities. These results provide evidences of interregional and intertemporal grain market integration and trading network in the eighteenth-century Yangtze River basin.
Author: Thomas B. Fomby
Publisher: Springer Science & Business Media
ISBN: 1441987460
Category : Business & Economics
Languages : en
Pages : 637
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Book Description
This book had its conception in 1975in a friendly tavern near the School of Businessand PublicAdministration at the UniversityofMissouri-Columbia. Two of the authors (Fomby and Hill) were graduate students of the third (Johnson), and were (and are) concerned about teaching econometrics effectively at the graduate level. We decided then to write a book to serve as a comprehensive text for graduate econometrics. Generally, the material included in the bookand itsorganization have been governed by the question, " Howcould the subject be best presented in a graduate class?" For content, this has meant that we have tried to cover " all the bases " and yet have not attempted to be encyclopedic. The intended purpose has also affected the levelofmathematical rigor. We have tended to prove only those results that are basic and/or relatively straightforward. Proofs that would demand inordinant amounts of class time have simply been referenced. The book is intended for a two-semester course and paced to admit more extensive treatment of areas of specific interest to the instructor and students. We have great confidence in the ability, industry, and persistence of graduate students in ferreting out and understanding the omitted proofs and results. In the end, this is how one gains maturity and a fuller appreciation for the subject in any case. It is assumed that the readers of the book will have had an econometric methods course, using texts like J. Johnston's Econometric Methods, 2nd ed.
Author: Virendra K. Srivastava
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 18
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Book Description
Author: H. Wold
Publisher: Elsevier
ISBN: 148329630X
Category : Mathematics
Languages : en
Pages : 351
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Book Description
The Fix-Point Approach to Interdependent Systems
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
ISBN: 9783540569404
Category : Business & Economics
Languages : en
Pages : 576
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Book Description
This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Author: Phoebus J. Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
Author: Mary Kathleen Vickers
Publisher:
ISBN:
Category : Asymptotes
Languages : en
Pages : 312
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Book Description
Four theorems are proven, which simplify the application to econometric models of Weiss's theorem on asymptotic properties of maximum likelihood estimators in nonstandard cases. The theorems require, roughly: the uniform convergence in any compact sets of the unknown parameters of the expection of the Hessian matrix of the log likelihood function; and the uniform convergence to 0 in the same sense of the variance of the same quantities. The fourth theorem allows one to conclude that the optimal properties hold on an image set of the parameters when the map satisfies certain smoothness conditions, and the first three theorems are satisfied for the original parameter set. These four theorems are applied to autoregressive models, nonlinear models, systems of equations, and probit and logit models to infer optimal asymptotic properties. (Author).
