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Author: Ekaterini Kyriazidou
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Ekaterini Kyriazidou
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Donald W. K. Andrews
Publisher: Cambridge University Press
ISBN: 1139444603
Category : Business & Economics
Languages : en
Pages : 589
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This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.
Author: Daniel A. Griffith
Publisher: Springer Science & Business Media
ISBN: 1475728999
Category : Business & Economics
Languages : en
Pages : 206
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The purpose of models is not to fit the data but to sharpen the questions. S. Karlin, 11th R. A. Fisher Memorial Lecture, Royal Society, 20 April 1983 We are proud to offer this volume in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Not one to model solely for the sake of modelling, the above quotation nicely captures Professor Paelinck's unceasing quest for the best question for which an answer is needed. His FLEUR model has sharpened many spatial economics and spatial econometrics questions! Jean Paelinck, arguably, is the founder of modem spatial econometrics, penning the seminal introductory monograph on this topic, Spatial Econometrics, with Klaassen in 1979. In the General Address to the Dutch Statistical Association, on May 2, 1974, in Tilburg, "he coined the term [spatial econometrics] to designate a growing body of the regional science literature that dealt primarily with estimation and testing problems encountered in the implementation of multiregional econometric models" (Anselin, 1988, p. 7); he already had introduced this idea in his introductory report to the 1966 Annual Meeting of the Association de Science Regionale de Langue Fran~aise.
Author: R.A.L. Carter
Publisher: Springer Science & Business Media
ISBN: 1461390168
Category : Business & Economics
Languages : en
Pages : 378
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The purpose of this volume is to honour a pioneer in the field of econometrics, A. L. Nagar, on the occasion of his sixtieth birthday. Fourteen econometricians from six countries on four continents have contributed to this project. One of us was his teacher, some of us were his students, many of us were his colleagues, all of us are his friends. Our volume opens with a paper by L. R. Klein which discusses the meaning and role of exogenous variables in struc tural and vector-autoregressive econometric models. Several examples from recent macroeconomic history are presented and the notion of Granger-causality is discussed. This is followed by two papers dealing with an issue of considerable relevance to developing countries, such as India; the measurement of the inequality in the distribution of income. The paper by C. T. West and H. Theil deals with the problem of measuring inequality of all components of total income vvithin a region, rather than just labour income. It applies its results to the regions of the United States. The second paper in this group, by N. Kakwani, derives the large-sample distributions of several popular inequality measures, thus providing a method for drawing large-sample inferences about the differences in inequality between regions. The techniques are applied to the regions of Cote d'Ivoire. The next group of papers is devoted to econometric theory in the context of the dynamic, simultaneous, linear equations model. The first, by P. J.
Author: K. A. Fox
Publisher: Springer Science & Business Media
ISBN: 3642461980
Category : Business & Economics
Languages : en
Pages : 474
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These essays in honor of Professor Gerhard Tintner are substantive contributions to three areas of econometrics, (1) economic models and applications,. (2) estimation, and (3) stochastic programming, in each of which he has labored with outstanding success. His own work has extended into multivariate analysis, the pure theory of decision-making under un certainty, and other fields which are not touched upon here for reasons of space and focus. Thus, this collection is appropriate to his interests but covers much less than their full range. Professor Tintner's contributions to econometrics through teaching, writing, editing, lecturing and consulting have been varied and inter national. We have tried to highlight them in "The Econometric Work of Gerhard Tintner" and to place them in historical perspective in "The Invisible Revolution in Economics: Emergence of a Mathematical Science. " Professor Tintner's career to date has spanned the organizational life of the Econometric Society and his contributions have been nearly coextensive with its scope. His principal books and articles up to 1968 are listed in the "Selected Bibliography. " Professor Tintner's current research involves the intricate problems of specification and application of stochastic processes to economic systems, particularly to growth, diffusion of technology, and optimal control. As always, he is moving with the econometric frontier and a portion of the frontier is moving with him. IV Two of the editors wrote dissertations under Professor Tintner's sup- vision; the third knew him as a colleague and friend.
Author: Niels Haldrup
Publisher: OUP Oxford
ISBN: 0191669547
Category : Business & Economics
Languages : en
Pages : 393
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This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing
ISBN: 1784411825
Category : Political Science
Languages : en
Pages : 772
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This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.
Author: Yaein Baek
Publisher:
ISBN:
Category :
Languages : en
Pages : 176
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Instability of parametric models is a common problem in many fields of economics. In econometrics, these changes in the underlying data generating process are referred to as structural breaks. Although there is an extensive literature on estimation and statistical tests of structural breaks, existing methods fail to adequately capture a break. This dissertation consists of three papers on developing econometric methods for structural breaks and forecasting. The first chapter develops a new method in estimating the location of a structural break in a linear model and provide theoretical results and empirical applications of the estimator. In finite sample the conventional least-squares estimates a break occurred at either ends of the sample with high probability, regardless of the true break point. I suggest an estimator of the break point that resolves this pile up issue and thus, provide a more accurate estimate of the break. The second chapter constructs a statistical test to test existence of a structural break when the direction of the parameter shift is known. In practice it is likely that a researcher is interested in testing for a structural break in a particular direction because the direction is known, such as policy change or historical data. We incorporate this information in constructing three tests that have higher power when direction is correctly specified. The last chapter proposes a multi-period forecasting method that is robust to model misspecification. When we are interested in obtaining long horizon ahead forecasts, the direct forecast method is more favorable than the iterated forecast because it is more robust to misspecification. However, direct forecast estimates tend to have jagged shapes across horizons. I use a mechanism analogous to ridge regression on the direct forecast model to maintain robustness while smoothing out erratic estimates.
Author:
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Category :
Languages : en
Pages :
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The purpose of this research has been to look into several econometric issues of concern to researchers doing applied work in macroeconomics. The first essay looks at Bureau of Economic Analysis data on inventories and sales of finished goods often used in studies of inventory behavior. Applying recently developed methods, the series are rigorously tested to determine their stationarity properties. Results indicate that neither first differencing nor linearly detrending the data is appropriate. For most series a trend function with one or more breaks offers a better fit and also generates stationarity. The results are used to determine the impact on estimation in a simple production-smoothing model of inventory behavior. The impact of different trend specifications on univariate forecasting of inventories is also considered. The second essay considers an alternative method of detrending time series data -- the Hodrick-Prescott (HP) filter. Previous research has shown that HP filtering can have serious adverse consequences when used to analyze co-movements between data series at business cycle frequencies. Despite this, the filter has also been used to induce stationarity in a data series prior to estimation of structural econometric models. Little work has been done in analyzing the possible effects this may have on parameter estimates from such models. A simulation study is conducted to assess the impact of HP filtering on parameter estimation and a comparison is made to other detrending methods. It is shown that the HP filter induces bias in the parameter estimates and also increases the root mean squared error of the estimates from the simulations. In addition, there is some adverse impact on the size of certain test statistics. The final essay looks at the impact of misspecification on estimation results from a structural econometric model when using a Generalized Method of Moments estimator. Simulated data consistent with a particular specification of the.
Author: Qi Li
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 242
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