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Book Essays in Information Theoretic Econometrics and High Dimensional Econometrics

Download or read book Essays in Information Theoretic Econometrics and High Dimensional Econometrics written by Yi Mao and published by . This book was released on 2019 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the structure of IT-based estimators, the number of moment conditions increase rapidly with the growing dimensionality of variables. Computational burden of maximum entropy estimation with all the observed moments becomes heavier accordingly. Thus, I link the problem of IT-based maximum entropy estimation and moment selection in Chapter 4. We propose a regularized ME approach to select relevant moments. We also use the entropy ratio test to select moments of which the Lagrange multipliers are significant. Simulation examples show that the probability of selecting relevant moments approaches to one as sample size gets larger. Lastly, I explore the regularization of high dimensional matrices in Chapter 5. I deal with the challenge of estimating large precision matrices which are often used in a variety of applications. I propose a dynamic conditional precision (DCP) algorithm by embedding a dynamic structure to conditional precision matrices. I show the consistency of the DCP estimator and apply it to a forecast combination application.

Book Essays on High Dimensional Econometrics

Download or read book Essays on High Dimensional Econometrics written by Yubo Hua and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book The Econometrics of Multi dimensional Panels

Download or read book The Econometrics of Multi dimensional Panels written by Laszlo Matyas and published by Springer. This book was released on 2017-07-26 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. The last two decades or so, the use of panel data has become a standard in many areas of economic analysis. The available models formulations became more complex, the estimation and hypothesis testing methods more sophisticated. The interaction between economics and econometrics resulted in a huge publication output, deepening and widening immensely our knowledge and understanding in both. The traditional panel data, by nature, are two-dimensional. Lately, however, as part of the big data revolution, there has been a rapid emergence of three, four and even higher dimensional panel data sets. These have started to be used to study the flow of goods, capital, and services, but also some other economic phenomena that can be better understood in higher dimensions. Oddly, applications rushed ahead of theory in this field. This book is aimed at filling this widening gap. The first theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.

Book Contributions to Econometric Theory and Application

Download or read book Contributions to Econometric Theory and Application written by R.A.L. Carter and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Information and Entropy Econometrics

Download or read book Information and Entropy Econometrics written by Amos Golan and published by Now Publishers Inc. This book was released on 2008 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information and Entropy Econometrics - A Review and Synthesis summarizes the basics of information theoretic methods in econometrics and the connecting theme among these methods. The sub-class of methods that treat the observed sample moments as stochastic is discussed in greater details. I Information and Entropy Econometrics - A Review and Synthesis -focuses on inter-connection between information theory, estimation and inference. -provides a detailed survey of information theoretic concepts and quantities used within econometrics and then show how these quantities are used within IEE. -pays special attention for the interpretation of these quantities and for describing the relationships between information theoretic estimators and traditional estimators. Readers need a basic knowledge of econometrics, but do not need prior knowledge of information theory. The survey is self contained and interested readers can replicate all results and examples provided. Whenever necessary the readers are referred to the relevant literature. Information and Entropy Econometrics - A Review and Synthesis will benefit researchers looking for a concise introduction to the basics of IEE and to acquire the basic tools necessary for using and understanding these methods. Applied researchers can use the book to learn improved new methods, and applications for extracting information from noisy and limited data and for learning from these data.

Book Econometrics and Economic Theory

Download or read book Econometrics and Economic Theory written by Willy Sellekaerts and published by Springer. This book was released on 1974-06-18 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Essays on Nonparametric and High Dimensional Econometrics

Download or read book Essays on Nonparametric and High Dimensional Econometrics written by Jesper Riis-Vestergaard Soerensen and published by . This book was released on 2018 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies questions related to identification, estimation, and specification testing of nonparametric and high-dimensional econometric models. The thesis is composed by two chapters. In Chapter 1, I propose specification tests for two formally distinct but related classes of econometric models: (1) semiparametric conditional moment restriction models dependent on conditional expectation functions, and (2) a class of high-dimensional unconditional moment restriction models dependent on high-dimensional best linear predictors. These classes may be motivated by economic models in which agents make choices under uncertainty and therefore have to predict payoff-relevant variables such as the behavior of other agents. The proposed tests are shown to be both asymptotically correctly sized and consistent. Moreover, I establish a bound on the rate of local alternatives for which the test for high-dimensional unconditional moment restriction models is consistent. These results allow researchers to test the specification of their models without introducing additional parametric, typically ad hoc, assumptions on expectations. In Chapter 2, I show that it is possible to identify and estimate a generalized panel regression model (GPRM) without imposing any parametric structure on (1) the function of observable explanatory variables, (2) the systematic function through which the function of observable explanatory variables, fixed effect, and disturbance term generate the outcome variable, or (3) the distribution of unobservables. I proceed with estimation using a series maximum rank correlation estimator (SMRCE) of the function of observable explanatory variables and provide conditions under which L2-consistency is achieved. I also provide conditions under which both L2 and uniform convergence rates of the SMRCE may be derived.

Book An Information Theoretic Approach to Econometrics

Download or read book An Information Theoretic Approach to Econometrics written by George G. Judge and published by Cambridge University Press. This book was released on 2011-12-12 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic econometric models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of power divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-model problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family.

Book Essays in Econometrics and Random Matrix Theory

Download or read book Essays in Econometrics and Random Matrix Theory written by Matthew C. Harding and published by . This book was released on 2007 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops new econometric procedures for the analysis of high-dimensional datasets commonly encountered in finance, macroeconomics or industrial organization. First, I show that traditional approaches to the estimation of latent factors in financial data underestimate the number of risk factors. They are also biased towards a single market factor, the importance of which is overestimated in samples. In Chapter 3, I derive a new consistent procedure for the estimation of the number of latent factors by examining the effect of the idiosyncratic noise in a factor model. Furthermore, I show that the estimation of factor loadings by Principal Components Analysis is inconsistent for weak factors and suggest alternative Instrumental Variables procedures. Chapter 4 uses the theoretical results of the earlier chapters to estimate the stochastic dimension of the US economy and shows that global risk factors may obfuscate the relationship between inflation and unemployment. Chapter 5 (co-authored with Jerry Hausman) suggests a new procedure for the estimation of discrete choice models with random coe±cients and shows that ignoring individual taste heterogeneity can lead to misleading policy counterfactuals.

Book Essays in High dimensional Econometrics

Download or read book Essays in High dimensional Econometrics written by and published by . This book was released on 2014 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The dissertation contains three papers on causal inference in econometrics.

Book Identification and Inference for Econometric Models

Download or read book Identification and Inference for Econometric Models written by Donald W. K. Andrews and published by Cambridge University Press. This book was released on 2005-06-17 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2005 collection pushed forward the research frontier in four areas of theoretical econometrics.

Book Essays in Honor of Cheng Hsiao

Download or read book Essays in Honor of Cheng Hsiao written by Dek Terrell and published by Emerald Group Publishing. This book was released on 2020-04-15 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Including contributions spanning a variety of theoretical and applied topics in econometrics, this volume of Advances in Econometrics is published in honour of Cheng Hsiao.

Book Essays on High dimensional Econometrics

Download or read book Essays on High dimensional Econometrics written by Guan Yun Kenwin Maung and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation consists of three chapters on high-dimensional econometrics. These chapters introduce novel methods to deal with econometric models where the number of unknown parameters is large relative to the available sample size. The first chapter introduces a dimension-reducing estimator for economic and financial networks. Many network econometric models rely on known adjacency matrices. This becomes a problem for investigations when the network structure is not readily accessed or constructed. Furthermore, direct estimation may be cumbersome or infeasible if the number of units in the network is large. To deal with this, I propose a Structural Vector Autoregression (SVAR) data-driven approach to recover the network structure via matrix regression under a large N and T asymptotic framework. The high-dimensionality of the problem is dealt with by focusing on low-rank representations of the network. I show, both theoretically and through simulations, that the reduced-form estimator is consistent and asymptotically normal, and suggest an identification strategy for the SVAR as implied by its network structure. In the empirical study, I extract volatility connectedness between major US financial institutions and find a greater degree of interconnectedness compared to the literature. I further demonstrate the utility of the estimated network for systemic risk analysis by identifying key propagators of volatility spillovers in the financial sector. The second chapter deals with maximum likelihood estimation of large Markov-switching vector autoregressions (MS-VARs). This problem might be challenging or infeasible due to parameter proliferation. To accommodate situations where dimensionality may be of comparable order to or exceeds the sample size, I adopt a sparse framework and propose two penalized maximum likelihood estimators with either the Lasso or the smoothly clipped absolute deviation (SCAD) penalty. I show that both estimators are estimation consistent, while the SCAD estimator also selects relevant parameters with probability approaching one. A modified EM-algorithm is developed for the case of Gaussian errors and simulations show that the algorithm exhibits desirable finite sample performance. In an application to short-horizon return predictability in the US, I estimate a 15 variable 2-state MS-VAR(1) and obtain the often reported counter-cyclicality in predictability. The variable selection property of the proposed estimators helps to identify predictors that contribute strongly to predictability during economic contractions but are otherwise irrelevant in expansions. Furthermore, out-of-sample analyses indicate that large MS-VARs can significantly outperform "hard-to-beat" predictors like the historical average. In the final chapter, I propose a new nonparametric estimator of time-varying forecast combination weights. When the number of individual forecasts is small, I study the asymptotic properties of the local linear estimator. When the number of candidate forecasts exceeds or diverges with the sample size, I consider penalized local linear estimation with the group SCAD penalty. I show that the estimator exhibits the oracle property and correctly selects relevant forecasts with probability approaching one. Simulations indicate that the proposed estimators outperform existing combination schemes when structural changes exist. An empirical application on inflation and unemployment forecasting highlights the merits of the approach relative to other popular methods in the literature."--Pages ix-x.

Book Recent Advances and Future Directions in Causality  Prediction  and Specification Analysis

Download or read book Recent Advances and Future Directions in Causality Prediction and Specification Analysis written by Xiaohong Chen and published by Springer Science & Business Media. This book was released on 2012-08-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Book High dimensional Econometrics And Identification

Download or read book High dimensional Econometrics And Identification written by Kao Chihwa and published by World Scientific. This book was released on 2019-04-10 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many applications of econometrics and economics, a large proportion of the questions of interest are identification. An economist may be interested in uncovering the true signal when the data could be very noisy, such as time-series spurious regression and weak instruments problems, to name a few. In this book, High-Dimensional Econometrics and Identification, we illustrate the true signal and, hence, identification can be recovered even with noisy data in high-dimensional data, e.g., large panels. High-dimensional data in econometrics is the rule rather than the exception. One of the tools to analyze large, high-dimensional data is the panel data model.High-Dimensional Econometrics and Identification grew out of research work on the identification and high-dimensional econometrics that we have collaborated on over the years, and it aims to provide an up-todate presentation of the issues of identification and high-dimensional econometrics, as well as insights into the use of these results in empirical studies. This book is designed for high-level graduate courses in econometrics and statistics, as well as used as a reference for researchers.

Book Econometrics  Alchemy Or Science

Download or read book Econometrics Alchemy Or Science written by David F. Hendry and published by Oxford University Press, USA. This book was released on 2000-10-26 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Econometrics: Alchemy or Science?" analyses the effectiveness and validity of applying econometric methods to economic time series. The methodological dispute is long-standing, and no claim can be made for a single valid method, but recent results on the theory and practice of model selection bid fair to resolve many of the contentious issues.The book presents criticisms and evaluations of competing approaches, based on theoretical economic and econometric analyses, empirical applications, and Monte Carlo simulations, which interact to determine best practice. It explains the evolution of an approach to econometric modelling founded in careful statistical analyses of the available data, using economic theory to guide the general model specification. From a strong foundation in the theory of reduction, via a range of applied andsimulation studies, it demonstrates that general-to-specific procedures have excellent properties.The book is divided into four Parts: Routes and Route Maps; Empirical Modelling Strategies; Formalization; and Retrospect and Prospect. A short preamble to each chapter sketches the salient themes, links to earlier and later developments, and the lessons learnt or missed at the time. A sequence of detailed empirical studies of consumers' expenditure and money demand illustrate most facets of the approach. Material new to this revised edition describes recent major advances in computer-automatedmodel selection, embodied in the powerful new software program PcGets, which establish the operational success of the modelling strategy.

Book Essays in Econometrics

Download or read book Essays in Econometrics written by Clive W. J. Granger and published by Cambridge University Press. This book was released on 2001-07-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: These are econometrician Clive W. J. Granger's major essays in causality, integration, cointegration, and long memory.