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Large Dimensional Factor Analysis

Large Dimensional Factor Analysis PDF Author: Jushan Bai
Publisher: Now Publishers Inc
ISBN: 1601981449
Category : Business & Economics
Languages : en
Pages : 90

Book Description
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.

Large Dimensional Factor Analysis

Large Dimensional Factor Analysis PDF Author: Jushan Bai
Publisher: Now Publishers Inc
ISBN: 1601981449
Category : Business & Economics
Languages : en
Pages : 90

Book Description
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.

Time Series and Panel Data Econometrics

Time Series and Panel Data Econometrics PDF Author: M. Hashem Pesaran
Publisher: Oxford University Press
ISBN: 0191058475
Category : Business & Economics
Languages : en
Pages : 1443

Book Description
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.

The Oxford Handbook of Panel Data

The Oxford Handbook of Panel Data PDF Author: Badi H. Baltagi
Publisher: Oxford University Press
ISBN: 0190210826
Category : Business & Economics
Languages : en
Pages : 705

Book Description
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.

Financial Signal Processing and Machine Learning

Financial Signal Processing and Machine Learning PDF Author: Ali N. Akansu
Publisher: John Wiley & Sons
ISBN: 1118745647
Category : Technology & Engineering
Languages : en
Pages : 312

Book Description
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Aid Effectiveness for Environmental Sustainability

Aid Effectiveness for Environmental Sustainability PDF Author: Yongfu Huang
Publisher: Springer
ISBN: 9811053790
Category : Science
Languages : en
Pages : 479

Book Description
This collection examines the role that foreign aid can play in dealing with the severe global challenge of climate change, one of the most pressing international development issues of the 21st century. Addressing the key threats of rising temperatures, changes in precipitation, coastal erosion and natural disasters, the book considers the implications for policy and future research, particularly in developing countries. Focusing on the worth of foreign aid in ensuring environmental sustainability, this collection consider how it can be used to improve access to sustainable energy, to promote efficient use of energy resources, to improve emission reduction and support the preservation of biodiversity in forests. Advancing our knowledge about foreign aid and climate change, it provides policy recommendations for the donors and recipient country governments. A cutting edge text on one of the most pressing international development issues of this century, this is key reading for all scholars of international development and climate change.

Macroeconomic Forecasting in the Era of Big Data

Macroeconomic Forecasting in the Era of Big Data PDF Author: Peter Fuleky
Publisher: Springer Nature
ISBN: 3030311503
Category : Business & Economics
Languages : en
Pages : 716

Book Description
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Advances in Economics and Econometrics

Advances in Economics and Econometrics PDF Author: Econometric Society. World Congress
Publisher: Cambridge University Press
ISBN: 9780521524131
Category : Business & Economics
Languages : en
Pages : 316

Book Description
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Partial Identification in Econometrics and Related Topics

Partial Identification in Econometrics and Related Topics PDF Author: Nguyen Ngoc Thach
Publisher: Springer Nature
ISBN: 3031591100
Category :
Languages : en
Pages : 724

Book Description


Handbook of Research Methods and Applications in Empirical Macroeconomics

Handbook of Research Methods and Applications in Empirical Macroeconomics PDF Author: Nigar Hashimzade
Publisher: Edward Elgar Publishing
ISBN: 0857931024
Category : Business & Economics
Languages : en
Pages : 627

Book Description
This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook concentrates on the most important issues, models and techniques for research in macroeconomics, and highlights the core methodologies and their empirical application in an accessible manner. Each chapter is largely self-contained, whilst the comprehensive introduction provides an overview of the key statistical concepts and methods. All of the chapters include the essential references for each topic and provide a sound guide for further reading. Topics covered include unit roots, non-linearities and structural breaks, time aggregation, forecasting, the Kalman filter, generalised method of moments, maximum likelihood and Bayesian estimation, vector autoregressive, dynamic stochastic general equilibrium and dynamic panel models. Presenting the most important models and techniques for empirical research, this Handbook will appeal to students, researchers and academics working in empirical macro and econometrics.

Dynamic Factor Models

Dynamic Factor Models PDF Author: Jörg Breitung
Publisher:
ISBN: 9783865580979
Category :
Languages : en
Pages : 29

Book Description