An Empirical Analysis of Macroeconomic Factor Models
Author:
Publisher:
Published: 1996
Total Pages:
ISBN-13:
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Dynamic Factor Models
Author: Siem Jan Koopman
Publisher: Emerald Group Publishing
Published: 2016-01-08
Total Pages: 685
ISBN-13: 1785603523
DOWNLOAD EBOOKThis volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Data-Rich DSGE and Dynamic Factor Models
Author: Mr.Maxym Kryshko
Publisher: International Monetary Fund
Published: 2011-09-01
Total Pages: 51
ISBN-13: 1463903499
DOWNLOAD EBOOKDynamic factor models and dynamic stochastic general equilibrium (DSGE) models are widely used for empirical research in macroeconomics. The empirical factor literature argues that the co-movement of large panels of macroeconomic and financial data can be captured by relatively few common unobserved factors. Similarly, the dynamics in DSGE models are often governed by a handful of state variables and exogenous processes such as preference and/or technology shocks. Boivin and Giannoni(2006) combine a DSGE and a factor model into a data-rich DSGE model, in which DSGE states are factors and factor dynamics are subject to DSGE model implied restrictions. We compare a data-richDSGE model with a standard New Keynesian core to an empirical dynamic factor model by estimating both on a rich panel of U.S. macroeconomic and financial data compiled by Stock and Watson (2008).We find that the spaces spanned by the empirical factors and by the data-rich DSGE model states are very close. This proximity allows us to propagate monetary policy and technology innovations in an otherwise non-structural dynamic factor model to obtain predictions for many more series than just a handful of traditional macro variables, including measures of real activity, price indices, labor market indicators, interest rate spreads, money and credit stocks, and exchange rates.
Applications of State Space Models in Finance
Author: Sascha Mergner
Publisher: Universitätsverlag Göttingen
Published: 2009
Total Pages: 235
ISBN-13: 3941875221
DOWNLOAD EBOOKState space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the context of widely used concepts in finance. The presented material will be useful for financial economists and practitioners who are interested in taking time-variation in the relationship between financial assets and key economic factors explicitly into account. The empirical part illustrates the application of the various methods under consideration. As a distinctive feature, it includes a comprehensive analysis of the ability of time-varying coefficient models to estimate and predict the conditional nature of systematic risks for European industry portfolios.
The Oxford Handbook of Economic Forecasting
Author: Michael P. Clements
Publisher: OUP USA
Published: 2011-07-08
Total Pages: 732
ISBN-13: 0195398645
DOWNLOAD EBOOKGreater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Handbook of Research Methods and Applications in Empirical Macroeconomics
Author: Nigar Hashimzade
Publisher: Edward Elgar Publishing
Published: 2013-01-01
Total Pages: 627
ISBN-13: 0857931024
DOWNLOAD EBOOKThis 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.
Empirical Macroeconomics and Statistical Uncertainty
Author: Mateusz Pipień
Publisher: Routledge
Published: 2020-08-06
Total Pages: 121
ISBN-13: 1000170845
DOWNLOAD EBOOKThis book addresses one of the most important research activities in empirical macroeconomics. It provides a course of advanced but intuitive methods and tools enabling the spatial and temporal disaggregation of basic macroeconomic variables and the assessment of the statistical uncertainty of the outcomes of disaggregation. The empirical analysis focuses mainly on GDP and its growth in the context of Poland. However, all of the methods discussed can be easily applied to other countries. The approach used in the book views spatial and temporal disaggregation as a special case of the estimation of missing observations (a topic on missing data analysis). The book presents an econometric course of models of Seemingly Unrelated Regression Equations (SURE). The main advantage of using the SURE specification is to tackle the presented research problem so that it allows for the heterogeneity of the parameters describing relations between macroeconomic indicators. The book contains model specification, as well as descriptions of stochastic assumptions and resulting procedures of estimation and testing. The method also addresses uncertainty in the estimates produced. All of the necessary tests and assumptions are presented in detail. The results are designed to serve as a source of invaluable information making regional analyses more convenient and – more importantly – comparable. It will create a solid basis for making conclusions and recommendations concerning regional economic policy in Poland, particularly regarding the assessment of the economic situation. This is essential reading for academics, researchers, and economists with regional analysis as their field of expertise, as well as central bankers and policymakers.
Multi-Factor-Asset Pricing Models for German Stocks
Author: Wolfgang Bessler
Publisher:
Published: 2006
Total Pages:
ISBN-13:
DOWNLOAD EBOOKThe large number of asset pricing models and empirical studies of stock returns are evidence of the desire to understand the return generating process of financial assets in general and for stocks in particular. One focus of the research in this area has been on multi-factor asset pricing models [Chen et al. (1986), Fama/French (1992)]. These models are based on the assumption that stock returns are generated by a limited number of economic variables such as company, industry or macroeconomic factors.The objective of this study is to analyze the importance of various economic factors in explaining the return structure for stocks in Germany and to investigate whether the impact of these factors is time varying. This is important, because in most studies of asset pricing models it is assumed that the parameters are non time varying. In particular, we investigate the time variability of the explanatory power and the beta coefficients in a multi-factor framework. For this we employ a rolling estimation procedure that allows us to analyze the time variability of the model coefficients.In the empirical analysis we use monthly data of four macroeconomic variables and the market index to explain the returns of four German industry indices for the period from 1974 to 2000. In contrast to most studies which exclude banks from their empirical analysis we use three industrial indices and a bank index. The economic factors included in our model are term spreads, interest rates, exchange rates and the ifo business index as well as the market index. The empirical results confirm that the factors used in our empirical analysis seem well suited to explain the stock returns especially for banks. Moreover, it is evident that the explanatory power and the beta coefficients are time varying.
Empirical Finance
Author: Sardar M. N. Islam
Publisher: Springer Science & Business Media
Published: 2005
Total Pages: 218
ISBN-13: 9783790815511
DOWNLOAD EBOOKThe emphasis of this book is on understanding special characteristics of the financial systems of emerging markets, where the existence of market imperfections such as asymmetric information, adverse selection and moral hazard can cause financial market failures. Considering the Thai stock market as an example, this book provides an econometric study of a typical Asian financial system. Many contemporary techniques and models are used in this study, including simple multivariate regression, multi-factor model, exponential smoothing, Holt Winter’s models, and GARCH type models. The findings of the existence of rational bubbles, anomalies, volatility and other characteristics reveal evidence of inefficiency in the Thai stock market. Based on these results, the book includes justifications for public policies in such economies and makes suggestions for further research areas.
Bank Stock Returns and Economic Variables
Author: Wolfgang Bessler
Publisher:
Published: 2006
Total Pages:
ISBN-13:
DOWNLOAD EBOOKThe large number of asset pricing models and empirical studies of stock returns are evidence of the desire to understand the return generating process of financial assets in general and for stocks in particular. One focus of the research in this area has been on multi-factor asset pricing models [Chen et al. (1986), Fama/French (1992)]. These models are based on the assumption that stock returns are generated by a limited number of economic variables such as company, industry or macroeconomic factors.The objective of this study is to analyze the importance of various economic factors in explaining the return structure for stocks in Germany and to investigate whether the impact of these factors is time varying. This is important, because in most studies of asset pricing models it is assumed that the parameters are non time varying. In particular, we investigate the time variability of the explanatory power and the beta coefficients in a multi-factor framework. For this we employ a rolling estimation procedure that allows us to analyze the time variability of the model coefficients.In the empirical analysis we use monthly data of four macroeconomic variables and the market index to explain the returns of four German industry indices for the period from 1974 to 2000. In contrast to most studies which exclude banks from their empirical analysis we use three industrial indices and a bank index. The economic factors included in our model are term spreads, interest rates, exchange rates and the ifo business index as well as the market index. The empirical results confirm that the factors used in our empirical analysis seem well suited to explain the stock returns especially for banks. Moreover, it is evident that the explanatory power and the beta coefficients are time varying.
