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Recent Econometric Techniques for Macroeconomic and Financial Data, 1st ed. 2021 Dynamic Modeling and Econometrics in Economics and Finance Series, Vol. 27

Langue : Anglais

Coordonnateurs : Dufrénot Gilles, Matsuki Takashi

Couverture de l’ouvrage Recent Econometric Techniques for Macroeconomic and Financial Data

The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models.


The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.



Introduction (Gilles Dufrénot and Takashi Matsuki, eds)
Part I. Macroeconometrics and international finance
Chapter 1. Quantile and copula spectrum: a new approach to investigate cyclical dependence in economic time series
Gilles Dufrénot, Takashi Matsuki and Kimiko Sugimoto
1.-Introduction: why using quantile spectrum?
2.- Quantile spectrum: non-parametric and parametric Methods
2.1.- Non-parametric approach
2.2.- Parametric approach: quantile spectrum and quantile regression models
3.- Copula spectral density and rank-based Laplace periodogram
4. Estimating quantile spectrum using software
4.1.-Estimation of non-parametric quantile spectrum using RATS estima
4.2.- Using R package to estimate quantile spectrum and cross spectrum
References
Chapter 2. On the seemingly incompleteness of the exchange rate pass-trough to import prices
Antonia Lopez-Villavicencio and Valérie Mignon
1.-Introduction
2.- Methodology
3.-data
3.1.-Time sample
3.2- Variables
3.3- Indicators of globalization
3.4.- Descriptive statistics
4.- Results
4.1.- Accounting for globalization
4.2.- Using disaggregated data accounting for the good level
4.3.- Accounting for globalization at the good level
5. Conclusion
References
Chapter 3. A state-space model to estimate potential growth in the industrialized countries
Thomas Brand, Gilles Dufrénot, Antoine Mayerowitz
1.- Introduction
2.- is potential growth led by financial variables: a simple Bayesian estimation
3.- A State-space model with theoretical relationships
3.1.- The general model
3.2.-Sub-models and comparison with other models used in the literature
3.3.-Estimation methods
3.4.- Data and methods
3.5.- Conclusion
References
Chapter 4.- A top-down method for rational bubbles: application of the threshold bounds testing approach to the Japanese, UK and US Financial markets
Jun Nagayasu
1.-Introduction
2.-The threshold autoregressive distributed lag model (T-ADRL)
3.-Application : testing bubbles
4.- Conclusion
References
Chapter 5.- An analysis of the time-varying behavior of the equilibrium velocity of money in the euro area
Mariam Camarero, Juan Sapena and Cecilio Tamarit
1.- Introduction: the shockingly low money velocity in the Euro Area (EA) and its consequences
2.- Money demand and velocity: income and transactions
3.- A short review of the literature
4.- Methodology and estimation.
4.1.-A time-varying parameters State-Space framework for panel data.
4.2.- An application to the money velocity in the EA.
5.- Conclusions
References
Chapter 6.- Revisiting wealth effects in France: a double-nonlinearity approach
Olivier Damette and Fredj Jawadi
1.- Introduction
2.- Econometric methodology
2.1. Linear cointegration specification for wealth effects
2.2. Threshold ECM effects for wealth effects
2.3. Time varying VECM specification for wealth effects
3. Data and empirical analysis
3.1. Data and preliminary analysis
3.2. The linear cointegration analysis
3.3. Nonlinear cointegration with asymmetric adjustment
3.4. NECMs with nonlinearity in the long-run
5.- Conclusions
References
Part II. Financial econometrics
Chapter 7.- Econometrics of commodities
Jean-François Carpantier
1.-Introduction
2.- Tests of the Prebisch-Singer hypothesis
3.- Tests of the commodity currencies hypothesis
4. Models of commodity risk-management
5.-Models of financiarization of commodities
6.-Data comparison
7. Conclusion
References
Chapter 8.- Conditional Beta of real estate
Marcel Aloy, Sébastien Laurent and Christelle Lecourt
1.-Introduction
2.- Literature review
3.- Theory
4.- Main results
5.-Conclusion
References
Chapter 9.- Common factors in international portfolio flows
Yushi Yoshida
1.- Introduction
2.- International Portfolio Flows
2.1.- Review of Related Literature
2.2.- Financial Account Flows (global and regional overview of financial account flows based on quarterly data by the Balance of Payment statistics, IMF)
2.3.- Portfolio Account Flows (bond flows and equity flows based on daily data by EPFR (Emerging Portfolio Fund Research) Global)
3.- Multivariate GARCH Analysis
3.1.- Bond Flows (between pairs of countries)
3.2.- Equity Flows (between pairs of countries)
3.3.- Bond and Equity (within a country)
4.- Detrending Common Factors
4.1.- Common Factors and Detrending (principal components)
4.2.- Multivariate GARCH with Detrended Flows
5.- Conclusion
References
Chapter 10.- Persistence in the stochastic cycles of stock prices
Luis Alberiko Gil-Alana and Guglielmo Maria Caporale
1.- Introduction
2.- Stochastic cycles
3.- Data description
4.- Empirical conclusions
5.- Conclusions
Chapter 11.- Commodities and cryptocurrencies: Markov-switching Lévy models
Stéphane Goutte and Benjamin Keddad
1.- Introduction
2.- Literature review
2.1. Economic properties of Cryptocurrencies
2.2. Commodities
3.- Theoretical background
3.1. Markov-Switching
3.2. Lévy Jump
4.- The Stochastic Model
4.1. Markov-Switching
4.2. Lévy Jump
4.3 Regime-switching Lévy
5.-Data
5.1 Sources
5.2 Descriptive statistics
6.- Results
6.1 Cross-dynamic between commodities and crypto-currencies
6.2 Forecasting
7.- Conclusion
List of contributors

Gilles Dufrénot is a Professor of Economics at Aix-Marseille School of Economics in France. His main fields of interest are applied econometrics in macroeconomics and finance. He has published in international journals including the Journal of Economic dynamics and Control, Macroeconomic Dynamics, Journal of International Money and finance, Oxford Economic Papers. He has been a guest editor for several journals on issues related to nonlinear dynamics, macroeconometrics and computational economics.

 

Takeshi Matsuki is a Professor of Econometrics and Statistics at the University of Osaka-Gakuin in Japan. He specializes in forecasting methods, nonlinear systems and nonstationary panels in economics and finance. He has proposed new techniques for investigating international spillovers in international markets, channeling quantitative easing policies and identifying structural breaks in economic time series.


Applies econometric methods to a wide range of issues in macroeconomics and financial economics

Offers new tools for studying non-linear and non-stationary behaviors

Explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization

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Ouvrage de 387 p.

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