Recent Econometric Techniques for Macroeconomic and Financial Data

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