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About this book

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.

Table of Contents

Frontmatter

Macroeconometrics

Frontmatter

Quantile and Copula Spectrum: A New Approach to Investigate Cyclical Dependence in Economic Time Series

Abstract
This chapter presents a survey of some recent methods used in economics and finance to account for cyclical dependence and account for their multifaced dynamics: nonlinearities, extreme events, asymmetries, non-stationarity, time-varying moments. To circumvent the caveats of the standard spectral analysis, new tools are now used based on copula spectrum, quantile spectrum and Laplace periodogram in both non-parametric and parametric contexts. The chapter presents a comprehensive overview of both theoretical and empirical issues as well as a computational approach to explain how the methods can be implemented using the R Package.
Gilles Dufrénot, Takashi Matsuki, Kimiko Sugimoto

On the Seemingly Incompleteness of Exchange Rate Pass-Through to Import Prices: Do Globalization and/or Regional Trade Matter?

Abstract
This paper assesses the impact of globalization and regionalization on exchange rate pass-through (ERPT) into import prices in three core eurozone countries. To this end, we consider various indicators of globalization and rely on both aggregated (i.e., country level) and disaggregated (i.e., good level) data. Using quarterly data since 1992, we do not find compelling evidence that global factors cause a structural change in the degree of exchange rate pass-through. Indeed, increased trade openness or lower trade tariffs push up ERPT in some sectors, though results are quite sparse. However, regionalization, defined as a higher proportion of intra-EU imports’ share in total imports, reduces the pass-through in a more generalized way. Most importantly, we show that ERPT incompleteness generally observed in the literature is in appearance only and not at play when intra-EU trade is controlled for. Overall, our findings show that ERPT is complete and significant in numerous sectors, meaning that exchange rate changes still exert important pressure on domestic prices.
Antonia López-Villavicencio, Valérie Mignon

A State-Space Model to Estimate Potential Growth in the Industrialized Countries

Abstract
This paper proposes new estimates of potential growth for 5 major industrialized countries. We use a state-space approach to obtain joint estimates of potential growth and the natural interest rates. The model is a reduced-form of a partial equilibrium model with a Phillips curve and an IS curve. In addition to the usual determinants of prices and business fluctuations, we consider financial variables as a determinant of the business cycle.
Thomas Brand, Gilles Dufrénot, Antoine Mayerowitz

Detecting Tranquil and Bubble Periods in Housing Markets: A Review and Application of Statistical Methods

Abstract
We provide a brief review of recent developments in research on price movements of real estate, especially bubbles, and highlight the gap between theoretical and statistical approaches to bubble detection. We also propose applying a top-down strategy to a bounds testing method (Pesaran et al. in J. Appl. Econom. 16(3):289–326, 2001) to investigate rational price bubbles. Furthermore, by introducing nonlinearity into the autoregressive distributed lag model, we modify the bounds test to be more suitable for bubble analyses.
Jun Nagayasu

An Analysis of the Time-Varying Behavior of the Equilibrium Velocity of Money in the Euro Area

Abstract
Recent developments in inflation and M3 velocity in the euro area have raised serious doubts about the reliability of M3 growth as a pillar of the ECB’s monetary policy strategy. We develop a very flexible and comprehensive state-space framework for modeling the velocity of circulation. Our specification allows for the estimation of different autoregressive alternatives and includes control instruments, whose coefficients can be set up either common or idiosyncratic. This is particularly useful to detect asymmetries in the reaction among countries to common shocks. Our findings first suggest that the downward trend of M3 velocity is mainly explained by the evolution of permanent income, proxied by the trend component of per capita income, and also exhibits a high persistence. A second relevant result is the asymmetric impact of business cycle fluctuations in the evolution of the unobserved state that drives the varying parameters, causing the instability of velocity. Third, the estimated model emphasizes the role of changes in uncertainty and risk premia with heterogeneous and asymmetric effects for the different member countries of the euro area. Hence, although monetary aggregates can be used as a nominal anchor, it is essential, especially for the case of peripheral EMU countries, to complement these measures with other policies, not only unconventional monetary policies, but also the use of fiscal and structural initiatives.
Mariam Camarero, Juan Sapena, Cecilio Tamarit

Revisiting Wealth Effects in France: A Double-Nonlinearity Approach

Abstract
This paper investigates the relationship between French wealth and household consumption in a nonlinear context. At first, we update the previous French wealth effects estimates by taking into account the post subprime crisis period; we show that the wealth effect is still positive but only about 8%, rather than 13% suggesting that the wealth effect slightly decreased after the subprime crisis. In addition, unlike previous studies, we enable the wealth–consumption relationship to exhibit asymmetry, time variation and nonlinearity. To this end, we specify, on the one hand, two different threshold autoregressive models (TAR and MTAR) in order to reproduce nonlinear wealth effects in the short-term. On the other hand, we propose a time-varying cointegration specification to the consumption–wealth relationship in the long term. Interestingly, our specification enables the introduction of nonlinearity not only asymmetrical adjustment in the short run but also in the long-term relationship in order to capture different and complex forms of wealth effects. We show a significant wealth effect and find evidence of an unstable wealth–consumption relationship, particularly in 2000 and during the subprime crisis, suggesting an increase in the wealth effect during these periods.
Olivier Damette, Fredj Jawadi

Productivity Spillovers in the Global Market

Abstract
This paper analyzes the effect of productivity shocks originating from other countries on economic growth in the home country. Traditionally, productivity shocks have been considered as driving forces of economic growth in their home countries. However, productivity improvements occur both at home and overseas. In liberalized global markets, economic growth is, in theory, also attributable to productivity shocks from other countries. Using data from 18 countries, we show that numerous countries benefit from productivity spillovers. Nevertheless, their impacts on the economy differ according to the origin of the economic shocks. On the one hand, US shocks are rather pervasive and affect many economies and regions, regardless of their development stage. On the other hand, shocks from other country groups exert less influence over foreign economies. Thus, homogeneous effects of productivity spillovers across countries, which are often assumed in previous studies using the standard panel data and spatial models, are inappropriate. The mixed results from previous global analyses, particularly using macroeconomic data, are attributable to such heterogeneous effects of productivity shocks.
Nazmus Sadat Khan, Jun Nagayasu

Financial Econometrics

Frontmatter

Commodity Prices in Empirical Research

Abstract
Commodity prices are key ingredients in many economic theories. We pick three of them (Prebisch–Singer hypothesis, commodity currencies, financialization of commodity markets) and give a critical view on the empirical challenges faced by practitioners, including measurement inconsistencies, endogeneity concerns, time series properties, and empirical design.
Jean-François Carpantier

Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs

Abstract
Beta coefficients are the cornerstone of asset pricing theory in the CAPM and multiple factor models. This chapter proposes a review of different time series models used to estimate static and time-varying betas, and a comparison on real data. The analysis is performed on the USA and developed Europe REIT markets over the period 2009–2019 via a two-factor model. We evaluate the performance of the different techniques in terms of in-sample estimates as well as through an out-of-sample tracking exercise. Results show that dynamic models clearly outperform static models and that both the state space and autoregressive conditional beta models outperform the other methods.
Marcel Aloy, Floris Laly, Sébastien Laurent, Christelle Lecourt

Revisiting the Glick–Rogoff Current Account Model: An Application to the Current Accounts of BRICS Countries

Abstract
Understanding what drives the changes in current accounts is one of the most important macroeconomic issues for developing countries. Excessive surpluses in current accounts can trigger trade wars, and excessive deficits in current accounts can, on the other hand, induce currency crises. The Glick–Rogoff (1995, Journal of Monetary Economics) model, which emphasizes productivity shocks at home and in the world, fit well with developed economies in the 1970s and 1980s. However, the Glick–Rogoff model fits poorly when it is applied to fast-growing BRICS countries for the period including the global financial crisis. We conclude that different mechanisms of current accounts work for developed and developing countries.
Yushi Yoshida, Weiyang Zhai

Cycles and Long-Range Behaviour in the European Stock Markets

Abstract
This paper uses a modelling framework which includes two singularities (or poles) in the spectral density function, one corresponding to the long-run (zero) frequency and the other to the cyclical (nonzero) frequency. The adopted specification is very general, since it allows for fractional integration with stochastic patterns at the zero and cyclical frequencies and includes both long-memory and short-memory components. The cyclical patterns are modelled using Gegenbauer processes. This model is estimated using monthly data for five European stock market indices (DAX30, FTSE100, CAC40, FTSE MIB40, IBEX35) from January 2009 to January 2019. The results indicate that the series are highly persistent at the long-run frequency, but they are not supportive of the existence of cyclical stochastic structures in the European financial markets. The only clear evidence of a stochastic cycle is obtained in the case of France under the assumption of white noise disturbances; in all other cases, there is no evidence of cycles.
Guglielmo Maria Caporale, Luis A. Gil-Alana, Carlos Poza

A Non-linear Approach to Measure the Dependencies Between Bitcoin and Other Commodity Markets

Abstract
In this paper, we explore the relationship across cryptocurrencies and a set of commodities by using a Markov-Switching-VAR model. The parametric form of the model allows us to compute the regime-dependent impulse response functions during high and low volatility episodes and then to quantify bidirectional spillovers between both markets. Our main results show that responses to commodity shocks are more important in the high volatility regime for almost all commodities. However, we find a very moderate impact of the Bitcoin fluctuations on commodities, although situations seem to differ according to the commodity.
Stéphane Goutte, Benjamin Keddad

Typology of Nonlinear Time Series Models

Abstract
This paper attempts to provide a comprehensive review of nonlinear time series models, starting with the rationale for such models, their superiority over their linear counterparts, and issues surrounding their analysis especially in terms of the simultaneous examination of nonlinear and nonstationary properties of the data. The study provides a detailed typology of various univariate nonlinear time series models, the aspects that it helps capture in data and their estimation procedures. The paper then provides an exposition of the concept of nonlinear cointegration in a multivariate context and some of the issues therein. As an illustrative example, the study estimates a SETAR model for the Indian money multiplier and provides a brief analysis. We conclude with the relevance and applicability of these models in further understanding the dynamics in economic data.
Aditi Chaubal

Pareto Models for Risk Management

Abstract
The Pareto model is very popular in risk management, since simple analytical formulas can be derived for financial downside risk measures (value-at-risk, expected shortfall) or reinsurance premiums and related quantities (large claim index, return period). Nevertheless, in practice, distributions are (strictly) Pareto only in the tails, above (possible very) large threshold. Therefore, it could be interesting to take into account second-order behavior to provide a better fit. In this article, we present how to go from a strict Pareto model to Pareto-type distributions. We discuss inference, derive formulas for various measures and indices, and finally provide applications on insurance losses and financial risks.
Arthur Charpentier, Emmanuel Flachaire
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