How have global shocks impacted the real effective exchange rates of individual euro area countries since the euro's creation?

This paper uncovers the response pattern to global shocks of euro area countries' real effective exchange rates before and after the start of Economic and Monetary Union (EMU), a largely open ended question when the euro was created. We apply to that end a newly developed methodology based on high dimensional VAR theory. This approach features a dominant unit to a large set of over 60 countries' real effective exchange rates and is based on the comparison of two estimated systems: one before and one after EMU. We find strong evidence that the pattern of responses depends crucially on the nature of global shocks. In particular, post-EMU responses to global US dollar shocks have become similar to Germany's response before EMU, i.e. to that of the economy that used to issue Europe's most credible legacy currency. By contrast, post-EMU responses of euro area countries to global risk aversion shocks have become similar to those of Italy, Portugal or Spain before EMU, i.e. of economies of the euro area's periphery. Our findings also suggest that the divergence in external competitiveness among euro area countries over the last decade, which is at the core of today's debate on the future of the euro area, is more likely due to country-specific shocks than to global shocks.Euro, Real Effective Exchange Rates, Weak and Strong Cross Sectional Dependence, High-Dimensional VAR, Identification of Shocks.

Theory and Practice of GVAR Modeling

The Global Vector Autoregressive (GVAR) approach has proven to be a very useful approach to analyze interactions in the global macroeconomy and other data networks where both the cross-section and the time dimensions are large. This paper surveys the latest developments in the GVAR modeling, examining both the theoretical foundations of the approach and its numerous empirical applications. We provide a synthesis of existing literature and highlight areas for future research

Big Data Analytics: A New Perspective

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique used to trade off parsimony and .t when the number of possible covariates is large, often much larger than the number of available observations. However, issues such as the choice of a penalty function and tuning parameters associated with the use of penalized regressions remain contentious. In this paper, we provide an alternative approach that considers the statistical significance of the individual covariates one at a time, whilst taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure The OCMT has a number of advantages over the penalised regression methods: It is based on statistical inference and is therefore easier to interpret and relate to the classical statistical analysis, it allows working under more general assumptions, it is computationally simple and considerably faster, and it performs better in small samples for almost all of the five different sets of experiments considered in this paper. Despite its simplicity, the theory behind the proposed approach is quite complicated. We provide extensive theoretical and Monte Carlo results in support of adding the proposed OCMT model selection procedure to the toolbox of applied researchers.boostin

Is There a Debt-threshold Effect on Output Growth?

This paper studies the long-run impact of public debt expansion on economic growth and investigates whether the debt-growth relation varies with the level of indebtedness. Our contribution is both theoretical and empirical. On the theoretical side, we develop tests for threshold effects in the context of dynamic heterogeneous panel data models with cross-sectionally dependent errors and illustrate, by means of Monte Carlo experiments, that they perform well in small samples. On the empirical side, using data on a sample of 40 countries (grouped into advanced and developing) over the 1965-2010 period, we and no evidence for a universally applicable threshold effect in the relationship between public debt and economic growth, once we account for the impact of global factors and their spillover effects. Regardless of the threshold, however, we find significant negative long-run effects of public debt build-up on output growth. Provided that public debt is on a downward trajectory, a country with a high level of debt can grow just as fast as its peers

Long-Run Effects in Large Heterogenous Panel Data Models with Cross-Sectionally Correlated Errors

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T) and the cross-section dimension (N) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates particularly when T is not too large and lies in the range of 30 _ T < 100

Revisiting the Great Ratios Hypothesis

The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth, arbitrage or solvency, the empirical literature has tended to find little evidence for them. We argue that this outcome could be due to episodic failure of cointegration, possible two-way causality between the variables in the ratios, and cross-country error dependence due to latent factors. We propose a new system pooled mean group estimator (SPMG) to deal with these features. Using this new panel estimator and a dataset spanning almost one and half centuries and seventeen countries, we find support for five out of the seven great ratios that we consider. Extensive Monte Carlo experiments also show that the SPMG estimator with bootstrapped confidence intervals stands out as the only estimator with satisfactory small sample properties

A Counterfactual Economic Analysis of Covid-19 Using a Threshold Augmented Multi-Country Model

This paper develops a threshold-augmented dynamic multi-country model (TG-VAR) to quantify the macroeconomic effects of Covid-19. We show that there exist threshold effects in the relationship between output growth and excess global volatility at individ

Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR

The paper contributes to the growing global VAR (GVAR) literature by showing how global and national shocks can be identified within a GVAR framework. The usefulness of the proposed approach is illustrated in an application to the analysis of the interactions between public debt and real output growth in a multicountry setting, and the results are compared to those obtained from standard single country VAR analysis. We find that on average (across countries) global shocks explain about one third of the long-horizon forecast error variance of output growth, and about one fifth of the long run variance of the rate of change of debt-to-GDP. Evidence on the degree of cross-sectional dependence in these variables and their innovations are exploited to identify the global shocks, and priors are used to identify the national shocks within a Bayesian framework. It is found that posterior median debt elasticity with respect to output is much larger when the rise in output is due to a fiscal policy shock, as compared to when the rise in output is due to a positive technology shock. The cross country average of the median debt elasticity is 1.58 when the rise in output is due to a fiscal expansion as compared to 0.75 when the rise in output follows from a favorable output shock

Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model

This paper studies the asymptotic power for the sphericity test in a Öxed e§ect panel data model proposed by Baltagi, Feng and Kao (2011), (JBFK). This is done under the alternative hypotheses of weak and strong factors. By weak factors, we mean that the Euclidean norm of the vector of the factor loadings is O(1). By strong factors, we mean that the Euclidean norm of the vector of factor loadings is O(√n), where n is the number of individuals in the panel. To derive the limiting distribution of JBFK under the alternative, we Örst derive the limiting distribution of its raw data counterpart. Our results show that, when the factor is strong, the test statistic diverges in probability to inÖnity as fast as Op(nT). However, when the factor is weak, its limiting distribution is a rightward mean shift of the limit distribution under the null. Second, we derive the asymptotic behavior of the di§erence between JBFK and its raw data counterpart. Our results show that when the factor is strong this difference is as large as Op(n). In contrast, when the factor is weak, this di§erence converges in probability to a constant. Taken together, these results imply that when the factor is strong, JBFK is consistent, but when the factor is weak, JBFK is inconsistent even though its asymptotic power is nontrivial