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AbstractThis paper develops a multilevel structural factor model to study international output comovement and its underlying driving forces. Our method combines a structural vector autoregression with a multilevel factor model, which helps us understand the economic meaning of the estimated factors. Using quarterly data of real GDP growth covering 9 emerging Asian economies and G‐7 countries, we estimate a global supply factor, a global demand factor, and group supply and demand factors for each group of the economies. We find that although the role of the global factors has intensified over the past 15 years for most of the economies, output fluctuations in Asia have remained less synchronized with the global factor than those in the industrial countries. The Asian regional factors have become increasingly important in tightening the interdependence within the region over time. Therefore, although emerging Asian economies cannot 'decouple' completely from the advanced economies, they have, nonetheless, sustained a strong independent cycle among themselves. We also find that synchronized supply shocks contributed more to the observed synchronization in output fluctuations among the Asian economies than demand shocks. This points to the role of productivity enhancement and transmission of other supply shocks through, for example, vertical trade integration, rather than dependence on external demand, as the primary source of business cycle synchronization in emerging Asia.

Networks of coupled oscillators in chimera states are characterized by an intriguing interplay of synchronous and asynchronous motion. While chimera states were initially discovered in mathematical model systems, there is growing experimental and conceptual evidence that they manifest themselves also in natural and man-made networks. In real-world systems, however, synchronization and desynchronization are not only important within individual networks but also across different interacting networks. It is therefore essential to investigate if chimera states can be synchronized across networks. To address this open problem, we use the classical setting of ring networks of non-locally coupled identical phase oscillators. We apply diffusive drive-response couplings between pairs of such networks that individually show chimera states when there is no coupling between them. The drive and response networks are either identical or they differ by a variable mismatch in their phase lag parameters. In both cases, already for weak couplings, the coherent domain of the response network aligns its position to the one of the driver networks. For identical networks, a sufficiently strong coupling leads to identical synchronization between the drive and response. For non-identical networks, we use the auxiliary system approach to demonstrate that generalized synchronization is established instead. In this case, the response network continues to show a chimera dynamics which however remains distinct from the one of the driver. Hence, segregated synchronized and desynchronized domains in individual networks congregate in generalized synchronization across networks. ; We acknowledge funding from the Volkswagen foundation, the Spanish Ministry of Economy and Competitiveness, Grant No. FIS2014-54177-R, the CERCA Programme of the Generalitat de Catalunya (R.G.A. and G.R.), and from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 642563 (R.G.A. and I.M.).

We propose a novel approach to investigate the synchronization of business cycles and we apply it to a Eurostat database of manufacturing industrial production time-series in the European Union (EU) over the 2000-2017 period. Our approach exploits Random Matrix Theory and extracts the latent information contained in a balanced panel data by cleaning it from possible spurious correlation. We employ this method to study the synchronization among different countries over time. Our empirical exercise tracks the evolution of the European synchronization patterns and identifies the emergence of synchronization clusters among different EU economies. We find that synchronization in the Euro Area increased during the first decade of the century and that it reached a peak during the Great Recession period. It then decreased in the aftermath of the crisis, reverting to the levels observable at the beginning of the 21st century. Second, we show that the asynchronous business cycle dynamics at the beginning of the century was structured along a East-West axis, with eastern European countries having a diverging business cycle dynamics with respect to their western partners. The recession brought about a structural transformation of business cyclesco-movements in Europe. Nowadays the divide can be identified along the North vs. South axis. This recent surge in asynchronization might be harmful for the European Union because it implies countries' heterogeneous responses to common policies.

Crisis is a conceptual tool for synchronizing different experiences of time. It is operative in notions of the Financial Crisis, the Crisis of Democracy, the Climate Crisis—and the Corona Crisis. This article explores that synchronization through an empirical inquiry into the different timescapes of the Corona Crisis. It builds empirically on 200 interviews with residents in Norra Botkyrka, which is located at the fringes of Sweden's capital Stockholm. The thematic analysis shows how the respondents' different time frames, time orders, tempos, and timings become synchronized through the crisis concept, but also how they invoke active and passive desynchronization. This temporal diversity points out the interplay between social differences and the various ways people are (de)synchronizing with the Corona Crisis.

We propose a novel approach to investigate the synchronization of business cycles and we apply it to a Eurostatdatabase of manufacturing industrial production time-series in the European Union (EU) over the 2000-2017 period.Our approach exploits Random Matrix Theory and extracts the latent information contained in a balanced panel databy cleaning it from possible spurious correlation. We employ this method to study the synchronization amongdifferent countries over time. Our empirical exercise tracks the evolution of the European synchronization patternsand identifies the emergence of synchronization clusters among different EU economies. We find thatsynchronization in the Euro Area increased during the first decade of the century and that it reached a peak duringthe Great Recession period. It then decreased in the aftermath of the crisis, reverting to the levels observable at thebeginning of the 21st century. Second, we show that the asynchronous business cycle dynamics at the beginningof the century was structured along a East-West axis, with eastern European countries having a diverging businesscycle dynamics with respect to their western partners. The recession brought about a structural transformation ofbusiness cycles co-movements in Europe. Nowadays the divide can be identified along the North vs. South axis.This recent surge in asynchronization might be harmful for the European Unio because it implies countries'heterogeneous responses to common policies.

We propose a novel approach to investigate the synchronization of business cycles and we apply it to a Eurostatdatabase of manufacturing industrial production time-series in the European Union (EU) over the 2000-2017 period.Our approach exploits Random Matrix Theory and extracts the latent information contained in a balanced panel databy cleaning it from possible spurious correlation. We employ this method to study the synchronization amongdifferent countries over time. Our empirical exercise tracks the evolution of the European synchronization patternsand identifies the emergence of synchronization clusters among different EU economies. We find thatsynchronization in the Euro Area increased during the first decade of the century and that it reached a peak duringthe Great Recession period. It then decreased in the aftermath of the crisis, reverting to the levels observable at thebeginning of the 21st century. Second, we show that the asynchronous business cycle dynamics at the beginningof the century was structured along a East-West axis, with eastern European countries having a diverging businesscycle dynamics with respect to their western partners. The recession brought about a structural transformation ofbusiness cycles co-movements in Europe. Nowadays the divide can be identified along the North vs. South axis.This recent surge in asynchronization might be harmful for the European Unio because it implies countries'heterogeneous responses to common policies.

Convergence of macroeconomic aggregates and subsequent synchronization of the cyclical features affecting these aggregates have been at the heart of economic debate for quite a while. Especially with the recent developments concerning the creation and crisis of a European common currency area, the question whether counties are similar enough to be targeted by uniform policy rules has been a crucial one. Beyond this relevance to an economist, the phenomena are also interesting from an econometric perspective. This thesis contains three self-contained chapters that contribute to the understanding of convergence and synchronization in various ways. Chapter 1 evaluates a novel approach to capture economic convergence as a process of transition. It considers the framework from Phillips and Sul (2007) that explicitly allows for periods of transitional divergence by separating a common component from idiosyncratic fluctuations and investigates its performance in a classical setting of time series convergence, considering both asymptotic results and Monte Carlo simulation methods. It turns out that in a setting where the time dimension considerably exceeds the cross-sectional dimension, the performance of the regression test is inferior to that of the standard cointegration tests. Chapter 2 considers a different way of incorporating transitory periods into convergence analysis. It argues that convergence is a dynamic process that can better be captured by considering changes in persistence. Tests for changes in persistence are applied for interest rate differentials on long-term government bonds for a broad set of countries. Overwhelming evidence for convergence in interest rates can be found when considering countries now using the Euro, while very little evidence can be found for previously stable relationships beginning to diverge. Chapter 3 puts the focus on comovement between output series and considers various concepts based in either the time or the frequency domain to detect and describe cyclical comovements in output data. The use of multivariate wavelet analysis and a modification of the cohesion statistic from Fourier analysis is suggested to simultaneously assess comovement at the frequency level and over time. The main finding is that synchronization does indeed vary with cycle length and that it has been affected by events during the time span of the sample.

Crisis is a conceptual tool for synchronizing different experiences of time. It is operative in notions of the Financial Crisis, the Crisis of Democracy, the Climate Crisis—and the Corona Crisis. This article explores that synchronization through an empirical inquiry into the different timescapes of the Corona Crisis. It builds empirically on 200 interviews with residents in Norra Botkyrka, which is located at the fringes of Sweden's capital Stockholm. The thematic analysis shows how the respondents' different time frames, time orders, tempos, and timings become synchronized through the crisis concept, but also how they invoke active and passive desynchronization. This temporal diversity points out the interplay between social differences and the various ways people are (de)synchronizing with the Corona Crisis.