Global and Regional Business Cycles - Shocks and Propagations

Thorsrud, Leif Anders

doi:10.2139/ssrn.2269609

Cited by 12 publications

(11 citation statements)

References 43 publications

(29 reference statements)

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“…We refer to this estimator as the "top-down PC estimator" as this estimator starts from a PC analysis of the entire system. In empirical studies this top-down PC estimator is employed by Beck et al (2011), Beck et al (2009, Aastveit et al (2011) and Thorsrud (2013). A problem with this estimator is that the regional factors give rise to a strong correlation among the regional clusters of idiosyncratic components.…”

Section: Relation To Existing (Non Bayesian) Approaches 241 Two-stementioning

confidence: 99%

Analyzing Business and Financial Cycles Using Multi-Level Factor Models

Breitung

Eickmeier

2014

SSRN Journal

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Research QuestionIn recent years (dynamic) factor models have become increasingly popular for macroeconomic analysis and forecasting in a data-rich environment. A serious limitation of the standard approximate factor model is that it assumes the common factors to affect all variables of the system. However, the efficiency of the Principal Component (PC) estimator for the common factors may deteriorate substantially if there are factors that load on subsets of variables only. Those factors may also be of independent interest. In an international context, for example, factors that load on variables associated with specific regions ("regional factors") could be (and have been) analyzed besides the global factors which link all variables in the model. Alternatively (or in addition), a block structure may represent economic, cultural or other characteristics. This paper addresses the question how such models can be estimated in a fast and easy way. ContributionThis paper makes several contributions. First, we provide a comprehensive comparison of existing estimation approaches for multi-level factor models and propose two very simple alternative estimation techniques based on sequential least squares and canonical correlations (which avoids any iterations). Second, we extend the sequential least squares estimation approach to a three-level factor model (with, for example, global, regional and variable-specific factors) with overlapping blocks of factors. Such factors structures are challenging as they cannot be estimated one level after another. A final contribution are three applications in which we study international comovements of business and financial cycles as well as asymmetries over the business cycle in the US. ResultsOur suggested estimation techniques provide (point) estimates in a tiny fraction of a second (in typical (macro) settings) compared to a Bayesian estimator that requires several hours. We also shows that based on Monte Carlo simulations that, in some circumstances, our proposed estimators tend to outperform alternative (two-step principal component and quasi maximum likelihood) estimation methods.In the first application we apply several estimation methodologies for twolevel factor models to an annual real activity dataset of more than 100 countries between 1960 and 2010. We estimate global and regional factors which turn out to be very similar across methods. We confirm Hirata et al.'s main finding that regional (business cycle) factors have become more important and global factors less important over time.In the second application, we use a large quarterly macro-financial dataset for 24 countries between 1995 and 2011. We estimate a global factor, regional factors, as well as variable-specific (macro and financial) factors. We find that financial variables strongly comove internationally, to a similar extent as macroeconomic variables. Macroeconomic and financial dynamics share common factors, but financial factors independent from macro factors also matter for financial variables. Finally, ...

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Section: Relation To Existing (Non Bayesian) Approaches 241 Two-stementioning

confidence: 99%

Analyzing Business and Financial Cycles Using Multi-Level Factor Models

Breitung

Eickmeier

2014

SSRN Journal

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“…Gregory, Head and Raynauld (); Kose et al . (); Thorsrud (), this is done under the assumption that any movements in the domestic factor that are not explained by the international factor must be purely due to domestic forces, and implemented by estimating the following equation:

F_{t}^{D} = β F_{t}^{I} + e_{t}

. Here,

F_{t}^{D}

and

F_{t}^{I}

are the estimated factors from the domestic and foreign data sets, containing variables that individually had a significant predictive power in explaining the forecast revisions (i.e.…”

Section: Predicting Forecast Revisionsmentioning

confidence: 99%

Do Central Banks Respond Timely to Developments in the Global Economy?

2019

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Our analysis suggests; they do not! We arrive at this conclusion by showing that revisions to the published interest rate path projections from the central banks in New Zealand, Norway and Sweden can be predicted by timely and forward‐looking international indicators. Furthermore, using individual country and Panel VARs, identified with an external instrument method, we show that the policy surprises induced by the predictable revisions likely contain information about how the central banks assess past, current and future economic conditions and thereby leads to a positive co‐movement between the interest rate and both financial markets and the macroeconomy.

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“…8 Di Mauro, Dees, and Mc Kibbon (2008) present a summary of different types of factors affecting global and regional linkages. Thorsrud (2012) document that regional demand and supply shocks play important roles in explaining national business cycles using a FAVAR model. Mumtaz, Simonelli, and Surico (2011) use a dynamic factor model and report that while the importance of the global factor has declined, regional cycles have become more pronounced over time.…”

Section: What Do We Know About the Evolution Of Global And Regionmentioning

confidence: 99%

“…Our findings are consistent with the results reported by studies that employ dynamic factor models. For example, Karagedikli and Thorsrud (2012) and Mumtaz, Simonelli, and Surico (2011) also report that regional business cycles have become more pronounced over time. We focus on a much larger dataset than these studies do.…”

Section: A Evolution Of Global and Regional Cyclesmentioning

confidence: 99%

“…We next assess the evolution of variance shares attributable to different factors in explaining consumption and investment fluctuations. For the world as a whole, the increase in the variance contribution of regional factors to consumption fluctuations is on average about 6 percentage points (from 8 percent to 14 percent), but the joint share of the global and region-specific factors 24 Karagedikli and Thorsrud (2012) employ a FAVAR model to analyze the evolution of activity (GDP and IP) and price (CPI and PPI) factors over time. They use the quarterly data of 31 countries covering four regions (Asia, Europe, North and South America) over the period 1990:1-2009:4.…”

Section: B Synchronization Of Cycles In Consumption and Investmentmentioning

confidence: 99%

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Regionalization vs. Globalization

2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: Both global and regional economic linkages have strengthened substantially over the past quarter century. We employ a dynamic factor model to analyze the implications of these linkages for the evolution of global and regional business cycles. Our model allows us to assess the roles played by the global, regional, and country-specific factors in explaining business cycles in a large sample of countries and regions over the period 1960-2010. We find that, since the mid-1980s, the importance of regional factors has increased markedly in explaining business cycles especially in regions that experienced a sharp growth in intra-regional trade and financial flows. By contrast, the relative importance of the global factor has declined over the same period. In short, the recent era of globalization has witnessed the emergence of regional business cycles. Terms of use: Documents in EconStor may JEL Classification 2 EXECUTIVE SUMMARYThe inexorable forces of globalization and regionalization have reshaped the world economic landscape over the past quarter century. Global trade and financial flows have registered unprecedented growth during this period. Intra-regional economic linkages have also become much stronger with the proliferation of regional trade agreements and common currency areas.These developments have appeared to affect the evolution of global and regional business cycles in unexpected ways. For example, despite the presence of strong global trade and financial linkages, there was significant variation in growth performance across different regions during the 2008-09 global financial crisis. Specifically, some regions (e.g., Asia) exhibited surprising resilience during the worst of the financial crisis and rapidly returned to high growth whereas some others (e.g., North America and Europe) experienced deep and prolonged contractions.These observations lead to a basic question: "Have regional elements become more important in driving business cycles in an era of globalization?" We answer this question using a dynamic factor model. Our model allows us to analyze the sources of fluctuations in output, consumption, and investment in a sample of 106 countries over the period 1960-2010. We consider cycles in seven regions: North America, Europe, Oceania, Asia, Latin America and the Caribbean, Middle East and North Africa, and Sub-Saharan Africa.Our results point to a surprising conclusion: The recent era of globalization has witnessed the emergence...

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Global and Regional Business Cycles - Shocks and Propagations

Cited by 12 publications

References 43 publications

Analyzing Business and Financial Cycles Using Multi-Level Factor Models

Analyzing Business and Financial Cycles Using Multi-Level Factor Models

Do Central Banks Respond Timely to Developments in the Global Economy?

Regionalization vs. Globalization

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