57 research outputs found

    Business Cycle Transmission from the US to Germany: a Structural Factor Approach

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    This paper investigates the transmission of US macroeconomic shocks to Germany by employing a large-dimensional structural dynamic factor model. This framework allows us to investigate many transmission channels simultaneously, including 'new' channels like stock markets, foreign direct investment, bank lending and the confidence channel. We find that US shocks affect the US and Germany largely symmetrically. Trade and monetary policy reactions to strong price effects seem to be most relevant; financial markets may have become more important over time. The speed of transmission does not seem to have increased. Negative domestic influences apparently more than compensated positive US influences in the German economy between 1995 and 2000, but the US recession in 2001 seemed mainly responsible for the German slump. --International business cycles,international transmission channels,dynamic factor models,structural VAR techniques

    Dynamic factor models

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    Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be useful in investigating macroeconomic problems. --Principal components,dynamic factors,forecasting

    The global dimension of inflation: evidence from factor-augmented Phillips curves

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    We examine the global dimension of inflation in 24 OECD countries between 1980 and 2007 in a traditional Phillips curve framework. We decompose output gaps and changes in unit labor costs into common (or global) and idiosyncratic components using a factor analysis and introduce these components separately in the regression. Unlike previous studies, we allow global forces to affect inflation through (the common part of) domestic demand and supply conditions. Our most important result is that the common component of changes in unit labor costs notably affects inflation. We also find evidence that movements in import price inflation have small effects on CPI inflation while the impact of movements in the common component of the output gap is unclear. A counterfactual experiment illustrates that the common component of unit labor cost changes and non-commodity import price inflation have held down overall inflation in many countries in recent years. Our results imply that monetary policy makers need to carefully monitor global forces when assessing and predicting inflation. In analogy to the Phillips curves, we estimate monetary policy rules with common and idiosyncratic components of inflation and the output gap included separately. Central banks have indeed reacted to the global components. --Inflation,globalization,Phillips curves,factor models,monetary policy rules

    How Synchronized are Central and East European Economies with the Euro Area? Evidence from a Structural Factor model 

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    Dynamic factor models, international business cycles, EMU enlargement, counterfactual experiment

    How synchronized are central and east European economies with the euro area? Evidence from a structural factor model

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    A high degree of cyclical synchronization between central and east European countries (CEECs) and the euro area is generally seen as a prerequisite for successful EMU enlargement. This paper investigates comovements between CEECs and the euro area. We first establish stylized facts on economic linkages using dynamic correlation and cohesion measures. By means of a large-scale dynamic factor model, we then identify the main structural common euro-area shocks and investigate their transmission to the CEECs in comparison to the current EMU members. We finally carry out a counterfactual experiment which allows us to assess the costs and benefits of accession to EMU for individual CEECs in terms of economic volatilities and the implications of enlargement for synchronization. Overall, our results are mixed. Dynamic business cycle and inflation correlations between CEECs and the euro area are, on average, lower than between individual EMU members and the euro area, but they are higher than for some small peripheral EMU countries. This is confirmed by our other measure, variance shares of output and inflation explained by common euro-area factors. The proliferation of euro-area shocks to the CEECs does not differ significantly from the propagation to EMU countries in most cases. Based on our counterfactual experiment, we do not find significant stabilizing or destabilizing effects through a common monetary policy and fixed exchange rates. We also find that business cycle synchronization between CEECs and between most CEECs and the euro area will increase. There seems to be considerable heterogeneity across CEECs, implying that for some countries, accession to EMU would be more costly than for others. According to our analysis and based on our measures, Poland, Slovenia, Hungary and Estonia are more suitable EMU candidates than other countries. --Dynamic factor models,international business cycles,EMU enlargement,counterfactual experiment

    Testing for structural breaks in dynamic factor models

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    From time to time, economies undergo far-reaching structural changes. In this paper we investigate the consequences of structural breaks in the factor loadings for the specification and estimation of factor models based on principal components and suggest test procedures for structural breaks. It is shown that structural breaks severely inflate the number of factors identified by the usual information criteria. Based on the strict factor model the hypothesis of a structural break is tested by using Likelihood-Ratio, Lagrange-Multiplier and Wald statistics. The LM test which is shown to perform best in our Monte Carlo simulations, is generalized to factor models where the common factors and idiosyncratic components are serially correlated. We also apply the suggested test procedure to a US dataset used in Stock and Watson (2005) and a euro-area dataset described in Altissimo et al. (2007). We find evidence that the beginning of the so-called Great Moderation in the US as well as the Maastricht treaty and the handover of monetary policy from the European national central banks to the ECB coincide with structural breaks in the factor loadings. Ignoring these breaks may yield misleading results if the empirical analysis focuses on the interpretation of common factors or on the transmission of common shocks to the variables of interest. --Dynamic factor models,structural breaks,number of factors,Great Moderation,EMU

    Monetary policy, housing booms and financial (im)balances

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    This paper uses a factor-augmented vector autoregressive model (FAVAR) estimated on U.S. data in order to analyze monetary transmission via private sector balance sheets, credit risk spreads and asset markets in an integrated setup and to explore the role of monetary policy in the three imbalances that were observed prior to the global financial crisis: high house price inflation, strong private debt growth and low credit risk spreads. The results suggest that (i) monetary policy shocks have a highly significant and persistent effect on house prices, real estate wealth and private sector debt as well as a strong short-lived effect on risk spreads in the money and mortgage markets; (ii) monetary policy shocks have contributed discernibly, but at a late stage to the unsustainable developments in house and credit markets that were observable between 2001 and 2006; (iii) financial shocks have influenced the path of policy rates prior to the crisis, and the feedback effects of financial shocks via lower policy rates on property and credit markets are found to have probably been considerable. JEL Classification: E52, E44, C3, E3, E43asset prices, factor model, financial crisis, housing, monetary policy, private sector balance sheets

    Forecasting national activity using lots of international predictors: an application to New Zealand

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    We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. Using these methods, we assess the marginal predictive content of international data for New Zealand GDP growth. We find that exploiting a large number of international predictors can improve forecasts of our target variable, compared to more traditional models based on small datasets. This is in spite of New Zealand survey data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best. We also assess the type of international data that contains the most predictive information for New Zealand growth over our sample. --Forecasting,factor models,shrinkage methods,principal components,targeted predictors,weighted principal components,partial least squares

    How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach

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    This paper surveys existing factor forecast applications for real economic activity and inflation by means of a meta-analysis and contributes to the current debate on the determinants of the forecast performance of large-scale dynamic factor models relative to other models. We find that, on average, factor forecasts are slightly better than other models' forecasts. In particular, factor models tend to outperform small-scale models, whereas they perform slightly worse than alternative methods which are also able to exploit large datasets. Our results further suggest that factor forecasts are better for US than for UK macroeconomic variables, and that they are better for US than for euro-area output; however, there are no significant differences between the relative factor forecast performance for US and euro-area inflation. There is also some evidence that factor models are better suited to predict output at shorter forecast horizons than at longer horizons. These findings all relate to the forecasting environment (which cannot be influenced by the forecasters). Among the variables capturing the forecasting design (which can, by contrast, be influenced by the forecasters), the size of the dataset from which factors are extracted seems to positively affect the relative factor forecast performance. There is some evidence that quarterly data lend themselves better to factor forecasts than monthly data. Rolling forecasts are preferable to recursive forecasts. The factor estimation technique seems to matter as well. Other potential determinants - namely whether forecasters rely on a balanced or an unbalanced panel, whether restrictions implied by the factor structure are imposed in the forecasting equation or not and whether an iterated or a direct multi-step forecast is made - are found to be rather irrelevant. Moreover, we find no evidence that pre-selecting the variables to be included in the panel from which factors are extracted helped to improve factor forecasts in the past. --Factor models,forecasting,meta-analysis
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