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. * The views expressed in this paper do not necessarily reflect the views of the Deutsche Bundesbank. Non-technical summaryAnalyzing data sets with a large number of variables and time periods involves a severe risk that some of the model parameters are subject to structural breaks.Dynamic factor models may be more affected by this issue than other econometrics models, since factor models rely on large datasets. 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. In our theoretical analysis, we first consider the effects of structural breaks. It turns out that structural breaks in the factor loadings increase the dimension of the factor space. The reason is that in the case of a single structural break, two sets of common factors are needed to represent the common components in the two subsamples before and after the break. Thus, structural breaks in the factor loadings do not only lead to inconsistent estimates of the loadings but also to a larger dimension of the factor space. If we are only interested in decomposing variables into common and idiosyncratic components, it is sufficient to increase the number of factors such that the factor space is large enough to represent the different subspaces of the two regimes. However, if we are interested in a more parsimonious factor representation that allows us to recover the original factors, the estimation has to account for the structural breaks in the factor loadings. It is therefore very important to have tests at hand which inform us about whether or not...
Abstract: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. it has advantages over other models used in this context, which are not able to investigate as many transmission channels simultaneously.In the paper, we identify two shocks which have their origin in the US, one medium-run supply shock and one short-run real demand shock. We find that these shocks affect the US economy and the German economy symmetrically. That is, the supply shock raises output and lowers prices and interest rates, and the demand shock increases all three variables in both countries. The supply shock displays mainly medium-run effects, and the demand shock displays short-run effects in both the US and Germany.As concerns the transmission channels: trade, influenced by movements of relative prices, seems to play a dominant role in the transmission. Besides trade, monetary policy reacts to relatively strong German price movements and seems to influence the impact of US shocks in the medium run. When we consider the entire period, no clear conclusion can be drawn on the role of financial markets and the confidence channel.
We analyze the link between banks and the macroeconomy using a model that extends a macroeconomic VAR for the U.S. with a set of factors summarizing conditions in about 1,500 commercial banks. We investigate how macroeconomic shocks are transmitted to individual banks and obtain the following main findings. Backward-looking risk of a representative bank declines, and bank lending increases following expansionary shocks. Forwardlooking risk increases following an expansionary monetary policy shock. There is, however, substantial heterogeneity in the transmission of macroeconomic shocks, which is due to bank size, capitalization, liquidity, risk, and the exposure to real estate and consumer loans.JEL codes: E44, G21
There is growing consensus that the conduct of monetary policy can have an impact on stability through the risk-taking incentives of banks. Falling interest rates might induce a "search for yield" and generate incentives to invest into risky activities. This paper provides evidence on the link between monetary policy, commercial property prices, and bank risk taking. We use a factor-augmented vector autoregressive model (FAVAR) for the U.S. for the period 1997-2008. We include standard macroeconomic indicators and factors summarizing information provided in the Federal Reserve's Survey of Terms of Business Lending. These data allow modeling the reactions of banks' new lending volumes and prices as well as the riskiness of new loans. We do not find evidence for increased risk taking for the entire banking system after a monetary policy loosening or an unexpected increase in property prices. This masks, however, important differences across banking groups. Small domestic banks increase their exposure to risk, foreign banks lower risk, and large domestic banks do not change their risk exposure.
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