Central bank research hub - Papers by Rolf Scheufele
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Research hub papers by author Rolf ScheufeleenMixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland
http://www.ijcb.org/journal/ijcb19q2a5.pdf
IJCB International Journal of Central Banking by Alain Galli, Christian Hepenstrick and Rolf ScheufeleMixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland2019-06-01T00:02:05ZWe compare several methods for monitoring short-term economic developments in Switzerland. Based on a large mixed-frequency data set, the following approaches are presented and discussed: a factor-based information combination approach (a dynamic factor model based on the Kalman filter/smoother and estimated by the EM algorithm), a model combination approach resting on MIDAS regression models, and a variable selection approach using a specific-to-general algorithm. In an out-of-sample GDP forecasting exercise, we show that the considered approaches clearly beat relevant benchmarks such as univariate time-series models and models that work with just one indicator. Moreover, we find that the factor model is superior to the other two approaches under investigation. However, forecast pooling of the three methods turns out to be even more promising.Mixed-Frequency Models for Tracking Short-Term Economic Developments in SwitzerlandFull texthttp://www.ijcb.org/journal/ijcb19q2a5.pdfChristian HepenstrickAlain GalliRolf ScheufeleAlain Galli, Christian Hepenstrick and Rolf Scheufele2019-06IJCB International Journal of Central BankingC32C53E37Mixed-frequency models for tracking short-term economic developments in Switzerland
http://www.snb.ch/n/mmr/reference/working_paper_2017_02/source/working_paper_2017_02.n.pdf
Swiss National Bank Working Papers by Alain Galli, Christian Hepenstrick and Rolf ScheufeleMixed-frequency models for tracking short-term economic developments in Switzerland2017-02-01T00:00:01ZWe compare several methods for monitoring short-term economic developments in Switzerland. Based on a large mixed-frequency data set, the following approaches are presented and discussed: factor-based information combination approaches (including factor model versions based on the Kalman filter/smoother, a principal component based version and the three-pass regression filter), a model combination approach resting on MIDAS regression models and a model selection approach using a specific-to-general algorithm. In an out-of-sample GDP forecasting exercise, we show that the considered approaches clearly beat relevant benchmarks such as univariate time-series models and models that work with one or a small number of indicators. This suggests that a large data set is an important ingredient for successful real-time monitoring of the Swiss economy. The models using a large data set particularly outperform others during and after the Great Recession. Forecast pooling of the most-promising methods turns out to be the best option for obtaining a reliable nowcast for the Swiss economy.Mixed-frequency models for tracking short-term economic developments in SwitzerlandAbstracthttp://www.snb.ch/en/mmr/papers/id/working_paper_2017_02Full texthttp://www.snb.ch/n/mmr/reference/working_paper_2017_02/source/working_paper_2017_02.n.pdfChristian HepenstrickAlain GalliRolf ScheufeleAlain Galli, Christian Hepenstrick and Rolf Scheufele2017-02-01Swiss National Bank SNB Working PapersC32C53E37Credit cycles and real activity - the Swiss case
http://www.snb.ch/n/mmr/reference/working_paper_2016_13/source/working_paper_2016_13.n.pdf
Swiss National Bank Working Papers by Gregor Bäurle and Rolf ScheufeleCredit cycles and real activity - the Swiss case2016-09-13T17:38:00ZThe global Great Recession has sparked renewed interest in the relationships between financial conditions and real activity. This paper considers the Swiss experience, studying the impact of credit market conditions and housing prices on real activity over the last three decades through the lens of a medium-scale structural Bayesian vector autoregressive model (BVAR). From a methodological point of view, the analysis is challenging for two reasons. First, we must cope with a large number of variables which leads to a high-dimensional parameter space in our model. Second, the identification of economically interpretable shocks is complicated by the interaction among many different relevant factors. As to the first challenge, we use Bayesian shrinkage techniques to make the estimation of a large number of parameters tractable. Specifically, we combine a Minnesota prior with information from training observations to form an informative prior for our parameter space. The second challenge, the identification of shocks, is overcome by combining zero and sign restrictions to narrow the plausible range of responses of observed variables to the shocks. Our empirical analysis indicates that while credit demand and, in particular, credit supply shocks explain a large fraction of housing price and credit fluctuation, they have a limited impact on real activity.Credit cycles and real activity - the Swiss caseAbstracthttp://www.snb.ch/en/mmr/papers/id/working_paper_2016_13Full texthttp://www.snb.ch/n/mmr/reference/working_paper_2016_13/source/working_paper_2016_13.n.pdfGregor BäurleRolf ScheufeleGregor Bäurle and Rolf Scheufele2016-09-13Swiss National Bank SNB Working PapersC11C32E30E44E51E52Foreign PMIs: A reliable indicator for exports?
http://www.snb.ch/n/mmr/reference/working_paper_2016_01/source/working_paper_2016_01.n.pdf
Swiss National Bank Working Papers by Sandra Hanslin and Rolf ScheufeleForeign PMIs: A reliable indicator for exports?2016-03-22T12:35:59ZForeign economic activity is a major determinant of export development. This paper presents an indicator for now- and forecasting exports, which is based on survey data that captures foreign economic perspectives. We construct an indicator by weighting foreign PMIs of main trading partners with their respective export shares. For two very trade exposed countries (Germany and Switzerland) the paper shows that the indicator based on foreign PMIs is strongly correlated with exports (total as well as goods exports). In an out-of-sample forecast comparison we employ MIDAS models to forecast the two different definitions of exports. We document that our export indicator performs very well relative to univariate benchmarks and relative to other major leading indicators using hard and soft data.Foreign PMIs: A reliable indicator for exports?Abstracthttp://www.snb.ch/en/mmr/papers/id/working_paper_2016_01Full texthttp://www.snb.ch/n/mmr/reference/working_paper_2016_01/source/working_paper_2016_01.n.pdfSandra HanslinRolf ScheufeleSandra Hanslin and Rolf Scheufele2016-03-22Swiss National Bank SNB Working PapersC53F14F17Quantification and characteristics of household inflation expectations in Switzerland
http://www.snb.ch/n/mmr/reference/working_paper_2014_11/source/working_paper_2014_11.n.pdf
Swiss National Bank Working Papers by Rina Rosenblatt-Wisch and Rolf ScheufeleQuantification and characteristics of household inflation expectations in Switzerland2014-12-12T17:32:00ZInflation expectations are a key variable in conducting monetary policy. However, these expectations are generally unobservable and only certain proxy variables exist, such as surveys on inflation expectations. This paper offers guidance on the appropriate quantification of household inflation expectations in the Swiss Consumer Survey, where answers are qualitative in nature. We apply and evaluate different variants of the probability approach and the regression approach; we demonstrate that models which include answers on perceived inflation and allow for time-varying response thresholds yield the best results; and we show why the originally proposed approach of Fluri and Spörndli (1987) has resulted in heavily biased inflation expectations since the mid-1990s. Furthermore, we discuss some of the key features of Swiss householdinflation expectations, i.e. the fact that there has been a shift in expectation formation since 2000 (expectations are better anchored and less adaptive, and there is lower disagreement of expectations). We suggest that this may be linked to the Swiss National Bank's adjustment of its monetary policy framework around this time. In addition, we outline how expectation formation in Switzerland is in line with the sticky information model, where information disseminates slowly from professional forecasters to households.Quantification and characteristics of household inflation expectations in SwitzerlandFull texthttp://www.snb.ch/n/mmr/reference/working_paper_2014_11/source/working_paper_2014_11.n.pdfRolf ScheufeleRina Rosenblatt-WischRina Rosenblatt-Wisch and Rolf Scheufele2014-11Swiss National Bank SNB Working PapersC22C82E31E50Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
http://www.snb.ch/n/mmr/reference/working_paper_2012_16/source/working_paper_2012_16.n.pdf
Swiss National Bank Working Papers by Katja Drechsel and Rolf ScheufeleBottom-up or Direct? Forecasting German GDP in a Data-rich Environment2013-01-07T12:37:00ZThis paper presents a method to conduct early estimates of GDP growth in Germany. We employ MIDAS regressions to circumvent the mixed frequency problem and use pooling techniques to summarize efficiently the information content of the various indicators. More specifically, we investigate whether it is better to disaggregate GDP (either via total value added of each sector or by the expenditure side) or whether a direct approach is more appropriate when it comes to forecasting GDP growth. Our approach combines a large set of monthly and quarterly coincident and leading indicators and takes into account the respective publication delay. In a simulated out-of-sample experiment we evaluate the different modelling strategies conditional on the given state of information and depending on the model averaging technique. The proposed approach is computationally simple and can be easily implemented as a nowcasting tool. Finally, this method also allows to retrace the driving forces of the forecast and hence enables the interpretability of the forecast outcome.Bottom-up or Direct? Forecasting German GDP in a Data-rich EnvironmentFull texthttp://www.snb.ch/n/mmr/reference/working_paper_2012_16/source/working_paper_2012_16.n.pdfKatja DrechselRolf ScheufeleKatja Drechsel and Rolf Scheufele2013-01-07Swiss National Bank SNB Working Papers