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How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach. (2008). Ziegler, Christina ; Eickmeier, Sandra.
In: Journal of Forecasting.
RePEc:jof:jforec:v:27:y:2008:i:3:p:237-265.

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  2. Exchange rate predictability: Fact or fiction?. (2024). Magkonis, Georgios ; Jackson, Karen.
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  5. Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts. (2023). Caporale, Guglielmo Maria ; Anderl, Christina.
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  6. Directed graphs and variable selection in large vector autoregressive models. (2023). Kascha, Christian ; Bruggemann, Ralf ; Bertsche, Dominik.
    In: Journal of Time Series Analysis.
    RePEc:bla:jtsera:v:44:y:2023:i:2:p:223-246.

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  7. Big data forecasting of South African inflation. (2022). Steenkamp, Daan ; Rankin, Neil ; Kotze, Kevin ; Botha, Byron ; Burger, Rulof.
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  8. Forecasting Inflation with a Zero Lower Bound or Negative Interest Rates: Evidence from Point and Density Forecasts. (2022). Caporale, Guglielmo Maria ; Anderl, Christina.
    In: CESifo Working Paper Series.
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  9. Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction. (2022). Salish, Nazarii ; Otto, Sven.
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  10. Forecasting using cross-section average–augmented time series regressions. (2021). Westerlund, Joakim ; Karabiyik, Hande.
    In: Econometrics Journal.
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  11. Factor extraction using Kalman filter and smoothing: This is not just another survey. (2021). Ruiz, Esther ; Miranda, Karen ; Poncela, Pilar.
    In: International Journal of Forecasting.
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  12. Forecasting imports with information from abroad. (2021). Lehmann, Robert ; Grimme, Christian ; Noeller, Marvin.
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    RePEc:eee:ecmode:v:98:y:2021:i:c:p:109-117.

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  14. Identifying US business cycle regimes using dynamic factors and neural network models. (2020). Soybilgen, Bari.
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    RePEc:wly:jforec:v:39:y:2020:i:5:p:827-840.

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  15. The role of temporal dependence in factor selection and forecasting oil prices. (2020). Binder, Kyle E ; Mjelde, James W ; Pourahmadi, Mohsen.
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  16. PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices. (2020). Uniejewski, Bartosz ; Serafin, Tomasz ; Maciejowska, Katarzyna.
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  17. Forecasting inflation with online prices. (2020). Bertolotto, Manuel I ; Aparicio, Diego.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:2:p:232-247.

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  18. Inflation expectations and the recovery from the Great Depression in Germany. (2020). Steege, Lucas Ter ; Daniel, Volker.
    In: Explorations in Economic History.
    RePEc:eee:exehis:v:75:y:2020:i:c:s0014498318301554.

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  19. A Suggestion for a Dynamic Multi Factor Model (DMFM). (2020). Tavlas, George ; Hall, Stephen ; Gibson, Heather D.
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  20. Directed Graph and Variable Selection in Large Vector Autoregressive Models. (2019). Brüggemann, Ralf ; Kascha, Christian ; Bruggemann, Ralf ; Bertsche, Dominik.
    In: Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy.
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  21. Nowcasting Swedish GDP with a large and unbalanced data set. (2019). Reijer, Ard ; Johansson, Andreas.
    In: Empirical Economics.
    RePEc:spr:empeco:v:57:y:2019:i:4:d:10.1007_s00181-018-1500-1.

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  22. Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model. (2019). Eftimoski, Dimitar.
    In: Journal for Economic Forecasting.
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  23. Sectoral Production and Diffusion Index Forecasts for Output in Lithuania. (2019). Barauskaite (Griskeviciene), Kristina ; Soofi-Siavash, Soroosh.
    In: Bank of Lithuania Discussion Paper Series.
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  24. Macroeconomic Forecasting with Factor-Augmented Adjusted Band Regression. (2019). Reschenhofer, Erhard ; Chud, Marek.
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  25. Macroeconomic forecasting for Australia using a large number of predictors. (2019). Hyndman, Rob ; Jiang, Bin ; Athanasopoulos, George ; Panagiotelis, Anastasios ; Vahid, Farshid.
    In: International Journal of Forecasting.
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  26. Forecasting Imports with Information from Abroad. (2019). Lehmann, Robert ; Grimme, Christian ; Noeller, Marvin.
    In: ifo Working Paper Series.
    RePEc:ces:ifowps:_294.

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  27. Inflation Expectations and the Recovery from the Great Depression in Germany. (2018). Steege, Lucas Ter ; Daniel, Volker.
    In: Working Papers.
    RePEc:zbw:pp1859:6.

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  28. Identifying US business cycle regimes using dynamic factors and neural network models. (2018). Soybilgen, Baris.
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    RePEc:pra:mprapa:94715.

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  29. Directed Graphs and Variable Selection in Large Vector Autoregressive Models. (2018). Kascha, Christian ; Bruggemann, Ralf ; Bertsche, Dominik.
    In: Working Paper Series of the Department of Economics, University of Konstanz.
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  30. Forecasting Current GDP Dynamics With Google Search Data. (2018). Lazaryan, Samvel S ; German, Nikita E.
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  31. Macroeconomic forecasting using penalized regression methods. (2018). Smeekes, Stephan ; Wijler, Etienne.
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    RePEc:eee:intfor:v:34:y:2018:i:3:p:408-430.

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  32. Nowcasting Canadian Economic Activity in an Uncertain Environment. (2018). Chernis, Tony ; Sekkel, Rodrigo.
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  33. A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?. (2017). Corona, Francisco ; Orraca, Pedro ; Gonzalez-Farias, Graciela.
    In: Latin American Economic Review.
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  34. Directed Graphs and Variable Selection in Large Vector Autoregressive Models. (2017). Kascha, Christian ; Bruggemann, Ralf .
    In: Working Paper Series of the Department of Economics, University of Konstanz.
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  35. A Unified Framework for Dimension Reduction in Forecasting. (2017). Bura, Efstathia ; Barbarino, Alessandro .
    In: Finance and Economics Discussion Series.
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  36. Forecasting inflation in emerging markets: An evaluation of alternative models. (2017). Mandalinci, Zeyyad.
    In: International Journal of Forecasting.
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  37. Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals. (2017). Duangnate, Kannika ; Mjelde, James W.
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  38. Macroeconomic Forecasting Using Penalized Regression Methods. (2016). Smeekes, Stephan ; Wijler, Etienne.
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  39. Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods. (2016). Babikir, Ali ; Mwambi, Henry.
    In: Empirical Economics.
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  40. Dynamic Factor model with infinite dimensional factor space: forecasting. (2016). Soccorsi, Stefano ; Lippi, Marco ; Giovannelli, Alessandro ; Forni, Mario.
    In: Center for Economic Research (RECent).
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  41. Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics. (2016). Stock, J H ; Watson, M W.
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  42. Commodities common factor: An empirical assessment of the markets drivers. (2016). Posch, Peter N ; Lubbers, Johannes .
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  43. Real-time factor model forecasting and the effects of instability. (2016). Clements, Michael.
    In: Computational Statistics & Data Analysis.
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  44. Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting. (2016). Soccorsi, Stefano ; Lippi, Marco ; Giovannelli, Alessandro ; Forni, Mario.
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  45. Economic Growth and Business Cycle Forecasting at the Regional Level. (2016). Lehmann, Robert.
    In: ifo Beiträge zur Wirtschaftsforschung.
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  46. Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods. (2015). Naser, Hanan.
    In: Empirical Economics.
    RePEc:spr:empeco:v:49:y:2015:i:2:p:449-479.

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  47. Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models. (2015). Mandalinci, Zeyyad.
    In: CReMFi Discussion Papers.
    RePEc:qmm:wpaper:3.

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  48. Forecasting Turkish Industrial Production Growth With Static Factor Models. (2015). Gunay, Mahmut.
    In: International Econometric Review (IER).
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  49. Housing Market Forecasting with Factor Combinations. (2015). Rahal, Charles .
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  50. House Price Forecasts with Factor Combinations. (2015). Rahal, Charles .
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  51. Analyzing business and financial cycles using multi-level factor models. (2014). Eickmeier, Sandra ; Breitung, Jörg.
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  52. Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?. (2014). Wohlrabe, Klaus ; Lehmann, Robert.
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  53. Analyzing business and financial cycles using multi-level factor models. (2014). Eickmeier, Sandra ; Breitung, Jörg.
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  54. Forecasting with factor-augmented error correction models. (2014). Masten, Igor ; Marcellino, Massimiliano ; Banerjee, Anindya.
    In: International Journal of Forecasting.
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  55. Forecasting with approximate dynamic factor models: The role of non-pervasive shocks. (2014). Luciani, Matteo.
    In: International Journal of Forecasting.
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  56. Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?. (2014). Kristensen, Johannes ; Tang, Kristensen Johannes .
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  57. Forecasting GDP at the regional level with many predictors. (2013). Wohlrabe, Klaus ; Lehmann, Robert.
    In: ERSA conference papers.
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  58. Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets. (2013). Reijer, Ard.
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  59. A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets. (2013). GUO-FITOUSSI, Liang .
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  60. Sectoral gross value-added forecasts at the regional level: Is there any information gain?. (2013). Wohlrabe, Klaus ; Lehmann, Robert.
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  61. Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview. (2013). Kitov, Oleg ; Hendry, David ; Castle, Jennifer.
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  62. Forecasting GDP at the regional level with many predictors. (2013). Wohlrabe, Klaus ; Lehmann, Robert.
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  63. Consistent Factor Estimation in Dynamic Factor Models with Structural Instability. (2013). Watson, Mark ; Plagborg-Mller, Mikkel ; Bates, Brandon J ; Stock, James H.
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  64. Dynamic factor models: A review of the literature. (2013). Barhoumi, Karim ; Ferrara, Laurent ; Darné, Olivier.
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  66. Consistent factor estimation in dynamic factor models with structural instability. (2013). Watson, Mark ; Plagborg-Moller, Mikkel ; Bates, Brandon J. ; Stock, James H..
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  67. Variable Selection in Predictive Regressions. (2013). Ng, Serena.
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  68. Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?. (2013). Wohlrabe, Klaus ; Lehmann, Robert.
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  72. Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies. (2012). Giovannelli, Alessandro.
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  73. Disentangling the Channels of the 2007-2009 Recession. (2012). Watson, Mark ; Stock, James.
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  74. Nowcasting German GDP: A comparison of bridge and factor models. (2012). Barhoumi, Karim ; Darné, Olivier ; Antipa, Pamfili ; Brunhes-Lesage, Veronique ; Darne, Olivier.
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  79. Disentangling the Channels of the 2007-09 Recession. (2012). Stock, James H. ; Watson, Mark W..
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  80. Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?. (2012). Kristensen, Johannes.
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  81. Classical time-varying FAVAR models - estimation, forecasting and structural analysis. (2011). Marcellino, Massimiliano ; Lemke, Wolfgang ; Eickmeier, Sandra.
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  84. Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP. (2011). Schumacher, Christian.
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  86. Forecasting national activity using lots of international predictors: An application to New Zealand. (2011). Ng, Tim ; Eickmeier, Sandra.
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  91. Financial Conditions Index: Early and Leading Indicator for Colombia?. (2011). Murcia, Andrés ; Pabon, Andres Murcia ; Gomez, Nancy Zamudio .
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    In: Discussion Paper Series 1: Economic Studies.
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  40. Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model. (2005). Eickmeier, Sandra.
    In: Discussion Paper Series 1: Economic Studies.
    RePEc:zbw:bubdp1:2936.

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  41. Shock Identification of Macroeconomic Forecasts based on Daily Panels. (2005). Fischer, Andreas ; Amstad, Marlene.
    In: Working Papers.
    RePEc:szg:worpap:0502.

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  42. Principal components at work: the empirical analysis of monetary policy with large data sets. (2005). Marcellino, Massimiliano ; Favero, Carlo ; Neglia, Francesca.
    In: Journal of Applied Econometrics.
    RePEc:jae:japmet:v:20:y:2005:i:5:p:603-620.

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  43. Time-varying pass-through from import prices to consumer prices: evidence from an event study with real-time data. (2005). Fischer, Andreas ; Amstad, Marlene.
    In: Staff Reports.
    RePEc:fip:fednsr:228.

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  44. Shock identification of macroeconomic forecasts based on daily panels. (2005). Fischer, Andreas ; Amstad, Marlene.
    In: Staff Reports.
    RePEc:fip:fednsr:206.

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  45. Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases. (2005). Reichlin, Lucrezia ; Giannone, Domenico ; Small, David .
    In: Finance and Economics Discussion Series.
    RePEc:fip:fedgfe:2005-42.

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  46. Forecasting Dutch GDP using Large Scale Factor Models. (2005). Reijer, Ard.
    In: DNB Working Papers.
    RePEc:dnb:dnbwpp:028.

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  47. Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases. (2005). Reichlin, Lucrezia ; Giannone, Domenico ; Small, David .
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:5178.

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  48. Shock Identification of Macroeconomic Forecasts Based on Daily Panels. (2005). Fischer, Andreas ; Amstad, Marlene.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:5008.

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  49. Forecasting Austrian GDP using the generalized dynamic factor model.. (2004). Schneider, Martin ; Scneider, Martin.
    In: Working Papers.
    RePEc:onb:oenbwp:89.

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  50. Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? / Die Schätzung von großen Faktormodellen für die deutsche Volkswirtschaft: Übertreffen si. (2004). Schumacher, Christian ; Dreger, Christian.
    In: Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).
    RePEc:jns:jbstat:v:224:y:2004:i:6:p:731-750.

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  51. Aggregation bias in macro models: does it matter foir the euro area?. (2004). Monteforte, Libero.
    In: Temi di discussione (Economic working papers).
    RePEc:bdi:wptemi:td_534_04.

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  52. The business cycle of European countries Bayesian clustering of country - individual IP growth series. (2003). Kaufmann, Sylvia.
    In: Working Papers.
    RePEc:onb:oenbwp:83.

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  53. Dating the Euro Area Business Cycle. (2003). Proietti, Tommaso ; Marcellino, Massimiliano ; artis, michael.
    In: Working Papers.
    RePEc:igi:igierp:237.

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  54. US, Japan and the euro area: comparing business-cycle features. (2003). McAdam, Peter.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:2003283.

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  55. Tracking Greenspan: Systematic and Unsystematic Monetary Policy Revisited. (2002). Sala, Luca ; Reichlin, Lucrezia ; Giannone, Domenico.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:3550.

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  56. Principal components at work: The empirical analysis of monetary policy with large datasets. (). Marcellino, Massimiliano ; Favero, Carlo ; Neglia, Francesca.
    In: Working Papers.
    RePEc:igi:igierp:223.

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