Why calculate a business sentiment indicator for services?
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
- Nijman, T E & Palm, F C, 1986.
"The Construction and Use of Approximations for Missing Quarterly Observations: A Model-based Approach,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 47-58, January.
- Nijman, T.E. & Palm, F.C., 1985. "The construction and use of approximations for missing quarterly observations : A model-based approach," Other publications TiSEM 22310454-d7c0-4639-b9a7-5, Tilburg University, School of Economics and Management.
- Angelini, Elena & Henry, Jerome & Marcellino, Massimiliano, 2006.
"Interpolation and backdating with a large information set,"
Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2693-2724, December.
- Angelini, Elena & Henry, Jérôme & Marcellino, Massimiliano, 2003. "Interpolation and backdating with a large information set," Working Paper Series 252, European Central Bank.
- Henry, Jerome & Marcellino, Massimiliano & Angelini, Elena, 2004. "Interpolation and Backdating with A Large Information Set," CEPR Discussion Papers 4533, C.E.P.R. Discussion Papers.
- Gomez, Victor & Maravall, Agustin & Pena, Daniel, 1998. "Missing observations in ARIMA models: Skipping approach versus additive outlier approach," Journal of Econometrics, Elsevier, vol. 88(2), pages 341-363, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Claudia Foroni & Massimiliano Marcellino, 2013.
"A survey of econometric methods for mixed-frequency data,"
Economics Working Papers
ECO2013/02, European University Institute.
- Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
- Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011.
"U-MIDAS: MIDAS regressions with unrestricted lag polynomials,"
Discussion Paper Series 1: Economic Studies
2011,35, Deutsche Bundesbank.
- Schumacher, Christian & Marcellino, Massimiliano & Foroni, Claudia, 2012. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," CEPR Discussion Papers 8828, C.E.P.R. Discussion Papers.
- Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
- Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Troy D. Matheson, 2014.
"New indicators for tracking growth in real time,"
OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 51-71.
- Mr. Troy D Matheson, 2011. "New Indicators for Tracking Growth in Real Time," IMF Working Papers 2011/043, International Monetary Fund.
- Marcellino, Massimiliano & Schumacher, Christian, 2007.
"Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP,"
Discussion Paper Series 1: Economic Studies
2007,34, Deutsche Bundesbank.
- Schumacher, Christian & Marcellino, Massimiliano, 2008. "Factor-MIDAS for now- and forecasting with ragged-edge data: A model comparison for German GDP," CEPR Discussion Papers 6708, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute.
- Massimiliano Marcellino, 2007.
"Pooling‐Based Data Interpolation and Backdating,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 28(1), pages 53-71, January.
- Marcellino, Massimiliano, 2005. "Pooling-based data interpolation and backdating," CEPR Discussion Papers 5295, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino, 2005. "Pooling-based Data Interpolation and Backdating," Working Papers 299, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
- Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
- Tommaso Proietti & Alessandro Giovannelli, 2021.
"Nowcasting monthly GDP with big data: A model averaging approach,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
- Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
- Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
- Angelini, Elena & Henry, Jerome & Marcellino, Massimiliano, 2006.
"Interpolation and backdating with a large information set,"
Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2693-2724, December.
- Angelini, Elena & Henry, Jérôme & Marcellino, Massimiliano, 2003. "Interpolation and backdating with a large information set," Working Paper Series 252, European Central Bank.
- Henry, Jerome & Marcellino, Massimiliano & Angelini, Elena, 2004. "Interpolation and Backdating with A Large Information Set," CEPR Discussion Papers 4533, C.E.P.R. Discussion Papers.
- Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
- Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
- Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
- Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
- Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020.
"Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
- Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economics Research Papers 2019-006, Friedrich-Schiller-University Jena.
- Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012.
"Short-run forecasting of the euro-dollar exchange rate with economic fundamentals,"
Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
- Marcos dal Bianco & Maximo Camacho & Gabriel Perez-Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1203, Banco de España.
- Maximo Camacho & Marcos Dal Bianco & Gabriel Perez Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1201, BBVA Bank, Economic Research Department.
- Gabriele Fiorentini & Alessandro Galesi & Gabriel Pérez-Quirós & Enrique Sentana, 2018.
"The rise and fall of the natural interest rate,"
Working Papers
1822, Banco de España.
- Gabriele Fiorentini & Alessandro Galesi & Gabriel Pérez-Quirós & Enrique Sentana, 2018. "The Rise and Fall of the Natural Interest Rate," Working Paper series 18-29, Rimini Centre for Economic Analysis.
- Gabriele Fiorentini & Alessandro Galesi & Gabriel Pérez-Quirós & Enrique Sentana, 2018. "The Rise and Fall of the Natural Interest Rate," Working Papers wp2018_1805, CEMFI.
- Gabriele Fiorentini & Alessandro Galesi & Gabriel Pérez-Quirós & Enrique Sentana, 2018. "The Rise and Fall of the Natural Interest Rate," Working Papers - Economics wp2018_14.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Pérez-Quirós, Gabriel & Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "The Rise and Fall of the Natural Interest Rate," CEPR Discussion Papers 13042, C.E.P.R. Discussion Papers.
- Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
More about this item
Keywords
business conditions analysis; survey data; services; interpolation; principal components.;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bfr:quarte:2008:13:02. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael brassart (email available below). General contact details of provider: https://edirc.repec.org/data/bdfgvfr.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.