FRED-SD: A Real-Time Database for State-Level Data with Forecasting Applications
Author
Abstract
Suggested Citation
DOI: 10.20955/wp.2020.031
Download full text from publisher
Other versions of this item:
- Bokun, Kathryn O. & Jackson, Laura E. & Kliesen, Kevin L. & Owyang, Michael T., 2023. "FRED-SD: A real-time database for state-level data with forecasting applications," International Journal of Forecasting, Elsevier, vol. 39(1), pages 279-297.
References listed on IDEAS
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005.
"The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting,"
Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
- Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario, 2002. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," CEPR Discussion Papers 3432, C.E.P.R. Discussion Papers.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Forni M. & Hallin M., 2003. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Computing in Economics and Finance 2003 143, Society for Computational Economics.
- Brayton, Flint & Levin, Andrew & Lyon, Ralph & Williams, John C., 1997.
"The evolution of macro models at the Federal Reserve Board,"
Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 43-81, December.
- Flint Brayton & Andrew T. Levin & Ralph W. Tryon & John C. Williams, "undated". "The Evolution of Macro Models at the Federal Reserve Board," Finance and Economics Discussion Series 1997-29, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
- Smith, Stephen M. & Gibson, Cosette M., 1988. "Industrial Diversification In Nonmetropolitan Counties And Its Effect On Economic Stability," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(2), pages 1-9, December.
- Marta Bańbura, 2008.
"Large Bayesian VARs,"
2008 Meeting Papers
334, Society for Economic Dynamics.
- Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta, 2008. "Large Bayesian VARs," Working Paper Series 966, European Central Bank.
- Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
- Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
- LeSage, James P. & Magura, Michael, 1988. "A Regional Payroll Forecasting Model That Uses Bayesian Shrinkage Techniques for Data Pooling," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 18(1), pages 1-17.
- Croushore, Dean & Stark, Tom, 2001.
"A real-time data set for macroeconomists,"
Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
- Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2015.
"Forecasting National Recessions Using State‐Level Data,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(5), pages 847-866, August.
- Michael T. Owyang & Jeremy M. Piger & Howard J. Wall, 2012. "Forecasting national recessions using state level data," Working Papers 2012-013, Federal Reserve Bank of St. Louis.
- Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2012. "Forecasting national recessions using state-level data," MPRA Paper 39168, University Library of Munich, Germany.
- Jon R. Miller, 1998. "original: Spatial aggregation and regional economic forecasting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 32(2), pages 253-266.
- Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010.
"Large Bayesian vector auto regressions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
- Marta Bańbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92, January.
- Domenico Giannone & Martha Banbura & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," ULB Institutional Repository 2013/13388, ULB -- Universite Libre de Bruxelles.
- Robert Lehmann & Klaus Wohlrabe, 2014.
"Regional economic forecasting: state-of-the-art methodology and future challenges,"
Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.
- Robert Lehmann & Klaus Wohlrabe, 2014. "Regional Economic Forecasting: State-of-the-Art Methodology and Future Challenge," CESifo Working Paper Series 5145, CESifo.
- Bernanke, Ben S. & Boivin, Jean, 2003.
"Monetary policy in a data-rich environment,"
Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
- Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
- Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
- Laura E. Jackson & Kevin L. Kliesen & Michael T. Owyang, 2015. "A Measure of Price Pressures," Review, Federal Reserve Bank of St. Louis, vol. 97(1), pages 25-52.
- Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003.
"Macroeconomic forecasting in the Euro area: Country specific versus area-wide information,"
European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
- Massimiliano Marcellino & James H. Stock & Mark W. Watson, "undated". "Macroeconomic Forecasting in the Euro Area: Country Specific versus Area-Wide Information," Working Papers 201, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015.
"Prior Selection for Vector Autoregressions,"
The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
- Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
- Jean Boivin & Serena Ng, 2005.
"Understanding and Comparing Factor-Based Forecasts,"
International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
- Boivin, Jean & Ng, Serena, 2005. "Understanding and Comparing Factor-Based Forecasts," MPRA Paper 836, University Library of Munich, Germany.
- Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
- Giacomini, Raffaella & Granger, Clive W. J., 2004.
"Aggregation of space-time processes,"
Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
- Giacomini, Raffaella & Granger, Clive W.J., 2001. "Aggregationn of Space-Time Processes," University of California at San Diego, Economics Working Paper Series qt77f76455, Department of Economics, UC San Diego.
- Raffaella Giacomini & Clive W.J. Granger, 2002. "Aggregation of Space-Time Processes," Boston College Working Papers in Economics 582, Boston College Department of Economics.
- Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010.
"Large Bayesian vector auto regressions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
- Reichlin, Lucrezia & Giannone, Domenico & Banbura, Marta, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
- Domenico Giannone & Martha Banbura & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," ULB Institutional Repository 2013/13388, ULB -- Universite Libre de Bruxelles.
- Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
- Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
- James P. LeSage & Zheng Pan, 1995. "Using Spatial Contiguity as Bayesian Prior Information in Regional Forecasting Models," International Regional Science Review, , vol. 18(1), pages 33-53, January.
- Stock, James H & Watson, Mark W, 1996.
"Evidence on Structural Instability in Macroeconomic Time Series Relations,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
- James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
- James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- David E. Rapach & Jack K. Strauss, 2005. "Forecasting employment growth in Missouri with many potentially relevant predictors: an analysis of forecast combining methods," Regional Economic Development, Federal Reserve Bank of St. Louis, issue Nov, pages 97-112.
- Hernandez-Murillo, Ruben & Owyang, Michael T., 2006.
"The information content of regional employment data for forecasting aggregate conditions,"
Economics Letters, Elsevier, vol. 90(3), pages 335-339, March.
- Ruben Hernandez-Murillo & Michael T. Owyang, 2004. "The information content of regional employment data for forecasting aggregate conditions," Working Papers 2004-005, Federal Reserve Bank of St. Louis.
- James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
- Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
- Theodore M. Crone & Alan Clayton-Matthews, 2005. "Consistent Economic Indexes for the 50 States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 593-603, November.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Lehmann, Robert & Wikman, Ida, 2022.
"Quarterly GDP Estimates for the German States,"
MPRA Paper
112642, University Library of Munich, Germany.
- Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Robert Lehmann & Ida Wikman, 2023. "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series 10280, CESifo.
- Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
- Emanuele Bacchiocchi & Andrea Bastianin & Graziano Moramarco, 2024. "Macroeconomic Spillovers of Weather Shocks across U.S. States," Papers 2403.10907, arXiv.org, revised Apr 2024.
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.- Luciani, Matteo, 2014.
"Forecasting with approximate dynamic factor models: The role of non-pervasive shocks,"
International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
- Matteo Luciani, 2011. "Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks," Working Papers ECARES ECARES 2011‐022, ULB -- Universite Libre de Bruxelles.
- Smeekes, Stephan & Wijler, Etienne, 2018.
"Macroeconomic forecasting using penalized regression methods,"
International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
- Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
- Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021.
"Macroeconomic data transformations matter,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
- Helmut Lütkepohl, 2014.
"Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey,"
Discussion Papers of DIW Berlin
1351, DIW Berlin, German Institute for Economic Research.
- Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," SFB 649 Discussion Papers SFB649DP2014-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014.
"Using large data sets to forecast sectoral employment,"
Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller & Josine Uwilingiye, 2011. "Using Large Data Sets to Forecast Sectoral Employment," Working Papers 201101, University of Pretoria, Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller & Josine Uwilingiye, 2011. "Using Large Data Sets to Forecast Sectoral Employment," Working papers 2011-02, University of Connecticut, Department of Economics, revised Aug 2012.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller & Josine Uwilingiye, 2011. "Using Large Data Sets to Forecast Sectoral Employment," Working Papers 1106, University of Nevada, Las Vegas , Department of Economics.
- Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011.
"Forecasting the US real house price index: Structural and non-structural models with and without fundamentals,"
Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 200927, University of Pretoria, Department of Economics.
- Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2010. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
- Michael Pfarrhofer, 2024.
"Forecasts with Bayesian vector autoregressions under real time conditions,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
- Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.
- Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
- Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019.
"Macroeconomic forecast accuracy in a data‐rich environment,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
- Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
- Raffaella Giacomini & Barbara Rossi, 2015.
"Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models,"
Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.
- Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
- Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
- Forni, Mario & Gambetti, Luca, 2010.
"The dynamic effects of monetary policy: A structural factor model approach,"
Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
- Forni, Mario & Gambetti, Luca, 2008. "The Dynamic Effects of Monetary Policy: A Structural Factor Model Approach," CEPR Discussion Papers 7098, C.E.P.R. Discussion Papers.
- Mario Forni & Luca Gambetti, 2008. "The dynamic e ects of monetary policy: A structural factor model approach," Center for Economic Research (RECent) 026, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
- Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023.
"Big data forecasting of South African inflation,"
Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
- Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
- Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
- Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
- Bork, Lasse, 2009.
"Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach,"
Finance Research Group Working Papers
F-2009-03, University of Aarhus, Aarhus School of Business, Department of Business Studies.
- Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.
- Matteo Luciani, 2015.
"Monetary Policy and the Housing Market: A Structural Factor Analysis,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
- Matteo LUCIANI, "undated". "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers wp2010-7, Department of the Treasury, Ministry of the Economy and of Finance.
- Matteo Luciani, 2012. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers ECARES ECARES 2012-035, ULB -- Universite Libre de Bruxelles.
- Matteo Luciani, 2013. "Monetary Policy, and the Housing Market: A Structural Factor Analysis," ULB Institutional Repository 2013/153324, ULB -- Universite Libre de Bruxelles.
- Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017.
"The role of indicator selection in nowcasting euro-area GDP in pseudo-real time,"
Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
- A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
- Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008.
"Nowcasting: The real-time informational content of macroeconomic data,"
Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
- Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
- Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
- Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series 633, European Central Bank.
- Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
- Raul Ibarra & Luis M. Gomez-Zamudio, 2017.
"Are Daily Financial Data Useful for Forecasting GDP? Evidence from Mexico,"
Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 173-203, April.
- Ibarra-Ramírez Raúl & Gómez-Zamudio Luis M., 2017. "Are daily financial data useful for forecasting GDP? Evidence from Mexico," Working Papers 2017-17, Banco de México.
- Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
More about this item
Keywords
factor models; Bayesian VARs; space-time autoregression;All these keywords.
JEL classification:
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
NEP fields
This paper has been announced in the following NEP Reports:- NEP-FOR-2020-10-05 (Forecasting)
- NEP-GEO-2020-10-05 (Economic Geography)
- NEP-URE-2020-10-05 (Urban and Real Estate Economics)
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:fip:fedlwp:88720. 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: Anna Oates (email available below). General contact details of provider: https://edirc.repec.org/data/frbslus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.