Weather-adjusting employment data
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005.
"There is a risk-return trade-off after all,"
Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2003. "There is a Risk-Return Tradeoff After All," CIRANO Working Papers 2003s-26, CIRANO.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "There is a Risk-Return Tradeoff After All," NBER Working Papers 10913, National Bureau of Economic Research, Inc.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "There is a Risk-Return Tradeoff After All," CIRANO Working Papers 2004s-24, CIRANO.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2012. "Temperature Shocks and Economic Growth: Evidence from the Last Half Century," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(3), pages 66-95, July.
- Andreou, Elena & Ghysels, Eric & Kourtellos, Andros, 2010.
"Regression models with mixed sampling frequencies,"
Journal of Econometrics, Elsevier, vol. 158(2), pages 246-261, October.
- Elena Andreou, Eric Ghysels & Eric Ghysels & Andros Kourtellos, 2007. "Regression Models with Mixed Sampling Frequencies," University of Cyprus Working Papers in Economics 8-2007, University of Cyprus Department of Economics.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Christopher L. Foote, 2015. "Did abnormal weather affect U.S. employment growth in early 2015?," Current Policy Perspectives 15-2, Federal Reserve Bank of Boston.
- Tom Stark, 2015. "First quarters in the national income and product accounts," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue May.
- Charles Fries & Francois Gourio, 2018. "Weather Shocks and Climate Change," 2018 Meeting Papers 1159, Society for Economic Dynamics.
- Erik Haustein & Sven Schreiber, 2016. "Adjusting production indices for varying weather effects," IMK Working Paper 171-2016, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
- Caglar Yunculer, 2015. "Estimating the Bridging Day Effect on Turkish Industrial Production," CBT Research Notes in Economics 1515, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
- Hyunju Kang & Hyunduk Suh & Jongmin Yu, 2019.
"Does Air Pollution Affect Consumption Behavior? Evidence from Korean Retail Sales,"
Asian Economic Journal, East Asian Economic Association, vol. 33(3), pages 235-251, September.
- Hyunju Kang & Hyunduk Suh & Jongmin Yu, 2017. "Does Air Pollution Affect Consumption Behavior? Evidence from Korean Retail Sales," Inha University IBER Working Paper Series 2017-4, Inha University, Institute of Business and Economic Research, revised Apr 2017.
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.- Galvão, Ana Beatriz, 2013.
"Changes in predictive ability with mixed frequency data,"
International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
- Ana Beatriz Galvão, 2007. "Changes in Predictive Ability with Mixed Frequency Data," Working Papers 595, Queen Mary University of London, School of Economics and Finance.
- J. Isaac Miller, 2014.
"Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures,"
Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
- J. Isaac Miller, 2012. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Working Papers 1211, Department of Economics, University of Missouri.
- Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
- Eric Ghysels & J. Isaac Miller, 2015.
"Testing for Cointegration with Temporally Aggregated and Mixed-Frequency Time Series,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 797-816, November.
- Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
- Eric Ghysels & J. Isaac Miller, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," Working Papers 1307, Department of Economics, University of Missouri, revised 07 May 2014.
- Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017.
"Density Forecasts With Midas Models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
- Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
- Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Papers No 3/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011.
"MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area,"
International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542, April.
- Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
- Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," Economics Working Papers ECO2009/32, European University Institute.
- Freitag L., 2014. "Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis," Research Memorandum 038, Maastricht University, Graduate School of Business and Economics (GSBE).
- Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
- Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
- Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
- Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016.
"Testing for Granger causality with mixed frequency data,"
Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
- Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
- Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
- Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
- Marie Bessec, 2019.
"Revisiting the transitional dynamics of business cycle phases with mixed-frequency data,"
Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
- Marie Bessec, 2016. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Working Papers hal-01358595, HAL.
- Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.
- Dufour, Jean-Marie & García, René, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- 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.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- 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.
More about this item
Keywords
Weather; employment data; seasonal adjustment; MIDAS;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
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
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:fedpwp:15-5. 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: Beth Paul (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.