IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model

  • Chevallier, Julien

This article assesses the transmission of international shocks to EUA spot, EUA futures, and CER futures carbon prices using a broad dataset that includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 to January 25, 2010 totalling 463 observations. The framework adopted is a Factor-Augmented Vector Autoregression model with latent factors extracted from the dataset, as proposed by Bernanke et al. (2005). The main results can be summarized as follows. First, based on impulse responses, we show that carbon prices tend to respond negatively (between -Â 0.2 and -Â 1.2 standard deviation) to an exogenous shock that reduces global economic indicators by one standard deviation. Second, we find evidence that the responses are heterogeneous among the different kinds of carbon prices: CER futures prices tend to react much more significantly than EUA spot and futures prices. Third, the factors explain about 50% of the total variance of all variables in the dataset. The largest contribution is accounted for by the factor correlated with commodities markets, which explains about 28% of the total variability.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/B6VB1-50NY2WT-2/2/0133dd811359f07bffd509177604300c
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal Economic Modelling.

Volume (Year): 28 (2011)
Issue (Month): 1-2 (January)
Pages: 557-567

as
in new window

Handle: RePEc:eee:ecmode:v:28:y:2011:i:1-2:p:557-567
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/30411

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2007. "Opening the black box: structural factor models with large cross-sections," Working Paper Series 0712, European Central Bank.
  2. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
  3. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
  4. Ben S. Bernanke & Ilian Mihov, 1995. "Measuring Monetary Policy," NBER Working Papers 5145, National Bureau of Economic Research, Inc.
  5. Jean Boivin & Michael T. Kiley & Frederic S. Mishkin, 2010. "How has the monetary transmission mechanism evolved over time?," Finance and Economics Discussion Series 2010-26, Board of Governors of the Federal Reserve System (U.S.).
  6. 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.
  7. repec:wbk:wboper:13403 is not listed on IDEAS
  8. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
  9. Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2009. "The Determinants of Stock and Bond Return Comovements," NBER Working Papers 15260, National Bureau of Economic Research, Inc.
  10. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1997. "Monetary policy shocks: what have we learned and to what end?," Working Paper Series, Macroeconomic Issues WP-97-18, Federal Reserve Bank of Chicago.
  11. Marc Hallin & Mario Forni & Marco Lippi & Lucrezia Reichlin, 2003. "Do financial variables help forecasting inflation and real activity in the Euro area ?," ULB Institutional Repository 2013/2123, ULB -- Universite Libre de Bruxelles.
  12. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2002. "VARs, Common Factors and the Empirical Validation of Equilibrium Business Cycle Models," CEPR Discussion Papers 3701, C.E.P.R. Discussion Papers.
  13. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
  14. Lucrezia Reichlin & Domenico Giannone & Luca Sala, . "Monetary policy in real time," ULB Institutional Repository 2013/10177, ULB -- Universite Libre de Bruxelles.
    • Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
  15. Rangan Gupta & Marius Jurgilas & Alain Kabundi, 2009. "The Effect Of Monetary Policy On Real House Price Growth In South Africa: A Factor Augmented Vector Autoregression (Favar) Approach," Working Papers 200905, University of Pretoria, Department of Economics.
  16. Jushan Bai & Serena Ng, 2004. "Evaluating Latent and Observed Factors in Macroeconomics and Financ," Econometrics 0408007, EconWPA.
  17. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  18. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
  19. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  20. Jean Boivin & Marc Giannoni, 2008. "Global Forces and Monetary Policy Effectiveness," NBER Working Papers 13736, National Bureau of Economic Research, Inc.
  21. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
  22. Jean Boivin & Marc P. Giannoni & Benoît Mojon, 2008. "How Has the Euro Changed the Monetary Transmission?," NBER Working Papers 14190, National Bureau of Economic Research, Inc.
  23. 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.
  24. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
  25. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  26. Zagaglia, Paolo, 2010. "Macroeconomic factors and oil futures prices: A data-rich model," Energy Economics, Elsevier, vol. 32(2), pages 409-417, March.
  27. Mönch, Emanuel, 2005. "Forecasting the yield curve in a data-rich environment: a no-arbitrage factor-augmented VAR approach," Working Paper Series 0544, European Central Bank.
  28. Ben Bernanke & Jean Boivin & Piotr S. Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, MIT Press, vol. 120(1), pages 387-422, January.
  29. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
  30. Sydeny C. Ludvigson & Serena Ng, 2005. "Macro Factors in Bond Risk Premia," NBER Working Papers 11703, National Bureau of Economic Research, Inc.
  31. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2009. "Estimation and forecasting in large datasets with conditionally heteroskedastic dynamic common factors," Working Paper Series 1115, European Central Bank.
  32. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  33. Ke Tang & Wei Xiong, 2010. "Index Investment and Financialization of Commodities," NBER Working Papers 16385, National Bureau of Economic Research, Inc.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:28:y:2011:i:1-2:p:557-567. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.