Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data
Is the relationship between energy and agricultural commodities an important factor in the increasing price variability of food commodities? Findings from the literature appear to be mixed and highly influenced by the data frequency used in those analysis. A recurrent task in time series applied work is to match up data at different frequencies, while macroeconomic variables are often found at monthly or quarterly observations, financial variables are sampled daily or even at higher frequencies. In order to match up time series at different frequencies a common procedure is to aggregate the higher frequency to fit in the low frequency, this has the potential of losing valuable information, and generating misspecification. We study whether the use of mixed frequency estimations with data for the 2006-2011 period helps to improve the out of sample performance of a model that explains grain prices as a function of energy prices, macroeconomic variables such as exchange rate, interest rate, and inflation. Preliminary results suggest that an improvement is feasible, however it is tenuous beyond two months horizons.
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- Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 521-536.
- Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
- Frank Schorfheide & Dongho Song, 2015.
"Real-Time Forecasting With a Mixed-Frequency VAR,"
Journal of Business & Economic Statistics,
Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
- Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.
- Frank Schorfheide & Dongho Song, 2013. "Real-Time Forecasting with a Mixed-Frequency VAR," NBER Working Papers 19712, National Bureau of Economic Research, Inc.
- 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.
- 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.
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
- Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
- Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
- Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
- Vacha, Lukas & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2013. "Time–frequency dynamics of biofuel–fuel–food system," Energy Economics, Elsevier, vol. 40(C), pages 233-241.
- Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
- Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilbermand, 2013. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," CAMA Working Papers 2013-27, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- 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, Research Centre.
- Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2012. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," CEPR Discussion Papers 8828, C.E.P.R. Discussion Papers.
- Teresa Serra & David Zilberman & José M. Gil & Barry K. Goodwin, 2011. "Nonlinearities in the U.S. corn‐ethanol‐oil‐gasoline price system," Agricultural Economics, International Association of Agricultural Economists, vol. 42(1), pages 35-45, 01.
- Marco Lombardi & Chiara Osbat & Bernd Schnatz, 2012. "Global commodity cycles and linkages: a FAVAR approach," Empirical Economics, Springer, vol. 43(2), pages 651-670, October.
- Lombardi, Marco J. & Osbat, Chiara & Schnatz, Bernd, 2010. "Global commodity cycles and linkages a FAVAR approach," Working Paper Series 1170, European Central Bank.
- Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
- Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
- Ching Wai (Jeremy) Chiu & Bjørn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.
- Berna Karali & Gabriel J. Power, 2013. "Short- and Long-Run Determinants of Commodity Price Volatility," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(3), pages 724-738.
- Qian, Hang, 2010. "Vector autoregression with varied frequency data," MPRA Paper 34682, University Library of Munich, Germany. Full references (including those not matched with items on IDEAS)
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