Degiannakis, Stavros and Filis, George (2020): Oil price assumptions for macroeconomic policy.
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Abstract
Despite the arguments that are put forward by the literature that oil price forecasts are economically useful, such claim has not been tested to date. In this study we evaluate the economic usefulness of oil price forecasts by means of conditional forecasting of three core macroeconomic indicators that policy makers are predicting, using assumptions about the future path of the oil prices. The chosen indicators are the core inflation rate, industrial production and purchasing price index. We further consider two more indicators, namely inflation expectation and monetary policy uncertainty. To do so, we initially forecast oil prices using a MIDAS framework and subsequently we use regression-based models for our conditional forecasts. Overall, there is diminishing importance of oil price forecasts for macroeconomic projections and policy formulation. An array of arguments is presented as to why this might be the case, which relate to the improved energy efficiency, the contemporary monetary policy tools and the financialisation of the oil market. Our findings remain robust to alternative oil price forecasting frameworks.
Item Type: | MPRA Paper |
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Original Title: | Oil price assumptions for macroeconomic policy |
Language: | English |
Keywords: | Conditional forecasting; oil price forecasts; MIDAS; core inflation; inflation expectations |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E27 - Forecasting and Simulation: Models and Applications E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q47 - Energy Forecasting |
Item ID: | 100705 |
Depositing User: | Dr. Stavros Degiannakis |
Date Deposited: | 28 May 2020 17:25 |
Last Modified: | 28 May 2020 17:25 |
References: | Aguiar‐Conraria, L.U.Í.S. & Wen, Y. (2007). Understanding the large negative impact of oil shocks. Journal of Money, Credit and Banking, 39(4), 925-944. Alquist, R. & Kilian, L. (2010). What do we learn from the price of crude oil futures?. Journal of Applied econometrics, 25(4), 539-573. Alquist, R., Kilian, L. & Vigfusson, R.J. (2013). Forecasting the price of oil. Handbook of Economic Forecasting, 2, 427-507. Andersen, T. G. & Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economic Review, 885-905. Andersen, T., Dobrev, D. & Schaumburg, E. (2012). Jump-Robust Volatility Estimation Using Nearest Neighbor Truncation. Journal of Econometrics, 169(1), 75-93. Andreou, E., Ghysels, E. & Kourtellos, A. (2010). Regression models with mixed sampling frequencies. Journal of Econometrics, 158(2), 246-261. Andreou, E., Ghysels, E. & Kourtellos, A. (2013). Should macroeconomic forecasters use daily financial data and how? Journal of Business & Economic Statistics, 31(2), 240-251. Antonakakis, N., Chatziantoniou, I. & Filis, G. (2014). Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Economics, 44, 433-447. Bachmeier, L. J. & Cha, I. (2011). Why don’t oil shocks cause inflation? Evidence from disaggregate inflation data. Journal of Money, Credit and Banking, 43(6), 1165-1183. Backus, D. K. & Crucini, M. J. (2000). Oil prices and the terms of trade. Journal of International Economics, 50(1), 185-213. Baker, S. R., Bloom, N. & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. Bańbura, M., Giannone, D. & Lenza, M. (2015). Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections. International Journal of Forecasting, 31(3), 739-756. Barnato, K. (2016). Here’s the key challenge Draghi will face at this week’s ECB meeting, CNBC, 30th May, http://www.cnbc.com/2016/05/30/heres-the-key-challenge-draghi-will-face-at-this-weeks-ecb-meeting.html. Barndorff-Nielsen, O. & Shephard, N. (2004). Power and bipower variation with stochastic volatility and jumps. Journal of Financial Econometrics, 2(1), 1-37. Barndorff-Nielsen, O. & Shephard, N. (2006). Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation. Journal of Financial Econometrics, 4, 1-30. Baumeister, C., Guérin, P. & Kilian, L. (2015). Do high-frequency financial data help forecast oil prices? The MIDAS touch at work. International Journal of Forecasting, 31(2), 238-252. Baumeister, C. & Kilian, L. (2012). Real-time forecasts of the real price of oil. Journal of Business & Economic Statistics, 30(2), 326-336. Baumeister, C. & Kilian, L. (2014). What central bankers need to know about forecasting oil prices. International Economic Review, 55(3), 869-889. Baumeister, C. & Kilian, L. (2015). Forecasting the real price of oil in a changing world: a forecast combination approach. Journal of Business & Economic Statistics, 33(3), 338-351. Baumeister, C., Kilian, L. & Lee, T.K. (2014). Are there gains from pooling real-time oil price forecasts? Energy Economics, 46, S33-S43. Baumeister, C., Kilian, L. & Zhou, X. (2018). Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis. Macroeconomic Dynamics, 22, 562-580. Blair, B.J., Poon, S.H. and Taylor, S.J. (2001). Forecasting S&P100 Volatility: the Incremental Information Content of Implied Volatilities and High Frequency Returns. Journal of Econometrics, 105, 5 -26. Blanchard, O. & Gali, J. (2009). The Macroeconomic Effects of Oil Shocks: Why Are the 2000s So Different from the 1970’s?. In: International Dimensions of Monetary Policy, edited by Jordi Gali and Mark Gertler, pp. 373–428. Chicago: University of Chicago Press. Blas, J. & Kennedy, S. (2016). For Once, Low Oil Prices May Be a Problem for World's Economy, Bloomberg, 2nd February, https://www.bloomberg.com/news/articles/2016-02-02/for-once-low-oil-prices-may-be-a-problem-for-world-s-economy. Bollerslev, T., Tauchen, G. & Zhou, H. (2009). Expected stock returns and variance risk premia. The Review of Financial Studies, 22(11), 4463-4492. Barndorff-Nielsen, O., Kinnebrock, S. & Shephard, N. (2010). Measuring downside risk – Realised semivariance. In: T. Bollerslev, J. Russell and M. Watson (eds) Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle. Oxford University Press. Carr, P. & Wu, L. (2008). Variance risk premiums. The Review of Financial Studies, 22(3), 1311-1341. Ciccarelli, M. & Garcia, J.A. (2009). What drives euro area break-even inflation rates?, European Central Bank working paper series, No. 996. Clark, T.E. & West, K.D. (2007). Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics, 138, 291–311. Coibion, O. & Gorodnichencko, Y. (2015). Is the Phillips curve alive and well after all? Inflation expectation and the missing disinflation. American Economic Journal: Macroeconomics. 7 (1), 197–232. Coimbra, C. & Esteves, P.S. (2004). Oil price assumptions in macroeconomic forecasts: should we follow futures market expectations? OPEC review, 28(2), 87-106. Degiannakis, S. & Filis, G. (2018). Forecasting oil prices: High-frequency financial data are indeed useful. Energy Economics, 76, 388-402. Degiannakis, S., Filis, G., & Arora, V. (2018a). Oil prices and stock markets: a review of the theory and empirical evidence. The Energy Journal, 39(5), 85-130. Degiannakis, S. & Filis, G. (2019). Forecasting European economic policy uncertainty. Scottish Journal of Political Economy, 66(1), 94-114. Degiannakis, S., Filis, G. & Hassani, H. (2018b). Forecasting global stock market implied volatility indices. Journal of Empirical Finance, 46, 111-129. ECB (2015). Economic Bulletin, Issue 4, European Central Bank. https://www.ecb.europa.eu/pub/pdf/other/art03_eb201504.en.pdf?cf0bb5d2a75e31d43e38b3c5d5540273. ECB (2016a). Economic Bulletin, Issue 4, European Central Bank. https://www.ecb.europa.eu/pub/pdf/other/eb201604_focus01.en.pdf?48284774d83e30563e8f5c9a50cd0ea2. ECB (2016b). A guide to the Eurosystem/ECB staff macroeconomic projection exercises, European Central Bank, https://www.ecb.europa.eu/pub/pdf/other/staffprojectionsguide201607.en.pdf. Elder, J. & Serletis, A. (2010). Oil price uncertainty. Journal of Money, Credit and Banking, 42(6), 1137-1159. Gelos, G. & Ustyugova, Y. (2017). Inflation responses to commodity price shocks–How and why do countries differ. Journal of International Money and Finance. 72, 28–47. Ghysels, E., Santa-Clara, P. & Valkanov, R. (2006). Predicting volatility: getting the most out of return data sampled at different frequencies. Journal of Econometrics, 131(1-2), 59-95. Giannone, D., Lenza, M., Momferatoud, D. & Onorante, L. (2014). Short-term inflation projections: A Bayesian vector autoregressive approach. International Journal of Forecasting. 30, 635-644. Güntner, J.H. & Linsbauer, K. (2018). The effects of oil supply and demand shocks on US consumer Sentiment. Journal of Money, Credit and Banking, 50(7), 1617-1644. Hamilton, J. D. (2008). Oil and the macroeconomy, The new Palgrave Dictionary of Economics. Blume (second ed.), Palgrave Macmillan. Hansen, P.R. (2005). A test for superior predictive ability. Journal of Business & Economic Statistics, 23, 365–380. Hansen, P.R. & Lunde, A. (2005). A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data. Journal of Financial Econometrics, 3(4), 525-554. Hooker, M. A. (2002). Are oil shocks inflationary? Asymmetric and nonlinear specifications versus changes in regime. Journal of Money, Credit, and Banking, 34(2), 540–561. IMF (2016). World Economic Outlook – Too slow for too long, International Monetary Fund: Washington DC. Jo, S. (2014). The effects of oil price uncertainty on global real economic activity. Journal of Money, Credit and Banking, 46(6), 1113-1135. Kang, W., de Gracia, F.P. & Ratti, R.A. (2017). Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations. Journal of International Money and Finance, 70, 344-359. Kilian, L., Rebucci, A. & Spatafora, N. (2009). Oil shocks and external balances. Journal of International Economics, 77(2), 181-194. Kilian, L. & Vigfusson, R.J. (2013). Do oil prices help forecast US real GDP? The role of nonlinearities and asymmetries. Journal of Business & Economic Statistics, 31(1), 78-93. Kilian, L. & Vigfusson, R.J. (2017). The role of oil price shocks in causing US recessions. Journal of Money, Credit and Banking, 49(8), 1747-1776. Koopman, S.J., Jungbacker, B. and Hol, E. (2005). Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements. Journal of Empirical Finance, 12(3), 445-475. Le Pen, Y., & Sévi, B. (2018). Futures trading and the excess co-movement of commodity prices. Review of Finance, 22(1), 381-418. Marcellino, M., Stock, J.H. & Watson, M.W. (2003). Macroeconomic forecasting in the euro area: Country specific versus area-wide information. European Economic Review, 47(1), 1-18. Martens, M. (2002). Measuring and forecasting S&P 500 index‐futures volatility using high‐frequency data. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 22(6), 497-518. Natal, J. (2012). Monetary policy response to oil price shocks. Journal of Money, Credit and Banking, 44(1), 53-101. Naser, H. (2016). Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach. Energy Economics, 56, 75-87. Patton, A.J. & Sheppard, K. (2015). Good volatility, bad volatility: signed jumps and the persistence of volatility. The Review of Economics and Statistics, 97(3), 683-697. Prokopczuk, M., Symeonidis, L. & Simen, C.W. (2017). Variance risk in commodity markets. Journal of Banking & Finance, 81, 136-149. Ravazzolo, F. & Rothman, P. (2013). Oil and US GDP: A Real‐Time Out‐of‐Sample Examination. Journal of Money, Credit and Banking, 45(2‐3), 449-463. Renou-Maissant, P. (2019). Is oil price still driving inflation?. The Energy Journal, 40(6), 199-219. Tang, K., & Xiong, W. (2012). Index investment and the financialization of commodities. Financial Analysts Journal, 68(6), 54-74. Tee, C. W. & Ting, C. (2017). Variance risk premiums of commodity ETFs. Journal of Futures Markets, 37(5), 452-472. Theodosiou, M. and Zikes, F. (2009). A comprehensive comparison of alternative tests for jumps in asset prices. Imperial College London. White, H. (2000). A reality check for data snooping. Econometrica, 68, 1097–1126. Zhang, Y., Ma, F., Shi, B. & Huang, D. (2018). Forecasting the prices of crude oil: An iterated combination approach. Energy Economics, 70, 472-483. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/100705 |