Pincheira, Pablo and Jarsun, Nabil (2020): Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate.
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Abstract
This draft is a summary of the paper entitled: Forecasting Fuel Prices with the Chilean Exchange Rate. In that paper we show that the Chilean exchange rate has the ability to predict the returns of oil prices and of three additional oil-related products: gasoline, propane and heating oil. The theoretical underpinnings of our empirical findings rely on the present-value theory for exchange rate determination and on the strong co-movement displayed by some commodity prices. The Chilean economy is heavily influenced by one particular commodity: copper, which represents nearly 50% of total national exports and attracts a similar share in terms of Foreign Direct Investment. As a consequence, the floating Chilean exchange rate is importantly affected by fluctuations in the copper price. As oil-related products display an important co-movement with base metal prices, it is reasonable to expect evidence of Granger causality from the Chilean peso to these oil-related products. We find substantial evidence of predictability both in-sample and out-of-sample. Our paper is part of a growing literature that in the recent years has explored the linkages between commodity prices and commodity currencies.
Item Type: | MPRA Paper |
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Original Title: | Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate |
English Title: | Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate |
Language: | English |
Keywords: | Exchange rates, energy, oil, gasoline, commodity prices, predictability, time-series |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics C - Mathematical and Quantitative Methods > C5 - Econometric Modeling C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E58 - Central Banks and Their Policies F - International Economics > F3 - International Finance F - International Economics > F3 - International Finance > F31 - Foreign Exchange F - International Economics > F3 - International Finance > F37 - International Finance Forecasting and Simulation: Models and Applications F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F47 - Forecasting and Simulation: Models and Applications G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation |
Item ID: | 105056 |
Depositing User: | Pablo Matías Pincheira |
Date Deposited: | 31 Dec 2020 06:50 |
Last Modified: | 31 Dec 2020 06:50 |
References: | 1. Akram Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31, 838–851. 2. Alquist R. and L. Kilian (2010). What do we learn from the price of crude oil futures? Journal of Applied Econometrics, 25, 539–573. 3. Alquist R., L. Kilian, and R. J. Vigfusson (2013). Forecasting the price of oil. In Handbook of Economic Forecasting, vol. 2, 427-507. 4. Anderson S., R. Kellogg, J. M. Sallee, and R. T. Curtin (2011). Forecasting Gasoline Prices Using Consumer Surveys. American Economic Review, 101:3, 110-14. 5. Baumeister C. and L. Kilian (2012). Real-Time Forecasts of the Real Price of Oil. Journal of Business & Economic Statistics, 30:2, 326-336. 6. Baumeister C. and L. Kilian (2015). Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach. Journal of Business & Economic Statistics, 33:3, 338-351. 7. Baumeister C. and L. Kilian (2016). Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us. Journal of Economic Perspectives, vol. 30:1, 139-160. 8. Baumeister C., L. Kilian, and T. K. Lee (2017). Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump. Journal of Applied Econometrics, 32:2, 275-295. 9. Beckmann J. and R. Czudaj (2013). Is there a homogeneous causality pattern between oil prices and currencies of oil importers and exporters? Energy Economics, 40, 665–678. 10. Beckmann J., R. Czudaj, and V. Arora (2017). The relationship between oil prices and exchange rates: Theory and evidence. US Department of Energy, Working paper series. 11. Belasen A. and R. Demirer (2019). Commodity-currencies or currency-commodities: Evidence from causality tests. Resources Policy, vol. 60 (C), 162-168. 12. Brahmasrene T., J. Huang, and Y. Sissoko (2014). Crude oil prices and exchange rates: Causality, variance decomposition and impulse response. Energy Economics, 44, 407–412. 13. Bützer S., M. Habib, and L. Stracca (2016). Global exchange rate configurations: Do oil shocks matter? IMF Economic Review, 64, 443–470. 14. Campbell J. and R. J. Shiller (1987). Cointegration and Tests of Present Value Models. Journal of Political Economy, 95:5, 1062-1088. 15. Central Bank of Chile (2018). Monetary Policy Report June 2018. 16. Chen Y., K. Rogoff, and B. Rossi (2010). Can exchange rates forecast commodity prices? Quarterly Journal of Economics, 125, 1145–1194. 17. Chen Y., K. Rogoff, and B. Rossi (2014). Can Exchange Rates Forecast Commodity Prices? An Update, manuscript. 18. Clark T. and M. McCracken (2001). Tests of equal forecast accuracy and encompassing for nested models. Journal of Econometrics, 105:1, 85-110. 19. Funk C. (2018). Forecasting the real price of oil - Time-variation and forecast combination. Energy Economics, vol. 76 (C), 288-302. 20. Garratt A., S. Vahey, and Y. Zhang (2019). Real‐time forecast combinations for the oil price. Journal of Applied Econometrics, vol. 34 (3), 456-462. 21. Gillman M. and A. Nakov (2009). Monetary effects on nominal oil prices. North American Journal of Economics and Finance, 20, 239–254. 22. Gomez‐Gonzalez J., J. Hirs‐Garzon, and J. Uribe (2019). Giving and receiving: Exploring the predictive causality between oil prices and exchange rates. International Finance, 2019; 1–20. 23. Goyal A. and I. Welch (2008). A comprehensive look at the empirical performance of equity premium prediction. Review of Financial Studies, 21 (4), 1455-1508. 24. Hamilton J. D. (2003). What is an oil shock? Journal of Econometrics, 113, 363–398. 25. Hamilton J. D. (2009). Causes and consequences of the oil shock of 2007–08. Brookings Papers on Economic Activity, vol. 1, 215–261. 26. Kilian L. (2009a). Not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. American Economic Review, 99, 1053–1069. 27. Kilian L. (2009b). Comment on: Causes and Consequences of the Oil Shock of 2007–08, by J. D. Hamilton. Brookings Papers on Economic Activity, vol. 1, 267–278. 28. Kilian L. and D. Murphy (2013). The Role of Inventories and Speculative Trading in the Global Market for Crude Oil. Journal of Applied Econometrics, 29, 454-478. 29. Kilian L. and C. Vega (2010). Do energy prices respond to US macroeconomic news? A test of the hypothesis of predetermined energy prices. Review of Economics and Statistics, 93, 660–671. 30. Knetsch T. A. (2007). Forecasting the price of oil via convenience yield predictions. Journal of Forecasting, 26, 527–549. 31. Lizardo R. A. and A. V. Mollick (2010). Oil price fluctuations and US dollar exchange rates. Energy Economics, 32, 399–408. 32. Lof M. and H. Nyberg (2017). Noncausality and the commodity currency hypothesis. Energy Economics, 65, 424–433. 33. Newey W. and K. D. West (1987). A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55 (3), 703-708. 34. Newey W. and K. D. West (1994). Automatic Lag Selection in Covariance Matrix Estimation. The Review of Economic Studies, 61 (4), 631-653. 35. Pincheira P. and N. Hardy (2019). Forecasting base metal prices with the Chilean exchange rate. Resources Policy, vol. 62 (C), 256-281. 36. Timmermann A. (2006). Forecast Combinations. In: The Oxford Handbook of Economic Forecasting, vol. 1, 135–196. 37. West K.D. (2006). Forecast Evaluation. In Handbook of Economic Forecasting Volume 1. G. Elliot, C. Granger and A. Timmermann editors. Elsevier. 38. Working H. (1960). Note on the Correlation of First Differences of Averages of a Random Chain. Econometrica, 28, 916-918. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/105056 |