Time Series Models for Exchange Rate and Agricultural Price Forecasts

Girard W. Bradshaw; David Orden

Authors

Girard W. Bradshaw Department of Agricultural Economics Virginia Polytechnic Institute and State University
David Orden Department of Agricultural Economics Virginia Polytechnic Institute and State University

Keywords:

time series, exchange rate, agricultural prices, forecasting, commodity prices, differencing

Abstract

In this study, we focus on the role of the exchange rate in explaining variations in agricultural commodity prices. Particular attention is paid to stationarity and models in levels versus differences and we find differencing useful in making agricultural prices forecasts.

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References

Akaike, H. (1971). Autoregressive model fitting for control. Annals of the Institute of Statistical Mathematics, 23, 163–180. https://doi.org/10.1007/bf02479221

Ashley, R. A. (1988). On the relative worth of recent macroeconomic forecasts. International Journal of Forecasting.

Banerjee, A., et al. (1986). Exploring equilibrium relationships in econometrics through static models: Some Monte Carlo evidence. Oxford Bulletin of Economics and Statistics, 48(3), 253–277. https://doi.org/10.1111/j.1468-0084.1986.mp48003005.x

Bernanke, B. S. (1986). Alternative explanations of the money-income correlation (NBER Working Paper N.º 1842). National Bureau of Economic Research.

Bessler, D. A. (1984a). Relative prices and money: A vector autoregression on Brazilian data. American Journal of Agricultural Economics, 66(1), 25–30.

Bessler, D. A. (1984b). An analysis of dynamic economic relationships: An application to the U.S. hog market. Canadian Journal of Agricultural Economics, 32(1), 109–124.

Bessler, D. A. (1986). Forecasting vector autoregressions with Bayesian priors. American Journal of Agricultural Economics, 68(1), 144–151. https://doi.org/10.2307/1241659

Bessler, D. A., & Babula, R. (1987). Forecasting wheat exports: Do exchange rates matter? Journal of Business & Economic Statistics, 5(3), 397–406.

Blanchard, O. J., & Watson, M. W. (1986). Are business cycles all alike? In R. J. Gordon (Ed.), The American business cycle: Continuity and change (pp. 123–179). University of Chicago Press.

Box, G. E. P., & Jenkins, G. M. (1970). Time series analysis, forecasting and control. Holden-Day.

Box, G. E. P., & Jenkins, G. M. (1976). Time series analysis, forecasting and control (2.ª ed.). Holden-Day.

Brandt, J. A., & Bessler, D. A. (1984). Forecasting with vector autoregressions versus a univariate ARIMA process: An empirical example with U.S. hog prices. North Central Journal of Agricultural Economics, 6(1), 29–36.

Cooper, R. L. (1972). The predictive performance of quarterly econometric models of the United States. In B. G. Hickman (Ed.), Econometric models of cyclical behavior. Columbia University Press.

Davidson, J. E. H., et al. (1978). Econometric modelling of the aggregate time-series relationship between consumers' expenditure and income in the United Kingdom. Economic Journal, 88(352), 661–692. https://doi.org/10.2307/2231972

Dickey, D. A. (1975). Estimation and hypothesis testing in nonstationary time series [Tesis doctoral]. Iowa State University.

Dickey, D. A., et al. (1986). Unit roots in time series models: Tests and implications. The American Statistician, 40(1), 12–26. https://doi.org/10.1080/00031305.1986.10475349

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. https://doi.org/10.2307/2286348

Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/1912517

Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100. https://doi.org/10.1080/07474938408800053

Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.

Engle, R. F., & Yoo, B. S. (1987). Forecasting and testing in co-integrated systems. Journal of Econometrics, 35(1), 143–159. https://doi.org/10.1016/0304-4076(87)90085-6

Fackler, P. (1988). Vector autoregressive techniques for structural analysis (Working Paper N.º 113). Department of Economics and Business, North Carolina State University.

Fuller, W. A. (1976). Introduction to statistical time series. John Wiley & Sons.

Granger, C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, 16(1), 121–130.

Granger, C. W. J. (1983). Co-integrated variables and error correcting models (Discussion Paper). University of California, San Diego.

Granger, C. W. J. (1986). Developments in the study of co-integrated economic variables. Oxford Bulletin of Economics and Statistics, 48(3), 213–228.

Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120.

Granger, C. W. J., & Newbold, P. (1986). Forecasting economic time series (2.ª ed.). Academic Press.

Granger, C. W. J., & Weiss, A. A. (1983). Time series analysis of error correcting models. In S. Karlin et al. (Eds.), Studies in econometrics, time series, and multivariate statistics. Academic Press.

Hall, G. (1986). An application of the Granger and Engle two-step estimation procedure to United Kingdom aggregate wage data. Oxford Bulletin of Economics and Statistics, 48(3), 229–239. https://doi.org/10.1111/j.1468-0084.1986.mp48003003.x

Hannan, E. J., & Quinn, B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society. Series B, 41(2), 190–195.

Harvey, A. C. (1981). The econometric analysis of time series. Philip Allan.

Hendry, D. F., & Mizon, G. E. (1978). Serial correlation as a convenient simplification, not a nuisance: A comment on a study of the demand for money by the Bank of England. Economic Journal, 88(351), 549–563. https://doi.org/10.2307/2232053

Hsiao, C. (1979). Autoregressive modeling of Canadian money and income data. Journal of the American Statistical Association, 74(367), 553–560.

Judge, G. G., et al. (1985). The theory and practice of econometrics. John Wiley & Sons.

Kennedy, P. (1985). A guide to econometrics. MIT Press.

Kling, J. L., & Bessler, D. A. (1985). A comparison of multivariate forecasting procedures for economic time series. International Journal of Forecasting, 1(1), 5–24. https://doi.org/10.1016/s0169-2070(85)80067-4

Litterman, R. B. (1976). Techniques of forecasting using vector autoregressions [Tesis doctoral no publicada]. Department of Economics, University of Minnesota.

Litterman, R. B. (1984). Specifying vector autoregressions for macroeconomic forecasting (Staff Report N.º 92). Research Department, Federal Reserve Bank of Minneapolis.

Litterman, R. B. (1986). A statistical approach to economic forecasting. Journal of Business & Economic Statistics, 4(1), 1–4. https://doi.org/10.1080/07350015.1986.10509485

Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303. https://doi.org/10.1093/biomet/65.2.297

Lucas, R. E., & Sargent, T. J. (1979). After Keynesian macroeconomics. In Rational expectations and econometric practice. University of Minnesota Press.

Lütkepohl, H. (1982). Differencing multiple time series: Another look at Canadian money and income data. Journal of Time Series Analysis, 3(4), 235–243.

Lütkepohl, H. (1985). Comparison of criteria for estimating the order of a vector autoregressive process. Journal of Time Series Analysis, 6(1), 35–52.

Meese, R. A., & Singleton, K. (1982). On unit roots and the empirical modeling of exchange rates. Journal of Finance, 37(4), 1029–1035. https://doi.org/10.1111/j.1540-6261.1982.tb03595.x

Nelson, C. R. (1972). The prediction performance of the FRB-MIT-PENN model of the U.S. economy. American Economic Review, 62(5), 902–917.

Nelson, C. R., & Kang, H. (1984). Pitfalls in the use of time as an explanatory variable in regression. Journal of Business & Economic Statistics, 2(1), 73–82. https://doi.org/10.1080/07350015.1984.10509371

Nelson, C. R., & Plosser, C. I. (1982). Trends and random walks in macroeconomic time series. Journal of Monetary Economics, 10(2), 139–162.

Orden, D. (1986). Agriculture, trade, and macroeconomics: The U.S. case. Journal of Policy Modeling, 8(1), 27–51.

Phillips, P. C. B. (1986). Understanding spurious regressions in econometrics. Journal of Econometrics, 33(3), 311–340.

Phillips, P. C. B., & Durlauf, R. N. (1986). Multiple time series regression with integrated processes. Review of Economic Studies, 53(4), 473–495. https://doi.org/10.2307/2297602

Prothero, D. L., & Wallis, K. F. (1976). Modelling macroeconomic time series (with discussion). Journal of the Royal Statistical Society. Series A, 139(4), 468–500.

Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461–464.

Schwert, G. W. (1987). Effects of model specification on tests for unit roots in macroeconomic data. Journal of Monetary Economics, 20(1), 73–103.

Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48. https://doi.org/10.2307/1912017

Sims, C. A. (1986). Are forecasting models usable for policy analysis? Federal Reserve Bank of Minneapolis Quarterly Review, 10(1), 2–16.

Stock, J. H. (1987). Asymptotic properties of least squares estimators of cointegrating vectors. Econometrica, 55(5), 1035–1056. https://doi.org/10.2307/1911260

Stock, J. H., & Watson, M. W. (1987). Interpreting the evidence on money-income causality (NBER Working Paper N.º 2228). National Bureau of Economic Research.

Thornton, D., & Batten, D. (1985). Lag-length selection and tests of Granger causality between money and income. Journal of Money, Credit and Banking, 17(2), 164–178.

Tiao, G. C., & Box, G. E. P. (1981). Modeling multiple time series with applications. Journal of the American Statistical Association, 76(376), 802–816. https://doi.org/10.1080/01621459.1981.10477728

U.S. Department of Commerce. (1974-1987). Survey of current business.

Wasserfallen, W. (1986). Non-stationarities in macroeconomic time series: Further evidence and implications. Canadian Journal of Economics, 19(3), 498–510. https://doi.org/10.2307/135343

Webb, R. H. (1985). Toward more accurate macroeconomic forecasts from vector autoregressions. Federal Reserve Bank of Richmond Economic Review, julio-agosto, 3–17.

Wold, H. (1954). A study in the analysis of stationary time series (2.ª ed.). Almqvist & Wiksell.

Yule, G. U. (1926). Why do we sometimes get nonsense-correlations between time-series? A study in sampling and the nature of time-series. Journal of the Royal Statistical Society, 89(1), 1–63. https://doi.org/10.2307/2341482

Zellner, A. (1979). Statistical analysis of econometric models. In Basic issues in econometrics (pp. 83–119). University of Chicago Press.

Zellner, A. (1982). Basic issues in econometrics, past and present. In Basic issues in econometrics (pp. 26–34). University of Chicago Press.

Time Series Models for Exchange Rate and Agricultural Price Forecasts

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