Crude-oil price volatility and agricultural employment in the USA

Applied Energy

Volumn 54, Issue 4, 1996, Pages 355-373

  Uri, Noel D ^a  

^a ECONOMIC RESEARCH SERVICE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL EMPLOYMENT; CRUDE OIL PRICE VOLATILITY; GRANGER CAUSALITY; NET FARM INCOME; REALIZED TECHNOLOGICAL INNOVATION; UNITED STATES; WAGE RATE;

AGRICULTURE; EMPLOYMENT; INDUSTRIAL ECONOMICS; MODERNIZATION; TECHNOLOGY; WAGES;

CRUDE PETROLEUM;

AGRICULTURAL EMPLOYMENT; EMPLOYMENT IMPACT; OIL PRICE; PRICE VOLATILITY;

USA;

EID: 0030206957     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/0306-2619(96)00005-0     Document Type: Article

References (41)

1. Eckstein, O., The DRI Model of the US Economy. McGraw-Hill, New York, 1983.
2. Lee, D., Labor market dynamics in the US food sector, American Journal of Agricultural Economics, 70 (1988) 90-103.
3. Lilien, D., Sectoral shifts and cyclical unemployment, Journal of Political Economy, 90 (1982) 777-793.
4. Mankiw, G., Macroeconomics, 2nd ed. Worth, New York, 1994.
5. Loungani, P., Oil price shocks and the dispersion hypothesis, The Review of Economics and Statistics, 58 (1986) 536-539.
6. Burbidge J. & Harrison, A., Testing for the effects of oil-price rises on using vector autoregressions, International Economic Review, 25 (1984) 459-484.
7. Darby, M., The price of oil and world inflation and recession, The American Economic Review, 72 (1982) 738-751.
8. Hamilton, J., Oil and the macroeconomy, Journal of Political Economy, 91 (1983) 228-248.
9. Gisser, M. & Goodwin, T., Crude oil and the macroeconomy: tests of some popular notions, Journal of Money, Credit and Banking, 18 (1986) 95-103.
10. Granger, C. W. J., Investigating causal relations by econometric models and cross-spectral methods, Econometrica, 37 (1969) 424-438.
11. Granger, C. W. J. & Newbold, P., Spurious regressions in econometrics, Journal of Econometrics, 2 (1977) 111-120.
12. Pierce, D. A. & Haugh, L. D., Causality in temporal systems, Journal of Econometrics, 5 (1977) 265-293.
13. Pierce, D. A. & Haugh, L. D., The characterization of instantaneous causality, Journal of Econometrics, 7 (1979) 257-259.
14. Pierce, D. A., Forecasting in dynamic models with stochastic regressors, Journal of Econometrics, 3 (1975) 349-374.
15. Hannan, E. J., Multiple Time Series. John Wiley, New York, 1970.
16. Haugh, L. D., The identification of time series interrelationships with special reference to dynamic regression. PhD dissertation, University of Wisconsin, 1972.
17. Geweke, J., Inference and causality in economic time series models. In: Handbook of Econometrics, ed. Z. Griliches & M. Intriligator. North-Holland, Amsterdam, 1984.
18. Mills, T., Time Series Techniques for Economists. Cambridge University Press, Cambridge, 1990.
19. Council of Economic Advisors, Economic Report of the President. US Government Printing Office, Washington, 1979.
20. Energy Information Administration, Monthly Energy Review. DOE/EIA-0035 (95/01), US Department of Energy, Washington, 1995.
21. Box, G. E. P. & Jenkins, G. M., Time Series Analysis: Forecasting and Control. Holden Day, San Francisco, 1971.
22. Sawa, T., Information criteria for discriminating among alternative models, Econometrica, 46 (1978) 1273-1291.
23. Priestley, M. B., Spectral Analysis and Time Series. Academic Press, London, 1981.
24. Ljung, G. & Box, G., On a measure of lack of fit in time series models, Biometrika, 66 (1978) 297-304.
25. Geweke, J., Meese, R. & Dent, W., Comparing alternative tests of causality in temporal systems: analytic results and experimental evidence, Journal of Econometrics, 21 (1983) 161-194.
26. Okun, A., Potential GNP: its measurement and significance. Proceedings of the American Statistical Association, Washington, 1962.
27. Kaplan, S., Energy Economics. McGraw-Hill, New York, 1983.
28. Hall, R. & Taylor, J., Macroeconomics. W.W. Norton, New York, 1986.
29. Johnson, C., A Historical Look at Farm Income. Economic Research Service, US Department of Agriculture, Washington, 1990.
30. Economic Research Service, Agricultural Outlook. US Department of Agriculture, Washington, 1995.
31. Uri, N. D., The structure of agricultural employment, Growth and Change, 20 (1989) 1-13.
32. Uri, N. D. & Day, K., Energy efficiency, technological change and the dieselization of american agriculture, Transportation Planning and Technology, 16 (1992) 221-231.
33. Uri, N. D., The Demand for Energy and Conservation in the United States. JAI Press, Greenwich, 1982.
34. Judge, G., Griffiths, W., Hill, R. C., Lutkepohl, H. & Lee, T. C., The Theory and Practice of Econometrics, 2nd ed. John Wiley and Sons, New York, 1985.
35. Belsley, D., Kuh, E. & Welsch, R., Regression Diagnostics. John Wiley and Sons, New York, 1980.
36. White, H., A heteroscedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity, Econometrica, 48 (1980) 817-838.
37. Godfrey, L., Misspecification Tests in Econometrics. Cambridge University Press, Cambridge, 1988.
38. Hamilton, J., A neoclassical model of unemployment and the business cycle, Journal of Political Economy, 96 (1988) 593-617.
39. Brown, R. L., Durbin, J. & Evans, J., Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society, 37 (1975) 149-163.
40. Harvey, A. C., The Econometric Analysis of Time Series. Phillip Allen, Oxford, 1981.
41. US Department of Agriculture, Agricultural Statistics. US Government Printing Office, Washington, 1995.