Boufateh, Talel (2016): Cycle-Trend Dichotomy of the Dutch Disease Phenomenon.
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Abstract
This paper aims to study the simultaneous effects of Dutsh Disease (DD) phenomenon on the industrial and agricultural sectors for five oilexporting countries with different development levels. To proceed, we propose to study the dynamic relationship between oil rent, industrial added value and agricultural added value in a structural multivariate framework. The idea is to capture both short and long term dynamics of this relationship, by performing the model’s cycle-trend dichotomy using SVECM approach. The results have shown that the DD phenomenon effects both agricultural and industrial sectors in the considered countries with one exception for each sector. The impacts and adverse effects that might have the DD phenomenon on each sector accordingly whether it is permanent or transient, depend on the economy nature and the strategy adopted. The findings confirmed that the DD phenomenon affecting the industrial sector ephemerally however the agricultural sector is rather being affected in the long term.The results also, have indicated that developing countries notably Morocco, is model to consolidate, and that the case of great emerging countr
Item Type: | MPRA Paper |
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Original Title: | Cycle-Trend Dichotomy of the Dutch Disease Phenomenon |
English Title: | Cycle-Trend Dichotomy of the Dutch Disease Phenomenon |
Language: | English |
Keywords: | Dutch Disease, industrial sector, agricol sector, cycle-trend, SVECM |
Subjects: | Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q10 - General Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General |
Item ID: | 71741 |
Depositing User: | Talel BOUFATEH |
Date Deposited: | 10 Jun 2016 06:10 |
Last Modified: | 06 Oct 2019 04:23 |
References: | [1] Apergis,N.,El-Montasser,G.,Sekyere,E., Ajmi,A.N, Rangan, G. (2014) ”Dutch disease effect of oil rents on agriculture value added in Middle East and North African (MENA) countries“. Energy Economics, v. 45, p. 485-490. [2] Auty, R. M. (2001). Resource abundance and economic development (p. 360). Oxford University Press. [3] Barro, R. J. and Sala-i-Martin, X. (1992), “Regional Growth andMigration: a Japanese-US Comparison”. Journal of the Japanese and International Economy, 6 (4), 312-346. (b). [4] Benjamin, N.C.. Devarajan, S. andWeiner R. J. (1989) “ The Dutch Disease in a Developing Country— Oil Reserves in Cameroon”. Journal of Development Economies. 30: 71-92 [5] Bernanke, B.S., (1986). ‘Alternative Explanations of the Money- IncomeCorrelation’, Carnegie-Rochester Conference Series on Public Policy, Vol.25, pp. 49-100. [6] Bernanke, B.S., and M. Gertler (1995), "Inside the black box: the credit channel of monetary policy transmission", Journal of Economic Perspectives 9:27~48. [7] Bjørnland, H.C. (1996). ‘Sources of Business Cycles in Energy ProducingEconomies-The Case of Norway and United Kingdom’, Discussion Papers179, Statistics Norway. [8] Bjørnland, H.C. (1998). ‘The Economic Effects of North Sea Oil on the- Manufacturing Sector’, Scottish. Journal of Political Economy, vol45, No 5.pp.553-585. [9] Blanchard, O.J., Quah, D., (1989). ‘The Dynamic Effects of Aggregate Demandand Supply Disturbances’, American Economic Review, Vol. 79, pp655-73. [10] Blanchard, O.J., Watson, M.W., (1986). ‘Are Business Cycles All Alike?’,The American Business Cycle: Continuity and Change, NBER and Universityof Chicago Press, pp.123-156. [11] Buiter, W.H. and Purvis, D.D. (1982). ‘Oil, disinflation and export competitiveness: a model of the Dutch disease’, in Bhandari, J. and Putnam,B. (eds.), Economic Interdependence and Flexible Exchange Rates, Cambridge, Mass., MIT Press. [12] Corden, W. M. and J. Peter, N. (1982). ‘Booming Sector and DeIndustrialisationIn A Small Open Economy’. The Economic Journal, vol 92. pp.825- 848. [13] Cox, G. M., & Harvie, C. (2010). ‘Resource price turbulence and macroeconomic adjustment for a resource exporter: A conceptual framework for policy analysis’. Energy Economics, vol32 No 2, pp. 469-489. [14] Dar A.A. and Amir khalkhali S. (2002): “Government Size, Factor Accumulation, and Economic Growth: Evidence from O.E.C.D. Countries,” Journal of Policy Modeling, Vol. 24, 679-692. [15] Eastwood, R.K and Venables, A.J. (1982). ‘The macroeconomic implicationsof a resource discovery in an open economy’.Economic Journal, vol 92.pp.285-99. [16] Engle, R.F., Granger, C.W.J., 1987. Co-integration and error correction: Representation, estimation and testing, Econometrica 55: 251—276. [17] Granger, C.W.J., 1981. Some properties of time series data and their use in econometric model specification, Journal of Econometrics 16: 121-130. [18] Granger, C.W.J., 1983. Co-integrated variables and error- correcting models, unpublished UCSD Discussion Paper 83-13. [19] Granger, C.W.J., Weiss, A. A., 1983. Time series analysis of errorcorrection$ models, in Studies in Econometrics, Time Series andMultivariate Statistics, New York: Academic Press, pp. 255-278. [20] Issaoui.F, Boufateh.T et El Montasser.G (2013): "The long run dynamic of the Dutch disease phenomenon: a SVAR approach", International Journal of Computational Economics and Econometrics, Vol. 3, Nos. 1/2. [21] Johansen, S., 1995. Likelihood-based inference in cointegrated vector autoregressive models”, Oxford University Press. [22] Johansen, S., 1988. Statistical Analysis of Cointegrating Vectors, Journal of Economic Dynamics and Control, 12, 231-54. [23] Lütkepohl, H., Reimers, H.E., (1992a). "Granger-causality in cointegrated VAR processes: The case of the term structure", Economics Letters 40: 263—268. [24] Lütkepohl, H., Reimers, H.E., (1992b). "Impulse response analysis of cointegrated systems", Journal of Economic Dynamics and Control 16: 53—78. [25] Nazlioglu, S. (2011), “World Oil and Agriculutral Commodity Prices: Evidence from Nonlinear Causality”, Energy Policy, 39(5), 2935-2943. [26] Nazlioglu, S., & Soytas, U. (2012). Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis. Energy Economics, 34(4), 1098-1104. [27] Olusi J. O. and Olagunju M. A. 2005. The Primary Sectors of the Economyand the Dutch Disease in Nigeria. The Pakistan Development Review, vol.44, No 2. pp. 159-175. [28] Quah D. et S. P. Vahey (1994): “Measuring core inflation”, The Economic Journal, September, 105. [29] Sachs, J. D., &Warner, A. M. (1999). The big push, natural resource booms and growth. Journal of Development Economics, 59, 43-76. [30] Sims, C.A. (1986): “Are Forecasting Models Usable for Policy Analysis”, Federal Reserve Bank of Minneapolis Quarterly Review, Winter, pp 2-16. [31] Sturm, M.; Zimmermann, M.; Schütz, K.; Urban,W. & Hartung, H. (2009). Rainwater harvesting as an alternative water resource in rural sites in central northern Namibia. Physics and Chemistry of the Earth, v. 34, p. 776- 785. [32] Warne A. (1993): "A Common Trends Model: Identification, Estimation and Inference", Seminar Paper No. 555, IIES, Stockholm University. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/71741 |