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Agricultural Inter-Sectoral Linkages and Its Contribution to Economic Growth in the Transition Countries


  • Subramaniam, Vijay
  • Reed, Michael R.


This study estimates an econometric model that incorporates the linkages among agriculture, manufacturing, service and trade sectors using a vector error correction model for Poland and Romania. Three cointegrating vectors for Poland and one for Romania confirm that the different sectors in the Poland and Romania moved together over the sample period, and for this reason, their growth rates are interdependent. The long-run relationship of industrial, service and trade sectors to agricultural sector were established, and the results show that the industrial sector in Poland contributes positively to the agricultural sector while the growing service sector shows mixed results. The results of Romania indicate that the industrial sector is detrimental to agriculture however, the service sector contributes positively. The short-run results show that the service sector is the most significant sector in the Polish economy and it contributes positively to all other sectors. However, growth in the industrial sector affects the other two sectors negatively. A similar effect is observed in the Romanian economy; however, the results are not significant. As expected, the role of agriculture in the short-run is not significant to the other sectors, but it made a positive impact on the industrial sector in Romania.

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  • Subramaniam, Vijay & Reed, Michael R., 2009. "Agricultural Inter-Sectoral Linkages and Its Contribution to Economic Growth in the Transition Countries," 2009 Conference, August 16-22, 2009, Beijing, China 51586, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae09:51586

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    References listed on IDEAS

    1. Niels‐Hugo Blunch & Dorte Verner, 2006. "Shared Sectoral Growth Versus the Dual Economy Model: Evidence from Côte d'Ivoire, Ghana, and Zimbabwe," African Development Review, African Development Bank, vol. 18(3), pages 283-308.
    2. Adelman, Irma, 1984. "Beyond export-led growth," World Development, Elsevier, vol. 12(9), pages 937-949, September.
    3. Johansen, Soren, 1992. "Determination of Cointegration Rank in the Presence of a Linear Trend," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 383-397, August.
    4. Johan F. M. Swinnen & Liesbeth Dries & Karen Macours, 2005. "Transition and agricultural labor," Agricultural Economics, International Association of Agricultural Economists, vol. 32(1), pages 15-34, January.
    5. Hwa, Erh-Cheng, 1988. "The contribution of agriculture to economic growth: Some empirical evidence," World Development, Elsevier, vol. 16(11), pages 1329-1339, November.
    6. Kanwar, Sunil, 2000. "Does the Dog Wag the Tail or the Tail the Dog? Cointegration of Indian Agriculture with Nonagriculture," Journal of Policy Modeling, Elsevier, vol. 22(5), pages 533-556, September.
    7. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    8. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    9. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    10. Adelman, Irma, 1984. "Beyond export-led growth," CUDARE Working Paper Series 309, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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    More about this item


    Transition economy; Inter-sectoral growth linkages; Cointegration analysis; International Development; Research Methods/ Statistical Methods; P20; 041; C32;

    JEL classification:

    • P20 - Economic Systems - - Socialist Systems and Transition Economies - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models


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