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Impact of price realization on India's tea export: Evidence from Quantile Autoregressive Distributed Lag Model

Author

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  • Debdatta PAL

    (Indian Institute of Management Raipur, Raipur, India)

  • Subrata Kumar MITRA

    (Indian Institute of Management Raipur, Raipur, India)

Abstract

The quantile autoregressive distributed lag model of Galvao et al. (2013) was employed to assess the impact of price realization on India's tea export. The results of the QADL varied significantly from the conditional mean estimates. It was found that the tea export from India had autoregressive impact, and that production and export price realization had asymmetric relationship with India's tea export that varied over quantiles.

Suggested Citation

  • Debdatta PAL & Subrata Kumar MITRA, 2015. "Impact of price realization on India's tea export: Evidence from Quantile Autoregressive Distributed Lag Model," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(9), pages 422-428.
    • Handle: RePEc:caa:jnlage:v:61:y:2015:i:9:id:209-2014-agricecon
    DOI: 10.17221/209/2014-AGRICECON
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    References listed on IDEAS

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    1. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
    2. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    3. Lee, Chien-Chiang & Zeng, Jhih-Hong, 2011. "Revisiting the relationship between spot and futures oil prices: Evidence from quantile cointegrating regression," Energy Economics, Elsevier, vol. 33(5), pages 924-935, September.
    4. Antonio F. Galvao JR. & Gabriel Montes-Rojas & Sung Y. Park, 2013. "Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 307-321, April.
    5. Xiao, Zhijie, 2009. "Quantile cointegrating regression," Journal of Econometrics, Elsevier, vol. 150(2), pages 248-260, June.
    6. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    7. Donaldson, R Glen & Kamstra, Mark, 1996. "A New Dividend Forecasting Procedure That Rejects Bubbles in Asset Prices: The Case of 1929's Stock Crash," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 333-383.
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