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Sugar Sector Decontrolling and Market Performance of Sugar Sector in India Vis-À-Vis Global Market: A Cointegration Analysis

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Abstract

The study analyses the extent, pattern and degree of spatial integration of sugar markets in India, as well as relationship of white sugar export prices of India and global market. The pattern and degree of integration were assessed by testing for the existence of the law of one price (LOOP) and ascertaining the speed of adjustment towards long-run equilibrium, using various tests by using cointegrated methods. Results indicated that only 4 of 11 sugar markets are cointegrated. The supply of sugar appears to be the most important factor shaping the long-run behaviour of its price levels in India. No single market is found to be the price leader. The prices of sugar exported by India to the global market were not cointegrated and did not conform to LOOP. Decontrolling of sugar sector from the clutches of monthly release mechanism plays an insignificant role in determining the relationship of sugar prices in the global market. The study suggests sugar policy reforms, consistent export and import strategies and abolition of export quota are absolutely essential for market integration and convergence of prices in the domestic and global market.

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Notes

  1. The Sugar No. 11 contract at New York is the world benchmark contract for raw sugar trading. The contract prices the physical delivery of raw cane sugar, free on board the receiver's vessel to a port within the country of origin of the sugar.

  2. The white sugar futures contract is used as the global benchmark for the pricing of physical white sugar. It is actively traded by the international sugar trade, sugar millers, refiners, and end-users (manufacturers) as well as by managed funds and both institutional and short-term investors.

  3. In statistics, a unit root test tests whether a time series variable is non-stationary and possesses a unit root. The null hypothesis is generally defined as the presence of a unit root, and the alternative hypothesis is stationarity, trend stationarity or explosive root depending on the test used. A commonly used test that is valid in large samples is the augmented Dickey–Fuller test. Unit root tests are closely linked to serial correlation tests. However, while all processes with a unit root will exhibit serial correlation, not all serially correlated time series will have a unit root.

  4. A stationary (time) series is one whose statistical properties such as the mean, variance and autocorrelation are all constant over time. Hence, a non-stationary series is one whose statistical properties change over time. Non-stationary data should be first converted into stationary data (for example, by trend removal), so that further statistical analysis can be performed on the de-trended stationary data. Most statistical forecasting methods assume that the time series are approximately stationary.

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Authors and Affiliations

  1. Economics and Statistics Section, ICAR- Sugarcane Breeding Institute (SBI), Coimbatore, 641 007, India

    P. Murali

  2. Social Science Division, Indian Institute of Wheat and Barley Research IIWBR, Karnal, Haryana, India

    R. Sendhil

  3. ICAR- NIVEDI - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, 560064, India

    G. Govindaraj

  4. Extension Section, ICAR- Sugarcane Breeding Institute (SBI), Coimbatore, 641 007, India

    D. Puthira Prathap & V. Venkatasubrmanian

  5. ICAR- Sugarcane Breeding Institute (SBI), Coimbatore, 641 007, India

    Bakshi Ram

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  1. P. Murali
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  2. R. Sendhil
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  3. G. Govindaraj
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  4. D. Puthira Prathap
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  5. V. Venkatasubrmanian
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  6. Bakshi Ram
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Murali, P., Sendhil, R., Govindaraj, G. et al. Sugar Sector Decontrolling and Market Performance of Sugar Sector in India Vis-À-Vis Global Market: A Cointegration Analysis. Sugar Tech 21, 557–568 (2019). https://doi.org/10.1007/s12355-018-0677-0

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