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Spatial Differences in Rice Price Volatility:A Case Study of Pakistan 1994–2011

Author

Listed:
  • Burhan Ahmad

    (Institute of Business Management Sciences (IBMS), Universality of Agriculture Faisalabad, Faisalabad)

  • Ole Gjølberg

    (NMBU School of Economics and Business, Norwegian University of Life Sciences (NMBU), Norway)

  • Mubashir Mehdi

    (Institute of Business Management Sciences (IBMS), University of Agriculture Faisalabad, Faisalabad)

Abstract

Prices of agricultural commodities tend to be more volatile in comparison to other commodities. Volatility can result in inefficient allocation of the resources by the farmers, traders and consumers. Rice is the second major staple and export item of Pakistan. This study presents the trends in volatility of regional rice markets of Pakistan and analyses spatial differences in volatility across regional rice markets in Pakistan from 1994 to 2011, and also draws comparison of volatility with the international market. ARCH-LM tests are applied to check the presence of volatility and volatility clustering is found in all the markets. Tests for equality of variance and dynamic conditional correlations (DCC) GARCH model are employed to analyse the spatial differences across the regional rice markets of Pakistan. The results indicate the presence of spatial differences in volatility. Positive conditional correlations in the dynamic conditional correlations (DCC) GARCH model are found which indicate positive association of volatility across markets. Spatial differences in volatility and its persistence reflect the differences in market forces, infrastructure and information flow which leads to varying degree of risk across markets and some regions are exposed to higher risk. The study found out that Hyderabad and Sukkur are the most volatile markets and their volatility levels are highly persistent and require highest time to return to its long-term mean which makes them the riskiest rice markets. Investments in infrastructure, particularly in transportation and controlling the market power of middlemen may reduce price risk across markets particularly in the most risky markets.

Suggested Citation

  • Burhan Ahmad & Ole Gjølberg & Mubashir Mehdi, 2017. "Spatial Differences in Rice Price Volatility:A Case Study of Pakistan 1994–2011," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 56(3), pages 265-289.
    • Handle: RePEc:pid:journl:v:56:y:2017:i:3:p:265-289
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Rice Prices Volatility; Regional Markets; Pakistan. DCC-GARCH-models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

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