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Spatial Price Transmission Analysis in Agricultural Markets: Does the Data Frequency Improve our Estimation?

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  • Amikuzuno, Joseph

Abstract

Unavailability of high frequency, weekly or daily data compels most studies of price transmission in developing countries to use low frequency, monthly data for their analyses. Analyzing price dynamics with monthly data may however yield imprecise price adjustment parameters and lead to wrong inferences on price dynamics. This is because agricultural markets in developing countries operate daily or weekly. In this paper, we investigate the relevance of data frequency in price transmission analysis. We use a standard- and a threshold vector error model to estimate and compare price adjustment parameters for a high frequency, semi-weekly, data and a low frequency, monthly data. The results reveal that adjustment parameters estimated from the low frequency data are higher in all cases than those estimated from the high frequency data. We suspect that using low frequency data leads to an overestimation of price adjustment parameters. The findings therefore confirm observations in the literature that high frequency data is capable of estimating price adjustment parameters more precisely than low frequency data. More research involving a large number of observations is however needed to enhance our learning from the usefulness of high frequency data in price transmission analysis.

Suggested Citation

  • Amikuzuno, Joseph, 2010. "Spatial Price Transmission Analysis in Agricultural Markets: Does the Data Frequency Improve our Estimation?," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 96167, African Association of Agricultural Economists (AAAE).
    • Handle: RePEc:ags:aaae10:96167
    DOI: 10.22004/ag.econ.96167
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    1. In Choi & Bhum Suk Chung, 1995. "Sampling frequency and the power of tests for a unit root: A simulation study," Economics Letters, Elsevier, vol. 49(2), pages 131-136, August.
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    3. Jones, William O., 1968. "The Structure of Staple Food Marketing in Nigeria as Revealed by Price Analysis," Food Research Institute Studies, Stanford University, Food Research Institute, vol. 8(2), pages 1-30.
    4. Christopher B. Barrett & Jau Rong Li, 2002. "Distinguishing between Equilibrium and Integration in Spatial Price Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 292-307.
    5. Choi, In, 1992. "Effects of data aggregation on the power of tests for a unit root : A simulation study," Economics Letters, Elsevier, vol. 40(4), pages 397-401, December.
    6. Shahidur Rashid, 2004. "Spatial Integration of Maize Markets in Post-liberalised Uganda," Journal of African Economies, Centre for the Study of African Economies, vol. 13(1), pages 102-133, March.
    7. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
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    Cited by:

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    2. Listorti, Giulia & Esposti, Roberto, 2012. "Horizontal Price Transmission in Agricultural Markets: Fundamental Concepts and Open Empirical Issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(01), pages 1-28, April.
    3. Hamulczuk, Mariusz & Makarchuk, Oksana & Sica, Edgardo, 2019. "Searching for market integration: Evidence from Ukrainian and European Union rapeseed markets," Land Use Policy, Elsevier, vol. 87(C).

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