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11.price behaviour of major cereal crops in bangladesh

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  • 1. Food Science and Quality Management www.iiste.orgISSN 2224-6088 (Paper) ISSN 2225-0557 (Online)Vol 3, 2012 Price Behaviour of Major Cereal Crops in Bangladesh Shakila Salam1 Shamsul Alam2 Md. Moniruzzaman 3* 1. Post graduate student, Department of Agribusiness and Marketing, Bangladesh Agricultural University, Mymensingh, PO:2202, Bangladesh 2. Professor, Department of Agribusiness and Marketing, Bangladesh Agricultural University, Mymensingh, PO:2202, Bangladesh 3. Associate Professor, Department of Agribusiness and Marketing, Bangladesh Agricultural University, Mymensingh, PO:2202, Bangladesh * E-mail of the corresponding author: [email protected] key concern of this research is to analyse the extent of the seasonal price fluctuation and spatialprice relationship of major cereal crops viz., Boro paddy and wheat in different markets in Bangladesh.This study was entirely based on secondary data from the period of 1986-87 to 2009-10 from differentsources. In estimating seasonal price fluctuation of selected crops it was found that crops pricesfluctuated in different months within the year. The difference between peak and trough prices washigher for Boro paddy than wheat. Coefficient of variation was also higher for Boro paddy than wheatbut these figures are decreasing gradually. The results of empirical evaluation of spatial price linkagethrough Engle-Granger co-integration method among regional selected markets of Bangladesh usingharvest price of Boro paddy and wheat indicate that these markets were well integrated. That means,information about price changes are fully and instantaneously delivered to the other markets inBangladesh. Price analysis and formation of policy at the aggregate level will be pertinent for policyimplementation.Keywords: Price behaviour, Cereal crops, Market integration, Unit root, Engle-Granger1. IntroductionThis paper has attempted to assess the nature of seasonal price movement and the degree of inter-relationships between price movements in two markets or market integration of selected crops. Asstabilisation of prices, particularly of major food grains, is a serious concern of most developingcountries, so the generated information may help government in taking appropriate decision at all. Thegeneral pattern of seasonal variation in prices, i.e., lower prices during the immediate post-harvestmonths and higher prices during the pre-harvest or off-season months is a normal feature of food grainsand repeated year after year. This is due mainly to seasonality in supply and factors affecting thestocking decisions of traders. Production of a particular food grain is usually confined to only oneseason while the demand is spread throughout the year. Thus storage becomes necessary and thisinvolves costs, resulting in seasonal price variations. The extent of seasonal price variation depends, inaddition to storage cost, on the degree of seasonal concentration of sales, perishability of the product,risk involved in holding the product over time and availability of storage, warehousing and creditfacilities (Acharya and Agarwal, 1994, p.82).Again, the single market does not stand alone as a determinant of either price or quantity and theactions of buyers and sellers in a particular market. Commodity markets are always influenced to alarge degree by the respective price signals and substitution possibilities in other related markets(George, 1984). A marketing system is spatially integrated when prices in each individual marketrespond not only to their own supply and demand but to the supply and demand of the set of allmarkets. In short, a local scarcity in an integrated system is less prejudicial to local consumers becauseit includes the arrival of products from other location. It increases supply and decrease the price. Thus,the degree of spatial price relationship is important for agricultural crops. The objectives of this papertherefore are: 1. To analyse the extent of the seasonal price fluctuation of major cereal crops in Bangladesh. 23
  • 2. Food Science and Quality Management www.iiste.orgISSN 2224-6088 (Paper) ISSN 2225-0557 (Online)Vol 3, 2012 2. To study the spatial price relationships of major cereal crops in different markets with the aim to assess extent of market integration.2. Methodology of the StudyFor this study leading cereal crops, Boro paddy and wheat have been selected according to theirascendancy in agriculture in terms of production and area coverage. These crops occupy largestcultivated area (33.12 percent) together out of total cultivated area in Bangladesh (BBS, 2006 p.33). AsBoro covers the major part in case of production among different rice varieties, only Boro has beenselected in the study. According to the BBS, Boro production was 56.67 percent of total rice productionin 2008-09.Harvest prices of selected crops have been taken into consideration for the reason that wholesale andretail prices may not reflect what the farmers actually receive, because they are set at a considerablyhigher level (covering cost of storage, transportation and risk). Moreover, bulk of the agriculturalproduces is marketed during the harvest or immediately post harvest period. So, harvest prices are themost relevant prices for the producer farmer. Unavailability of required data is one of a majorlimitation of this research work. For calculating monthly prices of selected crops four weeks priceswere averaged which were available in DAM weekly price bulletin.The study makes an extensive use of secondary data on prices and quantity available of selected cropsin Bangladesh for the period of 24 years from 1986-87 to 2009-10 (as the latest data available).Agricultural sector prior to eighties was highly subsidized by the Government. Withdrawal of subsidiesand handing over fertilizer and irrigation equipment marketing to private sector started from theeighties.For Boro paddy five and for wheat six district markets have been selected due to their leading growingareas. Due to unavailability of the Boro paddy price for Dhaka, Boro clean rice price was used in theanalysis of market integration measurement. As the research was solely based on secondary data, thesedata were obtained from various publications of Ministry of Finance, Bangladesh Bureau of Statistics,FAO statistical report, various books, journals, newspapers and internet. Furthermore, district wisemarket prices of different crops were collected from the weekly wholesale price bulletin of Departmentof Agricultural Marketing (DAM).2.1 Analytical TechniquesThe seasonal pattern is analysed by construction of seasonal index numbers by applying ratio tomoving average method. To avoid the problem of spurious correlation between time series variablesespecially price variable co-integration method which was developed by Engle and Granger (1987) formaking firm decisions on market integration has been used.A test of stationarity (or non-stationarity), that has been developed by Dickey-Fuller was applied in thisstudy. This test is to consider the following model: Yt = Yt-1 + Ut ................... (1)Where Ut is the stochastic error term that follows the classical assumptions, namely, it has zero mean,constant variance 2, and is non-autocorrelated. Such an error term is also known as a white noise errorterm. Equation (1) is a first-order, or AR (1), regression in that regress the value of Y at a time (t-1). Ifcoefficient of Yt-1 is in fact equal to 1, that is known as the unit root problem i.e., a non-stationarysituation. Therefore, if runs the regression, Yt =Yt-1+Ut ; -1 1 ................ (2)and actually find that = 1, then the stochastic variable has a unit root.For theoretical reasons, the equation (2) can be manipulated as follows: Yt Yt-1 = Yt-1 Yt-1 + Ut Yt = ( 1) Yt-1 + Ut ................. (3)which is alternatively written as, Yt = Yt-1 + Ut ................. (4) 24
  • 3. Food Science and Quality Management www.iiste.orgISSN 2224-6088 (Paper) ISSN 2225-0557 (Online)Vol 3, 2012where, = ( 1) and is the first difference operator. Note that Yt = (Yt Yt-1) therefore, insteadof estimating (2), estimating equation (3) and test the null hypothesis that = 0. If = 0, then = 1 wehave a unit root, meaning the time series under consideration is nonstationary.Under the null hypothesis = 0, i.e., ( 1) = 0, the conventionally computed t statistic is known as the (tau) statistic, whose critical values have been tabulated by Dickey-Fuller test (DF) on the basis ofMonte Carlo simulations. In the literature the tau statistic or test is known as the Dickey-Fuller (DF)test, in honour of its discoverers (Gujarati, 2004, p.975).The DF test is estimated in different forms under different null hypotheses:Without trend, Yt = 1 + Yt-1 + Ut ................. (5)With trend, Yt = 1 + 2t + Yt-1 + Ut ................. (6)In each case, the null hypothesis is that = 0; that is, there is a unit root the time series is non-stationary.The ADF test is run with the following equation, m Yt = 1 + 2t + Yt-1 + i Y

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