Estimation of Agricultural Production

Estimation of Agricultural Production

P. C. Gupta (University of Rajasthan – Jaipur, India)
DOI: 10.4018/978-1-4666-5146-3.ch004
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The successful implementation of e-governance mainly depends on the reliability of its database, as this can be efficiently utilized to give more precise estimates of future production. These predications can be made the basis of the policy for import and export of products like food grain or other crops, which are presently growing in the agricultural fields. Knowing the previous record of the product, as auxiliary variable, one can estimate its future production. This chapter, by constructing practical situational caricatures, emphasizes that the statistical tool like ratio analysis and regression analysis may be helpful in estimating the parameters of the variable in the agriculture field. It includes five illustrations to put forth the idea of application of statistical tools to make effective policy in the field of agriculture.
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Ratio Method Of Estimation (Ratio Estimator)

Suppose we select a random sample of size n from N units of the population with simple random sampling without replacement and wish to estimate R the population ratio of character Y to that of auxiliary variable X.978-1-4666-5146-3.ch004.m01, (1) where 978-1-4666-5146-3.ch004.m02 and 978-1-4666-5146-3.ch004.m03 are population means of characters Y & X respectively. Let the sample observations be (y1, x1), (y2, x2)… (yn, xn) and let 978-1-4666-5146-3.ch004.m04 and 978-1-4666-5146-3.ch004.m05 be the corresponding sampling means. We define the following


Also their sample estimators


Let p and r be the population and sample correlation coefficients between Y and X respectively. Then the estimator of R its bias and mean square error to first degree approximation (Sukhatme et. al. 1984) are given as

(6) and the consistent estimators of this bias and are given as:
(8) where, however, have population value978-1-4666-5146-3.ch004.m13, is known

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