Demand Forecasting for Consumer Non Durable Goods Like Eggs and Soaps

Topics: Regression analysis, Linear regression, Forecasting Pages: 4 (937 words) Published: April 24, 2012
DEMAND FORECASTING FOR CONSUMER NON-DURABLE GOODS LIKE EGGS & SOAP

Introduction:
Eggs are one of the popular items of food for non-vegetarians and semi-vegetarians. The present study tries to use regression technique of demad forecasting to estimate the demand fuction of eggs for Raigarh district of Chhatisgarh for various occupational groups in rural and urban areas. In this study we consider variables like size and composition of family, family income, occupation, number of earning members etc. Likewise for soaps we choose variables like growth in population and increase in per capita income for regression. Demand Forecasting for Eggs: Eggs are one of the popular items of food for non-vegetarians and semi vegetarians. We estimate demand function for eggs for Raigarh district of Chhatisgarh for various occupational groups in rural and urban areas. However we consider here the results for all groups combined. In our aggregated demand functions we consider the following variables:

1. Quantity of eggs consumed (the dependent variable),
2. Size and composition of family,
3. Family income,
4. Occupation and
5. Number of earning members in the family.
In our annual demand function we include only two variables viz., (i) quantity of eggs consumed, and (ii) per capita disposable income, for lack of data and problems of specification. The data on quantity of eggs and per capita disposable income have been taken arbitrarily for 20 years, from 1990-2010. We estimate the following forms of demand function: i) Y=a + b X (Linear)

Y= quantity of eggs consumed,
a = constant
b = intercept
X= per capita disposable income
Here we have used single equation regression model, which carries two variables one is dependent and another one independent variable.

The form equation is like this:
i) Y= 3.0085 + 0.0619 XR2 = 0.8569
(13.5301) (2.76)
The linear function gave a ‘consistently better fit to the data. From the...
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