Fitting of Engel Curve

able of Engel crape country-style Maharashtra Managerial Economics I Section D Group 6 Completed Under the Guidance of Prof. Kaushik Bhattacharya September 2011 Indian Institute of Management, Lucknow Submitted on September 5th, 2012 ? decision maker Summary This study aims to figure and analyze the family kinship between the monthly per capita expending on viands and the monthly per capita total spending for syndicates in rural Maharashtra. This relation is estimated by using the Engel Curve work which proves that as the income levels rise the percentage usance on nutrition heads decreases.The National Sample Survey Organisation (NSSO) conducted an all-India refresh of signs and unorganised service enterprises in the 63rd round of NSS during July 2006-June 2007. Surveys on consumer expenditure are being conducted once in every five days on a large sample of households from the 27th round (October 1972 September 1973). For this dispatch information from the 63rd Round of the National Sample Survey was used as a sample for depth psycho lumbery. The regression analysis was carried out using Linear, Working-Lesser and three-fold Log Models.The income breeze was careful in each case which sustain the fact that food is a necessity inviolable. Qualitative portions such as seasonality, occupation and accessible group were also incorporated into the regression analysis using close up proteans. A multivariate regression analysis revealed the expulsion of occupation as a relatively more significant factor compared to the others factors. The analysis is subject to certain limitations due to the assumptions made with the most immemorial assumption being that the total expenditure on all goods is interpretive program of the income of the individual.Other limitations arising out of the content of the survey fix also been listed. Contents Executive Summary2 Introduction4 Understanding the Data6 Data Collection6 Data processing6 cash in ones chips Formulation6 relapse Analysis7 ? Introduction The spirit of a particular good can be determined by an important parameter known as Income elasticity which helps us classifying the good as either inferior, a necessity or luxury. This parameter allows us to predict what goods will be determined by a hostel during various stages of development and provide insights into the behaviour of various sections of society to that good.In nows economic scenario Income elasticity of food in particular is of study significance. From a production perspective, it is important to determine the relationship between the food expenditure and income. This will help in predicting the demand in a growing economy and thus reduce the demand-supply gap. Form a insurance policy perspective, the income elasticity becomes all the more important as government aims to have an inclusive development. Knowing the income elasticity with respect to food expenditure will help in framing policies which fulfi l their aim of better economy.Income elasticity can be estimated empirically through Demand curves and Engel Curves. Engel curves describe how household expenditure on particular goods or services attends on household income. The name comes from the German statistician Ernst Engel (18211896) who was the first one to investigate this relationship systematically in an article published about 150 years ago. The best-known single result from the article is Engels law, which states that the poorer a family is, the larger the budget fate it spends on nourishment.Engel curves may also depend on demographic variables and other consumer characteristics. Empirical Engel curves are close to bilinear for many goods, and highly nonlinear for others. Engel curves are used for equivalence scale calculations and related welfare comparisons, and determine properties of demand systems such as agreeability and rank. Engel curves for public goods Engel curves for inferior goods The relationship b etween the food consumption and income on the Engel Curve has been analysed through various models, each with its own benefits.The three models used in this study are 1. Linear Regression Model It assumes a linear relationship between the two variables. It uses the equation Y = A0 + A1X. The elasticity is calculated through this model using the equation ? = ( X/Y) dy/dx = (X/Y) A1 2. Working-Lesser Model This model uses the equation Wi=A0+AilnX. Working-Lesser Model is the first empirical model employ in the study of consumption analysis In the Working-Leser model, each share of the food item is simply a linear function of the log of prices and of the total expenditure on all the food items under consideration.Here i represents each food items , wi is the expenditure share of food i among the n food items and x is the total expenditure of all food items include in the model. This model can be estimated for each food item by the ordinary. 3. Double Log Model This model assumes linea r relationship between logarithms of the dependent and commutative variable. The greatest benefit of this relationship is that the coefficients of the income variable directly represent the income elasticity. Its equation is lnY = A0 + A1 lnX.The elasticity is directly available as the co-efficient of the independent variable i. e. ?= A1. Understanding the Data Data Collection The selective information collected by The National Sample Survey (NSS), during its 63th round of selective information collection during July 1st 2005 to 30th June 2006, has been used in this project. The survey contained info regarding the expenditure of a on various items such as food, clothing, medical, alcoholic beverage etc. It also contains demographic information about each family pertaining to the religion, set, occupation, age, come alive etc. The survey is divided into two samples for data validation.We first canvass both the samples individually and then combined them to verify the validity o f the results obtained. Data processing We calculated the per capita total expenditure on food for 1702 families from Rural Maharashtra. Instead of income, which wasnt available, we calculated and used the monthly per capita total expenditure for each family to find the Engel Curve. The consumption of food of a family can depend on numerous variables. The variables that we included in our analysis are the social group or caste, occupation and seasonality. The factors which were excluded are__________________________.Rural Maharashtra is fairly homogenous and hence the vicinity or district of the respondent wasnt considered as a variable. Function Formulation We did a multivariate regression where the monthly per capita expenditure was the independent variable (i. e. X) while the per capita food expenditure was the dependent variable (i. e. Y). The factors of seasonality, caste and occupation were taken as dummy variables as they have scarce a qualitative and not a quantitative eff ect. ValuesDummy Variables SeasonalityJul-Sep, Oct-Dec, Jan-Mar, Apr-Jun CasteSC/ST, OBC, Others Occupation Self-Employed, honorarium/Wage Earning,Casual Labor, Others Monthly per capita food expenditure = f (monthly per capita total expenditure, dummy variables) This functional form was used to model the various regression models viz. linear regression, double log regression and the working-lesser form. Weighted least shape method was used to factor in the weights assigned to each household. Regression analysis was carried out for using the SPSS tool which was also used for extracting data from the flat file. A scatter plot of food versus total expenditure was also plotted to prove the Engels law. Regression Analysis