Food Price Elasticities from Household Survey Data in...

Journal of Emerging Issues in Economics, Finance and Banking (JEIEFB) An Online International Monthly Journal (ISSN: 2306-367X)

Volume:2 No.2 August 2013

655

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Food Price Elasticities from Household Survey Data in India: An

Application of Single Equation and System Demand Models

James L.T. Thanga

Department of Economics,

Mizoram University, Aizawl,

Mizoram, India.

E-mail: [email protected]

________________________________________________________________________

Abstract

The effectiveness of any policy measure to control food prices, especially subsidy, should depend

on the recognition and knowledge of the structure of food demand. This paper intends to analyse

food consumption patterns from household survey data and the performances of single equation

and system demand models. Un-tabulated NSS data for Mizoram State, India, has been analysed

using Working-Lesser (WL) and Almost Ideal Demand System (AIDS) models. It was found that

all food items have negative own price elasticities supporting the proposition of the traditional ‘law

of demand’. The two demand models showed slightly different results in respect of cross price

elasticities, and it was concluded that WL model could be successfully adopted to analyse even

small sample survey data as its admits frequency weigh. At the same time, AIDS model provides

more comprehensive results because it takes into account all desirable properties of demand

system; however, its computational complication setbacks its universal applicability.

________________________________________________________________________ Key words: Elasticities, food, demand, AIDS, cross price.

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1. Introduction

The rapid increase in prices of rice, wheat, corn and other food staples has sent a shock wave

through poor households around the world, as well as through governments and international policy

makers. While food prices are always volatile, recent increases are of a magnitude last seen in the

1970s (Polaski, 2008). India is among the developing countries which are seriously affected by the

rise in food price. Food prices remains the major political issues of the country till today since the

rising food price seriously affected the poor and is even considered as a ‘political good’

(Pangaribowo and Tsegai, 2011). Therefore, controlling the prices of food items would have

significant impact in an attempt to reduce poverty and hunger in the country. At the same time, the

effectiveness of the public policy measures on the control of food prices, especially subsidy, should

depend on the recognition and knowledge of the demand structure while formulating such policies.

That is, it is important for public policy to be well informed on how consumers change their

expenditure in response to changes in prices and income level. Thus, an in-depth analysis of food

demand provides better insights about important factors such as prices, including prices of related

goods, and income that will affect food consumption.

The knowledge of demand structure and consumer behaviour is essential for a wide range of

development policy questions like improvement in nutritional status, food subsidy, sectoral and

macroeconomic policy analysis, etc., (Mittal, 2006). It is understood that various demand models

give different results for food demand, price elasticities in particular. Meanwhile, the market

demand structures are generally analysed using time series data (Thanga, 2010); while the

household demand structures are usually analysed using survey data by fitting the functional

relationship between expenditure on particular item and total expenditure or income. So, household

consumer expenditure survey data is usually used to study the pattern of household expenditure

with the changes in income level, without taking into consideration the effect of prices. So, it is

tried, in this paper, to analyse and evaluate the performances of single equation and system demand

models to explain household food demand pattern using cross sectional survey data in the state of

Mizoram, India. The entire analysis being made in this paper is based on the un-tabulated primary

data of the various rounds of the National Sample Survey Organization (NSSO), Ministry of

Statistics and Programme Implementation, Government of India. The pertinent question that needs

to be answered, in using survey data to analyse household food demand pattern, is whether price

variations can be obtained from these surveys to estimate a complete demand system (Koç and

Alpay, 2000). However, Deaton (1988) states that these household surveys contain information on




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the spatial distribution of prices, and thus, by covering this information in a useful form one can

easily obtain the impact of prices on quantity demanded. The rest of the paper is organized as

follows, Section-II: overview of related literature, Section – III: Methodology, Section-IV: results

and discussion, and Section-V: conclusion.

2. Overview of Related Literature

Different food demand patterns have evolved on account of different socio-economic,

demographic and institutional factors. These differences within a food distribution network can be

detected from the values of various food price and expenditure elasticities (E. Erjavec, et.al, 1998).

Broadly, two basic approaches are used in demand analysis. The first is the traditional one, which

is based on the estimation of Engel curves where food expenditure and income elasticities are

subsequently derived. Another way to perform econometric estimation is to construct a demand

system and from it to compute uncompensated (Marshallian) price and compensated (Hicksian)

and expenditure elasticities.

Since the pioneering work of Engel in 1857, the estimation of Engel curves and expenditure

elasticities has been an important part in family budget studies with estimated expenditure

elasticities having been the main behavioural parameter. The Log-Linear, or sometimes called

Double-Log (DL) function, has been the most commonly adopted functional form to estimate

Engel’s curve and found its place in the study by Stuvel & James (1950), Houthakker (1957),

Iyengar (1960), Liviatan (1964), Theil (1965), Iyengar, et al (1968), NSS, Bhattacharya (1973),

Coondoo, et al (1981). The apparent advantages of log-linear Engel’s curve over any other

functional form is its assumption of constant elasticity of expenditure and the possibility of

introducing an additional variables, generally family size, enabling the estimation of economies of

scale in consumption. However, the general problem with this approach to household demand is

model misspecification due to the exclusion of price terms and other demographic factors affecting

food demand. Consequent upon the theoretical limitations of the traditional Engel’s curve, there

come a number of attempts to reconstruct the demand model. The new models give emphasis on

utility-based approaches as a system of equations which satisfies the condition of adding-up, non-

negativity of consumptions, etc. The Working-Leser (WL) model proposed by Working (1943) and

Leser (1963) and the almost ideal demand system (AIDS) of Deaton and Muellbauer (1980) have

become the most popular new demand models, the former being single equation while the latter is

considered as system model.




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WL model relates budget shares linearly to the logarithm of total household expenditure and

other variables of logarithm of prices and demographic dummy variables like age of household

head, log of family size, number of wage earners, regional dummy, etc. This model was used by

Chern, et.al (2002), Castaldo and Reily (2007), Tey, et. al (2008), Tey, et.al (2007), Lippe, et.al

(2010). Being a system model, AIDS model ensures flexibility and the model automatically

satisfies the adding-up restriction, non-negativity of expenditure, and with simple parametric

restrictions, homogeneity and symmetry can be imposed (Maschini, 1998). AIDS model has

attracted the attention of many researchers since 1980. Buse (1994) reported that during 1980-91

as many as 89 empirical works used the AIDS demand studies. These include Baharumshah and

Mohamed (1993), Mustapha (1994), Brester and Schoebet (1995), E.Erjavec, et.al (1998),

Mustapha, et.al (1999, 2000), Tey et.al (2007), Wadud (2006), Chern, et. al (2002), Xu and Veenam

(1996), Mittal (2006), Wadud (2006), Bopape (2006), Tey, et al., (2008), Mittal (2006), Chatterjee,

et al., (2007).

3. Methodology

3.1 Data Source

The whole analysis is based on the ungrouped primary data of National Sample Survey (NSS)

and the study used the consumer expenditure survey data of the 45th, 51st, 55th, 61st and 66th NSS

Rounds covering the period of 1989-90, 1994-95, 1999-00, 2004-05 and 2009-10 respectively.

Price for each food item was worked out by dividing the total monetary expenditure by total

quantity consumed. However, there are some food items which have no data on quantity

consumption, resulting in our inability to determine their prices. So, it was decided to drop all these

items, and finally, only 6 items were included in the analysis, namely, cereals, edible oils, pulses

& products, salt, spices and sugar.

3.2 Analytical Methods

Two models are adopted in the study, namely, Working-Leser (WL), i.e. single equation model,

and Almost Ideal Demand System (AIDS), i.e. system model. They are given as follows:

0

log logi i ij j ik k i

j k

w x p H

(WL Model) Eq. (1)

log( ) log , 1,2,....,11i i ij j j i

j

xw p u i

P

(AIDS Model) Eq. (2)




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where (i,j) = food items, iw = expenditure share of food i among six food items, jp = price of

food j, x = total expenditure on all food items, P = price index, Hk includes other variables like log

of household size and regional dummy (urban or rural) and i ’s & uj are random disturbances. The

following restrictions were imposed while estimating AIDS Model:

1i

i

w for all j; * *1

( ) , 1,...112

ij ij ji ji j

1, 0 0i i kj

i i k

and

As the price index in Eq.(2) raises the estimation difficulties due to non-linearity in

parameters, Stone index is widely used for AIDS estimation (Asche and Wessel, 1997).

Present study also adopt Stone index so that the model may be called Linearly

Approximated AIDS model (LA-AIDS). The Stone index is given by

*log( ) log( ) 1,..11.i i

i

P w p i Eq. (3)

where w is budget share among six selected commodities. The Stone index is an

approximation proportional to the translog, i.e. *P P where 0(log ))E . The AIDS

model with the Stone index can be seen as follows:

*

*log( ) logi i ij j j i

j

xw p u

P

Eq. (4)

where * * (log( ) (log( )))i i i i i i iand u u E .

Expenditure and price elasticities corresponding to these models are:

i) Expenditure Elasticities:

WL Model :

1 ii

i

ew

AIDS Model : 1

1 1log( )

i ii

i i

we

w x w

ii) Price Elasticities:

WL Model : ij

ij ij

i

ew




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AIDS Model :

1,..ij i

jij ij

i i

e w i nw w

where ij is the Kronecker delta that is unity if i=j and zero otherwise. AIDS model was

estimated by Full Information Maximum Likelihood Method (FIML) and the sample means were

adopted to be the point of normalization.

4. Results and Discussion

4.1 Expenditure Elasticities

Table 1 shows expenditure elasticities for six food items calculated from WL and AIDS models.

Cereals have shown unitary elasticities for both models that percentage expenditure for this item

would increase at the same rate as the increase in income level. In view of the high budget share,

this item shows itself to be the staple food item of the study area whose demand would have been

inelastic. So, the magnitude of this elasticity may be taken to reflect the weak purchasing power of

the people to purchase even their basic necessities of life. It may also be stated that large proportion

of the population in rural areas are rearing livestock and are feeding their animal with rice and

wheat; and hence, this may led to the increasing expenditure with the increase in income level.

Table: 1 Expenditure Elasticities of Demand

Items Average Budget Share+ (%) WL Model AIDS Model

Cereals 62.04 1.00** 1.0233

Edible Oils 13.5 1.19** 0.8661**

Pulse & Products 10.5 0.95** 0.8121**

Salt 1.2 0.63** 0.6759**

Spices 5.23 1.11** 1.2369**

Sugar 7.54 0.66** 0.8508** +percentage share in the total expenditure of the six items included in the model **Significant at 5% level of significance

As expected, the calculated expenditure elasticity is found to be lowest in case of salt for both

models for being the most inelastic items of consumption; while spices are most volatile with

respect to price change as its elasticities are more than unity for both models. Thus, spices may be

taken as superior items whose consumption tended to increase with the increase in income levels.




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It may be noted that normal goods are those whose demand (expenditure) increases with the

increase in income levels but less than proportionately; while demand are increasing more than

proportionately with the increase in income levels for superior goods. Meanwhile, the two models

(WL and AIDS) showed different elasticities in respect of edible oils. That is, it may be called

superior good in case of WL model while it is normal for AIDS model.

4.2 Own Price Elasticities

By own price elasticity we mean the changes in quantity demand of a commodity due to a

change in its price. Estimating the own price elasticities for various food items will enable us to

assess the sensitivity of the consumption or demand for particular item on the price change. The

estimates of Marshallian own price elasticities for both models are given in Table 2. The own price

elasticities are all found to be negative as expected for both WL and AIDS models. That is, there

is an inverse relationship between quantity demand and its own price for all items under

consideration in conformity with the traditional ‘Law of Demand’. For WL model, the value of

elasticity is found to be lowest for cereals followed by salt; while it is highest in case of spices

followed by edible oils. At the same time, for AIDS model, the absolute value of price elasticities

is lowest for pulse & products while it is highest for cereals. In a nutshell, all six food items

considered in the study are highly volatile, spices being the most volatile, with respect to price

change. Any increase in food price would result in significant decrease in its demand/consumption.

Table: 2 Estimated Marshallian Own Price Elasticities of Demand

Items Average Budget Share+ (%) WL Model AIDS Model

Cereals 62.04 -0.7803** -0.8933**

Edible Oils 13.5 -0.93908** -0.8564**

Pulse &

Products 10.5 -0.86492** -0.7497**

Salt 1.2 -0.83123** -0.8347**

Spices 5.23 -1.02415** -0.8562**

Sugar 7.54 -0.87916** -0.8266**

+percentage share in the total expenditure of the six items included in the model

**Significant at 5% level of significance

4.3 Cross Price Elasticities

The sensitivity of the demand for one commodity to a change in the price of other commodities

is known as cross price elasticities. Analysis of the cross price elasticities is very useful in

determining the nature of goods and services for their substitutability and complementarity. So, an




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attempt is made here to study the nature of cross price elasticities for the six food items being

considered in the analysis. If cross elasticity for two goods are negative, they are said to be

complementary; while they may be called competitive or substitutes if they have positive cross

elasticities. The results are shown in Table 3 and Table 4 for WL and AIDS models respectively. It

is found that cross price elasticities are significantly lower than own price elasticities for all items

and the cross price elasticities of demand are all below 10 percent of the total price variation. So,

prices of other food items do not have much impact upon the demand of the commodity in question,

and hence, own price remains the main determinant of food demand in the study area.

Table: 3 Estimated Own and Cross Price Elasticities (WL Model)

Items Cereals Edible Oils Pulses Salt Spices Sugar

Cereals -0.78030** -0.00864** -0.03963** -0.02481** 0.00782** -0.02208**

Edible Oils -0.93908** 0.07714** 0.02066** 0.02112** 0.00952**

Pulse & Products -0.86492** 0.04246** -0.00789** 0.04339**

Salt -0.83123** -0.04767** 0.04637**

Spices -1.02415** 0.02278**

Sugar -0.87916**


Table: 4 Marshallian Cross Price Elasticities, after imposing symmetric restriction ( AIDS Model)

Items Cereal Edible Oils Pulse Salt Spices Sugar

Cereal -0.0304** -0.0384** -0.0057** -0.0219** -0.0390**

Edible Oils 0.0504** -0.0063** 0.0176** 0.0311**

Pulse & Products -0.0053** 0.0153 0.0445**

Salt -0.0624** 0.0530**

Spices -0.0349**


The above tables showed slightly different result on the nature of cross price elasticity that edible

oils are competitive with pulses, salt, spices, and sugar for WL model; while it is complementary

to salt in case of AIDS model. First, in WL model, pulses is competitive to salt and sugar; while it

is complementary with spices, and, cereal is substitute items to all other food items except sugar.

Similarly, salt is found to be complementary to spices while it is substitute with sugar, and, spices




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are complementary to sugar. Second, in AIDS model, cereal is found to be competitive with the

remaining food items, and pulse is complementary with salt; while it is competitive with salt and

sugar. Further, salt is complementary to spices; while it is competitive to sugar and spices is also

found to be competitive items to sugar.

5. Conclusion

The analysis of expenditure elasticities shows that the item groups of cereals and spices have

characteristics of normal goods whose consumption tended to increase with the increase in family

income. It may be argued that the population at lower income bracket has been stayed away from

consuming spices and even for their staple food, i.e. cereals, which have shown volatility in the

face of price rise affecting the family’s real income. This phenomenon can also be taken to reflect

the improverishment of the society which cannot afford to make certain food items universally

accessible.

All food items considered in the analysis are found to have negative own price elasticities

supporting the proposition of the traditional ‘law of demand’. The result shows that food demands

in the study area are significantly sensitive to the changes in prices that, specifically, any 10 percent

increase in food price would result in the reduction of its consumption by more than 6 percent. The

result, therefore, suggests controlling prices for food items shall have unequivocal impact upon the

standard of living, especially, of the relatively poorer sections of the society, and which will

indirectly results in the reduction of poverty ratio.

Two models, Working-Leser (WL) Model and Almost Ideal Demand System (AIDS) Model,

applied in the study to analyse food demand from household survey data have shown their own

advantages and disadvantages. As it takes into account the effects of income, prices, and other

demographic factors in estimating individual demand function, WL model shows its wide

applicability in demand analysis with impressive goodness of fit. Like any other single equation

model its estimation ensures the possibility of applying frequency weight, which is usually

generated in a systematic survey by various survey organizations. This enables us to have better

estimates even in case of small sample. However, its theoretical limitation to take into account

certain desirable properties of demand models, including adding-up, symmetry, homogeneity, etc,

impedes its wider applications in advanced empirical research. AIDS model being more flexible

nature, which satisfies all these theoretical requirements, has attracted the attentions of many

researchers. However, its inappropriateness to lend itself suitable for applying frequency weight




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usually leads the results of test for small sample size to be insignificant. Further, its computational

complicacy should have also been a serious setback for its application.

Acknowledgement

The author acknowledged the financial support of the Indian Council of Social Science Research

(ICSSR), Ministry of Human Resources, Government of India, for the study.

References

Alston, J.M, Kenneth, A.F and Green, R.D (1994), ‘Estimating Elasticities with the Linear

Approximate Almost Ideal Demand System’, Economic Letters 71: 351-56.

Asche, F. and Wessels, C.R (1997), ‘On Price Indices in the Almost Ideal Demand System’,

American Journal of Agricultural Economics, 79: 1182-85.

Baharumashah, A.Z. (1993), ‘Applying the Almost Ideal Demand Systems to Meat Expenditure

Data: Estimation and Specification Issues, Malaysian Journal of Agricultural Economics, 10.

Blundell, R., Duncan A and Pendakur, K (1998), ‘Semiparametric Estimation of Consumer

Demand’, Journal of Applied Econometrics 13: 435-461.

Blundell, R., Pashardes, P and Weber, G (1993), ‘What do we learn about consumer demand

patterns from Micro data?, American Economic Review, 83: 570-597.

Bopape, L (2006), ‘Heterogeneity of Household Food Expenditure Patterns in South Africa’,

Selected Paper prepared for presentation at the American Agricultural Economics Association

Annual Meeting, Long Beach, California, July 23-26, downloaded from

http://ageconsearch.umn.edu/bitstream/21300/1/sp06bo03.pdf on 23.08.2009.

Bryne, P., Capps, O and Saha, A (1996), ‘Analysis of Food Away from Home Expenditure Patterns

for US Households’, American Journal of Agricultural Economics, 78: 614-627.

Buse, A (1994), ‘Evaluating the Linearized Almost Ideal Demand System’, American Journal of

Agricultural Economics, 76: 781-793.

Chern, S Wen; Kimiko Ishibashi; Kiyoshi Taniguchi and Yuki Tokoyama (2002), Analysis of Food

Consumption Behaviour By Japanese Households, Food and Agriculture Organization, Working

Paper No.0206/2002, downloaded from www.fao.org/es/esa on 6.07.2007.

Chung, Rebecca; Jonq-Ying Lee, & Mark G. Brown (2002), An Engel Curve Analysis of Household

Expenditure in Taiwan: 1996-98, Economic and Market Research Department, Florida Department

of Citrus, downloaded from http://econpapers.repec.org/paper/agsfdcr05/53388.htm on 01.06.2012

Coondoo, Dipankor (1969), ‘The Effect of Relative Prices on Engel Elasticity of Cereals in India’,

Arthaniti, Vol.12.


http://ageconsearch.umn.edu/bitstream/21300/1/sp06bo03.pdf%20on%2023.08.2009

http://www.fao.org/es/esa%20on%206.07.2007

http://econpapers.repec.org/paper/agsfdcr05/53388.htm%20on%2001.06.2012



665


Deaton, A.S. (1988), ‘Quality, Quantity, and Spatial Variation of Price’, American Economic

Review, 78: 418-30.

Deaton, A.S. (1990), ‘Price Elasticities from Survey Data: Extensions and Indonesian Results’,

Journal of Ecnometrics, 44(3):281-309.

Deaton, Angus., Parikh, Kirit and Subramaniam, Shankar (1994), ‘Food Demand Pattern and

Pricing Policy in Maharashtra: An Analysis Using Household Level Survey Data’, Sarvekshana,

October-December:11-34.

Deaton, A.S. and Muellbauer, J (1980), ‘An Almost Ideal Demand System’, American Economic

Review, 70: 312-326.

Directorate of Economics & Statistics (2009), Statistical Abstract of Mizoram: 2009, Government

of Mizoram.

Erjavec, E., Mergos, G.J., Mizzi, L and Turk, J (1998), ‘Food Demand in Slovenia’, Die

Bodenkultur, 49(4), downloaded from http://www.boku.ac.at/diebodenkultur/volltexte/band-

49/heft-4/erjavec.pdf on 01.06.2012

Green, R. and Alston, J.M (1990), ‘Elasticities in AIDS Models’, American Journal of Agricultural

Economics, 72: 442-45.

Houthakker, H.S. (1952), ‘Compensated Change in Quantities and Qualities Consumed’, Review

of Economic Studies, 19: 155-64.

Houthakker, H.S (1957), ‘An International Comparison of Household Expenditure Patterns,

Commemorating the Centenary of Engel's Law’, Econometrica, 25(4): 532-551

Intrilligator, Michael., Bodkin, Ronald and Hsiao, Cheng (1996), ‘Application to Households:

Demand Analysis’, in Econometric Models, Techniques, and Applications, New Jersey; Prentice-

Hall.

Iyengar, N. Sreenivasa (1960), ‘On a Method of Computing Engel Elasticities from Concentration

Curves’, Econometrica, 28(4): 882-891.

Koc, Ali and Alpay, Savas (2000), ‘Household Demand in Turkey: An Application of Almost Ideal

Demand System With Spatial Cost Index’, Ankara, downloaded from

http://www.erf.org.eg/CMS/uploads/pdf/1185354701_FM-B_Koc_&_Alpay.pdf on 01.06.2012

Lippe, Rattiya Suddeephong and Isvilanonda, Samporn (2010), ‘Food Demand Elasticities among

Urban Households in Thailand’, Thammasat Economic Journal, 28(2): 1-29.

Leser, C.E.V. (1963) ‘Forms of Engel Functions’, Econometrica, 31: 694-703.


http://www.boku.ac.at/diebodenkultur/volltexte/band-49/heft-4/erjavec.pdf%20on%2001.06.2012

http://www.boku.ac.at/diebodenkultur/volltexte/band-49/heft-4/erjavec.pdf%20on%2001.06.2012

http://www.erf.org.eg/CMS/uploads/pdf/1185354701_FM-B_Koc_&_Alpay.pdf%20on%2001.06.2012



666


Mittal, Surabhi (2006), Structural Shift in Demand for Food: Projections for 2020, Indian Council

for Research On International Economic Relations, Working Paper No. 184, downloaded from

http://dspace.cigilibrary.org on 10.01.2012.

Moschini, G. (1995), ‘Units of Measurement and the Stone Index in Demand System’, American

Journal of Agricultural Economics, 77:63-68.

Moschini, G. (1998), ‘The Semiflexible Almost Ideal Demand System’, European Economics

Review, 42: 346-64.

Mustapha, R.A. (1994), ‘Incorporating Habit in the Demand for Fish and Meat Products in

Malaysia’, Malaysian Journal of Economic Studies, 31(2): 25-35.

Pangaribowo, Evita Hanie and Tsegai, Daniel (2011), Food Demand Analysis of Indonesian

Households with Particular Attention to the Poorest, Zentrum für Entwicklungsforschung (ZEF),

downloaded from http://www.zef.de/fileadmin/webfiles/downloads/zef_dp/zef_dp_151.pdf on

1.06.2012

Planning & Programme Implementation (2011), Economic Survey Mizoram 2010-11, Government

of Mizoram.

Polaski, Sandra (2008), ‘Rising Food Prices, Poverty, and the Doha Round’, CARNEGIE,

downloaded from http://www.carnegieendowment.org/files/polaski__food_prices.pdf on

1.06.2012

Pollak, R. A. and Wales, T.J (1980), ‘Comparison of the Quadratic Expenditure System and

Translog Demand Systems with Alternative Specifications of Demographic Effects’,

Econometrica, 48: 595-612.

Pollak, R. A. and Wales, T.J (1981), ‘Demographic Variables in Demand Analysis’, Econometrica,

49: 1533-1551.

Prais, S.J. and Houthakker, H.S (1955), The Analysis of Family Budgets, Cambridge University

Press.

Prasad, A.R (2001), Consumption Behaviour in India: Theory and Evidence. Reliance Publishing

House, New Delhi.

Sinha, R.P (1966), ‘An Analysis of Food Expenditure in India’, Journal of Farm Economics,

48(1):113-123.

Stone, J. (1954), ‘Linear Expenditure Systems and Demand Analysis – An Application to the

Pattern of British Demand, Economic Journal, 64:511-27.


http://dspace.cigilibrary.org/

http://www.zef.de/fileadmin/webfiles/downloads/zef_dp/zef_dp_151.pdf%20on%201.06.2012

http://www.zef.de/fileadmin/webfiles/downloads/zef_dp/zef_dp_151.pdf%20on%201.06.2012

http://www.carnegieendowment.org/files/polaski__food_prices.pdf%20on%201.06.2012

http://www.carnegieendowment.org/files/polaski__food_prices.pdf%20on%201.06.2012



667


Thanga, L.T, James (2010), Consumer Behaviour in North-East India, Anshah Publishing House,

New Delhi, 2010.

Tey, Yeong-Sheng, Shamsudin, et. al (2008), Demand Analysis of Food in Malaysia: Effects of

Model Specifications and Demographic Variables, MPRA, downloaded from http://mpra.ub.uni-

muenchen.de/15063/ on 10.01.2012.

Theil, H. (1965), ‘The Information Approach to Demand Analysis’, Econometrica, 33:67-87.

Wadud, Md Abdul (2006), ‘Analysis of Meat Demand in Bangladesh Using Almost Ideal Demand

System’, The Empirical Economics Letter, 5(1); 29-35.

Working, H. (1943), ‘Statistical Laws of Family Expenditure’, Journal of the American Statistical

Association, 38:257-74.


http://mpra.ub.uni-muenchen.de/15063/

http://mpra.ub.uni-muenchen.de/15063/

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