Analysis of Demand for Major Spices in India
ABSTRACT India is the largest producer, consumer, and exporter of spices in the world. The demand scenario for major spices in India has been comprehensively examined in the study. The shift in preferences of domestic consumers for food items, increasing urbanization and rising incomes, altered demographic and social factors and the changes in productivity of spices have brought about changes in the pattern of their consumption and demand. A two-stage budgeting framework, which is a recent development in the theory, of demand with quadratic terms of total expenditure / food expenditure and is an appropriate technique for computing the expenditure elasticities, has been employed to work out the expenditure elasticities for spices in India. The resultant expenditure elasticities range between 0.40 and 0.60 and do not show much disparity across different income classes or regions and over the years. Also, the household consumption demand projections for important spices in the country for the years 2005, 2010 and 2015 show that the domestic demand for spices would increase further in the coming years.
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ABSTRACT: An analysis of fish consumption patterns, and how they are likely to change as income and relative price changes, is required to assess the welfare impact of technological and policy changes in the fisheries and aquaculture sectors. This analysis is based on a matrix of price and income elasticities of demand for fish by type, as fish is a heterogeneous product and consumption patterns may differ by type of product. This paper presents estimates of fish demand elasticities by fish type for Bangladesh, using individual household expenditure data (5,667 households) collected by the Bangladesh Bureau of Statistics in 1988/89. It uses a multistage budgeting framework that estimates a demand function for food in the first stage, a demand function for fish (as a group) in the second stage and a set of demand functions for fish by type in the third stage. Estimated demand elasticities vary across fish type and across income class. Among the various types of fish, carp have the highest (in absolute terms) own‐price elasticity. Income elasticities of all fish types consistently fall with the increase in per capita expenditure level of households, but none of the fish types become an inferior good at the highest income quartile. Dried fish has the lowest income elasticities for the richest quartile of the population.Aquaculture Economics & Management 01/2000; 4:63-81.
- Food production and demand in South Asia. 1-24..
- Food demand and supply projections for India. 98-01..
Agricultural Economics Research Review
Vol. 19 July-December 2006 pp 367-376
Analysis of Demand for Major Spices in India*
Shinoj P. and V. C. Mathur1
India is the largest producer, consumer, and exporter of spices in the world.
The demand scenario for major spices in India has been comprehensively
examined in the study. The shift in preferences of domestic consumers for
food items, increasing urbanization and rising incomes, altered demographic
and social factors and the changes in productivity of spices have brought
about changes in the pattern of their consumption and demand. A two-
stage budgeting framework, which is a recent development in the theory,
of demand with quadratic terms of total expenditure / food expenditure
and is an appropriate technique for computing the expenditure elasticities,
has been employed to work out the expenditure elasticities for spices in
India. The resultant expenditure elasticities range between 0.40 and 0.60
and do not show much disparity across different income classes or regions
and over the years. Also, the household consumption demand projections
for important spices in the country for the years 2005, 2010 and 2015 show
that the domestic demand for spices would increase further in the coming
Spices have been an integral part of the Indian diet, and the demand for
spices has been growing year after year. India has certain natural comparative
advantages with respect to production and utilization of spices; these include
diverse agro-climatic production environments, availability of innumerable
varieties and cultivars of each spice suitable for different climatic conditions,
cheap labour, large domestic market and a strong tradition of using spices
and their products in food, medicine and cosmetics. This is the reason that,
*The paper is drawn heavily from the M.Sc. Thesis of the first author, submitted to
the Indian Agricultural Research Institute (IARI), New Delhi in the year 2004
under the guidance of Prof. Praduman Kumar, Division of Agricultural Econom-
ics, Indian Agricultural Research Institute, New Delhi.
1Division of Agricultural Economics, Indian Agricultural Research Institute (IARI),
New Delhi -110012.
The authors thank the referee for his fruitful suggestions.
368 Agricultural Economics Research Review Vol.19 July-December 2006
in almost all the states and union territories of India, at least one spice is
grown in abundance. India is not only the largest producer but also the
largest consumer of spices in the world. There has been a steady increase
in the area and production of spices in India over the years. The annual
growth rates in area and production have been estimated to be 3.6 per cent
and 5.6 per cent, respectively for the year 2003 (Survey of Indian Agriculture,
2004). In the year 2002, the production of spices in India had reached a
level of 3.08 million tonnes on 2.60 million hectares of land (Economic Survey,
2002-03). The major contributors to the area and production of spices in the
country include chillies, ginger, turmeric, black pepper, cardamom and garlic.
India is also the largest exporter of spices, exporting 0.24 million tonnes of
spices, valued at Rs 23 thousand million (around 45 per cent by volume and
25 per cent by value of the world’s total spices trade). In addition, the
country exports spice oils and oleoresins to the global spices market. Though
these account for only 2 per cent of the country’s total quantum of spices
exports, they contribute about 24 per cent of the total export earnings from
spices (2001-02). The major proportion of the spices produced in India is
absorbed in the domestic market and only about 10 per cent is exported to
over 150 countries.
The pattern of spices production has been changing over time in different
regions. The shifts in preferences of domestic consumers, increasing
urbanization, rising incomes, demographic and social factors and the changes
in productivity of spices have brought about changes in the pattern of
consumption and hence the demand for spices. Liberalization of trade under
the WTO regime is expected to have a significant impact on the international
demand pattern of spices. Relatively little work has been done to
comprehensively study the dynamics of demand for spices in India. Hence,
the present study was undertaken specifically to (i) estimate demand model
and compute demand elasicities of spices, and (ii) project the demand for
spices in the medium-term, till the year 2015.
The study used household data on consumer expenditure and
consumption pattern from the nation-wide surveys conducted by the National
Sample Survey Organization (NSSO). Specifically, household data collected
under two major rounds of National Sample Survey (NSS) covering the
years, 1987-1988 (July-June) and 1999-2000 (July-June), numbered as 43rd
and 55th rounds, respectively were used for the study. The dietary
consumption of and expenditure on various spices in the food basket for the
rural and urban household levels falling under four income classes, namely,
Shinoj & Mathur: Analysis of Demand for Major Spices in India369
very poor (below 75% of the poverty line), moderately poor (from 75%
below the poverty line to the poverty line), non-poor low (from the poverty
line to 150% above the poverty line) and non-poor high (above 150% of the
poverty line) were used for carrying out the demand analysis.
A multi-stage budgeting framework was used for modelling the consumer
behaviour of households consuming spices (Dey, 2000; Jain et al., 1998).
The modelling was attempted in two stages (Fig. 1). In the first stage, the
household made the decision on how much of their total income was to be
allocated for food consumption, and the rest on non-food items, given their
household and demographic characteristics. In the second stage, the
household allocated a portion of food expenditure to spices consumption.
Food Expenditure Non-food Expenditure
Fig. 1. Budgeting framework for spices
Food Expenditure Function
A double log regression model was fitted the food expenditure as the
dependent variable and the variables like price of food, price of non-food,
per capita total expenditure, and other socio-demographic variables as the
independent variables. The specific model was as given in Eq. (1):
In(M) = α + γ1 ln(Pf) + γ2 ln(Pnf) + β1 ln Y + β2 (ln Y)2 + ΣθiZ
M = Per capita food expenditure
Y= Per capita total expenditure (income)
Pf = Household specific Stone price index for food
Pnf= Price index for non-food expenditure, and
Z= Socio-demographic vector (family size, year, and urban dummy).
The food expenditure Eq. (1) was estimated by the ordinary least squares
(OLS) method. The condition of homogeneity of degree zero in prices and
income was imposed by restricting γ1 + γ2 + β0 + 2β1 ln (Y) = 0 at the sample
mean of ln (Y).
370Agricultural Economics Research Review Vol.19 July-December 2006
Stone index for food was approximated using Eq. (2):
In Pf = Σ ω —
pi = Price of the ith food item.
i ln (pi) …(2)
i = Mean of expenditure share of the ith food item, and
Spice Consumption Function
In the second stage, spice consumption function in terms of quantity
was specified using Eq. (3):
Q = Per capita spice consumed in quantity
PS = Price of spices
M = Predicted per capita food expenditure from Eq. (1), and
Z = Socio-demographic vector (family size, year and urban dummy).
The spice consumption function (3) was estimated by the OLS method
by imposing homogeneity restriction of degree zero in prices and food
expenditure at sample mean of ln (M). The data used in the study belonged
to the spice consuming population and hence the consumption of spices was
The expenditure elasticity of food with respect to the total expenditure
(income) was directly obtained by differentiating the double log function
(Eq.1) as follows:
where, β1 is the expenditure elasticity of food with respect to total expenditure
Similarly, the expenditure elasticity of spices with respect to per capita
food expenditure was computed from Eq. (3):
where, β1 is the expenditure elasticity of spices with respect to food
Shinoj & Mathur: Analysis of Demand for Major Spices in India371
Finally, the expenditure elasticity of spices with respect to the total per
capita expenditure was estimated by Eq. (6):
= Expenditure elasticity of spices with respect to total expenditure
= Expenditure elasticity of food with respect to total expenditure, and
= Expenditure elasticity of spices with respect to food expenditure.
The per capita consumption demand for spices in the tth period was
calculated employing the following formulae:
dt = d0 (1 + d)t
Dt = dt × popt
= Per capita consumption demand for spices in the tth period
= Per capita consumption of spices in the base period
d= Growth in per capita spices consumption demand
= Total consumption demand for spices in the country, and
popt= Projected population of the country in the tth period.
Results and Discussion
The results of the fitted demand model for food expenditure and the
spices consumption and the expenditure elasticities estimated from these
results, along with the medium-term projections for household consumption
demand for major spices, are presented in this section.
The estimates of the parameters of the food expenditure function are
given in Table 1. The explanatory variables included in the model explained
96 per cent of the total variations in food expenditure (Table 1). The
coefficient of food price factor, as expected, was negative and statistically
significant. The coefficient of non-food price factor was positive which
explained that food and non-food commodities were substitutes. The linear-
term of per capita total income variable was positive and significant, indicating