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Reaching the rural poor: India's experience with the public distribution of food grains

Shanti Bapna


The main purpose of providing subsidized food through the Public Distribution System (PDS) in India is to improve household-level food security by insulating the poor and undernourished from increases in prices and by increasing their purchasing power. If managed efficiently, the programme of subsidies could be more effective in enhancing the nutritional status of the poor than employment and other income-transfer programmes. This is because the subsidy not only increases income levels by making food accessible to the poor but also increases the probability of higher food intake, given the high transaction costs for resale [1; 2]. This is especially true if the quantity of grains supplied at subsidized prices is less than existing consumption levels [3]. However, to be effective and cost-efficient, the food programme must correctly identify the target groups and their needs, and select the appropriate commodities, prices, and marketing channels. Unfortunately, programmes in most countries have been untargeted and have had several design limitations. These subsidies are very expensive, although politically palatable and easy to administer.

The PDS has evolved over the last 50 years, beginning with the Second World War, when rationing of food grains was introduced. The present gigantic system has a network of more than 3.6 million private and cooperative "fair-price shops," which annually distribute about 30 million tons of grains and other commodities, including sugar and edible oil. Almost the entire Indian population is covered. Food grains have generally been procured by a special organization, the Food Corporation of India, and are distributed to different state governments at the recommendation of the national government.

A review of the programme [4] showed that until the mid-1970s it had an urban bias [5] and was untargeted; rural areas were largely ignored in most states. (This is evident from the fact that even the basic information on the number of fair-price shops in rural areas was not available until the early 1980s, and detailed information on the quantity of grain distributed is still not available.) Appreciation of the large number of poor in rural areas led to increased attention to these areas. By the end of the 1980s almost the entire rural population was covered, at least by the setting up of fair-price shops. However, the programme lacked clarity of purpose, with implementation often occurring on an ad hoc basis [6]. Furthermore, commodity selection and distribution arrangements were such that the objective of helping the poor was not met effectively. Generally, only wheat and rice were distributed, although these are not staple grains in several areas. Thus, although the programme has evolved over 50 years, it is not clear to what extent it has achieved its objectives.

From time to time concern about the effectiveness of the PDS in reaching the poor has been voiced by policy makers and researchers, particularly in light of the mounting subsidy burden (or more accurately, fiscal cost)t to the government of India (currently, about 25 billion rupees, a significant amount for a low-income, resource-poor economy). Unfortunately, adequate knowledge about the programme's costs, benefits, and effects on different socio-economic strata and on macroeconomic variables is not available. A review of the available literature [4] showed that previous studies generally relied on small samples, the sample frames did not include households not registered in the programme, and they covered a small reference period, often only a week or a month. Moreover, they did not adequately explain the constraints faced by the PDS and by different consumer income groups. (Not many empirical studies have evaluated the PDS, prices, wages, etc. Only one in the 1960s, three from the 1970s, and five from the 1980s were available. Some of the recent ones are still in the prepublication stage.)

The available studies provide conflicting evidence on the use of the PDS by the poor. George [7] found that the poor took relatively more advantage of the programme than did the rich. According to Kumar [8], middle-income groups were in a better position to take advantage of the benefits. Singh [9] observed that middle- or upper-middle-income population groups in urban areas received more benefits from the programme. Recent surveys had large sample sizes and provided information on the extent of participation, but did not explain variations in the use of the PDS by different income groups [10; 11]. Nevertheless, Scandizzo and Swamy [12] found a positive cost-benefit ratio for the PDS, and George [7] found a positive impact on income distribution and nutrition levels for the poor in Kerala, but these results have limited relevance and are at best illustrative.

In view of the conflicting and inadequate evidence, there is an obvious need for further empirical studies to determine the extent of benefits to the poor in order to redesign a more efficient PDS. The study reported below attempts to explain the behaviour of consumers from different socio-economic groups with respect to their participation in the PDS.


Study design


The specific objectives of the study were to examine the behaviour of a cross-section of consumers in rural areas vis--vis the operations of fair-price shops and the benefits derived from the PDS and to identify the constraints faced by a cross-section of the rural poor in obtaining access to the PDS.



Poor households do not take full advantage of the PDS, whereas the non-poor receive more benefits. This is because:



Although a major initiative for the PDS has come from the government of India, the programme's implementation in a federal political structure is carried out by the state governments. In view of the differences in approaches to the PDS at the state level, 3 states out of 22-Andhra Pradesh, Maharashtra, and Rajasthan-were selected to provide three different topologies of PDS operations. Beginning in April 1983 the poor households were issued green cards entitling them to rice at Rs 2 per kilogram, compared with more than Rs 3.5 in the market and more than Rs 3 rupees in cost to the government. The non-poor were issued yellow cards, on which only a general subsidy was given. Thus, the state provided a means of examining the targeting of the subsidies.

Andhra Pradesh has a surplus of food grains and is a major rice-consuming state. Maharashtra and Rajasthan are major consumers of coarse cereals. However, Rajasthan is generally self-sufficient in food grains except in drought years, whereas Maharashtra has a deficit. (Agricultural production in the three states was below normal during the reference period of the study, December 1987-December 1988.) In addition to coarse cereals, in Maharashtra rice is important, and in Rajasthan wheat is a staple. The Maharashtra state government has procured coarse cereals for distribution to consumers, but the Rajasthan government generally restricts its operations to the commodities supplied by the federal government, usually wheat and rice.

Because of time constraints, only four villages were studied, but they were selected so that a representative picture of the operations of the PDS would emerge. One village each was selected in Andhra Pradesh and Rajasthan, and two were selected in Maharashtra to capture the effect of two separate schemes (one village had the general subsidy and the other a higher subsidy under the Integrated Tribal Development Programme, or ITDP). These villages were Mac-ram in Andhra Pradesh, K. Gaon (the ITDP village) and P. Gaon in Maharashtra, and Dhulia in Rajasthan. P. Gaon did not have a fair-price shop, so consumer access was constrained by having to travel to a nearby village.

The selection of 40 households from each village was made by a random sampling method after house-holds had been stratified according to land worked and occupation. Households were classified as labourers; marginal, small, and large farmers (since farm size varies in the different states, the classification of households as marginal, small, and large was adjusted to make them economically comparable in all the sample villages); and "others"-including village artisans, traders, and salaried and fixed-income households. Ten households each were selected from the categories of labourers, marginal farmers, and small farmers and five each from large farmers and "others." Some of them were subsequently reclassified because of reported changes in land holdings.

Information was collected from the households on consumption, purchases from the fair-price shop and open markets, and problems faced in getting access to the PDS. Interviews were conducted six times in each household, spread over 13 months in order to examine the behaviour of consumers in different seasons. Behaviour with respect to the PDS was examined by cross-tabulations of survey data and by a regression model. Operators of the fair-price shops in or closest to each of these villages were interviewed for information about their operations and constraints. Information on policy, management, and programme implementation was collected in discussions with PDS officials and from policy documents.


Salient features of the sample


The three selected states differed not only in types of PDS but also in their demographic and socioeconomic environments. Rajasthan is sparsely populated, having just 100 persons per square kilometre, compared with almost twice this number in each of the other two states (table 1). Road density is also very low (163 metres per square kilometre). The urban population in Rajasthan was just one-fifth of the total population of the state, whereas in the industrially developed state of Maharashtra, where the city of Bombay is located, more than one-third of the population lived in urban areas. The literacy rate in Rajasthan, particularly in rural areas, was much lower (18%) than in Maharashtra (38%). The backward caste population in Rajasthan was as high as 29%, compared with only 16% in Maharashtra and 21% in Andhra Pradesh. Agricultural labourers as a percentage of the total working population in rural Rajasthan were only 8%, compared to 42% and 35% in Andhra Pradesh and Maharashtra respectively.

Per capita annual production of food grains (average of 1979-1981) was 183 kg in Rajasthan compared with 193 kg in Andhra Pradesh and only 163 kg in Maharashtra. Examination of consumption patterns showed that in both Rajasthan and Maharashtra coarse cereal represented more than two-thirds of total grain consumption in rural areas and even more for low-income consumers [13]. In Andhra Pradesh rice was dominant. Per capita income in Rajasthan was much lower than in the other two states. The fair-price shop in Rajasthan, where road density is low, served about 3,400 persons, whereas in Andhra Pradesh and Maharashtra the number was much smaller. Per capita wheat/rice supplied by the PDS was 16.45 kg in Rajasthan compared with 22.7 kg in Maharashtra and 20.8 kg in Andhra Pradesh during 1987. Thus, among the three states, Rajasthan is backward in PDS infrastructure, income, literacy, agricultural productivity, and social structure; Maharashtra is better off than the other two states.



Three of the four selected villages had a multi-caste distribution pattern of households, while the fourth (P. Gaon in Maharashtra) was predominantly middle-caste and land holdings there were larger and less skewed than in other villages (table 2). The proportion of households with no or negligible amounts of land (< 0.25 ha) was very high in Mac-ram (34%) and K. Gaon (45%). However, in Dhulia almost all households had some land, although it was of poor quality. In P. Gaon 26% of the households were landless. The fair-price shop for P. Gaon was 7 km from the village, whereas it was located in the other three villages. In Mac-ram and K. Gaon a large number of households, mostly in the categories of labour and backward castes, did not have ration cards. The literacy rate was very low in all the villages except P. Gaon (61%, compared with 22% in Dhulia). Thus, economically and socially, P. Gaon ranked highest, although access to the fair-price shop was not as convenient.


Sample households

The average family size of the sample households was less than five in Mac-ram and Dhulia, where a limit on the quantity of food supplied by the PDS and on other income-transfer programmes was adopted. (For detailed information on the sample households, see Bapna [14].) In the other two villages, in Maharashtra, the family sizes were 7.13 and 5.88 respectively. Labourer households in all the villages had smaller families than average. Most of them did not have land, or only a very small piece. In three of the four villages about half the family members were workers; in Dhulia only one-third worked. Socially backward castes were generally in the labour and marginal-farm categories. Six households in K. Gaon belonging to the labourer and marginal-farm groups did not have ration cards.

The literacy rate was lowest in the labourer house holds. Also, it is interesting to note that the proportion of children under 10 years of age was much lower in P. Gaon, where the level of education was high.

TABLE 1. Selected information on three sample states compared with all of India, 1981

  India Andhra Pradesh Maharashtra Rajasthan
Population (millions) 685.2 53.5 62.8 34.3
Density of population/km2 216 195 204 100
Proportion of urban to total population (%) 23.3 23.3 35 21
Literacy rate (%)
  Rural 29.6 23.2 38.1 18
  Urban 57.4 52 63.9 48.3
Cultivators ( % of rural working population) 50 38.4 47.9 73.1
Agricultural labour (% of rural working population) 29.8 42 35.1 8.3
Non-workers (% of total rural population) 45.2 38.1 44.5 48.1
Backward caste in population (%) 23.5 20.8 16.3 29.2
Per capita income 1986-1987 (rupees) 2,974 2,302 3,731 2,150
Per capita production of food grains 1979-1981 (kg/yr) 181 193 163 183
Variability in annual grain production (%) 14 12 23 23.5
Food grain yield (kg/ha) 1,158 1,247 659 611
Population per FPS 2,334 1,828 2,160 3,391
Coarse cereals as % of cereal consumption 30.9 32.1 72.4 71.6
Per household cereal supply from PDS, 1987a (kg/mo) 17.1 20.8 22.7 16.4
Roads/km2 (metres) 376 422 466 163

a. Data supplied by PDS.

TABLE 2. Important features of sample villages

  Mac-ram K. Gaon P. Gaon Dhulia
Population (no.) 892 1,743 845 1,575
Households (no.) 170 266 149 303
Distance from market (km) 5 1 8 10
Occupation of HH (%)
  Labourer 51.2 33.8 29.5 14.8
  Farmer 40.6 50.7 37.6 81.2
  Artisan 2.3 2.6 6.0  
  Service 5.9 12.2 26.8 4.0
Annual income/HH (rupees) 5,014 6,578 6,064 3,370
Ration-card holders (% of HH) 92.4 81.2 97.3 100
Land cultivated/HH (ha) 0.9 0.9 2.1 0.6
HH with <0.25 ha land (%) 33.5 45.5 26.2 3.3
Landless HH (% ) 24.1 26.3 19.5 2.6
Caste of HH (%)
  Upper 1.1 1.1 4.6  
  Middle 12.3 32.7 68.4 30.4
  Lower 24.7 5.3 4.0 14.8
  SC and STa 62.9 60.9 19.9 54.8
Illiterate head of HH (%) 82.4 60.5 28.2 62.7

HH = household.
a. Scheduled castes and tribes making up socially and economically backward communities in India.

Household purchasing behaviour

The behaviour of different categories of consumers with respect to participation in the PDS was examined by cross-tabulations of survey data and by using a regression model.


Participation in the PDS

Indicators of household participation in the PDS included the following:

TABLE 3. Participation in the PDS by 40 sample households in each of four villages

Participation Mac-ram K. Gaon P. Gaon Dhulia
% buying at FPS 98.9 61.2 55.4 70.0
Grain/household/mo (kg) 18.2 8.6 4.9 22.3
Grain/capita/mo (kg) 3.7 1.2 0.8 4.8
% of entitlement 93.2 18.6 14.3 57.8
  All cereals 25.2 9.0 6.4 36.9
  Wheat _ 30.7 42.3 62.5
  Rice 51.1 9.8 63.6 26.0


Ownership of cards

Owning a ration card entitles one to buy food grains and other commodities from an FPS and facilitates access to employment programmes. All sample households in Dhulia owned cards, as did all but 4 of 149 households in P. Gaon. However, 13 of 170 households in Mac-ram and 50 of 266 in K. Gaon did not have cards. Among the 157 households in Macram that had cards, only 7 did not have green cards. Thus, 88% of all households could enter the special subsidy scheme even when as many as three attempts had been made to verify eligibility.

In Dhulia, owning a ration card facilitated participation in government employment programmes for one adult per household. Because of repeated droughts in Rajasthan, particularly in the early 1980s, a strong motivation to obtain a card, or to get additional cards through splitting families, was observed. In Macram, where a special plan for supplying rice at only Rs 2 per kilogram was begun in 1983, a large number of households were new entrants to the programme. Since a limit of 5 kg of rice per family member per month for a family of five had been fixed by the state government in 1983, the tendency was to split households. It is interesting that in both Andhra Pradesh and Rajasthan villages the average family size was very close to the limit of five.

Despite the large benefits from subsidized grains, however, several households could not obtain cards. For the most part, they belonged to backward castes and the members were illiterate. It is obvious that the reason for not having cards was the difficulty in getting them, rather than lack of motivation. (The experiences of seven households in the sample that did not have ration cards, six in K. Gaon and one in P. Gaon, point to the obstacles to be overcome in obtaining cards. Five households made several visits to the PDS office, but access was difficult and the formalities were many. The other two households, which belonged to the high-income group, did not try to obtain cards.)

In contrast, in K. Gaon and P. Gaon, where distribution was generally on a per capita basis, no attempts to acquire additional cards were discerned. In fact, in K. Gaon wheat and rice under ITDP was available at a highly subsidized rate (Rs 1.55 for wheat and Rs 1.8 for rice, compared to Rs 2.2 and Rs 2.8 respectively in non-ITDP areas). In spite of this, 18.8% of the households did not have cards. Again they generally owned no land or only small amounts, and most belonged to backward castes and were illiterate.


Proportion of card-holders using cards

The extent of participation by card-holders can be seen by examining the use of the cards. In Mac-ram 99% of the card-holders participated in the PDS in all survey months (table 3). In Dhulia participation was 70%, in K. Gaon it was 61%, and in P. Gaon it was only 55%.

Another way to examine participation is through regularity of card use. The field study was done six times between December 1987 and December 198X. In Mac-ram all but one of the households participated regularly; however, participation in other villages was irregular, particularly among farm labourers and marginal farmers.


Purchases per household and per capita

Household purchases of rice from the fair-price shop were 18.2 kg per month in Mac-ram. Labourer and marginal-farmer households bought less grain from the fair-price shop than did other household categories. However, in terms of purchases as a percentage of entitlement there was not much variation across the sample groups.

In Dhulia average purchases from the fair-price shop were 22.3 kg of wheat. Farm labourers, marginal farmers, and "other" households bought less than small- and large-farmer households. In terms of purchases as a percentage of entitlement there was not much variation across subgroups, except that small farmers took a much higher share of their entitlement.

In K. Gaon, the average monthly purchase from the fair-price shop was 8.6 kg. Small farmers and farm-labour households purchased slightly more than average (10.5 and 9.0 kg respectively). However, "other" households purchased about half of the average quantity per household (18.6 % of the entitlement). Purchases by labourers and marginal and small farmers were higher.

In P. Gaon purchases were only 4.9 kg per cardholder. On a per capita basis, they were slightly higher for labourer households, but this should be viewed in the light of the very small role played by the PDS is Maharashtra villages.


Fair-price shop purchases as percentage of cereal consumption

In Mac-ram 25% of total cereal consumption was obtained from a fair-price shop. The percentage bought by labourer and marginal- and small-farmer households was slightly higher than average. Since rice is the major staple food in this village, the contribution of the fair-price shop to rice consumption was 51%.

In Dhulia, grain purchases from the fair-price shop was 37% of consumption. Except for small farmers, who bought a higher proportion of their total cereal consumption from the shop, there was not much variation across sample subgroups. Wheat consumption was important, with 62.5% coming from the fair-price shop. Small farmers purchased a relatively higher proportion of their wheat from the shop and large farmers and "other" households a relatively lower proportion.

In K. Gaon and P. Gaon the fair-price shop purchases were only 9% and 6.4% of total cereal consumption respectively. Wheat is not an important food in these villages; of the total consumption, 31% and 42% respectively were obtained from the shop. Except for large farmers, who purchased a much smaller share of their wheat from the shop, the groups did not differ much from the average.

In conclusion, except in Mac-ram, where nearly all households participated in the PDS, participation in other villages ranged from 70% in Dhulia to 55% in P. Gaon. Across states, some exclusion of farm labourers and marginal-farm households from the programme, as well as lower fair-price shop purchases by these groups, was observed.


Reasons for not purchasing from fair-price shops

Ration-card holders may not purchase food grains from a fair-price shop if the price is not significantly lower than the market price (allowing for quality variation and prices of substitute products) or if the household lacks money or credit. Also, the purchases are reduced if the PDS imposes constraints such as reduced quota allocations, delays in supply, long queues, and tactics that involve other, less desired products. In Mac-ram, where almost all households participated in the PDS, consumers showed satisfaction with the working of the PDS.

In Dhulia, uncertainty in supply and lack of household purchasing power, as well as less preference for wheat, were important reasons for partial participation or non-participation. However, there was not much dissatisfaction with the quality of wheat supplied.

In K. Gaon, purchases as a percentage of entitlement were very low. Uncertainty of supply, poor quality, less preference for rice and wheat, and lack of purchasing power were important factors. In 1987 consumers in Maharashtra rejected an offer of sorghum because of its poor quality.

In P. Gaon, distance from the fair-price shop, uncertainty of supply, and long queues were significant constraints. Distance was responsible for lack of information and uncertainty of supply. Dissatisfaction with the quality of the rice and wheat and lack of purchasing power were also deterrents.

These responses were largely from labourers and marginal farmers belonging to backward castes in three villages. The PDS apparently did not take into account the habits of these individuals, who often tend to buy in small quantities. Lower preference for the product supplied was indicated as a reason for non-purchase by all classes of households, especially large farmers and "other" households. Dissatisfaction with grain quality was a common complaint in K. Gaon and P. Gaon.

The price of substitute commodities also affected participation. This could be seen in the behaviour of households over time (table 4), which indicates that the price of substitute commodities played a role in determining quantities purchased.

In Mac-ram the price of substitute cereal (sorghum) was highest in August-October and December 1988 (Rs 2.01/kg) and was lowest in March 1988 (Rs 1.62/ kg). The behaviour in terms of percentage of entitlement actually bought from the fair-price shop corresponded to the price variable; that is, in December 1988 over 98% of the entitlement was purchased' but in March it was only 89%.

In K. Gaon, where rice and wheat were provided at highly subsidized prices (Rs 1.80 and Rs 1.55/kg respectively), prices of substitute cereals were highest (Rs 2.63/kg) in May-July 1988 and lowest (Rs 2.19/ kg) in December 1987. The corresponding cereal purchases were 46% and 12%. In P. Gaon the highest and lowest prices were in December 1988 and December 1987 respectively; the corresponding fair-price shop purchases were 34% and 9%.

In Dhulia the percentage of grain entitlements purchased at the fair-price shop in 1988 varied from 133% in January to 17% in December. This had little apparent relationship to the fluctuations in the price of substitute grains. The explanation for this unusual purchase pattern was that the actual availability of supplies at the store was very irregular. For example. the purchase of 133% of the entitlement in January occurred when the PDS made an unusually large grain allocation to compensate for short allocation in previous months.

TABLE 4. Comparison of grain entitlements, purchases from FPS, and the price of substitute commodities

  Dec Jan Mar May-July Aug-Oct Dec
1987 1988 1988 1988 1988 1988
Mac-ram entitlement (kg) 22.1 22.1 22.1 19.5 9.5 22.1
  % purchased 95 97 89 86 91 98
  Price substitute 1.87 1.85 1.62 1.97 2.01 2.01
K. Gaon entitlement (kg) 78.9 79.8 59.2 13.2 23.0 23.0
  % purchased 12.4 15.3 19.2 45.7 16.9 36.1
  Price substitute 2.19 2.27 2.46 2.63 2.26 2.52
P. Gaon entitlement (kg) 67.4 67.4 24.2 11.1 19.6 16.8
  % purchased 9 10 14 32 22 34
  Price substitutea 99 1.96 2.40 2.31 2.15 2.52
Dhulia entitlement (kg) 49.8 27.9 27.9 46.8 51.2 27.9
  % purchased 58 133 75 41 45 17.0
  Price substitute 2 54 2 68 2.69 2.92 3.00 2.00

a. The substitute commodities were jowar (sorghum) in Mac-ram, bajra (pearl millet) in K. Gaon, and maize in Dhulia. The prices are in rupees per kilogram.

A regression model of consumer behaviour

Consumer behaviour in purchasing food grains from fair-price shops can be explained by using a consumption function and treating these grains as a separate commodity. The consumer does not treat the grains provided by fair-price shops as perfect substitutes for grains from other sources because of the extra costs, waiting, and inconvenience incurred, as well as the lower quality of the product. Above, purchasing behaviour was examined by using two-way tables. To illustrate the factors affecting consumer behaviour more precisely. the following regression model was designed:

C = (Cf + Cm + C0)
C = f (Pm+ Pf+ Po+ I+ T)
Cf = C - (Cm + C0)
Cf = f(Fm+Pf+Po+I+T) - Cm+C0

where C is consumption of food grains; the subscripts f, m, and o refer to fair-price shops, the market, and other sources of food grains respectively; and /. P, and T are income, prices, and other factors.

If the supply from fair-price shops is restricted, the consumer will buy the entire quantity offered or as much as income or financial position permits. However, no attempt was made to represent a low preference for wheat and rice as compared to coarse cereals.

Since income is usually underreported. assets such as land can further explain the variations in the amounts purchased. This is represented here by sample groups. There are differences in consumption patterns across castes; therefore, the variable "caste" was added to the equations. The variables family size and composition were added as factors affecting demand. Furthermore, it is hypothesized that the demand for PDS food grains declines after the crop harvest. As stocks are depleted, interest in purchasing from PDS increases. Therefore, the variable "month" was added.

These factors all relate to demand. If the supply from the fair-price shop is not available when the consumer wants to buy or if it is reduced by the PDS administration (changes in the allocation are made by the administration depending on supplies, stocks, purchases by consumers, and prices in the market). the consumer cannot obtain the usual quota or intended quantity. To capture this phenomenon, supply variables were introduced: the date of the food-grain purchase by the shop owner from a taluka (a PDS geographical administrative unit) supply point, the quantity purchased by the owner, and the quantity distributed by the PDS authorities. After experiments with several specifications of variables. the following function was estimated:

Cf = a + b1l + b2WPf + b3RPf + b4WPm + b5RPm + b6SPm + b7CST + B8SG + b9FS +b10CH + b11R + b12M + b13P + b14YP + b15Q + b16QL + b17DL + e,

where the subscripts f and m refer to purchase from fair-price shops and the market respectively, and

C = consumption of cereals,
I = annual income of the household, in rupees,
WP = the price of wheat,
RP = the price of rice,
SP = the price of substitute products,
CST = cast of the household (high = 1, middle = 2, low = 3, backward = 4),
SC = the sample group, FS = family size,
CH = percentage of children under 5 years of age,
R = other supply, including stock at the beginning of the month,
M = month (Oct. = 1, Dec. = 2, Jan. = 3, Mar. = 4. May-Aug. = 5)
P = participation in fair-price shop (cardholder),
YP = year of becoming a member of the fair-price shop,
Q = quantity distributed by a PDS taluka to all fair-price shops in the area,
QL = quantity purchased by the sample fair-price shop.
DL = date of purchase of quota by the sample fair-price shop,
e = resident term.

The data on the purchases for all six months of the survey were pooled and a month variable (M) was used. (Because the program for the error component model for pooled data was not available, a general regression model was estimated using a month dummy as a close substitute.) The results of the equations that were selected for the four villages are given in table 5.

The variation among rs from the regressions ranged from 0.78 for Mac-ram, 0.42 for Dhulia, and 0.35 for K. Gaon to only 0.18 for P. Gaon.

TABLE 5. Results from regression models explaining household purchases of cereals from fair-price shops in the sample villages

  Regression coefficients
Mac-ram K. Gaon P.Gaon Dhulia
Intercept -14.55 1.87 31.81 2.13 48.60 - 137.06 1.51
I 0.0004 0.24 0.0002 1.24 0.0008 0.93 -0.0001 0.24
RPf - - 2.14 1.55 - 9 35 1.68 10.36 1.17
WPf - - -7.34 1.03 -4.48 0.62 -98.40 2.32
RPm -0.08 0.09 -1.20 0.80 0.37 0.52 15.21 2.54
WPm - - 0.52 2.00 -0.20 0.14 -1.36 0.10
SPm -0.13 0.08 -1.36 0.49 1.35 0.62 -6.31 0.61
SG -0.17 0.69 -1.83 3.89 0.36 0.75 -1.10 1.00
CST -0.26 1.22 -1.55 3.62 -0.13 0.22 -0.50 0.48
FS 2.18 7.86 1.43 1.47 0.89 3.74 3.04 4.16
CH 0.0004 0.19 0.10 2.08 0.06 1.34 -0.20 2.92
M -0.37 0.61 1.56 2.14 1.00 0.94 18.02 4.94
R 0.03 1.69 0.002 0.14 0.0002 0.09 -0.005 0.58
YP 0.06 0.82 0.14 6.19 0.07 1.60 -1.51 1.96
Q 0.08 0.60 -0.08 1.98 -0.20 1.55 -0.0069 2.80
QL 0.51 1.80 0.18 2.64 0.43 1.53 0.51 4.74
DL 0.04 0.27 -0.33 1.02 0.87 1.52 -0.85 3 60
r2 0.78 0.78 0.35 0.30 0.18 0.12 0.42 0.38


An earlier tabular analysis showed some association between rice purchased from fair-price shops and market prices of sorghum. However, the regression for Mac-ram shows that changes in the market prices of rice and sorghum had no effect on purchases from the fair-price shop. The price difference between the shop and the market for rice is so large that minor variations in market prices do not affect purchases from the former. Furthermore, the price for jowar (sorghum) varied with the fair-price shop prices.

Hence, the effect of sorghum price variations could not be seen. Alternatively, when the prices of grain are high, the PDS system may have a small supply because of reduced stocks. This is reflected in the positive and significant coefficient for the purchase by fair-price shops (QL). As indicated earlier, household purchases as a percentage of entitlement in the face of supply constraints were quite high. Family size (FS) was positive and significant. All other variables, except caste, were not significant. The variable 'caste" was negative (-0.26), which could indicate either some amount of discrimination against the backward castes and have-nots or the fact that these groups had insufficient purchasing power.


K. Gaon

Most of the variables were significant and had the expected signs. Among price variables, the fair-price shop price for wheat had a negative sign and the market price had a positive sign, implying an increase in purchases from the shop when the market price of wheat increases. The prices of rice and the substitute commodity did not have the expected signs, and the coefficients were not significant. The variables family size (FS) and percentage of children under 5 years of age (CH) were significant and positive. The supply-constraining variable (quantity purchased by the fair-price shop-QL) was positive and significant (0.18), but the date of purchase (DL) was not. It had a negative sign. which implies some negative effect on purchases if supply at the shop is delayed. Thus, price considerations, family size, caste, and supply-constraining variables were important influences on household purchases from the fair-price shop.


P. Gaon

Although the r was very low. the price of rice at the fair-price shop (RPf) and in the market (RPm) and the price of coarse cereals (SPm) had the expected signs. However, apart from the price of rice at the shop, the other price coefficients were not significant. However, the family size and the supply-constraining variables were highly significant. The quantity purchased by the fair-puce shop had a positive and significant effect on consumer purchases, indicating that it was largely supply that was a constraint. The date of purchase by the shop owner (DL) did not seem to affect consumers adversely, since they purchased the products even if they were supplied late in the month.



The price of wheat at the fair-price shop had the expected sign and was significant, but the price of wheat and maize in the market did not. Family size was a very important variable, as were seasonality, and date and amount purchased by the shop. In other words, the quantity supplied was easily absorbed by the consumer, but a delay in the supply had an adverse effect on purchases.

Income did not seem to influence purchases of cereals by households in the four villages; its effect may have been captured by other variables, such as the quota allocated and purchased, and the date of purchase by the shop. This confirms the tabular analysis, which showed almost no difference in purchases across sample groups except for labourer households.

To conclude, the constraining variables, seasonality, and socio-economic status as shown by caste and selected demographic features were very important in explaining consumer behaviour. Because the price at fair-price shops was low compared with that in the market, price variables did not show the expected signs and were not significant. The hypothesis of lower participation by the poor (labourer and marginal farmers) was verified and explained by socioeconomic factors such as caste, lack of liquid means of purchase, and supply constraints such as the provision of less preferred commodities and uncertainties in supply.

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