Chapter-5 Conclusions and Suggestions

Chapter-5 Conclusions and Suggestions 147

Chapter 5 Conclusions and Suggestions The present study has been undertaken with the core objective of deriving the demand parameters and making demand projections for major food items like cereals, pulses, milk & milk products, sugar, edible oil, meat/fish/chicken and vegetables. For estimating the demand parameters, the researcher has used the OLS (Ordinary Least Square) and QUAIDS (Quadratic Almost Ideal demand System) models. For calculating the own price and cross elasticities of demand, the coefficients of different parameters derived by QUAIDS model have been used. The monthly per capita consumption data on the major food items in physical terms and monetary terms have been used for calculating the prices and demand of major food items. These data have been compiled from various rounds on consumption pattern by the NSSO. The expenditure elasticities of various food items have been derived by the panel regression approach. Then, after projecting supplies of these commodities in future based on simple models, an attempt has been made to determine demand-supply gaps. The conclusions of this study have been divided in three sections. In the first section, the researcher has covered the conclusions derived from consumption expenditure pattern in rural and urban areas of India. The results of QUAIDS model applied for deriving demand parameters have been put in the second section and in the last section of this chapter the results of panel regression approach, demand and supply projections models have been summarized. 5.1 Consumption Pattern in India (1) It has been found that over a period of time the Monthly Per Capita Food Consumption Expenditure (MPFCE) has increased in terms of money but it has declined in terms of proportion both in rural and urban areas of India. However, when we compare this pattern between rural and urban areas, it has been found that in urban area the increase in MPFCE in monetary term had increased more than rural areas. But in the terms of proportionate change the declining rate was found to be higher in rural area than in urban area. So one can say that, the rural people have shifted from food consumption to nonfood consumption faster. [See table no. 1.2.4.1] 148

(2) The Monthly Per capita Consumption Expenditure (MPCE) on various food items have been found to be increasing over a period of time excepting Fruits (dry) in the rural area. The MPCE on milk & milk products, edible oil, Meat/fish/chicken, vegetables, sugar, spices and beverages have increased more in rural area than in urban area. However, in the case of cereals, cereal substitutes, pulses and pulses products and fruits (fresh), the monthly per capita consumption expenditure have increased more in urban area. [See table no. 1.2.4.2] (3) The proportions spent on consumption of various food items have been found to be declining for almost all food items excepting vegetables, fruits and beverages during the period of 1999-00 to 2009 in both rural and urban areas of India. A declining rate has been noted higher in rural areas only for the cereals. [See table no. 1.2.4.3] (4) It has been found that the monthly per capita consumption of food items like cereals, pulses, sugar and salt had decreased in physical term in both rural and urban areas of India. It has decreased by 10.77%, 22.62%, 15.48% and 33.33% respectively in rural area and by 9.985, 21.0%, 18.0% and 32.43% in urban areas. But in monetary terms, it has increased for all these food items. Hence, one can concluded that the increase in the monthly per capita consumption expenditure of these food items is a result of increase in the prices of these items. In the case of food items like milk, edible oil, meat, fish & chicken, vegetables, fruits (fresh), consumption has increased in both rural and urban areas in physical terms. It indicates that in the food basket, the consumption expenditure has shifted from foodgrains to non-foodgrains items in rural and urban areas. The researcher believes that this shifting may be due to various reasons like income growth and urbanization and relative changes in life styles, changes in relative prices and easy availability of non-food grain items. [See table no. 1.2.4.4] 149

(5) It has been concluded that the budget shares of cereals, pulses & pulses products, sugar, spices and for total food have considerably decreased for all classes of families during the period of 1999-00 to 2007-08 in rural area. However the extent of decrease in budget share on cereals and pulses varied from high to low in the very poor, poor, non-poor and rich families respectively. On the other hand budget shares of milk, edible oil, meat, fish & chicken, vegetables and fruits have increased for very poor, poor and non-poor families. However in the case of rich families, the budget share has increased for some items and decreased for other items, which means that the pattern is found to be complex in rural areas. In the case of urban areas, a similar pattern has been found. The major difference in rural and urban areas is in the budget shares of different food items. It has been found to be less in the urban areas than the rural areas for almost all food items. [See table no. 1.2.4.5] 5.2 Applications of OLS and QUAIDS Models (1) The demand parameters derived by OLS method have been found to be significant for almost all items in rural, urban and for all India level. But in the case of the QUAIDS model a number of parameters have been found to be insignificant. The researcher has considered the demand parameters estimated from the QUAIDS model. The major reason for selecting this model is that the OLS method basically takes all the observations in a time series format. Therefore this method is not able to capture the time invariant effects like state effect. The studies by Ray (1979), Majumder (1980), Mittal (2006, 2008, and 2010) have concluded that the QUAIDS model is better than the OLS method. (2) In the rural area, the square term of per capita food expenditure was significant for all the food items excepting pulses. So, it can be say that there is nonliner relationship between total budget on these food items and budget share on food items like cereals, milk & milk products, sugar, Edible oil, meat, fish & chicken and vegetables. Only for pulses there may be a liner relationship because in OLS method the coefficient of per capita food expenditure has 150

been found to be significant. The coefficient of own price has been found to be negative for cereals, pulses, mil, meat, fish & chicken and vegetables. On other hand it has been found to be positive for sugar and edible oil. However these associations are significant only for the milk, edible oil and meat, fish & chicken. The time effect has been found to be significant only for the milk, sugar and meat, fish & chicken. This effect is negative for milk and sugar, and positive for meat, fish & chicken. Therefore we can say that over a period of the budget shares of milk and sugar have been reduced and for meat, fish & chicken it has increased in rural areas. The value of R 2 ranged from 0.08 to 0.77. The lowest value of R 2 is found for pulses and highest for cereals. [See table no. 3.2.1(a) and 3.2.1(b)] (3) In the case of urban area, the square term of per capita food expenditure has been found to be significant only for the cereals, milk, sugar and meat, fish & chicken. The food items like pulses and edible oil, the single and square terms of per capita food expenditure have found to be insignificant both in the OLS method and the QUAIDS model. Hence, the researcher can say that other model/method of estimating demand parameters should be applied which may be give satisfactory results. The coefficients of own price has found to be positive for all food items which implies that in whatever way the prices of these food items changed urban people tried to maintain their budget share of these food items. The value of R 2 ranged from 0.10 to 0.59. The lowest value of R 2 is found for pulses and highest for pulses. [See table no. 3.2.2(a) and 3.2.2(b)]. (4) The comparison of the results of the QUAIDS model applied for rural and urban areas concluded that the budget share of meat, fish & chicken has declined with increase in its price for both the rural and the urban areas. But the budget share of meat, fish & chicken has declined more in urban areas than in rural areas. Both rural and urban people have tried to maintain their budget share of sugar and edible oil when their prices had increased. The signs of the coefficients of own price elasticity for cereals, pulses, milk and vegetables have found to be different for rural and urban areas. These coefficients are positive in urban areas and negative for rural areas which 151

show that the budget shares of these food items in urban areas have been maintained when prices are increase but the budget share among rural people has declined. (5) For all India level, it is found that the square term of per capita food expenditure is significant for all food items. Hence, one can infer that the QUAIDS model is better for all food items. This result is found to be contrast to the results derived by the Mittal (2010) in her study. She had found that the squared term of per capita expenditure of food was significant only for pulses and edible oil. The coefficient of own price has been found to be negative only for the milk and meat, fish & chicken. These coefficients were significant only for the sugar, edible oil and meat, fish & chicken. The coefficient of urban dummy is found to be significant only for the cereals, milk and edible oil. These coefficients are found to be positive for cereals and edible oil which implies that budget share elasticity with respect to monthly per capita total food expenditure is higher in rural area than urban area. In the case of milk, it is higher in urban area than rural area. Over a period of time the budget share on milk and edible oil has been significantly affected. The coefficients of time trend are negative for milk and positive for edible oil which implies that over a period of time the budget share of milk consumption has declined and budget share on edible oil has increased. [See table no. 3.2.3(a) and 3.2.3(b)]. (6) The classification of the different food items in substitute and complementary groups indicate that cereals is the common complementary item for the consumption of pulses and edible oil both in the rural and the urban areas. However for milk and sugar, cereals have found to be substitute item in rural areas and complementary in urban areas. On the other hand for edible oil, meat, fish & chicken and vegetables consumption the cereals have found to be complementary in rural areas and substitute in urban areas. [See table no. 3.3.1(a) and 3.3.1(b)]. (7) The results of uncompensated and compensated own price elasticities of major food items show that, excepting milk the own price elasticities of different 152

food items is less in compensated criteria than uncompensated criteria for both rural and urban areas of India. In the case of milk, the own price effect is noted to be higher under compensated criterion than under uncompensated criterion. [See table no. 3.3.2 (a), 3.3.2 (b), 3.3.3(a) and 3.3.3 (b)] (8) Compared to the urban area, the rural area is more affected by the change in prices of different food items excepting edible oil and meat, fish & chicken. The notable price effect is found for milk consumption, in rural area the own price effect is almost more than -4.04 but in urban it has found to be -0.24. So we can say that in rural area livestock rearing is a major occupation after agricultural activities and therefore when price of milk is increased they try to sell more milk by reducing their self consumption. However urban people give higher preference to the milk consumption in their food basket. The similar results have been observed by the Abdulai et.al. (1999) and Mittal (2006, 2008 and 2010) in their studies. [See table no. 3.3.2 (a), 3.3.2 (b), 3.3.3(a) and 3.3.3 (b)] (9) In rural area, the own price elasticity of cereals and sugar has found to be varying from low to high in very poor, poor, non-poor and rich families respectively (i.e. -0.81 to -0.88 for cereals and -0.78 to -0.83 for sugar) which implies that rich families are more affected by the cereals and sugar prices than poor families. It may due to the large varieties in the consumption basket of rich families. In the case of milk, edible oil and meat, fish & chicken the own price effect varied from low to high in rich, non-poor, poor and very poor families respectively (i.e. -2.79 to -6.88 for milk and -0.76 to -0.78 for edible oil and -2.78 to -3.48 for meat, fish & chicken). Therefore one can say that the consumption of milk, edible oil and meat, fish & chicken was more affected by their prices for poor class families than rich class families. In the case of pulses and vegetables the own price elasticities have been found similar for class of families (-1.02 for pulses and -1.04 for milk). [See table no. 3.3.2 (a), 3.3.2 (b), 3.3.3(a) and 3.3.3 (b)] (10) The own price elasticities has been found greater than one for pulses, milk, meat, fish & chicken and vegetables (i.e. -1.02, -4.04, -2.02 and -1.03 153

respectively) in rural area. The uncompensated own price elasticities of various food items also shows that the food items like pulses, milk, meat, fish & chicken and vegetables fall in the category of luxurious consumption in rural area. The prices of these food items significantly affect their consumption and the food items like pulses, milk and vegetables are more required for nutrition in food basket. Therefore it is necessary to control the increase in the prices of these food items. [See table no. 3.3.2 (a), 3.3.2 (b), 3.3.3(a) and 3.3.3 (b)] (11) In urban area, the own price elasticities of cereals, pulses and sugar has found to be higher for poor class of families than rich class of families. In the case of milk, the own price effect is found to be higher on families of the rich class than families of the poor class. Out of all food items, the own price elasticity of meat, fish & chicken is found to be higher than that of other food items. [See table no. 3.3.2 (a), 3.3.2 (b), 3.3.3(a) and 3.3.3 (b)] (12) The food budget/income elasticities of different food items indicates the ratio of proportionate change in expenditure on specific food item due to one percent change in total expenditure on selected food items. These food budget elasticities are found to have a similar pattern in the rural and the urban areas. [See table no. 3.17 and 3.18] (13) The food budget/income elasticity of cereals for families of the poor class show that it is a very important food item in their food consumption basket both in the rural and the urban areas. Similarly for families of the rich class, milk is found to be an important item among selected food items. [See table no. 3.17 and 3.18] (14) The food budget/income elasticity has found to be greater than one for meat fish & chicken and for vegetables both in the rural and the urban areas for all classes of families. Hence, these food items have been classified as the luxurious goods both in the rural and urban areas. The value of the food income elasticity of meat, fish and chicken is higher for the urban areas. On 154

the other hand, food income elasticity of vegetables is found to be higher in the rural areas. [See table no. 3.4.1 and 3.4.2] (15) The food income elasticity at all India level is found to be positive for all the families which implies that with increase in the budget share on the selected food items, the consumption of these food items also increases. The food income elasticity of cereals, pulses, sugar, edible oil and meat, fish & chicken for different class of families implies that the increased in the budget of these food items has higher for economically poor families than rich families. However, in the case of milk and vegetables the budget share has been found increasing at higher rate for rich families than economically poor families. [See table no. 3.4.3] 5.3 Panel Regression Approach (1) On the basis of the conclusion arrived at by using Joint-test, Breusch-Pagan test and Hausman test, the researcher has used the fixed effect panel regression model for estimating the expenditure elasticities of cereals, pulses, milk, edible oil, vegetables and for total food for both the rural and the urban areas of all India. However, in the case of meat, fish & chicken and sugar the random effect model has been applied in the rural area and pooled OLS model has been applied in the urban area for estimating expenditure elasticities. At all India level, fixed effect panel regression model has been used for food items like cereals, pulses, edible oil, vegetables and total food. The random effect has been observed for the milk, meat, fish & chicken and sugar consumption expenditure. Therefore, the random effects model has been used for estimating expenditure elasticities. [See table no. 4.2.1(a), 4.2.2 (a) and 4.2.3 (a)] (2) The expenditure elasticities of major food items like cereals, pulses, milk, edible oil, meat, fish & chicken, vegetables and sugar are found to be 0.49, 1.01, 0.74, 1.01, 1.25, 1.31 and 0.78 respectively for the rural area. On the other hand for theurban area, these elasticities are found to be 0.26, 0.56, 1.21, 0.53, 0.93, 0.63 and 0.71 respectively. So, it can be said that excepting 155

milk, the expenditure elasticities of different food items are higher in the rural area than the urban area which indicates that rural people are more responsive to consumption expenditure on these food items when total expenditure/income level is changed. However in the case of milk, urban people are found to be more responsive which indicate that urban people are giving higher priority to consumption of milk in food basket than rural people. A similar conclusion was also derived by Thamarajkshi (1963), Abdulai et al. (1999), Mittal 2006 and Praduman Kumar (2011) in their studies. However, the values of the elasticities vary among the items. Estimates of expenditure elasticities of milk and meat, fish & chicken derived by Sinha (1966) in his study are against the results derived in this study. (3) At all India Level, the expenditure elasticities of milk and vegetables are noted to be greater than one which implies that there is more variation in the monthly per capita consumption expenditure of these food items compared to change in the monthly per capita total consumption expenditure. Hence, these food items have been considered to be luxurious items in food basket. The higher expenditure elasticity also show that if the per capita income will grow at a certain rate, the demand for these food items will also grow at a faster rate. The lowest expenditure elasticity is recorded for cereals and the highest for vegetables. Mittal (2006) and Praduman Kumar (2011) had also observed a similar pattern in the expenditure elasticities of these food items in their studies. [See table no. 4.2.3 (b)]. The coefficient of urban dummy is found to be statistically significant for cereals, pulses, edible oil, vegetables and sugar. These coefficients are positive which implies that there is significant difference between the effects of the monthly per capita total consumption expenditure on these food items in the case of rural and urban areas. The expenditure elasticities of these food items are higher in rural areas than urban areas. (4) If the data on the monthly per capita expenditure on different food items were classified according to the expenditure classes, it was observed that the random factors are affecting on the consumption expenditure on various food 156

items. Hence in the majority cases, the expenditure elasticities of different food items have been derived by random effects model. (5) The expenditure elasticity of cereals and vegetables has been found to be varying between high to low values from the very poor families to poor families. In the case of rich families expenditure elasticity of cereals is found to be negative which implies that with increase in the total expenditure, the rich families have decreased the share of cereal consumption. This share is increased by a greater proportion by very poor families than poor and non-poor families. In the case of pulses, the expenditure elasticity is found to be varying between high to low values from non-poor families to very poor families. Like cereals, the expenditure elasticity of pulses is negative for rich families. (See table no. 2.2.4 (a-1) to 2.2.4 (d-2)]. (6) The expenditure elasticities of milk is found to be greater than one excepting for the families of rich class. Hence one can say that when income of these classes of families increases the consumption expenditure on milk also increases by a higher proportion. In the case of edible oil the expenditure elasticity is found to be greater than one for all classes of families. 5.4 Conclusions derived from Demand and Supply Projections (1) Trend in the population growth gives a positive signal to Indian economy because population growth is reducing over time. However due to the high rate of urbanization the urban population will increase at a high rate in future. [See table no. 4.3.1] (2) According to all the three alternative assumptions of per capita income growth the demand for various food items will increase in future at all India level. But the rate of increased demand for these food items is found to be declining rate. [See table no. 4.3.3 to 4.3.5] 157

(3) When we assume that the per capita income growth is at the actual rate, cereals demand will increase by 1.59%, 1.33%, 1.12% and 0.92% per annum during the period of 2011 t0 2021, 2021 to 2031, 2031 to 2041 and 2014 to 2051 respectively. On the other hand, the demand for cereals will increase by 1.59%, 1.43%, 1.21% and 1% under the assumption of low per capita income growth and 1.46%, 1.28%, 1.08% and 0.88% under the assumption of high per capita income growth. So, we can say that the demand for cereals will increase in projected time period but at a diminishing rate. (4) The projected demand for other food items indicates a similar trend. The growth rate of projected demand of various food items under alternative scenario ranges between 1.60% to 0.80% for the selected food items. (5) The projected demand for pulses, milk and vegetables will increase at a faster rate compared to the other food items. This is due to high income elasticities of demand for these food items. [See table no. 4.3.3 to 4.3.5] (6) The growth rate of projected demand for various food items has a declining rate which can be explained by the decline in the future population growth. But when we consider the total projected demand in physical term, it will be increased in future due to the increase in total population. (7) The projected demand for various food items in the rural areas indicates that the demand will increase upto 2021 in quantity terms but after 2021 the demand will decline. In terms of percentage change in projected demand for various food items, according to actual and high rate of growth assumption the demand for various food items will increase upto 2021 then it will tend to decrease. However if we assume the low per capita income growth, the demand for cereals, milk and sugar will increase upto 2041, and then it will decline. But the projected demand for pulses, edible oil, meat, fish & chicken and vegetables will increase during the projected years but at a decreasing rate. [See table no. 4.3.3] (8) On the other hand, the projected demand for various food items in urban areas shows that due to high urbanization the demand for various food items 158

will increase rapidly. But due to decline in the growth rate of total population and low elasticity of demand for various food items the demand will increase at a decreasing rate. Notably, the researcher has observed that in the demand projections for various food items in urban area, if we assume the high per capita income growth, the projected demand will increase over a period of time in future but the increase will be less than that under the assumption of actual and low per capita income growth. This is due to the low expenditure elasticity of various food items in the urban area. [See table no. 4.3.4] (9) The projected supply of various food items is determined under two alternative scenarios. Under first scenario (If Area Harvesting Growth is according to table no.4.4.2) the supply of cereals is estimated to be 350.23 million metric tons in 2021, which will increase to 438.78 million metric tons in 2051. For pulses, sugar, edible oil and vegetables, supply is estimated to be about 30.86, 61.45, 12.27 and 283.86 million metric tons in 2021 respectively which will increase to 68.26, 101.98, 27.28 and 826.29 million metric tons in 2051 respectively. (10) If we examine the gap between demand and supply, then according to first scenario of output and if the per capita income increases at the actual rate excepting the sugar, there will be deficit in availability of various food items. The demand and supply gap of cereals is expected to be 85.94 million metric tons in 2021 which will reach to 185.02 million metric tons in 2051, whereas the gaps for pulses, edible oil and vegetables are expected to be 18.67, 58.4 and 79.31 million tons in 2051 respectively. Excepting cereals and edible oil, the future gap of demand and supply will decrease. This may be due to decline in the growth rate of future population, high growth rate in production and productivity in India. However, according to scenario-2, the deficits in the supply of all food items have been observed. (11) Under the assumption of low per capita income growth rate, there no any remarkable decline in the availability of supply of different food items excepting edible oil according to the scenario-1. But according to scenario-2, 159

the supply of all food items have been found to be inadequate to its demand excepting sugar. (12) If the projected gap between demand and supply under the assumption of per capita income will grow at higher rate, there huge deficits will arise in future according to scenario-1 and scenario-2. This deficit will be serious if the growth rate of are under harvesting of different food items will be zero in projected years, ie. The harvesting areas remain constant. (13) On the basis of overall discussion on the gap between demand and supply of different food items, the researcher can say that the assumptions of actual and higher per capita income growth rates have higher probability in future in this globalize era. However, it is also true that the assumption regarding the output of different food items are more relevant to scenario-1. (14) On the basis of projected data of demand and supply of various food items under the actual and higher per capita income growth assumptions and area under harvesting, production and productivity growth under scenario-1, the one can say that significant deficiency will arise in the availability of supply of all food items like cereals, pulses, edible oil and vegetables. So the policy makers should focus on increasing the production of these food items by various measures like increase in productivity of land, better utilization of land and other resources, adoption of the modern technology, multiple cropping pattern, increased the use of high yielding varieties, fertilizers, insecticides and presticides, improving farming practices, more irrigation facilities etc.. The other alternative is to design the import and export policy of these food items in future, so as to bridge these gaps. 160

Implications (1) The price elasticities of all the selected food items excepting cereals found to be higher for economically poor families than rich families especially for the milk and meat, fish & chicken and vegetables. Therefore, government should tries to control the prices of these food items for increase the nutritional status of the poor families. (2) In urban areas, the expenditure elasticity is found to be greater than one only for the milk. So, the government should take steps to see that supply of milk increases more rapidly in the urban areas otherwise the price of the milk will increase quickly with increase the level of income of urban people. For all other items steps should be to taken to increase their flows in the rural areas as compared to the urban areas because the expenditure elasticities of pulses, edible oil, meat, fish & chicken and vegetables found to be greater than one in rural areas. (3) At all India level, the expenditure elasticities of milk and vegetables found to be greater than one which implies that if the per capita income will grow faster rate, the demand for these food items will also grow faster rate. This requires strategies to by the government to keep supply in tune with demand. So, that the price rise does not go out of control. (4) The history of the development of the Indian economy clearly shows that the level of income increases over a period of time. Hence, the assumption of the per capita growth at higher rate is more reliable than the assumption of actual and lower per capita income growth.as well as the assumption of the production of selected food items according to scenario-1 is also acceptable because over a period of time the production and productivity of land increases. The demand for and supply of the selected food items under the above assumptions shows that there will be a shortage of all food items in projected years. The shortage of the cereals and vegetables will be a huge. So, the policy maker should foucused on increase the production of these food items as well as design the appropriate import and export policy of these food items. 161