Growth & Productivity of Food Processing Industries in India.

AuthorKhosla, Rajiv

Introduction

Indian agricultural sector is continuously getting gripped under economic crisis. On the one hand, the peasantry faces problems related to decreasing productivity, exploitation in the hands of middlemen and traders, high cost of inputs and inadequate knowledge with respect to farming on commercial lines etc. At the same time, declining public expenditure on agriculture or failure to establish a link between rising cost of production and remunerative prices by the government is increasingly making farming an unviable proposition. In order to amicably sort out the problems on this front, a strategy is required to be devised which can offload the burden on the farm sector by reducing the disguised unemployment and also ensure sustained increased earnings for the farmers, besides increasing the real allocations towards the agriculture sector.

Fan (2018) has proposed a "move up, move out" strategy for the Indian farmers so as to create better economic opportunities for them. The stratagem aims at moving the farmers out from rural areas in order to make them work in urban areas. Remaining farmers in rural areas are also required to shift towards the production of high-value food products. Similarly, agricultural entrepreneurs are sought to move from urban areas to rural areas in order to produce healthy food with the latest technology. China broke the shackles of poverty in agriculture sector by adopting this approach.

Food processing industries are expected to play a catalytic role at this juncture. With an increase in prosperity in urban areas along with consciousness about healthy foods, demand for nutritious foods is further expected to shift towards fruits, dairy products and meat products. Food processing industries facilitate both the backward and forward linkages. In terms of backward linkages, food processing industries source their raw material from the farm as well as non-farm sector (Khosla et al, 2010). Similarly, in the context of forward linkages, output from the food processing industries is used as input to process foods, milk, beverages, and juices etc. Thus, a developed food processing industry can help reduce wastages, ensure value addition and generate additional employment opportunities thereby offering better socio-economic conditions to millions of farm families. The present study attempts to find out the growth and productivity of food processing industries in India. Specifically, objectives of the study are:

  1. To find out the dominant and fastest growing food processing industries in India since 1980-81

  2. To analyze the total factor productivity growth and pattern of labor in food processing sector in India

Data Base & Methodology

For the purpose of study, secondary data from various issues of Annual Survey of Industries (ASI) published by the Central Statistical Organization for the years 1980-81, 1990-91, 2001-02, 2010-11 and 2015-16 is used. Broad classification of industries listed in the group of food-processing have undergone drastic regrouping from 1980-81 to 2015-16. In order to arrive at comparable and meaningful results a concordance is developed by clubbing the similar industries classified under different codes in National Industrial Classification--2008 (Annexure I). To examine the dominance of different food-processing industries in the state, we have assessed the share of food processing industries in total food processing group and overall manufacturing sector over a period of time. The comparison is undertaken in terms of six variables i.e. number of factories, number of workers, invested capital, total output, net value added and profits. Further, to study the growth of food-processing industries, compound growth rate of each of the selected indicators have been calculated for different time periods. Trends in growth are studied by computing the compound growth rate through principle of least squares, using the following formula

Log Y = Log a + (Log b)t

The data given in ASI reports is at current prices but for proper comparison, values are deflated with the help of suitable deflator (1993-94 = 100).

For finding out the productivity, we have used the non-parametric method of Data Envelopment Analysis (DEA) primarily on the assumption that all food processing industries in India share common production practice. We have taken gross value added as output and labor and capital as two inputs in the production function. The Malmquist indices are computed on the basis of annual time series data for the time-period 1980-81 to 2015-16. Further, it is decomposed into pre (1980-81 to 1990-91) and post (199091 to 2015-16) liberalization regimes. Using DEA, Malmquist indices of productivity change is decomposed into components of change in pure technical efficiency, technical progress, and scale efficiency. It helps to identify the sources of productivity growth so as to make efforts to transform the lagging industries into the leading ones. We assume that all the industries are operating at an optimal scale. The Malmquist input oriented Total Factor Productivity (TFP) change index between the base period t and the following period t+1 is defined as:

[Please download the PDF to view the mathematical expression]

A value of M greater than unity implies a positive TFP growth from period t to period t+1 whereas a value of M less than one indicates a TFP decline. Equation above is the geometric mean of two TFP indices. The first index is calculated with respect to period t technology, while the second index is evaluated with respect to period t+1 technology. The advantage of Malmquist index is that it allows us to distinguish between shifts in the production frontier i.e. Technological Change (TC) and movement of firms towards the frontier Technical Efficiency Change (TEC). The measure of technical efficiency must be between 0 and 1.

Total Factor Productivity Change Index =

[Please download the PDF to view the mathematical expression]

Technological Change Index =

[Please download the PDF to view the mathematical expression]

Technical Efficiency Change Index

[Please download the PDF to view the mathematical expression]

Pure Technical Efficiency Change Index =

[Please download the PDF to view the mathematical expression]

Scale Efficiency Change Index =

[Please download the PDF to view the mathematical expression]

The use of Malmquist Index gives a fair idea about the Total Factor Productivity growth and the components...

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