To
study the impact of livestock industrialization on the scales of operations in
milk production and livelihoods and welfare of rural households, one needs a
sample containing a sufficient number of households representing various scales
of operations (small, medium, large, commercial) and regions. This chapter
briefly outlines the survey design followed to select the regions/states, and
sample households and methods employed to collect field data.
The
data used in this study come from a survey of 520 households in six districts
of three leading milk-producing states that have well-developed infrastructure
for dairy production. Figure 4.1 shows the location of the study area.
4.1 Sampling Methodology
The
major objective of the study was to examine the impacts of ramping up the scale
of operations-and particularly commercialization of dairy production-on
social-health-environment (SHE) outcomes, particularly the livelihoods of rural
households in different milk-producing regions in India that reflect
significant differences in the structure of the industry. The study was
conducted in three states-Gujarat, Punjab, and Haryana-that are well-developed,
leading milk-producing states and represent different forms of organizational
structure. In Gujarat, a successful dairy development program has been achieved
largely through milk cooperatives, and it is considered one of the most
successful models of dairy development. In contrast, Punjab and Haryana are
dominated by the private sector, and the presence of cooperatives is limited to
a few pockets. The livestock population in the selected states is shown in
Annex Tables 4.1, 4.2, and 4.3.
Figure 4.1 Map of India showing
the study area
4.2 Sample Size and Composition
Given the central importance of scale of operation in
the study, efforts were made to select a representative sample of households
(small and large) covering differences in the extent of dairy development,
likely potential for further development, types of marketing channels, and scale
of activity. The farmers were categorized into three categories on the basis of
number of milk animals: small-up to 3 animals; medium-4 to 10 animals;
large-more than 10 animals. We also decided to include a small sample of
commercial/peri-urban dairy farms that are close to the cities. Based on these
criteria and discussion with various stakeholders-including government
officials, private sector players, and village leaders-a stratified sample of
520 households consisting of 260 farmers from Gujarat, 130 from Punjab, and 130
from Haryana was drawn. Sample selection was done randomly, except that an
effort was made to include statistically significant subsamples of small-scale
and larger-scale dairy farms for each region. The study area covered three villages
from Mehsana, five villages from the Kheda district of Gujarat, two villages
each from the Ludhiana and Moga districts of Punjab, and two villages each from
the Karnal and Jind districts of Haryana (see Annex Table 4.5). The
commercial/peri-urban dairy farmers close to these cities were also included in
the sample. The main focus in choosing the villages was to represent scale
differences and types of marketing arrangements existing in the study area. The
distribution of sample households in various districts is given in Table 4.1.
4.3 Survey Timing and Problems Encountered
The household survey was carried out during the months
of December 2002 and March 2003. The data were collected using a pretested
structured questionnaire. The questionnaire was pretested in all locations
during September and October 2002 and then, based on the response and
experience, the questionnaire was revised for better effectiveness. The
questionnaire was administered to the decision maker in the family. The
information collected in the survey included data on household demographics,
land ownership, cropping pattern, agricultural production, livestock ownership,
asset ownership, milk production and marketing, labor employment in dairying,
feed and fodder use, animal health and breeding services, credit, and
environmental issues. The agricultural data cover the 2001-02 rabi and kharif[70]seasons.
Table 4.1 Distribution of sample households by
category and state
|
Region/State |
Small
|
Medium
|
Large
|
Commercial
|
Total
|
|
North Zone |
100
|
68
|
58
|
34
|
260
|
|
Punjab |
|||||
|
Ludhiana |
25
|
18
|
14
|
5
|
62
|
|
Moga |
25
|
15
|
16
|
17
|
73
|
|
Haryana |
|||||
|
Karnal |
25
|
17
|
14
|
8
|
64
|
|
Jind |
25
|
18
|
14
|
4
|
61
|
|
West Zone |
100
|
80
|
50
|
30
|
260
|
|
Gujarat |
|||||
|
Mehsana |
50
|
40
|
25
|
15
|
130
|
|
Kheda |
50
|
40
|
25
|
15
|
130
|
|
TOTAL |
200
|
148
|
108
|
64
|
520
|
Source: IIM/IFPRI India Dairy Field Survey, 2002-2003.
The
household survey was carried out by selected enumerators who had fairly good
experience and communication ability. Extensive training was given to the
enumerators to make them acquainted with the questionnaire. All enumerators
were able to understand the language, culture, and tradition of the area, which
enabled them to overcome barriers of communication with the households. In the
course of data collection, there was appropriate supervision to ensure the high
quality of information. Incomplete questionnaires were detected and improved by
revisiting respondents wherever possible.
Relevant secondary information related to the study area was also collected from published and unpublished sources based on discussion with key stakeholders in the study area to supplement the primary data collected from selected households. Local administration offices, State Milk Marketing Federations, and dairy plants were visited to obtain supplementary information.
The
survey experienced several problems common to fieldwork. The most serious
problem was meeting with the household head, who was always preoccupied with
routine work. In the dairy sector, there are seasonal variations in milk
production and feeding patterns, which were not captured in the one-time survey
of selected households due to time and other constraints. The wide regional,
cultural, social, and linguistic variations in India might have had some effect
on the quality of the information.
Relevant secondary information related to the study area was also collected from published and unpublished sources based on discussion with key stakeholders in the study area to supplement the primary data collected from selected households. Local administration offices, State Milk Marketing Federations, and dairy plants were visited to obtain supplementary information.
4.4 Variable Construction
The data collected covered information necessary to
make farm-level indices of social, economic, and environmental outcomes and
efficiency indicators comparable across different categories of farms. An
attempt was made to explicitly measure differences across farms in the extent
to which negative environmental externalities from keeping livestock are offset
by specific measures to mitigate these effects. In order to empirically investigate
the research questions raised in the study, we constructed variables. Dependent
variables include profit per unit of output for the stochastic profit frontier
model and expenditure per unit of output on pollution abatement for the
environmental regression model. Independent variables include farm inputs and
infrastructure per unit of output, input and output prices, farm-household
socioeconomic and demographic characteristics, a scale variable, and many other
relevant explanatory variables. This section describes the variables included
in the analysis and discusses the estimation technique.
4.4.1 Expenditure on Pollution
Abatement
Expenditure on pollution abatement was measured in terms of imputed value of manure, annualized expenditure on manure storage sheds, cost of transportation of manure from production to end-use point, cost of spreading manure in the field, cost of making dung cakes (if used as fuel), and other taxes and fees. Expenditure per unit of milk was used as a proxy for the pollution abatement expenses.
4.4.2 Net Returns from Milk Production
Net returns/profit from milk-production activity were calculated by taking the difference between gross returns and variable costs. Gross returns were derived by adding revenue from main product and by-products; that is, milk production (quantity produced times price of milk) and imputed value of manure. Variable costs included cost of feed and fodder, hired labor, veterinary services and medicines, cost of breeding and extension services, cost of transport of inputs, cost of maintenance of building and equipment, and other overhead costs.
4.4.3 Price of Fodder
The price of fodder was derived by taking the weighted average of market/imputed price paid by the farmer for different kinds of green fodder and dry fodder fed to dairy animals. It was expressed in rupees per kg of fodder.
4.4.4 Price of Feed
The price of feed was estimated by calculating weighted average market price paid by the farmer for various types of concentrates and other feed supplements fed to the animals. This variable was expressed in rupees per kg of concentrate feed.
4.4.5 Buildings and Equipment
The annualized value of cattle sheds, fodder storage sheds, milk cans, buckets, measuring instruments, chaff cutters, and other equipment used in milk production was derived through annualizing the value of buildings and equipment.
4.4.6 Wage Rate
Since most of the farmers were not employing hired labor for milk-production activities on their farms, it was difficult to get exact information about the wage rate. Moreover, there were large variations in wages paid to farm workers in the study area. Therefore, we have taken the prevailing wage rate in the study area as the wage rate for the selected farms. However, in certain cases there are very small variations in the wage rates within a given sample. Wage rate was expressed in terms of rupees per day.
4.4.7 Family Labor
Milk production is an important activity for small and marginal farmers, and family labor is used for most of the dairy farming activities. Detailed information on employment in various milk-production activities-such as bringing fodder from fields, cleaning cattle sheds, milking animals, and selling the milk-was collected from all the selected households. The average family labor use (minutes) per unit of output was computed from the data.
To explain the variations in net returns per unit of output and/or environmental pollution abatement behavior across different categories of farms, selected socioeconomic variables representing age, education, experience, membership in organizations, number of livestock/agribusiness training programs attended during the past two years, and distance to market were included in the efficiency models. To capture the impact of transactions costs on the profitability of a farm, dummy variables-such as access of the household to information, market, credit, technology, and land tenure system-were used in the model. A brief discussion of the socioeconomic and demographic characteristics of the sample households is given in Chapter 5.
Expenditure on pollution abatement was measured in terms of imputed value of manure, annualized expenditure on manure storage sheds, cost of transportation of manure from production to end-use point, cost of spreading manure in the field, cost of making dung cakes (if used as fuel), and other taxes and fees. Expenditure per unit of milk was used as a proxy for the pollution abatement expenses.
4.4.2 Net Returns from Milk Production
Net returns/profit from milk-production activity were calculated by taking the difference between gross returns and variable costs. Gross returns were derived by adding revenue from main product and by-products; that is, milk production (quantity produced times price of milk) and imputed value of manure. Variable costs included cost of feed and fodder, hired labor, veterinary services and medicines, cost of breeding and extension services, cost of transport of inputs, cost of maintenance of building and equipment, and other overhead costs.
4.4.3 Price of Fodder
The price of fodder was derived by taking the weighted average of market/imputed price paid by the farmer for different kinds of green fodder and dry fodder fed to dairy animals. It was expressed in rupees per kg of fodder.
4.4.4 Price of Feed
The price of feed was estimated by calculating weighted average market price paid by the farmer for various types of concentrates and other feed supplements fed to the animals. This variable was expressed in rupees per kg of concentrate feed.
4.4.5 Buildings and Equipment
The annualized value of cattle sheds, fodder storage sheds, milk cans, buckets, measuring instruments, chaff cutters, and other equipment used in milk production was derived through annualizing the value of buildings and equipment.
4.4.6 Wage Rate
Since most of the farmers were not employing hired labor for milk-production activities on their farms, it was difficult to get exact information about the wage rate. Moreover, there were large variations in wages paid to farm workers in the study area. Therefore, we have taken the prevailing wage rate in the study area as the wage rate for the selected farms. However, in certain cases there are very small variations in the wage rates within a given sample. Wage rate was expressed in terms of rupees per day.
4.4.7 Family Labor
Milk production is an important activity for small and marginal farmers, and family labor is used for most of the dairy farming activities. Detailed information on employment in various milk-production activities-such as bringing fodder from fields, cleaning cattle sheds, milking animals, and selling the milk-was collected from all the selected households. The average family labor use (minutes) per unit of output was computed from the data.
To explain the variations in net returns per unit of output and/or environmental pollution abatement behavior across different categories of farms, selected socioeconomic variables representing age, education, experience, membership in organizations, number of livestock/agribusiness training programs attended during the past two years, and distance to market were included in the efficiency models. To capture the impact of transactions costs on the profitability of a farm, dummy variables-such as access of the household to information, market, credit, technology, and land tenure system-were used in the model. A brief discussion of the socioeconomic and demographic characteristics of the sample households is given in Chapter 5.
|
[70] Rabi
season crops are sown in the beginning of winter season (October-November)
and harvested in March-April. Kharif season crops are sown in the beginning
of the monsoon season in June-July and harvested in September-October.
|
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