Download PDF

Ind. Jn. of Agri. Econ.
Vol.66, No.2, April-June 2011
Gender Earning Differentials in Flower Trading Market in
West Bengal: Capital Constraints on Women’s Income
Sanjukta Chakrabarti and Debnarayan Sarker*
I
INTRODUCTION
The place and relevance of the gender issue in relation to professions,
organisations, etc. has of late attracted the attention of scholars throughout the world
as a result of the national and international resurgence of the women’s movement.
Traditionally ‘gender’ was referred to the biological differences between men and
women. Social scientists use gender to describe a fundamental axis of social
differentiation, alongside class and race. Over time the differences between men and
women have become the basis for gender analysis - often placing the women at a
disadvantage in many ways. There exist gender earnings differentials in which
women usually receive lower wage/income than men in the same occupation, and this
is true across all occupations. Despite considerable research in intra-occupational
gender earning differentials in some areas, there is little research on this issue in the
trade market of flower crop. This study is an attempt to examine this issue in the
trade market of flower crop in West Bengal, which employs a large section of women
workforce (Sarkar, 2004, Government of West Bengal, 2001,2004).1
Despite the fact that the intra-occupational gender earnings differentials may be
due to labour market discrimination or differences in education, experience, effort
and working conditions, the other crucial factors responsible for intra-occupational
gender earnings differentials are demand side constraints of the participants in the
labour market. They are not the same for all occupations; rather they vary across
occupations and also within the same occupation over time and space. While
examining viable entrepreneurial trades for women in agriculture in Haryana, if not
particularly the trade in floriculture, the study undertaken by Agro-Economic
Research Unit (2007) on Haryana shows that the poor women face limitations, among
others, in terms of virtually negligible capital base, which fails them to receive
potential gains from trade compared with their male counterpart. However intraoccupational gender earnings differentials under flower crop marketing have hardly
*Assistant Professor, Bangar Mahavidyalaya, Bhangar, 24 Parganas, South 24 Parganas and Professor and
Secretary, Centre for Economic Studies, Presidency University, Kolkata, respectively.
This paper is a revised version of the part of Ph.D. work of the first author. The authors are grateful to the
anonymous referee and the editor of this Journal for their helpful comments, suggestions and valuable insights on the
earlier draft of the article. However the usual disclaimers do apply.
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
199
been studied. Newman (2001) finds that the gender gap in wages in the flower
industry is smaller than that in any other sector in Ecuador, though the hypothesis is
not tested directly. In spite of increasing involvement of women in the agricultural
sector either as agricultural workers or as marketing agents, there exists wage/income
gap between male and female workers or between male and female marketing agents
(Elson, 1997). Maerterns and Swinnen (2009) observe that more than 75 per cent of
women are engaged in cut flower industry in Kenya; but the economic benefits to
women have diminished in the trade market of flower crop because, the economic
constraints, among others, have positive impact on women’s lower economic benefit
compared with their male counterpart. The main objective of this paper is not to
examine the intra-occupational gender earnings differentials in the trade market of
flower crop in West Bengal due to possible market discrimination - the main critique
of mainstream economic analysis of gender (Rubery, 1989;Blau and Ferber,1986)- or
differences in such factors as education, skill, effort, responsibility and working
conditions which support the mainstream economic perception of gender analysis
(Bergmann, 1986; Gunderson,1994); rather this paper tries to explore whether the
capital constraints act as an important part for intra-occupational gender earnings gap
between women and men marketing agents. The evidence seems to help us draw
certain inferences on women employment in an informal sector- domestic trade
market of flower crop in West Bengal, which has to be substantiated by more
intensive work.
West Bengal is India’s third largest flower producer after Karnataka and Tamil
Nadu in the production of cut flowers. West Bengal produces flowers like rose,
tuberose, marigold, gladiolus, gardenia, carnation, gerbera, chrysanthemum, which
have vast scope for its external and internal demand. The area under flower crop in
West Bengal was 9.8 thousand hectares in 1996-97, but in 2002-03, it stood at 17.33
thousand hectares, registering around 9.8 per cent compound growth rate per annum
between 1996-97 and 2002-03, whereas production growth was around 16.54 per cent
during that period (Government of West Bengal, 2001, 2004). Though the history of
growing flowers and ornamental plants is too old, the commercial trade on these have
picked up recently, mainly, due to the impact of economic reform (1991-92).
Following these reforms, West Bengal has started commercial farming on a large
scale from the mid-1990s. The production of cut flowers increased over the years to
attain a production of 1,952 million flowers during 2002-07 from 615 million cut
flowers in 1992-97. West Bengal leads the pack with a contribution of 8,963 lakh cut
flowers followed by Karnataka with 4,134 lakh cut flowers. But the commercial
flower farming is mainly restricted to certain districts of the state (Government of
West Bengal, 2001): five districts, namely, Midnapore, Howrah, Nadia, 24 Parganas
(North), 24 Parganas (South) - mainly produce commercial flower crops in West
Bengal in alluvial zone and Darjeeling district produces commercial flower crops in
the hill zone (Sarker and Chakraborty, 2005; p.67).
200
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
The traditional commercial flower crops produced in alluvial zone of West
Bengal are, mainly, rose, tuberose, gladiolus, marigold, jui, bel and chrysanthemum.
But the flower farming and marketing in alluvial zone and hill zone of West Bengal
have hardly been studied. A study of flower farming in alluvial zone of West Bengal
reveals that flower crops like tuberose, marigold, rose, gladiolus are more productive
and profitable than that of the main field crops like paddy and potato (Rahmin and
Sarkar, 1997). Also important is that, the trade market of flower crop in West Bengal
has employed a large section of women work force, the weaker section of the society
(Sarkar, 2004). So, it is important to study as to whether the capital constraints fail
women marketing agents to receive the potential gains from trade of flower crops in
West Bengal compared with their male counterparts.
The paper is organised as follows. Section II presents the data set and
methodology. The important results are contained in Section III. Section IV presents
the conclusions.
II
THE DATA SET
To examine the stated objectives field survey (primary source) is the main source
of data collection for this study. As no published data relating to the marketing
agents of the flower markets under study are available from any secondary source,
hence data for the year 2006-07 were collected through the field survey method. Data
collected from the sample respondents were taken up from April 2006 to March
2007. This study undertook household survey of 400 flower crop marketing agents 200 female marketing agents (core group) and 200 male marketing agents (control
group) - taking samples from four types of markets,2 primary, secondary, sub- and
metropolitan - under five districts of West Bengal, using stratified random sampling
method. The procedure of selection is in the following lines.
Firstly, according to the information from Directorate of Horticulture,
Government of West Bengal, West Bengal, five districts - Midnapore, Nadia,
Howrah, 24 Parganas (North) and 24 Parganas (South)- having higher proportion of
area under commercial flower crops in alluvial zone and Darjeeling district produce
commercial flower crops in hill zone (Government of West Bengal, 2001). We
consider all our samples from alluvial zone.
Secondly, two markets of each type were selected from three types of market
(village level, secondary and sub-markets) under five districts including Kolkata,
with the principle that those markets have higher number of marketing agents than
other markets from each district, and one metropolitan market (Mallikghat) from
Kolkata. It is worthwhile to mention that Mallikghat flower market is the highest
metropolitan market of eastern India, because the daily volume (quantity) of sale and
purchase of different types of commercial flower crops is the highest of all flower
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
201
markets in eastern India. Moreover, the inter-state trade and inter-country trade of
flower crop are executed from Mallikghat flower market in Kolkata.
The village level markets selected for final survey are Puranagar from Nadia
district and Gaighata from 24 Parganas(S) district. Similarly, the secondary level
markets selected for final survey are Thakurnagar from North 24 Parganas district
and Deolti from Midnapore districts; sub-markets selected from Kolkata are New
Market and Sealdah Market; the only metropolitan market selected for final survey is
Mallikghat flower market, the highest flower market (in quantitative flow of
business) in eastern India.
Thirdly, selection of the sample of marketing agents of core group (female
marketing agents) has been done by the method of Simple Random Sampling
Without Replacement (SRSWOR) depending on pilot survey (or preliminary survey
of population) on the total number of marketing agents in each market selected for
final survey. The common features that appears from pilot survey ( or preliminary
survey) of this study are: (i) Marketing agents (or market middlemen) can be
classified as LW (local wholesaler), SW (secondary wholesaler), MW (market
wholesaler) and retailer; (ii) More than 78 per cent of women marketing agents
(core group) are retailers in all categories of flower crop markets, about 62 per cent
of the LW were male marketing agents (control group) in all categories of flower
crop markets; (iii) the prevalent flower crops offered for purchase and sale are rose,
tuberose, bel, jui, marigold, gladiolus and chrysanthemum.
Finally, the female marketing agents’ households of each selected market under
core group are randomly selected (SRSWOR) from the population of the same
obtained from pilot survey with two principle characteristics. (i) We took samples
only from retailers, because they are the most prevalent marketing agents in the
flower crop markets in our surveyed area appearing from pilot survey. (ii) Also
important is that we took samples from pure marketing agents, i.e. marketing agents
who independently (not jointly) act as retailer.
Samples for core group (female marketing agents’ households) in each market
were 25. As each type of market comprises two markets, the number of samples for
each type of market is 50. However combining all samples together total samples for
core group (female marketing agents’ households) in four types of market work out to
200 in number3.
Similarly, male marketing agents’ households (control group) are randomly
selected (SRSWOR) from the population of each selected market based on pilot
survey taking equal number of samples in keeping with core group selected from
each market. However, data have been collected from 400 households - 200 from
core group and 200 from control group - from an intensive field enquiry through a
scheduled questionnaire.
In order to study the different aspects of flower marketing, tabular analysis,
proportions, simple percentage, averages, etc. have been used. A Classical Linear
Regression Model is also used following Ordinary Least Square (OLS) method in
202
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
order to provide an answer to the question of how real net annual income (Rs.) of
flower marketing agent relates to types of interest rate (namely, daily interest rate,
monthly interest rate and yearly interest rate on the basis of mode of repayment),
types of market (village level market, secondary level market, sub-level market and
metropolitan market) and gender of the marketing agent (male and female). To
estimate the regression model we have used the computer software package SPSS.
The regression model is estimated in linear form with constant term. The problems of
heteroskedasticity and multicollinearity have also been checked for the regression
model.
Following is the form of Classical Linear Regression Model:
NR = α+β1ARI+β 2MRI+β 3DRI+γ11D11+γ12D12+γ13D13+λD3+δD4+ μ
Where NR= per capita net real annual income of flower marketing agent,
RI=Annual Rate of Interest; MRI=Monthly Rate of Interest; DRI=Daily Rate of
Interest; D11=1 for Metropolitan Market,=0 for Otherwise; D12=1 for Secondary
Market, =0 for Otherwise; D13=1 for Sub-market, =0 for Otherwise; D3=1 for
Female,=0 for Otherwise; D4=1 for Lean Season,=0 for Otherwise; α= the intercept;
μ = the error term.
III
RESULTS
The socio-economic profile of the sample villages is presented in Table 1. Some
of the important characteristics emerge from the Table. (1) Considerable majority of
men and women marketing agents’ households in all types-markets (more than twothirds of households in all markets) belong to SC or ST. (2) Majority of the women
marketing agents’ households in village level and secondary level market live under
BPL category. Even about 42 per cent of women marketing agents’ households in the
sub-level market live under BPL category. (3) Individual marketing agent bearing
major household’s income (real) from flower trading business works out to 79 per
cent or more in all types of markets. It indicates that the considerable majority of
marketing agents in all types of markets are the main and major bread earners of their
households and they receive their major income (real) from flower trading business
only. But the incidence of dependence for household’s income (real) on individual
marketing agents is much higher for women marketing agents in all types of markets
(the range varying between 92 per cent and 100 per cent cases) as compared with
their male counterparts.(4) More than two-third of both male and female marketing
agents in all types of market have received education up to primary level. All these
facts seem to suggest that both women and men marketing agents’ households
possess low social status; but from economic point of view women marketing agents’
households, in particular, have much poorer economic conditions compared with
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
203
their male counterpart in almost all types of market. Therefore dependence on the
trade market of flower crop particularly for female marketing agents under this
sample, in particular, is expected to have a substantial impact on the livelihood of
those households.
TABLE 1. SOCIO-ECONOMIC CHARACTERISTICS OF SAMPLE HOUSEHOLDS
Types of
market/ Types
of marketing
agents (MAs)
(1)
Village level
Retailer
Sec. level*
Retailer
Average
size of
households
(2)
4.68
(5.27)
4.26
(4.33)
Per cent of
HH
belonging
to SC and
ST
(3)
92
(84)
Per cent of
HH
illiterate
(4)
6
(10)
88
(92)
4
(6)
Per cent
of HH
primary
education
(5)
80
(84)
Average
size of
land
holding
(acres)
(6)
0.16
(0.46)
Per cent of
BPL
households+
(7)
72
(28)
Per cent of
MAs
bearing
major HH
Income
(real)
(8)
100
(86)
76
(80)
0.11
(0.53)
58
(22)
97
(78)
3.89
80
4
71
0
42
92
Sub-market
Retailer
(4.45)
(72)
(0)
(76)
(0.36)
(10)
(79)
Metro market**
3.86
76
2
68
0
0
91
Retailer
(4.18)
(68)
(2)
(72)
(0.22)
(0)
(83)
Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents.
*Secondary Level Marker; **Metropolitan Market; + As per BPL Survey 2005, Department of Panchayats and
Rural Development, Government of West Bengal.
Participation of Credit Markets and Sources of Borrowings
First, we try to examine the incidence of dependence on credit market-formal and
informal4 for both men and women retailers, the only type selected because they are
the most prevalent women marketing agents in all types of flower crop markets
(village level, secondary level, sub–level and metropolitan level) in the area we
surveyed. Table 2 reveals two important facts. First, women marketing agents
belonging to 86 per cent cases or more in each type of market depend on credit
market as debtors, whereas for men marketing agents it accounts for about 62 per
cent cases or more in each type of market. Second, women marketing agents depend
on informal loan in cent per cent cases, whereas the dependence on formal loan is
almost negligible for men marketing agents. These results, however, suggest that the
considerable majority of both female and male marketing agents depend on informal
credit market as debtors to meet up their credit requirements, and their dependence of
formal loan is almost nil. Also the incidence of indebtedness on informal loan is
much higher for all categories of female marketing agents who have no access to
formal loan.
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
204
TABLE 2. PARTICIPATION OF MARKETING MIDDLEMEN IN CREDIT MARKET
UNDER DIFFERENT TYPES OF MARKET
Percentage of borrowing marketing agent
under different category of loan
Types of market/ Types of
marketing agents
(1)
Percentage of marketing
agents borrowing
(2)
Formal
(3)
Village level market
90
Retailer
(78)
Secondary level market
86
Retailer
(62)
97
Sub-market
Retailer
(76)
(01)
90
Metropolitan market
Retailer
(74)
(03)
Source: Field survey..
Note: Figures in parentheses indicate percentages for male marketing agents.
Informal
(4)
Both
(5)
100
(100)
100
(98)
100
(95)
100
(97)
(02)
(04)
-
Informal Loan: Lenders Type, Collateral and Purpose
As informal loan is the only source of loan for almost all categories of female and
male marketing agents of this study, this paper now explains lenders type, collateral
and purpose of informal loan in different types of market for both types of female and
male marketing agents (Table 3). Informal lenders of this study are, mainly, of three
types-money lenders, traders or vendors and others (friends, relatives etc). The
important findings of Table 3 are of the following lines: First, as regards the informal
loan is concerned, the incidence of dependence of traders/vendors loan is much
higher for female marketing agents, whereas such a dependence of money lenders’
loan is much higher for male marketing in all types of market. Second, minority of
men marketing agents obtain loans from informal sources offering some sort of
collateral in all types of market, the receiving of collateral loan by men marketing
agents being at least 27 per cent in all types of markets. The majority of men
marketing agents, who receive collateral loan, offer non-land collateral for obtaining
informal loan. But women marketing agents obtain loans from informal sources
without offering any type of collateral in any type of market. It seems to imply that
women marketing agents have virtually negligible capital base as compared with their
male counterparts in the domestic trade market of flower crop in the area we
surveyed. Third, in majority of the cases both women and men marketing agents use
informal loans for production purposes in all types of villages, although the relative
incidence of production and consumption loan are somewhat higher for men and
women marketing agents respectively. The overall findings that emerge from Table
3 are that almost all marketing agents in all types of markets receive informal loans
mainly either from money lenders or from traders without any collateral and such
loans are mainly used for production purpose.
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
205
TABLE 3. LENDER TYPES, COLLATERAL AND PURPOSE FOR LOAN IN
DIFFERENT TYPES OF MARKET
Percentage of loan contract from
different informal sources
Types of market/
Types of
marketing agents
(1)
Village level
Retailer
Money
lenders
(2)
29
(45)
Traders/
Vendors
(3)
71
(45)
Others
(friends
or
relatives)
(4)
(10)
Secondary level
Retailer
19
(54)
79
(26)
02
(20)
Percentage of
loan with
collateral
Percentage
of loan
without
collateral
(5)
96
(73)
95
(62)
Land
(6)
(09)
Others
(7)
04
(18)
(11)
05
(27)
Percentage of loan used
for the purpose of
Production
(8)
62
(82)
Consum
-ption
(9)
38
(18)
67
(79)
33
(21)
Sub-market
48
50
02
98
02
65
Retailer
(72)
(19)
(09)
(71)
(10)
(19)
(93)
20
67
13
96
04
77
Metro.market**
Retailer
(53)
(41)
(06)
(69)
(07)
(24)
(89)
*Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents.**Metropolitan market.
35
(07)
23
(11)
Mode of Repayment of Informal Loan
Table 4 represents the characteristics of the informal loan. Here loans are
categorised into three types depending on their mode of repayment, namely, yearly,
monthly and daily. Some issues of the Table are worth noting. First, in majority of
the cases women marketing agents receive daily loans in all types of markets, while
on the other hand majority of male marketing agents receive non-daily loans in those
markets. In other words, women retailers are more prone to daily loan whereas
majority of male retailers prefers monthly or yearly loans in all types of markets.
Second, the average size of daily loan is considerably higher for female marketing
agents, but in contrast average size of both monthly and yearly loan is much higher
for men marketing agents in all types of market. Third, the average annual rate of
interest of daily loan is exceedingly higher than either of annual rate of interest of
monthly loan or of annual rate of interest of yearly loan. For daily repayment of loan
the annual rate of interest varies between Rs.547.65 and Rs.1277.50 paid for the
principal of Rs. 100, which is much higher than either of the monthly repayment of
loan (the annual rate of interest varies between Rs111 and Rs.159 against principal of
Rs.100) or of the yearly repayment of loan (the annual rate of interest varies between
Rs.29 and Rs.40 against principal of Rs.100). Fourth, as the incidence of dependence
of traders/vendors loan is much higher for female marketing agents (Table 3), in
major cases of money lenders loan to female retailers might be on daily payment
basis. As the overall results of Table 4 seems to suggest in all types of market,
although almost all women and men marketing agents are tied with informal loan
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
206
contract, majority of women marketing agents, unlike their male counterpart, in all
types of villages bear the burden of higher size of informal daily loan whose rate of
interest is exceedingly higher than either of the monthly loan contract or of yearly
loan contract compared with their male counterpart.
TABLE 4. CHARACTERISTICS OF INFORMAL LOAN (MODE OF REPAYMENT:
YEARLY/MONTHLY/DAILY)
Yearly
Types of
market/Types
of marketing
agents
(1)
Village Level
Retailer
Secondary
Level
Retailer
Sub-Market
Retailer
Metro Market**
Retailer
Monthly
Daily
Agent
(per
cent)
(2)
24
(24)
22
(16)
Average
amount
(Rs.)
(3)
1400
(2575)
2463.64
(4700)
Average
rate of
interest*
(4)
33
(29)
34
(32)
Agent
(per
cent)
(5)
16
(36)
26
(48)
Average
amount
(Rs.)
(6)
1333.33
(2000)
1562.5
(2700)
Average
rate of
interest*
(7)
120
(111)
147.35
(139)
Agent
(per
cent)
(8)
60
(40)
52
(36)
Average
amount
(Rs.)
(9)
625
(225)
656.82
(462.5)
Average
rate of
interest*
(10)
730
(547.65)
1195
(912.50)
22
(36)
15
(44)
8227.23
(9000)
10700
(14275)
40
(36)
37
(35.25)
26
(40)
30
(28)
5576.92
(6280)
5900
(7050)
159
(150)
150.63
(145)
52
(24)
55
(28)
688
(475)
552.27
(200)
1277.50
(1000)
1060
(780)
Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents; Average **Metropolitan
Market;*Average annual rate of interest.
Income Status and the Incidence of Informal Loan
In Table 5, an attempt is made to examine the income status of marketing agents
in four types of market. Here we present the annual net real income (average) of
marketing agents which is determined by deflating the money income by cost of
living index of agricultural labourer for the year 2007-08 taking 1986-87 as the base
year. Net money income is calculated by subtracting marketing cost and cost of
interest from gross income. It shows that net income (money/real) is the highest in
metropolitan market for both men and marketing retailers followed by sub-market,
secondary level market and village level market, and as compared with male
marketing agent female marketing agent receives lower net (money/real) income for
all types of market.
In Table 6, we examine the impact of important determinants (namely, interest
rate, sex of marketing agent and types of markets,) on per capita annual real net real
income (Rs.) of flower marketing agents based on a simple OLS regression model.
The results show that all the variables considered in the regression model are of
expected sign but all are not significant. As regards rate of interest is concerned,
although the coefficient of all types of rate of interest (daily, monthly, yearly) are of
expected (negative) sign, the value of coefficient for daily interest rate is only
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
207
TABLE 5. ANNUAL PER CAPITA NET REAL INCOME OF MARKETING AGENTS
(Rs.)
Types of
market
(1)
Primary
Market
Types of
marketing
agent
(2)
Retailer
Secondary
Sub-Market
Retailer
Retailer
Metro. Market
Retailer
Gross
income
(3)
23400
(27360)
28080
(33840)
43700
(55800)
55580
(64080)
Marketing
cost
(4)
2404
(3660)
2127
(4300)
4334.15
(5446.79)
5057.80
(6633)
Interest
cost
(5)
3896
(3180)
5433
(4700)
9485.85
(8553.21)
9842.20
(8847)
Total
cost
(6)
6300
(6840)
7560
(9000)
13820
(14000)
14900
(15480)
Net
money
Income
(7)
17100
(20520)
20520
(24840)
29880
(41800)
40680
(48600)
Net real
income
(8)
4120.48
(4944.58)
4944.58
(5985.54)
7200
(10072.29)
9802.41
(11710.84)
Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents.
TABLE 6. OLS REGRESSION OF THE DETERMINANTS OF ANNUAL PER CAPITA NET REAL
INCOME OF MARKETING AGENTS
Variables
(1)
Constant
Annual interest rate
Monthly interest rate
Daily interest rate
Marketing time(Dummy)
Retailer(Lean Season)
Sex(Dummy)
Female
Type of market(Dummy)
Metropolitan market
Secondary market
Sub-market
Adjusted R2
R2
F-ratio
D-W statistic
No. of observations
Coefficients
(2)
4.002*
-1.023
-1.261
-9.841*
-.226*
Standard error
(3)
.140
.980
1.085
1.556
.022
-.952*
.072
.345*
.101*
.230*
.968
.971
36.32
1.868
400
.012
.012
.013
Source: Field survey; *Significant at 99 per cent level.
significant at 99 per cent level; but the values of coefficient for monthly interest loan
or yearly interest loan is not significant either at 95 or 90 per cent level. It might be
an indication that that the effect of daily rate of interest has much higher adverse
impact on annual net return (Rs.) of flower marketing agents in relation to other types
of rate of interest (namely, monthly rate of interest and yearly rate of interest). The
non-significance of the regression parameter of monthly rate of interest and yearly
rate of interest may be judged by the fact that the incidence of burden of annual rate
of interest of monthly loan or of yearly loan borne by flower marketing agents is
markedly less severe than that of annual rate of interest of daily loan they used to
208
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
bear (the annual rate of interest of daily loan varies between Rs.547.65 and
Rs.1277.50). We use dummy variables for determining the effect on income for
female marketing agents. The results show that income of female marketing agents is
lower compared to male, and it is significant. As regards seasonal market dummy is
concerned, it appears negative sign of the parameter which is significant implying
that income level of both male and female marketing agents significantly decreases
during lean season as compared with their income level they receive during peak
season. This is expected because profit per unit of sale and the quantum of sale for
all types flower crops in all types of markets are much higher for both male and
female marketing agents during peak season in relation to lean period. But lean or
peak season for all types of flower crops are not same. However during pujas and
national festivals the price for almost all flower crops under our study becomes
usually high and profit per unit of sale for those crops is much high. The results of
market dummies reveal that income level of marketing agents of metropolitan market
is much higher positive (and significant) impact on annual net real income (Rs.) of
marketing agents followed by sub-market and secondary level markets as expected.
How do capital constraints affect annual net income (money/ real) of women
marketing agents, in particular? Table 4 shows that despite the fact that almost all
women and men marketing agents are tied with informal loan contract, majority of
men marketing agents are tied with non-daily loan contract (monthly/yearly loan
contract), whereas women marketing agents in major cases in all types of villages are
tied with daily loan contract, whose rate of interest is exceedingly higher than either
of the monthly loan contract or of yearly loan contract. Also important is that the
average size of daily loan received by women marketing agents in all types of
villages is considerably higher than men marketing agents. Table 5 also shows that
the per capita annual interest cost of women marketing agents is about 22.52 per cent
more than that of men in the village level market. Such a burden for women
marketing agents in the secondary level, sub-level and metropolitan market is about
15.60 per cent, 10.90 per cent and 11.25 per cent more respectively as compared with
their male counterpart. Table 6 also reveals that the effect of daily rate of interest has
much higher adverse impact on annual net return (Rs.) for flower marketing agents in
relation to other types of loan contract. So, the higher size of receiving daily loan
with exceedingly higher than other types of informal loan contracts by majority of
women marketing agents in all types of villages has yielded more adverse impact on
the net annual income of women marketing agents as compared with their male
counterparts, because in almost all cases the former are the main and major bread
earners of their households (Table 1). It implies that poor women faces limitations,
among others, in terms of virtually negligible capital base, which fails them to receive
potential gains from trade compared with their male counterpart.
A relevant issue is: what are the other constraining factors for the lower income
levels of the women marketing agents as compared with their male counterparts?
These may be due to difference in source (market), quantity of flower traded, profit
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
209
per unit for types of flower traded and period of trading flowers. They have been
examined during two periods of an agricultural year: Table 7 (peak season) and Table
8 (lean season). Some important facts to be noted here are: (1) quantum of transaction
and profit per unit of sale are much lower for female retailers as compared with their
male counterparts for all types of flowers under all types of markets during both peak
and lean seasons. (2) Both the quantum of transactions and profit per unit of sale are
much lower for both male and female retailers during lean season in relation to peak
season in an agricultural year for all types of flowers and for all types of markets. (3)
The quantum of sale for both female and male marketing agents is higher in
metropolitan and secondary markets in relation to sub- and primary markets for all
types of flowers under all types of markets. (4) When units are measured in kg, profit
per unit of sale is higher for bel and jui in all types of markets for male and female
retailers during both the seasons, but average quantum of sale is not uniformly higher
in all types of markets. (5) Despite the fact that rose is measured in number (100
flowers= 1 unit), the profit per unit of sale for rose is the highest of all during both the
seasons. (6) When measurement unit is dozen spikes, profit per unit of
chrysanthemum is somewhat higher than gladiolus in almost all markets for both
male and female retailers during both the seasons; but the quantum of sales for both
TABLE 7. QUANTITY TRADED (AVERAGE) PER DAY, TYPE OF FLOWER TRADED
AND PER UNIT PROFIT FOR INDIVIDUAL RETAILER LEVEL (AVERAGE) IN
DIFFERENT TYPES OF MARKETS DURING PEAK SEASON
Type of market/
quantity sold/Profit
(1)
Village
Profit per unit (Rs.)
Quantity traded (per
day in kg /unit/D.S)
Secondary
Profit per unit (Rs.)
Quantity traded (per
day in kg/unit/D.S)
Sub-level
Profit per unit (Rs.)
Quantity traded (per
day in kg/unit/D.S)
Metropolitan
Profit per unit ( Rs.)
Rose
(1 unit=100
Flowers)
(2)
Tuberose
(1 kg)
(3)
Bel
(1 kg)
(4)
Jui
(1 kg)
(5)
7.40
(8.75)
13
(38)
8.5
(12.5)
9
(21)
8.45
(11.5)
7.5
(23.5)
10.7
(12.20)
8.5
(24)
4.0
(5.22)
6.5
(18)
4.75
(6.38)
12
(29)
5.4
(6.92)
9
(22)
9.85
(13.0)
18
(42)
3.35
(5.75)
16.5
(27)
9.4
(11.2)
15.5
(28)
9.25
(12.5)
9
(24.5)
5.18
(7.1)
10
(26.5)
6.79
(8.46)
15.5
(37)
7.75
(9.21)
16
(40)
14.4
(17.0)
12
(26.5)
7.0
(10.7)
9.5
(27.5)
11
(14.0)
6.5
(30.5)
9.7
(12.75)
8
(27.5)
7.3
(8.52)
7.5
(23)
7.0
(9.75)
10
(39)
7.0
(9.6)
8.5
(26)
14.0
(19.0)
39
(61)
6.0
(8.9)
15
(37)
9.46
(11.0)
12.5
(35)
10.90
(12.75)
16.5
(32.5)
4.90
(5.9)
11
(26.5)
5.75
(7.55)
14
(37)
5.75
(8.13)
25.5
(63)
Quantity traded (per
day in kg/unit/D.S)
Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents.
Marigold
(1 kg)
(6)
Gladiolus
(dozen
Chrysanthemum
spikes)
(dozen spikes)
(7)
(8)
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
210
TABLE 8. QUANTITY TRADED (AVERAGE) PER DAY, TYPE OF FLOWER TRADED AND
PER UNIT PROFIT FOR INDIVIDUAL RETAILER LEVEL (AVERAGE) IN DIFFERENT
TYPES OF MARKETS DURING LEAN SEASON
Type of market/
quantity sold/Profit
(1)
Village
Profit per unit (Rs.)
Quantity traded (per
day in kg/unit/D.S)
Secondary
Profit per unit (Rs.)
Quantity traded (per
day in kg/unit/D.S)
Sub-level
Profit per unit (Rs.)
Quantity traded (per
day in kg/unit/D.S)
Metropolitan
Profit per unit (Rs.)
Rose
(1 unit=100
Flowers)
(2)
Tuberose
(1 kg)
(3)
Bel
(1 kg)
(4)
Jui
(1 kg)
(5)
3.1
(4.80)
7
(16)
1.0
(2.65)
4
(13)
3.9
(4.25)
3
(11.5)
5.0
(5.35)
4.5
(10)
1.5
(2.34)
3
(11)
2.5
(3.90)
6
(18)
0.9
(1.20)
5
(15)
5.75
(7.4)
10
(22)
2.0
(4.37)
6.5
(14.5)
2.75
(5.17)
6.5
(15)
5.0
(7.0)
6
(13.5)
2.3
(3.25)
5.5
(15)
2.6
(3.2)
8
(19)
3.7
(3.1)
7
(18)
6.5
(9.5)
7
(16.5)
3.95
(5.75)
4.5
(11.5)
5.0
(8.0)
4.5
(15.0)
6.6
(8.2)
8
(16.5)
2.5
(4.35)
7.5
(14.4)
2.0
(4.7)
10
(16.5)
3.4
(6.3)
8.5
(15.5)
4.3
(5.5)
15
(36)
2.25
(4.0)
7
(18.5)
4.2
(6.0)
8
(17.5)
6.25
(9.0)
8.5
(24)
1.45
(2.0)
6.5
(17.5)
2.0
(4.0)
9
(20.5)
4.25
(6.55)
16
(36)
Quantity traded (per
day in kg /unit/D.S)
Source: Field survey.
Note: Figures in parentheses indicate values for male marketing agents.
Marigold
(1 kg)
(6)
Gladiolus
(dozen
pikes)
(7)
Chrysanthemum
(dozen spikes)
(8)
categories of retailers is lower in village and sub-markets during peak seasons and in
village, secondary and sub-markets during lean season. These results, however, seem
to suggest that without increasing the cost of marketing there is scope for increasing
income for both women and male retailers from the selection of the trade of those
types of flower crops which yield higher profit per unit of sale instead of decreasing
the sale of those which yield lower profit per unit of sale. In this perspective both
female and male retailers can increase their income through higher quantum of sale of
rose, which yields the highest profit per unit of sale , instead of decreasing the sale of
those which beget lower profit per unit of sale. They may also increase their income
through increasing quantum of sale, particularly, for bel and jui in all types of
markets during both the seasons, for chrysanthemum in village and sub-markets
during peak season and in the village, secondary and sub-markets during lean season.
IV
CONCLUSIONS
This study lends credence to the fact that women marketing agents in all types of
markets receive lower annual net real income compared with their male counterpart,
though all the reasons of lower income for the former is not tested directly. However
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
211
the study suggests that one of the reasons for much lower per capita net real income
for women retailer in relation to their counterparts is the former’s higher indebtedness
to informal source of credit with much higher rate of interest. Due to their virtually
negligible capital base women retailers have higher incidence of receiving informal
loan for their business on daily basis whose rate of interest is exorbitantly higher than
either of the monthly rate of interest or of the yearly rate of interest. It might imply
that the effect of daily rate of interest has much higher adverse impact on annual net
return (Rs.) for female flower marketing agents in relation to other types of loan
contract. This study also shows that informal loan is the only source of loan for
almost all categories of female and male marketing agents, since institutional credit
have been negligibly served to them, with female retailers having no access of formal
loan. In effect, it may lead to the poverty trap, particularly, for female retailers,
because they are, in almost all cases, the main and major bread earners of their
households and they receive their major income (real) from flower trading business
only.
These results also suggest that some other reasons for lower income of both
women and male retailers are difference in quantity of flower traded, profit per unit
for types of flower traded, types of market, and period of trading flowers. However,
without increasing the cost of marketing there is a scope for increasing income for
both women and male retailers from the selection of the trade of those types of flower
crops which yield higher profit per unit of sale instead of decreasing the sale of those
which yield lower profit per unit of sale.
This study, however, has significant implications for policy. Institutional credit is
the urgent need of this hour for both male and female marketing agents to make
domestic trade market of flower crop more profitable for marketing agents .Most
importantly, the provision of institutional credit to female marketing agents , in
particular, must play an important role in lowering the intra-occupational gender
earnings gap between female and male marketing agents in the domestic trade market
of flower crop in West Bengal, which employ a large section of women workforce
who are both socially and economically weaker. So, some schemes need to be
launched by the institutional sources including government for providing greater
supply of credit to these marketing agents because almost all female marketing agents
have virtually no land or any valuable assets to offer as collateral. Added to it, it is
suggested that the institutional credit agencies should think about the means by which
credit could be released to the borrowers without delay in disbursement so that it
might meet up their credit requirements as and when necessary. If the women
marketing agents, in particular, cannot reap the benefit of lower interest rates, they
will fall into debt trap under these informal lenders- money lenders or vendors. They
could be rescued from the grip of these lenders from the informal credit market, who
are executing the practice of lending money at a rate of interest considered to be too
high, only through greater supply of formal loan to them as and when necessary. It
would also help reduce the intra-occupational gender earnings gap in the informal
212
INDIAN JOURNAL OF AGRICULTURAL ECONOMICS
sector - domestic trade market of flower crop - of a developing economy like India
where a large section of women workforce, the weaker section of the society, can
participate in successful income generating programmes and thereby augment rural
employment of backward women. Although this evidence permits us to draw certain
inferences on women in the informal sector, it needs to be substantiated by more
intensive work.
Received October 2010.
Revision accepted June 2011.
NOTES
1. In areas having high incidence of flower crop production, about 60 per cent of working women are
involved as marketing agents in the domestic trade market of flower crop in West Bengal. In India the
Census 2001 data show that 39 per cent of the total workers in farming (cultivators plus agricultural
labour) are women and participation of women is relatively high in non crop agricultural activities such
as live stock, horticulture, fisheries, forestry, processing, storage and transportation. (Vepa, 2005,
p.2563). Floriculture in India has offered a wide range of opportunities to women in terms of
employment, income generation, empowerment and above all self-fulfillment. It plays an important role
in the Indian economy by augmenting rural employment and empowerment of backward women and
earning foreign exchange (Goswami, 2009: p.85).
2. Primary village level markets usually exist at the village level where the flower crop is originally
produced, and directly connect the trade flow to the secondary market or/and metropolitan market.
Secondary markets, which gather larger quantity of flowers than primary markets, usually sit nearby the
important railway station or bus terminus, and directly connect the trade flow to the metropolitan market.
The sub-markets sit usually at different districts towns, sub-divisional towns and other important town
areas. The character of primary and secondary markets is that a considerable portion of flowers of these
two markets are sent to metropolitan market mainly for sale, whereas the marketing agents of sub
markets usually purchase flower crop from metropolitan market or secondary market or primary market
and sell those crops in the former markets (sub-markets). In metropolitan market, which makes a close
link to all other types of market, the daily volume (quantity) of sales and purchase of different types of
commercial flower crops is the highest of all types of markets.
3. Out of 200 samples selected from core group(female marketing agents’ households)50 were taken
from village level market (25 from Gaighata and 25 from Puranagar), 50, from secondary level markets
(25from Thakurnagar and 25 from Deulti), 50, from sub markets (25 from New market and 25 from
Sealdah) and 50, from Metropolitan market (Mallikghat flower market at Howrah in Kolkata).
4. Formal sources of credit include commercial banks and the credit co-operative societies and
informal sources, the village money lender, traders or vendor, friend and relatives in our study areas.
REFERENCES
Agro Economic Research Unit (2007), “Viable Entrepreneurial Trades for Women in Agriculture in
Haryana”, Agricultural Situation in India, Vol. 64, No 5. August.
Bhattacharyya, R. (2009), “Diversification Towards Horticulture in India”, Artha Beekshan,, Vol 18, No.
1, June, pp-88-115.
Bergmann, B. (1986), “The Economic Emergence of Women”, in F. Blau and M. Ferber (Eds.) (1986),
The Economics of Women, Men and Work, Basic Books Englewood Cliffs, NJ:Printice-Hall, New
York.
Elson, Diane (1997), “Integrating Gender Issues into National Budgetary Policies and Procedures within
the Context of Economic Reform: Some Policy Options”, Preparatory Country Mission to
GENDER EARNING DIFFERENTIALS IN FLOWER TRADING MARKET
213
Integrate Gender into National Budgetary Policies and Procedures, Commonwealth Secretariat.,
London.
Goswami , S. (2009), “An Analysis of the Indian Horticulture Industry with Reference to Floriculture”,
Artha Beekshan, Vol 18. No.2, September, pp-85-91.
Government of West Bengal (2001, 2004), Information of Studies of Major Horticulture Crops: West
Bengal, Food Processing Industries and Horticulture Directorate, West Bengal.
Maertens, M. and J.F.M. Swinnen (2009), Gender and Modern Supply Chains in Developing Countries,
LICOS Discussion Paper Series, Discussion Paper 231, pp1-36.
Newman, C. (2001), Gender, Time Use and Change: Impacts of Agricultural Export Employment in
Ecuador, Gender and Development Working Paper 18, The World Bank, Washington, D.C., U.S.A.
Rahim, K.M. and D. Sarker (1997), “Techno-organization Characteristics of Floriculture in West
Bengal”, Indian Journal of Agricultural Economics, Vol.52,No.3. July-September.
Rubery, J. (1989),”Women’s Wage”, in J.M. Eatwell, Milgate and P. Newman (Eds.) (1989), The New
Palgrave Social Economics, Macmillan Reference Books.
Sarkar, D (2004), “Gender Bias and Violence Against Women: A Case Study of Flower Marketing
Agents in West Bengal” Indian Journal of Human Rights and the Law, Vol I, No 1-2, pp. 43-60.
Sarkar, D. and S. Chakraborty (2005), “Household Decision Making in Agricultural Labour HHs: A
Case Study of WB”, Indian Social Science Review, Vol 17. No 2, pp 55-79.
Vepa, S.S. (2005), “Feminisation of Agriculture and Marginalisation of their Economic Stake”,
Economic and Political Weekly, Vol. 40, No.25, pp. 2563-2568.