CHAPTER THREE
MICAH M. CHEATHAM
PRIVATE SECTOR SOLUTIONS TO FERTILITY REDUCTION IN INDIA
The Demographic Transition
The demographic transition is the very core of family planning theory,
tracing the transition of a given society across time, from very high
birth and death rates to very low ones, such that the post-transition gap
between births and deaths is less than or equal to its level prior to the
transition. Conceptually, the demographic transition begins in an
environment in which households, in need of familial labor and heirs,
must compensate for high levels of mortality by producing large numbers
of children; as the provision of public health and sanitation
technologies increases, mortality should greatly decrease, cutting death
rates far below rates of birth. At this point in the transition, high
birth rates are no longer being offset by high rates of death, and
population will boom; the perceived value of having children will
eventually change, and individual reproductive behaviors will adapt,
lowering birth rates until the difference between birth and death rates
is similar to, if not lower than, that which existed prior to the transition.
In the transition experienced by most industrialized nations,
mortality fell slowly and haltingly, relying on innovation and invention
to incrementally cut death rates; eventually, fertility followed this
trend and, after two hundred years of transition (Demeny, 1989), Europe
and the rest of the industrialized world eventually reached stable birth
and death rates and a steady fertility rate at near replacement level.
The experience of the developing world, however, has been quite
different; not until after World War II, and the end of colonialism, did
this region begin its transition. Medical and public health technologies
first discovered during the European transition had since been perfected,
and were grafted into the transition of the developing world, cutting
death rates to levels enjoyed by the industrialized world in a quarter of
the time (U.S. Census Bureau, 1991). Unfortunately, despite the infusion
of large amounts of Western monetary and technological aid, birth rates
have resisted most attempts at forced reduction, leaving a large gap
between current birth and death rates.
As a result, population in much of the developing world today is
growing almost without bound. As the sheer numbers of people within a
given region reach and surpass levels that can be sustained by existing
political, economic, or ecological systems, family planning becomes an
issue of increasing importance. Unfortunately, many fertility-reducing
programs, both past and present, have generally been of limited
effectiveness; although a number of programs have been able to cut
fertility rates to some extent, most of the developing world continues to
face frighteningly high growth rates and
above-replacement-level-fertility. One major limitation of past programs
was a concentration on supply-side marketing; family planners assumed
that there existed a latent demand for contraceptive technology and that
fertility could be reduced by providing a supply of this technology.
This is not to say that these programs have been failures; many have
quite effectively reduced fertility, but in each case, birth rates have
reached some lower threshold, beyond which they simply cannot pass.
Building a Theory on Fertility Reduction
Family planning practices that seek only to meet latent demand
will always reach a limit to fertility reduction which they cannot
breach; this lower limit is, in fact, indicative of a saturation of the
natural (latent) demand market. Clearly, any family planning program
that seeks to overcome limits to fertility reduction must be based not on
meeting an existing, limited demand for contraceptive technology, but on
the expansion of demand markets. Supply-side theories fail in family
planning because they disregard the externalities that exist within a
given households decision to reproduce: The social costs of high
population, and therefore high fertility, are extremely high; yet, so
long as large families are desirable, or profitable, to the individual
household, the (individual) opportunity costs of high fertility will
remain significantly below the (aggregate) social costs, and households
will continue to produce large numbers of children. Thus, effective
family planning programs can exist only where the household opportunity
costs of high fertility are more reflective of its social costs.
Significant reductions in fertility come about only where reduced
fertility is perceived as beneficial to the individual household; in
other words, family planning practices can only truly be accepted where
they are seen as a desirable expansion of choice.
The increasing prevalence of fertility reduction theories of the
type outlined above amongst demographers and family planners (Coale;
Knodel, 1984; Cleland, 1987) has generated a growing body of
policy-related variables that effect fertility rates; one variable with a
pronounced effect on fertility is womens education. As women become
increasingly educated, they begin to take on more of the skills required
for wage-labor; the wages associated with female employment, because they
would be lost to women rearing large numbers of children, provide a
disincentive to high fertility by increasing the opportunity costs
associated with large families. The scatter-point diagram on the
following page seems to support this hypothesis, showing a clear negative
correlation between fertility rates (1990) and the percentage of females
aged twenty-five or older who have completed primary school (1989) over a
wide range of countries.
Although the conceptual link between womens education and
fertility makes intuitive sense and seems to be supported by empirical
evidence, it reveals only one part of a more complex relationship.
Womens education, in this case, acts as a proxy for the somewhat vague
concept of the value of women; specifically, the average level of
education attained by females within a particular society should act as a
flag, indicating the degree to which women participate in that society,
including the value that is placed on their labor. The level of
acceptance of female education within a society should be correlated with
that societys acceptance of female employment in the formal sector; in
other words, womens ability to develop their own human capital, in the
form of education, must be linked to the market demand for female human
capital. Under these conditions, female education acts as a proximate
measure of a given societys norms regarding the full participation of
women in formal sector employment; this is part of what is meant by the
value of women. The link between market demand for female labor and
fertility provides the same conclusion as the link between female
education and fertility, only in a more direct way: The possibility of
losing the potential to earn a wage increases the opportunity costs
associated with large families, and thus has a dampening effect on fertility.
Fertility Reduction in India
The theorization laid out above is heavily biased towards solving
the population problems of the developing world. This concentration is
characteristic of most theories in family planning and is by no means
accidental; the population problems experienced in this part of the world
are more severe than those affecting the industrialized nations, as are
the consequences of ignoring them. In so saying, the key to
understanding the difficulties of this region is in remembering that
these problems are not unique to the nations of the developing world so
much as they are characteristic of the stage of the demographic
transition which most of these nations have reached.
The nation of India is suffering the effects of being trapped in
the median stages of the demographic transition perhaps more than any
other country in the developing world. India currently enjoys a death
rate of 10.07 deaths per 1,000 population (CIA World Factbook, 1995),
lower than that of
both Europe and Russia (U.S. Census Bureau, 1991); yet, its birth rate
remains unnecessarily high, at 27.78 births per 1,000 population (CIA,
1995). In a nation of almost 950 million people (CIA, 1995), a birth
rate-death rate gap of over 17 births per 1,000 population produces a
population increase of over 16 million in excess of replacement levels.
A combination of strong political support on the national level for
family planning programs and extensive Western aid has reduced Indias
fertility rate to 3.4 births per woman (CIA, 1995), an enviably low level
by developing world standards; unfortunately, in a nation as large as
India, the population pressure of even this low a fertility rate is
incredible. The age structure of the Indian population adds an air of
urgency to efforts to reduce fertility; thirty-five percent of the
population is under fifteen years of age, and fertility rates must be
reduced before this cohort reaches reproductive age.
Unfortunately, there is little evidence to suggest that fertility
rates in India will fall in the near future. With national family
planning programs dating back to 1951, no other government in the world
has placed as much of an emphasis on reducing family size than Indias;
however, these programs have generally failed to see the results that
they could have. Government family planning programs have ranged from
offering incentives to couples for contraceptive use to forced male
sterilization, yet none of these has brought about significant reductions
in fertility, largely because the low social status of women has been
consistently ignored. Indian households bear a strong preference for
male children; the son in the traditional Indian household not only
serves as heir and continuation of the family line, but also provides
labor for the family and, according to Hindu tradition, must perform the
parents sacred burial rites. A daughter, on the other hand, represents a
net economic liability because of the financial pressures that her dowry
places on her parents. The dichotomous relationship between the sexes
creates a situation in which women are denied the property rights and
control over economic resources that would increase their social value,
relative to men.
A Free-Market Solution
In a society where womens roles are marginalized, the value of
their labor tends to be underestimated. Where this is the case, the
private sector has the ability to capitalize on this undervaluation by
hiring women at a lower wage than that which is offered to men, thus
capturing increased returns to production; the difference between actual
female wages and the potential wage bill, had males been employed,
generates a fiscal surplus that can be invested into capital expansion of
the industry. Now, if it is true that increasing the employment
opportunities available to women has a significant negative effect on
fertility, this implies that private industry has the opportunity to
affect positive social change in the course of normal profit-seeking
operations. The situation at hand is beneficial to both society and
industry alike.
Where a firm hires women to capture the lower wages associated
with female labor, that firm can experience lower costs of production
without reducing the market price of its goods, in this way increasing
its returns to labor. As other firms recognize the scale effects of
increasing their female work force, they will hire increasingly more
females, boosting the rate of growth of the female labor force. The
female labor force will grow increasingly until the environment of
heightened demand begins to nudge the female wage upward; at this point,
the growth rate of the female labor force will begin to decline. The
growth rate of female participation in formal labor will incrementally
decline as the female average wage increases; eventually, the female wage
will rise to a point where employers are indifferent between the sexes,
and the female participation rate will stabilize.
The increasing-then-decreasing rates of growth story is typical
of models of innovations that lead to lowered costs of production; if the
increased use of womens labor can be characterized as an innovation, the
growth of the female labor force can be mapped out in another way, one
which is complimentary to that which is outlined above. When a firm in a
competitive market captures a lower wage bill due to the employment of an
increased number of women, that firm will lower the asking price for its
particular good, in an effort to expand its share of the market for its
product. Once several firms in an industry expand their female labor
force, they will be in direct competition with each other to capture the
greatest savings to production that this innovation can offer. As more
firms increase their female work force, the practice of hiring women will
become more commonplace, and the original innovators will not see
significantly greater returns to labor over their direct competitors. At
this point, these firms will begin to look to other sources of economic
growth, and the growth rate of the female labor force will begin to
decrease. Once female-to-male employment ratios are equalized across the
industry, the individual firm will have nothing more to gain from
employing more women, and the industrys female labor force will stabilize.
Systems that experience growth rates that at first increase and
then decrease to a steady state equilibrium of no growth can be
replicated with the following generalized equation:
dY/dt = kY * (q - Y)/q (partial derivative)
Here, Y is the percentage of the national labor force that is female, q
is an exogenously-generated upper boundary to growth, t is time, and k is
the constant of proportionality. The variable k is referred to as the
constant of proportionality because the derivative of Y at any point can
be explained, at least partially, as some proportion k of the original
function Y. That the partial derivative of Y is equal to some form of
itself implies that this is an exponential function: de^t/dt = e^t * dt,
and above, dY = kY * dt * (q - Y)/q. The second part of this equation,
(q - Y)/q, is a forcing term, introduced to limit the growth of the
exponential in this equation; this equation is attempting to predict the
growth of a variable that is measured in percentages, and so we must
necessarily impose an upper limit of one hundred percent, if not some
even lower value. The forcing term (q - Y)/q dampens growth by
interacting with Y; where Y is a small number, the term is very close to
one, but as Y increases, the forcing term approaches zero. In short,
this equation states that the female percentage of the labor force would
grow exponentially over time (kY), if it were not for the existence of
some exogenous limit to growth ({q - Y}/q); instead, it grows
exponentially only up to a point, after which growth slows until the
function stabilizes at a fixed value.
We can see that the equation laid out above is just another
interpretation of the Verhulst equation:
Y'/Y = (k/q) * (q - Y), -- 1
where Y'is another form of notation for the first derivative of Y with
respect to t.
We can approach a general form solution of the equation by integrating
equation 1. We begin by multiplying through by Y
dY/dt = Y * [k - {(k/q) * Y}], -- 2
and then separating variables
dY/(Y * [k - {(k/q) * Y}] = dt. -- 3
In order to simplify the integration process, we want to separate the
left hand side of equation 3 into the form:
1/(Y * [k - {(k/q) * Y}] = A/Y + B/{k - (k/q) * Y},
where A and B are as yet unknown. To do this, we multiply both sides of
the above equation by Y * [k - {(k/q) * Y}], to get:
(A * k) - [A * (k/q) * Y] + (B * Y) = 1.
Now, where Y = 0, A = (1/k), and where Y = 1, [(1/k) * k] - [(1/k) *
(k/q)] + B = 1, which gives us the solution B = (1/q). Thus,
1/(Y * [k - {(k/q) * Y}] = (1/k)/Y + (1/q)/{k - (k/q) * Y}.
(This can be checked by multiplying the equation through by Y * [k -
{(k/q) * Y}], which produces 1 - (Y/q) + (Y/q) = 1.)
We now have an equation of the form
[(1/k)/Y + (1/q)/{k - (k/q)Y}] * dY = dt. -- 4
Integrating with respect to t gives us
(1/k) * ln Y - (1/k) * ln[k - (k/q) * Y] = t + C, -- 5
where C is the constant of integration.
Multiplying both sides by k and consolidating the natural logs produces
the following solution:
ln[Y/(k - {(k/q) * Y})] = k * (t + C), -- 6
which simplifies to...
Y = [k * e^(k * {t + C})]/[1 + {(k/q) * e^(k * {t + C})}] -- 7
This is the generalized form of the solution to the Verhulst equation
above; it makes explicit the relationship between time and growth for
this model.
Equation number seven is extremely useful in describing the
growth of the female labor force in India, with some caveats; the most
important of these considerations is that time is used as a proxy for
attitudes towards womens labor. The hypothesis, as stated, is highly
time-dependent; womens labor is used increasingly over time as more of
the individual players in the labor market recognize its value. The use
of time as a proxy for this phenomenon may be slightly misleading, but
the malleability of time as a variable makes it a satisfactory measure of
what is actually a rather nebulous concept. Time is a valid proximate of
any incremental change because it is measured in ordinal numbers; that
is, each number in a time series measures only its location within a
sequence, and does not have any particular value attached to it. Thus,
time will continue to be used in further transformations of the above
equation, with the implicit assumption that it is a proxy for the
changing intensity of use of womens labor.
The generalized solution form makes explicit the relationship
between Y and t, q, and the two constants k and C; however, in order to
generate solutions for specific data, k and C must be replaced with more
definite values. Conventionally, the constant of integration, C, is used
only in indefinite integration; where at least one explicit relationship
between the variables is known, this is definite integration, and C is
assumed to be equal to zero. If we use the most recent value for female
labor force participation available from the World Resources Database and
assume a specific upper limit to growth, we have values for Y and t, and
q, respectively, and can assume C out of the equation, generating a new
generalized form:
Y = [k * e^(k * t)]/[1 + {(k/q) * e^(k * t)}]. -- 8
Unfortunately, the argument of definite integration is not, by itself,
the most robust justification for assuming away C; the transition from
equations 4 to 5 is actually one of indefinite integration. This is
because our explicit relationship between variables uses observed data
from 1990; however, there is no reason to believe that any behavioral
change occurred in 1990 to institute the growth that this equation
describes. Our 1990 data does not constitute any initial conditions, but
instead acts as a baseline for speculation as to the general
applicability of this model.
Nineteen-ninety data is used as a baseline value only because it
is the most recent available; this by no means implies that the process
described above commenced at this date. We perform indefinite
integration between equations 4 and 5 because the data we are using is
clearly not the start of an historical example of the above process; were
it actual historic data, it would be referred to as initial conditions,
and definite integration could be performed. Instead, we use baseline
values, plugging them into the variables in question to generate
hypothetical scenarios as a means of testing the robustness of our model;
we use indefinite integration to preserve the generalizability of the
solution equation, allowing us to test the results of a variety of
baseline assumptions. We are now placed in a position where we have
specific data, yet we have performed indefinite integration and, as a
result, we have the constant C in our equation. Yet, precisely because
we do have specific data, we can still assume away C; we can do this
because, in the following analysis, we treat each set of baseline values
as if it were historical data, and we know that C is not included in the
definite integration of historical values.
Baseline values play their most important role in the
determination of definite values for the constant of proportionality, k.
The World Resources Database provides the following baseline data:
Females accounted for 48.318% of the population, yet only 25.191% of the
labor force of India in 1990. Thus, Y = 0.25191 and, because 1990 is the
baseline year in our iteration, time t = 0. If we assume that, once a
demand increase has been generated, the percentage of women in the labor
force will expand up to but not beyond their proportional representation
in society, then we have set our upper limit to growth at q = 0.48318.
We now have the tools necessary to generate an estimate of k; we begin
with the general form solution,
Y = [k * e^(k * t)]/[1 + {(k/q) * e^(k * t)}] -- 8
and include our baseline values, to generate the following:
0.25191 = [k * e^(k * 0)]/[1 + {(k/0.48318) * e^(k * 0)}]. -- 9
Replacing e^(k * 0) with 1 and multiplying the right hand side of the
equation by (0.48318/0.48318) produces...
0.25191 = (0.48318 * k)/(0.48318 + k),
which provides us with a k-value of approximately 0.52630. Thus, the
general form of our solution for this set of assumptions is:
Y = [0.5263 * e^(0.5263 * t)]/[1 + {(0.5263/q) * e^(0.5263 * t)}]. -- 10
The equation now provides an explicit relationship between the
independent variable t, the policy variable q, and the dependent variable
Y, subject to the baseline assumption that Y(0) = 0.25191, q = 0.48318.
The following graph details the convergence of this equation on the upper
boundary of Y = 0.48318. The accompanying table clarifies the growth
pattern of the function, highlighting the fact that it infinitely
approaches 0.48318 without actually reaching that value.
Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
% 25.10 31.19 36.41 40.40 43.20 45.04 46.20 46.92 47.35 47.61
L.F. 4 3 0 2 0 3 8 5 9 9
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
47.77 47.86 47.92 47.95 47.97 47.98 47.99 47.99 47.99 47.99 47.99
4 6 1 3 2 4 0 4 7 8 9
The upper limit to this equation was arbitrarily set at 0.48318,
the percentage of the total population of India that was female in 1990;
however, this percentage has been growing steadily, although marginally,
over the past twenty years. This implies that our equation may be more
reflective of the growth pattern it attempts to describe if the upper
limit q of our equation were to be included as an increasing function of
t instead of as an arbitrarily determined constant. In fact, the
regression of this data over the years 1970 to 1990 produces the function
Y = (0.000026 * t) + 0.4823, which grows at so slow a rate that it can be
legitimately approximated by any constant function at or about Y = 0.4823.
Although it seems to be appropriate to estimate the upper
boundary to growth with a constant function based on current estimates of
female representation in the general population, the thinking behind this
conclusion may be ignoring some rather serious considerations. India has
a long cultural history of son-preference between children, which may
bias contraceptive and child-rearing techniques; although these practices
have become less prevalent in modern India, the proportion of females in
Indian society in 1990 was still only 48.23%, less than the world rate of
49.68% and significantly below the 51.54% faced by the industrialized
world (WRD, 1994). It may not be unrealistic to assume that some
residual son-preference continues to exist within Indian culture, and
that this is maintaining the proportion of females in society at an
artificially low level; this sort of consideration is linked to the above
model because the prevalence of son-preference amongst households is
directly related to the value of women within a society. Now, where an
increase in womens employment is brought about in a climate of
son-preference, it seems safe to assume that the increased potential for
future wage labor that this places upon a female child may compensate for
any cultural predilection towards sons; in this way, the growth of the
percentage of females in the labor force may increase the percentage of
females in the general population, thus expanding the upper limit q used
in the predictive model.
Any activity that reduces artificial constraints placed upon the
size of the female population within a society is inarguably producing a
public good; however, any points regarding the effects of this
demographic change on the model may be moot. As the graph shows, our
predictive function converges with its upper limit in only ten iterations
(iterations here are denoted as years because this is the unit of measure
that seems to make sense, although other units of time could be used); it
seems unlikely that behavioral patterns that are as deeply ingrained as
son-preference could be changed in as short a time as ten years.
Further, the delayed effects of changes in reproductive behaviors on the
labor pool ensure that any increase in the female population will occur
long after the demand boom has passed, such that female employment rates
are unlikely to be effected by an increase in the female population at
this stage.
A more fundamental criticism of the model suggests that there is
no reason to believe that the growth of the female labor force will be at
all limited by the proportion of females in the general population; it is
more likely that the female labor force will overshoot the proposed limit
of percentage female representation in society. If an individual firm,
in the course of expanding its labor force, recognizes lower costs to
production by employing women instead of men, there is little to prevent
that firm from further reducing costs by replacing as many currently
employed men as possible with women. The only hindrance to this sort of
mass replacement (if we can momentarily assume away contradictory
cultural norms) would be a limited supply of sufficiently-educated women,
and this constraint should weaken significantly once individual
households begin to recognize the newly increased value of their daughters.
It is difficult to determine the extent of the predicted excess
growth of the female labor force; it is easy to believe that employers
themselves will generally be male and will not be replacing themselves,
and so the female labor participation rate could never reach one hundred
percent. In fact, most upper- and middle-management positions would be
closed to women for this same reason; the most physically strenuous jobs,
too, would almost certainly be denied to women. This implies that some
significant percentage of employment positions within the economy exist
which are simply unavailable to women; that is, the demand for female
labor associated with this percentage is inelastically fixed at zero. In
1990, male representation in the work force exceeded male representation
in society by approximately 23%; the fact that men, in a male-dominated
society, are over-represented in the labor force by twenty-three percent
seems to make this figure an appropriate estimate of the extreme-case
upper limit to growth of the womens labor force. This assumption implies
a new upper boundary value of q = (0.48318 + 0.23) = 0.71318, which
generates a generalized solution form of
Y = [0.38948 * e^(0.38948 * t)]/[1 + {(0.38948/q) * e^(0.38948 * t)}], -- 11
the graph of which follows.
Year 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
% 29.65 28.46 27.18 26.20 25.19 56.54 68.75 70.94 71.26 71.31
L.F. 0 0 1 6 1 8 6 1 4 0
2020 2025 2030
71.31 71.31 71.31
7 8 8
Again, a table is provided for ease of reference.
Growth of female representation in the labor force is staggering
here, and probably not particularly realistic. Lack of availability of
data requires that time be expressed in units of five years, which may
exaggerate the graphical representation of the function; however, this
does not negate the fact that the percentage of females in the labor
force more than doubles between 1990 and 1995. In order to make this
data at all useful, the ordinal nature of time must be taken advantage
of; if the difference between two years can be seen only as a difference
of a few places in a generalized time series, then the model can begin to
take on more meaning. Where 1990 is viewed as simply the one thousand,
nine hundred, ninetieth iteration of the series, then the span of a unit
of time increases in its variability, and can take on values larger than
a single year. Although this assumption increases the applicability of
the model, it does so at the expense of its reliability; more
importantly, it fails to address more fundamental ethical questions
associated with female employment overshooting female representation in
society.
Policy Implications
Sustainable economic growth occurs where new jobs are created;
yet within this model, the primary engine for growth of female
representation in the labor force is female replacement of males in
existing jobs. Where females simply replace males at a lower wage, the
individual firms operating costs fall, but social costs may actually
rise; even if each displaced male worker were replaced by a female in the
same household, the overall average household income will fall. Only
where male replacement frees up capital for expansion of the labor force
can replacement dampen the social costs it incurs; unfortunately, this
case increases the number of households earning a wage income while
reducing the wage earned. The true social benefits of replacement growth
come from the reduction in birth rates that this generates; where female
employment rises, fertility should fall, and, under any conditions,
reductions in fertility will cut overall costs to society.
It is quite likely that the population effects of female
replacement may more than compensate for the effects of male
unemployment. In 1990, the labor force growth rate only marginally
exceeded the rate of population growth, while a mere five percent of
working-age Indians were employed in the formal sector (26 million person
labor force, 503 million persons between the ages of 15 and 65, WRD); in
a slow-growth, low employment economy, the sort of restructuring of the
labor market that female replacement requires may incur only a minor
social cost. If this is the case, the benefits of fertility reduction
should easily exceed the costs of male unemployment, leading to clear and
direct benefits to society, at least in the short run. Long run
forecasting is more difficult because the long-term effects of male
unemployment at the expense of females is unclear. The direct effects of
increased male unemployment in an environment of extremely high
unemployment may, indeed, be minor, as discussed above; however, the
effective gender transition of the households primary wage-earner, from
male to female, may produce significant disruptive forces in the
pervading culture.
It should be clear that any increase in the value of women,
especially one as significant as this, is acting in opposition to current
trends and, therefore, must necessarily act as either the cause or the
product of a significant cultural disruption, the effects of which could
never be predicted in their entirety. While this may seem to be a rather
melodramatic conclusion to make, the uncertainty involved in the decision
to consciously change a culture must be taken into full account; the
risks involved in such endeavors must be clearly outweighed by the
benefits. In so saying, it does appear as if Indias population growth
may warrant such strong actions: the negative effects on society,
culture, and the environment associated with large population growth
rates cumulatively represent the greatest problem India has had to face
to date. Sacrificing an indeterminate, and possibly quite large, amount
of culture for the preservation of society as a whole is hardly an ideal
solution; it is not a first- or second-best solution, but an nth-best
solution, the optimal solution subject to a large number, n, of constraints.
One such constraint that has been excluded from discussion to
this point is the fundamental lack of employment opportunities across
both sexes. Where only five percent of the working-age population is
engaged in non-agricultural employment, it is conceivable that the sheer
numbers of unemployed men would bid the male wage down to such a point
that a significantly lower female wage would be infinitesimal; if the
female wage were as low as this suggests, it would actually provide a
disincentive for a given woman to leave the home, as her earned wages
could not compensate for the domestic work she would be sacrificing in
order to enter into formal wage employment. However, in a country that
is 70% rural (WRD, 1995), yet concentrates a majority of its educational
opportunities in urban areas, a majority of the 95% unemployed are
actually agricultural laborers; any residual un- or under-employment may
be composed mostly of rural immigrants to industrial centers who lack the
education, and therefore the job skills, required for increasingly
technical industrial jobs. This implies what we already know to be true
about all labor markets: there is no universal wage; instead, wages are
graded across positions, based on the skills required to perform a
particular job and the responsibilities entailed in it. This model is
meant to consider female entrance into higher-skill, and therefore higher
wage, employment, where a womans wage can be less than that of a man
without being menial; these are the types of job that have an implicit
value attached to them and, by association, can raise the perceived value
of women within Indian society.
The policy implications of this sort of theorization are heavily
dependent upon the amount and the type of economic growth that is
stimulated by female replacement. Where the implications to the firm of
female replacement are extra-normal profits, the government should be
concerned with how and where those profits are invested; the government
has the capability to lower the interest rate through the central bank
and to provide tax incentives for capital expansion, both of which are
powerful investment-stimulating tools. More importantly, the government
is the only player in the market that has the power to confront
traditional biases against women in employment; it must take the leading
role in the stimulation of demand for womens labor that should eventually
generate the process described in the model. The government has the
ability to make female labor more attractive to firms by increasing
female education opportunities, providing logistical and management
training and support to firms transitioning towards a greater female/male
ratio amongst their work forces, and continuing its long-standing
tradition of encouraging female participation in all levels of government.
It seems clear that this program could not succeed if the
government were to focus on either the education of women or the
generation of demand for their labor alone; both must be given equal
attention, and a direct link between the two must be made at every stage
of the process. Although a number of approaches to this problem exist,
the simplest and most direct may be the best option in the earliest
stages; one example would be to increase the degree to which funding of
public schools is based on female representation in classes and to
provide tax credits to individual firms based on the income taxes
collected from their female employees. These types of policies are
suggested not only because they reduce the costs to the central
government that are generally imposed by recruitment campaigns, but more
importantly, because they assign recruitment responsibilities in a more
efficient manner; it seems likely that local public school administrators
and teachers and the owners and operators of local industry would be more
familiar and respected in their communities, and therefore better able to
affect social change there, than unknown bureaucrats from economically,
if not geographically, distant New Delhi. Under its New Economic Plan,
the Indian central government has very successfully turned over many of
its powers to more efficient private-sector groups; by concentrating more
normative taxes on firms, the government can continue in this policy by
privatizing away governmental responsibilities where it can be done at
less cost or with increased efficiency in the private sector.
The one policy implication that should not be garnered from this
material is that a laissez-faire, free market approach to the economy
will provide solutions to social problems. This paper outlines a partial
solution to Indias population problems that works in the private sector
and probably only on a regional level, but only with governmental
support. Without significant government involvement, cultural
predilections will continue to overrule profit-seeking tendencies, and
the role of women in the labor force will always be inappropriately
discounted. Without continued government funding of its own and other,
private family planning programs, the supply of contraceptive technology
could not meet the increase in demand that would come about from the
fertility-reducing effects of female replacement. Most importantly, it
is the role of government of the largest democracy in the world to
regulate both the use of womens labor in its economy and the reduction of
fertility in its society to ensure that its citizens are protected and
that its policies create positive and lasting social change and economic
development.
REFERENCES
Chiang, Alpha C. Fundamental Methods of Mathematical Economics. London:
McGraw-Hill Book Co., 1984.
Cleland, John and Chris Wilson. Demand Theories of the Fertility
Transition: An Iconoclastic View. Population Studies 41, 1987.
(Publisher unknown)
Coale, Ansley J. The History of Human Population. Scientific American.
(Date and publisher unknown)
Concept Paper: Commercial Contraceptive Marketing. USAID/New Delhi:
1995. (Unpublished)
Conly, Shanti R. and Sharon L. Camp. Indias Family Planning Challenge:
From Rhetoric to Action. Country Study Series #2, 1992. Washington,
D.C.: Population Action International.
Demeny, Paul. World Population Growth and Prospects. Working Papers, No.
4, 1989. Washington, D.C.: The Population Council.
Knodel, John, et. al. Fertility Transition in Thailand: A Qualitative
Analysis. Population and Development Review 10, 1984. (Publisher unknown)
Lewis, Maureen A. and Genevieve Kenney. The Private Sector and Family
Planning in Developing Countries. The Urban Institute International
Activities, V. 3686-01, (July) 1988. Washington, D.C.: The Urban Institute.
Mason, Karen Oppenheim. The Impact of Womens Social Position on
Fertility in Developing Countries. Sociological Forum, V. 2, # 4. (Date
and publisher unknown)
Simon, Carl P. and Lawrence Blume. Mathematics for Economists. New
York: W.W. Norton & Co., 1994.
Watkins, Susan. Conclusion. in The Decline of Fertility in Western
Europe, ed. by Susan Cotts Watkins and Ansley J. Coale. New Jersey:
Princeton University Press, 1986.
World Population Profile: 1991. Washington, D.C.: U.S. Census Bureau.
World Resources Database, 1994. Baltimore, Maryland, USA: World
Resources Institute.
1995 CIA World Factbook. Washington, D.C.:US Central Intelligence Agency