The impact of global cotton and wheat prices on rural poverty in Pakistan.
Orden, David ; Salam, Abdul ; Dewina, Reno 等
The incidence of rural poverty in Pakistan increased during the
late 1990s after having declined during the 1980s and early 1990s. A
number of structural factors have been identified as contributing to
rural poverty in Pakistan. Among them are low levels of health and
education spending and the unequal of farmland distribution. These
structural factors help explain the levels of poverty in Pakistan, but
not the increase in poverty in the late 1990s. One hypothesis is that
the increase in rural poverty is the result of an adverse trend in world
commodity prices, particularly cotton, a major commercial crop, and
other agricultural commodities such as wheat, rice, and sugar.
The overall objective of this paper is to measure the impact of
changes in world commodity prices on poverty in rural Pakistan, with
particular focus on cotton prices and the main cotton producing
districts of Punjab and Sindh provinces.
GLOBAL COTTON MARKETS
About one third of global cotton production is traded
internationally. The US, Australia, Uzbekistan, Egypt, and Greece are
the five main exporters of cotton, accounting for more than 60 percent
of global cotton exports. The production of the other four major
producers (the PRC, India, Pakistan, and Turkey) is destined mainly for
local consumption by their own textile industries. For a number of other
poor countries, cotton is an important component of their merchandise
trade. The United Nations classifies about one third of cotton-producing
countries as least developed countries.
Cotton is the main cash crop and major source of government
revenue, foreign exchange earnings, investment, and economic growth, for
several countries in Central and Western Africa, considered the
world's poorest regions. In these developing countries, cotton is
an important aspect of the livelihoods of the poor. Around one billion
people, mostly in developing countries, are either directly or
indirectly involved in the production and marketing of cotton [Towsend
(2004)].
Traditionally Pakistan exported large quantities of raw cotton, but
has now shifted to exporting value-added textile products and cotton
'made ups'. In recent years, Pakistan has participated in the
world market as both an exporter and importer of cotton to meet the
requirements of its domestic textile industry. International cotton
prices remain an important reference for domestic transactions in cotton
lint and hence for prices of seed cotton at the farm level. In view of
various technical considerations and characteristics important in
determining its quality (such as staple length, micronaire, quality of
ginning, and the price received in the intemational market), Pakistani
cotton is grouped with Index B cottons. Average annual world market
prices of this group are illustrated in Figure 1. World cotton markets
exhibit substantial annual price variability around a slight declining
trend in nominal and real terms from 1990-91 to 2004-05. The price of
index B cotton decreased from its peak in 1994-95 to trough in 2001-02
by 57.8 percent in nominal terms. In real terms, the Index B cotton
price (in 2000 US dollars) declined from $107.13 per 100 lb to $37.87, a
decrease of 64.7 percent.
[FIGURE 1 OMITTED]
Effect of Subsidies and Trade Barriers on World Cotton Prices
As for other agricultural commodities, the production and
international trade of cotton in most countries has been the subject of
considerable government subsidies, border protection, and other
interventions. Interventions that cause market distortions include high
tariffs, tariff escalation, large domestic production support, vague
rules on what constitutes trade-distorting support programmes, and
considerable export subsidies. The International Cotton Advisory
Committee (ICAC) estimates that more than half of world cotton
production benefits from direct price and income supports. On the demand
side, there is a complex range of trade barriers in the form of tariffs,
quotas, and other measures on raw cotton, yams, textiles, and apparel.
Aksoy and Beghin (2004) estimate that the combined support for cotton
production by eight major world producers (the US, PRC, Greece, Spain,
Turkey, Egypt, Brazil, and Mexico) between 1997-98 and 2001-02 ranged
from $3.8 billion to $5.3 billion.
Numerous recent studies have attempted to measure the impact of
cotton subsidies on world cotton prices and production. A summary of
several of these studies is provided by the Food and Agriculture
Organisation [Poonyth, Sarris, Sharma, and Shui (2004)]. The studies
have adopted several modeling frameworks, focusing on different
countries to examine the impact of subsidies and other policies in
recent years, and have shown a range of estimates of the effects of
subsidy elimination. The studies generated divergent results, reflecting
partly the particular structure of the models and assumed elasticities,
as well as the base period, subsidies considered, and other factors.
Estimates of the studies fall into three categories: those reporting
relatively small effects (2-5 percent); those reporting moderate effects
(10-25 percent), and those reporting relatively large effects (near 30
percent or more). The WTO panel in the Brazil/US cotton case found that
US support policies damaged Brazil by depressing world prices but did
not give an empirical estimate of the magnitude of this effect. The
middle-range estimates receive the most support in the studies.
Nominal and Real Domestic Cotton Prices
Table I shows the harvest-season market and government support
prices of seed cotton between 1990-91 and 2004-05. Nominal support
prices were revised upward in 11 years, and substantially downward once,
during the reference period. The average annual growth rate of nominal
seed cotton prices during 1990-91 to 2004-05 was 10 percent compared to
the average annual increase of 7.25 percent in the consumer price index
(CPI). Correspondingly, the real value of support prices has trended
upward since 1990-91.
The nominal price of seed cotton in the domestic market during the
reference period was also marked by large fluctuations. The overall mean
value of the nominal domestic price of seed cotton for the period under
review was PRs730/40 kg, with a coefficient of variation of 34.39
percent.
As shown in Table 1, except in 2 recent years (2001-02 and
2004-05), market prices have been higher than support prices. In those
years, as market prices fell, the Government of Pakistan (GoP) tried to
maintain prices above the support price level by procuring cotton lint
through the TCP. The TCP procured from the market 0.203 million bales in
2001-02 and 1.6 million bales in 2004-05, but these interventions,
notwithstanding their positive impact on market sentiment, failed to
sustain the support price announced by the GoP as the price received by
cotton growers.
In 1999-2000, no support price was agreed on and announced by the
GoP; moreover, there was a change in government on 12 October 1999, the
middle of the cotton season. The new government took time to design the
required policy framework and institutional arrangements for market
intervention. In the meantime, international prices continued to fall,
exerting downward pressure on domestic prices. The textile industry,
taking advantage of low international prices, arranged for substantial
imports of cotton from abroad, which also depressed the domestic market
price. The market price of seed cotton in the 1999-2000 crop season thus
averaged only 70 percent of the previous year's level.
The nominal domestic market price of seed cotton can also be
compared to the nominal world prices implied by the export and import
parity prices (border prices) of cotton lint. As estimated from the
prices of Index B cottons the import and export parity prices of seed
cotton also vary considerably, as shown in Figure 2 (see the ADB Background Paper 8 for technical discussion of the parity prices). The
average value of export parity prices between 1990-91 and 2004-05 comes
to PRs 733/40 kg, with a coefficient of variation of 31.13 percent. The
average value of import parity prices during this period comes to PRs
976/40 kg, with a coefficient of variation of 28.59 percent. The average
increase in nominal export parity price of seed cotton, worked back from
the international price of Index B cottons and expressed in rupees, is
estimated at 5.52 percent per year. In contrast, the nominal price of
Index B cottons (in $) is estimated to have decreased by minus 2.54
percent per year on average for the reference period. These opposite
trends illustrate the effect of substantial inflation in Pakistan on
nominal seed cotton price levels.
[FIGURE 2 OMITTED]
Comparison of export parity prices with the corresponding domestic
market prices of seed cotton shows that the two price series generally
track closely together (Figure 2). Even so, in 7 out of 15 years, export
parity prices were higher. Import parity prices are on average 25-35
percent higher than export parity prices. A comparison of domestic
prices with import parity prices indicates that the price of imported
cotton was substantially higher than the domestic price. Accordingly,
the coefficient of nominal protection, estimated using the import parity
price, is always less than one and by a considerable margin. Generally,
years in which substantial quantities of cotton were exported are
characterised by higher export and import parity prices while those with
considerable imports have been years of lower parity prices.
While nominal domestic prices track export parity prices relatively
closely, the real price of cotton (adjusted for domestic inflation)
depicts more realistically price levels affecting the purchasing power and economic well-being of cotton farmers. Real market prices of seed
cotton in Pakistan and real export and import parity prices of seed
cotton are shown in Figure 3. The real cotton price in Pakistan dropped
in the late 1990s--a similar pattern to world prices in US dollars--but
the decline in real prices in Pakistan was moderated by real
depreciation of the rupee, which raised the value of world prices in
domestic currency. In real terms (adjusted for inflation in Pakistan and
the US), the rupee depreciated by 32.5 percent between 1994-95 and
2001-02. Due to this real depreciation, the real domestic market price
of cotton declined by 38.7 percent between 1994-95 and 2001-02, compared
to the world price decline of 64.7 percent in real dollars. The decline
in the 3-year averages of real world and domestic prices centred on the
peak and trough years are less: a decline of 49.1 percent in world
dollar prices and 19.6 percent in domestic rupee prices.
[FIGURE 3 OMITTED]
The real market price of seed cotton also fluctuated widely during
the period under review. For 7 out of 14 yearly changes from 1990-91 to
2004-05, the real value of market prices was less than the preceding
year. Further, in 5 of the years, the purchasing power of seed cotton
was less than in 1990-91. The real value was highest in the 1995-96 crop
season while the highest nominal price was observed in 2003-04. As a
result of the swings in the real value of market price of seed cotton,
there is no statistically significant trend during the reference period.
Effects of World Cotton Prices on Poverty in Pakistan
Pakistan's population was estimated to be 148 million in 2003.
The incidence of rural poverty in Pakistan, income sources, and other
characteristics of poor and nonpoor rural households, have been
carefully assessed in a recent study by Malik (2005). The next sections
provide an additional overview of the income levels of nonfarm and farm
households, paying particular attention to landowner and sharecropper
cotton-producing households in Punjab and Sindh. Then a simulation
analysis is provided of the effects of cotton prices on incomes and
poverty in Pakistan.
HOUSEHOLD CHARACTERISTICS
The HIES for 2001-02 carried out by the GoP's Federal Bureau
of Statistics (FBS) consists of an adjusted sample of 16,182 households
within seven provinces/regions: Punjab, Sindh, the North-West Frontier
Province (NWFP), Balochistan, Azad Jammu and Kashmir, the Northern
Areas, and the Federally Administered Tribal Areas. For this analysis,
following FBS (2003) and Malik (2005), the focus is on the four
provinces, represented by a sample of 14,522 households. Table 2
provides some summary household statistics by location and agricultural
activities for the national level, the provinces of Punjab and Sindh,
and the primary cotton-producing districts of both provinces. The
results reported in Table 2 and in subsequent tables are nationally
representative, and based on weighted sample data.
At the national level, 29.4 percent of households are urban and
70.6 percent rural. Households engaged in farming comprise 40.7 percent
of the total sample. Farmers are concentrated in rural areas where more
than half of households engage in some farming activity. A small set of
households (1.9 percent of all households nationally) are classified as
urban and also engage in some farming activity. These households are 6.5
percent of urban households.
Sources of Income of Cotton-producing Households
Table 3 provides information on the sources of income of landowner
cotton-producing households by geographic area. The average income of
landowner cotton-producing households is estimated to exceed the
national average among rural households, while sharecroppers farm less
acreage and report lower incomes (not shown in the table). Reported net
incomes of landowner cotton farmers are higher in Sindh than Punjab.
Among landowner cotton farmers nationally, crops account for 78.9
percent of average household net income and wages for 10.0 percent.
Distributing crop production expenses in proportion to the acreage of
each crop, cotton accounts for 48.9 percent of net crop income or 38.6
percent of household total net income for landowners. For sharecroppers,
income from crops accounts for 77.5 percent of the total net income at
the national level and cotton income for an estimated 57.5 percent of
crop income and 44.6 percent of total income. Thus, cotton income is
important to the well-being of landowner and sharecropper households.
Within Punjab, crop income accounts on average for 73.5 percent of
total income among landowner households producing cotton, and cotton for
44.4 percent of crop income and 32.6 percent of total income. In Sindh,
crops account on average for 93.7 percent of the total income of
landowner cotton-producing households. Crop and cotton income appear to
be more important for landowner and sharecropper cotton-producing
households in Sindh than in Punjab. The higher proportion of net income
reported from crops arises largely because of reported losses on
livestock, which offset earnings from other sources, (1) Cotton accounts
for 56.9 percent of average crop income and 53.3 percent of total income
among landowner cotton-producing households in Sindh.
Direct Effects of Cotton Prices on Household Incomes and Poverty
To measure the linkages between global cotton prices and rural
poverty in Pakistan a simulation analysis is undertaken, as in the study
of the impact of lower cotton prices on rural poverty in Benin by Minot and Daniels (2005). The direct effects of changes in cotton price on
incomes and poverty among cotton-producing households are assessed first
assuming no change in production levels. The direct effects on the
incomes of and poverty among these households are also assessed allowing
for a supply response by the farmers.
Direct Effects: The direct effects of changes in cotton price are
analysed based on survey information on the value of cotton sales by
households. For cotton farmers who own their land, per capita income derived from a price change can be calculated as
[DELTA][y.sub.i] = 1/[H.sub.i]([Q.sub.ci][DELTA][P.sub.c]) ... (1)
where [DELTA][y.sub.i] is the change in per capita income of
household i due to a change in the price of cotton; [Q.sub.ci] is the
quantity of cotton sold by household i; [DELTA][P.sub.c] is the change
in the real price of cotton; and [H.sub.i] is the number of members in
household i. If a household does not grow cotton, then [Q.sub.ci] = 0
and the direct effect of cotton prices is zero ([DELTA][y.sub.i] = 0),
but if [Q.sub.ci] > 0, then a price reduction ([DELTA][P.sub.c] <
0) implies that income will fall ([DELTA][y.sub.i] < 0). Conversely,
a price increase implies that income also rises. From Equation 1, the
change in per capita income can be calculated for each household in the
sample to provide a detailed picture of the distributional impact of
lower or higher cotton prices. To further assess the poverty impacts of
changes in cotton price on cotton-producing households, the analysis
takes into account the fact that farmers will, at least to some extent,
substitute away from cotton and reduce input use when cotton prices
fall, and substitute into cotton production and expand input use when
cotton prices rise. Sharecroppers only retain half the cotton they
produce, and Equation (1) is modified accordingly. This
'microsimulation' approach makes it possible to estimate the
change in income for any sample group defined by income, farm size, or
other variables.
Poverty Measures: The simulated impact of price changes on poverty
is evaluated using the Foster-Greer-Thorbecke (1984) measures of
poverty, defined as
[P.sub.[alpha]] = 1/N [[summation].sub.i] [[[mu] -
[y.sub.i]/[mu]].sup.[alpha]] (2)
where [P.sub.a] is the poverty measure, N the number of households,
[mu] the poverty line, and [y.sub.i] the income or expenditure of poor
household i (the summation occurs only over poor households). Different
values of a (a = 0, 1, and 2) yield different measures of poverty,
giving different weights to the degree of poverty and inequality among
the poor. When a = 0, the poverty measure P0 is the incidence of
poverty, i.e., the proportion of households whose income is below the
poverty line. When a = 1, the poverty measure P1 is the poverty-gap
measure. The poverty gap is equal to the incidence of poverty multiplied
by the average gap between the poverty line and the income of a poor
household, expressed as a percentage of the poverty line. Thus, it takes
into account the depth of poverty as well as the percentage of
households that are poor. If a = 2, then the poverty measure P2 takes
into account the degree of inequality among poor households, as well as
the depth of poverty and number of poor households. This
'poverty-gap squared' is a measure of the severity of poverty.
Simulated Direct Effects of Cotton Price on Incomes and Poverty
Simulations based on the 2001-02 HIES data were carried out to
evaluate the direct effects of cotton prices on incomes and poverty in
Pakistan. Since the base data refers to a period of low cotton prices,
the simulations incorporated a range of increases in the farm-level
price of seed cotton ([DELTA][P.sub.c]), consistent with recent
historical experience. To evaluate whether or not a household was in
poverty, the study compared its annual per capita (adult equivalent)
consumption expenditure with a per capita poverty line based on the
government-recognised level of PRs 748/person/month. Additional income
resulting from an increase in cotton prices was assumed to be utilised
to increase household consumption.
Average annual consumption expenditures by cotton-producing
households, and the effects on their incomes of 10 percent to 40 percent
increases in cotton price are shown in Tables 4 and 5 for landowners and
sharecroppers, respectively. Table 6 aggregates these results for all
cotton farmers (landowners, sharecroppers, and other types of land
tenure). Separate results are shown for Punjab, Sindh, and at the
national level. Total household consumption expenditures are higher
among landowners than sharecroppers. Total consumption expenditures are
higher in Sindh than Punjab despite lower per capita expenditures in
Sindh (not shown in the table), where households are larger. (2)
In the simulation analysis, every 10 percent increase in the price
of cotton raises a landowner's average household income by PRs
4,806 in Punjab and PRs11,700 in Sindh, assuming fixed levels of
production. (3) Among sharecroppers, every I0 percent increase in the
price of cotton raises average household income by PRs 3,914 in Punjab
and PRs 4,894 in Sindh. A modest supply elasticity of 0.3 is assumed for
supply response simulations. This leads to slightly higher gains in
household income (for example, PRs 4,878 and PRs 11,876 for landowners
in Punjab and Sindh, respectively, for every 10 percent increase in
cotton price).
households to 25 percent in Punjab and 22 percent in Sindh. These
represent 22 percent and 49 percent reductions in the poverty level
among landowner cotton farmers. The depth and severity of poverty are
also reduced by cotton price increases, as shown by the measures of
poverty gap (P1) and poverty gap squared (P2).
The effects of increases in cotton price on the level, depth, and
severity of poverty among cotton-producing households are shown in the
lower part of Tables 4, 5, and 6. Based on an analysis of the 2001-02
HIES data, 32 percent of landowner cotton-producing households in Punjab
are estimated to have per capita expenditures below the poverty line,
with a corresponding 43 percent in Sindh. A 20 percent rise in cotton
prices--such as would offset the decline in real domestic prices
observed between 3-year averages centred on the peak and trough years of
1994-95 and 2001-02--is estimated to reduce the rate of poverty among
landowner cotton-producing Among sharecroppers, a 20 percent increase in
cotton prices reduces initial poverty rates of 56-58 percent in Punjab
and Sindh to 38 percent and 45 percent, respectively. These represent
declines in initial poverty rate of 33 percent in Punjab and 23 percent
in Sindh. Again, the depth and severity of poverty also fall. Overall,
cotton prices have quite a significant effect on rural poverty among
cotton-producing households. When farmers respond to a price increase by
expanding cotton production, the estimated reductions in poverty are
similar even though the supply response increases their average
household incomes somewhat more.
The aggregated results shown in Table 6 encompass poverty
reductions among all cotton-producing households. For the nation as a
whole, 40 percent of cotton-producing households are estimated to have
per capita consumption expenditures below the poverty line in 2001-02,
based on the 2001-02 HIES data [FBS (2003)]. A 20 percent increase in
cotton prices reduces the poverty rate among cotton-producing households
to 28 percent. Using the population estimate of 148 million in 2002,
assuming a national average household size of 7.0, and an estimated 9.8
percent of households producing cotton, there are an estimated 828,800
cotton-producing households below the poverty line. With a 20 percent
increase in cotton prices, this falls to 580,160 households in poverty.
Cotton-producing households have an average size of 7.8 persons, and
thus a 20 percent increase in cotton prices is estimated to reduce
poverty in Pakistan by 1.939 million people.
Effects of Farm Household Poverty on Regional Poverty Levels
While the rate and degree of poverty among households producing
cotton is strongly affected by cotton prices, only a subset of farm
households actually produce cotton. The broader impact on poverty levels
of direct reductions in poverty among cotton farmers depends on the area
of geographic aggregation, as shown in Table 7.
Within the primary cotton-producing districts of Punjab and Sindh,
cotton farmers account for 23.7 percent and 29.3 percent of households,
respectively. When cotton prices rise by 20 percent, poverty levels
within these geographic regions decrease by 2 percent in Punjab and 6
percent in Sindh because of the direct effect on incomes of
cotton-producing households. Cotton farmers account for 11.6 percent and
11.8 percent, respectively, of the population of Punjab and Sindh. At
the provincial level, overall poverty falls by only 1-3 percent as a
direct effect of a 20 percent increase in cotton prices. At the national
level, overall poverty falls by 1 percent and rural poverty by 2 percent
since households producing cotton are only 9.8 percent of all
households.
COMPARATIVE RESULTS FOR WHEAT
To put these results into a broader context, we also examined the
evolution of wheat prices internationally and domestically from 1990-91
to 2004-05. World prices of wheat decline during the late 1990s but by
less than cotton prices. Nominal wheat prices in Pakistan are found to
track closely the estimated import parity prices in Karachi through the
1990s, but fall below these import parity prices after the large
domestic harvest in 2000. In real terms, the overall level of domestic
wheat prices at the farm level is found to have been quite stable in
Pakistan although with some annual variability.
To assess the effects of an increase of wheat prices on poverty
simulation analysis is undertaken for price increases of 5 percent to 20
percent. Results for all households producing wheat are shown in Table
8. Whereas, cotton is produced by 24.0 percent of farm households in
Pakistan, wheat is produced by most of these households and by another
42.7 percent of farm households that do not grow cotton. Thus, wheat
prices have effects on the income of more farm households, as well as
affecting the cost of a key food consumption commodity for farm and
non-farm households. The net incomes of farm households producing wheat
are less dependent on its production than net incomes of households
producing cotton depend on cotton income. Moreover, a change in wheat
price affects household income only for that portion of the wheat
produced that is sold commercially. For these reasons, the effects of a
given increase in wheat prices on incomes of households producing wheat,
and the reduction of the initial rates of poverty among these households
is less than the effects of the same percentage increase of cotton
prices on those households producing cotton. Because more households
produce wheat, and also taking effects on non-wheat-producing households
into account, we estimate that the overall effects of a given percentage
change in wheat prices on poverty levels among all farmers, and on
poverty measured at the provincial or national level, are similar to the
deeper but more concentrated effects of an equal percentage increase in
cotton prices. In interpreting the simulation results for wheat, it must
be kept in mind that wheat prices did not decline as much as cotton
prices in the late 1990s.
SUMMARY AND CONCLUSIONS
In this study Pakistan domestic seed cotton prices are found to
closely track their export parity values. Evaluation of the importance
of cotton to the incomes of households is based on the 2001-02 Pakistan
Household Integrated Survey (HIES). We distinguishe between landowners
and sharecroppers and results are reported separately for Punjab and
Sindh, and for the primary cotton-producing districts within each
province.
Poverty was found to be substantial among cotton-producing
households. Among all cotton-producing households, 40 percent are below
the poverty line based on per capita consumption expenditures. Among
landowner households producing cotton, 34 percent are below the poverty
line. Sharecropper households producing cotton are more heavily
concentrated in the lower end of the national income distribution, with
57 percent below the poverty line.
Simulation analysis was undertaken to evaluate the effects of
cotton prices on poverty. A simulated increase of low cotton prices in
2001-02 back toward the higher levels of earlier years moves a
substantial number of cotton farmers out of poverty. The study examines
changes of 10 percent to 40 percent with the discussion focused on a
cotton price increase of 20 percent, which is the extent which real
prices of cotton fell in Pakistan in the late 1990s and is consistent
with several analyses of how much world prices might increase if all
subsidies and tariff barriers were removed globally.
The study estimates that an increase of real cotton prices by 20
percent reduces the poverty rates among landowner cotton households in
Punjab and Sindh from initial levels of 32 percent and 43 percent,
respectively, to 25 and 22 percent. Among sharecropper households
producing cotton, a 20 percent increase in cotton prices lowers rates of
poverty from 56-58 percent in Punjab and Sindh to 38 percent and 45
percent, respectively. At the national level, a 20 percent increase in
cotton prices causes poverty among all cotton-producing households to
fall from 40 percent to 28 percent. Lesser effects are reported for a
given percentage change in wheat prices, but a larger proportion of the
farmers in Pakistan grow wheat.
REFERENCES
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and University of Missouri-Columbia. (Working Paper 02-WP 317.)
Foster, J., J. Greer, and E. Thorbecke (1984) A Class of
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and Trade Policies Affecting the Cotton Industry. Washington, DC: ICAC.
Malik, S. J. (2005) Agricultural Growth and Rural Poverty in
Pakistan. Pakistan Resident Mission, Islamabad. Asian Development Bank.
(Working Paper No. 2.)
Minot, N., and L. Daniels (2005) Impact of Global Cotton Markets on
Rural Poverty in Benin. Agricultural Economics 33 (Supplement): 453-466.
Orden, David, et al. (2006) Impact of Global Cotton Markets on
Rural Poverty in Pakistan. Pakistan Poverty Assessment Update,
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Pakistan, Government of (2003) Accelerating Economic Growth and
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Islamabad: Ministry of Finance.
Poonyth, D., A. Sarris, R. Sharma, and S. Shui (2004) The Impact of
Domestic and Trade Policies on the World Cotton Market. Rome: FAO. (FAO
Commodity and Trade Policy Research Working Paper No. 8.)
Towsend, Terry (2004) Competitiveness in the World Cotton Industry.
Washington, DC:ICAC. Available: http://
www.icac.org/icac/cotton_info/speeches/Townsend/2004/competitive_2004.pdf
United States Department of Agriculture (2005) Cotton Statistics.
Available: http://www.fas.usda.gov/cotton/circular/2005/07/table09.pdf
David Orden <
[email protected]> is Senior Research Fellow, in
the Markets, Trade and Institutions Division, International Food Policy
Research Institute (IFPRI), Washington, DC. Abdul Salam
<
[email protected]> is Professor, Federal Urdu University of
Arts, Science and Technology, lslamabad. Reno Dewina
<
[email protected]> is Senior Research Assistant, IFPRI. Hina
Nazli <
[email protected]> is PhD student, University of Guelph.
Nicholas Minot <
[email protected]> is Senior Research Fellow,
IFPRI.
Authors' Note: Our research for this paper was supported by
the Asian Development Bank (ADB) as part of a project on cross-cutting
poverty issues in rural Pakistan. A report on the cotton analysis is
available from the ADB lslamabad Resident Mission titled
"Background Paper 8. Pakistan Poverty Assessment Update", An
earlier version of the paper was presented at the American Agricultural
Economics Association Annual Meeting, Long Beach, California, July
23-26, 2006, and the full report was presented at a seminar at the ADB
Islamabad Resident Mission in February 17, 2006.
Sources: International Cotton Advisory Committee. Cotton World
Statistics. Issues through 1992-93; Cotton Outlook. Various issues
1994-95 onward.
Note: Index B is the average of the three cheapest cottons among
the following: Orleans/Texas (SLM 1-1-32"); Brazilian type 5/6
(1-1-16") Argentine Grade c-1/2, (1-1-16"); Turkish Adnast. l
white, (1-1-16"); RG Central Asian (SLM 1-1/16"); Pakistani
Sindh/Punjab (SG Afzal 1-1-32"); Indian J-34 SG; and Chinese (Type
527). Prices for 2000-01 onward are based on a revised index as reported
in Cotton Outlook 83 (25), 2005.
(1) Overall, cotton farmers in Sindh report average feed costs of
PRs17,453 versus gross revenue from livestock of PRs12,793, resulting in
negative net income reported for livestock.
(2) The average household size nationally is 7.0. Among cotton
farmers, it is 7.8 nationally, 7.3 in Punjab, and 8.9 in Sindh. These
estimates are based on the weighted sample data but are not adjusted to
an adult-equivalent basis.
(3) With production fixed, this represents an increase in gross and
net income from cotton, whereas the initial net income from cotton is
reported (as a percentage of net crop income) in Table 6.
Table 1 Support and Market Prices of Seed Cotton
Nominal Price (PRs/40 kg)
Support Market
Year Price Price CPI
1990-91 245 327 43.20
1991-92 280 334 47.41
1992-93 300 384 52.07
1993-94 315 497 57.94
1994-95 400 785 65.48
1995-96 400 754 72.60
1996-97 500 793 81.11
1997-98 500 843 87.45
1998-99 -- 914 92.46
1999-2000 -- 641 95.78
2000-01 725 900 100.00
2001-02 780 761 103.54
2002-03 800 914 106.75
2003-04 850 1,219 111.63
2004-05 925 885 121.99
Real Price (PRs/40 kg)
Support Market
Year Price Price
1990-91 567 758
1991-92 591 704
1992-93 576 737
1993-94 544 858
1994-95 611 1,198
1995-96 551 1,039
1996-97 616 978
1997-98 572 964
1998-99 -- 989
1999-2000 -- 669
2000-01 725 900
2001-02 753 735
2002-03 749 857
2003-04 761 1,092
2004-05 758 725
Sources: Market prices are an average of the prices in important
producer area markets during the cotton harvest season, and are taken
from various reports of the Agricultural Prices Commission and
Pakistan Central Cotton Committee. Support prices are adapted from
policy reports of the Agricultural Prices Commission and Pakistan
Journal of Agricultural Economics. No support price for seed cotton
was fixed for the 1998-99 and 1999-2000 crops, while that for the
2000-01 crop was announced by the federal Ministry of Commerce in its
Cotton Policy. The CPI is taken From the Pakistan Economic Survey
2004-O5 and adjusted in light of the 9.28 percent inflation reported
for 2004-OS in Duwn (16 August 2005).
CPI = consumer price index.
Note: Real prices are expressed in terms of 2000-O1 rupees (PRs).
Table 2
Distribution of Households by Location and Agricultural Activity
Province
Household National (a) Punjab Sindh
Percent of All Households
Total Population 100.0 59.8 23.6
Nonfarmers 59.3 34.4 15.3
Farmers 40.7 25.4 8.3
Urban Population 29.4 17.0 9.8
Nonfarmers 27.5 15.9 9.4
Farmers 1.9 1.2 0.5
Rural Population 70.6 42.8 13.8
Nonfarmers 31.8 18.5 6.0
Farmers 38.8 24.2 7.8
Percent of Farm Households
Among Farmers 100.0 62.4 20.3
Livestock Only 23.4 17.4 4.0
Producing Crops 76.6 45.0 16.3
Landowners 55.4 35.8 7.6
Sharecroppers 13.9 4.1 8.0
Other Land Tenures (c) 7.3 5.1 0.7
Of Which Producing
Cotton 24.0 17.0 6.8
Landowners 16.6 13.1 3.3
Sharecroppers 5.1 1.9 3.2
Other Land Tenures (c) 2.3 2.0 0.3
Wheat, but not Cotton 42.7 24.5 6.7
Landowners 31.8 19.9 3.1
Sharecroppers 6.9 2.1 3.3
Other Land Tenures (c) 4.0 2.5 0.3
Neither Cotton nor Wheat 9.9 3.5 2.8
Primary Cotton-producing
Districts of (b)
Household Punjab (c) Sindh (d)
Percent of All Households
Total Population 25.9 8.5
Nonfarmers 11.9 4.3
Farmers 14.1 4.1
Urban Population 3.7 1.9
Nonfarmers 3.2 1.6
Farmers 0.5 0.3
Rural Population 22.2 6.6
Nonfarmers 8.6 2.8
Farmers 13.6 3.8
Percent of Farm Households
Among Farmers 34.6 10.2
Livestock Only 9.4 1.8
Producing Crops 25.2 8.4
Landowners 19.7 3.9
Sharecroppers 2.6 4.1
Other Land Tenures (c) 2.9 0.4
Of Which Producing
Cotton 15.1 6.2
Landowners 11.4 2.9
Sharecroppers 1.8 3.0
Other Land Tenures (c) 1.9 0.3
Wheat, but not Cotton 8.7 1.7
Landowners 7.1 0.8
Sharecroppers 0.8 0.8
Other Land Tenures (c) 0.8 0.1
Neither Cotton nor Wheat l.4 0.5
Sources: Based on weighted sample from the 2001-02 Household
Integrated Economic Survey.
(a) Based on Punjab, Sindh, the North-West Frontier Province, and
Balochistan.
(b) Primary cotton-producing districts are determined as districts
with more than 1 percent of national acreage during 2001-02 to
2003-04.
(c) Includes the districts of Bahawalpur, Rahimyar Khan, Vehari,
Lodhran, Rajanpur, Khanewal, M. Garh, Bahawalnagar, Multan, Dcra Ghazi
Khan, Sahiwal, Jhang, Toba Tck Singh, Pakpatan, Faisalabad, and
Layyah.
(d) Includes the districts of Ghotki, Sanghar, Khairpur, Nawab Shah,
Hyderabad, Mirpurkhas, Nowshero Fcrozc, and Sukkur.
(e) Includes other types of land arrangement and non-respondents.
Table 3
Sources of Income of Landowner Cotton producing Households at the
Provincial, and Primary Cotton producing District Levels
Province
National Punjab Sindh
Income Source Annual
Income
(PRs)
Total 77,721 69,672 108,915
Percent
Crops 78.9 73.5 93.7
Livestock 3.0 6.2 -5.5
Rental 1.4 1.8 0.3
Nonfarm Business 5.1 6.5 1.6
Wages 10.0 9.8 9.9
Transfers 1.7 2.2 0.0
Among Crops 100.0 100.0 100.0
Cotton 48.9 44.4 56.9
Wheat 29.5 32.6 23.9
Sugarcane 8.8 6.1 14.3
Rice I.0 1.3 0.5
Maize 0.1 0.2 0.0
Pulses 0.3 0.5 0.0
Fruits/Vegetables 2.1 2.4 1.5
Fodder 5.4 7.4 1.5
Other 3.9 5.2 1.3
Farm Size (ha) 4.7 4.2 6.7
Primary Cotton-producing
Districts of
Punjab Sindh
Income Source Annual
Income
(PRs)
Total 67,383 112,575
Crops 75.0 93.1
Livestock 5.4 -5.2
Rental 1.9 0.3
Nonfarm Business 5.1 1.8
Wages 10.0 10.3
Transfers 2.6 -0.3
Among Crops 100.0 100.0
Cotton 45.8 57.3
Wheat 32.6 24.0
Sugarcane 5.5 14.1
Rice 1.0 0.4
Maize 0.2 0.0
Pulses 0.4 0.0
Fruits/Vegetables 2.3 1.5
Fodder 7.0 l.3
Other 5.2 1.3
Farm Size (ha) 4.2 6.9
Source: Based on weighted sample from the 2001-02
Household tnlegraled Economic Swvey.
Table 4
Simulated Effects of Increased Cotton Prices on Poverty among Landowner
Cotton-producing Households at the Provincial and National Levels
Effect on Cotton-producing Households
Punjab Sindh
Fixed Supply Fixed Supply
Item Supply Response Supply Response
Base Expenditures 79,015 84,835
(PRs)
Net Income per 10% 4,806 4,878 11,700 11,876
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.32 0.43
With Cotton Price
Increase of
10% 0.28 0.28 0.29 0.29
20% 0.25 0.25 0.22 0.21
30% 0.23 0.23 0.12 0.11
40% 0.21 0.20 0.09 0.08
Poverty Gap (P1)
Base 0.064 0.089
With Cotton Price
Increase of
10% 0.053 0.053 0.052 0.051
20% 0.045 0.045 0.031 0.030
30% 0.039 0.038 0.020 0.019
40% 0.033 0.032 0.014 0.013
Poverty Gap Sq. (P2)
Base 0.019 0.028
With Cotton Price
Increase of
10% 0.015 0.015 0.014 0.014
20% 0.012 0.012 0.008 0.008
30% 0.010 0.010 0.005 0.005
40% 0.009 0.008 0.004 0.003
Effect on Cotton-producing
Households
National
Fixed Supply
Item Supply Response
Base Expenditures 80.376
(PRs)
Net Income per 10% 6,181 6,273
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.34
With Cotton Price
Increase of
10% 0.28 0.28
20% 0.24 0.24
30% 0.20 0.20
40% 0.18 0.17
Poverty Gap (P1)
Base 0.068
With Cotton Price
Increase of
10% 0.053 0.052
20% 0.042 0.041
30% 0.035 0.034
40% 0.029 0.028
Poverty Gap Sq. (P2)
Base 0.020
With Cotton Price
Increase of
10% 0.015 0.014
20% 0.011 0.011
30% 0.009 0.009
40% 0.007 0.007
Source: Based on weighted sample from the 2001-02
Household Integrated Economic Survey.
Table 5
Simulated Effects of Increased Cotton Prices on Poverty among
Sharecropper Cotton-producing Households at the Provincial
and National Levels
Effect on Cotton-producing Households
Punjab Sindh
Fixed Supply Fixed Supply
Item Supply Response Supply Response
Base Expenditures 60,861 66,211
(PRs)
Net Income per 10% 3,914 3,973 4,894 4,967
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.56 0.58
With Cotton Price
Increase of
10% 0.44 0.44 0.53 0.53
20% 0.38 0.38 0.45 0.44
30% 0.34 0.34 0.34 0.33
40% 0.34 0.32 0.29 0.28
Poverty Gap (P1)
Base 0.118 0.144
With Cotton Price
Increase of
10% 0.090 0.089 0.110 0.110
20% 0.072 0.071 0.082 0.081
30% 0.058 0.057 0.062 0.060
40% 0.048 0.046 0.047 0.044
Poverty Gap Sq. (P2)
Base 0.035 0.049
With Cotton Price
Increase of
10% 0.024 0.024 0.033 0.033
20% 0.017 0.017 0.023 0.023
30% 0.013 0.013 0.016 0.015
40% 0.010 0.009 0.011 0.010
Effect on Cotton-producing
Households
National
Fixed Supply
Item Supply Response
Base Expenditures 64,241
(PRs)
Net Income per 10% 4,533 4,601
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.57
With Cotton Price
Increase of
10% 0.49 0.49
20% 0.42 0.42
30% 0.34 0.33
40% 0.31 0.29
Poverty Gap (P1)
Base 0.135
With Cotton Price
Increase of
10% 0.103 0.102
20% 0.078 0.077
30% 0.061 0.059
40% 0.047 0.045
Poverty Gap Sq. (P2)
Base 0.044
With Cotton Price
Increase of
10% 0.030 0.030
20% 0.021 0.021
30% 0.015 0.014
40% 0.011 0.010
Source: Based on weighted sample from the 2001-02
Household Integrated Economic Survey.
Table 6
Simulated Effects of Increased Cotton Prices on Poverty among all
Cotton-producing Households at the Provincial and National Levels
Effect on Cotton-Producing Households
Punjab Sindh
Fixed Supply Fixed Supply
Supply Response Supply Response
Base Expenditures 75,942 75,013
(PRs)
Net Income per 10% 4,857 4,930 8,305 8,430
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.36 0.50
With Cotton Price
Increase of
10% 0.31 0.31 0.39 0.39
20% 0.27 0.27 0.32 0.31
30% 0.24 0.24 0.22 0.21
40% 0.21 0.21 0.18 0.17
Poverty Gap (P1)
Base 0.073 0.113
With Cotton Price
Increase of
10% 0.058 0.058 0.077 0.077
20% 0.047 0.046 0.054 0.053
30% 0.039 0.038 0.039 0.038
40% 0.032 0.031 0.029 0.027
Poverty Gap Sq. (P2)
Base 0.021 0.036
With Cotton Price
Increase of
10% 0.016 0.016 0.023 0.022
20% 0.012 0.012 0.015 0.014
30% 0.010 0.009 0.010 0.010
40% 0.008 0.008 0.007 0.007
Effect on Cotton-Producing
Households
National
Fixed Supply
Supply Response
Base Expenditures 75,848
(PRs)
Net Income per 10% 5,839 5,927
Cotton Price
Increase (PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.40
With Cotton Price
Increase of
10% 0.33 0.33
20% 0.28 0.28
30% 0.24 0.23
40% 0.20 0.20
Poverty Gap (P1)
Base 0.084
With Cotton Price
Increase of
10% 0.063 0.063
20% 0.049 0.048
30% 0.039 0.038
40% 0.031 0.030
Poverty Gap Sq. (P2)
Base 0.025
With Cotton Price
Increase of
10% 0.017 0.017
20% 0.013 0.013
30% 0.010 0.009
40% 0.008 0.007
Source: Based on weighted sample from the 2001-02 Household
Integrated Economic Survey.
Note: Includes cotton-producing households that are landowners,
sharecroppers, or subject to other land tenures. Net income per
10 percent cotton price increase exceeds that of landowners or
sharecroppers shown in Tables 4 and 5 for Punjab because of the
higher gross cotton income of cotton-producing households in the
other land tenures category, which includes 11.8 percent of
cotton-producing households in the province.
Table 7
Simulated Effects on Increased Cotton Prices on Poverty at the Primary
Cotton-producing District, Provincial, and National Levels
Effect on Regional Population
Primary
Cotton-producing
Districts of Province
Punjab Sindh Punjab Sindh
Base Expenditures 62,268 72,939 72,919 92,392
(PRs)
Poverty Incidence (P0) Percent (as Proportion)
Base 0.45 0.43 0.34 0.32
With Cotton Price
Increase of
10% 0.44 0.39 0.33 0.30
20% 0.43 0.37 0.33 0.29
30% 0.42 0.34 0.33 0.28
40% 0.42 0.32 0.32 0.28
Poverty Gap (P1)
Base 0.108 0.091 0.077 0.067
With Cotton Price
Increase of
10% 0.105 0.080 0.075 0.063
20% 0.102 0.073 0.074 0.060
30% 0.100 0.068 0.073 0.058
40% 0.098 0.066 0.072 0.057
Poverty Gap Sq. (P2)
Base 0.037 0.028 0.026 0.021
With Cotton Price
Increase of
10% 0.035 0.024 0.025 0.019
20% 0.034 0.022 0.025 0.018
30% 0.034 0.020 0.024 0.017
40% 0.033 0.019 0.024 0.017
Effect on Regional
Population
National
Base Expenditures 78,561
(PRs)
Poverty Incidence (P0)
Base 0.33
With Cotton Price
Increase of
10% 0.33
20% 0.32
30% 0.32
40% 0.31
Poverty Gap (P1)
Base 0.072
With Cotton Price
Increase of
10% 0.070
20% 0.068
30% 0.067
40% 0.067
Poverty Gap Sq. (P2)
Base 0.023
With Cotton Price
Increase of
10% 0.022
20% 0.021
30% 0.021
40% 0.021
Source: Based on weighted sample from the 2001-02
Household Integrated Economic Survey.
Table 8
Simulated Effects at the Provincial and National Levels of Increased
Wheat Prices on Poverty among all Households Producing Wheat
Effect on Wheat-producing
Households
Punjab
Fixed Quantity
Item Quantities Response
Base Expenditures (PRs) 78,455
Net Income per 10%
Wheat Price Increase
(PRs) 2,211 2,260
Poverty Incidence (P0) Percent (as Proportion)
Base 0.31
With Wheat Price Increase of
5% 0.30 0.30
10% 0.29 0.29
15% 0.28 0.28
20% 0.28 0.27
Poverty Gap (P1)
Base 0.062
With Wheat Price Increase of
5% 0.059 0.059
10% 0.057 0.057
15% 0.055 0.054
20% 0.052 0.052
Poverty Gap Sq. (P2)
Base 0.018
With Wheat Price Increase of
5% 0.017 0.017
10% 0.016 0.016
15% 0.015 0.015
20% 0.015 0.015
Effect on Wheat-producing
Households
Sindh
Fixed Quantity
Item Quantities Response
Base Expenditures (PRs) 75,277
Net Income per 10%
Wheat Price Increase
(PRs) 2,520 2,577
Poverty Incidence (P0) Percent (as Proportion)
Base 0.50
With Wheat Price Increase of
5% 0.48 0.48
10% 0.46 0.46
15% 0.44 0.44
20% 0.43 0.42
Poverty Gap (P1)
Base 0.111
With Wheat Price Increase of
5% 0.106 0.106
10% 0.101 0.100
15% 0.096 0.096
20% 0.092 0.091
Poverty Gap Sq. (P2)
Base 0.036
With Wheat Price Increase of
5% 0.033 0.033
10% 0.031 0.031
15% 0.030 0.029
20% 0.028 0.027
Effect on Wheat-producing
Households
National
Fixed Quantity
Item Quantities Response
Base Expenditures (PRs) 79,570
Net Income per 10%
Wheat Price Increase
(PRs) 2,007 2,053
Poverty Incidence (P0) Percent (as Proportion)
Base 0.34
With Wheat Price Increase of
5% 0.33 0.33
10% 0.32 0.32
15% 0.31 0.31
20% 0.30 0.30
Poverty Gap (P1)
Base 0.069
With Wheat Price Increase of
5% 0.066 0.066
10% 0.064 0.063
15% 0.061 0.061
20% 0.059 0.059
Poverty Gap Sq. (P2)
Base 0.020
With Wheat Price Increase of
5% 0.019 0.019
10% 0.018 0.018
15% 0.017 0.017
20% 0.017 0.017
Source: Based on weighted sample from the 2001-02 Household
Integrated Economic Survey.
Note: Quantity Response includes supply and demand responses
to higher prices.