ECONOMIC IMPLICATIONS OF COTTON PRODUCTION IN DISTRICT NAUSHAHRO FEROZE, SINDH PROVINCE OF

PAKISTAN

T H E S I S

BY

GHULAM RAZA SARGANI REG.NO: 2K9-AE-137

DEPARTMENT OF AGRICULTURAL ECONOMICS

FACULTY OF AGRICULTURAL SOCIAL SCIENCES SINDH AGRICULTURE UNIVERSITY

TANDO JAM 2012

ECONOMIC IMPLICATIONS OF COTTON PRODUCTION IN DISTRICT NAUSHAHRO FEROZE, SINDH PROVINCE OF

PAKISTAN

BY

GHULAM RAZA SARGANI REG.NO: 2K9-AE-137

A THESIS SUBMITTED THROUGH THE DEPARTMENT OF AGRICULTURAL ECONOMICS, FACULTY OF AGRICULTURAL

SOCIAL SCIENCES, TO SINDH AGRICULTURE UNIVERSITY, TANDOJAM IN CONNECTION WITH THE PARTIAL

FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE (AGRICULTURE) HONOURS IN

AGRICULTURAL ECONOMICS 2012

TABLE OF CONTENTS

CHAPTER PARTICULARS PAGE

APPROVAL CERTIFICATE BY THE SUPERVISORY COMMITTEE i

RESEARCH CERTIFICATE ii

THESIS RELEASE FORM iii

HALF TITLE PAGE iv

ACKNOWLEDGEMENTS v

LIST OF TABLES vi

LIST OF ANNEXTURES vii

ABSTRACT viii

I INTRODUCTION 01

II REVIEW OF LITERATURE 05

III METHODOLOGY 13

IV RESULTS 18

V DISCUSSION 34

VI CONCLUSION AND SUGGESTIONS 39

LITERATURE CITED 43

QUESTIONNAIRE 50

SYNOPSIS 53

i

ECONOMIC IMPLICATIONS OF COTTON PRODUCTION IN DISTRICT NAUSHAHRO FEROZE, SINDH PROVINCE OF PAKISTAN

BY

GHULAM RAZA SARGANI

APPROVAL CERTIFICATE BY THE SUPERVISORY COMMITTEE 1. SUPERVISOR MUMTAZ ALI JOYO

Assistant Professor Department of Agricultural Economics Faculty of Agricultural Social Sciences Sindh Agriculture University Tando jam.

2. CO-SUPERVISOR-I SANAULLAH NOONARI Assistant Professor Department of Agricultural Economics Faculty of Agricultural Social Sciences Sindh Agriculture University Tando jam.

3. CO-SUPERVISOR-II GHULAM MUJTABA KHUSHK Assistant Professor Department of Rural Sociology Faculty of Agricultural Social Sciences Sindh Agriculture University Tando jam.

DATE OF THESIS DEFENCE ________________________________2012

sarganiStamp

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DEPARTMENT OF AGRICULTURAL ECONOMICS FACULTY OF AGRICULTURAL SOCIAL SCIENCES

SINDH AGRICULTURE UNIVERSITY TANDOJAM

RESEARCH CERTIFICATE

This is to certify that the present research work entitled "Economic

Implications of Cotton Production in District Naushahro Feroze, Sindh Province of

Pakistan", embodied in this thesis has been carried out by Mr. Ghulam Raza Sargani, under

my supervision and guidance in connection with partial fulfillment of the requirements for the

degree of Master of Science (Agriculture) Honours in Agricultural Economics and that the

research work is original.

Dated_________________________2012

( MUMTAZ ALI JOYO )

Assistant Professor and

Research Supervisor

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iii

SINDH AGRICULTURE UNIVERSITY, TANDO JAM

THESIS RELEASE FORM I, Ghulam Raza Sargani, authorize the Sindh Agriculture University, Tandojam, to supply

copies of my thesis to libraries or individual upon request.

----------------------- Signature ----------------------- Date

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ECONOMIC IMPLICATIONS OF COTTON PRODUCTION IN DISTRICT NAUSHAHRO FEROZE, SINDH PROVINCE OF PAKISTAN

BY

SARGANI

v

ACKNOWLEDGEMENTS All acclamation and approbation is due to Allah (Subhan-u-Tahala) my

Creator, my Shaper out of naught, my Fashioner, Omnipresent, Omniscient to what I need,

cognizant of my deed, the Only ONE who is nearer to me than my jugular vein, to whom are

ascribed the traits of Absolute Perfection and Beauty. Eternal blessing and peace be upon the

beloved of Allah who has been sent as Mercy for all the worlds- Hazrat Muhammad (PBUH),

the city of knowledge, the illuminating torch and the rescuer of humanity from going astray

I offer my humble thanks to Almighty Allah" Who enabled me to complete

one of my lifes academic urges. I express my real thoughts and feelings to Supervisor

honorable Mr. Mumtaz Ali Joyo, Assistant Professor, Department of Agricultural Economics,

Faculty of Agriculture Social Sciences, Sindh Agriculture University Tandojam, for his

courteous professional advises, thesis transcript checking and its improvement, motivation,

fruitful suggestions and encouragement during this study.

The Author is extremely indebted to Mr. Sanaullah Noonari, Assistant

Professor, Department of Agricultural Economics, Mr. Allah Bux Chhutto, Associate Professor,

Department Statistics, Mr.Ghulam Mujtaba Khushk Department of Rural Sociology Faculty

of Agricultural Social Sciences, Sindh Agriculture University Tandojam, for their precious

guidance, help, and valuable suggestions during research work and management of the

manuscript.

I transcend my power of narration to express how I feel obliged to my

cherished and venerated Father for whatever I have achieved in the field of education and on

the highway of life. I will love to be extraordinary thankful to my mother, a great strength

behind me in the shape of oceans of prayers for me. I owe a special debt of gratitude to my

elder brother Mr. Ghulam Qambar Sargani who is a symbol of love, sacrifice and affection. I

am thankful to my younger brothers and my sisters for their moral support and prayers.

Friends who were the main source of encouragement for me; they prayed for my success and

shared my responsibilities with unprecedented patience.

GHULAM RAZA SARGANI

vi

LIST OF TABLES

TABLE P A R T I C U L A R PAGE

3.1 Distribution of sample Cotton growers in the study area during 2010-11 17

3.2 Distribution of sample Cotton growers by farm size in the study area during 2010-11 17

4.1 Socio-economic profile of cotton growers in study area during 2010 -11 19

4.2 Education levels of cotton growers in study area, during 2010-11 20

4.3 Cropping patterns of sample cotton growers in the study area during 2010-11 21

4.4 Land Tenurial Status of cotton growers in study area, during 2010-11 22

4.5 Cotton varieties planted on the selected farms in study area, during 2010-11 22

4.6 Sources of technical information to sample cotton growers in study area, during 2010-2011 23

4.7 Area, production and yield of cotton in Sindh and Pakistan during 2001- 02 to 2011 -12 24

4.8 Averages per acre land inputs realized by cotton growers in study area, during 2010-2011. 25

4.9 Averages per acre labour cost incurred by the selected cotton growers in study area, during 2010-2011 26

4.10 Averages per acre capital inputs applied by the selected cotton growers in study area, during 2010-2011 27

4.11 Averages per acre marketing costs incurred by the selected cotton grower in study area, during 2010-2011 28

4.12 Averages per acre total costs incurred by the selected cotton growers in study area, during 2010-2011 29

4.13 Averages per acre physical productivity realized by cotton growers in the study area, during 2010-2011 30

4.14 Averages per acre revenue productivity realized by selected cotton growers in study, during 2010-2011 31

4.15 Averages per acre net income realized by the cotton growers in study area, during 2010-2011 32

4.16 Input-output and cost benefit ratio calculated by the selected cotton growers in study area, during 2010-2011 33

vii

LIST OF APPENDICES

APPENDIX

PARTICULARS

PAGE

I

Distribution of sample Cotton growers by farm size in the Study area during 2010-11 45

II

Area under Cotton Crop in Pakistan during 1990-2011

46

III

Productions of Important Crops in Pakistan during 1990-2011

47

IV

Yield Per Hectare of Cotton Crop in Pakistan during 1990-2011

48

viii

AN ABSTRACT OF THE THESIS OF Ghulam Raza Sargani For Master of Science (Agri.) Honors Economics

Major Agricultural Economics TITLE: ECONOMIC IMPLICATIONS OF COTTON PRODUCTION IN DISTRICT

NAUSHAHRO FEROZE, SINDH PROVINCE OF PAKISTAN

The present study was designed to explore the important factors affecting such as socio-economic conditions of cotton growers which affect the yield of cotton crop. The data on various cost items including land inputs, labour inputs, capital inputs, marketing costs and physical and revenue productivity, net return, input-output ratio and cost-benefit ratio on various farm sizes during the year 2010-11, were collected from 60 selected cotton farmers for this purpose, different villages of taluka Kandiaro district N.Feroze by using multi-stages cluster sampling survey method. The education level of selected growers was in order of that the education level of selected growers was in order of 35 % primary (5-years), 18.30 % middle (8-years), 13.30 % matriculate (10-years) 6.70 % intermediated (12-years), 2 % graduate more than 25 % of cotton respondents were illiterate in the study area. However, the 33.3% of selected farmers obtained technical information from neighboring farmers. Relatively senior members of farmers family were operating the farming business and had 28.6 years of farming experience. Cotton growers spend average per acre fixed costs of Rs.12277.95 that includes rent of land, land tax, irrigation charges and local fund. Cotton farmers spent an average per acre labour cost of Rs 4381.30 including ploughing, fertilizer, and picking cost, inter culturing and leveling. Cotton farmers spent on capital inputs as average per acre Rs. 6707.00 including costs of seed, urea, pesticides/ insecticides, machinery and equipments charges. Cotton growers on average spent per acre marketing cost Rs. 1504.77 including expenses on transportation, loading, unloading and commission charges costs. Cotton respondents expend an average per acre total cost Rs. 24871.00 including fixed and variable costs viz labour costs, capital inputs and marketing costs. Cotton farmers realized average per acre physical productivity of 23.35 and harvested between 20.00 to 28.00 maunds per acre yield. Cotton growers realized an average per acre revenue productivity of Rs. 41249.16 and ranged between Rs. 30400.00 to Rs. 49400.Cotton respondents get average per acre net returns / income of Rs. 16378.20 that ranged Rs. 10085.10 to Rs. 18691.09 growers received as net returns from cotton produce. The input-output ratio of cotton growers average was 1: 1.65 and cost benefit ratio of cotton producers of Rs. 1:0.65 averages while investing a rupee which is meager benefit. The poor production implies that the soil quality, inadequate canal water, insect pest and poor extension services could be the causes to this low production due to lack of marketing facilities at village level, less payment by the marketing agencies, high prices of inputs, lack of timely availability of genuine fertilizers. The practical results indicate that significant increase in output of cotton in the study area could be traced mainly to use of latest technology plays the key role in cotton productivity enhancement.

1

CHAPTER-I

INTRODUCTION

Agriculture is the single largest sector of Pakistan economy, it plays a

central role and accounting for over 21 percent of GDP and remains by far the largest

employer, absorbing 45 percent of the countrys total labour force. Agriculture has

contributed 5.9 percent value added in growth of Gross Domestic Products (GDP).

Nearly 62 percent of the countrys population resides in rural areas, and is directly or

indirectly linked with agriculture for their livelihood continues to revolve around

agriculture and allied activities (GOP, 2011).

Pakistan is the 5th largest producer of cotton, 4th largest consumer of

cotton, 4th largest exporter of cotton yarn and 3rd largest exporter of raw cotton, in

the world. Cotton (Gossypium: Hirsutum) is known as white gold and important

non-food cash crop lifeline for the economy and is playing significantly role in the

uplift of the economy is the principle source of raw material for textile sector the

largest agro-based industry which provides 45 percent employing of workforce and

60% foreign exchange earnings, cotton is an occupation of more than 1.5 million

farming families which contributes to the exports of country in the form of raw

cotton, yarn cotton cloth and other by-products. Cotton contributes 6.9 percent of

value added in agriculture and 1.4 percent of GDP. Cotton was cultivated on the area

of 3106 thousand hectares, 10.1 percent more than last year 2820 thousand hectares

the production was estimated 12.7 million bales for 2009-10, highly by 7.4 percent

over the last years production of 11.8 million bales. Cotton production expected to

decline by 1.3 million tons to 22.2 million tons, as against a rise in consumption to

24.1 million tons, in. higher consumption is pushing prices up (GOP, 2011).

2

In cotton growing areas, the sale of cotton produce may account as

much as 40% of cash income of rural household besides this, it accounts for 60% of

our export earnings and about 85% of domestic oil production comprising some 400

textile mills, 7 million spindles, 27,000 looms in the mill sector (including 15,000

shuttle less looms), over 250,000 looms in the non-mill sector, 700 knitwear units,

4,000 garment units (with 200,000 sewing machines), 650 dyeing and finishing units,

nearly 1,000 ginneries, 300 oil expellers, and 15,000 to 20,000 indigenous, small scale

oil expellers (kohl us) depends upon cotton. More often relatively low domestic price

of cotton, through the imposition of export duties, in order to support domestic

industry. Cotton crop of the country has been witnessing ups and downs over last two

decades. (GOP, 2011)

Since the inception of Pakistan, cotton production has increased

tremendously; cotton occupied an area of just over 1 million acres during 1947-48,

whereas now it has been increased to 32.3 million acres in 2010-2011. However

figure reveals that cotton production has been shown considerable variability in recent

years, due to mainly in yield fluctuation, with area tending to grow steadily status of

cotton production, area and yield of cotton in Pakistan (GOP, 2011).

Cotton cultivation in the province has been recorded on 611,000 acres

this year which is 21,000 acres more than the target fixed by the federal government.

The Kharif crops suffered a loss of $4bn in foreign exchange earnings or 2.323

percent of the GDP, agriculture. Cotton received a loss of 1.8 million bales,

accounting for 1.8 percent of the GDP, Earlier the cotton production target was set at

14.5 million bales for 2011-12 however almost 50 percent of the cotton crop was

intensively and extensively damaged by heavy rains and devastating floods in Sindh

and cotton production would reduce to 13 million bales for the year. Cotton growers

have lost heavily as there. Quality of seed-cotton and the resultant lint have also been

3

badly damaged; seed-cotton was sold as low as Rs 1,500 per maund of 40 Kg ex-gin

while lint cotton was sold as low as Rs 3,500 per maund of 37.324 kg ex-gin. These

rates are well below production cost. Due to this, Sindh has large unsold stocks of

cotton to 33 percent of total arrivals. This season, stocks of unsold cotton are 2.04

million bales against 1.08 million bales same time last season - about 100 percent

increase from last year. The fall in seed-cotton prices were mainly due to lower

economic activity caused by massive power load shedding it was further compounded

by cash flow problems with the ginners, creating a bottleneck in bulk purchase of

seed-cotton from farmers. In view of future forecast of world supply and demand,

cotton prices in the international market are likely to be higher than last year.

Similarly, the market price of seed-cotton is also expected to follow the same pattern

in view of the depressed demand for it (GOP, 2010).

Overall 32 percent cotton sown area of Tharparkar, Umerkot,

Mirpurkhas, Sanghar, Tando Allahyar, Badin, Tando Muhammad Khan, Kashmore-

Kandhkot, Hyderabad, Matiari, Jamshoro, Dadu, Shikarpur, Naushahro Feroze,

Nawabshah, Khairpur, Sukkur and Ghotki districts of Sindh province. The bales from

Tando Adam in Sindh reportedly sold at Rs 1890 per maund (37.32 kgs), while

another 200 bales from the same station were said to have been sold at Rs 1900 per

maund; 400 bales from Benzirabad (Nawabshah) sold at Rs 1900 per maund, 500

bales Naushahro Feroze sold at Rs 1800 per maund; while 1000 bales from the

Khairpur district sold at Rs 1950 per maund. During 2009-10, the domestic price of

seed-cotton was reported at around Rs 1,900 per 40 kilograms in early season.

However, the price started sliding, particularly in November-December, and touched

the level of Rs 1,300 per 40 kilograms at some places the (Arshad, 2010).

4

The fall in seed-cotton price was mainly due to lower economic

activity caused by massive power load shedding. It was further compounded by cash

flow problems with the ginners, creating a bottleneck in bulk purchase of seed-cotton

from farmers. In view of future forecast of world supply and demand, cotton prices in

the international market are likely to be higher than last year. Similarly, the market

price of seed-cotton is also expected to follow the same pattern in view of the

depressed demand for it (GOP, 2010).

Looking at the above facts and economic importance of cotton crop in

our country the study was designed to achieve following objectives.

Objectives

1. To examine the status and growth of cotton production in Sindh and Pakistan.

2. To analyze the production cost of cotton crop in the study area.

3. To identify the production, marketing constraints in the study area.

4. To suggest policy measures & program initiatives for efficient cotton

production.

5

CHAPTER-II

REVIEW OF LITERATURE

A literature review is a body of text that aims to review the critical

points of current knowledge including substantive findings as well as theoretical and

methodological contributions to a particular topic a piece of discursive prose, not a list

describing or summarizing one piece of literature after another. Meeting this demand

for increasing productivity depends upon a stream of knowledge about cotton and its

environment and new technologies to utilize that knowledge; including knowledge

about resource use in the cultivation of cotton. The most relevant literature on

economic analysis of cotton carried out in different parts of the world is reviewed in

this chapter.

McKinion, et al. (2001) reported that the precision agriculture is that

through more precise timing and usage of seed, agricultural chemicals and irrigation

water that higher economic yields can occur while enhancing the economic

production of field crops and protecting the environment. The analyses performed in

this manuscript demonstrate proof of concept of how precision agriculture coupled

with crop simulation models and geographic information systems technology can be

used in the cotton production system in the Mid South to optimize yields while

minimizing water and nitrogen inputs. The 1997 yield was used as a comparison for

the analysis. Actual cultural practices for 1997 were used as input to the model. After

the 201 simulations were made using the expert system to optimize for water and

nitrogen on a one acre basis, the model predicted that an increase of 322 kg/ha could

be obtained by using only an average increase of 2.6 cm of water/ha and an average

decrease of 35 kg N/ha.

6

Ashiq and Khan (2002) conducted a study to measure the

competitiveness of seed cotton production and to determine the consistency between

current policies with existing comparative advantage. The analysis covered two major

cotton producing provinces, Punjab and Sindh due to their major share in total cotton

production. The cost of production estimates are based on the data of Agricultural

Prices Commission (APCOM) for five harvesting years i.e. 1997-98 to 2001-02.

Average cost per acre is calculated for each province by taking over into average over

five harvesting years. At national level data is obtained by taking the weighted

average of provinces depending upon their shares in production. They select policy

analysis matrix (PAM) approach to determine the comparative competitiveness of

Pakistans cotton and policy effects the comparative advantage was measured through

Domestic Resource Cost (DRC) ratio, and Social Benefit Cost Ratio (SBC).

Tariq, et al. (2003) has examined the cotton crop and found that it has

120 to 130 days life span in many countries rather than 200 days or even more in

Pakistans case. He further explains that 60,000 to 80,000 plants are sown per acre but

in Pakistan 50,000 plants per acre are maintained. Besides, cotton crop is attacked by

various diseases which reduce the overall production of the country. In this regard, he

has suggested a few main points for increasing the output of cotton production.

Firstly, when this crop is attacked by the insects, chemical means are not the only

solution to control them. But the varieties having multi-adversity resistance (MAR)

should be use for this purpose.

Siddiqui (2004) studied the role of support price for various

agricultural commodities including cotton. The author observes that support price

help raise the production and safeguards the interest of the farmers against falling

prices in the postharvest months particularly when the harvest is a bumper-one.

7

Moreover, it helps to stabilize inter-year and intra-year prices of the agriculture

commodity. The author further examined custom ginning and hedge trading.

Sharma et al. (2004) evaluated that the effects of plant spacing (60 x

60, 60 x 30 and 60 x 15 cm) and NPK level (80:40:20 and 120:60:30 kg/ha) on the

seed cotton yield and yield attributes (bolls per plant, boll weight per plant, yield per

plant and plant height) of 6 cotton cultivars (Vikram, Khandwa-2, Khandwa-3, LRA-

5166, A-51-9 and 79-BH-5-3). The crop was raised under recommended practices.

Seed cotton yield and its attributes (except boll weight and plant height) were

significantly influenced by various plant spacing and genotypes. In contrast, no

significant differences in these parameters were observed due to varying NPK levels.

The closest spacing of 60 x 15 cm recorded the highest seed cotton yield (954 kg/ha)

compared with 60 x 30 and 60 x 60 cm spacing (826 and 764 kg/ha, respectively).

Among the cultivars, BH-79-5-3 recorded the highest yield (1072 kg/ha), followed by

Vikram with (974 kg/ha).

Yingnan (2004) studied that the cotton production Management

System (MSCP) based on the validated Cotton plus simulation model for Xinjiang

and Huang-Huai-Hai regions in China. By applying the techniques of crop simulation

model and knowledge engineering, MSCP can conduct the decision-making for

optimal multi-objectives, optimal cultivation for all-growth season and decision-

making for production on time. The computer simulation experiments for optimal

cultivation for all-growth season before planting in Xinjiang have been made by using

MSCP, the test results showed that the production objective could be obtained by

following the suggested cultivation. The conclusion is that the establishment of MSCP

brings the development on model based.

8

Javed and Hassan. (2006) assessed the comparative advantage of

cotton production in Pakistan and determined that how far the current set of policies is

consistent with the comparative advantage. The Domestic Resource Cost (DRC),

Nominal Protection Coefficient (NPC) and Effective Protection Coefficient (EPC)

were used for the analysis of data for the harvesting years, 1998-99 to 2002-2003. The

analysis was carried out in the context of Policy Analysis Matrix (PAM). The

Domestic Resource Cost (DRC) analysis for Punjab concluded that farmers in Punjab

had comparative advantage in producing seed cotton for the study period. The value

of Nominal Protection Coefficient showed that the seed cotton farmers in Punjab were

taxed. This was further confirmed by the values of Effective Protection Coefficient.

The analysis showed that Sindh had more comparative advantage than Punjab.

Khan and Yasin (2006) calculated the cost of cotton ginning in

Pakistan. The author observes that there are 1263 ginning factories in the country with

about 5745 gin stands, out of which 2.5 percent, 63 percent, and 33 percent and 1.5

percent gin stands have 80, 90, 100 and 120 saws respectively. The cost of ginning

was calculated basing on electric cost, depreciation of the machinery, repair and

maintenance cost of the building and machinery, cost of establishing a ginning

factory, cost of mechanical staff including unskilled and skilled labour and cost of

ministerial staff.

Naidu and Shankar (2007) analysed that the cotton is no remunerative

as a commercial crop that farmers, even in agro-climatic zones not suitable for cotton

cultivation, grow cotton. This scenario underwent a change during the recent years,

due to heavy borrowing, over investment in inputs and frequent crop failure, the

cotton growers in India had to suffer severe and unbearable hardships. This paper

made an attempt to probe into economic aspects of production and productivity of

cotton crop by using the Cobb-Douglas Production function. It was observed that the

9

multiple coefficient of determination was significant at the 1% level for all the

categories of farmers, indicating that there was significant contribution of all

independent variables to the farm output of the sample farmers. It was also evident

that the large farmers were more benefited form per rupee investment in cotton

cultivation, compared to other categories of sample farmers. Finally, the study

suggested certain measures for the profitability of cotton crop.

Das et al. (2008) reported that the productivity of the cotton-wheat

cropping system used in the Indo-Gangetic plains is low, mainly due to improper and

imbalanced use of chemical fertilizer and organic manure. An experiment was carried

out between 2001 and 2003 at the Research Farm of Agronomy Division, Indian

Agricultural Research Institute, New Delhi, under irrigated conditions. The objective

of the experiment was to study the effect of inorganic and organic sources of nitrogen

(prilled urea fertilizer nitrogen, farmyard manure (FYM), and Azotobacter) alone and

in their various combinations on the performance of cotton (Gossypium hirsutum L.)

The results of this study showed considerable improvement in growth, yield

attributes, and yield of cotton with addition of higher doses of fertilizer N through

prilled urea. The performance of cotton with FYM @12 t ha-1 was found to be

intermediate (from 30 to 60 kg N ha-1). The highest growth and yield (2.33 t seed

cotton ha-1) was recorded following an integrated application of 30 kg N ha-1 through

prilled urea and FYM @12 t ha-1 along with Azotobacter (M4), and was 48.2% higher

than control.. The highest seed cotton equivalent yield (3.88 t ha-1) and production

efficiency (12.79 kg ha-1 day-1) were achieved with an integrated application of 30 Kg

N ha-1 through prilled urea and FYM @ 12 t ha-1 along with Azotobacter (M4). The

same combination also gave the highest net returns (US $ 954.7 ha-1).

Khachatryan et al. (2008) reported that cultivated cotton on about half

of its 4.5 million arable lands since independence the government has embarked on a

10

program of diversification, aimed at self-sufficiency in wheat production by

encouraging the gradual shift from cotton to wheat. It tried to realize a

macroeconomic program of reforms, which includes privatizing input and output

markets, increasing production incentives, eliminating the state order for cotton, and

streamlining the export system. Despite the announced program, the state continues to

play a major role in the production and marketing of cotton (sets production quotas

and prices, supplies inputs, and purchases the crop). Those attempts of restructuring

the agriculture have not brought any positive social or economic results. This paper

argues that restructuring cotton production by decreasing the areas under traditional

cotton in favor of cotton under plastic will result in welfare gains.

Dagistan et al. (2009) determined that the input and output involved in

cotton production in the Hatay province of Turkey. The average energy consumption

of the farms investigated in this study is 19 558 MJha-1. Of the total energy, 2.87% is

direct and 71.13% is indirect. Renewable energy accounts for 12.30% and energy

usage efficiency is found to be 2.36. The total energy input into the production of one

kilogram of average Turkish cotton is estimated to be 4.99 MJ. The dominant

contribution to input is energy in the form of nitrogen fertilizer (40.28%), followed by

water for irrigation (22.37%) and diesel oil (17.04%). The cost of cotton production

per acre is found to be 2 246 $ha-1 in the region, with 79.87% of this being variable

costs. It can be concluded that intensive cotton farms are being operated in the area

since the variable cost ratio is quite high. As a result of benefit-cost ratio (1.24)

analysis, cotton production is found to be economically efficient.

Javed et al. (2009) estimated that the technical, allocative and

economic efficiency and subsequently to investigate the determinants of technical,

allocative and economic inefficiency of cotton-wheat and rice-wheat farming systems

11

in Punjab, Pakistan. Data were collected from 400 farmers (200 farmers from each

farming system) for the crop year 2005-06. Technical, allocative and economic

efficiency scores were estimated by a non-parametric data envelopment analysis

procedure. Technical, allocative and economic inefficiency scores were separately

regressed on socio-economic and farm specific variables to identify the sources of

technical, allocative and economic inefficiency using a Tobit regression model. The

mean technical, allocative and economic efficiency calculated for the cotton wheat

system was 0.75, 0.44 and 0.37, respectively. Results of the study revealed that if

sample farms in cotton-wheat system operated at full efficiency level they could

reduce their input use by 25 percent and cost of production by 56 percent without

reducing the level of output and with the same technology.

Khan and Chaudhry (2009) examined the factors affecting cotton

production in Multan region using primary source of data. A sample of 60 small

farmers, 25 medium and 15 large farmers was randomly selected from two Tehsils

namely Multan and Shujabad of district Multan. The Cobb-Douglas Production

Function is employed to assess the effects of various inputs like cultivation, seed and

sowing, irrigation, fertilizer, plant protection, inter-culturing / hoeing and labour cost

on cotton yield. The results depicted that seed, fertilizer and irrigation were found

scarce commodity for all category of farmers in district Multan. The Cobb-Douglas

Production Function results revealed that the coefficients for cultivation (0.113) and

seed (0.103) were found statistically significant at 1 percent level. The Cost-Benefit

Ratio for the large farmers was found higher (1.41) than that of small (1.22) and

medium (1.24) farmers. There is a dire need to ensure the availability of these scarce

inputs by both public and private sectors as these inputs were major requirement of

the cotton crop.

12

Daniel et al. (2010) reported that the study examined the Net Income

and efficiency of resource use among cotton farmers in the southern part of Adamawa

State where cotton is predominantly grown. Analysis of the sampled farmers showed

that 86% of them were youth which suggest that if proper attention is given to cotton

cultivation, a lot of youth would be gainfully employed. The results also revealed that

40% of the farmers did not attend any formal school while 14% attended tertiary level

of education. About 59% of the respondents reported. The average cost and returns

per acre of the cotton farmers was N46, 046.25 and N56, 224.90 respectively. This

showed a profit of N10, 175.15 per acre. The R2

of 0.86 of the regression model

shows that 86% of the farmers income is being explained by the exogenous variables.

Land, labour and seed have positive influence on farmers income and the first two

significant at 1% and 10% levels respectively. Fertilizer, chemical and transportation

had negative influence on farmers income probably due to their escalating prices.

The marginal physical product analysis revealed that an extra acre of land acquired

for cotton will result to an increase of over one ton of cotton.

Khan and Akhtar (2011) studied provides cost-benefit analysis of

cotton production and processing by different stakeholders in Pakistan. In order to

analyze the cost-benefit analysis, Multan and Bahawalpur regions were selected as

study area since majority of the cotton producers are living herein. Cotton is one of

the major crops of Pakistan and have important role in agricultural production. It has

been identified that spinners and ginners have an incentive in the shape of profit to

raise their production. Basing on the study, it is recommended that the Government of

Pakistan should support the cotton producer by giving subsidies in the inputs and with

the help of support price system. By promoting productive capacities of grower, the

poverty can be reduced in the study areas

13

CHAPTER-III

METHODOLOGY

Primary as well secondary data was used in the study. Primary data

was collected from sample of 60 cotton growers through multistage clustered

sampling method which equally distributed among different categories of farmers

were selected by sampling techniques from the farms located study area. The selected

respondents were interviewed through a well prepared and designed questionnaire for

the purpose. Secondary data collected from literatures, reports and publications etc.

Data so collected was analyzed, tabulated and interpreted in the thesis. Every

successful research starts with an appropriate planning before taking any further action.

Planning is a series of actions that a researcher has decided to take in order to achieve

something. Therefore, a care full plan is essential for all research studies.

The material required for research in economics is the collection of

facts and figure their information collected by the research worker from both primary

and secondary sources. Thus the material for the present research work comprises

data collected from cotton growers of District Naushahro Feroze of Taluka kandiaro

areas on Socio-Economic characteristics, farming system, production techniques

adopted in cotton crop, constraints and issues in cotton production, marketing system

of cotton crop, problems in the disposal of cotton, cost and investment made by the

cotton growers, income and net returns realized by the cotton growers in the study

area.

The study was helpful in suggesting the ways and means to eliminate

constraints and issues in order to create incentives among growers and increase

production of cotton crop. The research problems are tackling with the specific

methodology to grip all the objectives already determined for the research study

14

Survey is considered the best method to carry out researches in the field of social

sciences. The main task of the research workers in social science is to investigate the

general conditions prevailing, in the study area. It is this said that generalization could

be best apprehended through survey method. Survey has so far, proved successful to

spell out generalization on certain aspects. General tendency of the people towards

any particular aspect could be judged after recording the interviews of a sample of

respondents. Therefore survey method was considered meaningful o examine cotton

production and constraints around the study area.

Cost function analysis Y= f (Xn)

Cost function describes the relationship between inputs and outputs;

the output depends on various quantities of input, so the production is dependent is

dependent variable, while the factors of cost are independent variables. The factors of

costs include land inputs, labour inputs, capital inputs and marketing costs. There is

great potential for increasing crop yields which can be achieved in considerable

shorter span of time and with much less financial costs. Proper managements of

production factors such as land, labour, capital and other water and non water inputs

are the key to meet this end. Mechanization of agricultural operations is an important

aspect, which meets to be adopted along with brining improvements in use of other

inputs e.g water, fertilizer, seed, herbicides and pesticides steps for efficient adequate

use of other water and non water initiated at the same time. Adoption of appropriate

irrigation practices for on farm water management along with use of right type of

agricultural equipment to ensure timely and properly establishment of cotton can help

in achieving higher levels of productivity in the study area.

15

Following is the mathematical form of cost of production function

Y = f (Xn)

Y= (X1, X2, X3, Xn)

Where

X1.n= per hac input used

Standard error of X is estimated as

)x(var )x( s.e. =

Where var )x( = n

)x(var (Anderson et al., 2001)

Arithmetic Mean

It is defined as value obtained by dividing the sum of all observations

by their numbers. Arithmetic mean or average can also be used for tabulated

presentation of data.

A.M or Average = Xn n

Where

= Total or Sum, Xn = Variables observations used in analysis. n = No. of

observations.

Standard Deviation

Deviation of a data from its mean is called the standard deviation. If a

deviation of it Mean is squared then the resulting deviation is called standard

deviation.

S.D = [(X-X*) / n]

Where

X = Value of Observations, X* = Mean of a Variable, n= No. of observations.

= Square Root and = Summation

16

Standard Error

Square root of standard deviation is called standard error

S. Error = ( [(X-X*)/n])

Where

X = Value of Observations, X* = Mean of a Variable & n= No. of observations

= Square Root and = Summation

Data analysis

Initially the data were arranged and organized in coding system. By

using the coding sheet, all the data were tabulated, summarized and analyzed through

computer software SPSS (Statistical Package for Social Sciences).Descriptive

statistics were uses to calculate interpret and discuss results and formulate the

recommendation. The data were summarized and presented in the form of tables and

figures.

Sampling Method

Multistage cluster sampling was applied to select representative

samples of respondents. Cluster sampling has two important advantages over Simple

Random Sampling and Stratified Sampling. Firstly, it is economical and secondly it is

suitable for selecting a sample when the sampling frame of individual elements is not

available. Cluster Sampling only needs a list of elements in the clusters sampled

(Anderson et al., 2001)

17

Table-3.1 Distribution of sample Cotton growers in the study area during 2010-11

Selected Taluka Union Council Name of Village No. of Farmers Percent

Kandiaro

Kamal Dero

Paryal Sargani 13 21.66

Jara Dakhan 12 20.00

Sher Mohammad 7 11.66

Mohabat Dero

Chuttal Sargani 8 13.33

M.Ismail Bhagat 9 15.00

Sanjar Lashari 11 18.33

All 60 100.00

The present study were sampled as multistage clustered sampling so

that one taluka Kandiaro from district Naushahro Feroze out of which two union

councils Mohabat Dero and Kamal Dero were selected in each union council three

villages were selected and among each village different number of farmers were

randomly selected from the study area hence over all sixty respondents were

interviewed for the study.

Table 3.2 Distribution of sample Cotton growers by farm size in the study area during 2010-11

Farm Size No. of Farmers Percent

Small (20 acres) 11 18.33

All 60 100.00

The result shown in table-3.2 that the distribution of cotton growers

38.33 percent of having less than ten acres of land were small farmers, 18.33 percent

of having more than 20 acres of land and 43.33 percent were large cotton growers and

having 10-20 acres of land were medium size of cotton growers in the study area

18

CHAPTER IV

RESULTS

Production is a process whereby some goods and services called inputs

are transformed into other goods and services called outputs. Production of agriculture

commodities not only results through the transformation of various inputs into outputs

but it is also subject to the physical, natural and socio economic condition of the area.

It is therefore necessary to have a brief account of the socio-economic indicators like

family size, educational level etc. as prevailing in the study area, and to account the

production practices as well as returns in physical and revenue terms. The present

study was carried out to investigate the economic implications of cotton production in

Kandiaro area of district Naushahro Feroze.

Characteristics of Sample Cotton Growers

The knowledge of socio-economic characteristics of sample farmers

provide better insights for understanding the general environments the farmers are

working in some selected socio-economic characteristics of sample owner farmers are

generally believed to be more responsive to technological changes and are considered

to be in a better position to take risk of adoption of new technologies with uncertain

outcomes. Others are of the view that owner-cum-tenants are more innovative as they

can share the risk with land owners. These arrangements show the importance of

information on land tenure system. More than sixty five percent of the sample farmers

were owner farmers. Since the majority of the farmers are resource poor farmer

thereby only 13 percent of the samples growers have own tractors. In addition to their

own land preparation, they rented out tractors to other farmers. Majority of the

farmers (77 percent) used rented tractors. The sample farmers are classified into three

groups on the basis of their ages viz., 27 percent were 20 to 30 years old, 43 percent

19

were 31 to 40 years old, and 30 percent were more than 40 years old. Education level

of sample farmers was also obtained. Literacy ratio was very low in the study area as

more than 25 percent of the respondents were illiterate. Farmers were also inquired

about the sources of information regarding latest crop technology. More than 88.3

percent of the sample cotton grower opinioned that they did not know about the

extension activities of the Sindh Agricultural Extension Departments, among the

reason for cotton cultivation 40% growers told that it increase income and 60% were

opinion that it makes the property more productive and fair. The soil types of cotton

fields were recorded from farmers perception and classified into four main groups. In

study area clay, clay-loam, saline and sandy soil was 10.8, 54.2, 27.6 and 7.4 percent,

respectively.

Table -4.1 Socio-economic profile of cotton growers cotton growers

Characteristics Average Standard Error

Age of respondent (years) 51.28 1.49

Formal education (years) 13.02 0.25

Farming experience (years) 28.6 1.6

The information regarding socio-economics characteristics of the

sample cotton grower is presented in table-4.1. On an overall basis the average age of

selected cotton growers was 51.28 years, implying that relatively senior members of

farmers family were operating the farming business and had 28.6 years of farming

experience.

Educational levels

Education and training make the grower skilled and more efficient,

education not only enhance the standard of living but also help in maintenance of

farms which can bring prosperity of his family. Therefore, literacy level was asked

from the selected cotton growers in the study area.

20

Table -4.2 Education levels of cotton growers in study area, during 2010-2011

Education level No. of respondents Percentage

Illiterate 15 25.00

Primary 21 35.00

Middle 11 18.30

Matriculate 8 13.30

Intermediate 4 6.70

Graduate 1 1.70

Total 60 100.00

It was observed in table-4.2 that the education level of selected

growers was in order of 35.00% primary (5-years), 18.30% middle (8-years), 13.30%

matriculate (10years) 6.70% intermediated (12-years), 1.70% graduate beyond the

25.00% of cotton respondents were illiterate in the study area.

Crop seasons and Cropping Patterns

There are two main crop seasons; "Kharif" and "Rabi" in the study

area. The Kharif season starts from April-May and ends in October-November while

the Rabi starts from November-December and ends in April-May. However due to

regional variation in temperature, several factors i.e. varieties, availability of water,

soil texture etc determine the crop pattern, sowing and harvesting time. Wheat,

Cotton, Rice, Sugar-cane are the major crops of the district; Jowar, & Mustard,

Mattar, Onion, Bajra and Maize fall in the category of minor crops. Cropping patterns

in study area is shown in Table 4.3. In study area during Kharif season, rice,

sugarcane, Jowar and cotton, were the major predominant crops with 22.4, 15.2, 5.6

and 45.6 percent of the total cropped area, respectively. Also, wheat vegetables,

21

barseem, maize had 74.4, 18.6, 5.8 percent respectively sizable share in the Rabi

cropping pattern of sample cotton growers.

Table -4.3 Cropping patterns of sample cotton growers in the study area

during 2010-11

Crops Percent area

Kharif crops

Cotton 45.6

Rice 22.4

Sugarcane 15.2

Jowar 5.6

Vegetables 6.8

Others 4.4

All 100.00 Rabi Crops

Wheat 74.4

Sugarcane 18.6

Barseem 5.8

Others 1.2

All 100.00

Land Tenure Status

It was apparent from the result in the table-4.4 that 65.00 percent were

owner, 18.30 percent were owner cum tenant and 16.70 percent of the respondents were

identified as tenant in the study area during 2010-2011

22

Table -4.4 Land Tenurial Status of cotton growers in study area, during 2010-2011

Land Tenure Status No. of respondents Percentage

Owner 39 65.00

Owner Cum Tenant 10 16.70

Tenant 11 18.30

Total 60 100.00

Cotton varieties

The result shown in the table -4.5 that most popular commercial cotton

varieties Ali Akbar-802, CIM-109, NIAB-78, CIM-111, Neelam- 121 and Qalandri

were grown the by the farmers in the area of study. Whereas NIAB-78, CIM-109,

Qalandri, Neelam- 121, CIM-111 varieties covered about 30.00, 25.00, 13.30, 13.30,

and 10.00 percent of land and Ali Akbar-802 variety planted by the selected growers

on cotton covered 8.30 percent on the studied farms in study area during 2010-11

Table -4.5 Cotton varieties planted on the selected farms in study area, during 2010-11

Cotton varieties No. of respondents Percentage

Ali Akbar-802 5 8.30

CIM-109 15 25.00

NIAB-78 18 30.00

CIM-111 6 10.00

Neelam- 121 8 13.30

Qalandri 8 13.30

Total 60 100.00

23

Sources of Information about cotton

The most common and acceptable source of information of rural area

have always been personal sources like experienced farmers, Electric media,

Newspapers, Neighbors, Agriculture department is also significant in the wake of

increasing literacy and informational knowledge about recommended technologies of

cotton.

Table -4.6 Sources of technical information to sample cotton growers in study area, during 2010-2011.

Sources of information No. of respondents Percentage

Friends 12 20.0

Relatives 16 26.7

Neighboring grower 20 33.3

Govt. Agri. Department 7 11.7

Media (Electric/print) 5 8.3

Total 60 100.0

It is demonstrated in the table-4.6 that majority of the selected cotton

farmers i.e. obtained technical information from neighboring farmers that was 33.3%

while obtained 26.7% from relatives, 20.0% from friends, 8.3% knowledge about

cotton production practices from electric media and newspapers and 11% from

government agricultural department the role of agriculture department on providing

technical information was meager about cultural practices and marketing was found

minor.

24

Status of and growth cotton production in Sindh and Pakistan

The status and growth of cotton production of Sindh province area 547

million acres were grown, 2443 production in million bales and 759 yield per hectares

in kilograms (lint) and 2929 million acres area, 10800 million bales production and

627 yield per hectare in kilogram (lint) attributed during 2001-02. During 2011-12

there slight increase area 549 million acres, 2448 million bales production, 761 yield

per hectare kilogram (lint) in Sindh and 3200 area in million acres, 14010 production

in million bales and 744 yield per hectare in kilograms (lint) in Pakistan were studied

the details of area, production and yield of cotton in Sindh and Pakistan from 2001-

2002 to 2011-12 of area, production and yield of cotton production of the study area is

given which meets first objective of study is given in appendices.

Table-4.7 Area, production and yield of cotton in Sindh and Pakistan during 2001- 02 to 2011 -12

Year

Sindh Pakistan

Area (in 000 acres)

Production (in 000 bales)*

Yield/ hec in

kgs (lint)

Area (in 000 acres)

Production (in 000 bales)*

Yield/ hec in

kgs (lint)

2001-02 547 2443 759 2929 10800 627

2002-03 542 2411 756 3114 10900 595

2003-04 561 2242 680 2751 10133 626

2004-05 635 3016 808 2994 10061 571

2005-06 637 2648 707 3210 14600 773

2006-07 570 2398 716 3100 13000 713

2007-08 607 2536 711 3072 13000 719

2008-09 562 2978 901 3035 11665 653

2009-10 634 4270 1144 2850 12060 719

2010-11 650 4282 1098 3120 12698 692

2011-12 547 2443 759 3200 14010 744

* 1 bale = 170 kg

25

Total Fixed cost

Total fixed cost is simply the summation of the several types of fixed

costs (Ronald, 1996). In the present study the total fixed costs include the rent of land

(lease) and the land taxes. These are sunk costs. They do not vary with the volume of

output and can have no bearing upon decisions regarding an increase or decrease in

productions. Fixed costs are those cots, which are incurred irrespective of the level of

output. Other characteristic of fixed costs is that they are not under the control of the

manager in the short run. They exist and at the same level regardless of how much or

how little the resource is used. They only way they can avoid is to sell the item, which

can be done in the long run.

Table -4.8 Averages per acre land inputs realized by cotton growers in study area, during 2010-2011.

Item Minimum Maximum Average Standard Deviation

Standard Error

Rent of land 10250.00 13000.00 11543.36 955.81 30.91

Land tax 202.35 465.40 302.91 83.32 9.13

Irrigation charges 182.11 323.76 238.43 56.01 7.48

Local fund 121.41 323.76 193.24 45.56 6.74

Total 10755.87 14112.91 12277.95 1140.71 54.26

It is apparent from the results presented in the table-14.8 that the

selected cotton growers spend average per acre fixed costs of Rs.12277.95 ( 54.26)

including rent of land, land tax irrigation charges and local fund an average per acre

cost of Rs. 11543.36 ( 30.91) as land rent, land tax per acre was Rs. 302.91 ( 9.13),

while irrigation charges per acre was 238.43 ( 7.48) and local fund was 193.24

(6.74) per acre ,land rent ranged between Rs 10755.87 to 14112.91 in the study area.

26

Labour inputs

Labour inputs, averages physical and mental effort for the performance

of any work. Inputs analyzed in this study include man as well as animal labour.

Labour inputs refer to all outlays incurred to labour for production process. The actual

labour used for various operations carried out by farmers have been calculated and

multiplied with wage rate for calculating the costs incurred on labour. Labour inputs

were employed for all cultural operations during the period of cotton cultivation in

study area. These operations are ploughing, leveling, sowing and inter-culturing,

application of fertilizer and picking.

Table -4.9 Averages per acre labour cost incurred by the selected cotton growers in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Leveling 700.00 987.00 867.33 73.68 8.58

Sowing 400.00 900.00 688.90 136.86 11.69

Ploughing 456.00 956.00 790.88 119.90 10.95

Fertilizer 400.00 950.00 700.36 158.11 12.57

Picking 456.00 900.00 739.30 134.79 11.68

Inter-culturing 400.00 823.00 594.51 114.15 10.68

Total 2812.00 5516.00 4381.30 737.53 66.15

The results presented in the table-4.9 the averages per acres labour cost

that revealed the cotton farmers incurred an average per acre cost of Rs 4381.30 (

66.15) including ploughing, fertilizer, picking, inter culturing and leveling as labor

costs. The table further indicated that the labour cost in the study area ranged between

Rs. 2812.00 to Rs. 5516.00.

27

Capital inputs

Capital has been defined as material goods used in further production.

Capital may be defined as that part of wealth, which is used for further production of

wealth. It is the capital that yields a farm entrepreneur to determine the type of

farming amongst various substitutes. Capital is a factor of production, which

possesses some distinct characteristics. The volume of capital can be increased or

decreased. Capital plays a strategic role in boosting up o the productivity. Certainly a

farm entrepreneur would like to invest capital in a type of farming from which he

expects high turnover. Capital also determines the role of technological innovation in

agriculture, which results in the increase of output, decrease in the cost or both. The

volume of capital can be increased or decreased. Capital plays a strategic role in

boosting up of the productivity.

Table -4.10 Averages per acre capital inputs applied by the selected cotton

growers in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Seed 800.00 1200.00 1000.00 159.71 12.63

Urea 1800.00 2300.00 1947.5000 137.60 17.76

D.A.P. 2500.00 4000.00 2880.0000 450.16 58.11

Pesticides/Insecticide 500.00 750.00 589.6500 31.53 4.07

Equipment charges 150.00 500.00 290.0000 115.27 14.88

Total 5750.00 8750.00 6707.15 894.27 107.45

The cotton growers spent on capital inputs as average per acre costs is

presented in table-4.10. Total average per acre cost is Rs. 6707.15 (107.45). The

further cost ranges from Rs. 5750.00 to Rs. 8750.00 in the study area.

28

Marketing costs

Marketing costs are those expenses which are incurred by the growers

when agriculture commodities move from the producing field (farm gate) to the final

consumers for the disposal of their production, the growers it included number of

expenses on transportation, loading, unloading and commission charges. All these

expenses paid on the basis of per unit.

Table -4.11 Averages per acre marketing costs incurred by the selected cotton

grower in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Loading 140.00 350.00 209.50 85.597 9.25

Transportation 437.00 900.00 482.66 89.11 9.40

Commission 270.00 580.00 498.85 67.04 8.18

Un loading 150.00 500.00 313.76 124.22 7.79

Total 997.00 2330.00 1504.77 365.967 34.62

It is apparent that the result presented in table-4.11 that the selected

cotton growers on average spent Rs. 1504.77 (34.62) per acre marketing charges,

these includes Rs.209.50 (9.25) loading charges, Rs.482.66(9.40)

Rs.313.76(7.79) on unloading and Rs.498.85(8.18) on commission charges. The

table further presented in the study area ranged between Rs. 997.00 to Rs. 2330.00

incurred marketing cost.

29

Total Cost of Production

The total cost is defined as sum of fixed cost plus variable costs make

the total cost of production. To determine the cost of production, it was considered

essential to being together all costs calculated under various headings. Therefore,

fixed costs (land inputs) and variable costs viz, labour costs, capital inputs and

marketing costs incurred by the just to fix selected cotton growers in study area, were

consolidated it can be seen from the results shown in table-4.12

Table -4.12 Averages per acre total costs incurred by the selected cotton

growers in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Total fix cost 10755.87 14112.91 12277.95 1057.39 33.77

Labour cost 2812.00 5516.00 4381.30 737.53 27.15

Capital input 5750.00 8750.00 6707.00 894.00 30.00

Marketing cost 997.00 2330.00 1504.77 365.967 34.62

Total 20314.90 30708.90 24871.00 3054.89 125.54

Each cotton grower operating on average performance total costs of

production is presented in table-4.12 the result revealed that cotton farmers incurred

an average per acre cost Rs. 24871.00 (125.54) as total cost of production including

fixed cost, labour cost, capital inputs and marketing cost. The data further indicates

that cotton grower spent in the study area ranged between Rs. 20341.90 to Rs.

30708.90 on total cost in the study area.

30

Physical productivity

The yield when expressed in terms of physical weight is known as

physical productivity. It is generally expressed in terms of unit weight of production

obtained. In other words physical productivity of cotton farm is the same as the total

yield obtained of other crop by farmers is was determined by using following formula

APP = (TY-AS)

In the above formula APP stands for average physical productivity,

and TY total yield, whereas AS is symbolized the area sown under cotton production.

Table -4.13 Averages per acre physical productivity realized by cotton growers

in the study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Physical productivity 20.00 28.00 23.35 2.01 1.41

It explicit the results shown in that each cotton grower harvested and

average physical productivity presented in table-4.13. The results revealed that cotton

grower realized average per acre physical productivity of 23.3500 ( 1.41). The data

further indicates that the total physical productivity in the study area growers

harvested between 20.00 to 28.00 maunds per acre yield was attributed.

Revenue productivity

The value of farm production of gross profit it refers to money income

accruing to the farmers from the sale of their production. It is calculated by

multiplying the physical productivity (yield) obtained with the price, it is sold. For the

purposes of economic analysis, the revenue productivity at sample cotton farms in the

study area was also calculated the same formula for each individually farm and then

31

the averages per acres were derived, which is shown in table-4.14

Table -4.14 Averages per acre revenue productivity realized by selected cotton

growers in study, during 2010-2011.

Item Minimum Maximum Average Standard Deviation

Standard Error

Revenue 30400.00 49400.00 41249.16 4705.18 68.59

The revenue productivity average per acre is presented in table 16. The

result reveals that cotton growers realized an average per acre revenue productivity of

Rs. 41249.16 ( 68.59). The table further indicated that in the study area ranged

between Rs. 30400.00 to Rs. 49400.00 the revenue productivity was attributed.

Net - farm income

Net farm income is gross profits remains cash operating expenses and

depreciation cost of machinery and equipments costs could be obtained by subtracting

the gross revenue from cash operating expenses. Net income actually represents the

reward of the entrepreneur for producing a specific crop. Net income Averages output

or gross income after subtracting all farm expenses. Net income is calculated to judge

the efficiency of farm business as a whole. In order to measure the economic

efficiency of cotton per acre net return were computed by subtracting average per acre

cost from average per acre income obtained by sample growers.

32

Table -4.15 Averages per acre net income realized by the cotton growers in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Gross income (a) 30400.00 49400.00 41249.16 4705.18 68.59

Total cost of production (b) 20314.90 30708.90 24871.00 3054.89 125.54

Net income a-b=c 10085.1 18691.1 16378.20 1650.29 -56.95

The result showed that in the study area cotton growers received the

average per acre net income is presented in table-4.15. Results reveal that cotton

farmers realized an average per acre net returns of Rs. 16378.20 (56.95). The table

further indicates in the study area ranged between Rs. 10085.10to Rs. 18691.09 which

the growers received as net returns from cotton produce in the study area.

Input Output and Cost Benefit Ratio Relationship

The main objective of input-output ratio is usually used to determine

the production efficiency of some enterprise. That is calculated by dividing total

income with the total cost of production. The cost benefit ratio is defined as net

returns compared to cost of production. It is calculated by dividing net returns with

cost of production was computed on the basis of formula: Cbr = Nvp / Tcp

In the above formula CBR represents cost benefit relationship

NVP denotes net value of productivity, where TCP symbolizes total cost of

production. The results regarding the input: output and cost: benefit ratio for the

cotton growers in Kandiaro area of district Naushahro Feroze are recorded.

33

Table -4.16 Input-output and cost benefit ratio calculated by the selected cotton growers in study area, during 2010-2011

Item Minimum Maximum Average Standard Deviation

Standard Error

Input-output Ratio 1:1.49 1:1.60 1:1.65 1.54 0.54

Cost Benefit Ratio 1:0.49 1:0.60 1:0.65 0.54 -0.45

In the above table-4.16 the results indicated that the input-output ratio

was 1: 1.65 and cost benefit ratio ranges 1:0.49 to 1:0.60. It evidently showed that

cotton producers obtained benefit of Rs. 1:0.65 an average while spending a rupee in

the study area which is meager benefits for the cotton grower it is due to the

unfavorable prices of their produce in the study area were examined.

34

CHAPTER-V

DISCUSSION

The most important sector of the economy of Pakistan is agriculture

through more than two-third population of the country lives in rural areas and their

livelihood continues to revolve around agriculture and allied activities. Pakistan is by

and large a mono-crop economy as cotton is the lifeline for the economy many others

are indirectly linked with cotton value chain. Thus, livelihood of millions of farmers

are directly associated with cultivation and harvesting of cotton crop and sale of lint

and of those employed along the entire cotton value chain is dependent on this single

crop. Nature has bestowed the province of Sindh with a variety of ecological

conductions suitable for the production of cotton crops (GOP, 2011).

Cotton is major crop of Sindh. It is grown over 602.183 thousand acres

producing 2966.040 thousand bales annually .Cotton production is expected to decline

by 1.3 million tons to 22.2 million tons, as against a rise in consumption to 24.1

million tons, in. Higher consumption is pushing prices up, and ICAC secretariat

forecasts a rise in prices to a season average of US$1.63 per kilogram of cotton during

2009-10. Production will rebound to 24.4 million tons due to increases in area as well

as increases in yields. Consumption will also raise, thus expected supporting prices in

2010-11. The cotton crop is produced in area of Sindh comprising Ghotki Khairpur

Mirs, Sukkur, Shaheed Benzirabad (Nawabshah), Sanghar, Mirpurkhas Hyderabad

and Naushahro Feroze districts. (GOP, 2010).

The average farm size was estimated at 15.23 acres land out of which

11 acres was under cotton crop, which indicates the importance of cotton crop in

cropping pattern. The education level of selected growers was observed that selected

growers was in order 35.00% primary (5-years), 18.30% middle (8-years), 13.30%

35

matriculate (10-years) 6.70% intermediated (12-years), 1.70% graduate beyond the

25.00% of cotton respondents were illiterate in the study area. It was found that

majority of the selected cotton farmers i.e. obtained technical information from

neighboring farmers that was 33.3 percent while obtained 26.7 percent from relatives,

20.00 percent from friends, 8.3% knowledge about cotton production practices from

electric media and newspapers and 11% from government agricultural department the

role of agriculture department on providing technical information was meager about

cultural practices and marketing was found minor.

The cotton growers were not satisfied with marketing system at

prevailing in the area. They claim that major portion of retail price was snatched by

the local traders who do not take part in production and leaving a major share for

them which was too small of their production activities. The marketing organization

of cotton due to increased production has assumed paramount importance. Yet it was

characterized to the in efficient as the traders working between growers and

consumers were completely dominating over the cotton marketing system. Cotton

marketing has been almost ignored and it has been left to regulate by itself in the

study area. Some established conventions were operative to govern cotton marketing

system which mostly favors the traders and middleman who exercise their control

over the prices.

The results indicated that cotton farmers incurred an average per acre

cost of there is apparent from the results presented in the table-4.8 that the selected

cotton growers in the study area paid average per acre fixed costs of Rs.12277.95

including rent of land, land tax irrigation charges and local fund. The results revealed

that cotton farmers incurred an average per acre cost of Rs. 11543.36 ( 30.91) as

land rent, land tax per acre was Rs. 302.91 ( 9.13), while irrigation charges per acre

was 238.43 ( 7.48) and local fund was 193.24 (6.74) per acre. The table further

36

indicated that the land rent ranged between Rs 10755.87 to 14112.91 in the study

area. The results revealed the cotton farmers incurred an average per acre cost of Rs

4381.30 ( 66.15) as labor costs; it further indicated that the labour cost ranged

between Rs. 2812.00 to Rs. 5516.00 averages per acres in the study area.

While GOP (2006) reported that the variations were in yield which

suggests that there may be a reliable potential for improving productivity. The cotton

growers of the study area were confronted with many constraints, which were limiting

the expansion of cotton area and production. Haresh and uncertain climatic

conditions, shortage of irrigation water, improper use of inputs, ignorancy cultivation

techniques and in efficient marketing system were the main handicap constraints

causing low yield. Whereas, Sial et al. (2004) found that the improper agronomic

practices low, input supply and socio-economic constraints causing low yield.

The results shown that cotton farmers incurred average per acre cost

selected cotton growers spent 1504.77 (34.62) per acre marketing charges, these

includes Rs.209.50 (9.25) loading charges, Rs.482.66 (9.40) Rs.313.76(7.79) on

unloading and Rs.498.85(8.18) on commission charges the marketing cost in the

study area ranged between Rs. 997.00 to Rs. 2330.00. The cotton growers spent on

capital inputs as average per acre costs and total average per acre cost is Rs. 6707.00

(107.00). The further cost ranges from Rs. 5750.00 to Rs. 8750.00 per acre.

The result indicated that cotton farmers incurred an average per acre

cost each cotton grower operating on average performance total costs of production is

presented in table-4.12. The result revealed that cotton farmers incurred an average

per acre cost Rs. Rs. 24871.00 (125.54) as total cost of production including fixed

cost, labour cost, capital inputs and marketing cost. The data further indicates that

cotton grower spent cost in cotton production ranged between Rs. 20341.90 to Rs.

37

30708.90 in the study area.

The results further revealed that cotton grower realized average per

acre physical productivity of 23.3500 ( 1.41). The data indicates that the total

physical productivity in the study area growers harvested between 20.00 to 28.00

maunds per acre yield was attributed. Result interpreted that cotton growers realized

an average per acre revenue productivity of Rs. 41249.16 ( 68.59). The table further

indicated that in the study area ranged between Rs. 30400.00 to Rs. 49400.00.00 the

revenue productivity was recognized. Results reveal that cotton farmers realized an

average per acre net returns / income of Rs. 16378.20 (56.95). The result further

indicates in the study area ranged between Rs. 10085.10to Rs. 18691.09 which the

growers received as net returns from the study area and indicated results that the

input-output ratio of cotton growers average was 1: 1.65 and cost benefit ratio was

1:0.60. It evidently examined that cotton producers obtained benefit of Rs. 0.60

average while spending a rupee in the study area. While Sial et al. (2004) reported

that the cotton growers received Rs. 4235, average per acre returns. In that study area

input output and cost benefit ratio were estimated 1: 1.81 and 1: 0.81.

The result discussed in above section clearly indicate that the cost of

production as well as returns (physical and revenue) have increased over the time.

Normally, the increases in revenue returns take place because of technologically back

stopping or technical efficiencies, abundant availability of water in the area, and use

of hybrid seed cotton crop.

Although constraints were in the study area as follows:

(A) Production constraints were found from the study area

(1) Physical constraints of seed, labour and fertilizers

38

Lack of pure and quality seeds of cotton, Lack of agricultural labour

during peak seasons, lack of availability and high price of genuine fertilizers, lack of

availability of micro-nutrient fertilizers and lack of knowledge about recommended

package of practices (by agencies)

(2) Irrigation constraints

Underground water not fit for irrigation of cotton, inadequate irrigation

facilities, low availability of irrigation power, and high cost of irrigation

power.

(3) Plant protection constraints

High incidence of diseases, high incidence of sucking insect in cotton,

high incidence of other insect pest in cotton and lack of availability of genuine plant

protection chemicals

(4) Credit constraints

Lack of capital resources, lack of credit availability from institutional

sources and high cost of credit

(B) Marketing constraints were found from the study area

Lack of timely availability of good quality seeds, high prices of quality

seeds, lack of timely availability of genuine fertilizers, lack of timely availability of

plant protection appliances, lack of marketing facilities at village level, low price of

farm produce at the time of harvesting, lack of storage facilities, lack of grading and

standardization, lack of cheap and efficient transport, delay in payment by the

marketing agencies and less payment by the marketing agencies

39

CHAPTER-VI

CONCLUSION AND SUGGESTIONS

The present research study on economic analysis of cotton cultivation

in study area was conducted to investigate the average status of cotton production in

Sindh and Pakistan, average per acre cost of production, physical and revenue

productivity, net return, input output ratio, cost benefit ratio, issues and constraints,

faced by cotton growers and to suggest policy measures for sustainable cotton

production. The results derived from the study are concluded here under:

On the basis of present investigation in may be summing up, it is

concluded that cotton is the main cash crop of Pakistan and plays an important role in

the economy of the country. In our country, there are 80 percent of small growers and

they face financial constraints at the time of ploughing farms. They purchase their

input from the local traders on loan at high interest rates or pay 10 percent to 25

percent more price. While purchasing input from the market, they pay more prices

and when they bring their output for sale, they receive smaller amount. Keeping in

view these problems, they are unable to save from income for future crop.

In the study area an average age of selected cotton growers was 51.3

years. Almost all the respondents were married with family size 12 members. 60% of

the selected cotton growers were engaged full time in farm whereas, 40% were

operating as part time business. The selected cotton growers on an average owned 39

acres land overall, and about 80% were under cotton cultivation. The main source of

irrigation was canal and somehow was on tube well.

In the study area the most popular commercial cotton varieties Ali

Akbar-802, CIM-109, NIAB-78, CIM-111, Neelam- 121 and Qalandri were

40

respectively grown the by the farmers. More or less all the selected cotton growers

applied in drilling system. Fertilizer and pesticides sprayed 1 to 3 times during the

season. The selected respondents carried ploughing, sowing, fertilizer applications,

inter-culturing and picking operation by hired labour. The selected cotton growers

marketed or sold cotton produce at taluka level and local market. It was observed that

about all the selected cotton growers were self marketing their produce. It was

investigated that cotton grower got benefit of Rs. 1:0.60 average while spending a

rupee in the study area.

Hence, the farmers are not getting potential benefits from their cotton

crop. It is also to mention that due to fast growing inflation in the country, the cost of

cotton production, even calculated a year ago, would not serve the purpose. Thus, it is

quite imperative to calculate production costs of cotton on yearly basis till the stability

in the capital and recurring costs. The economic analysis review indicates that cost of

cotton production is in a continuous change due to inflation and the prices of inputs

are continuously changing. The fast changing scenario in costs on inputs used in

cotton, services rates and capital costs demands a regular study on the economic

parameters of cotton production. The main problem reported by the selected cotton

growers was on farms shortage of irrigation, low quality of seed and pesticides,

market distance low price of cotton crop received, poor farm market road, costly

inputs and exploitation of local traders. The cotton in important commercial crop in

study area, therefore its cultivation may be increased. Yet the growers are confronting

with many problems due to which per acre yield is declining.

41

Summary

1. Fixed cost

Average fixed cost per acre. Rs. 12277.95

2. Variable costs

Average labour cost per acre. Rs. 4381.30

3. Marketing cost

Average per acre marketing costs Rs. 1504.77

4. Capital inputs

Average per acre capital inputs Rs. 6707.00

5. Total costs

Average per acre total costs Rs. 24871.00

6. Physical productivity

Average per acre productivity 23.35 Mds (40 kg)

7. Revenue products

Average Revenue productivity per acre Rs. 41249.16

8. Net Farm income

Average net income per acre Rs. 16378.20

9. Input-Output ratio Rs. 1:1.65

10. Cost benefit ratio Rs. 1:0.65

42

SUGGESTIONS

The agricultural extension people of the provincial governments posted in the

rural areas provide on the spot guidance in the correct methods of production

practices and marketing.

To reduce losses during harvesting, bagging, marketing, transport have been

provided the facilities between main producing and consuming centers.

The growers should be trained about proper farm management practices

(proper use of chemical fertilizers, pesticides, inter-culturing and irrigation).

The loan facilities either public bank or by commercial banks should be

provided at low interest rate.

Farm to market roads should be constructed by government or by private

agencies on self help basis. Research, extension and education system should

be strengthened to cash the current research findings.

Availability of good quality high yielding hybrids seeds are required to

accelerate cotton growth and adoption of quality seed of desired varieties

along with timely supply of fertilizers may be ensured fertilizer, pesticides,

sprayers and other inputs of farm should be provided at subsidized rates.

The proper diffusion of modern technical knowledge and recommended

agronomic practices should be introduced through on farm research trials.

It is possible to increase cotton production by increasing the support price

programmed should be continued with the objective of attaining self

sufficiency in cotton crop. Support prices should be announced well before

sowing time and implemented effectively. Understand that unless it becomes

economically viable no new investment will take place for the profitability of

cotton growers.

43

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