e Pakistan Rehman

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Modeling the Cotton Sector of PakistanA Preliminary Empirical Investigation1

By

Tazeem-ur-Rehman2

Dr. Sajjad Akhtar3

1. Introduction

Pakistans yearly economic performance is heavily dependent on cottonc rop . Its stand ing as prod uc er and consumer of c otto n in the world isfa irly high, as it is the fourth largest p rod uc er and third la rgest c onsumer ofc otto n. Co tton based textiles c ontribute over 60 percent to the tota lexports, accounts for 46 percent of the total manufacturing and providesemp loyment to 40 percent of the manufac turing labour forc e. In times ofbelow normal crop, Pakistan imports a substantial quantity to meet the

req uirement o f the dome stic industry. Given cottons imp ortanc e in thenational economy, one needs to understand the dynamics anddeterminants of its exports and domestic consumption by the mill andnon-mill sector (the two largest sources of its use) for effective planning,forec asting a nd polic y intervention in this vital sec tor.

The ob jec tive o f this p reliminary investiga tion is to mo del the exports ofraw cotton and mill plus non-mill consumption and understand theirhistorical dynamics through quantifying the impact of other relevantmacro economy indicators on these two major uses of cotton crop.These imp ac t multip liers c an b e used to assess the effica c y of p olic y

interventions, project the demand by mill and non-mill sector and finetune the polic y on exports of raw c otto n. After a b rief review of theliterature on modeling of cotton sector, we outline the data base,empirical methodology and modeling specification in section 3.Exploratory ana lysis and estima tion results a re p resented in sec tion 4. Thelast sec tion conta ins the summ ary and polic y imp lic a tions.

2. Review of Literature

There may ha ve been o nly spa rse informa l (unpub lished ) a ttempts a tmodeling the Pakistans cotton economy in a behavioral mode, as the

autho r d id not find any pub lished em piric a l litera ture o n this issue. At theinternational level an article by Goreux, et al, (2007)4 modeled index of

1This artic le is a co ntribution from the ICAC c oo rdinating ag enc y in Pakistan. Any c omm ent should be

subm itted d irec tly to the autho rs.2Direc tor (Mktg . Eco.) Resea rch, PCCC, Karac hi.

3Free Lanc e Ec onom ist a nd former direc tor of Ce nter for Resea rch on Poverty Red uction a nd Inco meDistribution, Islama ba d.4 Internationa l Cot ton Ad visory Co mm ittee , Review of t he World Situation ,Vol.60, No.7, July-August 2007.


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inte rna tiona l pric es [(Cotlook A Index) see Annex- II] for forec asting purposesand tested its ex-post and ex-ante forecasting performance. Heformulated the determinants of world price of cotton (captured by theabove index) in a price expectations framework, with the ratio of end-of-yea r stoc k to m ill c onsumption ratio (STKSMIL) as the ma in d etermina nt o f

expec ted pric e. The lowe r this ra tio, the g rea ter wo uld be the p ressure onwo rld p rices. In order to c ap ture the pric e expec ta tions, he used the ratioof current a nd lag ged STKSMIL.

3. Data b ase and m ode l spec ifica tion

The histo rica l annua l time series spans the Y70 to Y08 (Co tton Sea son sta rtsAugust-July) and is c olla ted from va rious sourc es. The da ta sourc es a re:Data base of Pakistan Central Cotto n Com mittee, Pub lic a tions of Fed eralBureau o f Sta tistics, World Development Rep ort a nd va rious issues ofInte rna tiona l Cot ton Ad visory Comm ittee, USA.

In a red uced form fram ework, the c otton ec onom y is modeled in a set o fthree behavioral equations, consisting of determinants of i) exports of rawcotton, ii) mill plus non-mill consumption and iii) domestic price of cottonin c ents per pound .

I. Raw cotton exp orts (XPRTS)

It is postulated to depend on world production (WRLDPRD), internationalc otto n p rice index (INDEXA), tota l domestic ava ilab ility (TSUP) and mill p lusnon-mill co nsumption (MNMLCON).

II. Mill plus Non-m ill Consumption

The domestic use of raw c otton is related to textile expo rts (TEXTLXPRTS),total domestic availability, 5-year moving average of growth rate in percapita income (PCYAV5) and domestic price of cotton in cents(PKPRICE).

III. Domestic Price

Domestic price of cotton is a function of mill plus non-mill consumption,

interna tiona l c otto n price inde x and imports (MPRTS). For Pakista n, ava riant o f Goreux (2007) mo del is a lso estimated from the da ta , by using ara tio of current to lag ged va lue of stoc ks to mill ra tios (RATIO)

IV. Estimation Methodology

The a bove three mo dels in red uc ed form w ill be estima ted sep ara tely byOrdinary Least Squa re (OLS) Tec hnique a lso popularly know n a s multip le


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variable regressions. Serial correlations in estimation results will becorrected through trial and error choice of combination of auto-reg ressive (AR) and mo ving average (MA) terms.

V. Long-Term Trends and Desc riptive Statistics

We plot each of the above determinants as well as the dependentva riab les aga inst time in Figure 1-9. The fo llowing patte rns em erge fromthe trends: a) Domestic price and index of international price showconsiderable year to year fluctuations and move in a coordinatedma nner. B) Mill p lus non-mill c onsumption and textile e xports p icked up a ta rapid rate since 1985, while imports picked up with a fluctuating trendsinc e 90s. c ) tota l dom estic supp ly and wo rld p rod uc tion show a grad ua lrising trend with fluc tua tions. Structural positive shift in domestic sup p lyoccurred around 1985, with another discrete jump in 2005. d) Except for

the period from mid-80s to mid-90s, the trend in export of raw cotton isa lmo st fla t or sta tiona ry, e) Exc ep t for a e xtrem e fla re-up a round 1975,the ratio of current to lagged value of stocks to mill ratio remain aroundthe va lue o f 0.5 and 2.

Tab le 1 gives the desc riptive sta tistics of the va riab les used in themodeling exercise. On the average mill plus non-mill consumption is 76pe rc ent of average supp ly. Another 14 pe rc ent of the raw c otton on theaverage is expo rted p er yea r. Nineteen pe rc ent of mill c onsump tionrem ains as the end o f yea r stoc k. Coefficient of Varia tion which is a ratioof variability and me an ca n be com pared a c ross va riab les. Dome stic

price, international cotton price index and world production have thelea st amo unt of varia tion, a round 20 percent. Imp orts a rec entphenomenon, raw cotton exports and value of textile exports in $ termsshow va riability of around and m ore than 100 percent. Stoc ks to m ill ra tioshow less variation than the ratio of current to lagged value of thisvariable Annual Compound Growth Rate (ACGR) for each of theva riab les for the p eriod is a lso g iven in Tab le 1. Exce pt textile exports andimport o f raw c otto n, all va riab les exhib it a low single d igit grow th. This is tobe expected given the fluctuations in the historical series and thatc om pound g row th ra te is taken ove r two p oints in time . Raw c otton

exports show a slow dec lining trend since the 1970s.


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Fig-1

Fig-2


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Fig-3

Fig-4


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Fig-5

Fig-6


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Fig-7

Fig-8


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Fig-9

Fig-10


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Fig-11


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Table 1

Mean Std. Dev. Co- efficient

of

Variation

Annual

Compound

Growth

Rate

Observation

Domestic Cotton Price in

Cents/lb (PKPRICE) 58.95 13.93 23.63 1.44 37

Cotlook Index A incents/lb

(INDEXA)66.55 15.42 23.17 2.2 37

Mill + Non-millConsumption in 000ba les of 170 Kgs(MLNMLCON)

6596.14 4044.63 61.32 1.5 37

Imports in 000 balesof 170 Kgs

446.32 757.98 169.83 17.8 37

Exports in 000 balesof 170 Kgs 1194.84 1151.02 96.33 -1.72 37

World Production in 000MT

(WRLDPRD)17473.76 3962.54 22.68 2.3 37

Tota l do me sticAvailability in 000 bales

of 170 Kgs(TSUP)8687.65 4225.82 48.64 4.62 37

Textile Export

(TEXTLXPRTS) 3013.28 3153.64 104.66 13.50 37

5-year moving averageof growth rate in percapita income

(PCYAV5)

2.31 1.23 53.25 - 37

Current Stoc ks Mill Ratio

(STKSMILLRAT) 0.194166 0.117996 60.76 8.02 38Current to lagged valueof Stocks to mill Ratios

(RATIO)1.2909895 1.103800 85.51 3.17 38

4. Estimation Results

I. Raw Cotton Exports

Tab le 2 g ives the estimation results of m od eling the raw c otton expo rts fromPakista n in the last 37 yea rs. The mod el is free from serial correla tion w ith the use

of ARIMA terms and impac t of exoge nous va riab les is as per a p riori expe c ta tionsand sta tistica lly signific ant. Higher world p rod uc tion of co tton and d om esticc onsump tion imp ac t neg atively on raw c otton exports from Pakistan. Inc rea se of1 pe rc ent in ea c h o f these indica tors lea ds to a dec line o f slightly more tha n 3

perce nt in raw c otto n exports. Dom estic prod uc tion plus c a rry over stoc ks andlagged index of international prices impact positively on exports, although the

impac t o f interna tional p rices is only slightly ab ove unita ry e lasticity.


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II. Mill plus Non-Mill Consumption

Most of raw c otton is c onsumed dom estic a lly by the forma l and informa l textilesec tor. Till the nineties, dome stic p rod uc tion w as suffic ient to m ee t the dom esticdemand, but the latter outstripped the former and since then imports have

become more or less a regular yearly feature, except in years of abnormalp rod uc tion suc h as in FY05. The results of estima ting the m od el for do me stic useare g iven in Tab le 3. The seria l co rrelation in the m od el is c orrec ted with the use

of approp ria te ARIMA te rms a fter expe rime nta tion. The a p riori imp ac ts of thedeterminants for domestic use are confirmed in case of textile exports anddom estic supp ly by the estima tion. Experime nta tion with bo th dom estic p rices of

raw cotton and index of international prices in turn yielded statisticallyinsignifica nt results. Inc lud ing do me stic p ric e how eve r gave a lower standard

error of reg ression3. Signific ant and neg ative imp ac t of grow th ra te of pe r c apitaincome (5 year moving average)4 on the domestic use challenges the a priori

notion, but suggests that raw cotton may be regarded as inferior commodityand/or consumption switches to blended and expensive textiles with growth ininc om e. Although neg a tive, the imp ac t is very sma ll, i.e., a 1 pe rc ent inc rea se in

growth rate low ers raw c otton c onsump tion in the country by 0.06 percent. Forevery one percent increase in the value of textile exports, the use of raw cotton(in physical quantities) increases by 0.61 percent.

2During the period 1970-2007, impo rts have range d from a low o f 0.02 percent in 1991 to

a high o f 23 perce nt in 2004 of d omestic p rod uct ion.

3See append ix for the estimat ion results with inde x of internationa l pric es.

4Since growth in GDP per cap ita in Pakista n is c losely linked with performanc e o f the

textile industry a nd in turn c otto n p rod uc tion in the c ountry, these c ontrad ic tory results

c an be the p ossible outcom e o f end og ene ity as we ll as multicollinea rity be twe en these

three indica tors. The simp le c orrelation be twe en 5-yea r moving a verage of g row th rate

of M LNMLCON and PCYAV5 is 0.39 and betw ee n 5-year mo ving a verag e of TSUP and

PCYAV5 is 0.62.


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Table 2

Depend ent Va riab le: LOG (XPRTS)

Me thod : Lea st Squares

Sample (adjusted): 1974-2007

Inc luded ob servations: 34 afte r ad justments

Variable Coefficient Std. Error t-Statistic Prob.

C 15.100 4.717 3.201 0.004

LOG(WRLDPRD) -3.374 0.950 -3.552 0.002

LOG(INDEXA(-1)) 1.244 0.458 2.717 0.012

LOG(TSUP) 5.269 0.332 15.880 0.000

LOG(MLNMLCON) -3.255 0.332 -9.793 0.000

XPRTDUM -2.933 0.314 -9.346 0.000

AR(1) -0.386 0.190 -2.034 0.054

AR(2) -0.234 0.237 -0.989 0.333

AR(3) 0.327 0.170 1.918 0.068MA(1) 0.530 0.089 5.973 0.000

MA(2) 0.995 0.094 10.604 0.000

Adjusted R-squared 0.9312 Mean of dependent variable 6.5135

S.E. of regression 0.3363 F-statistic 45.6399

Durbin-Watson stat 1.9573 Probability(F-statistic) 0.0000

III. Domestic Price of Raw Co tton

Theoretic ally the p ric e o f raw c otton in the c ountry should b e d etermined by its

de ma nd a nd supp ly. How eve r as Pakistan is a ma jor prod uc er and c onsume r ofc otto n, its p rod uc tion influenc es the w orld ava ilab ility and in turn is influenc ed bythe rest of the wo rld p rod uc tion. Conseq uently under a parad igm of c ostless

flow of information and law of one price domestic price is influenced andinfluenc es the w orld p rice a nd thereb y index of internationa l p rices.

The e xplana tory po wer of this mo del is less as indica ted by the low va lue o fad justed R2 c om pa red to the expo rt and m ill c onsump tion mod el. How eve r the

impacts are significant and according to a priori expectations, with no serialc orrelation. The d om estic p rice m ore or less mo ves in tandem with the index ofinternational prices as 1 percent increase in it leads to 0.94 percent increase in

dom estic p ric e. Inc rea sed mill p lus non-mill c onsumption also supports the

do me stic p ric e. A one percent increase in the physic al co nsump tion by thetextile sec tor pushes up the p ric e b y 0.14 percent. Last yea r imports damp endom estic p ric e by a lmo st a n insignifica nt a mo unt, but is sta tistica lly significa nt.

Nave form of price expectation model as suggested by Goreux (2007) is also

em p irica lly estima ted fo r Pakistan. The results a re g iven in Tab le 5. The ra tio ofc urrent to lag ged stoc k-to-mill ra tio (RATIO) ha s the c orrec t sign a nd is sta tistica llysignific ant. An inc rea se o f one unit of ratio red uc es the d om estic c otton price b y


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2 percent. The imp ac t of index of inte rna tiona l p rices on do me stic pric e

we akened ma rginally in this mo de l as c om pa red to the p revious mo de l. Theovera ll fit sta tistics of th is mod el are b et te r tha n the first va riant , with higher ad j. R2and lowe r standard error of reg ression.

Table 3

Dep end ent Va riab le: LOG (MLNMLCON)



Variab le Coeffic ien Std. Error t-Statistic Prob .

C 1.648 0.431 3.824 0.001

LOG(TEXTLXPRTS) 0.614 0.049 12.481 0.000

LOG(TSUP) 0.298 0.059 5.023 0.000

PCYAV5 -0.065 0.017 -3.792 0.001

LOG(PKPRICE(-1)) 0.000 0.065 0.001 0.999

DUMTEXXPRTS -0.444 0.082 -5.415 0.000

AR(1) 0.799 0.197 4.052 0.000

AR(2) -0.164 0.161 -1.019 0.318

MA(1) -0.015 0.040 -0.377 0.709

MA(2) -0.958 0.033 -28.625 0.000

Ad justed R-squa red 0.9914Mean of dependent

variable 8.6378

S.E. of reg ression 0.0597 F-sta tistic 438.3134

Durbin-Watson sta t 2.0904Probability(F-

sta tistic ) 0.0000


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Table 4

Dependent Variable: LOG(PKPRICE)


Sample (a d justed ): 1972 -2007Inc luded ob servations: 36 afte r ad justments

Variable

Coefficin Std . Error t-Sta tistic Prob .

C -1.026 0.630 -1.627 0.115

LOG(INDEXA) 0.947 0.080 11.821 0.000

LOG(MLNMLCON) 0.138 0.050 2.789 0.009

LOG(MPRTS(-1)) -0.020 0.009 -2.305 0.029

AR(1) 0.840 0.149 5.653 0.000

AR(2) -0.455 0.154 -2.960 0.006

MA(1) -0.731 0.039 -18.655 0.000MA(2) 0.995 0.039 25.638 0.000

Ad justed R-squa red 0.8771Mean of dependent

variable 4.0640

S.E. of reg ression 0.0822 F-sta tistic 36.6774

Durbin-Watson sta t 2.0635 Prob ab ility(F-sta tistic ) 0.0000

Table 5

Dependent Variable: LOG(PKPRICE)

Me thod : Lea st SquaresSample: 1970-2007

Inc luded ob servations: 38

Variab le Coeffic ient Std . Error t -Sta tistic Prob .

C 0.296 0.265 1.120 0.271

LOG(INDEXA) 0.909 0.064 14.285 0.000

RATIO -0.025 0.006 -3.962 0.000

MA(1) 0.827 0.175 4.723 0.000

MA(2) -0.151 0.180 -0.840 0.407

Ad justed R-

squared 0.9195Mean of dependent

variable 4.0283

S.E. of regression 0.0781 F-sta tistic 106.6559

Durbin-Watson sta t 1.9982 Prob ab ility(F-sta tistic ) 0.0000


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5. Summ ary and Conc lusions

The o b jec tive of this em p iric a l investiga tion is to m od el the use o f raw c otto n

produc ed in the country. As the fourth largest produc er of cotton and thirdlargest consumer of cotton, casual empiricism suggests that the performance of

Pakistans cotton sector influences and is influenced by the rest of the worldc otton sec tor pe rforma nce. How eve r for a be tter unde rstand ing and p olic yplanning purposes it is imperative to quantify the extent of intra-world

transmission on the domestic cotton sector. As the author is unaware of anyem piric al studies on mo de ling of the c otton sec tor, any p reliminary a ttemp ts tomo de l it, ca n c ontribute to the unde rstanding o f multip lier imp ac ts and a c t as a

springboa rd for further resea rc h.

Using the time series data on raw cotton use, production, carry-over stocks,prices and imports, from 1970 onwards, three reduced form single equation

independent models are estimated for:- a) raw cotton exports, b) mill plus non-mill c onsump tion a nd c ) dom estic pric e. Most of the imp ac ts estima ted from

using single eq ua tion OLS tec hnique c onfirm the a p riori expe c ta tions reg a rd ingtheir c ausa lity. Imp ortant find ings a re a s follow s:- a ) Inc rea se o f 1 percent e ac hin world production and higher domestic consumption decrease raw cotton

exports by 3 percent, b) A one percent increase in domestic production andlagge d index of internationa l p ric es increase raw c otton exports by 5.27 and 1.24percent respectively, c) For every one percent increase in the value of textile

expo rts, the use of raw c otton (in p hysica l qua ntities) increa ses by 0.61 perce nt.,d) Dome stic pric e of c otton has no imp ac t on c onsumption of raw c otton b y the

textile industry, d) A one percent increase in production of cotton encouragesmill c onsump tion by 0.3 perce nt, e) Dom estic p rice is c ong ruent w ith the index ofinternational p ric es, and f) there is evidenc e that do me stic pric e setting b eha vior

adapts to and is influenced by end-year stocks in relation to mill consumption,ra ther tha n just mill p lus non-mill c onsump tion.

From a policy angle, these impacts need to be taken into consideration, whenassessing policy interventions such as imports, forecasting the impact of

increased mill consumption and textile exports and planning for higherproduc tion a nd c arry-ove r stoc ks. A b roa der finding though not startling or novel

and in many respects obvious, is that given the importance of Pakistan in theinternational cotton market, the domestic market in terms of price signals is wellinteg ra ted with the rest of the wo rld c otton sec tor.


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APPENDIX

Dep end ent Va riab le: LOG (MLNMLCON)


Sample (a d justed ): 1973 -2007


Va riab le Coeffic ient Std . Error t-Sta tistic Prob .

C 1.514 0.525 2.884 0.008

LOG(TEXTLXPRTS) 0.639 0.054 11.858 0.000LOG(TSUP) 0.293 0.060 4.895 0.000

PCYAV5 -0.064 0.017 -3.813 0.001

LOG(INDEXA(-1)) -0.004 0.067 -0.052 0.959

DUMTEXXPRTS -0.462 0.085 -5.437 0.000

AR(1) 0.891 0.207 4.296 0.000

AR(2) -0.173 0.162 -1.063 0.298

MA(1) -0.024 0.059 -0.412 0.684

MA(2) -0.970 0.048 -20.423 0.000

Ad justed R-squa red 0.9911

Mean of dependent

variable 8.6378S.E. of reg ression 0.0609 F-sta tistic 422.1753

Durbin-Watson sta t 2.2199Probability(F-

sta tistic ) 0.0000

Annex-II

Co tlook Index A is the o ffering p rice on internationa l raw c otto n ma rket. It is anaverage of the cheapest five quotations from a selection (at present nineteen)of p rincipa l up land c otto ns c lassed 1-3/32 trad ed interna tiona lly. Those g row ths

are the mo st c om petitive, which the refore a re likely to b e trad ed mo st freq uentlyand in mo st volume.

Tod ay the Co tlook Indices are ac knowledg ed by the trad ing frate rnity,go vernments, and interna tiona l orga niza tions suc h a s UNCTAD a nd ICAC, a s

ac c ura te m ea sures of the fluc tua tion of internationa l raw c otto n values. Seve ra lproducing countries incorporate the indices, or elements thereof, into national

farm legislation.

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e Pakistan Rehman