From he SelecedWorks of Marin Ravallion December 2006 China's (Uneven) Progress Agains Povery Conac Auhor Sar Your Own SelecedWorks Noify Me of New Work Available a: hp://works.bepress.com/marin_ravallion/2
Journal of Developmen Economics, forhcoming China s (Uneven) Progress Agains Povery Marin Ravallion and Shaohua Chen 1 Developmen Research Group, World Bank 1818 H Sree NW, Washingon DC, 20433, USA While he incidence of exreme povery fell dramaically in China over 1980-2001, progress was uneven over ime and across provinces. Rural areas accouned for he bulk of he gains o he poor, hough migraion o urban areas helped. Rural economic growh was far more imporan o naional povery reducion han urban economic growh; agriculure played a far more imporan role han he secondary or eriary sources of GDP. Taxaion of farmers and inflaion hur he poor; local governmen spending helped hem in absolue erms; exernal rade had lile shor-erm impac. Provinces saring wih relaively high inequaliy saw slower progress agains povery, due boh o lower growh and a lower growh elasiciy of povery reducion. Keywords: China, povery, inequaliy, economic growh, policies JEL: O15, O53, P36 1 The auhors are graeful o he saff of he Rural and Urban Household Survey Divisions of China s Naional and Provincial Bureaus of Saisics for heir invaluable help in assembling he daa base we draw on in his paper. Helpful commens were received from David Dollar, Tamar Manuelyan Ainc, Jusin Lin, Michael Lipon, Will Marin, Nahalie Milbach-Bouche, Thomas Pikey, Lan Priche, Sco Rozelle, Dominique van de Walle, Shuilin Wang, Alan Winers, seminar/conference paricipans a he Naional Bureau of Saisics, Beijing, he McArhur Foundaion Nework on Inequaliy, Beijing Universiy, Tsinghua Universiy, he Ausralian Naional Universiy, he Inernaional Moneary Fund, he World Bank and he journal s anonymous referees. These are he views of he auhors and should no be aribued o he World Bank or any affiliaed organizaion. Addresses for correspondence: mravallion@worldbank.org and schen@worldbank.org.
1. Inroducion This paper aims o documen and explain China s record agains povery over he wo decades following Deng Xiaoping s iniiaion of pro-marke reforms in 1978. We apply new povery lines o newly assembled disribuional daa much of which has no previously been analyzed and we address some of he daa problems ha have clouded pas esimaes and poin o some coninuing concerns abou he daa. We hus aim o offer he longes and mos inernally consisen series of naional povery and inequaliy measures, spanning 1980-2001. While daa are less complee a he provincial level, we can esimae rends since he mid-1980s. Armed wih hese new measures, we address some long-sanding quesions in developmen economics, applied o he Chinese seing. How much do poor people share in he gains from economic growh? Does he secoral and geographic paern of growh maer? Wha role is played by urbanizaion? How did iniial disribuion influence subsequen raes of growh and povery reducion? How imporan are economic policies? Our principal findings are as follows: Finding 1: China has made huge overall progress agains povery, bu i has been uneven progress. In he 20 years afer 1981, he proporion of he populaion living in povery fell from 53% o 8%. However, here were many sebacks for he poor. Povery reducion salled in he lae 1980s and early 1990s, recovered pace in he mid-1990s, bu salled again in he lae 1990s. Half of he decline in he number of poor came in he firs half of he 1980s. Some provinces saw far more rapid progress agains povery han ohers. Finding 2: Inequaliy has been rising, hough no coninuously and more so in some periods and provinces. In marked conras o mos developing counries, relaive inequaliy is higher in China s rural areas han in urban areas. However, here has been convergence over 2
ime wih a seeper increase in inequaliy in urban areas. Relaive inequaliy beween urban and rural areas has no shown a rend increase over he period as a whole, once one allows for he higher increase in he urban cos of living. Absolue inequaliy has increased appreciably. boh beween and wihin boh urban and rural areas, and absolue inequaliy is higher in urban areas. Finding 3: The paern of growh maers. While migraion o urban areas has helped reduce povery naionally, he bulk of he reducion in povery came from rural areas. Growh in he primary secor (primarily agriculure) did more o reduce povery and inequaliy han eiher he secondary or eriary secors. Saring in 1981, if he same aggregae growh rae had been balanced across secors, i would have aken 10 years o bring he povery rae down o 8%, raher han 20 years. The geographic composiion of growh also maered. While provinces wih higher rural income growh ended o have higher povery reducion, growh was no higher in he provinces where i would have had he mos impac on povery naionally. The paern of growh also maered o he evoluion of overall inequaliy. Rural and (in paricular) agriculural growh brough inequaliy down; urban economic growh was inequaliy increasing. Rural economic growh reduced inequaliy in boh urban and rural areas, as well as beween hem. Finding 4: Economy-wide policies have had a mixed record. Agrarian reforms and lower axes on farmers (noably hough public procuremen policies) have helped reduce povery. Conrolling inflaion has also been pro-poor, boh absoluely and relaively. Public spending has reduced povery, bu no inequaliy, and he gains have ended o come from provincial and local governmen spending no cenral spending. The score-card for rade reform is blank; we find no evidence ha greaer exernal openness was povery reducing. Finding 5: Inequaliy has emerged as a concern for boh growh and povery reducion. Wih he same growh rae and no rise in inequaliy in rural areas, he number of poor in China 3
would have fallen o less han one-quarer of is acual value (a povery rae in 2001 of 1.5% raher han 8%). This calculaion would be decepive if he rise in inequaliy was he price of high economic growh, which did help reduce povery. However, we find no evidence of such an aggregae rade off. The periods of more rapid growh did no bring more rapid increases in inequaliy. Nor did provinces wih more rapid rural income growh experience a seeper increase in inequaliy. Thus provinces ha saw a more rapid rise in inequaliy saw less progress agains povery, no more. Over ime, povery has also become far more responsive o rising inequaliy. A he ouse of China s ransiion period, levels of povery were so high ha inequaliy was no a major concern. Tha has changed. Furhermore, even wihou a furher rise in inequaliy, he hisorical evidence suggess ha more unequal provinces will face a double handicap in fuure povery reducion; hey will have lower growh and povery will respond less o ha growh. 2. Daa on income povery and inequaliy in China We draw on he Rural Household Surveys (RHS) and he Urban Household Surveys (UHS) of China s Naional Bureau of Saisics (NBS). 2 NBS ceased doing surveys during he Culural Revoluion (1966-76) and saed afresh in 1978; he earlies disribuional daa available o us are for 1980 (for rural areas) and 1981 (urban). While all provinces were included from 1980, 30% had sample sizes in he surveys for he early 1980s ha NBS considered oo small for esimaing disribuional saisics (hough sill adequae for he mean). However, his does no appear o be a source of bias; we could no rejec he null hypohesis ha he firs available esimaes of our povery measures were he same for hese small sample provinces as he res. 3 2 On he hisory and design of hese surveys see Chen and Ravallion (1996) and Bramall (2001). 3 Included provinces had a povery rae by our main povery lines ha was 1.9% poins higher, bu his is no significanly differen from zero (-raio=0.32). This held for all oher povery measures. 4
Sample sizes for he early surveys were smaller; 16,000 households were inerviewed for he 1980 RHS and abou 9,000 for he 1981 UHS. Sample sizes increased rapidly, wih 30,000 households in he RHS for 1983. Since 1985, he surveys have had samples of 68,000 in rural areas and 30-40,000 in urban areas. Though smaller, he sample sizes for he early 1980s are sill adequae for measuring povery naionally (hey are larger samples han for many naional surveys). Also, he Chinese economy was far less diversified in he early 1980s han now, paricularly in rural areas where here was very lile non-farm aciviy and less diversiy in farm oupu han now. The more homogeneous rural economy of he early 1980s can be represened wih smaller samples. Agains his, i can be conjecured ha he earlies surveys underrepresened remoe rural areas ha he saisical officers would have had a hard ime reaching probably leading us o underesimae povery measures for his period. An unusual feaure of hese surveys is ha heir sample frames are based on China s regisraion sysem raher han he populaion census. This means ha someone wih rural regisraion who has moved o an urban area (bu kep rural regisraion) is missing from he sample frame. Migrans from rural areas gain from higher earnings (he remiances back home are capured in he RHS), bu are probably poorer on average han regisered urban residens. Agains his likely source of downward bias in povery esimaes from he UHS, he UHS income aggregaes do no capure fully he value of he various enilemens and subsidies received exclusively by urban residens, hough hese have been of declining imporance over ime. While NBS has selecively made he micro daa (for some provinces and years) available o ouside researchers, he complee daa are no available o us for any year. Insead we use abulaions of he income disribuion following a sandardized design in which households are ranked by income per person and all fraciles are populaion weighed. The majoriy of hese 5
daa are unpublished and were provided by NBS. 4 The income aggregaes include impued values for income from own-producion, bu exclude impued rens for owner-occupied housing. (Impuaion is difficul, given he hinness of housing markes.) The usual limiaions of income as a welfare indicaor remain. For example, our measures of inequaliy beween urban and rural residens may no adequaely reflec oher inequaliies, such as in access o public services (healh, educaion, waer and saniaion all of which end o be beer provided in urban areas). There was a change in valuaion mehods for consumpion of own-farm producion in he RHS in 1990 when public procuremen prices were replaced by local selling prices. (Pas esimaes have used he old prices for he 1980s and he new prices for 1990 onwards, ignoring he change.) Unil he mid-1990s, public procuremen prices for grain were held below marke prices. Using hese prices o value own consumpion over-esimaes povery. 5 This pracice was largely abandoned from 1990s onwards in favor of using local selling prices for valuaion. Using he old valuaion mehod, he impued value of food consumed from own-farm producion accouned for 21.8% of aggregae ne rural income in 1990; under he new valuaion mehod his rose o 27.4% for he same year (RSO, 2002); his came almos enirely from a 37.2% increase in he impued value of food consumpion in kind for 1990. While hese numbers make clear ha here was a subsanial change in 1990, no all provinces swiched fully o marke prices from 1990 onwards. From our discussions wih NBS saff is appears ha a few provinces (hree-five) used a mixure of procuremen prices and marke prices up o he mid-1990s. Two reasons were given. Firsly, provincial auhoriies 4 There are a number of abulaions in he NBS Saisical Yearbook, bu hey only provide he percenages of households in each income class; wihou he mean income for each income class and mean household size hese abulaions are unlikely o give accurae esimaes of he Lorenz curve. Some of hese daa are available in he Provincial Saisical Yearbooks or he Household Survey Yearbooks. 5 Ravallion and Chen (1999) examine he implicaions for measuring inequaliy in China. 6
hough ha marke prices would over-value consumpion from own farm producs on he grounds ha farmers end o sell heir beer qualiy grain; his is no likely o be a serious source of bias for he poor, given ha hey end o consume a large share of heir produc (Chen and Ravallion, 1996). Secondly, i was hough ha local officials in some poor counies were worried ha higher measured incomes would mean fewer public resources from he cener; his would enail over-esimaion of povery measures in he affeced provinces. 6 Wih complee access o he micro daa we could readily eliminae he inconsisencies in valuaion mehods over ime and across provinces. 7 Wihou he micro daa we have o find an alernaive mehod. To help us correc for he change in valuaion mehods in 1990, NBS provided abulaions of he disribuion in 1990 by boh mehods, allowing us o esimae wha he income disribuions for he lae 1980s would have looked like if NBS had used he new valuaion mehod. The Appendix describes he correcion mehod in deail. Our correcions enail lower povery measures in he lae 1980s. In measuring povery from hese surveys, we use wo povery lines. One is he longsanding official povery line for rural areas of 300 Yuan per person per year a 1990 prices. (There is no comparable urban povery line.) I has been argued by many observers ha his line is oo low o properly reflec prevailing views abou wha consiues povery in China. I can hardly be surprising ha in such a rapidly growing economy, percepions of wha income is needed o no be considered poor will rise over ime. 8 6 Yunnan was given as an example by NBS saff, and we verified wih Yunnan saff in Kunming ha mixure prices had been used up o he mid 1990s. The problem was no confined o poor provinces; for example, Guangxi and Guizhou used marke prices only from 1990 onwards. 7 In Chen and Ravallion (1996) we creaed a consisen series for 1985-90 from he micro daa for a few provinces. However, his is no feasible wihou he complee micro daa. 8 Povery lines across counries end o be higher he higher he mean income of he counry, hough wih an iniially low elasiciy a low income (Ravallion, 1994). 7
In collaboraion wih he auhors, NBS has been developing a new se of povery lines ha appears o beer reflec curren condiions. Region-specific food bundles are used, wih separae food bundles for urban and rural areas, valued a median uni values by province. The food bundles are based on he acual consumpion of hose beween he poores 15 h percenile and he 25 h percenile naionally. These bundles are hen scaled o reach 2100 calories per person per day, wih 75% of he calories from foodgrains. 9 Allowance for non-food consumpion are based on he nonfood spending of households in a neighborhood of he poin a which oal spending equals he food povery line in each province (and separaely for urban and rural areas). The mehods closely follow Chen and Ravallion (1996). For measuring povery naionally we have simply used he means of hese regional lines. Wih a lile rounding off, we chose povery lines of 850 Yuan per year for rural areas and 1200 Yuan for urban areas, boh in 2002 prices. (Ideally one would build up all naional povery measures by applying he regional povery lines o he provincial disribuions and hen aggregaing. However, his would enail a subsanial loss of informaion given ha we have only 10-12 years of rural daa a province level.) We use he 2002 differenial beween he urban and rural lines o calculae an urban equivalen o he 300 Yuan rural line a 1990 prices. Finally, we conver o prices a each dae using he rural and urban Consumer Price Indices (CPI) produced by NBS. For rural areas, here is a concern ha he rural prices colleced by NBS relae o markes in close proximiy o urban ceners. (We do no have hard evidence of his bu he possibiliy was noed by provincial NBS offices in our inerviews.) We reurn o his poin in he nex secion. 9 Wihou he laer condiion, he rural food bundles were deemed o be nuriionally inadequae (in erms of proein and oher nuriens) while he urban bundles were considered o be preferable. The condiion was binding on boh urban and rural bundles. 8
We also use hese urban and rural povery lines as deflaors for urban-rural cos-of-living (COL) adjusmens in forming aggregae inequaliy measures and for measuring inequaliy beween urban and rural areas. Pas work in he lieraure on inequaliy in China has ignored he COL difference beween urban and rural areas, and we will see ha his does maer. However, our COL adjusmens are no ideal, in ha a common deflaor is applied o all levels of income. We provide hree povery measures: The headcoun index (H) is he percenage of he populaion living in households wih income per person below he povery line. The povery gap index (PG) gives he mean disance below he povery line as a proporion of ha line (he mean is aken over he whole populaion, couning he non-poor as having zero gap.) For he squared povery gap index (SPG) he individual povery gaps are weighed by he gaps hemselves, so as o reflec inequaliy amongs he poor (Foser e al., 1984). For all hree, he aggregae measure is he populaion-weighed mean of he measures across any complee pariion of he populaion ino subgroups. Da and Ravallion (1992) describe our mehods for esimaing he Lorenz curves and calculaing hese povery measures from he grouped daa provided by he NBS abulaions. 3. Povery measures for China 1981-2001 The urban populaion share rose from 19% in 1980 o 39% in 2002 (Table 1). 10 This may be a surprisingly high pace of urbanizaion, given ha here were governmenal resricions on migraion (hough less so since he mid-1990s). 11 We do no know how much his semmed from urban expansion ino rural areas versus acual migraion from rural o urban areas. 10 The urban populaion shares are based on he daa provided by he census bureau of NBS, including he annual sample surveys used beween he decadal censuses. These daa are based on addresses raher han regisraions so he aforemenioned problem of undercouning he urban populaion based on regisraions does no arise. 11 For example, in India (wih no such resricions) he share of he populaion living in urban areas increased from 23% o 28% over he same period. 9
The cos-of-living differenial rises over ime, from 19% o 41% in 2002. The divergence beween urban and rural inflaion raes sared in he mid-1980s. I could well reflec he impac of urbanizaion on he prices of commodiies ha are no raded beween secors, such as housing and services. 12 The (parial) removal of subsidies on urban commodiies (including services) could also have shown up in a higher rae of inflaion in urban areas. Given ha he urban rae of inflaion exceeded he rural rae, he aforemenioned possibiliy of an urban bias in he rural CPI (secion 2) suggess ha we may have underesimaed he rae of rural povery reducion since he mid-1980s. Table 1 also gives our esimaes of mean income for rural and urban areas. The large dispariies in mean incomes beween urban and rural areas echo a well-known feaure of he Chinese economy, hough our COL adjusmen narrows he differenial considerably. 13 We will reurn in secion 5 o discuss he implicaions for urban-rural inequaliy. Table 2 gives our rural povery measures. Table 3 gives our esimaes for urban areas. For all years and all measures, rural povery incidence exceeds urban povery, and by a wide margin. Rural povery measures show a srong downward rend, hough wih some reversals, noably in he lae 1980s, early 1990s and in he las wo years of our series. The urban measures also show a rend decline, hough wih even greaer volailiy. Table 4 gives he naional aggregaes and Figure 1 plos he naional headcoun indices for boh povery lines. By he new lines, he headcoun index falls from 53% in 1981 o 8% in 12 A breakdown of he urban and rural CPI by ype of commodiy is only available from 1990 onwards. Over his period, he prices of services increased far more han oher goods, and far more in urban areas han rural areas. While he overall urban CPI increased by a facor of 2.16 from 1990-2001, as compared o 1.92 for he rural CPI, he services componen increased by a facor of 4.83, versus 3.81 in rural areas. Similarly, housing prices increased more seeply in urban areas, and more so han he overall CPI. 13 Since he laer adjusmen is based on he povery lines, i may no be appropriae for he mean (a leas oward he end of he period). Bu i is our bes available opion. 10
2001. Conservaively assuming he 1981 urban number for 1980, he naional index was 62% in 1980. There was more progress in some periods han ohers. There was a dramaic decline in povery in he firs few years of he 1980s. The bulk of his decline came from rural areas. By our new povery line, he rural povery rae fell from 65% in 1981 (76% in 1980) o 23% in 1985 (Table 2). On weighing by he rural populaion share, his accouns for 77% of he decline in he naional povery rae beween 1981 and 2001. By conras, he lae 1980s and early 1990s were a difficul period for China s poor. Progress was resored around he mid-1990s, hough he lae 1990s saw a marked deceleraion, wih signs of rising povery in rural areas. 14 We can decompose he change in naional povery ino a populaion shif effec and a wihin secor effec. 15 Leing P denoe he povery measure for dae, while i P is he measure for secor i=u,r (urban, rural), wih corresponding populaion shares exac decomposiion of he change in povery beween =1981 and =2001 as: r r r u u u u r u u (1) P01 P81 = [ n01( P01 P81) + n01( P01 P81)] + [( P81 P81)( n01 n81)] Wihin-secor effec Populaion shif effec i n, we can wrie an The wihin-secor effec is he change in povery weighed by he final year populaion shares while he populaion shif effec measures he conribuion of urbanizaion, weighed by he iniial urban-rural difference in povery measures. The populaion shif effec should be inerpreed as he parial effec of urban-rural migraion, in ha i does no allow for any effecs 14 Using differen daa, Benjamin e al., (2005) also find evidence of a deceleraion in he rae of growh in rural incomes in he laer par of he 1990s. Indeed, heir resuls indicae a decline in rural incomes, while we sill find gains over his period. This could reflec a difference in daa sources. Benjamin e al., use survey daa for nine provinces colleced by Minisry of Agriculure, for which he sample frame is only for agriculural households, while he RHS sample frame is he rural populaion as whole. The RHS daa also indicae sagnaion in he growh of rural household income from agriculure; by conras, rural non-farm aciviies acually did well in his period; income from agriculure accouned for 61% of China s rural ne income in 1995; his had fallen o 48% by 2000 (RSO, 2002). 15 This is one of he decomposiions for povery measures proposed by Ravallion and Huppi (1991). 11
of migraion and remiances on povery levels wihin urban and rural areas. 16 For example, urbanizaion may be an indirec cause of higher rural incomes, bu his would no be revealed by he decomposiion in (1). Thus i is a descripive decomposiion raher han causal. (Our regression-based decomposiion in he nex secion will be beer able o pick up indirec effecs.) Table 5 gives he decomposiion based on equaion (1). We find ha 35% poins of he 45% poin decline in he naional headcoun index is accounable o he wihin-secor erm; wihin his, 33% poins was due o falling povery wihin rural areas while only 2% poins was due o falling povery in urban areas. The populaion shif from rural o urban areas accouned for 10% poins. The oher povery measures ell a very similar sory, hough he rural share is slighly higher for SPG han PG, and lowes for H. As can be seen from he lower panel of Table 5, he paern is also similar for he period 1991-2001, he main difference being ha he wihinurban share falls o zero using he old povery line, wih he rural share rising o around 80%. So we find ha 75-80% of he drop in naional povery incidence is accounable o povery reducion wihin he rural secor; mos of he res is aribuable o urbanizaion of he populaion. Undersanding wha has driven rural povery reducion is clearly of firs-order imporance o undersanding he counry s overall success agains povery. 4. Povery reducion and economic growh We begin by examining he relaionship beween our esimaed povery measures and mean incomes, afer which we ake a closer look a he role played by he paern of growh. The relaionship beween povery and growh. Povery in China fell as mean income rose; he regression coefficien of he log naional headcoun index on he log naional mean is 1.43, 16 This can be inerpreed as a Kuznes process of migraion whereby a represenaive slice of he rural disribuion is ransformed ino a represenaive slice of he urban disribuion. 12
wih a -raio of 15.02. However, his is poenially decepive, given ha boh series are nonsaionary; he residuals show srong serial dependence (he Durbin-Wason saisics is 0.62). Differencing deals wih his problem. 17 Table 6 gives regressions of he log difference in each povery measure agains he log difference in mean income per capia. There is a possible upward bias in he OLS esimaes semming from common measuremen errors in he dependen and independen variable; when he mean is overesimaed he povery measure will be underesimaed. Following Ravallion (2001) we use he GDP growh rae as he insrumen for he growh rae in mean income from he surveys, under he assumpion ha measuremen errors in he wo daa sources are uncorrelaed. (China s naional accouns have been based largely on adminisraive daa.) Boh he OLS and IVE resuls in Table 6 confirm sudies for oher counries indicaing ha periods of higher economic growh ended o be associaed wih higher raes of povery reducion. 18 The implied elasiciy of povery reducion o growh is over hree for he headcoun index and around four for he povery gap measures. The IVE elasiciy is similar o ha for OLS, suggesing ha he aforemenioned problem of correlaed measuremen errors is no a serious source of bias. Noice ha he inerceps are posiive and significan in Table 6. Our OLS resuls imply ha a zero growh, he headcoun index would have risen a 11% per year (16% for PG and 19% for SPG). So falling povery in China has been he ne oucome of wo srong bu opposing forced: rising inequaliy and posiive growh. 17 The correlograms of he firs differences of he hree log povery measures shows no significan auocorrelaions. While he firs difference of he log mean sill shows mild posiive serial correlaion, he residuals of he regression of he log difference of he povery measure on he on he log difference of he mean shows no sign of serial correlaion. 18 Evidence on his poin for oher counries can be found in Ravallion (2001). 13
Table 6 also gives regressions including he change in inequaliy. I is unsurprising ha his has a srong posiive effec on povery. (The regression can be viewed as a log-linear approximaion of he underlying mahemaical relaionship beween a povery measure and he mean and he Lorenz curve on which ha measure is based.) Wha is more ineresing is ha here is evidence of a srong ime rend in he impac of inequaliy, as indicaed by he posiive ineracion effec beween ime and he change in inequaliy. Povery in China has become more responsive o inequaliy over his period. Indeed, he size of he ineracion effec in Table 6 suggess ha he elasiciy of povery o inequaliy was virually zero around 1980, bu he elasiciy rose o 3.7 in 2001 for he headcoun index and 5-6 for he povery gap measures. The paern of growh. While China s economic growh has clearly played an imporan role in he counry s long-erm success agains absolue povery, he daa sugges ha he secoral composiion of growh has maered. 19 This can be seen clearly if we decompose he growh raes by income componens. Consider firs he urban-rural decomposiion for he survey mean. The overall mean a dae is r r u u µ = n µ + n µ where i µ is he mean for secor i=r,u for rural and urban areas. I is readily verified ha he growh rae in he overall mean can be wrien as: r r u ln µ = s ln µ + s ln µ u + [ s r u r s ( n / n u )] ln n r where i i i s = n µ / µ (for i=r,u) is he income share. We can hus wrie down he following regression for esing wheher he composiion of growh maers: r r r u u u n r u n r (2) ln P = η 0 + η s ln µ + η s ln µ + η ( s s. ) ln n u + ε n r 19 The lieraure has ofen emphasized he imporance of he secoral composiion of growh o povery reducion; for an overview of he argumens and evidence see Lipon and Ravallion (1995). The following analysis follows he mehods inroduced in Ravallion and Da (1996), which found ha he composiion of growh maered o povery reducion in India. 14
where ε is a whie-noise error erm. The moivaion for wriing he regression his way is i eviden when one noes ha if he η (i=r,u,n) parameers are he same hen equaion (2) collapses o a simple regression of he rae of povery reducion on he rae of growh ( ln µ ). i Thus esing H 0 : η = η for all i ells us wheher he urban-rural composiion of growh maers. Noe ha his regression decomposiion is based on somewha differen assumpions o ha used in he analyic decomposiion in equaion (1) based on he assumpion ha urbanizaion follows a Kuznes process. In paricular, any sysemaic wihin-secor disribuional effecs of urbanizaion would now change he measured conribuion o povery. i Table 7 gives he resuls for all hree povery measures. The null hypohesis ha η = η for all i is convincingly rejeced in all hree cases. Furhermore, we canno rejec he null ha only he growh rae of rural incomes maers. A second decomposiion is possible for GDP per capia which we can divide ino n sources o esimae a es equaion of he following form: (3) ln P = π 0 + π isi lnyi + ε n i=1 where Y i is GDP per capia from source i, i s = Y / Y is he source s share, and ε is a whienoise error erm. In he special case in which π i = π for i=1,..,n, equaion (3) collapses o a simple regression of he rae of povery reducion on he rae of GDP growh ( lny ). i Wih only 21 observaions over ime here are limis on how far we can decompose GDP. We used a sandard classificaion of is origins, namely primary (mainly agriculure), secondary (manufacuring and consrucion) and eriary (services and rade). Figure 2 shows how he shares of hese secors evolved over ime. The primary secor s share fell from 15
30% in 1980 o 15% in 2001, hough no mononically. Almos all of his decline was made up for by an increase in he eriary-secor share; he share of secondary secor has no overall rend, bu has been rising in he 1990s. However, i should no be forgoen ha hese are highly aggregaed GDP componens; he near saionariy of he secondary secor share over he whole period reflecs he ne effec of boh conracing and expanding manufacuring sub-secors. Table 8 gives he esimaed es equaions based on (3) for H and PG, while Table 9 gives he resuls for SPG (for which a slighly differen specificaion is called for, as we will see). We find ha he secoral composiion of growh maers o he rae of povery reducion. The primary secor has far higher impac (by a facor of abou four) han eiher he secondary or eriary secors. The impacs of he laer wo secors are similar (and we canno rejec he null ha hey have he same impac). For SPG we canno rejec he null ha only he primary secor maers and Table 9 gives he resriced model for his case. Our finding ha he secoral composiion of growh maers echoes he findings of Ravallion and Da (1996) for India, hough eriary secor growh was relaively more imporan in India han we find for China. These aggregae resuls do no ell us abou he source of he povery-reducing impac of primary secor growh. Wih a relaively equiable disribuion of access o agriculural land and higher incidence and deph of povery in rural areas i is plausible ha agriculural growh will bring large gains o he poor. There is evidence for China ha his may also involve exernal effecs a he farm-household level. One imporan source of exernaliies in rural developmen is he composiion of economic aciviy locally. In poor areas of souhwes China, Ravallion (2005) finds ha he composiion of local economic aciviy has non-negligible impacs on consumpion growh a he household level. There are significan posiive effecs of local economic aciviy in a given secor on income growh from ha secor. And here are a number 16
of significan cross-effecs, noably from farming o cerain nonfarm aciviies. The secor ha maers mos as a generaor of posiive exernaliies urns ou o be agriculure (Ravallion, 2005). A naural counerfacual for measuring he conribuion of he secoral composiion of growh is he rae of povery reducion if all hree secors had grown a he same rae. We call his balanced growh. Then he secor shares of GDP in 1981 would have remained consan over ime, wih 32% of GDP originaing in he primary secor. From Table 8, he expeced rae of change in he headcoun index, condiional on he overall GDP growh rae, would hen have been 0.155 4.039 lny (where 4.039=0.32 x 7.852 + 0.68 x 2.245, based on Table 8). For he same GDP growh rae, he mean rae of povery reducion would hen have been 16.3% per year, raher han 9.5%. Insead of 20 years o bring he headcoun index down from 53% o 8% i would have aken abou 10 years. This calculaion would be decepive if he same overall growh rae would no have been possible wih balanced growh. There may well be a rade off, arising from limied subsiuion possibiliies in producion and rigidiies in some aggregae facor supplies; or he rade-off could sem from aggregae fiscal consrains facing he governmen in supplying key public infrasrucure inpus o privae producion. I is suggesive in his respec ha here is a correlaion of 0.414 beween he wo growh componens idenified from Table 8, s1 lny1 and s2 lny2 + s3 lny3. However, his correlaion is only significan a he 6% level, and i is clear ha here were sub-periods (1983-84, 1987-88 and 1994-96) in which boh primary secor growh and combined growh in he secondary and eriary secors were boh above average. So hese daa do no offer srong suppor for he view ha more balanced growh would have mean lower growh. 17
We have seen ha growh accouns for a sizeable share of he variance in raes of povery reducion. When measured by survey means, growh accouns for abou half of he variance; when measured from he naional accouns, i accouns for one fifh of he variance. However, he share of variance explained is doubled when we allow for he secoral composiion of growh, wih he primary secor emerging as far more imporan han he secondary or eriary secors (hough again here may well be heerogeneiy wihin hese broad secors). 5. Inequaliy and growh The lieraure has provided numerous parial picures of inequaliy in China, focusing on sub-periods (such as in Khan and Riskin, 1998, who used wo surveys spanning 1988-1995; he longes we know of is for 1985-95, in Kanbur and Zhang, 1999) and/or seleced provinces (such as Tsui, 1998) or beween urban and rural areas (as sudied by Yang, 1999). As we will see, hese parial picures can be decepive. We begin by considering inequaliy beween urban and rural secors; hen wihin secors and in he aggregae. Finally we urn o he relaionship beween inequaliy and growh. Inequaliy beween urban and rural areas. Figure 3 gives he raio of he urban mean income o he rural mean. Wihou our adjusmen for he cos-of-living difference, here is a significan posiive rend in he raio of urban o rural mean income. The regression coefficien of he raio of means on ime is 0.047, wih a -raio of 3.12 (his is correced for serial correlaion in he error erm). However, when using he COL-adjused means he coefficien drops o 0.021 and is no significanly differen from zero a he 5% level (=1.79). Noice ha here are sill some relaively long sub-period rends in which he raio of he urban o he rural mean was rising, including he period 1986 o 1994. The raio of means fell sharply in he mid- 1990s, hough re-bounding in he lae 1990s. 18
There is a rend increase in absolue inequaliy beween urban and rural areas. This is measured by he difference beween he urban and rural means, as in Figure 4. The rend in he absolue difference (again calculaed as he regression coefficien on ime) is 0.044 per year, wih a -raio of 3.40 (again correced for serial correlaion in he error erm). However, here oo here were periods ha wen agains he rend, including in he early 1980s and mid-1990s. Inequaliy wihin urban and rural areas. We find rend increases in inequaliy wihin boh secors, hough rural inequaliy fell in he early 1980s and again in he mid-1990s (Table 10). In marked conras o mos developing counries, relaive income inequaliy is higher in rural areas, hough he rae of increase in inequaliy is higher in urban areas; i looks likely ha he paern in oher developing counries will emerge in he fuure. Noice also ha here appears o be a common facor in he changes in urban and rural inequaliy; here is a correlaion of 0.69 beween he firs difference in he log rural Gini index and ha in he log urban index. We will reurn o his poin. Overall inequaliy. In forming he naional Gini index in Table 10 we have incorporaed our urban-rural cos of living adjusmen. The able also gives he unadjused esimaes (as found in pas work). As one would expec, naional inequaliy is higher han inequaliy wihin eiher urban or rural areas. And allowing for he higher cos-of-living in urban areas reduces measured inequaliy. By 2001, he COL adjusmen brings he overall Gini index down by over five percenage poins. While a rend increase in naional inequaliy is eviden (Figure 5), he increase is no found in all sub-periods: inequaliy fell in he early 1980s and he mid-1990s. The rise in absolue inequaliy is even more pronounced. Figure 6 gives he absolue Gini index, in which income differences are normalized by a fixed mean (for which we use he 1990 naional mean). (The absolue Gini is no bounded above by uniy.) I is noable ha while 19
relaive inequaliy is higher in rural areas han urban areas, his reverses for absolue inequaliy, which is higher in urban areas a all daes. Rising inequaliy grealy dampened he impac of growh on povery. On re-calculaing our rural povery measures for 2001 using he 2001 rural mean applied o he 1981 Lorenz curve, we find ha he incidence of povery in rural areas (by our upper line) would have fallen o 2.04% in 2001, insead of 12.5%. The rural PG would have fallen o 0.70% (insead of 3.32%) while he SPG would have been 0.16 (insead of 1.21). Repeaing he same calculaions for urban areas, povery would have virually vanished. Bu even wih he same urban povery measures for 2001 (so leing inequaliy wihin urban areas rise as i acually did), wihou he rise in rural inequaliy he naional incidence of povery would have fallen o 1.5%. This begs he quesion of wheher he same growh rae would have been possible wihou higher inequaliy. If de-conrolling China s economy pu upward pressure on inequaliy hen we would be underesimaing he level of povery in 2001 ha would have been observed wihou he rise in inequaliy, because he lower inequaliy would have come wih a lower mean. Inequaliy has cerainly risen over ime, in line wih mean income. The regression coefficien of he Gini index on GDP per capia has a -raio of 9.22 (a correlaion coefficien of 0.90). Bu his correlaion could well be spurious (in he Granger-Newbold sense); indeed, he Durbin-Wason saisic is 0.45, indicaing srong residual auo-correlaion. This is no surprising since boh inequaliy and mean income have srong rends, hough possibly associaed wih differen causaive facors. A beer es is o compare he growh raes wih changes in inequaliy over ime. 20 Then i becomes far less clear ha higher inequaliy has been he price of China s growh. The 20 There is no sign of serial correlaion in he residuals from he regression of he firs difference of log Gini on log GDP. So he (firs-order) differenced specificaion is defensible. 20
correlaion beween he growh rae of GDP and log difference in he Gini index is 0.05. Now he regression coefficien has a -raio of only 0.22 (and a Durbin-Wason of 1.75). This es does no sugges ha higher growh per se mean a seeper rise in inequaliy. The same conclusion is reached if we divide he series ino four sub-periods according o wheher inequaliy was rising or falling, as in Table 11. If here was an aggregae growh-equiy rade-off hen we would expec o see higher growh in he period in which inequaliy was rising. This is no he case; indeed; he wo periods wih highes growh in household income per capia were when inequaliy was falling. No clear paern emerges for GDP growh. These calculaions do no reveal any sign of a shor-erm rade off beween growh and equiy. Possibly hese ime periods are oo shor o capure he effec. Anoher es is o see wheher he provinces ha had higher growh raes saw higher increases in inequaliy; we reurn o ha quesion in secion 7. Inequaliy and he paern of growh. Wha role has he secoral composiion of growh played in he evoluion of inequaliy? 21 Repeaing our es based on equaion (2) bu his ime using changes in he log Gini index as he dependen variable we find srong evidence ha he evoluion of he Gini index is correlaed wih he urban-rural composiion of growh: (4) ln G r r u = 0.020 0.511 s ln µ + 0.466 s ln µ 0.366[ s s ( n / n )] ln n + ˆ ε (1.285) ( 4.399) (2.651) u ( 0.208) R 2 =0.622; n=20 There is no sign of a populaion shif effec on aggregae inequaliy and he rural and urban r + u coefficiens add up o abou zero. The join resricions η η = 0 and η = 0 (borrowing he r u r n u r G 21 The lieraure on disribuion and developmen has emphasized he imporance of he secoral composiion of growh (see, for example, Lipon and Ravallion, 1995; Ravallion and Da, 1996; Bourguignon and Morrison, 1998). 21
noaion of equaion 2) pass comforably, giving he rae of change in inequaliy as an increasing funcion of he difference in (share-weighed) growh raes beween urban and rural areas: (5) u u ln G = 0.015+ 0.499( s ln µ s ln µ ) + ˆ ε R 2 =0.619; n=20 (2.507) (5.405) r r G Looking insead a he componens of GDP by origin, one finds ha primary secor growh has been associaed wih lower inequaliy overall, while here is no correlaion wih growh in eiher he secondary or eriary secors (Table 12). I is also clear ha an imporan channel hrough which primary secor growh has been inequaliy reducing is is effec on he urban-rural income dispariy. There is a negaive correlaion beween primary secor growh and he changes in he (log) raio of urban o rural mean income; he correlaion is sronges if one lags primary secor growh by one period, giving he following OLS regression for he log of he u raio of he urban mean ( Y ) o he rural mean ( Y ): r (6) u r ln( Y / Y ) = 0.044 0.969 lny1 1 (2.657) ( 3.802) + εˆ Y R 2 =0.437; n=20 Table 13 gives regressions of he log difference of he Gini index by urban and rural areas on he growh raes (log differences) of boh rural and urban mean incomes. We find ha higher rural incomes were inequaliy reducing naionally. This happened in hree ways. Firsly, rural economic growh clearly reduced inequaliy beween urban and rural areas; secondly i reduced inequaliy wihin rural areas; hirdly, rural economic growh also reduced inequaliy wihin urban areas. As in oher developing counries, he forunes of China s urban poor are likely o be linked o rural economic growh hrough migraion, ransfers and rade. These linkages can readily enail disribuional effecs of rural economic growh on urban areas, given ha i is more likely o be he urban poor (raher han urban non-poor) who gain from rural economic growh (such as by reduced need for remiances back o rural areas). However, we also find a srong and 22
roughly offseing lagged growh effec in rural areas, suggesing ha i is he posiive (negaive) shocks o rural incomes ha reduce (increase) inequaliy. This could arise from a shor-erm effec of rural income changes on migraion and remiances. Growh in urban incomes is inequaliy increasing in he aggregae and wihin urban areas, bu no rural areas. This echoes resuls of Ravallion and Da (1996) for India. Wha hen is driving he co-movemen of inequaliy beween urban and rural areas? The answer appears o lie in he role of rural incomes. As we have seen, for boh urban and rural areas, he firs differences in he log Gini index are negaively correlaed wih rural income growh. The regression residuals for he changes in rural inequaliy in Table 13 show no significan correlaion wih hose for urban inequaliy, indicaing ha rural economic growh is he key common facor. 6. Economy-wide policies and povery In principle, many policies could maer o he paern of growh and (hence) rae of povery reducion. Here we focus on hose ha have received mos aenion in he lieraure, namely agrarian reform, agriculural pricing, macroeconomic sabilizaion, public spending and openness o exernal rade. Agrarian reform. The early 1980s saw high growh in primary secor oupu and rapid rural povery reducion in he wake of de-collecivizaion and he privaizaion of land-use righs under he household responsibiliy sysem. (Agriculural land had previously been farmed by organized brigades, in which all members shared he oupu more-or-less equally.) Since his was a one-off even across he whole counry, we canno es is explanaory power. However, he lieraure has poined o he imporance of hese reforms in simulaing rural economic growh a he early sages of China s ransiion (Fan, 1991; Lin, 1992; Chow, 2002). And (as we 23
have seen) rural economic growh was key o falling povery in ha period. I would no be unreasonable o presume ha he agrarian reforms around 1980 accouned for he bulk of rural povery reducion in he firs half of he 1980s, which (as we have also seen) accouned for roughly hree-quarers of he oal decline in he naional povery rae over 1981-2001. Agriculural pricing policies. Unil recenly, he governmen has operaed a domesic foodgrain procuremen policy by which farmers are obliged o sell fixed quoas o he governmen a prices ha are ypically below he local marke price. For some farmers his is an infra-marginal ax, given ha hey produce more foodgrains han heir assigned quoa; for ohers i will affec producion decisions a he margin. I has clearly been unpopular wih farmers (see, for example, Kung s, 1995, survey of Chinese farmers aiudes.) Reducing his ax by raising procuremen prices appears o have simulaed primary secor GDP. We find a srong correlaion beween he growh rae of primary secor oupu and he real procuremen price of foodgrains (nominal price deflaed by he rural CPI); see Figure 7. There is boh a curren and lagged effec; an OLS regression of he growh rae in primary secor GDP on he curren and lagged raes of change in he real procuremen price (PP) gives: (7) lny = 0.045+ 0.210 ln PP + 0.315 ln PP + 1 εˆ 1 R 2 =0.590; D-W=2.60; n=19 (5.937) (2.152) (3.154) I is no hen surprising ha we find a srong negaive correlaion beween he changes in he governmen s procuremen price and changes in inequaliy; Figure 8 plos he wo series (lagging he procuremen price change by one year); he simple correlaion coefficien is 0.609. Cuing his ax has been an effecive shor-erm policy agains povery. 22 The regression coefficien of ln H on ln PP 1 is 1.060 (-raio= 3.043). The channel for his effec was 22 This is only one of many axes and ransfers wih bearing on income disribuion in China. I would be of ineres o see a complee accouning of he incidence of axes and ransfers. This does no appear o exis in he lieraure a he ime of wriing. 24
clearly hrough agriculural incomes. (The regression coefficien changes lile if one adds conrols for secondary and eriary secor growh.) The elasiciies of naional povery o procuremen price changes are even higher for he povery gap indices; for PG he coefficien is 1.433 (= 2.929) and for SPG i is 1.708 (= 3.134). Macroeconomic sabilizaion. There were wo inflaionary periods in China, 1988-89 and 1994-95. Povery rose in he former period and fell in he laer. However, when one conrols for procuremen price changes we find an adverse effec of lagged changes in he rae of inflaion for all hree povery measures; for he headcoun index: 2 (8) ln H = 0.082 1.257 ln PP 1 + 1.249 lncpi 1 + εˆ ( 3.058) ( 3.688) (2.493) R 2 =0.491; D-W=1.86; n=19 where CPI is he rural CPI. (The regression was similar for he oher povery measures.) The srong adverse effec of inflaion echoes findings elsewhere. 23 There are also srong (pro-poor) disribuional effecs of procuremen and inflaionary shocks as can be seen by he fac ha boh regressors in (8) remain significan if one conrols for he log difference in overall mean income: 2 (9) ln H = 0.060 1.040 ln PP 1 + 0.882 ln CPI 1 2.335 lny 0.739 ˆ ε 1 + ˆ ν (3.791) ( 8.049) (4.651) ( 9.843) ( 3.775) R 2 =0.907; D-W=2.28; n=18 Governmen spending. Fiscal expansions ended o reduce povery; when he change in log real public spending is added o equaion (8), is coefficien is 0.737 (= 2.095). 24 However, adding lny rendered he public spending variable insignifican (he coefficien dropped o 0.063, =0.325). We also ried wo decomposiions of public spending, namely agriculure and non-agriculure and cenral and local. We found no evidence ha governmen 23 Including Easerly and Fischer (2001) and Dollar and Kraay (2002) boh using cross-counry daa, and Da and Ravallion (1998) using daa for India. 24 On including he curren and lagged values separaely he homogeneiy resricion passed comforably. The public spending daa are from NBS (1996, 2003) and include all ypes of spending a boh cenral and local levels. The rural CPI was used as he deflaor. 25
spending on agriculure had any greaer povery reducing impac han oher spending; his was esed by adding he (share-weighed) change in log real public spending on agriculure as an addiional regressor. The share of spending on agriculure was generally low (around 6-7% unil he mid-1990s, falling o 5% afer ha), so i may well be difficul o pick up is impac (even when share-weighed). However, here was a srong indicaion ha spending by provincial and local governmens was more effecive in reducing povery han spending by he cener. 25 Indeed, we could no rejec he null ha cenral governmen spending had no impac, giving he model: 2 GL (10) ln H = 0.003 1.601 ln PP 1 + 1.064 ln CPI 1 1.319 s ln GL 0.502 ˆ ε 1 + ˆ ν (0.106) ( 6.201) (2.889) ( 3.988) ( 1.986) R 2 =0.640; D-W=1.681; n=19 where L s is he share of local spending in oal spending and resuls were similar wihou share-weighing; he coefficien on GL is real local spending. (The ln GL was 0.676, = 2.494.) Changes in log cenral governmen spending were insignifican when added o his regression (a regression coefficien of 0.100 wih a -raio of 0.486; oher coefficiens were affeced lile). Here oo, here is no sign of a disribuional effec of public spending; if we add s lngl o L equaion (9) (conrolling for changes in he log mean) hen is coefficien drops o 0.305 and is no significanly differen from zero (= 1.271). Public spending has reduced absolue povery bu saisically we can rejec he null ha is effec has been roughly disribuion-neural. 26 Exernal rade. I has been claimed ha China s exernal rade reforms helped reduce povery (World Bank, 2002; Dollar, 2004). However, he iming does no sugges ha exernal rade expansion is a plausible candidae for explaining China s progress agains povery. 25 Local spending accouned for 65.3% of he oal in 2001; in 1980 i accouned for 45.7%. 26 Similarly, if we re-esimae (10) replacing he headcoun index by he Gini index, we find ha ln GL is highly insignifican while he oher wo variables remain significan. 26