结构转型和产业升级外文文献

The impacts of structural transformation and industrial upgrading on regional inequality in China Tsun Se CHEONG Yanrui WU Business School University of Western Australia 35 Stirling Highway Perth WA 6009 Australia a r t i c l ei n f oa b s t r a c t Article history Received 27 February 2014 Received in revised form 23 September 2014 Accepted 23 September 2014 Available online 2 October 2014 China has achieved unprecedented success in economic growth since the initiation of economic reforms The high growth could partly be attributed to the successes in structural transformation of the economy and industrial upgrading of the manufacturing sector toward high value added products However regional inequality in China has increased considerably behind the scenes In order to have sustainable economic growth it is thus crucial to investigate the impacts of both structural transformation and industrial upgrading on regional inequality This paper con tributes to the literature by employing a database compiled at the county level Decompositions are performed for different spatial groupings so as to provide a clear view of evolution of regional inequality In addition the contributions of the major industries to inequality in industrialization are examined by using another database of value added compiled at the provincial level The results may have important policy implications for the formulation of a comprehensive and coherent strategy in managing inequality while promoting structural transformation and indus trial upgrading 2014 Elsevier Inc All rights reserved JEL classifi cation D63 O10 O14 O15 O53 Keywords China Inequality Industrialization Structural transformation Industrial upgrading 1 Introduction Followingtheinitiationofeconomicreformin1978 Chinahasexperiencedrapidgrowthandisoftencitedasa miracle ineconomic development Grossdomesticproduct GDP increasedfrom365billionYuanin1978to51 89trillionYuanin2012 whileGDPpercapita increased from 381 Yuan to 38 420 Yuan in that period State Statistical Bureau 2013 Of this unprecedented success Yu 2012 sug gests that the rapid economic growth can be attributed to the successes in structural transformation and industrial upgrading The strong economic growth not only has benefi ted China but also has driven the economic growth of nearby countries Saari 2007 Moreover China s economic growth has contributed signifi cantly to the decline of global inequality Hung Goh Luo Alesina Dutt Muller trigger social tensions and pose a clear and present danger to social China Economic Review 31 2014 339 350 Corresponding author Tel 61 8 64885639 E mail addresses james t s cheong T S Cheong yanrui wu uwa edu au Y Wu http dx doi org 10 1016 j chieco 2014 09 007 1043 951X 2014 Elsevier Inc All rights reserved Contents lists available at ScienceDirect China Economic Review andpolitical stabilityand therefore totheverysustainability ofthegrowth process itself Thisargumentissupported by thefactthat thenumber of mass incidents in China includingprotests demonstrationsand clashes with police increased from 10 000 in 1993 to 87 000 in 2005 Wen 2007 Similarly Wang and Hu 1999 suggest that inequality may lead to economic and social instability and may even affectthe unityof China Cheongand Wu inpress alsofi ndthat there is a positive correlation betweenregional inequality and crime rates in China Therefore it calls for an in depth study on regional inequality so that policies can be formulated to mitigate inequality In fact the problem of regional inequality has attracted the attention of researchers from different disciplines and many studies have been carried out to examine regional inequality in China However most of the studies have been based on provincial level data while only a few studies have investigated inequality using county level data Cheong 2012b The main objective of this paper is to fi ll the void in the literature and provide a thorough examination of the impacts of structural transformation on regional inequality in China by using a county level database In the second part of this study the focus will turn to industrialization itself and thedisparity in industrialupgradingwill be evaluated through an examination of value added of the major industries Decompo sitions of inequality are performed in the vertical and horizontal directions Decompositions are fi rst applied vertically to different groupings at various spatial levels while another set of decomposition is applied horizontally so as to determine the contributions of the different industrial sectors Thispaperisstructuredasfollows Section2presentsareviewoftheliteratureandotherrelevantinformation onindustrialization and industrial upgrading Section 3 provides a discussion of the research methods Section 4 describes data issues Section 5 presents the fi ndings and discussions Further analysis at the industrial sub sector level is reported in Section 6 while Section 7 concludes 2 Industrialization and industrial upgrading in China ItiswellknownthatamajorfeatureofChina seconomicdevelopmentisthedramaticchangeinsectoralcompositionofGDPdueto structuraltransformation ThestructuraltransformnotonlyhasradicallyalteredtheeconomiclandscapeofChina butalsohasledtoan increase in regional inequality Cheong and Wu 2013a employ generalized method of moments GMM estimator in their analysis and they fi nd that industrialization and tertiary industry development both exert positive effects on regional inequality in China Basically all the economic activities in China can be categorized into three strata of industries namely the primary industry which refers to agriculture forestry animal husbandry and fi shery and services in support of these industries the secondary industry which referstominingandquarrying manufacturing productionandsupplyofelectricity waterandgas andconstruction andthetertiaryin dustry which refers to all other economic activities not included in the primary or secondary industries State Statistical Bureau 2013 Since 1978 the percentage composition of the primary industry has declined from 28 2 to 10 1 in 2012 while the share of the secondary industry has remained more or less the same being 47 9 in 1978 and 45 3 in 2012 The percentage of tertiary industry increased substantially from 23 9 in 1978 to 44 6 State Statistical Bureau 2013 An enormous reallocation of labor from primary sectortosecondaryandtertiarysectorscanalsobeobserved Thepercentageofemployedpersonsintheprimarysectordeclinedfrom 70 5 in 1978 toonly 33 6 in 2012 The change is sodramatic that thepercentageoftheprimary sector fell more than half of it initial value in the reform era By contrast the percentage of the secondary sector increased from 17 3 to 30 3 whereas the percentage of thetertiary sector increasedfrom 12 2 to36 1 State Statistical Bureau 2013 Although thestructuraltransformation in Chinawas verysuccessfuland led toconsiderableimprovementof thelivingstandards of its people however inequalityalsoincreasedsubstan tially in this period It is worth noting that Huang Kuo and Kao 2003 show that development in the secondary sector is the largest contributor to regional inequality in China Therefore our study mainly focuses on the impacts of industrialization on inequality The neoclassical model of Solow 1956 and Swan 1956 predicts that conditional convergence is possible and regional inequality will be reduced in the long run as the poor regions tend to grow faster than the rich regions However according toKuznets 1955 in equalityalwaysincreaseswithindustrializationintheearlystagesofeconomicdevelopment Hesuggeststhat iftheincomedistribution is more unequal for the non agricultural sector than for the agricultural sector or if the per capita income differential among the two sectors increases or if both conditions are present then the rise over time in the relative weight of the non agricultural sector can exac erbate income inequality considerably This evolutioncanbe explained bytheconcentrationof savings andthestructuralshiftfrom the agricultural sector to the non agricultural sector Therefore it is often argued that an increase in regional inequality is inevitable in pro moting economic growth through structural transformation and so it is necessary to bear the pain of inequality in the process Theneweconomicgeographytheory whichtakestheeffectsofincreasingreturnstoscale geography economiesofscale imperfect competition localized spillovers product differentiation transportation costs factor mobility intermediate inputs and other elements into consideration also suggests that regional inequality can be affected by many agglomeration forces for example see the best known works of Fujita Krugman Krugman 1991a 1991b Krugman Huang et al 2003 Kanbur Pradhan 2009 Rozelle 1994 1996 Tsui 1996 Tsui 2007 Wan 2004 Yang 2002 Yao 1997 Rozelle 1994 points out that the policies that helped agriculture could reduce inequality whilethosethatpromotedruralindustrializationwouldincreaseinequality Inanotherarticle Rozelle 1996 claimsthattheincrease in inequality could be attributed to the expansion of the industrial sector By using factor decomposition Tsui 1996 fi nds that the 340T S Cheong Y Wu China Economic Review 31 2014 339 350 industrial sector has played a central role in the rise of regional inequality Golley 2002 suggests that industrial development has occurred at a very uneven pace across the provinces in China leading to industrial agglomeration which has been accompanied by an increase of regional disparities in gross regional product GRP per capita and growth rates Yang 2002 suggests that in thepre reformperiod massiveamountsof resourceswereextracted fromtheagricultural sectorsoastoacceleratethepaceof indus trialization and this strategy has led to an increase in inequality in China Huang et al 2003 fi nd that unevenness in distribution of secondary industry among the provinces accounted for half of the overall inequality in China from 1991 to 2001 Kanbur and Zhang 2005 report that theincrease in the ratio of heavy industry to gross output is positively correlated with inequality especially in the period from 1952 to 1978 Tsui 2007 shows that the difference in provincial share of secondary industry sector to national total led to disparity in growth which in turn exacerbated inter provincial inequality in China Pradhan 2009 also shows that industrializa tion affected income inequality in China during 1952 2005 It should be noted that the township and village enterprise TVE sector also plays a major role in rural industrialization in China SeveralresearchersstudytheimpactsofruralindustrializationoninequalitybyexaminingtheeffectsofTVEs andtheyreportthatthe unequal development of TVEs exacerbated regional inequality in China see Wan 2004 Yao 1997 Zhang 1999 All studies mentioned above suggest that industrialization is the crux of the problem of regional inequality in China therefore the focus of this paper is mainly on industrialization Intheprocessofindustrialization itiscrucialtogothroughtheprocessofindustrialupgradingtowardhighvalue addedindustries so as to increase total output and maintain a sustainable economic growth In the beginning of the industrialization process many developingcountries would fi rst rely on light industries for example textiles and food industries The raw materials of these lightin dustries are readilyavailable from theagriculturalsector moreover theskill requirementof thelabor is not high for these industries Therefore these industries can be set up easily in the beginning of the industrialization process and many developing countries rely on these industries heavily in the fi rst stage of industrialization However with the continued improvement of human capital and technological level economic development will then reach a bottleneck In order to maintain economic growth it is thus required to undergo industrial reform and upgrading so as to move toward high value added industries A similar pattern can be observed from the industrialization in China Fig 1 shows the change in percentage composition of total value addedforthemajorindustriesfrom1993to2007 ThedatawascompiledfromtheChinaIndustrialEconomyStatisticalYearbook which provides the fi gures of value added of 20 major industries from 1993 up to 2007 It can be observed that the percentage com position of the beverage manufacturing tobacco processing and textile sectors fell in that period By contrast the high technological andhighvalue addedsectorsliketransportationequipmentmanufacturing electric equipment andmachinery aswell asinstrument and meter sectors all of them registered an increase It should be noted that the electronics and telecommunications sector had the highest growth in percentage composition it rose from 3 74 in 1993 to 9 68 in 2007 which is equivalent to an increase of 158 Chinahasreachedthestagethatsheneedstorelyonindustrialupgradingsoastoachievesustainabledevelopmentinthesecond arysector Forthatreason theChinesegovernmenthascalledforindustrialupgradingandmanypoliciesareintroducedtoencourage the low technological level and low value added industries to migrate to higher value added industries Therefore it is vital to identify the pattern of inequality in value added for the different industries This information can reveal the disparity in industrial upgradingin Chinaand it can aid in the formulation of a comprehensive and coherentstrategyin managinginequality while promot ingindustrialupgrading However informationonthecontributionofeachindividualindustrialsectortothedisparityinvalue added across the provinces is not available in the literature It is very unfortunately that even though the development of the high value added industries and its distribution across the provinces are crucial components of the industrialization story in China but as yet no decomposition of inequality has been carried out to examine the impacts 3 Methods Although there are many different indicators for inequality measurement the most common one is the Gini coeffi cient The Gini coeffi cient has several merits it satisfi es both the Pigou Dalton condition and the property of income zero homogeneity The Pigou Daltonprinciplesuggeststhatifthereisatransferofincomefroma richentitytoapoorentity then itshouldresultinadecline of the inequality indicator so long as the transfer does not reverse the ranking of the two in the overall income distribution The property of income zero homogeneity suggests that the value of the inequality measurement should remain unchanged when there is a scalar change of the whole income distribution The calculationof Ginicoeffi cientis based ontheLorenzcurve whichplots the cumulativeshareof incomeagainstthecumulative shareof populationfromlowesttohighestincomes TheGinicoeffi cientcan becalculatedastheratiooftheareathatliesbetween the uniform distribution line that is the 45 degree line of the Lorenz curve and the Lorenz curve over the total area under the uniform distributionline TheGinicoeffi cientcanbe calculated by differentformulae Oneformula of thepopulation weighted Ginicoeffi cient is in the form X i X j yi yj 2 ni N nj N 1 where yiand yjare the income per capita in region i and region j respectively niand njare the population in region i and region j respectively N is the total population in all the regions and i yini N Tsui 1996 341T S Cheong Y Wu China Economic Review 31 2014 339 350 The value of the Gini coeffi cient ranges from 0 to 1 The value of 1 corresponds to perfect income inequality while the value of 0 corresponds to perfect income equality The Gini coeffi cient can be decomposed into various income sources so as to work out the contribution of each income source to total inequality It is worth noting that there are many different ways to decompose the Gini coeffi cient from game theory Hyndman Bashtannyk Villaverde Wang 2011 to matrix calculation He 2010 However the approach suggested by Yao 1999 is adopted in this paper because of its simplicity and accuracy G XS s 1wsCs 2 whereGistheGinicoeffi cient wsistheincomeshareofsourcesinthetotalincomeandCs istheconcentrationcoeffi cientsoftheincome sources SotheoverallGinicoeffi cientcanbeviewedas aweightedsumofconcentrationcoeffi cientswhichcanbecalculatedby Cs 1 Xm j 1Pj 2Qsj wsj 3 whereQsj l 1 j wsl Pjisthepopulationshareintotalpopulation forregion j andwsjistheshareofincomeforregionjintotalsource incomes ItshouldbenotedthatbothwsjandPjshouldbesortedinascendingorderoftotalincomepercapitainthecalculationofCs for details interestedreaderpleaserefertoYao 1999 BasedonEqs 2 and 3 thecontributionofeachindividualsourceincomecanthen be calculated as Contribution of source income s wsCs G 4 0 2 4 6 8 10 12 14 Food Processing Food manufacturing Beverage manufacturing Tobacco processing Tex les Papermaking and paper products Petroleum processing and coking products Chemical raw materials and chemical products Medical and pharmaceu cal products Chemical fi bres Non metallic minerals Smel ng and processing of ferrous metals Smel ng and processing of nonferrous metals Metal products General equipment manufacturing Special purpose equipment manufacturing Transporta on equipment manufacturing Electric equipment and machinery Electronics and telecommunica ons Instruments and meters Value added Percentage in 1993 Value added Percentage in 2007 Fig 1 Percentage of value added for the major industries in 1993 and 2007 Source Authors own calculation using data from the China Industrial Economy Statistical Yearbook 1994 2008 342T S Cheong Y Wu China Economic Review 31 2014 339 350 4 Data Twodatabasesareusedinthisstudy Thefi rstoneisacounty leveldatabasewhich isusedindecompositionofinequalityinterms of GRP per capita by three strata of industries namely the primary secondary and tertiary industries The analysis result of this databasecanshowthecontributionsofthethreeindustries tooverall inequalityamongthecounty level units therefore itcan reveal the impacts of structu