The Effects of Rural Infrastructure Development on Agricultural. Production Technical Efficiency: Evidence from the Data of Second

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1 The Effects of Rural Infrastructure Development on Agrcultural Producton Techncal Effcency: Evdence from the Data of Second Natonal Agrcultural Census of Chna Zongzhang L 1, 2 and Xaomn Lu 1 1. School of Economcs and Management, South Chna Agrcultural Unversty 2. School of Economcs and Commerce, South Chna Unversty of Technology Contrbuted Paper prepared for presentaton at the Internatonal Assocaton of Agrcultural Economsts Conference, Bejng, Chna, August 16-22, 2009 Copyrght 2009 by Zongzhang L and Xaomn Lu. All rghts reserved. Readers may make verbatm copes of ths document for non-commercal purposes by any means, provded that ths copyrght notce appears on all such copes. Zongzhang L: Emal: Lzzstat@scau.edu.cn. Address: School of Economcs and Management, South Chna Agrcultural Unversty, Guangzhou , Chna. Xaomn Lu: Emal: luxaomnd@sna.com. Address: School of Economcs and Management, South Chna Agrcultural Unversty, Guangzhou , Chna. 1

2 The Effects of Rural Infrastructure Development on Agrcultural Producton Techncal Effcency: Evdence from the Data of Second Natonal Agrcultural Census of Chna ABSTRACT Ths paper studes the effects of rural nfrastructure development on agrcultural producton techncal effcency, usng data from the second agrcultural census of Chna. Employng Data Envelopment Analyss, ths paper frst estmates agrcultural producton techncal effcency of each admnstratve area of Chna. A Tobt model s then appled to study the effects on agrcultural producton techncal effcency of varous types of rural nfrastructures. Our emprcal results suggest that transportaton nfrastructure plays the most substantal postve role on techncal effcency, followed by vocatonal/techncal educaton nfrastructure, electrcty facltes and water supply systems. In addton, other potental factors nfluencng agrculture techncal effcency nclude regonal ndustral structure, mechancal ntensty, the qualty of labor and geographcal locatons. Keywords: Rural nfrastructure, agrcultural producton, techncal effcency 2

3 The Effects of Rural Infrastructure Development on Agrcultural Producton Techncal Effcency: Evdence from the Data of Second Natonal Agrcultural Census of Chna 1. Introducton The development of rural nfrastructure s hghly related to agrcultural producton. Rural nfrastructure not only provdes essental agrcultural producton condtons such as roads, telecommuncatons, powers and rrgaton systems, but also provdes educaton and medcal servces related to enhancng the qualty of rural labors such as cultural and educatonal facltes, vocatonal/techncal schools, and medcal nsttutes etc. Complete rural nfrastructure can boost regonal economc development. Announced by the Chnese State Councl on November 9, 2008 as an addtonal central government nvestment ths year, the 100 bllon yuan ($14.7 bllon) stmulus package s expected to be used n socal welfare projects, nfrastructure constructon, envronmental protecton and ndustral restructurng. The Natonal Development and Reform Commsson emphaszed that one thrd of the stmulus package around 340 bllon yuan ($5.0 bllon) wll be nvested n rural nfrastructure constructons 1. It would be of profound nterest to scholars and polcy makers to know to what extent rural nfrastructure affect the techncal effcency of agrcultural producton. Based on a representatve sample of 30 admnstratve areas n 2006, Data Envelopment Analyss (DEA) approach s used to estmate the techncal effcency of each dvson. Then, based on the regresson method, we examne whether the 1 3

4 development of nfrastructure s an explanatory factor n the varatons n techncal effcency. Ths study contrbutes to the lterature n three respects. Frst, that s the frst emprcal study of varouse knds of rural nfrastructure on agrcultural producton techncal effcency wth provncal level data n Chna. Second, ths study makes use of recently publshed natonal agrcultural census data of Chna. The Second Natonal Agrcultural Census of Chna was conducted n 2007, whch provdes an overall nvestgaton on agrculture, rural areas and farmers. Thrd, the measurement of rural nfrastructure development emphaszes the popularty rate of dfferent types of nfrastructure such as power, telecommuncaton, roads, rrgatons and schools n towns and vllages, whch s a new research angle dfferent from the prevous studes (Aschauer, 1989, Fan and Chan-Kang, 2005) focusng on the nfrastructure stock. Ths paper s organzed nto several sectons. A lterature revew and the research hypotheses of ths paper are presented n secton 2. Before analyzng the emprcal results n secton 4, the methodology and the profle of sample data are brefly dscussed n Secton 3. Fnally, the mplcatons and the major fndngs of ths paper are dscussed n Secton Lterature Revew and Research Hypotheses There are many tme-nvarant factors that affect agrcultural producton effcency. In ths paper rural nfrastructure s dentfed as beng mportant n explanng the varaton n techncal effcency n agrculture. The status and development of rural nfrastructure not only nfluence agrcultural producton and operaton modes drectly, 4

5 but also mprove the lvng standards for rural people and enhance the qualty of rural labor. Defcent rural nfrastructure may hnder agrcultural producton and nduce poor techncal performance. Rural nfrastructure s consdered to have an effect on agrcultural producton effcency and s regarded as a strategc varable. Most exstng research explores the nfluence of nfrastructure on agrcultural producton, rural growth and poverty reducton. Chen and Ln (2002) found that rural nfrastructures such as rrgatons, transportaton, storages, prmary products market and weather forecastng servce can decrease producton cost, transportaton cost, storage expenses, dealng cost and operaton rsk, and enhance producton effcency. They concluded that rural nfrastructures provde ndspensable support for the sustanable development of rural regons. Peng (2002) ponted out that country road constructon could reduce the expendture of agrcultural producton. Fang et al. (2004) revealed that the potental of agrcultural producton can be released through rural nfrastructure nvestment. The postve mpact of nfrastructure on regonal economc development s well documented n the lterature by Fan and Zhang (2004). Lttle research has been done to understand the relatonshp between rural nfrastructure and agrcultural producton techncal effcency. The objectves of ths paper are to emprcally ascertan the mpact of nfrastructure development on agrcultural producton techncal effcency and to answer a number of other questons that are relevant to the above theme. For nstance, among varous nfrastructures, whch nduce the most substantal mpact on agrcultural producton techncal effcency? 5

6 The development of nfrastructure s an mportant ndcator of a regon s economc and socal status. World Bank (1994) evaluated adequate supply of nfrastructure as an essental ngredent of productvty and growth. Most nfrastructure lterature focus on one specfc nfrastructure sector, such as telecommuncatons (Roller and Waverman, 2001), roads( Fernald,1999), rrgaton systems etc. Ths study wll gve an overall research on fve dfferent types of rural nfrastructures ncludng transportaton, telecommuncatons, water lnes, electrcty and schools, and ther mpact on agrculture techncal effcency. Therefore, t s hypotheszed that: H1: There s a postve relatonshp between the popularty rate of rural nfrastructure and agrcultural techncal effcency. To solate the relatonshp between rural nfrastructure popularty rate and agrcultural producton techncal effcency, t s essental to ntroduce nto the model other ndependent varables that are lkely to affect effcency. Among the exstng lterature, factors nfluencng agrcultural productvty ncludes mechanzaton, specalzaton, educatonal level (Chen, Huffman and Rozelle, 2006), scale operaton (Wang et al., 1996), access to credt (Chavas et al. 2005, Dong and Putterman, 1997), and locaton characterstcs (Coell, Rao, and Battese 1998). Four representatve provnce-attrbute factors are chosen to be control varables: ndustral structure, mechancal ntensty, labor qualty, and locaton. Industral structure s measured as the share of GDP. Mechancal ntensty s computed as the rato of total power of agrcultural machnery to the total number of rural people 6

7 engaged. Labor qualty s the proporton of labor wth senor secondary school educaton or above Chna s a large country and there s obvous gap between dfferent regons. Geographc locaton may affect the effcency of agrcultural producton. In ths study, admnstratve areas are classfed nto 3 regons 2, and two dummy varables are defned to represent regonal varatons. 3 Methodology and Data 3.1 Data Envelopment Analyss The non-parametrc DEA approach s used to compute the techncal effcency of each provnce and muncpalty n Chna. DEA bulds an equ-effcency fronter and an effcency envelope for each DMU. A number of studes, such as Färe et al. (1989), and Chaves & Cox (1990), have suggested that for the estmate of techncal effcency at provncal level, a non-parametrc approach appears to outperform a parametrc approach such as the stochastc fronter approach. DEA does not nvolve any pror specfcaton of producton functon or of the producton relatonshp between nputs and outputs. DEA analyzes each DMU separately and reveals those whch exhbt best practce. If a DMU's nput-output combnaton les on the best practce fronter, t s regarded as beng effcent. By contrast, f t les below the fronter, t s consdered to be neffcent. In a DEA analyss, t s generally assumed that there are n DMUs usng amounts of k dfferent nputs to produce m outputs. 2 Eastern regon ncludes Bejng, Tanjn, Laonng,Hebe, Shangha, Jangsu, Zhejang, Fujan, Shandong, Guangdong, Hanan. Central regon covers Helongjang,Shanx, Anhu, Jangx, Henan, Hube, Hunan. Western regon ncludes Inner Mongola, Guangx, Chongqng, Schuan, Guzhou, Yunnan, Tbet, Shaanx, Gansu, Qngha, Nngxa, Xnjang, Jln. 7

8 X : k n vector of observatons on DMUs' nputs x th th : the column of X s the DMU's k dfferent nputs Y : m n vector of observatons on DMUs' outputs y th th : the column of Y s the DMU's m dffer ent outputs λ : n 1 vector of constants specfyng the optmal non-negatve weghts of nputs/outputs Under the assumpton of all DMUs operatng at an optmal scale, the output-orented constant returns to scale (CRS) DEA model s as followng: Where 1 φ, and φ 1 max, φλφ, st φy + Yλ 0, x Xλ 0, λ 0, s the proportonal ncrease n outputs that could be acheved by the -th DMU, wth nput quanttes held constant. The nverse of φ defnes a TE score wth vares between zero and one. The effcency measure obtaned n CRS DEA model s referred to CRS techncal effcency, and marked as TE. However, n the real market envronment, due to mperfect competton and constrants on fnance, most DMUs can not operate at an optmal scale. Banker et al (1984) ponted out that the use of the CRS specfcaton when not all DMUs are operatng at the optmal scale wll result n measures of TE whch confounded by scale effcences, and extended the CRS DEA model to account for varable returns to scale (VRS). Mathematcally, f the condton of λ = 1 s added, then VRS are mposed and wll permt the calculaton of TE devod of these SE effects. CRS max, φλφ, st φy + Yλ 0, x Xλ 0, λ 0, λ = 1 The effcency measure obtaned n VRS DEA model s referred to pure techncal effcency, and marked as TE VRS. VRS TE s always greater than or equal to TE CRS snce 8

9 VRS model forms a convex hull of ntersectng planes whch envelope the data ponts more tghtly than the CRS concal hull. TECRS can be decomposed nto two components, one due to scale neffcency and one due to pure techncal neffcency. TE = TE SE CRS VRS When solvng the above output-orented VRS model, φ 1s the proportonal ncrease n outputs that could be acheved by the -th DMU, wth nput quanttes held constant. In ths paper VRS DEA model s used to capture the agrcultural producton techncal effcency. 3.2 Tobt Model To determne whether and to what extent the techncal effcency of each provnce can be explaned by rural nfrastructure development, we regressed the techncal effcency on the strategc varables together wth the fve control varables. As the techncal effcency ranges between zero and one, the dstrbuton of effcency s truncated above from unty. If the OLS method s appled, then the parameter estmates would be based. The usual way to overcome ths problem s to use a lmted dependent varable model. In ths context, we employed the Tobt model (Tobt, 1958). The underlyng assumpton of the OLS model s that, n terms of the populaton, techncal effcency follows a normal dstrbuton, whereas the dstrbuton of effcency estmates of our sample frms obtaned by DEA s a mxture of contnuous and dscrete dstrbuton. By contrast, the dstrbuton of techncal effcency n the stochastc fronter approach s often assumed to be skewed, for example, half-normal and truncated normal. If we want to obtan the orgnal normal dstrbuton of 9

10 techncal effcency, t s more approprate to employ the Tobt model when accountng for truncated effcency scores rangng between zero and one. Wth ths assumpton, the probablty of a DMU beng fully effcent s bascally the same as f t were extremely neffcent. The specfcaton of the equaton s as follows: TE = α0 + α1road + α2electrcty + α3telecommuncatons + α4water _ Supply + α5schools + α6industral _ Structure + α7mechancal _ Intensty + α8educatonal _ level + α Eastern + α Mddle + ε (1) 9 10 Before proceedng to dscuss the emprcal results, the data profle of ths research s brefly descrbed. 3.3 Data Ths paper bases on the 2006 data on the 30 dvsons of admnstratve areas n Chna. There are 22 provnces, 5 autonomous regons and 4 muncpaltes n Chna. Due to the mssng observatons on Tbet Autonomous Regon, a sample of 30 admnstratve regons remaned. All the data are publshed by Natonal Bureau of Statstcs of Chna and local Bureau of Statstcs, and cted from the Chna Rural Statstcal Yearbook 3, Communqué on Major Data of the Second Natonal Agrcultural Census of Chna, and local Communqué 4. The varables used n the DEA models are defned as follows: the output varable: Q s the added value of farmng, forestry, anmal husbandry, and fshery of each admnstratve area. In the agrcultural producton, the man nputs are land, labor, chemcal fertlzer, and agrcultural machnery. Four varables are chosen as nput. 3 Chna Rural Statstcal Yearbook 2007, Chna Statstcs Press, Bejng, Natonal and local Communqué on Major Data of the Second Natonal Agrcultural Census could be downloaded from the webstes from natonal or local Bureau of Statstcs of Chna. 10

11 varables. A s the total sown area, L s the number of rural persons engaged at year-end, F s the consumpton of chemcal fertlzer, and M s the total power of agrcultural machnery. The defntons of ndependent varables used n tobt model are explaned n Table 1, and the descrptons of all varables are lsted n Table 2. Varable Q = added value A = land Table 1 Defntons of Varables Descrpton of the varables added value of farmng, forestry, anmal husbandry, and fshery (n bllon yuan) total sown area ( n 10,000 hectares) L = labor Total number of rural persons engaged at year-end (n 10,000 people) F=chemcal fertlzer Consumptons of chemcal fertlzer ( n 10,000 ton) M=agrcultural machnery Road Electrcty Telecommuncaton Water_Supply Schools Industral_Structure Mechancal_Intensty Educatonal_level Eastern Mddle Total power of agrcultural machnery ( n 10,000 kw) The proporton of towns and townshps wth hghways above second class n local areas The proporton of towns and townshps fnshed grd modfcaton The proporton of vllages havng accessed to telephone The proporton of towns conductng concentrated water supply The proporton of towns and townshps constructed vocatonal/techncal schools The agrcultural share of GDP. The rato of total power of agrcultural machnery to the total number of rural people engaged. The proporton of agrcultural laborers wth educatonal level of senor secondary school or above. Dummy varable wth a value of one f the provnce/muncpalty locates n Eastern regon of Chna. Dummy varable wth a value of one f the provnce/muncpalty locates n Mddle regon of Chna. 11

12 Table 2 Descrptve Statstcs of Varables Varable Mean Standard devaton Mnmum Maxmum Q A L F M Road Electrcty Telecommuncaton Water_Supply Schools Industral_Structure Mechancal_Intensty Educatonal_level Eastern Mddle Results and Dscussons 4.1 Results from the DEA model The Data Envelopment Analyss Program (DEAP ) was used to calculate techncal effcences n producton for our output-orented VRS DEA model. DEAP estmates techncal effcences varyng between zero and one n a non-parametrc mathematcal programmng approach, and wth the VRS specfcaton, the measures of TE are devod of scale effcences. The average score of the sample regons was 71.06%. The dstrbuton of techncal effcency s as followng: 5 DEAP 2.1 was wrtten by Professor Tm Coell whch could be downloadable from 12

13 Fgure 1 Frequency Dstrbuton of Estmated Techncal Effcences 8 Hstogram of Techncal Effcency Number of observatons Techncal Effcency 4.2 Results from the Tobt Model After computng the techncal effcences, we proceeded to test the hypotheses on whether nfrastructure development enhance agrcultural producton techncal effcency, by estmatng equaton (1) usng the TOBIT method. The results of the estmaton of the equatons wth techncal effcency as the depended varable are gven n Table 3. The parameters of the Tobt model were obtaned by usng maxmum lkelhood estmators. Table 3 Estmaton results of the effects of strategc and control varables on techncal effcency of provncal data of Chna, 2006 Dependent Varable = techncal effcency Tobt Model Constant (0.735) Road ** Industral_Structure * (0.932) (0.517) Electrcty ** Mechancal_Intensty * (0.811) (0.041) Telecommuncaton Educatonal_level ** (0.832) (0.070) Water_Supply ** Eastern ** (0.233) (0.120) Schools ** Mddle (0.990) (0.091) Number of observatons 30 Log lkelhood Notes: (1) The fgures n parentheses are the estmated standard errors. (2) * denotes the sgnfcance at the 10% level; ** denotes the sgnfcance at the 5% level. 13

14 The parameter estmates for the tobt model lsted n Table 3 suggest the mpact of dfferent types of nfrastructure on agrcultural techncal effects. The results ndcate that except telecommuncaton, the popularty rates of road, the proporton of towns and townshps fnshed grd modfcaton, the proporton of towns conductng concentrated water supply and the proporton of towns and townshps constructed vocatonal/techncal schools all have sgnfcant effects n determnng levels of techncal effcency. The coeffcent estmate of road s 2.859, sgnfcant at the 0.05 level, and also exhbts the expected postve sgn, ndcatng that provnces n Chna wth hgher proportons of towns and townshps wth hghways above second class n local areas attan hgher levels of agrcultural producton techncal effcences. The road varable s an ndcator of the development of transportaton nfrastructure. The more towns and townshps have hgher class roads, the less the crculaton costs of materals and prmary products are. If the proporton of towns and townshps wth hghways above second class n local areas ncreases by one unt, the agrcultural producton techncal effcency would ncrease by unts. The relatvely large coeffcent estmate ndcates that ths factor s the most substantal determnant of level of effcency. Electrcty facltes also play a sgnfcant and postve role on techncal effcency. The status of electrcty facltes s represented by the proporton of towns and townshps fnshed grd modfcaton. In the past, there sn t suffcent nvestment on the constructons of rural grd, so the poor qualty, expensve prce and low effcency of rural grd cumbered the economc development of rural areas. Snce 14

15 1998, central and local government started to modfy rural grd. At the end of 2006, the proporton of towns and townshps fnshed grd modfcaton occuped 81.9 percent throughout Chna 6. However, among dfferent provnces, the grd modfcaton progressng rate vared greatly from 45.9% to 100%. Telecommuncaton s the proporton of vllages havng accesse to telephone. The sgn of the coeffcent on telecommuncaton varable s negatve, and telecommuncaton popularty rate s unlkely to have a sgnfcant effect on TE. Ths result s out of our expectance and may be ascrbed to the concentrated dstrbuton of telecommuncaton. In the rural area of Chna, the proporton of most vllages havng access to phone reaches to 97% or above. The mean of telecommuncaton s and ts standard devaton s 0.041, wth a range from to 1. If the varaton of an ndependent varable s not obvous, ths ndependent varable would not exhbt sgnfcant explanaton effect on the varaton of the dependent varable. The rrgaton nfrastructure s proxed by the proporton of towns conductng concentrated water supply. The coeffcent of water supply s and sgnfcant at 0.05 level. Regons wth more concentrated water supply exhbt hgher agrcultural producton effcency. Concentrated water supply could help reducng the rrgaton cost and enhancng rrgaton effcency. The popularty rate of vocatonal/techncal schools n towns and townshps has sgnfcant and postve effect on agrcultural producton effcency. The coeffcent estmate of schools s 2.643, and the magntude s the second largest among the fve 6 Communqué on Major Data of the Second Natonal Agrcultural Census of Chna. 15

16 types of nfrastructure. Vocatonal/techncal schools play great role on tranng rural laborers, and are mportant components of educatonal nfrastructure. From the above analyss, we could rank the fve types of rural nfrastructure by ts margnal mpact on agrcultural producton techncal effcency, the frst s road, and the second s school, and then followed by electrcty, water supply and telecommuncatons. We now turn to examnng the effects of the fve control varables of local ndustral structure, mechancal ntensty, educatonal level of rural laborers, and locatons. Industral structure s measured as the rato of agrcultural share of GDP. The coeffcent estmate of ths rato s negatve and sgnfcant at 0.05 level, whch means the lower porton of the agrcultural share of GDP s, the hgher techncal effcency the agrcultural producton acheves. Agrcultural share of GDP was found to be around 12.8% and ranges from 0.9% to 32.7%. In chna, the ndustral structure dffers greatly among provnces and muncpaltes. In the regons wth larger proporton of agrcultural ndustry, the support role of the ndustry and commercal servces sector on agrculture are less promnent than n the areas wth more developed ndustry and servces. The coeffcent estmate of mechancal ntensty (measured by power of agrcultural machnery per rural people engaged) s postve and sgnfcant at 0.10 level, and suggests that regons that are hghly mechanzed are more effcent. The use of agrcultural machnery can enhance agrcultural producton effcency. 16

17 The qualty of labor s often used as an explanatory varable for varatons n techncal effcency (Parkh and Shah, 1994). Educatonal level s evaluated by the proporton of rural labors that have completed senor secondary school or above. The postve and sgnfcant estmate coeffcent suggests that rural labors recevng more educaton are better at agrcultural producton. To control for the dsparty of locatons, we nclude two dummy varables. The base group comprses of provnces and muncpaltes n the western regon of Chna. The estmated coeffcent of dummy varable eastern s and sgnfcant at 0.05 level, whch means the average techncal effcency of provnces n the eastern regon of chna are hgher than those located n the western. Whle the nsgnfcant estmate of coeffcent on mddle area reveals that the dfference of agrcultural producton techncal effcences between mddle regon and western regon are not obvous. 5 Conclusons To conclude, ths paper has emprcally examned the effects of fve types of rural nfrastructure on the techncal effcency of 30 provnces and muncpaltes n Chna, and has also nvestgated the role of four control varables, ndustral structure, mechancal ntensty, educatonal level of rural labor, and geographcal locatons n generatng effcency. Ths study nvolved a two-stage process where agrcultural effcency was estmated usng DEA and varaton n the resultng effcency of agrcultural producton effcency was explaned by usng a tobt model. 17

18 Usng a data set consstng of cross sectonal provncal data newly publshed n the Second Natonal Agrcultural Census of Chna, We have found that all the selected fve types of rural nfrastructure, except telecommuncatons, the popularty rates of towns and townshps havng roads, fnshng grd modfcaton, conductng concentrated water supply, constructng vocatonal/techncal schools are postvely assocated wth agrcultural producton techncal effcency to a certan extent. The research hypothess on rural nfrastructure development and agrcultural techncal effcency s supported by the emprcal evdence. We also compare the mpact effect of varous types of rural nfrastructure on agrcultural techncal effcency. Transportaton nfrastructure plays the most substantal postve role on techncal effcency, followed by the vocatonal/techncal educaton nfrastructure, electrcty facltes and water supply systems. These results lead us to suppose that ncreasng rural nfrastructure constructon can enhance agrcultural producton techncal effcency, government can boost agrculture development through mprovng the nfrastructure facltes n rural areas. Furthermore, we also analyzed control factors that may affect agrcultural producton effcency. We found, as expected, that ndustral structure, mechancal ntensty and the qualty of rural labor are regonal attrbutes determnng agrcultural producton effcency. Provnces and muncpaltes n eastern Chna exhbt hgher agrcultural producton techncal effcency than those n mddle Chna, whle the dfference between mddle and western regon s not sgnfcant. 18

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