Technologcal Change, Skll Demand and Wage Inequalty n Rural Inda Arndam Bank, Ph.D ( Delh School of Economcs) Professor and Drector Internatonal Management Insttute, Kolkata; Edtor: Global Busness Revew, Sage Publcatons /4C, Judges Court Road Alpore Kolkata 70007 INDIA Moble:+98400383 Fax:+9 33 665968;Emal:arndambank@m.edu Pradp K Bhaumk, B.Tech ( IIT-Delh), FPM ( IIM Ahmedabad) Professor Internatonal Management Insttute, New Delh B0, Qutab Insttutonal Area New Delh 006 INDIA Emal:pkbhaumk@m.edu February, 08
Abstract Most newer technologes enterng the market through newer products and processes are skll-based n the sense that they use sklled workers more ntensvely than the older technology. Economsts have found that adopton of new technology s affected by the relatve supply of sklled workers n the regon regons havng a hgher supply are lkely to be qucker n new technology adopton. Also, whle the real wages of sklled workers are expected to ncrease as new skll-based technology s adopted, the wages of unsklled workers may ether reman unaffected or even fall. The ssue of supply of sklled labour has, therefore, become an area of mmense nterest largely because of the rsng nequalty n the relatve wages of sklled and unsklled labour. In ths paper we examne the relatonshp between the supply of sklled labor (artsans) wth mproved toolkts, changes n rural economc actvtes, and the relatve ncomes. Our study of rural artsans data n Indan lends support to the vew that supply of sklled artsans wth mproved toolkts s assocated wth hgh and acceleratng ncome. The estmate of the logt regresson reveals that the artsans as a broad socal group were more lkely to have benefted from the programme. Also the mportance of use of toolkts appears to be more sgnfcant factor n enhancng the ncome of artsans households as compare to educatonal level of the artsan. The small, though sgnfcant, negatve estmated coeffcent of the number of other assets varable shows that the artsan havng more assets s less lkely to have ncome ncreases. ( JEL classfcaton codes:i3,i3,i38,o0,5,o7). Introducton
The ssue of supply of sklled labor have been the subject of research for more than a decade, largely due to the rsng nequalty n the relatve wages of sklled and unsklled labor. Studes on supply of sklled labor can broadly be dvded nto two groups: those that assume that skll-based technologcal change s exogenous versus those that are based on the assumpton that the adopton of skll-based or unsklled-based technologes s endogenous. The overwhelmng majorty of papers belong to the frst group and have argued that skll-based technologcal change have played a central role on the ncreased nequalty n the ncomes of sklled workers as well as counterng the slowdown n productvty. Central to ths argument s the assumpton that skll-based technologcal change s exogenous (Bound and Johnson 99, 995; Katz and Murphy 99; Mncer 993, 995; Greenwood 996; Greenwood and Yorukoglu 996; Kahn and Lm 997; and Egger and Grossmann 00; Mcgrattan and Prescot 009). Endogenous analyss of supply of sklled labor and skll-based technologes has been carred out n a number of papers (Barro and Sala-I-Martn 995; and Acemoglu 996) but only recently has ths phenomenon been gven specal treatment (Kley 997). Kley concentrates on the endogenous growth model and argues that an ncrease n the supply of sklled labor leads to temporary stagnaton n the wages of sklled and unsklled workers. Further an ncrease n the supply of sklled labor accelerates skll-based technologcal change and under plausble condtons, lowers output growth, at least temporarly. In ths paper we examne the relatonshp between the supply of sklled labor (artsans) wth mproved toolkts, changes n rural economc actvtes, and the relatve ncomes. The mproved toolkts were provded to poor, rural artsans by the government of Inda at a 90 percent subsdy under ts SITRA (Supply of Improved Toolkts to Rural Artsans) 3
programme. In accountng for the role of mproved toolkts n both producton actvtes of the artsans and rural economc actvtes, we hypothesze the followng: Frst, the decson to supply mproved toolkts affects the rural areas n two prncpal ways by way of drect and ndrect benefts. Second, an ncrease n the supply of sklled labor wth mproved toolkts fosters organzatonal change and rases the employment share of artsans wthn the rural economy, wthout lowerng relatve ncomes. Thrd, the mproved toolkts rase ncome nequalty by affectng the organzaton of producton (Eggar and Grossmann 00; Parro 03; Kurukawa 0). Ths paper s organzed as follows. Secton dscusses the theoretcal model. In secton 3 we present the emprcal model. In secton 4, the methods of data collecton are explaned. Secton 5 examnes the rural households based on select parameters. Secton 6 presents the results of the emprcal analyss. Secton 7 concludes.. The model.. Decson to Supply Improved Toolkts We begn wth the followng assumptons: () the economc condtons of the rural artsans n the developng country are stark enough durng the perod [0, T]; () At any gven tme t, the economc condtons have reached a certan poston x(t) and () for fxed t there s nothng the government can do to change ths poston. Consder now that the decson of the government to supply mproved toolkts over a small tme nterval [t, t+dt] provde an opportunty for the rural artsans to change ther economc condton by a small amount, say dx. Ths change n poston or decson, dx can affect the benefts accrung to the artsans n two ways: The frst s the drect effect, whch wll be 4
U(t, x, dx/dt).dx () where U(t, x, dx/dt) s the socal utlty per unt of transfer at x(t), whch s regarded as ndependent of the amount of transfer as dx s small. In order to determne the ndrect effect, the entre stream of margnal beneft generated by the small change n poston dx must be known,.e. Ux(τ, x, dx/dτ), τ [t, T] () where Ux(τ, x, dx/dτ) s the present value of the future socal utlty per unt of transfer made at tme t from the ndrect beneft generated at tme τ. Let trajectory or extremal along whch the rural economy moves be denoted by E. Thus the present value of the stream of benefts generated by the decson dx s gven by: T J n j T E E (3) = = j U x ( τ, x, dx / dτ ). τ.dx = U x ( τ, x j, dx j / dτ ). τ.dx j j t j t where the subscrpt j refers to the th person n the j th socal group, both for the socal utlty functon and the change n the economc poston. The socal utlty functons for backward classes and castes may be dfferent for example under the SITRA programme, 50 percent of the benefcary artsans were to be from the Scheduled Castes (SC) and Scheduled Trbes (ST) communtes. The total ndrect beneft (present value) can be further separated nto current and future ndrect benefts. Ths gves t+ dt t U x T ( τ, x, dx / dτ ). τ.dx + E U t+ dt x ( τ, x, dx / dτ ). τ.dx (4) 5
Snce the future ndrect benefts are of major mportance, the total beneft accrung to the rural economy durng tme nterval [t, T] as a result of the decson to supply mproved toolkts s then the sum of () and (4)... Toolkts Technology The rural economy conssts of three categores of labor () sklled labor wth toolkt (L st ); () sklled labor wthout toolkt (L s ) and () unsklled labor (L u ). We defne the toolkt as a labor-augmentng techncal progress that enhances the value of sklled labor to more than that of sklled labor wthout toolkts and unsklled labor respectvely. Ths s due to the assumpton that sklled labor wth toolkts are more productve than sklled labor wthout toolkts and unsklled labor. Consder now n dentcal artsans who produce a homogeneous good. Let the artsans dffer n toolkts technology, such that there wll be a segmented labor market and nelastc supply of L st and L s respectvely. We assume that L s complements ether L st or L u, not both. L s complements L st by sellng servces and work as per customer s need. We shall treat sklled labor wthout toolkts as supportng labor. Producton wth L s and L st s a perfect substtute for producton wth L st. Kley(997) has argued that the assumpton of perfect substtuton reflects the dea that there are dfferent ways to produce a good, and that the choce of the mx of producton processes s endogenous. Gven these assumptons, the output Y of artsan s gven by the lnear homogeneous producton functon F: Y = F( U, V ) U. f ( κ ), (6) 6
where U L ) and V L ) are the effcency unts of artsan labor wthout and wth ( s ( st mproved toolkts respectvely, κ V / U represents the skll-ntensty n producton of the th artsan whle f κ ), as an ndcatrx, s a strctly ncreasng and strctly concave ( functon. In the economc enterprse of a rural artsan, the only relevant factor of producton s labor. There s vrtually no captal or land or any other factor of producton commtted to the artsanal economc enterprse. The effcency unts of labor n producton depends on the artsans wthout mproved toolkts and those wth toolkts. Although artsans wthout mproved toolkts enter the producton functon as productvty-augmentng through the expanson of say N (the goods avalable for producton wth sklled labor), they are employed at the same ntensty level as those artsans wth mproved toolkts. By mplcaton, producton s lnear n U and V respectvely. The constant returns to producton mx mply that expanson of N goods allows for endogenous technologcal progress, as n the well known AK model of endogenous growth (see Kley, 997;Barro and Sala-I-Martn, 995). However, we are dfferentatng between categores of sklled labor n terms of tools or technology. Consder now where addtonal unts of mproved toolkts greatly mprove the artsans productvty. Then the effcency unts of artsans wthout mproved toolkts and artsans wth toolkts are gven as: U = U + α U and V = V + βv (7) where α and β are relatve effcences and both are assumed to be greater than mplyng a productvty gan.e. addtonal supply of mproved toolkts to artsans leads to hgher productvty of both artsans wthout toolkts and those wth the same. It should 7
be noted that U and V are the addtonal unts of labor n producton by artsans wthout and wth toolkts respectvely, after the addtonal toolkts are suppled and do not mply the physcal contnuaton of prevous labor and an add-on to the same. Followng Nadr (987) t can be argued that the supply of addtonal toolkts wll lead to a jont producton functon. Let m represent the addtonal toolkt whch can be used to produce outputs by artsans not havng a toolkt earler or those havng a toolkt earler. The physcal unts of labor suppled by the th artsan are U and V respectvely, whereas the effcency unts of labor would be α U and β V. Then, m = ω.g( α U, βv ) ω. U. g(χ ) (8) G s a lnear homogeneous functon; χ V / U represents skll-ntensty n producton due to the addtonal mproved toolkts, ω s the fracton of producton or shft n effcency parameter due to the addtonal toolkt, and g(χ) s assumed to be strctly ncreasng and strctly concave. The mplcaton of (8) s that every addtonal mproved toolkt suppled creates an effect on sklled artsans n two ways: Frst, f t s used by an artsan wthout a toolkt, m = ω.g( α ) and second, f t s used by an artsan wth toolkt then m = ω.g( β ).It U V may be noted that a maxmum of one mproved toolkt s suppled by the government under SITRA but artsans can purchase addtonal unsubsdzed toolkts from the market. Next consder the wages and proft structures n the rural economy. Let fnal goods output produced by dfferent artsans be dentcal. There are no market mperfectons.e. sales of fnal product does not depend on whether t was produced wth subsdzed toolkt 8
or not. To maxmze profts artsans take all wages ( w U, w U, w V,w V and w m ) pad to U, U, V, V and m as a datum. We can wrte the decson facng a gven artsan as, U 0, U Max 0, V 0, V 0 F( U U U + α U, V + αv ) w U w U w V w V w.m (9) V V m Let κ = κ and χ χ for all gven that all artsans are dentcal. The frst order = condtons for the proft- maxmzng employment levels are: f ' ( ) w U κ (0) ' g ' U m α f ( κ ) w + w ω (χ) () f ' ( ) κf ( κ ) w V κ () ' ' ' V m g g β ( f ( κ ) κf ( κ )) w + w ω( (χ) χ (χ)) (3) Condtons (0) (3) respectvely show the margnal product of labor on the left-hand; and the margnal costs on the rght-hand. The margnal costs for labor after addtonal mproved toolkts are suppled U and V equal the sum of ther wage rate ( w U and w V respectvely) and margnal wage costs for the sklled labor wthout toolkts..3. Wages and Skll based Technology Change In ths study, we treat mproved toolkts of all types as skll-based technology. Snce n our model we are dstngushng between dfferent categores of sklled labor n terms of tools or technology, t has endogenous and exogenous mplcatons for relatve wages. Frst, our model mples that more mproved toolkts for the artsans rase the skll wage premum for both artsans wth and wthout mproved toolkts. Ths s due to the endogenous development of more toolkts for sklled labor. The endogenous development 9
arses from our assumpton that sklled artsans wthout mproved toolkts can sell servces or work as per customer s need. In effect, more nvestment n mproved toolkts wll shft the demand for artsans and lead to hgher share of artsans labor n the rural economy. Second, our model also mples an exogenous change n the share of the artsans on the growth of each type of mproved toolkt and the relatve wages of both artsans wth or wthout toolkts. The relatve supply of toolkts s expected to rse dramatcally due to government s support for mproved toolkts. For example, to sut the needs of the artsans from varyng trades, many dfferent toolkts have been developed by the research & development (R&D) organzatons of the government of Inda and also the state governments. About types of toolkts have already been developed snce 99. Also, the artsans can drectly purchase the mproved toolkts from the market and ths provdes another possble exogenous change. Ths then leads to the research queston: wll exogenous skll-based technology lead to relatve hgh wages of artsans wth or wthout mproved toolkts? Followng Egger and Grossmann (00) and the model developed above, ths would depend on whether the effcency unts of labor of artsans wth toolkts relatve to that of artsans wthout toolkts result n () ncreasng α, () ncreasng β, () decreasng ω, (v) does not depend on U and V. If α ncreases, the relatve demand for artsans wthout toolkts and thus wage dsperson wll ncrease. An ncrease n β, means that the relatve demand for artsans wth toolkts become more attractve. As a result, equlbrum wage nequalty ncreases. An ncrease n ω mples that cost of buyng toolkt s rsng and supportng sklled labor wthout toolkts becomes more expensve. Thus the wage dsperson declnes. Fnally, the effect 0
of both ncrease n U and declne n V cancel out n equlbrum due to the lnear homogenety of G( α U, βv ). 3 Emprcal analyss The hypotheses generated n the prevous secton are tested n ths study on feld data collected n Inda durng 000. The SITRA (Supply of Improved Toolkts to Rural Artsans) programme was launched by the government of Inda n 99 under whch the benefcary artsans receved mproved toolkts related to ther trade at a heavy subsdy of 90 percent. Ths programme has snce been merged wth the Swarnjayant Gram Swarozgar Yojana (SGSY) programme wth effect from Aprl 999. We examne some characterstcs of the benefcary artsans based on our earler dscusson and attempt to fnd f any of these have contrbuted to a sgnfcant ncome effect. The econometrc analyss adopted s probablstc. The model used s a bnomal logt model. The dependent varable s a bnary varable whch measures f there has been an ncrease n ncome or not. The probablty of the event occurrng s determned by: ( ) Pr ob Y = = F( α + βx ) exp( α + βx) = + exp( α + βx ) For the logt model the nterpretaton of the coeffcent s transparent, consderng the log odds rato. The logt model can be wrtten as, log e [ Pr ob( Y = ) / Pr ob( Y = ) ] =α + βx
The effect of a unt change n X on the log odds rato of the event occurrng s gven by the beta coeffcent. Takng the log odds rato nto consderaton s very useful snce the nterpretaton of the coeffcent s mmedate. As logt models are not lnear n the parameters, they are estmated by usng maxmum lkelhood technques. Dependent Varable Defnton of Varables INCEFF = Income effect on benefcary artsan household s ncome from craftsmanshp, f ncome from craftsmanshp after recevng toolkts s greater than the correspondng ncome before recevng the toolkt, 0, otherwse Independent Varables SCLGRP Socal Group of the artsan benefcary =, f benefcary artsan belongs to SC, 0, otherwse ST or OBC
EXPCR HEDUC LDOWD ASSOD TYPPR UTOOL Experence n craftsmanshp, 0-5 years, 6-0 years = 3, -5 years 4, more than 5 years = = = Hghest educaton completed,, 3, 4, 5, cannot can read / wrte some schoolng (upto 4 years) SSC/HSC Techncal read / wrte tranng Land Owned (n hectares) Assets or Durables Owned (formal / nformal) Number of asset categores owned by the household among namely Tractor, Power Tller, Combned thresher Celng fan, Three - wheeler and Motor Typcal products produced or servces sold 0,,, standard product produced sell the servce/ work as custom produce on order per Use of Tool Kts: extent of use = 0,,, 3, usng usng usng usng none some most all and kept customer' s cycle/ scooter for sale needs /harvester, eght categores specfed Refrgerator, Televson set, 3
The dependent varable INCEFF s bnary wth Y havng a value, f the th benefcary artsan has had an ncrease n ncome and 0 otherwse. Although ths may look to be a crude nomnal measurement, t reduces the measurement errors nherent n ncome measurements of poor and qute often llterate artsans wthout any regular source of ncome. The ndependent varable SCLGRP categorses all benefcary artsans nto two categores vz. the relatvely backward socal groups Scheduled Caste (SC), Scheduled Trbe (ST) and Other Backward Castes (OBC) are assgned the value of, whle all others get 0. Whle the backward socal groups are preferred whle selectng benefcares, socal utlty wll actually ncrease only f they can successfully use the mproved toolkts and rase ther ncome levels. The next two varables (EXPCR and HEDUC) measure the human captal represented by the benefcary artsan. If the number of years n craftsmanshp (EXPCR) s found sgnfcant, then ths could perhaps be nferred to affect the skll and productvty of the artsan. Both these varables could also affect the way an artsan adopts and adapts the new technology represented by the mproved toolkts. These varables could lead to a hgher or lower wage nequalty dependng on the sgn of the coeffcent. Smlarly, ASSOD and LDOWD represent the asset holdngs (other assets and land respectvely) of the benefcary artsan and as proxy of other factors of producton say captal and land, are expected to explan f the producton functon of the artsans should nclude varables other than labor. The varable TYPPR measures an nterestng characterstc of an artsan how exactly s the labor offered n the market. If ths varable s found sgnfcant, then sklled artsan 4
labour may not be homogenous and supply of mproved toolkts mght actually rase wage nequalty. Fnally UTOOL measures the utlty of the toolkt receved to the artsan. It s expected that only relevant and useful toolkts would enhance labour productvty and rase ncome level. An nsgnfcant coeffcent would mply ncome rses unrelated to the use of mproved toolkts and should lead to search of other unknown varables. 4. Feld data Sample Frame, Method of Collecton and Data Structure The feld survey was conducted from January 000 to July 000. The data collecton was based on nformaton gathered from three man sources, namely the mplementng agency (DRDA), the gram panchayat and the ndvdual artsans from the target group both benefcares and non-benefcares. The benefcares got the beneft durng 996-997, 997-998 or 998-999. In ths paper we have analyzed benefcary artsans only. The number of dstrcts for the study was fxed at 0 per cent of the total number of dstrcts subject to a mnmum of two dstrcts n each state. The dstrcts were selected through purposve samplng to ensure that these dstrcts were adequately representatve of the state wth respect to geographcal dstrbuton and specal condtons of the state, f any. The sample of dstrcts was further refned to ensure that at least one dstrct (f avalable) was ncluded under the mplementaton of watershed programmes, namely, Desert Development Programme (DDP), Draught Prone Area Programme (DPAP) and Integrated Wasteland Development Programme (IWDP). 5
The sample dstrcts were grouped nto two strata, one stratum comprsng dstrcts where no watershed projects under DDP, DPAP or IWDP had been mplemented, and the other stratum comprsng the dstrcts where at least one of these programmes had been mplemented. In each of the non-watershed dstrcts, 30 per cent of the blocks (rounded upward) were selected through crcular systematc samplng usng the Drectory of Blocks as the frame of reference. In each of the watershed dstrcts, the blocks were grouped nto two man strata, one consstng of blocks where none of the schemes had been mplemented (non-watershed blocks) and the other stratum comprsng blocks where at least one of these schemes exsted (watershed blocks). The sample sze of the watershed blocks was also fxed at 30 per cent (rounded upward). The sample blocks n each dstrct were selected through random samplng wth preference gven to those blocks where the maxmum numbers of programmes (DDP, DPAP, IWDP) were n exstence. We selected 9 dstrcts as sample dstrcts across states, excludng North Cachar Hlls and Karb Anglong n Assam. The scheme dd not cover the Munger and Gumla dstrcts of Bhar. Lkewse t dd not cover the Samanda, Rankor, Mawkyrwat and Nongstan blocks of Meghalaya. In Sangsax block, the survey could not be undertaken due to heavy ranfall. Hence a total of 3 dstrcts were consdered as sample dstrcts for the study. It s to be mentoned here that a gram panchayat s the lowest admnstratve unt. In some cases a sngle gram panchayat may consst of only one vllage, whle n others t may have a number of vllages, hamlets or padas. Data on vllage ndcators were avalable for a gram panchayat rather than for a vllage. The feld-level agences, whch actually 6
carred out the data collecton work, therefore found t convenent to collect nformaton from the gram panchayat offce. The schedule for collectng such nformaton was approprately called the gram panchayat schedule. The feld-level agences carred out the selecton of vllages/gram panchayats carefully, so that these would properly represent the mplementaton of the SITRA programme n the blocks. Indvdual artsans were the fnal samplng unts. However, two types of respondents were covered namely BPL artsans who were benefcares under SITRA and below poverty level (BPL) artsans who were non-benefcares. The Government of Inda enumerated BPL households n two censuses, n 99 and 997. The lst of BPL households n each vllage was obtaned from the DRDA, wth due care beng taken to dentfy the reference year. Wherever avalable, the BPL household lst from the 997 BPL census was used. In all other cases the 99 BPL census lst was used. From ths lst of BPL households, a frame of artsans (ndvduals not households) was prepared and benefcares and non-benefcares under SITRA were dentfed. From the frame of BPL artsans, fve benefcares (selected randomly) or all of the benefcares n case there were less than fve were selected as benefcary respondents and the schedule for benefcares flled up for each of them. Smlarly, one nonbenefcary artsan from ths frame of BPL artsans was chosen as a sample for the nonbenefcary artsan category. 7
5. Rural Artsans n Inda - A close look Ths secton summarzes those characterstcs of rural artsans whch have been measured and analyzed. Ths would also present a profle of rural artsans of Inda. Although data from 30 states and Unon terrtores (UTs) have been used n the econometrc study, those for seventeen major states are gven n the tables below, whle the All Inda fgures relate to the complete sample sze of 6788 benefcares. The sample szes for the same state may vary somewhat n dfferent tables because of mssng data. The ncome dstrbuton of benefcary artsan households n the major states of Inda both before and after recevng the mproved toolkts s shown n Table. The dvergence n ncomes among rural artsans n dfferent states can be seen qute clearly. Whle Kerala had a relatvely hgh ncome level of ts benefcary rural artsans, the same was qute low n West Bengal and Bhar. On the other hand, the reported ncrease n ncome level appeared to be sgnfcant n most states. Type Table somewhere here 8
Table Income effect of SITRA on benefcary artsan households' ncome: Major states (000) Major state Total No. of HH n sample HH wth ncr n ncome HH wth no ncr n ncome Andhra Pradesh 30 88..9 Assam 66 89.4 0.6 Bhar 858 83. 6.9 Gujarat 89 93. 6.9 Haryana 3 9.6 8.4 Hmachal Pradesh 6 75.0 5.0 Jammu & Kashmr 5 87..8 Karnataka 4 69.4 30.6 Kerala 30 7.4 8.6 Madhya Pradesh 70 6. 37.9 Maharashtra 35 93. 6.8 Orssa 5 79.7 0.3 Punjab 73 8.7 7.3 Rajasthan 53 86.3 3.7 Taml Nadu 49 9.4 7.6 Uttar Pradesh 7 8.4 8.6 West Bengal 344 79.9 0. All Inda 6788 79.5 0.5 Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng ncome-effect group. Table presents the mpact of SITRA on benefcary households ncome from craftsmanshp. At all Inda level 80 per cent of the total sample artsans were able to rase ther ncome after recevng the toolkts. The largest percentage of artsans who rased ther ncome has been reported n Maharashtra, Gujarat and Taml Nadu (between 90 and 93 percent). About 36 per cent artsans were unable to rase ther ncome n Madhya Pradesh the hghest n ths category. 9
Table 3 Artsan benefcares under dfferent socal groups: Major states (000) Major State Total No. Percentage artsan benefcares from Physcally SC ST OBC Women Handcap. Others Andhra Pradesh 30.3 5.8 0.0 8.7.0 63. Assam 66 0.6.7 0.0 0.0 4.5 6. Bhar 858 4.9 0.5 55. 5. 0.6 3.5 Gujarat 89 3.8 6.3 3. 0.5.6 64.6 Haryana 3 9.8 0.0 78.6 0.0.5 0.0 Hmachal Pradesh 6 75.0 0.0 5.0 0.0 0.0 0.0 Jammu & Kashmr 5.4 5.6 0.0 0.8 0.0 7. Karnataka 4.4 7.4 0. 3.3. 54.5 Kerala 30 9.6 6.3 8.7.3.0 0.0 Madhya Pradesh 70 5.7 9. 4.9 0.4..7 Maharashtra 35.9 4.8 7.4 0.6 0.3 0.0 Orssa 5.3 8.0 46..9.7 0.0 Punjab 73 44.5 0.0 44.5.7 5. 4.0 Rajasthan 53 37.3 3.9 0.0 55.6 3.3 0.0 Taml Nadu 49.7. 69.9 6.4 0.8 0.0 Uttar Pradesh 7 40.6. 5.6 5.0.8 0.0 West Bengal 344 5.7 8.7 0.0.. 37. All Inda 6788 4.0 5.7 38.4 4.8.5 5.6 Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng socal group. 00 000 Benefcary Artsans (No.) 800 600 400 00 Others 0 Physcally Handcap. Women OBC ST SC Andhra Pradesh Assam Bhar Gujarat Haryana Hmachal Pradesh Jammu & Kashmr Karnataka Kerala Madhya Pradesh Maharashtra Orssa Punjab Rajasthan Major States Taml Nadu Uttar Pradesh West Bengal 0
The dstrbuton of artsan benefcares under varous socal groups n the sample are presented n Table 3. It s evdent that the percentage of benefcares under other backward castes (OBC) category at all Inda level domnates the total sample (about 38 per cent) followed by the socal group SC (4 per cent). However, ths trend vares substantally across states. The hghest percentage of OBC benefcares was from Kerala (about 8 percent), whle the lowest was from Gujarat (only about 3 per cent). In contrast, SC artsans formed the hghest percentage n rural West Bengal (about 5 per cent) and the lowest n Kerala (about 0 per cent). Varatons could also be observed among artsans under women, physcally handcapped and others categores. Table 4 reveals the benefcary artsan s experence n craftsmanshp among the major states of Inda. At all Inda level young artsans havng up to 0 years of experence formed about 6 per cent of the total respondent artsans. However, there were wde dfferences from the all Inda averages. Whle states lke Maharashtra, Andhra Pradesh, Kerala and Orssa had artsans wth longer experence n craftsmanshp, t was shorter n states lke Madhya Pradesh, West Bengal and Hmachal Pradesh. The level of educaton and techncal tranng of the benefcary artsans are shown n Table 5. The rate of llteracy (can not read or wrte) at all Inda level was reported to be 9 per cent among the artsan benefcares. Interestngly, whle the rate of llteracy among artsan benefcares was the lowest n Kerala (about 3 per cent), the state also had a large percentage of rural artsans wth formal educaton up to SSC/HSC level but wth no techncal tranng ether formal or nformal. The role of formal or nformal techncal
tranng appears to be an nsgnfcant factor mplyng that the artsans are n the present professon by nhertance. Table 4 Benefcary artsans' experence n craftsmanshp: Major states (000) Major State Percentage artsans wth an experence of Total No. 0-5 years 6-0 years -5 years > 5 years Andhra Pradesh 308 3.7 8.5.8 36.0 Assam 66 37.9 3.8 0.6 9.7 Bhar 77 3.4 37.4 0. 0. Gujarat 86 3.8 6.3.4 8.5 Haryana 3.. 6.0 39.7 Hmachal Pradesh 6 43.8 3.3.5.5 Jammu & Kashmr 0 4. 0.0 0.8 45.0 Karnataka 4 8.7 34.9 9.9 6.6 Kerala 30 6.9 4.6.6 36.9 Madhya Pradesh 53 44.6 40.5 9. 5.6 Maharashtra 35 7.4 0.8 30. 4.6 Orssa 495 0.4.8 8.4 39.4 Punjab 73 5.6 4..4 0.8 Rajasthan 44 4.4 7. 8.3. Taml Nadu 49 8.4 43.0 8.5 0. Uttar Pradesh 095 37. 6.6 4.3.0 West Bengal 339 45.7 33.9.5 8.8 All Inda 647 3.5 30.6 5..7 Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng experence group. Whle land owned by the benefcary artsans s shown n Table 7, the other assets or durables owned by them are presented n Table 6. It appears that celng fans and threewheeler cycles domnate the other assets or durables owned by the artsans. In states lke Punjab and Haryana, the number of motorzed two wheelers (motor cycle/scooters) owned by artsans appears to be much hgher than n most other states.
Table 5 Level of educaton of benefcary artsans: Major states (000) Major States Total No. cannot read or wrte Percentage benefcary artsans who can/ have had some schoolng can read or wrte (up to 4 years) 5-9 years of school SSC/HSC Techncal Tranng (formal/ nformal) A & N Islands 05 4.3 9.5.9 38. 5..0 Andhra Pradesh 30 45.8 6.8 4.5 5.5 5.5.9 Assam 66 8. 5. 7.6 5. 43.9 0.0 Bhar 858 37. 35. 7.3 8.4.5 0.5 Gujarat 89 8.6 0.6 6.4 34.4 0. 0.0 Haryana 3. 37.4 4.6.9 0.7.3 Hmachal Pradesh 6 5.0.5 6.3 5.0 3.3 0.0 Jammu & Kashmr 5 6.6 8.8 4.0 7.6 7. 0.8 Karnataka 4 4.0 7.9 7.7 8.5. 0.8 Kerala 30.7 9.6 5.6 9.6 39.9.7 Madhya Pradesh 70 38.9 6.3 9.7 5.4 9.7 0.0 Maharashtra 35 0. 5.6 7.0 7.8 8.8 0.6 Orssa 5 39. 6.9 5.9.3 5.6 0. Punjab 73 7. 4.3 5. 6.0 6.. Rajasthan 53 3.7.9.8 8. 4.6 0.0 Taml Nadu 49 3.7 43.8 3.7 3.3 5. 0.4 Uttar Pradesh 7 9.6 5.0 9.9 7.3 7.7 0.4 West Bengal 344. 43.9 9.8 0.3 3. 0.6 All Inda 6788 8.9.9.6 3.4.5 0.6 Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng educaton group. 3
Table 6 Benefcary artsan households' ownershp of other assets: Major states (000) Major State Total No. Trac tor Percentage benefcary artsan households that own Power Tller Thre/ Harv. Comb Refr gera tor Cel. Fan M. Cycle/ Scoot TV Three Whlr Andhra Pradesh 30 0.3 0.3 0.0 0.3 35.5.3 6. 9.4 Assam 66 0.0 0.0 0.0 0.0 3.0 0.0 3.0 3.0 Bhar 858 0.3 0. 0. 0..7 0.5 4. 5.8 Gujarat 89 0.5 0.0 0.0.6 5.9.6 8.0 6.4 Haryana 3 0.8 0.8 0.8.5 68.7 5.3 9.8 50.4 Hmachal Pradesh 6 0.0 0.0 0.0 0.0 8.8 0.0 43.8 37.5 Jammu & Kashmr 5 0.0 0.0 0.0 4.0 5.8 0.0 6.0 7. Karnataka 4 0.4 0.0 0.0 0.8 4.9.5.9 38.0 Kerala 30 0.3 0.0 0.0 0.3 35.5.0.6 5.6 Madhya Pradesh 70 0.9 0. 0. 0.6 8.7 0.6 6.7 5. Maharashtra 35 0.0 0.0 0.0 0.3.5.7.6 8.8 Orssa 5 0.0 0.0 0.4 0. 8.8 0.8 5.8.9 Punjab 73.3 3.5 3.5 6. 84.4 4.5 43.9 34. Rajasthan 53.3.0 0.0.3 7.8 0.0 7. 7.5 Taml Nadu 49 0.8 0.4 0.4 0.4 47.4 3. 3.3 8.0 Uttar Pradesh 7 0.4 0.4 0. 0. 7.0 0.9 9.4 7.7 West Bengal 344 0.3 0.3 0.3 0.3 3. 0.3.5 4.4 All Inda 6788 0.4 0.3 0.3.0 7.5.6.3 5.0 Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans havng the correspondng asset. Table 7 presents the land owned and the typcal products produced and sold by the benefcary artsans. The percentage of artsans reportng to sell ther servce/work as per the customer s needs seems to domnate at both all Inda and state levels. Indeed, the fgure s as hgh as 88 percent n Taml Nadu and Hmachal Pradesh and Kerala. In contrast, majorty of the artsans n Rajasthan and Andhra Pradesh produce only custom products produced on order. Fnally, the artsans who sell standard products to be sold n the market appear to consttute 3 percent of all benefcary artsans n Bhar and 36 percent n Orssa. 4
Table 7 Land owned and typcal products produced and sold by benefcary artsans: Major states (000) Percentage artsans who sell Major State Average land owned (ha) Total No. Standard Products produced and kept for sale Servce/Work as per the customer's needs Custom Products produced on order Andhra Pradesh 0.8 8 6.4 39.0 54.6 Assam 0.49 66 0.0 93.9 6. Bhar 0.308 773 3.4 6.9 5.7 Gujarat 0.89 83 6.0 68.9 5. Haryana 0.095 5 0.4 80.8 8.8 Hmachal Pradesh 0.457 6 0.0 87.5.5 Jammu & Kashmr.36 9. 43.8 47. Karnataka 0.53 4 5.4 63. 3.5 Kerala 0.38 93 5.8 87.4 6.8 Madhya Pradesh 0.650 59. 69.6 8.4 Maharashtra 0.3 344 7.3 64.5 8. Orssa 0.387 49 36.4 36.6 7.0 Punjab 0.07 7 6.4 73. 0.5 Rajasthan 0.707 34 4.9 0. 64.9 Taml Nadu 0.037 48 4.8 88.3 6.9 Uttar Pradesh.4 030.7 57.5 30.8 West Bengal 0.39 34.0 64.6 3.4 All Inda 0.597 644 4. 59.4 6.5 Average land owned by benefcary artsan s n hectares. Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng sellng group. The extent of use of the mproved toolkts provded to the benefcary artsans s captured n Table 8. About 36 percent of all benefcary artsans report to be usng all the tools n the toolkt, whle another 3.5 percent use some of the tools. As many as 9.5 percent of the benefcary artsans n Karnataka and 3.9 percent n Orssa do not use any of the tools. On the other hand, n Gujarat, Haryana, Jammu and Kashmr and Taml Nadu more than 50 percent of all benefcary artsans use all the tools receved. 5
Table 8 Benefcary artsans' use of toolkts: Major states (000) Major State Total No. No/ Usng none Usng some Usng Most Usng All Andhra Pradesh 30 7.7 39.7 48. 4.5 Assam 66 4.5 40.9 9. 45.5 Bhar 770 0.3 47.8.5 9.5 Gujarat 86 0.0 8..0 7.0 Haryana 3.5 6.0. 60.3 Hmachal Pradesh 6 6.3 37.5 5.0 3.3 Jammu & Kashmr 4 0.0 0.8 33. 66. Karnataka 4 9.5 4.. 8.3 Kerala 95 9. 4.6 6.6 59.7 Madhya Pradesh 533 5. 46.7.0 6.3 Maharashtra 345 8.4 4.9 5.7 33.0 Orssa 5 3.9 47.5 9.5 9. Punjab 7 9.4 68.4 8. 4.0 Rajasthan 39 4.3 3.0 55.4 7.3 Taml Nadu 48 4.0 6.5.4 58. Uttar Pradesh 0 5.3 5.7 7. 4.9 West Bengal 34 0.6.3 4. 36.0 All Inda 6449 5.8 3.5 5.7 36. Total No. refers to the total number of benefcary artsans for the major state. All other fgures refer to the percentage of artsans belongng to the correspondng sellng group. 6. Estmaton Results Table 9 presents the parameter estmates of the logt regresson of the bnary dependent varable (INCEFF) denotng that a benefcary artsan s ncrease n ncome after recevng the toolkts as, or 0 otherwse, on a selecton of the artsan s socal group (SCLGRP), experence n craftsmanshp (EXPCR), hghest educaton (HEDUC), land owned (LDOWD), other assets owned (ASSOD), typcal products produced (TYPPR) and use of toolkts (UTOOL). The lst of varables used, ther defntons and measurements have already been detaled n Secton 4 above. The estmaton, usng the SPSS software package, was performed on the dataset consstng of 6788 observatons (benefcary 6
artsans). We had to delete 90 observatons because of mssng data. Thus we consdered 5878 observatons for the purpose of logt analyss. Table 9 Logt Estmates of Benefcary Artsans' Increase n Household Income from Craftsmanshp on Select Varables Varable Coeffcent Estmate Constant.63** (0.9) SCLGRP.4604** (0.083) EXPCR -0.043 (0.036) HEDUC -.00** (0.034) LDOWD 0.0005 (0.004) ASSOD -.0878* (0.044) TYPPR.788* (0.0583) UTOOL.366** (0.0366) Total Number of observatons (A) 6788 Number rejected because of mssng data 90 Number of cases ncluded n the 5878 analyss (B) % B/A 86.59 Log Lkelhood for Logstc 578.578 Ch square value 40.5 Notes: Standard errors are n parentheses ** Sgnfcant at per cent level * Sgnfcant at 5 per cent level The estmated coeffcent for SCLGRP,.e. socal group (SC, ST and OBC) s postve and sgnfcant mplyng that artsans from the relatvely backward socal groups as a whole are more lkely to ncrease ther ncome. Among these groups, the results are expected to be vared, further nvestgaton of whch we have planned for. It also confrms our earler remark that the ncome tends to rse among artsan benefcary households. In other words, wth everythng else held constant, rural artsans from 7
backward socal groups are more lkely to have addtonal ncrements of ncome by usng toolkts. Ths s a very sgnfcant fndng of ths study. In Inda, the backward socal groups are generally backward n almost all respects economc, cultural, educatonal, etc. Specal provsons exst for the protecton of the socally underprvleged for example even under the SITRA programme, a mnmum 50 percent of the benefcary artsans are mandated to be from the SC and ST categores mplyng a hgher socal utlty from benefts accrung to the socally backward compared to smlar benefts accrung to the non-backward. A statstcally sgnfcant postve co-effcent mples a reduced ncome nequalty as a consequence of the benefts from SITRA. It s more dffcult to hypothesze possble reasons for ths postve co-effcent. It would seem that the dsadvantaged status of these rural artsans pushes them harder to explot the technology made avalable to them, work harder and more productvely and consequently gan ncome ncreases. The greater the ntal handcap, the stronger the motvaton to do better. The varable EXPCR representng experence n craftsmanshp exerts a negatve but nsgnfcant mpact on ncrease n ncome earned under the benefcary category. Other thngs beng equal a young and enterprsng artsan wll be more prone to be nnovatve and hardworkng, and thus be able to gan more from the mproved toolkt. However, ths mpact s not found to be statstcally sgnfcant. 8
The varable HEDUC,.e. hghest educaton completed by the artsan reveals an nterestng negatve coeffcent. Ceters parbus, lower general educaton of artsans s more lkely to contrbute to ncreases n ther household ncome. It s to be noted that a small and neglgble percentage (only 0.5%) of sample benefcares had any techncal tranng ether formal or nformal. Both educaton and experence seem to have a negatve relatonshp wth ncome ncreases. Agan, we fnd that the more dsadvantaged an artsan, the greater the resolve to use the new technology effectvely and the greater the lkelhood of an ncome ncrease. Although the basc logc s the same, the strength of the argument s stronger for educaton wth a statstcally very sgnfcant negatve coeffcent and not-so-strong for experence wth a statstcally nsgnfcant negatve coeffcent. Ths suggests that lack of experence s perhaps not as much of a handcap as lack of educaton. Land owned represented by varable LDOWD shows nsgnfcant but postve coeffcent. On the other hand, the varable ASSOD representng other assets or durables owned sgnfcantly affects artsan household s ncrease n ncome from craftsmanshp. In other words households ownng more categores of assets are less lkely to experence ncrease n ncome. Ths, agan corroborates the general argument that the more underprvleged and dsadvantaged end up ganng more from the faclty provded through mproved toolkts. The mportance of typcal products produced or servces sold on ncome,.e. varable TYPPR, s reflected n the postve and sgnfcant coeffcent. Ths mples that artsans 9
are more lkely to rase ther ncome when they servce/work as per the customer s needs or produce customzed products on order than f they produce standard products and offer the same for sale. As t s, the ncome level of artsans producng standard products and keepng the same for sale s expected to be lower than the ones who sell servce/work as per the customer s needs or produce customzed products on order. The new technology would then result n hgher ncome nequalty. Fnally, the varable UTOOL,.e. Use of Toolkts: extent of use may be consdered as a proxy of qualty of toolkts. The artsans do not always receve hgh qualty toolkts due to transacton cost, wrong selecton of toolkts, etc. The postve and sgnfcant coeffcent mples that when artsans receve toolkts of hgh qualty they are more lkely to use all of them and experence ncrease n ncome from craftsmanshp. Ths s ntutve and calls for proper choce, desgn and development of the mproved toolkts so that the mproved toolkts are used extensvely and actually contrbute to ncreasng the artsans ncome from craftsmanshp. 7. Conclusons In ths artcle, we have developed a theoretcal model n explanng how exogenous technologcal change may cause wage nequalty n rural areas. The artsans may be benefted due to skll and supply of tool kts. The exstng poverty reducton programmes may have overlooked ths aspect, as they are short run specfc and accordngly devate from the actual stuaton. Sometmes, effectve government nterventons can make the stuaton dfferent(for varous studes addressng ths ssue, see Basu98;Knack and Keefer,997; Granovetter,995;Rodrk,998;Narayan,997;Krshna,00;Grootaert and 30
Narayan,999;North,990; Brd,Graham, and Sabot,998 ; Stgltz,000;,998 and Lucas 998; Esqusvel and Rodrguez-Lopez 003;Gervas et al 05). There are two categores of skll populaton n the rural areas; one wth toolkts and the others are wth out toolkts. The underlyng forces of demand and supply of skll labours may explan by the toolkts technology suppled to them. In such a stuaton the relatve demand for artsans wth toolkts become more attractve. As a consequence, equlbrum wage nequalty ncreases. Ths may be consdered as an equlbrum outcome n the skll category n a rural market settng. The nequalty may dsperse as more and more poor take advantage of the nterventon. The model was verfed wth the help of a farly large number of samples of rural artsans n Inda. The backward class wth skll s the real benefcary due to the ownershp of toolkts. The ownershp of other assets appears to be less sgnfcant whch shows that assets are less lkely to beneft them. Surprsngly, the benefcares are underprvleged and dsadvantaged artsans. The development of sklls and supply of toolkts are strongly related. The result may serve certan nterests n both academc and polcy crcles. 3
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