Urbanization and Returns to Human Capital Investment

Transcription

1 Journal of Economcs, Busness and Management, Vol. 4, No. 2, February 2016 Urbanzaton and Returns to Human Captal Investment Sung Soo Lm 1 Abstract Many developng economes are undergong urbanzaton processes through rural-urban mgraton. One of stylzed facts n mgraton s that educaton s postvely correlated wth mgraton. Ths study nvestgates and tests the underlyng cause of the postve educaton effects. In partcular, usng Heckman s two step procedure, ths study fnds dfferental returns to human captal nvestment across educaton groups n urban areas of Indonesa. The results show that more educated people have a greater ncentve to mgrate to urban areas. Index Terms Urbanzaton, mgraton, returns to educaton, human captal. I. INTRODUCTION Many developng economes are undergong urbanzaton processes through rural-urban mgraton. Emprcal studes of mgraton provde a number of stylzed facts, one of whch s that educaton wll tend to ncrease mgraton. So why s mgraton more lkely for more educated people? In the neoclasscal framework, mgraton occurs f a potental mgrant s expected earnngs n the cty net of her expected earnngs n the vllage and net of the drect costs of mgraton are strctly postve. In fact, the returns to hgher educaton are generally low n the rural areas of most developng countres. Thus, t may be necessary for rural resdents to move to a Metropoltan area to reap the monetary rewards of hgher educaton. An alternatve, yet smlar vew s that ctes are places for accumulatng human captal [1], [2]. Accordng to ths vew, benefts of ctes accrue over tme and the urban wage premum s a wage growth effect rather than a wage level effect. The postve effect of educaton on mgraton may then be explaned by greater ncome growth rates of more educated groups n urban areas. Emprcal studes testng these explanatons are rare, although the dentfcaton of true causes has sgnfcant mportance for polcy makers [3], [4]. To nvestgate and test the valdty of these explanatons, one may compare returns to educaton between urban and rural areas. Hgher returns to educaton or hgher ncome growth rates n urban areas would support the explanatons. For example, between and, the growth of real ncome of male college graduates n ctes was much hgher than that found n rural areas of Indonesa (Table I). In partcular, the mean ncome growth of the former s approxmately 40 percentage ponts hgher thanlatter for males and 15 percentage ponts hgher for female workers wth college educaton n urban areas. However, there are two concerns wth ths test. Frst, hgh urban wages foundn many Manuscrpt receved November 13, 2014; revsed January 24, Sung Soo Lm s wth the School of Busness and Admnstraton, Amercan Unversty n Duba, Meda Cty, UAE (e-mal: slm@aud.edu). countres may nduce low-skll workers to mgrate to low-productvty cty jobs and unemployment, who mght otherwse be more productve n rural sectors [3], [5]. If ths s true, then estmatons of returns to educaton may be msleadng when one smply compares urban and rural wages. Another concern wth ths test s that t s based on an assumpton that mgrants correctly expect ther earnngs post mgraton. However, perceved returns and actual returns to educaton may dffer. For nstance, Jensen [6] fnds that there s dscrepancy between the measured returns to schoolng n the Domncan Republc and the returns perceved by students. Lkewse, returns to educaton perceved by potental mgrants may be dfferent from measured returns of the sample. To crcumvent these ssues, ths study compares, usng Heckman s [7], [8] two step procedure, mgrants post mgraton wages wth what the mgrants would have earned had they not moved, and tests whether mgrants and stayers make ratonal mgraton decsons consstent wth the neoclasscal explanatons of educaton effects. Furthermore, ths study nvestgates the growth rate of mgrants post mgraton wages and tests f t s consstent wth mgraton growth rates of each educatonal group. The results of ths study provde strong evdence for hgher returns to human captal nvestment n urban areas, supportng the explanaton that mgrants are motvated by hgher ncome gans n urban areas. II. SURVEY DATA AND CHARACTERISTICS OF THE SAMPLE POPULATION Indonesa, the fourth most populous naton n the world, has enjoyed rapd economc growth over the past three decades. Furthermore, snce 1980Indonesa has rapdly urbanzed, exceedng many other developng countres n urbanzaton rates. Ths paper uses three waves (1993,, and ) of panel data from the Indonesan Famly Lfe Survey (IFLS), a hgh-qualty panel survey of ndvduals, households, and communtes. The survey contans nformaton from more than 10,000 households representng about 83% of the Indonesan populaton, those who lve n the 13 most populous of the naton s 26 provnces. The IFLS collected a broad array of demographc, socoeconomc, and health nformaton on ndvduals, households, and communtes whle capturng the cultural and socoeconomc dversty of Indonesa. The survey data also contan detaled mgraton nformaton. In partcular, t contans nformaton on each subsequent locaton of resdence for all moves that crossed a vllage boundary and lasted for longer than 6 months. One unque aspect of ths data set s that t contans nformaton on atttudes towards rsk derved from a seres of questons asked n the wave of the IFLS. To measure rsk atttudes, respondents were asked to choose between a DOI: /JOEBM.2016.V

2 Journal of Economcs, Busness and Management, Vol. 4, No. 2, February 2016 sure amount of money and lotteres of varous types. Based on ther answers to these questons, the respondents were classfed nto four groups accordng to ther preferences wth respect to rsky lotteres. Ths drect measure of rsk atttudes allows one to control for the effects of rsk atttudes when analyzng the effects of uncertanty on mgraton decsons. In addton to the IFLS data, ths study utlzes nformaton on travel dstance by a car to major ctes n Indonesa obtaned va Google Maps. The dstance nformaton was collected at the kecamatan level, a subdvson of a cty. TABLE I: MEAN REAL INCOME AND INCOME GROWTH OF MALES AND FEMALES ( AND ) % % change Real Real Income Real Income change - Income - % change - Year Regon Gender college graduates hgh school less than hgh school Urban Male % % Rural 30% 47% Urban % % 1339 Female Rural 46% 162% Source: IFLS 3 & 4, Unt: thousand Rupah 27% 51% 56% 120% Due to data lmtatons on less populated slands, regresson analyses are conducted only for the sample populaton who lve n Sumatra or Java, whch ncludes approxmately 70% of the households n the IFLS. The workng sample conssts of 6696 ndvduals n the 18 to 65 age bracket n, for whom complete nternal mgraton and employment hstores for the and as well as nformaton on other varables of nterest were avalable. Mgrants n ths study are defned to be ndvduals between the ages of 18 and 65 who crossed a vllage boundary to move to urban areas for the frst tme n ther lves between the years and and who stayed n the destnaton for longer than 6 months. III. METHODOLOGY Heckman s self-selecton model recognzes the exstence of measured and unmeasured heterogeneous sklls among agents. Denotng by the log wages of mgrants and by those of nonmgrants, the two earnngs equatons can be wrtten as y y X (1) X, (2) m m m m n n n n where m and n are vectors of exogenous varables. When standard Heckman [7], [8] sample selecton bas correcton formulae are used, the expected values of the wage data for mgrant () and nonmgrant (j) are where E y G 0 X, (3) m m m m m j X E y G 0, (4) j j j n n n n n G s a latent varable that represents gans to mgraton, and m m n, n (5) Unbased estmates of and can be obtaned by OLS only when and respectvely. The selectvty control varables and are denoted as follows. f f m F γ Z γ Z, m, γz 1 F γz where ) s the cumulatve densty functon such that ) = Pr( ) and f s the densty of the normal dstrbuton.predctng the wage gans to mgraton for each educaton group, however, requres the counterfactual earnngs of mgrants of each group. That s, one needs to measure what mgrants would have earned had they not moved.for mgrant, the wage gan equals the expected wage n the mgraton regme less that n the nonmgraton regme, condtonal on the fact that the agent s a mgrant. Followng Davanzo and Hosek [9] and Tunal [10], I obtan the counterfactual wage by means of the consstent estmates of,, and : G 0 X E y n n n n n (6) (7) Thus, a mgrant s expected wage gan from mgraton equals E y G 0 E y G 0, (8) m n whch compares the mgrant s predcted wage n the mgraton regme wth her predcted counterfactual wage n the nonmgraton regme. A nonmgrant s expected wage gan from stayng can also be estmated by n E ym E y G 0 G 0, (9) 145

3 Journal of Economcs, Busness and Management, Vol. 4, No. 2, February 2016 whch compares the nonmgrant s predcted wage n the nonmgraton regme wth her predcted counterfactual wage n the mgraton regme. Comparng the expected gan for each educatonal group, one can nnocuously test f mgrants are motvated by expected ncome gans. TABLE II: COMPARISON OF EARNINGS BETWEEN MIGRATNTS AND STAYERS IN Model 1 Model 2 Model 3 Model 4 Mode 5 Model 6 Dependent Var Income Heckman Heckman Income Heckman Heckman Mgrants Stayers Personal Educatonal mddle school *** 0.297*** 0.321*** (0.796) (1.046) (1.560) (5.405) (8.139) (8.241) hgh school 0.709*** 0.770*** 0.640*** 0.662*** 0.706*** 0.676*** (4.808) (5.010) (2.691) (11.558) (20.185) (17.361) unversty 1.372*** 1.438*** 1.130*** 1.098*** 1.203*** 1.097*** (8.270) (8.295) (4.222) (13.460) (25.005) (19.636) Demographc age *** 0.067*** 0.113*** (1.158) (0.903) (1.015) (6.066) (7.834) (11.140) age squared *** *** *** (-0.677) (-0.538) (-0.504) (-6.496) (-8.314) ( ) female *** *** *** *** *** (-2.670) (-2.642) (1.360) ( ) ( ) ( ) Vocatonal self employed *** 0.356*** 0.268*** (0.988) (0.997) (0.350) (7.005) (8.750) (6.831) government 0.398* 0.404* *** 0.982*** 0.705*** (1.687) (1.736) (1.071) (14.387) (17.978) (11.266) prvate *** 0.554*** 0.445*** (1.037) (1.201) (0.859) (9.284) (13.348) (10.486) Behavoral rsk atttude * (-0.263) (-0.285) (-1.219) (0.106) (1.772) (0.504) rsk atttude * 0.209* * 0.109*** 0.075** (1.716) (1.744) (-0.162) (1.879) (3.599) (2.198) rsk atttude ** 0.325*** 0.193** (-0.049) (0.010) (0.108) (2.214) (5.043) (2.418) Vllage dstance (ln) *** *** *** *** *** *** (-3.174) (-3.238) (-2.705) (-5.157) ( ) (-9.005) Java sland * *** *** *** (0.915) (0.866) (1.698) (-7.261) (-8.650) (-5.474) constant *** *** *** *** *** *** (27.734) (27.769) (12.776) (69.407) (99.590) (67.531) R Inverse mlls rato *** Standard Error * p<0.05, ** p<0.01, *** p<0.001, All standard errors were adjusted for wthn cluster dependence. IV. RESULTS Table II shows that results of earnngs regressons estmated by the Heckman two step procedure. The regresson results of the selecton equatons are presented n the Appendx II. As excluson restrctons, the varable marred s ncluded for probt regressons for both mgrants and stayers. In addton, the varable land s ncluded n the selecton model of mgrants. Intutvely, urban ncome s less lkely to be affected by the possesson of land n rural areas whle t s more lkely to affect the mgraton propenstes. The regresson results are found to be consstent wth ths conjecture. The results show that the coeffcents on the educaton dummes have all expected sgns and magntudes, and the results are consstent across all models. Assumng the coeffcents on the educaton dummes properly estmate dfferental returns to educaton for each educaton group n urban and rural areas, the results appear to be consstent wth the hypothess that college graduates have greater ncentves to mgrate to urban areas n Indonesa between the years and. In partcular, mgrants wth college educaton n have roughly 24% greater returns to educaton than those n rural areas (Model 2 and Model 4). The gan n returns s comparatvely greater than mgrants wth hgh school educaton, and the opposte s true for mgrants wth mddle school educaton. The results are consstent when educaton dummes are replaced wth educaton years although the results are not shown n ths study. On the other hand, as expected, the ncome gans are larger when the selecton bas s not controlled (Model 1 and 3), mplyng the exstence of a selecton bas. One concern wth ths test s that t s based on one perod of tme ( -) and may not justfy the assumpton that mgrants have correct expectatons on ther earnngs post mgraton. Ideally, to justfy the assumpton, one would need data showng hstorcal varatons n returns to educaton as well as changes n mgraton propenstes.ths study nstead utlzes three waves of survey data and tests f there exst greater growth rates n returns to hgher educaton for mgrants, gven that the ncrease n mgraton propenstes between and - s greater for more educated people. Table 3 shows supportve results. A comparson of mgraton propenstes between two 146

4 Journal of Economcs, Busness and Management, Vol. 4, No. 2, February 2016 perods (1993- and -) ndcates that the growth n mgraton propenstes s greater for more educated groups. It shows that one year of educaton s assocated wth a margnal ncrease of mgraton propenstes by 0.2% between and, whch s twce the ncrease n propenstes between 1993 and. On the other hand, the growth n returns to educaton appears to be lower between and, compared wth the growth rate between 1993and. The results are consstent at all educaton levels, regardless of mgrants or stayers. The decrease, however, appears to be much greater for rural stayers than mgrants to urban areas. In other words, there s relatvely a greater ncentve to mgrate to urban areas for more educated people. Results are consstent whether the estmaton models use categorcal varables or contnuous varables for educaton levels. Agan, the results support the hypothess that there s a greater ncentve for mgraton for more educated groups. V. CONCLUSION Overall, the results of ths study support the conjecture that there are greater economc gans from mgraton for more educated people. In partcular, comparng mgrants post wages wth ther counterfactual wages n rural areas, ths study fnds sgnfcantly larger ncome gans for more educated groups. The results of ths study also support the vew that ctes are places for accumulatng human captal [1], [2]. If we adopt ths perspectve, then the coeffcents of educaton varables would be returns on human captal nvestment for each educatonal group. For nstance, each addtonal year of educaton s assocated wth an accumulaton of a 5 tmes greater earnngs premum for mgrants, compared wth rural stayers, durng the perod of and. More ntutvely, for nstance, educated workers may partcularly beneft from skll spllovers n urban areas, where human captal accumulaton s accelerated by a greater share of educated workers (e.g. [2], [10]). On the other hand, ths study fnd no evdence economcally justfyng the rural-urban mgraton of less educated people. In fact, the returns appear to be greater n rural areas. Ths mples that polcy makers need to pay specal attenton to the dfferental returns to human captal nvestment f they are concerned about a rapd urbanzaton. Fnally, whle ths study presents supportve results for the neoclasscal explanaton, there are some caveats to be noted. Ideally one needs to account for confoundng factors such as ambton and motvaton as well as rsk atttudes. Assumng these factors count, the returns to educaton of mgrants may have been somewhat overestmated. In fact, the realty of mgraton decsons may not be as straghtforward as t s explaned by the human captal theory of mgraton. TABLE III: CHANGES IN MIGRATION PROPENSITIES AND RETURNS TO EDUCATION Mgrants to bg ctes Rural stayers Educaton level Trend educaton years Growth n returns to educaton mgraton propenstes mddle school educaton Growth n returns to educaton vs. elementary educaton mgraton propenstes hgh school educaton Growth n returns to educaton vs. elementary educaton mgraton propenstes college educaton Growth n returns to educaton vs. elementary educaton mgraton propenstes APPENDIX I: DEFINITION OF EXPLANATORY VARIABLES AND DESCRIPTIVE STATISTICS Abbrevaton Defnton Dependent Var Mean St.Dev cty00-07 Mgrated to bg ctes between and cty93-00 Mgrated to bg ctes between 1993 and Personal Elementary 1 f educaton s hgher than elementary school (reference) mddle school 1 f educaton s above elementary school but less than hgh school hgh school 1 f educaton s above mddle school but below college Unversty 1 f educaton s hgher than college marred 1 f marred age age n years female 1 f female self employed 1 f self employed government 1 f government worker prvate 1 f prvate worker unpad 1 f unpad famly worker (reference) casual 1 1 f casual worker rsk atttude 1 most rsk averse (reference) rsk atttude 2 rsk averse rsk atttude 3 rsk lovng rsk atttude 4 most rsk lovng Famly famly ncome (ln) logarthm of total famly yearly ncome land possesson 1 f land holders

5 Journal of Economcs, Busness and Management, Vol. 4, No. 2, February 2016 Vllage earnngs gap mean ncome of the closest metro cty 2 mnus that of kecamatan of orgn standard devaton gap Income standard devaton of the closest metro cty mnus that of kecamatan dstance (km) travel dstance by a car to the center of the closest metro cty Java sland 1 f Java sland Source IFLS.* All varables were measured pror to any mgraton except rsk averson and tme preference varables, whch were avalable only n IFLS data. 1) Casual workers are defned to be people who supply servces on an rregular or flexble bass. 2) Ctes wth populaton of one mllon or larger. APPENDIX II: HECKMAN SELECTION MODEL IN EARNING ESTIMATIONS Dependent Var Mgraton=Yes(N=389) Personal coeffcent (t-value) Educatonal mddle school 0.183* (1.785) hgh school 0.457*** (5.094) unversty 0.570*** (4.871) General marred *** ( ) age *** (-2.604) female *** (-6.688) Vocatonal self 0.912** (2.513) gov 0.849** (2.247) prvate 1.153*** (3.179) Casual 0.996*** (2.688) Behavoral rsk atttude (0.174) rsk atttude (0.213) rsk atttude (0.582) Famly Yearly ncome(ln) *** (-3.946) land *** (-4.289) Vllage earngap *** (-2.653) std gap of earnngs (0.848) dstance(ln) *** (-4.044) Java (-1.476) constant 1.311* (1.705) REFERENCES [1] R. R. Lucas, Lfe earnngs and rural-urban mgraton, Journal of Poltcal Economy, vol. 112, no. 1, pp. 29, 2004 [2] E. I. Glaeser and D. C. Mare, Ctes and sklls, Journal of Labor Economcs, vol. 19, no. 2, Aprl, pp [3] B. Mc Cormck and J. Wahba, Why do the young and educated n LDCs concentrate n large ctes? Evdence from mgraton data, Economca, vol. 72, no. 285, pp , [4] Woznak, Why are college graduates more responsve to dstant labor market opportuntes? Unversty of Notre Dame, [5] R. E. Lucas, The effects of proxmty and transportaton on developng country populaton mgratons, Journal of Economc Geography, vol. 1, no. 3, pp. 323, [6] R. Jensen, The (perceved) returns to educaton and the demand for schoolng, The Quarterly Journal of Economcs, vol. 125, no. 2, pp. 515, [7] J. J. Heckman, The common structure of statstcal models of truncaton, sample selecton and lmted dependent varables and a smple estmator for such models, NBER, [8] J. J. Heckman, Sample selecton bas as a specfcaton error, Econometrca: Journal of the Econometrc Socety, pp , 1979 [9] J. D. Vanzo and J. R. Hosek., Does Mgraton Increase Wage Rates?: An Analyss of Alternatve Technques for Measurng Wage Gans to Mgraton, Santa Monca, CA.: Rand, [10] E. I. Glaeser, Learnng n ctes, Journal of Urban Economcs, vol. 46, pp , economcs. Sung Soo Lm was born n South Korea. He receved hs B.A. degree from Unversty of Wsconsn at Madson and hs M.Sc. from Unversty of Illnos at Urbana-Champagn. He also holds hs Ph.D. degree n appled economcs, whch was awarded from Unversty of Mnnesota at Twn Ctes n Dr. Lm s currently an assstant professor of economcs at Amercan Unversty n Duba. Hs man research area s n development 148