Regional and Sectoral Economic Studies Vol (2013)

Transcription

1 Regonal and Sectoral Economc Studes Vol (2013) INDUSTRY AGGLOMERATION AND WAGE DIFFERENTIATION: AN EMPIRICAL STUDY ON TAIWAN S MANUFACTURING INDUSTRY CHEN, Chh Cheng Abstract In ths paper, we applyng the segmented regresson model to test the concept of crtcal mass n the model of agglomeraton externalty by settng agglomeraton degree(ad) as the threshold varable to nvestgate the relatonshp between the ndustry agglomeraton and the wage dfferentaton of employees n Tawan s manufacturng ndustry. Our estmated results prove that there exsts a threshold effect of AD as determnng wage rate of an employee and confrm that the AD of an ndustry can sgnfcantly nfluences the wage rate of an employee, no matter where he/she works. The margnal effect of AD on wage rate s hgher for workers who work outsde the cluster than the nsders n the manufacturng ndustry, as well as n the hgh-tech ndustres. JEL Codes: Keyword: ndustry agglomeraton, wage dfferentaton, segmented lnear regresson, manufacturng ndustry 1. Introducton The mportance of ndustral clusters has been emphaszed by Porter(1990). The most famous example s the Slcon Valley n the Unted States, a ndustry cluster of electronc and computer ndustry. Saxanan(1994) compared the regonal developments between Slcon Valley and Route 128 area n Massachusetts, and conclude that the culture and ndustry organzaton are more open n the former and thus resulted n a better development of computer ndustry after the mcrocomputer revoluton. She also ponted that the agglomeraton externaltes happened because the workers n dfferent companes can exchange ther thoughts and deas easly and convenently speeded up the spllover effects n ths area under ths open atmosphere and the agglomeraton of computer companes. As concernng wth the man sources of agglomeraton economes, Marshall (1920) suggests that the sharng of nputs whose producton nvolves nternal ncreasng returns to scale, the poolng of labor market poolng where agglomeraton allows a better match between an employer's needs and a worker's sklls, and the spllovers n knowledge because the clusterng of frms allowng ther workers to learn from each other. Other theoretcal foundatons for the exstence of agglomeraton externaltes are also dscussed. Fujta et al.(1999) s book heavly rely upon the Dxt-Stgltz model of monopolstc competton that offers a analyss framework to deal wth the effects of ncreasng returns at the level of the ndvdual frm. Fujta and Thsse(2002) further explan the trade-off between varous forms of ncreasng returns and dfferent types of moblty costs. It explores several knds of the formaton of agglomeratons and the dscussed the exstence of mbalance development between regons. Duranton and Puga(2004) provded three types of mcro-foundatons mechansms of urban agglomeraton formaton, such as sharng, matchng, and learnng. Besdes, the effects of ndustral agglomeraton are also Chh Cheng Chen, Assstant Professor, Graduate Program of Socal Informatcs, Yuan Ze Unversty, Tawan. Contactng nformaton: address: No.135, Yuan-Tung Road, Chung-L Cty, Tauyuan County, Tawan. Emal: chhcheng@saturn.yzu.edu.tw.

2 Regonal and Sectoral Economc Studes Vol (2013) mentoned extensvely. For example, Krugman(1991) ponted out that the comparatve advantage of a country mght be changed because of the rses of ndustral productvty resulted from ts ndustral clusters. Henderson(1980) and LaFountan (2005) dscussed the locaton problem of an ndustry or a frm as consderng of effects of ndustral agglomeraton. As for the emprcal evdences on the effects of agglomeraton externaltes for manufacturng ndustres, Beeson(1987) nvestgated the determnants of productvty growth n the manufacturng sector wth specal emphass on the effects of a state's urbanzaton characterstcs on productvty growth. The results showed that no relatonshp s found between urbanzaton and overall productvty growth. Cccone and Hall (1996) focused on the dfferences n labor productvty as concernng wth local geographcal externaltes and wth the dversty of local ntermedate servces whch mght result n aggregate ncreasng returns. They concluded that the average labor productvty ncreases as the degree of employment agglomeraton (employment densty) rses. Cccone(2002) estmated the agglomeraton-effects for European countres and show that ths effect and the elastcty of average labor productvty wth respect to employment densty n these countres were slghtly smaller than the ones n the US. Fnally, Rosenthal and Strange (2003) fnd that the average labour productvty n manufacturng ndustry ncreases as the agglomeraton ncreases. Accordngly, we mght conclude precsely that the agglomeraton externaltes wll rase the labour productvty. As for the nfluences of urban agglomeraton on wage rate, Hansen(1990) ndcated that the agglomeraton economes enhance plants productvty wthn metropoltan area, but frms must pay for these benefts n hgh wages and land costs. Tabuch and Yoshda(2000) estmated the urban wage premum and found that wages mght ncrease by 10% f the cty sze doubles n Japan. Wheaton and Lews(2002) found that workers n the manufacturng sector earn hgher wages when they are n urban labor markets and the wllngness of frms to pay more for equvalent workers n dense markets as evdence of an agglomeraton economy. Glaeser and Mare (2001) and Yankow (2006) found that the agglomeraton premum on wage accountng for a large porton of the urban wage premum as holdng other factors be equal. Wheeler (2006) who shows that urban wage gans are due to more frequent job changes n large ctes rather than to return-to-tenure dfferentals. As for a specfc ndustry, Freedman(2008) showed that clusterng makes t easer for workers to job hop wthn the software sector and earn hgher earnngs levels n more agglomerated areas. He also ponted that agglomeraton mproves labor market coordnaton and facltates greater learnng and human captal formaton. In ths paper, we nvestgate the relatonshp between the ndustry agglomeraton and the wage dfferentaton of employees n Tawan s manufacturng ndustry. LaFountan (2005) theoretcally ponts out that the geographc agglomeraton of an ndustry mght ncrease the productvty of frms whch are located n the same area due to the producton externalty resulted from the economy of cluster, and thus ncrease the wage rate of the employees who are employed by these frms. It also mples that the wage rate of employees n the cluster mght be hgher than the ones who are employed outsde the cluster. We apply the threshold model n econometrcs wth settng the degree of ndustry cluster n dfferent geographc areas as the threshold varable to nvestgate ths hypothess. Our estmated results prove that there exsts threshold effects of ndustry cluster on the wage rate dfferentaton and confrm LaFountan(2005) s theory. 148

3 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry The paper proceeds as follows. The next secton nterprets our emprcal econometrc model used n ths paper. Secton 3 descrbes the data operaton procedures and how we ntegrate the database Industry, Commerce and Servce Census (held n every 5 years) held by the Drectorate General of Budget, Accountng and Statstcs (DGBAS) n Tawan s Executve Yuan n 2001 nto another dataset, the Manpower Utlzaton Survey, whch was also held by DGBAS n 2008 and offered the varable of wage rate of each employee. Secton 4 turns to the emprcal analyss and dscusses the results n lght of theoretcal models. In addton, we wll compare the average wage rate between the employees who work n the area wth a agglomeraton degree lower and upper the threshold crteron. In secton 5 are some the conclusons and suggestons. 2. Methodology In ths secton, we wll dscuss the theory whch s related to the ndustral agglomeraton and wage dfferentaton and the reasons why we propose the econometrc threshold model as our emprcal method. From the dscussons above, t s sure that the agglomeraton externaltes rse up the average labor productvty. Accordng to the subsecton 2.2 n LaFountan(2005), he focus on how the land rent prce n an regon s nfluenced by f the frms n ths regon enjoy the local producton externaltes, a phenomenon exsts when a frm s producton possbltes expand as other frms located n the same regon. Ths type of producton externalty mght result from the knowledge spllovers whch occur as employees n dfferent frms have nformal contact wth each other, or because hgh turnover n local employees. Frms n ths area beneft from the knowledge owned by ts employees who accumulate such knowledge from ther prevous jobs. LaFountan(2005) also ponted out that the producton externaltes are classfed as localzaton externaltes and urbanzaton externaltes. He mentoned that the formers exst when frms beneft from proxmty to smlar frms or other frms n the same ndustry and the latter exst when frms beneft from locatng n a dverse locaton or from proxmty to frms engaged n varety of dfferent ndustres. In ths paper, we only concern about the localzaton externaltes because we are wth specfc nterest on ndustral agglomeraton. After hs calculaton of ths producton externaltes model, LaFountan(2005) ponted out that the frms n an ndustry n a regon wll beneft not only from localzaton externaltes but also from urbanzaton externaltes. Thus, the regonal share of employment n ths ndustry n ths regon wll postvely affect the margnal productvty of labor, whch wll affect regonal wages(whch wll n turn affect regonal demand for land and thus regonal land rents). The ncrease of productvty n ths ndustry ncreases the margnal productvty of labor employed n the ndustry, and thus rases the real wage rate of employees n ths regon. Accordng to the theory proposed by LaFountan(2005), we nfer to that the employees employed by frms located n the regon wth hgher agglomeraton degree wll earn a hgher wage rate as compare wth the counterparts out of the ndustry clustered area because of the exstence of localzaton externaltes whch ncrease the margnal productvty of labor. In other word, the agglomeraton degree of an ndustry n a regon(or an area) would be an mportant factor nfluencng the wage dsparty(or gap) between the employees nsde and outsde the ndustry cluster. In ths paper, we apply the segmented lnear regresson n econometrcs wth settng the degree of ndustry cluster n dfferent geographc areas as the threshold varable and 149

4 Regonal and Sectoral Economc Studes Vol (2013) there exst a(or some) breakpont(s)(or threshold) (or the smlar concept: crtcal mass) to segment the observatons nto dfferent groups, hence, the ndependence varables n dfferent data clusters mght have dfferent nfluences on the dependence varable. The modfcaton why we employ ths econometrc model s related to the ndustral agglomeraton externaltes. agglomeraton externaltes means that frms locate n the same regon (cluster) to receve nformaton spllng over from other frms, to reduce transport costs of nter frm trade, and to enhance the dversty of frms and local products avalable, and hence ncrease ther own productvtes. Harrson and Rodrguzs-Clare(2009) show that there exsts multple equlbra of economc developments under the phenomenon of Marshallan externaltes. If the market sze of an economy s too small to surpass the crtcal mass, thus t wll be dffcult for ts ndustry to generate postve Marshallan externaltes and, hence, be mpossble to change ts comparatve advantage n the nternatonal trade. As dscussng the relatonshp between the Marshallan externaltes and economy development, Carllo and Pugno(2004) assumes that Marshallan externaltes depend postvely on the number of actve frms n the economy. They model a non-lnearty structure of Marshallan externaltes functon by a suggeston n the lterature on economc development: an economy wll accelerate ts overall effcency when t has reached a mnmal sze. 1 In other words, untl the number of frms n an economy has reached a mnmal crtcal threshold value, the Marshallan externaltes ncrease and become postvely related to the number of frms. Accordngly, we argue that, as consderng the Marshallan externaltes n an ndustry cluster area, the agglomeraton externaltes wll be accelerated as long as the degree of agglomeraton surpass a crtcal mass (or the breakpont) and thus enforce the regon to arrve a good equlbrum. Thus, we apply the segmented regresson model as our emprcal method. Segmented regresson analyss are threshold models because some decson must be made concernng what s the approprate threshold at whch to splt the sample. Hansen(2000) ponted out that the threshold models have a wde varety of applcatons n economcs, such as separatng and multple equlbra and sample splttng n cross secton topcs and the threshold autoregressve model n the nonlnear tme seres lteratures. Krugman(1991) and Arthur(1996) proved that there wll be at least two development equlbra n a regon wth Marshallan externaltes. Therefore, t s adequate to apply segmented regresson model to estmate the effects of agglomeraton degree on the wage rate dfferentaton between the employee nsde and outsde an ndustral cluster area. Generally speakng, to nvestgate the relatonshp between the wage rate of an employee and the agglomeraton degree n the area hs/her frm locates, ths paper estmates the followng equaton, w AD ' X, (1) where w s the wage rate of employee, AD measure the level of the agglomeraton degree of where hs/her frm s locates. X s a vector contans other control varables that 1 The mportance of multple equlbra and crtcal mass has been mentoned n Arthur(1994) and other researches whch are focusng on the network effects. 150

5 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry can affect wage rate; s the error term. and are the parameters we are gong to estmate. From our theoretcal model, we know that dfferent levels of regonal agglomeraton degree mght result n dfferent level of wage rate because of agglomeraton externaltes (Marshallan externaltes). To capture ths effect, we can extend equaton (1) nto a nonlnear two regmes threshold model, w ( 1 AD 1 ' X ) L( AD ) (2) ( AD ' X ) L( AD ), 2 2 j where L(.) s the ndcator functon and s the threshold parameter. Ths model permts the regresson parameters ( 1, 1, 2 and 2 ) to swtch between regmes dependng on whether AD s smaller or larger than the unknown threshold value. We apply the endogenous threshold regresson approach proposed by Hansen (2000) to estmate equaton (2). Hansen (2000) provdes an algorthm that searches over value of usng condtonal ordnary least square (OLS) regressons base on a sequental searchng procedure. It also provdes estmates of regresson parameters n the searchng process. Another mportant hypothess whch we care about s that there ndeed exsts the effect of threshold. Another mportant hypothess whch we care about s that there ndeed exsts the effect of threshold. The null hypothess, for example, can be expressed as, H 0 : 1 2 (3) We employ the heteroskedastcty-consstent Lagrange Multpler (LM) test whch s proposed by Hansen (1996) to examne hypothess (3). If the hypothess n (3) s rejected, t s adequate to splt the sample nto two dfferent regmes. 3. Data To estmate the emprcal equaton (2), we have to ncorporate two surveyed databases n Tawan. The frst one s the Industry, Commerce and Servce Census Survey held n every 5 years by the Drectorate General of Budget, Accountng and Statstcs (DGBAS) by Tawan s Executve Yuan n In ths dataset, we calculate the agglomeraton degree(ad) of every two dgtal ndustres n every town n Tawan 2. Then we ntegrate ths varable nto the Manpower Utlzaton Survey dataset, another survey held by DGBAS n 2008 and offered the varable of wage rate of each employee, by ts ndustry and locaton codes. In equaton (2), n addton to AD, we also nclude other explanatory varables accordng to prevous lteratures related to wage dfferentaton, such as gender, age(or work experence), educaton level, martal status, work attrbute (professonal or not), and the frm sze(numbers of employees) n where he/she works. As for the calculaton of AD of frm n town j, we employ the method proposed by Chan et al.(2004), where AD w AS (4) j j j j w j s the employment rato of frm n town j, whch s calculated by 2 Town s the thrd level of geographc admnstratve regon n Tawan. 151

6 Regonal and Sectoral Economc Studes Vol (2013) w j employment employment,, k j k k j (5) and AS j s the total employment of frms n town j except frm and the total employment of frms n the same ndustry located n the neghbor town connected to town j. That s (6) AS employment employment j ~ r ~ j S N j r S where employment r s the employment of frm r n the neghbor town S of town j and N s the set of all neghbor towns. Equaton (4) combnes equaton (5) and (6) as j consderng that the agglomeraton degree of a town should not only nclude the employment of tself but also ts neghbor towns because of the possble spllover effects resulted from the movements of labors between these regons. We calculate ths ndex of every ndustry n every regon they located n. Accordng to the dscusson before, the predcted sgn of AD should be postve, no mater the segment regme upper or lower the threshold. As for other varables, the gender wage gap has, however, persstently been an mportant ssue n modern labor economcs, and several studes have tred to explan the wage gap between males and females by controllng for demographc and productvtyrelated factors. Altonj and Blank(1999) ponted out that the gender s an mportant factor nfluencng the wage dscrmnaton because of employer s preference, the comparatve advantage, and the pre-work nvestment n human captal. Ham et al.(1995) concluded that women n Communst Czechoslovaka earned on average about 70 percent of men s wages n Schafgans(2000) concluded that dscrmnaton favorng men n Malaysa s stll qute prevalent. Kunze(2005) also argued that sex segregaton explans a large porton of wage dfferences and leads to a permanent wage dsadvantage for women. Accordngly, we consder that the gender wll nfluence the wage rate sgnfcantly. In ths paper, we set a worker s gender to be 1 f male and to be 0 f female. Hence, the sgn of gender would be postve. In addton, the age and work experence are consdered as mportant factors whch affect the wage rate sgnfcantly even they mght be hghly correlated and the former often be the proxy varable of the latter. In usual, the elders who work for more years than the younger and earn hgher wage rate because of hs/her hgher productvty resulted from hs/her work experence. Wllams(2009) found that for all male workers, tenure plays a modest role, ncreasng wages by about 1% each year over the frst 10 years on the job. General labor market experence has a larger role, and after 30 years wages have ncreased by about 60%. Munasnghe et al (2008) found that the overall wage return on an extra year of labor market experence s lower for women than men. After ther decomposton analyss, they ponted out that the wage return to job tenure s substantally lower for women than men, and that the wage returns to experence s hgher for women than men. Therefore, the predct sgn of the age(or work experence) varable s postve. As consderng about the nfluence of educaton level on wage rate, a person wth hgher educaton level mght result n a hgher productvty and then earn a hgher return. 152

7 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry Thus, the wage dsparty between workers mght be affected by ther dfference of educaton level. Cortez(2001) argued that the relatve wage return resulted from the hgher educaton level would ncrease the ncome nequalty n Maxco. Gndlng and Sun(2002) proved that the relatve supply of workers wth hgher educaton s the man factor rasng the relatve wages of Tawanese workers wth hgher educaton between 1978 and Neuman and Zderman(2003) found that the vocatonal educaton could rase the wage levels of mmgrants n Israel. Gonzalez(2003) also conclude that the mmgrants wth more US schoolng wll earn more f the returns to US schoolng are greater than the returns to foregn schoolng, holdng total educaton constant. Accordngly, we mght predct that the sgn of estmated parameter of educaton level should also be postve. As for the relaton between the martal status and the wage rate, the stuaton s more complex. Frst, Becker(1991) mentoned that marrage makes men more productve because the marred men have greater opportuntes to specalze n labor market actvtes when ther wves specalze n home producton. Thus, the marrage wage premum reflects a productvty gap between marred and never-marred men. Second, Nakosteen and Zmmer (1987, 1997) argued that marred men are more productve not because they become more productve after marrage, but because they were more productve before marrage. Chun and Lee(2001) concluded that the selecton of hghablty men nto marrage s the cause of the marrage wage premum. As for women, Greenberg Qunlan Rosner(2007) mentoned that the unmarred women and men have lower mean personal earnngs than the marred ones respectvely. Ths means that the marrage wage premum exsts no matter what your gender s. In ths research, we set a worker who s marred s 1 and 0 for whom s not get marred n our data. We thnk that f the martal status of a worker s marred, then he/she wll earn a hgher wage rate and the predct sgn of ths varable should be postve. Fnally, as for the nfluence of frm sze on the wage rate dfferentaton, Krueger and Summers (1988), Brown and Medoff (1989), O and Idson (1999) and Bertola and Garbald(2001) had argued that the larger frms or plants pay hgher wages. Besdes, Meagher and Wlson(2004) also concluded that the plant sze effect for supervsors s at least double that of non-supervsors. In ths paper, we use the employment sze as the frm sze of a worker s frm and dvde the frm sze nto two classes: large and small. Accordng to the defnton of a small and medum enterprses (SMEs) on the number of regular employees defned by Small and Medum Enterprses Admnstraton(SMEA) n Mnstry of Economc Affar n Tawan, the number of regular employees must be less than 200 n the manufacturng ndustry. And n the Manpower Utlzaton Survey, t categorze the total employment of a worker s frm nto 8 level. Frms total employment n 1~199 workers are categorzed nto the frst sx classes. Therefore, we redefne the frm sze of an employee as a dummy varable wth value 1 f hs answer s the 7 th and 8 th category of frm sze. Thus, we also predct the frm sde effects would be postve. In addton, the work attrbute (for example, professonal or not) of a worker should postvely nfluence hs/her wage rate. An expert or a professonal work would earn a hgher wage rage because of hs/her hgher productvty resulted from hs specalzaton. In ths study, we defne a worker who s a professonal worker as 1 and others to be 0 and thus t s ntutve to predct ts sgn of estmated parameter postve. In addton, to fgure out f the agglomeraton externalty n hgh-tech ndustry s sgnfcant n hgh-tech ndustres, we also defne a dummy as Hgh-Tech for a employee who works n 153

8 Regonal and Sectoral Economc Studes Vol (2013) Computer, Communcatons, and Audo and Vdeo Electronc Products Manufacturng and Electronc Parts and Components Manufacturng. In table 1, we lst the basc statstc summary of explanatory varables n whole manufacturng ndustry n Tawan. We also offer the statstc summares of AD of twodgt manufacturng ndustres n Tawan n appendx. Table 2 s the correlaton coeffcents for all explanatory varables. In ths table, we fnd the correlaton coeffcent s very hgh between the hgh-tech ndustry dummy and the AD, whch reflects the clusterng of hgh tech ndustres n Tawan. Table 1 Statstc Summares of Explanatory Varables Varables Mean Maxmum Mnmum Varance Observaton Wage Rate(NT$) Sex(Dummy) AD Frm Sze(Dummy) Hgh-Tech(Dummy) Marrage(Dummy) Educaton(yrs) Experence(yrs) Professonal(Dummy) Table 2 Correlaton Coeffcents between Explanatory Varables Wage Rate Sex AD Frm Sze Hgh_ Tech Marrage Edu caton Expe rence Profes sonal Wage Rate 1 Sex AD Frm Sze Hgh-Tech Marrage Educaton Experence Professonal Emprcal Results We lst our estmated results of whole manufacturng ndustry n table 3. In ths table, we report the results of ordnary least square(ols) estmaton of whole samples wthout consderng the threshold effect n the frst part. As for the second and thrd part, the OLS regresson results of observatons under and upper the threshold value are lst separately wth the estmated threshold value of AD at From the results of heteroskedastcty-consstent Lagrange Multpler (LM) test, t rejects of null hypothess n equaton(3). There are two mplcatons of ths result. In the one hand, t frstly represents that the estmated parameters of AD under and upper the threshold are not equal to each other. Besdes, t also tells us that such a segmented regresson analyss s adequate to dscuss the crtcal mass concept n the theores of agglomeraton externalty. 154

9 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry Besdes, the R-squared values are and n the ndvdual regresson model, whch means that they are acceptable too. Table 3 Parameter Estmaton for the Whole Manufacturng Industry n Tawan Model Wthout Threshold Wth Threshold AD< Wth Threshold AD> Varable Parameter t-value Parameter t-value Parameter t-value Constant 9.108** ** ** Sex 0.314** ** ** Marrage 0.054** ** ** Educaton 0.040** ** ** Experence 0.027** ** ** Experence^ ** ** ** Professonal 0.213** ** ** Hgh-Tech ** ** Frm Sze 0.090** ** ** AD 3.36E-06** E-06* 2.086* 1.08E-06* Observatons R-squared Heteroskedastcty Test (P-Value) 7.33E-18*** Note: *: at 5% sgnfcance level; **: at 1% sgnfcance level. As for the ndvdual varables, most explanatory varables of wage rate determnaton are sgnfcant wth consstent sgns we predcted before, except the one of hgh-tech ndustry dummy. The nsgnfcance of ths estmated parameter s pretty surprsng and counterntutve because Tawan s famous on ts producton of ICT products n global hgh-tech market and s attrbuted to the rse of employees wage rate n Tawan. The reason for ths nsgnfcance mght due to ts low correlaton wth wage rate or the hgh correlaton wth AD n table 2. Besdes, the margnal effects of AD on wage rate nsde and outsde the cluster s dfferent. The margnal effect of AD on wage rate outsde the cluster s hgher than the one nsde the cluster n Tawan s manufacturng ndustry. Ths mght happen because the AD outsde the cluster s relatve low whch results n a hgher margnal effect on wage rate due to the hgher margnal productvty of AD, or the dmnshng returns on wage rate of AD, or the less crowdng out effect whch mght be much serous nsde the cluster resulted from the negatve nfluence of space congeston n manufacturng ndustry. The effect of sex varable on wage rate outsde the cluster s larger than the one nsde the cluster, whch means that the level of wage dfferentaton n average between males and females outsde the cluster s hgher than one nsde the cluster. The former mght reflects the natural dfference of mental structure between the males and females. The lower wage dfferentaton n average between the males and females employees nsde the cluster mght happen because the potentals of females mght be stmulated by the agglomeraton externalty and shorten the range of wage dfferentaton. In addton, the estmated results of marrage varable of employees who work nsde the cluster s hgher than the one outsde the cluster, whch mean that, from the vew that persons who get marred are more productve and thus earn hgher money, wth the agglomeraton externalty, the frms nsde the cluster are more possble to offer a hgher wage rate for the marred persons. Fnally, the quadratc form estmated result of work experence on wage rate s also worthy emphaszed. The negatve sgnfcance of squared experence 155

10 Regonal and Sectoral Economc Studes Vol (2013) mples a dmnshng margnal return for work experence on employees wage rate n manufacturng ndustry n Tawan. We have mentoned that the dummy varable of hgh-tech ndustry n the whole manufacturng ndustry s not sgnfcant n table 3. Therefore, we further subgroup the samples who works n the ICT ndustry and estmate the parameters n equaton(2) ndependently. The estmated results are lst n table 4. The test results of heteroskedastcty-consstent Lagrange Multpler (LM) rejects of null hypothess n equaton(3) too, whch means that the threshold regresson s also sutable for estmaton the data n ICT ndustres. The R-squared values are also acceptable wth values at and As for the threshold pont, t s , a value much hgher than the counterpart n the whole manufacturng ndustry. Table 4 Parameter Estmaton for the Hgh-Tech Industry n Tawan Model Wth Threshold Wthout Threshold Wth Threshold AD< AD> Varable Parameter t-value Parameter t-value Parameter t-value Constant 8.960** ** ** Sex 0.213** ** ** Marrage 0.060** ** ** Educaton 0.057** ** ** Experence 0.024** ** ** Experence^2 3.31E E ** Professonal 0.200** ** ** Frm Sze 2.45E E E E AD 1.55E-06* E-06** E-06* Observatons R-squared Heteroskedastcty Test (P-Value) 3.42E-06*** Note: *: at 5% sgnfcance level; **: at 1% sgnfcance level. We fnd that estmated parameters of most varables are sgnfcant and are consstent wth the predcted sgns we dscussed before, except the varable of experence square and the frm sze. The nsgnfcance of parameter of experence square, whch s dfferent from the estmated result n table 3, means that work experence n hgh-tech ndustry doesn t result n dmnshng margnal returns on wage rate. Besdes, the nsgnfcant estmated resulted of frm sze n table 4 s also dfferent from the one n table 3, whch s also dfferent from the results n prevous studes. The reason here mght attrbute to that the frms our sampled employees work n are large one n hgh-tech ndustres n Tawan, whch could not nfluence the wage rate effectve, no matter they located nsde or outsde the cluster. The hgher level of wage dfferentaton n average between males and females outsde the cluster s also hold here, but the dfference s much shortened. Fnally, n table 4, both of the margnal effects of AD on wage rate nsde and outsde the cluster are sgnfcant, but the one n the outsder of cluster area s stll hgher than the one n the nsder. The reasons for ths phenomenon are smlar to the arguments mentoned above n explanng the n manufacturng ndustry. As comparng ther dfference wth the counterpart n table 3, the range of these two parameters n hghtech ndustres s smaller than the one n manufacturng ndustry. The lower margnal 156

11 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry effects of AD outsde the cluster n hgh-tech ndustres, as comparng wth the effects n manufacturng ndustry, mght due to the lower margnal productvty of AD because of hgher dmnshng margnal returns. And the hgher margnal effects of AD n the hghtech cluster than the one n the manufacturng ndustry cluster mght come from the stronger agglomeraton externalty and the less crowdng-out effects n hgh-tech cluster. Fnally, we compare the average wage rate of employees who work nsde and outsde the cluster wth the threshold crteron estmated n table 3 and 4. We lst the results n table 5. In manufacturng ndustry, we fnd that the average wage rate of employees nsde the cluster s hgher than the one n outsde wth the magntude of NT$ The t-value and p-value of test results support our argument before. The stuaton s smlar to the hgh-tech ndustry. The average wage rate nsde the cluster s also sgnfcantly hgher than the one of outsder accordng to the sgnfcance of t-value and p-value, even through the magntude s smaller than n manufacturng ndustry. Thus, we conclude that the agglomeraton externalty resulted from the ndustry agglomeraton n regons(areas) could consequently results n the wage dfferentaton between employees who works nsde and outsde the cluster, accordng to the emprcal results here. Furthermore, the threshold values, whch represent the concept of crtcal mass, should be consdered n the analyss model of agglomeraton. Table 5 The Average Rate n the Subsamples Under and Upper the Threshold Value Manufacturng Industry Hgh-Tech Industry Group Observatons Mean Std. Err.Observatons Mean Std. Err. Total AD< AD> AD< AD> Dfference ** * t-value t = t = Ho: Dfference = 0 Pr(T > t) = Pr(T > t) = Note: *: at 5% sgnfcance level; **: at 1% sgnfcance level. 5. Conclusons and Suggestons In ths paper, we apply the segmented regresson analyss to nvestgate the relatonshp between the geographcally ndustry AD and the wage rate dfferentatons of employees n Tawan s manufacturng ndustry and hgh-tech ndustres n Tawan. We get the regonal AD of every Tawan s employee n the two-dgt manufacturng ndustres by calculatng the geographc AD of each town n every ndvdual ndustry from the Industry, Commerce and Servce Census frstly, and then nvolve these data n the Manpower Utlzaton Survey wth the data of each employee by matchng the twodgt ndustres and locaton n whch an employee s frm belong to. Accordng to our emprcal results, the factors resultng n the wage dfferentaton nclude the gender, educaton level, marrage status, work experence, the frm sze and the AD of an employee. Our results also confrm LaFountan (2005) s theory that the geographc agglomeraton of an ndustry could ncrease frms productvty n the cluster and thus ncrease the wage rate of the ther employees. Furthermore, we confrm that the 157

12 Regonal and Sectoral Economc Studes Vol (2013) wage rate of employees n the cluster mght be hgher than the ones who are employed outsde the cluster. The exstence of the threshold values from the estmated results n segmented regresson model mples the mportance of consderng the crtcal mass n a model wth agglomeraton externalty. In addton, our estmated results that margnal effects of AD on wage rate outsde the cluster are hgher than the ones nsde the cluster are counterntutve, but we thnk such results mght be reasonable as consderng the prncple of dmnshng margnal return. One shortage n ths research s that the lag perod of AD the Industry, Commerce and Servce Census from the Manpower Utlzaton Survey. For further researches, t would be better to use the new survey of Industry, Commerce and Servce Census held by DGBAS n Tawan n Besdes, n ths paper, we concern about the localzaton externaltes only as the defnton of AD, but the concept of urbanzaton externaltes n an ndustry cluster s also mportant n the lteratures of geographc agglomeraton. Thus, the researches n the future could take t nto consderaton and dscuss ts nfluence on the wage rate. Fnally, the congeston effects resulted from the agglomeraton of ndustres mght domnate the postve externalty trggered by agglomeraton. Thus, how to nvolve ths concept n practce s also worthy for further dscussng. References Altonj, J. G. and Blank, R. M.(1999), Race and gender n the labor market, In O. Ashenfelter and D. Card(ed), Handbook of Labor Economcs: 3C, Arthur, B.(1994), Increasng Returns and Path Dependence n the Economy, Ann Arbor: Unversty of Mchgan Press. Becker, G. S. (1991), A Treatse on the Famly, Cambrdge, MA: Harvard Unversty Press. Beeson, P. E. (1987). Total factor productvty growth and agglomeraton economes n manufacturng, , Journal of Regonal Scence, 27 (2), Bertola, G. and Garbald, P.(2001), Wages and the sze of frms n dynamc matchng models, Revew of Economc Dynamcs, 4(2), Brown, C. and Medoff, J. (1989), The employer sze-wage effect, Journal of Poltcal Economy, 97, Carllo, M. R. and Pugno, M.(2004), The underground economy and underdevelopment, Economc Systems, 28(3), Chan, L. Y., Chang, M. C. & Hsu, C. C. (2004), Vertcal dsntegraton and ndustry agglomeraton n Tawan s manufacturng sector, Tawan Economc Revew, 32(4), (In Chnese). Chun, H. and Lee, I.(2001), Why do marred men earn more: productvty or marrage selecton?, Economc Inqury, 39 (2), Cccone, A. and Hall, R. E.(1996), Productvty and the densty of economc actvty, Amercan Economc Revew, 86(1), Cccone, A.(2002), Agglomeraton effects n Europe, European Economc Revew, 46(2), Cortez, W.W., (2001), What s behnd ncreasng wage nequalty n Mexco, World Development, 29(11), Duranton, G. and Puga, D.(2004). Mcro- foundatons of urban agglomeraton economes, n Henderson and Thsse (ed.), Handbook of Regonal and Urban Economcs, Chapter 48,

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15 Chen,C.C. Industry Agglomeraton and Wage Dfferentaton n Tawan s Manufacturng Industry Appendx: The Statstc Summares of Agglomeraton Degree n Two-Dgt Manufacturng Industres n Tawan n 2001 Industry Observatons Mean Mnmum Maxmum Varance Food and Beverage Manufacturng Textles Mlls E+07 Apparel, Clothng Accessores and Other Textle Product Manufacturng E+07 Leather, Fur and Alled Product Manufacturng Wood and Bamboo Products Manufacturng Furnture and Fxtures Manufacturng Pulp, Paper and Paper Products Manufacturng Prntng and Related Support Actvtes E+07 Chemcal Materal Manufacturng Chemcal Products Manufacturng Petroleum and Coal Products Manufacturng Rubber Products Manufacturng Plastc Products Manufacturng E+07 Non-metallc Mneral Products Manufacturng Basc Metal Industres E+07 Fabrcated Metal Products Manufacturng E+07 Machnery and Equpment Manufacturng and Reparng E+08 Computer, Communcatons, and Audo and Vdeo Electronc Products Manufacturng E+08 Electronc Parts and Components Manufacturng E+08 Electrcal Machnery, Supples and Equpment Manufacturng and Reparng E+07 Transport Equpment Manufacturng and Reparng E+07 Precson, Optcal, Medcal Equpment, Watches and Clocks Manufacturng Other Industral Products Manufacturng Total E+08 Note: Accordng to the 7 th modfcaton of Standard Industral Classfcaton of Tawan n