Human Capital and Regional Economic Growth in Slovenia

Transcription

1 Human Captal and Regonal Economc Growth n Slovena Matjaž Novak and Štefan Bojnec Unversty of Prmorska Slovena Ths artcle presents the emprcal results concernng the economc growth n Slovena at the aggregate and muncpaltes level for the years Both the aggregate and the regonal crosssectonal-tme seres data are used to econometrcally test the sgnfcance of labour reallocaton on the nature of the economc growth n Slovena. The emprcal results confrm the mportant contrbuton of human captal to economc growth, whle the uncompleted process of sectoral labour reallocaton has negatve mpact on the growth of the total factor productvty n the Slovenan economy. The comparson of the estmated parameters of both the stochastc fronter producton functon and the average producton functon clearly ndcates an neffcent use of human captal n the Slovenan economy durng the analysed perod. INTRODUCTION Prevous studes of the economc performance and growth of the Slovenan economy durng the transton to a market economy rases an nterestng theoretcal and emprcal queston regardng the role of human captal. Orazem and Vodopvec (1995) confrmed the wnners and losers assocaton as wnners returns to educaton and to a lesser extent to experence. Bojnec and Konngs (1999) provde an analyss of job creaton and job destructon at the mcro-level n comparson wth some other transton countres. Bojnec at al. (2003) speak about the crucal role of human captal for the ntersectoral moblty of labour among agrculture, ndustry and servces. Bojnec (2003) found that the dfferences n the level of economc development n Slovena are due to the regonal locaton wth assocated economc and human captal structures. Novak (2004) speaks about the mportant contrbuton of human captal to the aggregate economc growth, but wth a negatve nfluence on the growth of total factor productvty. In ths artcle we present the emprcal results on the nature of economc growth n the Slovenan economy at the aggregate and muncpaltes level for the perod The research was conducted on 15

2 Matjaž Novak and Štefan Bojnec 16 the bass of the aggregate cross-sectoral-tme seres data. Addtonally, we tested the sgnfcance of labour reallocaton on the nature of economc growth n the Slovenan economy usng the regonal-cross-sectonaltme seres data. The n-depth analyss at the muncpalty level was necessary to obtan a suffcent number of observatons for testng statstcal sgnfcance of the parameters assocated wth the labour reallocaton on the nature of economc growth. For the perod , the tme seres data offer only 7 observatons. Muncpaltes dsaggregated data offer observatons for the varables analysed by 174 Slovenan muncpaltes, whch provde the approprate database for a robust statstcal estmatons. Hence, the dsaggregated data by muncpaltes enable us to nvestgate the characterstcs of the economc growth n Slovena durng the second stage of transton. We used the stochastc fronter producton functon and the average producton functon. We confrmed the mportant contrbuton of human captal to economc growth. We also confrmed that there s an uncompleted process of sectoral labour reallocaton whch s the man factor for a negatve contrbuton of human captal to the growth of total factor productvty n the Slovenan economy. The comparson of the estmated parameters of the stochastc fronter producton functon and the average producton functon clearly ndcates an neffcent use of human captal. The followng secton brefly ntroduces a theoretcal background on the role of human captal n realzng economc growth. In the next secton we present the methodology used for analysng the role of human captal and the nature of economc growth n Slovena between the years 1996 and The fnal secton concludes wth the man fndngs. THEORETICAL BACKGROUND ON THE ROLE OF HUMAN CAPITAL IN REALIZING ECONOMIC GROWTH Human captal s defned as a factor of economc growth, whch captures the abltes, sklls and knowledge of workers (Romer 1994). It plays a dual role n the process of economc growth. Frst, t s a factor of producton and second, t s a source of nnovaton (Mncer 1989, 1). The human captal lterature s dchotomsed between two basc frameworks. Frst, the Becker s (1964) theory of human captal, whch was further developed by Lucas (1988). They frst emphasze that human captal s an alternatve source of sustaned growth (smlar to the technologcal progress). Ths approach, whch s used also n our emprcal analyss,

3 Human Captal and Regonal Economc Growth n Slovena s based on the dea that accumulaton of human captal s crucal for economc growth. Second, there s the Schumpeter s growth lterature, whch was ntally developed by Nelson and Phelps (1966) that hghlghts the mportance of human captal stock (and not ts accumulaton) for economc growth. Regardless of whch theoretcal framework s used, human captal can be regarded as a producton factor and hence can be smply bult nto the model of economc growth (producton functon). The most popular n the emprcal lterature on human captal and economc growth n advanced market economes are growth regressons proposed by Barro and Sala--Martn (1995), emprcal analyss conducted by Mankw, Romer and Wel (1992) and researches by Benhabn and Spegel (1994). There exsts also a body of lterature and emprcal analyss on the role of human captal n transton countres. Conventonal wsdom holds that transton countres are well endowed wth human captal. Ths s consstent wth Barro and Lee (2001) who state that most human captal ndcators are placed better n transton countres than n OECD countres. But Boer (2000) was the frst to argue that the sklls acqured are over specalsed what consequently lowers labour force moblty across ndustres. Our analyss s based on the Lucas s (1988) framework. For calculatng the human captal varable we use a conventonal methodology that measures t n terms of an effectve labour force as follows: x 1 = HKI L, where (1) k HKI = W j K j, (2) j=1 where symbols mean: x 1 varable that measures the amount of human captal expressed n terms of effectve labour force used for producton, HKI human captal ndex, L labour force expressed as number of employees, w j coeffcent of relatve real wage for j-th level of acqured educaton, K j share of employed people (labour force) wth j-th level of acqured educaton. Usng ths approach we combne two separate explanatory varables (labour force and human captal) n one common explanatory varable named as effectve labour force. 17

4 Matjaž Novak and Štefan Bojnec 18 ESTIMATION OF AVERAGE AND STOCHASTIC FRONTIER PRODUCTION FUNCTIONS The role of both human captal and the nature of economc growth s deducted by the comparson of the estmated producton functon coeffcents, partcularly of elastcty of output wth respect to human captal. However, there exst two dfferent producton functon frameworks used for economc analyss: frst, the average producton functon framework and second, the margnal stochastc fronter producton functon framework. The advantage of the stochastc fronter model s that t consders neffcency and random dsturbances as a reason why producton at a certan moment n tme s not at the technologcal fronter. On the other hand, the average producton functon approach assumes that producton s at the technologcal fronter. Hence, ths approach does not dstngush between technologcal progress and effcency gans when explorng the reasons why the total factor productvty s changng. We can use ths dfference for detectng a possble neffcency n producton. Namely, f there exsts a large dfference between the estmated coeffcents of the stochastc fronter producton functon and the aggregate producton functon, the producton factor s not used effcently. For answerng ths queston we estmated the aggregate producton functon as defned n equaton 3. Frst, we estmated t as an average producton functon usng a convenent ordnary least square (OLS) estmator for panel data. Second, we estmated the same model as margnal stochastc fronter producton functon. y = [( β 0 x β 1 1 xβ 2 2 ) exp(ε) ] where symbols mean: y varable that measures the amount of produced output, β 0 constant term that expresses the level of total factor productvty, x 1 varable that measures the amount of used producton factor human captal, β 1 coeffcent of elastcty, x 2 varable that measures the amount of used producton factor physcal captal, β 2 coeffcent of elastcty, ε error term. The stochastc producton fronter models were ntroduced frst by Agner, Lovell and Schmdt (1977) and Meeusen and van den Broeck (3)

5 Human Captal and Regonal Economc Growth n Slovena (1977). The nature of the stochastc fronter producton functon can be best deducted from the average producton functon model (lke n equaton (3)) that s approprate only for economes wthout neffcency. A fundamental element of the stochastc fronter producton functon s that an economy produces less than t mght due to neffcency. The producton functon that consders ths standpont s specfed as follows: y = [( β 0 x β 1 1 xβ 2 2 ) exp(ε) ] δ (4) where symbols mean: y varable that measures the amount of produced output, β 0 constant term that expresses the level of total factor productvty, x 1 varable that measures the amount of used producton factor human captal, β 1 coeffcent of elastcty, x 2 varable that measures the amount of used producton factor physcal captal, β 2 coeffcent of elastcty, ε error term. δ term of techncal neffcency. δ must be n the nterval (0, 1). If δ = 1 than the economy s achevng the maxmum output wth technology emboded n the producton functon (see equaton (4)). Snce output s assumed to be strctly postve, the degree of techncal effcency s also assumed to be strctly postve. Takng the natural logarthms of equaton (4) and defnng yelds: ln(y) = [ln(β 0 ) + β 1 ln(x 1 ) + β 2 ln(x 2 ) +ε] u (5) Note: Defntons of symbols are reported n equaton 4. Snce u s subtracted from ln(y) the restrcton 0 < δ 1 mples that u 0. For estmatng the parameters of the stochastc fronter producton model (and also the average producton functon wth the OLS estmator) we used the statstcal package Stata 8 that provdes the Maxmum-lkelhood estmator for tme-nvarant and tme-varyng decay stochastc fronter producton functon model for truncated-normal random varable u d N + (µ,σ 2 µ). Table 1 presents the estmated results. The frst column summarses estmates of the average producton functon usng the OLS estmator and the second column reports estmates of the margnal stochastc fronter 19

6 Matjaž Novak and Štefan Bojnec 20 TABLE 1 Econometrc estmates of aggregate average and aggregate margnal stochastc fronter producton functons (1) (2) (3) ε y1,x ε y1,x β ε y1,x 1 +ε y1,x Note: Column headngs as follows: (1) aggregate average producton functon, (2) aggregate margnal stochastc fronter producton functon, (3) aggregate average producton functon (results from our earler analyss, Novak 2003). ε y1,x 1 coeffcent of elastcty of output wth regard to human captal, ε y1,x 2 coeffcent of elastcty of output wth regard to physcal captal, β 0 constant term. Source: Own calculatons. producton functon usng the Maxmum-lkelhood estmator for the tme-nvarant model. A comparson of the results of the estmated average and stochastc fronter producton functon does not ndcate any large dfferences. We could make an asserton that persstent dfferences are due to dfferent estmators used. But of specal nterest are ratos of estmated parameters. The estmated parameters related to human captal n the average producton functon are n both cases hgher than the estmated parameters related to physcal captal. Yet, the estmated parameters of the margnal stochastc fronter aggregate producton functon exhbt opposte values. The estmated parameter related to physcal captal s hgher than the estmated parameter related to human captal. The detected dfferences are qute mportant from an economc pont of vew. We are namely faced wth two dfferent measures of economc polcy wth the objectve to acheve a faster economc growth. If our startng ponts are estmates of the average producton functon we wll support the growth of human captal as n ths case the ncrease of human captal by 1% s assocated wth the ncrease of output by 0.507% and the ncrease of physcal captal by 1% s assocated wth the ncrease of output by only 0.312%. But f our startng pont are estmates of the aggregate stochastc fronter producton functon the advce for polcy makers wll be exactly opposte. In ths case the ncrease of physcal captal wll be a more approprate measure of economc polcy wth an objectve of hgher economc growth. The ncrease of physcal captal by

7 Human Captal and Regonal Economc Growth n Slovena TABLE 2 Estmates of growth accountng (1) (2) (3) δ γ y Note: Column headngs as follows: (1) aggregate average producton functon, (2) aggregate margnal stochastc fronter producton functon, (3) aggregate average producton functon (results from our earler analyss, Novak 2003). δ contrbuton of human captal to economc growth n %, γ contrbuton of physcal captal to economc growth n %, y 2 contrbuton of total factor productvty to economc growth n %. Source: Own calculatons. 21 1% s assocated wth the ncrease of output by 0.501%, whereby the ncrease of human captal by 1% s assocated wth the ncrease of output by only 0.321%. The receved results are nterestng also because of the decreasng returns to scale n both producton functon models (average and margnal stochastc fronter). Ths swap of the estmated coeffcent that depends on the selected framework of producton functon, reflects an neffcent use of one or both producton factors. Foundatons for ths statement arse from the methodologcal futures of the margnal stochastc fronter model compared wth the average producton functon. As we have hghlghted, there s no dstncton between technologcal progress and techncal effcency wthn the average producton functon framework. It s assumed that producton factors are used effcently. Ths s not the case wthn the framework of the stochastc fronter producton functon that permts also neffcency. The exstence of neffcency s demonstrated by the dstance of the actual producton from the producton fronter. Increasng neffcency reduces the value of estmated elastcty coeffcents of output related to the producton factor that s used neffcently. In our case the hghest value of the coeffcent of elastcty of human captal s sgnfcant n the average producton functon framework that postulates ts effcent use. It s lower than the relevant coeffcent of elastcty, whch s estmated wthn the stochastc fronter framework. Therefore, we confrm that human captal s the producton factor that s used neffcently n the Slovenan economy. Due to ths, we appled the growth accountng analytcal framework, whch was based on

8 Matjaž Novak and Štefan Bojnec estmated parameters of the average aggregate producton functon and the stochastc fronter aggregate producton functon. Results are summarsed n table 2 (on p. 21). As we can see from the recorded results, the contrbuton of physcal captal to economc growth (approxmately 56%) remans constant, regardless of whch producton functon framework s used. Ths s obvously not the case for the contrbuton of human captal to economc growth that s sgnfcantly smaller than wthn the stochastc fronter framework. Ths ndcates that there exsts a potental for a more effcent use of human captal that wll also rase ts contrbuton to economc growth. 22 STRUCTURAL AND STANDARDISED COMPONENT OF AGGREGATE PRODUCTIVITY GROWTH From the comparson of the estmated parameters of the average and the stochastc fronter producton functons and the belongng results from the growth accountng equatons we can conclude that durng the perod human captal (as a producton factor) was used neffcently. That was the man reason for the decreasng returns to scale at the aggregate level. Ths fact rases a queston about the man reasons leadng to the neffcent use of human captal n the Slovenan economy. Some results from our earler analyss (Novak 2003) ndcate that ths could be related to the unrealsed process of sectoral labour reallocaton towards more propulsve ndustres wth greater labour productvty n terms of value-added per employee. As we have found out, one of the key characterstcs of structural adjustments that occurred n Slovena between the years 1996 and 2002 s that there was only a margnal change n the labour reallocaton from less productve ndustres (decreasng ndustres) towards more productve and propulsve ones. In 1996 about 61% of labour was employed n ndustres wth the average productvty that was lower than the average productvty n the Slovenan economy as a whole. By 2002 ths share had fallen to approxmately 60%. The requred structural change of labour reallocaton and adjustment had obvously not been realsed suffcently durng the analysed perod. McCombe (1991, 70 85) argues that the unfnshed process of sectoral reallocaton of labour could negatvely nfluence the growth of aggregate productvty, whch s the man source of the ntensve nature of economc growth. We followed hs methodology and decomposed the growth rate of aggregate productvty n the Slovenan economy durng

9 Human Captal and Regonal Economc Growth n Slovena the perod nto the structural component that measures the contrbuton of sectoral reallocaton of labour to the growth of aggregate productvty and nto the standardsed component that measures the contrbuton of other factors to the growth of aggregate productvty. Usng McCombe s methodologcal framework, we express the level of the aggregate productvty at tme t n terms of sectoral components as (1991, 73): P t = Q,t E t = P,t a,t, where (6) P,t = Q,t E,t and (7) a,t = E,t E t, where symbols mean: P t level of average productvty at the aggregate level at tme t, Q,t level of output n -th ndustry at tme t, E t level of employment n a whole economy at tme t, P,t level of average productvty n -th ndustry at tme t, a,t share of employment of sector n total employment at tme t, E,t level of employment n ndustry at tme t. Moreover, the average annual growth rate of the aggregate productvty s defned as a geometrc average of an ndex wth a base year and the total number of years n the analysed perod: P k p = T T, (9) P 0 (8) 23 where symbols mean: k p coeffcent of the average productvty growth between 1996 (t = 0) and 2002 (t = T = 7), T termnal year of observaton (T = 7), P T level of the average aggregate productvty n the termnal year of observaton (T = 7), P 0 level of the average aggregate productvty n the base year of observaton (t = 0). Takng the logarthms of (9) and rearrangng the (6) wth (7) and (8), the average annual growth rate of productvty of the whole economy s defned as (McCombe 1991, 73):

10 Matjaž Novak and Štefan Bojnec ln ( ( ) [ ( ) ) 1 k p = ln T P,T a,t ln 24 ( )] P,0 a,0 = p, (10) where symbols mean: k p coeffcent of the average productvty growth, T termnal year of observaton (T = 7), P,T level of the average productvty of sector n the termnal year of observaton, a,t share of employment sector n total employment n the termnal year of observaton, P,0 level of the average productvty of sector n the base year of observaton, a,0 share of employment of sector n total employment n the base year of observaton, p annual exponental growth of the average aggregate productvty. Fnally, the growth of the aggregate productvty s dchotomsed nto two components: the standardsed and the structural (McCombe 1991, 74): ( ) {[ ( ) ( )] 1 p = ln T P,T a,0 ln P,0 a,0 + [ ln ( ) P,T a,t ln defntons of symbols are reported n equaton 10. ( )]} P,T a,0, (11) The standardsed growth s defned as the aggregate productvty growth that would have occurred f all sectors had experenced the same growth rate of employment,. e. f ther employment had grown at the same rate as that of the total employment. Ths component s expressed n the frst square brackets. The structural component of the aggregate productvty growth s caused by the labour reallocaton from less productve towards more propulsve ndustres, whch s leadng to the changes n the sectoral structure of employment n the natonal economy. As the propulsve sectors,. e. ndustres wth labour productvty that s greater than the average labour productvty n the whole economy, were regarded the followng ndustres accordng to NACE classfcaton: CA Mnng and quarryng of energy materals, CB Mnng and quarryng

11 Human Captal and Regonal Economc Growth n Slovena TABLE 3 Data used for calculatng the standardzed and structural components of the aggregate productvty growth n the Slovenan economy between the years 1996 and 2002 ln P,T a,0 ln P,0 a,0 ln P,T a,t T Note: Meanng of symbols s reported n equaton (10). Source: Own calculatons. not energy materals, DE Manufacturng of paper, publshng and prntng, DG Manufacturng of chemcals products and man-made fbres, E Electrcty, gas and water supply, I Transport, storage and communcaton, J Fnancal ntermedaton, K Real estate, rentng and busness actvtes, L Publc admnstraton and defence, M Educaton, N Health and socal work, O Other socal and personal servces. Note that the results can be based towards government polces and assocated polcy transfers that had been n place pror to the Slovenan accesson to the European Unon (EU). As dgressve (or declnng, lackng behnd) were regarded those ndustres, whch experenced a labour productvty that was lower than the average productvty of the whole economy. The data needed for calculatng the standardzed and structural components of the aggregate productvty growth n the Slovenan economy are summarsed n table 3. Usng the data from table 1 we calculated the structural and standardzed components of the aggregate productvty growth accordng to equatons (12) and (13) as follows: p = p st + p s (12) [ ( ) ( )] = 1 T ln P,T a,0 ln P,0 a,0 + 1 T [ ln ( ) P,T a,t ln ( )] P,T a,0 (13) 25 = 1 7 [ ] + 1 [ ] 7 = , where symbols mean: p st the structural component of the aggregate productvty growth, p s the standardsed component of the aggregate productvty growth. Source: Own calculatons.

12 Matjaž Novak and Štefan Bojnec 26 The obtaned results support our hypothess on the deteroraton n the sectoral structure of labour n the Slovenan economy durng the perod Ths s partcularly revealed by the negatve contrbuton of the structural change of labour to the aggregate factor productvty growth. On the bass of the presented emprcal results of the estmated average and stochastc fronter producton functons, extended wth the growth accountng framework and the standardsed and structural component of the aggregate productvty growth we can now explan the nature and causes of the growth of the Slovenan economy between the years 1996 and The prevaled extensve nature of the economc growth was charactersed by the decreasng returns to scale that was the consequence of an neffcent use of human captal. The man reason for ths neffcent use of human captal was the unfnshed process of sectoral labour reallocatons. We clearly confrm that the labour force wth the emboded technologcal knowledge (. e. human captal) remans allocated neffcently across ndustres. IMPACT OF SECTORAL LABOUR REALLOCATION ON THE NATURE OF ECONOMIC GROWTH Fnally, ths paper deals wth the problem of testng the sgnfcance of the mpact of sectoral labour reallocaton on the nature of economc growth. For conductng ths test we needed a suffcent number of observatons for both, the varable that expresses the nature of economc growth and the varable that expresses labour reallocaton towards propulsve ndustres. For satsfyng ths crteron we extended our emprcal analyss from the cross-sectoral-tme seres analyss to the regonal-crosssectoral-tme seres analyss. Hence we estmated the stochastc fronter producton functons together wth the belongng growth accountng equatons for 147 Slovenan muncpaltes. On ths bass we calculated a coeffcent of the sectoral labour reallocaton for each Slovenan muncpalty. Our objectve s to explan the nature of the Slovenan economc growth durng the analysed perod. We have tred to fnd out f there exsts a sgnfcant mpact of labour reallocaton across ndustres on the extensve nature of economc growth n the Slovenan economy. We use estmates of the coeffcent of correlaton, the coeffcent of elastcty and the estmates of odds ratos from the logt model. The theoretcal specfcatons used n the emprcal nvestgaton are explaned below.

13 Coeffcent of correlaton Human Captal and Regonal Economc Growth n Slovena r = [(x 3 x 3 )(y 2 ȳ 2 )] (n 1)σ x3 σ y2 (14) Elastcty model y 2 = α 0 x α 1 3 exp(e)/ln ln(y 2 ) = ln(α 0 ) +α 1 ln[x 3 ] + e (15) Logt model ( ) P(y3 = 1 x L r = 3 ) = β 0 + β 1 x 3 + e (16) 1 P(y 3 = 1 x 3 ) Symbols: r coeffcent of correlaton, x 3 varable that measures the sectoral reallocaton of labour, x 3 average value of the varable x 3, y 2 varable that measures the nature of economc growth n terms of the contrbuton of the total factor productvty to economc growth, ȳ 2 average value of the varable y 2, n number of observatons, σ x3 standard devaton for varable x 3, σ y2 standard devaton for varable y 2, α 0 regresson constant, α 1 coeffcent of elastcty, e error term, L logt (logarthm of odds rato), y 3 bnary dependent varable wth value 1 f the nature of the observed muncpalty s economc growth was ntensve (. e. the contrbuton of total factor productvty exceeded 50%) or value 0 f the nature of economc growth of the selected muncpalty was extensve (. e. the contrbuton of physcal and human captal to economc growth together exceeded 50%), P probablty that the nature of economc growth s ntensve. In all three models (14), (15) and (16) the explanatory varable was estmated usng the followng framework: x 3 = Ω 2002 Ω 1996, where (17) Ω 1996 = LP 1996 LD 1996 and (18) Ω 2002 = LP 2002 LD (19) 27

14 Matjaž Novak and Štefan Bojnec TABLE 4 Theoretcal specfcatons of the coeffcent of correlaton, elastcty model and logt model Coeffcent of correlaton r = 0.45 Coeffcent of elastcty α 1 = 0.54[p = ] Odds rato ϑ = Source: Own calculatons. 28 Symbols: x 3 varable that measures the sectoral labour reallocaton expressed as the change n the share of labour force employed n the propulsve ndustres wth respect to labour force employed n the dgressve ndustres, Ω 2002 varable that measures the share of labour force employed n the propulsve ndustres wth respect to labour force employed n the dgressve ndustres n 2002, Ω 1996 varable that measures the share of labour force employed n the propulsve ndustres wth respect to labour force employed n the dgressve ndustres n 1996, LP 1996 varable that measures labour force employed n the propulsve ndustres n 1996, LD 1996 varable that measures labour force employed n the dgressve ndustres n 1996, LP 2002 varable that measures labour force employed n the dgressve ndustres n 2002, LD 1996 varable that measures labour force employed n the propulsve ndustres n Estmates of the correlaton coeffcent, the coeffcent of elastcty, the logt and odds rato are reported n table 4. The coeffcent of correlaton ndcates a medum lnear relatonshp between the contrbuton of total factor productvty and the labour reallocaton towards the propulsve ndustres (both varables are expressed n natural logarthms). A hgh statstcally sgnfcant coeffcent of elastcty ponts out that the labour reallocaton towards the propulsve ndustres nduces a 0.542% ncrease of the contrbuton of total factor productvty whch s a relatvely substantal nfluence. Statstcally sgnfcant s also the estmated parameter of the logt model. The odds rato ndcates a tmes ncrease of the odds ntensve growth f the share of the labour force employed n the propulsve

15 Human Captal and Regonal Economc Growth n Slovena ndustres wth respect to the share n the dgressve ndustres rses for one percentage pont. CONCLUSIONS Durng transton to a market economy and the process of Slovenan adjustments for the EU membershp the majorty of the Slovenan economc growth was due to an extensve growth of labour and captal. Ths paper more specfcally analyses the nature of the Slovenan economc growth n the perod pursung the man objectve to recognze the reason for the decreasng returns to scale. We have appled the average producton functon and the stochastc fronter producton functon allowng an estmaton of the parameters of the muncpalty producton functons on the bass of the cross-sectonal and tme-seres data. Usng these pooled econometrc approaches and the obtaned results we developed the growth accountng equatons for 147 Slovenan muncpaltes, whch allow an estmaton of the contrbutons of each partcular producton factor (physcal captal, human captal and total factor productvty) to the muncpalty output growth. Thus, we have analysed the man factors that are mportant for the economc growth and development of muncpaltes. The n-depth econometrc analyss at the muncpalty level was also necessary to obtan a suffcent number of observatons for testng a statstcal sgnfcance of the parameters assocated wth the labour reallocaton on the nature of economc growth. We have econometrcally tested the sgnfcance of the labour reallocaton process to the nature of economc growth n the Slovenan economy usng the muncpalty-cross-sectonal-tme seres data. We have found out that the man reason for the decreasng returns to scale n the Slovenan economy n the perod was an neffcent use of human captal n the producton process. One of the man constrants for ths neffcency s the uncompleted structural labour reallocaton from the decreasng ndustres towards the more propulsve ones. The emprcal results of the coeffcent of correlaton, the coeffcent of elastcty and the odds rato of the estmated logt model clearly ndcate that the reallocaton of labour towards the propulsve ndustres has statstcally sgnfcantly nfluenced the rse of total factor productvty. The labour force wth the emboded technologcal knowledge (. e. human captal) remans allocated neffcently across ndustres. 29

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