( 200 ) Japanese Research Vol.33No.1 Fed , (1., ;2., ) : 30 47, GMM, :(1), ;(2),,,,,, : ; GMM; :F1 :A : (2019)01

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1 ( 200) Japanese Research Vol.33No.1 Fed ( ; ) : 30 GMM :(1) ;(2) : ; GMM; :F1 :A : (2019) DOI: /j.cnki.rbwtyj % : % % [2] 15% ; 5.0 ( ) [1] [3] ; ; : : A (GJ SCX2975) : (1959 ) 20

2 : (Roper2002 [16] ) () : (1) Schneider (2008) (Siliv- U [17] erstovs2011 [4] ) (2) (1) :(1) (2) (Miyaza- wa2006 [8] ) 7% 14% 23( ( ) 1993) : (1) (D Aboal2012 [10] ;D 1 Singh2015 [11] ) (2) (Montobbio2002 [12] ; Metecalfe2005 [13] GaiandPissarides2007 [14] ) (3) [15] () (Rogerand Wasmer2011 [5] ) [9] (2) [6] (3) (1) (Frosch2009 [18] ) MenzandKühling (2011) (4) [7] (2)

3 () [19] (2018) [21] 11 [20] 1 1 (Y) GDP /GDP; ; GDP/ ; GDP/ ; DEA-Malmquist ; /GDP; /GDP; ; : t+1 t M i (x t+1 : y t+1 x t y t ) t t+1 3 D t D t+1 ir= (gmn -g) 2 槡 hmn t t (1) n=1 g +1 t t+1 (1)gmn m n ;g ;h mn n ir [22] Malmquist (GPCA) [23][24] : D t 槡 M i (x t+1 y t+1 x t y t )= (x t+1 y t+1 (x Dt+1 t+1 y t+1 Di t (x t y t D t+1 i (x t y t (2) KMO (x t+1 y t+1 ) (x t y t ) Bart- 22

4 : let : % INV it= (1- )INV it-1+l i it (3) % 85% INV i0= Li1 (4) gi+ i INV it L it () i t i INV i0 Haletal.(2010) [25] gi 1 GDP 2 2 Groups CY JY LnCAGE LnJAGE LnCINV LnJINV LnCINV LnCAGE LnJINV LnJAGE LnCGOV LnJGOV LnCI LnJI LnCC LnJC LnCH LnJH LnCTRAD LnJTRAD ;2. (65 )/ (15~64) /GDP % 23

5 ; ; ; :

6 : () : Y it=α+β 1Yit-1+ β 2lnINVit+ β 3lnAGEit+ β 4lnGOVit+ β 5lnIit+ β 6lnCit+ β 7lnHit+ β 8lnTRADit+ μ i+εit (5) 4 5 AR Hansen Y it=α+η 1Yit-1+ η 2lnINVit+ η 3lnAGEit+ η 4lnINV AGE it+η 5lnGOVit+ η 6lnIit+ η 7lnCit+ η 8lnHit+ η 9lnTRADit+ μ i+εit (6) i t Y it-1 Y it lninv it lnage it lninv AGE it lngov it lni it lnc it lnh it lntrad it μ i εit 1% % 1% (5) % (6) (GMM) GMM GMM GMM GMM (5) (6) GMM : 5 9 ΔY it=δβ 1Yit-1+Δ β 2lnINVit+Δ β 3lnAGEit+ Δβ 4lnGOVit+Δ β 5lnIit+Δ β 6lnCit+Δ β 7lnHit+ Δβ 8lnTRADit+Δεit (7) ΔY it=δη 1Yit-1+Δ η 2lnINVit+Δ η 3lnAGEit+ Δη 4lnINV AGE it+δη 5lnGOVit+Δ η 6lnIit+ Δη 7lnCit+Δ η 8lnHit+Δ η 9lnTRADit+Δεit (8) (7) (8) GMM Δ 1% % (5) (6) GMM (SYS-GMM) GMM GMM GMM GMM GMM [26] GMM GMM (5)(8) % % 1% %; 5% 1 2 :y=β0+β1x 1 +β2x 2 +β3x 1 x 2 +μ : y=α 0 + α 2 x 2 +α 3 (x 1 -μ1 )( x 2 -μ2 ) +μ μ1 μ2 x 1 x 2 : ( ) Hansen p

7 SYS-GMM L.CY *** *** *** *** *** *** * (0.7840) (0.0731) (0.0744) (0.0852) (0.0768) (0.0757) (0.0606) (0.0598) LnCAGE ** * * ** *** *** ** (0.0568) (0.0416) (0.0495) (0.0460) (0.0521) (0.0557) (1.4522) (0.6176) LnCINV ** *** ** *** *** ** * *** (0.0290) (0.0305) (0.0272) (0.0330) (0.0280) (0.0276) (0.49) (0.3337) LnCINV LnCAGE (0.0320) (0.0293) (0.0288) (0.0386) (0.0412) (1.2292) LnCH ** ** *** *** *** *** (0.0544) (0.0251) (0.0266) (0.0556) (0.0441) (0.04) (0.5671) (0.18) LnCGOV ** * *** *** *** * (0.0584) (0.0222) (0.0408) (0.0621) (0.0556) (0.8908) (0.7935) LnCC *** *** * * (0.0810) (0.0549) (0.0695) (0.0729) (1.0734) (1.1409) LnCI ** *** (0.0287) (0.0367) (0.0298) (0.8178) (0.61) LnCTRAD ** ** (0.0180) (0.0180) (0.2641) (0.2406) Cons *** ** * ** *** *** (0.2017) (0.1698) (0.1812) (0.2732) (0.2373) (0.2202) (5.8071) (5.2563) AR(1) (0.016) (0.016) (0.016) (0.016) (0.017) (0.017) (0.029) (0.019) AR(2) (0.954) (0.786) (0.779) (0.846) (0.949) (0.857) (0.532) (0.659) Hansen (0.745) (0.632) (0.677) (0.678) (0.790) (0.833) (0.769) (0.750) Wald (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Obs Groups :1 * * * * * * 1% 5% 10% () ;2AR(1) AR(2)Hansen () P 26

8 : 5 SYS-GMM L.JY *** *** *** *** *** *** (0.0373) (0.0889) (0.0817) (0.0854) (0.0861) (0.0814) LnJAGE ** * * ** ** ** (0.2162) (0.2456) (0.2527) (0.2660) (0.2751) (0.2667) LnJINV ** * * ** * (0.0048) (0.0077) (0.0076) (0.0079) (0.0075) (0.0065) LnJINV LnJAGE ** ** ** ** ** (0.0541) (0.0481) (0.0517) (0.0522) (0.0487) LnJC ** ** ** ** ** * (0.05) (0.0714) (0.0745) (0.0811) (0.0904) (0.0974) LnJGOV (0.0360) (0.0223) (0.0348) (0.0357) (0.0336) LnJI (0.0216) (0.0301) (0.0287) (0.0262) LnJH (0.0089) (0.0129) (0.0110) LnJTRAD * (0.0191) (0.0250) Cons *** ** ** *** *** *** (0.3062) (0.3133) (0.3500) (0.3961) (0.3886) (0.3750) AR(1) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) AR(2) (0.207) (0.171) (0.179) (0.190) (0.173) (0.180) Hansen (0.101) (0.088) (0.097) (0.089) (1.121) (0.122) Wald (0.000) (0.000) 0.000) (0.000) (0.000) (0.000) Obs Groups : 4 27

9 () ; GMM ; : L.CY * * * L.JY * * * * * * * * * (0.0621) (0.0594) (0.0572) (0.0814) (0.1703) (0.0351) LnCAGE LnJAGE * * * * * * (2.4633) (1.9269) (2.1432) (0.0738) (0.1703) (0.0461) LnCINV * * * * * LnJINV * * * (0.4355) (0.6563) (0.6614) (0.0065) (0.0689) (0.0105) LnCINV LnCA LnJINV LnJA * * * * * GE (1.0298) (1.05) (0.9500) GE (0.0135) (0.1703) (0.0164) AR(1) AR(1) (0.027) (0.025) (0.024) (0.002) (0.002) (0.002) AR(2) AR(2) (0.609) (0.566) (0.540) (0.240) (0.204) (0.203) Hansen Hansen (0.822) (0.797) (0.788) (0.136) (0.102) (0.105) Wald Wald (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Obs Obs Groups Groups :

10 : 7 : 21 OLS 22 FE 23 RE 24 2SLS 25 DIF-GMM ( ) 26 DIF-GMM ( ) L.CY * * * * * * (0.1084) (0.1195) LnCAGE * * * * * * * * * * * * * * * * (0.1171) (0.1059) (0.1171) (0.0694) (0.0684) (0.0818) LnCINV * * * * * * * * * * * * * * * * (0.01) (0.0394) (0.01) (0.0272) (0.0527) (0.0626) LnCINV LnCAGE (0.0737) (0.0684) (0.0737) (0.0498) (0.0507) (0.0564) R AR(1) (0.003) (0.021) AR(2) (0.415) (0.449) Hansen (0.140) (0.140) Obs Groups : 4 [28] 30 GMM : ; ( ) [29] [27] 29

11 [R].[ ].htps://www. kantei.go.jp/jp/singi/keizaisaisei/pdf/miraitousi2017 t pdf. 11.8% 61.6% [4]SILIVERSTOVSBKHOLODILIN K ATHIESSEN U.DoesaginginfluencestructuralchangeEvidencefrom 65 paneldata[j].economicsystems201135(2): % [5]ROGER MWASMER M.Heterogeneity Maters:La- bourproductivity Diferentiatedby AgeandSkils[R]. [30] Documentsde Travaildela DESE-rWorking Papersof thedese2011. [31] [6]. [J] (4): [7]MENZ TK HLINGJ.Populationagingandenviron mentalqualityin OECDcountries:evidencefromsulfur dioxideemissionsdata[j].population & Environment (1): [8]MIYAZAWA K.Growthandinequality:ademographic explanation[j].journalofpopulation Economics (3): [9]. [J]. 2014(3): [10]ABOALDGardaP.TechnologicalandNontechnologi- calinnovation and Productivityin Servicesvisa vis ManufacturinginUruguay[J].IdbPublications2012. [11]DAVINDER SINGHJAIMAL SINGH KHAMBA TARUN NANDA.RoleofTechnologicalInnovationin Improving ManufacturingPerformance:A Review[J]. InternationalScholarlyandScientificResearch &Inno- vation20159(1): [12]MONTOBBIO F.Anevolutionary modelofindustrial growthandstructuralchange[j].structuralchange & ; EconomicDynamics200213(4): [13]METCALFEJSRAMLOGAN R.Competitionand theregulationofeconomicdevelopment[j].quarterly ReviewofEconomics & Finance200545(2-3):215 [ ] [1]. [14]GAIL RPISSARIDES C A.StructuralChangeina MultisectorModelofGrowth[J].American Economic [EB/OL].[ ]. Review200797(1): com/ /27/c htm. [2]. 2014(6):1-6. [J]. [16]ROPERSLOVEJH.Innovationandexportperform- ( )2018(5): ance:evidencefromtheukandgermanmanufacturing [3] Society [15]. [J]. plants[j].researchpolicy200231(7):

12 : [17]SCHNEIDER L.AlterungundtechnologischesInnova- tionspotential[j].zeitschriftfürbevlkerungswissen- schaft200833(1): [18]FROSCH KTIVIG T.Labour Marketsand Demo- [25]BRONWYN H. HalJacques Mairesse Pierre Mohnen.Measuringthe Returnsto R&D[J].UNU- rmerit WorkingPapersISSN :1-46. [26]WINDMEIJERFRANK.Afinitesamplecorrectionfor graphicchange[m].wiesbaden:vs VerlagfürSozial- wissenschaften2009: [19]HICKSN L.GrowthvsBasicNeeds:IsThereaTrade- rof[j].worlddevelopment20067(11): (8): [21]. [28]. [J]. ( )2018(5): [J]. 2018(5): [22] (4): [M]. : 2013:144. [23]. ( )[ ].htp://www8.cao.go. [J] (1): [24]VIDAL RMA YSASTRY S.Generalized principal componentanalysis(gpca)[j].ieee Transactionson jp/kourei/whitepaper/w -2017/zenbun/29pdfindex. html. [31]. [J]. Patern Analysis & Machine Inteligence (4): (12): tors[j].journalofeconometrics (1): [27]ARJUN KHARPAL.JapanhasnofearofAI itcould boostgrowthdespitepopulationdeclineabesays[eb/ rdespite-rpopulation-rdecline-rabe-rsays.html. [29]. [J]. [30]. 29 [EB/OL]. [ ] TheEffectsofPopulationAgingandTechnologyInnovation onthequalityofeconomicgrowth BasedonSystem GMM EstimationforDynamicPanelData ZHANGJi-feng 1 DENG Mei-wei 2 (1.InstituteofJapaneseStudiesChineseAcademyofSocialSciencesBeijing100007China; 2.GraduateSchoolChineseAcademyofSocialSciencesBeijing102488China) thevarianceoflineareficienttwo-rstep GMM estima- [20]. OL].[ ].htps:// [J] /japan-rhas-rno-rfear-rof-rai-r-rit-rcould-rboost-rgrowth- Abstract:Bymeasuringtheeconomicgrowthqualityindicatorsof31provincesinChinaandcountiesin Japanthispaperexplorestheinfluencesoftechnologicalinnovationandagingonthequalityofeconomic growththroughsys-gmm model.themainconclusionsareasfolows:firstlyforbothchinaandjapan technologicalinnovationcanefectivelypromotethequalityofeconomicgrowthandtheagingofpopula- tionhasanegativeimpactonit;secondlytheinteractionbetweentechnologicalinnovationandpopulation aginghaspositiveinfluenceonthequalityofeconomicgrowthandtechnologicalinnovationcanbeusedas apowerfulmeasuretodealwiththechalengeofpopulationaging.howeverthisimpactissignificantin thejapaneseempiricalsamplebutnotinthechineseempiricalsample.inview ofthesechinashould learnfromjapanpromotethehealthlevelofagedpeopleandencourageagedpeopletoparticipateinso- cialactivitiesandreturntowork. Keywords:technologicalinnovation;populationaging;sys-gmm;regionaleconomy 31

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