Cointegration Analysis of Government R&D Investment and Economic Growth in China

Transcription

1 Proceedngs of he 7h Inernaonal Conference on Innovaon & Manageen 349 Conegraon Analyss of Governen R&D Invesen and Econoc Growh n Chna Mao Hu, Lu Fengchao Dalan Unversy of Technology, Dalan,P.R.Chna, 6023 (E-al: kjjkjhzc@63.co, fengchaolu@26.co) Absrac Governen R&D nvesen has been playng a very poran role n he econoc developen. Based on he daa fro 978 o 2008 ssued by Chna Sascal Bureau, hs paper analyzes he dynac equlbru relaonshp beween governen R&D nvesen and econoc growh by usng conegraon analyss n econoercs. The resuls show ha here s sable long-er balancng relaonshp beween he governen R&D nvesen and econoc growh n Chna, and governen R&D nvesen s an causaon whch brngs abou econoc growh. Key words Econoc growh; Governen R&D nvesen; Granger causaly; Error correcon odel Inroducon A presen, Chna s beng n he sraegy opporuny e, and enhanceen ndependen nnovaon ably has becoe he curren econoy developen an poran opc n Chna. Alhough Chna has nally esablshed a dversfed R&D nvesen paerns, he Governen R&D nvesen ll plays an poran role n a long e due o he enerprses sze l. In 2008, he proporon of governen funds n collecon of R&D funds has reached 23.% and accouns for a large proporon, however, how governen R&D nvesen pac on econoc growh n Chna, and how o play a ore effecve of governen R&D nvesen n econoc growh and prove capacy for ndependen nnovaon. In hs paper, we suded he relaon beween he governen R&D nvesen and econoc growh of Chna fro he deonsraon aspec n he e-seral dynac balanced relaon s conegraon analyss echnque n econoercs, wh he sascal daa ssued by Chna sasc bureau fro 978o The Model and Mehod of he Conegraon Analyss Conegraon Analyss s a echnque used o esae he long-er equlbru paraeer n he nonequlbru varable equaon, and has been broadly used n he dynac odel enacen, esang and es, also, has srong sably and relably and can avod llusve regresson, overcoe varous dffcules of he radonal easure analyss used n nonequlbru econoc e-seral analyss. When carryng ou he conegraon analyss, he general order s es he sably of e-seral varable and s sngle-order dfference seral frsly, hen, es he conegraon relaonshp of he varables, esablsh he error correcon equaon beween he conegraon varable and he equlbru, a las, furherly es he causaly of he conegraed e-seral varables agan. 2. Equlbru es of he e-seral varables Generally speakng, f he ean and varance of a e-seral keep sable a any e, and he covarance (or auocovarance) beween he perod of and +k only depends on he dsance (nerval or lag) k of he wo perods, and rrelevan wh he real perod of hese covarances, hen he e-seral s sooh. The e-seral won be sooh f hose hree condons are no all eeed. Anoher ehod o express non-sably s known as un roo, whch can ransfor he es of non-sably no he es of un roo. The varable x has un roo f he sngle-order dfference of whch s sable, and hs process s known as un roo es. In hs paper, he ADF ehod s used o es he varables sably, analyse as follows: Δx = k 0 + α + α 2 x + α 3Δx + μ = α () and hen, carry ou hypohess es: H 0 : α 0; H : α 2 <0. If accep he hypohess H 0, and rejec H, hen he seral has un roo, and he seral s no sooh; oherwse, he seral x has no un roo, and he seral s sooh. We have o add k lag es no equaon () whch can ransfor he resdual error o fla nose.

2 350 Proceedngs of he 7h Inernaonal Conference on Innovaon & Manageen I needs o es sably of he sngle-order dfference (or growh rae), f he varable s no sooh. The varable s I () f s sngle-order s sooh. All he varables sngle-order are sooh s he requreen ha he varables have conegraon relaonshp. 2.2 Conegraon analyss of he e-seral varables Conegraon sands for ha wo or ore e-seral s lnear cobnaon s sooh, hough a sngle e-seral s no sooh. The varables nvolved n he conegraon analyss are all non-sooh, bu hey drf ogeher. Ths collecve drf of he varables ake ha here are long-er lnear relaon aong he varables, and hen, he sudy of he long-er equlbru relaonshp aong he econoc varables becoes possble. The sgnfcance of conegraon s ha exposs a long-er sable equlbru relaonshp, ees he suaon ha he econoc varables can be oo dsan fro each oher, a sngle e aack only can ake he leave he balanced saon n shor e, and wll reurn o he balanced saon auoacally n he long er. The econoc sgnfcance of he conegraon s ha here s a long-e equlbru relaonshp f here are wo varables, whch boh have long e flucuan dscplne, and s conegraed beween hese wo varables. Whereas, here s no long e balanced relaon beween he wo varables f hey are no conegraed. Now, here are any dographc echnque odels abou he es and esaon o he conegraon relaon, such as Engle-Granger wo-sep process, Johnhansen axu lkelhood ehod, frequency doan non-paraeer specru regresson ehod, ec. We choose he Johnhansen axu lkelhood ehod o es he conegraon relaon of he varables n hs paper. Johnhansen axu lkelhood ehod can deerne he nuber of conegraon equaon, and hs nuber s called conegraon order. The conegraon lkelhood rao s hypoheszed as: H 0 :There are r conegraon relaons a os H :There are conegraon relaons Tes he race sascs Q r = T = r+ log( λ ) λ s he h egenvalue, T s he observaon perod s oal nuber. Ths s a seres of es correspondng o r s dfferen value, no an unaded es. Fro he null hypohess ha he es has no conegraon relaon, o here s only one conegraon relaon a os, o here are - conegraon relaon a os, here are ess and he alernave hypohess don change. There are fve possble suaons n Johnhansen axu lkelhood ehod s analyss frae: he seral has ean value and he conegraon equaon has no nercep e; he seral has ean value and he conegraon equaon has nercep e; he seral has ean value and lnear rend e, he conegraon equaon has no nercep e; he seral has ean value and lnear rend e, he conegraon equaon has nercep e and lnear rend; he seral has ean value, lnear and quadrac rend e, and he conegraon has nercep e and lnear rend e. To he gven conegraon order, he fve ess above are srcly decreasng. 2.3 Error correcon odel Conegraon analyss also can be used n he esaon of he shor-er of non-balanced paraeer, accordng o Granger Theory, varable X has long-er equlbru relaonshp wh varable Y f hese wo varables are conegraed. However, n shor er, hese varables can be no balanced. The urbulency e s he equlbru error ξ, he dynac srucure of he shor-er non-balanced relaon beween he wo varables can be descrbed by he error correcon odel (ECM). The EMC, whch conacs shor-er and long-er acon of he wo varables, can be specfed n he followng equaon: ΔY = lag( ΔY, ΔX ) + λε + v (2) n he equaon,y ~I(), X ~I(), Y, X ~CI (), ξ = Y -β 0 -β X ~I(0), v s fla nose;λ s shor-er pondage facor 2.4 The granger causaly of he e-seral varables In he regresson analyss, he regresson can easure he conac degree beween he varables, bu can no esfy he causaly. The causaly denfcaon s very poran n he sudy based on es. The basc dea of he causaly es ehod advanced by Granger and S s: f varable X s helpful o forecas varable Y, and when carryng regresson o Y accordng o Y s used value, and f can boos up he regresson s nerpreng ably rearkably afer addng up X s used value, hen, X s called he Granger cause of Y, oherwse, called he non-granger cause. The es process o he Granger causaly beween X and Y s: o es he orgnal hypohess X s no he causaon o arse he change of Y, and

3 Proceedngs of he 7h Inernaonal Conference on Innovaon & Manageen 35 esae he followng wo regresson odel: b X + = = Non-led condon regresson: Y = ay + Led condon regresson: Y = = a Y + μ (3) μ (4) The varous regresson s resdual error quadrac su and F s sac value are used o es f he coeffcens b,b 2,, b do no equals zero rearkably a he sae e or no. If he above resul s YES, hen, we rejec he orgnal hypohess X s no he causaon o arse he change of Y. And hen, es he oher orgnal hypohess Y s no he causaon o arse he change of X, carry ou he sae regresson esaon, change X o Y, es Y s lag e does no equal zero rearkably or no. If he resul s YES, hen rejec Y s no he causaon o arse he change of X. 3 Deonsraon Analyss of he Relaon Beween Governen R&D Invesen and Econoc Growh We choose GDP as econoc growh easureen (PGDP as pracce daa afer adjusng prce ndex), and GST as governen R&D nvesen (PGST as pracce daa afer adjusng prce ndex). We ge logarh of PGDP and PGST n able, hen ge LNPGDP and LNPGST, and ake e ls fgure and do fgure. Accordng o fgure and fgure 2, we can see ha boh of varables are growng up, and wh he sae aspec. I eans ha here lkely o exs relaon. Fgure 3 also shows ha econoc growh and governen R&D nvesen exs srong relaon. Afer coun, he relaon coeffcen s grea (0.9708) LOGPGDP 3.5 LOGPGST Fgure LNPGDP Trend Fgure 2 LNPGST Trend LOGPGST LOGPGDP Fgure 3 Do of LNPGDP & LNPGST

4 352 Proceedngs of he 7h Inernaonal Conference on Innovaon & Manageen In order o sudy hs relaon, noral ehod s o se up a regress equaon basng on he sylebook daa. When we ake a radonal regress analyss, we need a balanced e ls, or resul n fake-regress. However, n fac, econoc e ls usually s unbalanced (doesn have obvous change rend), whch desroyed he assue of balance. So for he regress akes sense, we can ake balance. General ehod s o dffer he level ls, hen akes he dfference ls regress. Bu he resul gnores soe useful nforaon n he level ls, whch s necessary and poran for our analyss. Conegraon heory provdes a ehod o deal wh unbalanced daa. 3. Equlbru es of he varables seral I us es he varables equlbru before he conegraon analyss. We do equlbru es o LNPGDP, LNPGST n Table and her sngle-order varables: DLNPGDP and DLNPGST, and he resuls are n Table 2. Table 2 Equlbru Tes Resul Varable ADF es value Tes class(c,,k) 5%crcal value 0% crcal value resul LNPGDP (c,,) Dsequlbru LNZLSQ (c,,) Dsequlbru DLNPGDP (c,,)) Equlbru DLNZLSQ (c,0,) Equlbru noe: The c and n es for sae he cons e and he rend e, and k saes he lag exponen nuber; 2 The crcal value of ADF es coes fro Evews 3. sofware; 3 The chosen sandard of he lag e, k, s accordng o he prncple ha he AIC value and he SC value are a nu DLOGPGDP -.5 DLOGPGST Fgure 4 Sngle-order vary rend of GDP Fgure 5 Sngle-order rend of GST 3.2 Conegraon es and error correcon odel We es he conegraon relaonshp of Chna s econoc growh and governen R&D nvesen fro 978 o 2008 n Johansen conegraon es ehod, and he es resuls are n Table 3. Table 3 Johansen Conegraon Tes Resul Egenvalue Lkelhood rao 5% crcal vale 0% crcal value Orgnal hypohess Alernave hypohess r=0 r= r<= r=2 The lkelhood rao saes: here s a conegraon relaonshp a he 0%conspcuous level. And he conegraon vecor, (LNPGDP, LNPGST, C), urns o (.0000,.656, ) afer beng sandardzed, and hen, he long e equlbru equaon of he governen R&D nvesen and he econoc growh s: LNPGDP=.656*LNPGST The error correcon odel of he adjusen o he shor er flucuaon o long e equlbru of he governen R&D nvesen s change s: DLNPGDP= *EC *DLNPGDP *DLNGST *DLNGST The above analyss resuls show ha: () Durng , governen R&D nvesen and econoc growh n Chna exs a long

5 Proceedngs of he 7h Inernaonal Conference on Innovaon & Manageen 353 and balanced relaon. (2) In shor order, he change of GDP s affeced by governen R&D nvesen and s own. Thereno, econoc growh varable lagng one year and governen R&D nvesen varable laggng one years and hree years affecs change of GDP arkedly, and oher lagng perod affecs change of GDP nconspcuously. (3) EC s he error correcon e, and hs coeffcen reflecs he acon echans of he error correcon scale, whch correcs he based equlbru error. The GDP and governen R&D nvesen n he pre year would adjus o equlbru sae n he followng year when he correcon coeffcen s. The coeffcen of hs odel s only , whch eans GDP growh change s affeced by any oher facors. The balanced relaon beween GDP and governen R&D nvesen doesn affec curren unbalanced error correcon ably grealy. 3.3 Causaly es Conegraon es resuls ndcae ha governen R&D nvesen and econoc growh n Chna exs a long and balanced relaon. However, governen R&D nvesen growh resuls n econoc growh, or econoc growh resuls n governen R&D nvesen, needs a furher proved. We use he daa of governen R&D nvesen and GDP n fgure o do Granger Causaly es, resuls as able 4. The frs row s a null hypohess as Granger cause and effec es, he frs lne n oher rows s sasc F, and he second lne s probably of noably level, when sasc F under he null hypohess. Table 4 Granger Causaly resuls null hypohess observaons Sasc F Noably level The change of governen R&D nvesen s no he reason for he change of GDP The change of GDP s no The change of governen R&D nvesen Table 4 ndcaes ha governen R&D nvesen s an causaon ha brngs abou econoc growh and econoc growh s no an causaon ha brngs abou governen R&D nvesen, whch eans n Chna, governen R&D nvesen growh resul n econoc growh, bu econoc growh doesn resul n governen R&D nvesen growh. 4 Concluson Accordng o he analyss above, we can draw a concluson ha governen R&D nvesen and econoc growh n Chna exs a srong relaon. Though neher growh s seady, for a long perod, hey have a long, seady and equpose relaon. A shor lag econoc growh and governen R&D nvesen affec acual GDP grealy, bu econoc growh and governen R&D nvesen do a weak effec of unequpose error. As a whole, here s sngle way causaly beween governen S&T nvesen and econoc growh fro 978 o 2008, and governen S&T nvesen s an causaon ha brngs abou econoc growh. These phenoenon ndcae ha we should pay uch aenon o he gross of governen S&T nvesen so as o enhance he ndependen nnovaon ably and prooe Chna s econoy o a rapd growh. References [] Zhang Xaolng. Research on he for, characerscs, arge and funcon of governen R&D nvesen Yangze Trbune, 2006,(3):56-60 (In Chnese) [2] Naon Sascs Bureau. Chna Sascal Yearbook(2009)[M]. Bejng Chna Sascal Press, 2009 (In Chnese) [3] Wang Weguo. Econoercs[M]. Dalan Norheasern unversy of Fnance and Econocs Press, 2002 (In Chnese) [4] Zhu Chunku. A research on he relaon of dynac equlbru beween fnancal npu n S.&T. and econoc growh[j] Scence of Scence and Manageen of S.&T., 2004 (3): (In Chnese) [5] Granger C W J. Invesgang Causal Relaons by Econoerc Models and Gross Specral Mehods[J] Econorrca, 98