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      基于擁擠效應(yīng)的陜西省水利投資最優(yōu)規(guī)模研究

      2014-06-28 19:55:47任靜陸遷
      關(guān)鍵詞:陜西省

      任靜 陸遷

      摘要 確定最優(yōu)投資規(guī)模是陜西省水利投資決策的關(guān)鍵問(wèn)題之一。目前已有學(xué)者通過(guò)實(shí)證研究表明,區(qū)域性準(zhǔn)公共物品在最優(yōu)供給中存在“擁擠效應(yīng)”,同時(shí)也有學(xué)者已從理論上證實(shí),“擁擠效應(yīng)”會(huì)影響準(zhǔn)公共物品的最優(yōu)供給規(guī)模。而確定準(zhǔn)公共物品最優(yōu)投資規(guī)模的傳統(tǒng)方法——道格拉斯函數(shù)法,卻忽略了其“擁擠效應(yīng)”屬性,因而產(chǎn)生一定局限。那么,陜西省水利設(shè)施作為一種具體的區(qū)域性準(zhǔn)公共物品,其在最優(yōu)供給中是否也存在“擁擠效應(yīng)”?擁擠程度如何?如何實(shí)證的估計(jì)具有擁擠性的水利設(shè)施最優(yōu)投資規(guī)模?基于上述思路,本文首先借鑒國(guó)外學(xué)者對(duì)“擁擠效應(yīng)”的測(cè)度方法,建立水利設(shè)施擁擠效應(yīng)測(cè)度模型,以驗(yàn)證陜西省水利設(shè)施的“擁擠效應(yīng)”及擁擠程度;其次,將“擁擠效應(yīng)”的測(cè)度方法引入到傳統(tǒng)的道格拉斯函數(shù)法中,對(duì)其進(jìn)行修正,建立估計(jì)擁擠性水利設(shè)施最優(yōu)投資規(guī)模的實(shí)證模型;最后,運(yùn)用陜西省1978-2011年時(shí)間序列數(shù)據(jù),對(duì)上述兩個(gè)模型進(jìn)行實(shí)證估計(jì)。結(jié)果表明,陜西省水利設(shè)施供給存在顯著的擁擠效應(yīng);若考慮到“擁擠效應(yīng)”,當(dāng)人均水利投資約占人均產(chǎn)出的5.74%時(shí),陜西省水利投資水平達(dá)到最優(yōu);與最優(yōu)水平相比,陜西省歷年的水利投資均低于其最優(yōu)水平。此外,模型中水利設(shè)施供給彈性的估計(jì)值(=-0.441 8)表明水利設(shè)施具有較強(qiáng)的公共物品性質(zhì),水利投資的主體應(yīng)該是以政府為代表的公共部門;同時(shí),人均水利設(shè)施供給量對(duì)人均補(bǔ)貼的彈性(φ=0.380 1)為正且數(shù)值不小,說(shuō)明中央政府的財(cái)政補(bǔ)助及民間資金對(duì)改善陜西省人均水利供給會(huì)產(chǎn)生積極影響,因此,陜西省應(yīng)重視民間資金的引入,積極拓展融資渠道,構(gòu)建多元化的投融資機(jī)制。

      關(guān)鍵詞 水利投資;準(zhǔn)公共物品;擁擠效應(yīng);最優(yōu)投資規(guī)模;陜西省

      中圖分類號(hào) F282 文獻(xiàn)標(biāo)識(shí)碼 A 文章編號(hào) 1002-2104(2014)04-0169-08

      水利是國(guó)民經(jīng)濟(jì)的基礎(chǔ)產(chǎn)業(yè)和基礎(chǔ)設(shè)施。水利發(fā)展有賴于投入的保障,而投入不足,水資源供需矛盾突出,制約著陜西經(jīng)濟(jì)社會(huì)的可持續(xù)發(fā)展。目前省內(nèi)40%的大型灌區(qū)骨干工程、50%-60%的中小型灌區(qū)存在大型灌排泵站的設(shè)備完好率不足60%[1]。2011年 “中央一號(hào)文件”和中央水利工作會(huì)議都將水利問(wèn)題提到了前所未有的高度,提出未來(lái)10年水利投資將達(dá)到4萬(wàn)億元,陜西省水利投資也迎來(lái)了前所未有的新機(jī)遇,水利建設(shè)投入規(guī)模大幅增加。但是,水利投資存在一個(gè)最優(yōu)投資規(guī)模問(wèn)題,任何投資過(guò)度或不足都會(huì)影響投資效率,因此,如何確定水利最優(yōu)投資規(guī)模就成為水利投資決策的關(guān)鍵問(wèn)題之一。

      目前理論界確定水利等基礎(chǔ)設(shè)施最優(yōu)投資規(guī)模通常采用生產(chǎn)函數(shù)法,即將基礎(chǔ)設(shè)施投資作為一種生產(chǎn)要素,運(yùn)用生產(chǎn)函數(shù)估計(jì)它們的邊際貢獻(xiàn),確定其最優(yōu)投資規(guī)模。該方法簡(jiǎn)單明了,容易估算,國(guó)內(nèi)外許多學(xué)者采用這種方法對(duì)基礎(chǔ)設(shè)施等投資最優(yōu)規(guī)模進(jìn)行計(jì)算[2-4,8-12,20-21]。但該方法缺陷是忽略了基礎(chǔ)設(shè)施具有準(zhǔn)公共物品的特性。這種準(zhǔn)公共物品實(shí)質(zhì)上是一種“俱樂(lè)部產(chǎn)品”(一種排他且非競(jìng)爭(zhēng)性準(zhǔn)公共物品),在使用中會(huì)產(chǎn)生 “擁擠效應(yīng)”現(xiàn)象,即當(dāng)使用者人數(shù)超過(guò)一定規(guī)模后,俱樂(lè)部產(chǎn)品則具備一定的競(jìng)爭(zhēng)性,從而使其人均獲得量小于人均供給水平。一些學(xué)者僅在理論層面上基于擁擠性討論了“俱樂(lè)部產(chǎn)品”的最優(yōu)投資規(guī)模問(wèn)題[3,5,7],但是,關(guān)于擁擠性公共物品最優(yōu)投資規(guī)模的實(shí)證研究目前尚處于探索性階段。

      水利作為公益性極強(qiáng)的基礎(chǔ)設(shè)施,具有明顯的準(zhǔn)公共物品屬性。我國(guó)學(xué)者劉小魯證實(shí)了我國(guó)省際一般性準(zhǔn)公共物品的最優(yōu)供給中存在顯著的擁擠效應(yīng)[6]。但是,水利設(shè)施是準(zhǔn)公共物品的一種具體形態(tài),若將準(zhǔn)公共物品的擁擠效應(yīng)納入到水利最優(yōu)投資規(guī)模的分析框架中,需要解決兩個(gè)問(wèn)題:首先是水利設(shè)施的最優(yōu)供給中是否也存在擁擠效應(yīng)?擁擠程度如何?其次是如何構(gòu)建一個(gè)包含擁擠性的水利投資最優(yōu)規(guī)模決定模型,估算出擁擠性的水利最優(yōu)投資規(guī)模?因此,本文運(yùn)用陜西省1978-2011時(shí)間序列數(shù)據(jù),實(shí)證估計(jì)陜西水利投資擁擠性效應(yīng),確定出陜西水利最優(yōu)投資規(guī)模。

      2 模型構(gòu)建

      2.1 水利設(shè)施擁擠效應(yīng)測(cè)度模型的建立

      2.1.1 水利設(shè)施的擁擠效應(yīng)

      某地區(qū)的水利設(shè)施(如防洪工程 、水保及生態(tài)環(huán)境建設(shè)工程、水資源工程等)對(duì)每個(gè)當(dāng)?shù)鼐用裼绊懙募涌偪赡懿⒉坏扔谡麄€(gè)水利設(shè)施所能帶來(lái)的效用。在給定水利設(shè)施供給量的情況下,地區(qū)居民所能獲得的水利設(shè)施服務(wù)水平在一定程度上決定于其使用者人數(shù):如果人數(shù)超過(guò)了當(dāng)?shù)厮O(shè)施的承載力,那么居民可能需要排隊(duì)等待,或者獲得一個(gè)較低水平的服務(wù)。從這種意義上來(lái)說(shuō),水利設(shè)施具備“俱樂(lè)部”物品的性質(zhì),當(dāng)使用這人數(shù)超過(guò)一定規(guī)模后,人均水利設(shè)施獲得量小于其實(shí)際供給水平,這種現(xiàn)象被稱作“擁擠效應(yīng)”。

      第四,擁擠效應(yīng)γ的估計(jì)結(jié)果亦可揭示,張光南和周華仙等[2]為避免基礎(chǔ)設(shè)施擁擠性對(duì)其最優(yōu)投資規(guī)模影響,將基礎(chǔ)設(shè)施供給的人均量而非總量引入生產(chǎn)函數(shù)模型的做法是不恰當(dāng)。因?yàn)檫@種做法暗含的假設(shè)條件實(shí)質(zhì)是γ=-1,而這只是在理論上的一種可能值,并不一定是基礎(chǔ)設(shè)施擁擠效應(yīng)的實(shí)際值,所以,這種做法不一定能避免基礎(chǔ)設(shè)施的擁擠性。

      (編輯:王愛(ài)萍)

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      [26]Reiter M, Weichenrieder A J. Public Goods, Club Goods, and the Measurement of Crowding [J]. Journal of Urban Economics, 1999, (1): 69-79.

      [27]Takahashi T. On the Optimal Policy of Infrastructure Provision Across Regions [J]. Regional Science and Urban Economics, 1998, (2): 213-235.

      [14]Barro S, Ruiz R, Mira J. Multimicroprocessor System for Online Monitoring in a CCU[J]. Medical & Biological Engineering & Computing, 1990, (4): 339-349.

      [15]Barro R, SalaIMartin X. Convergence[J]. Journal of Economic Growth. 1992, 100(2): 223-251.

      [16]Borcherding T E, Deacon, et al. The Demand for the Services of Nonfederal Governments [J]. The American Economic Review, 1972, (5): 891-901.

      [17]Bergstrom T C, Goodman, et al. Private Demands for Public Goods[J]. American Economic Review, 1973, (3): 280-96.

      [18]Craig P. Resurfacing Full Thickness Burns of Scalp: The Crossword Technique [J]. Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery, 1987, (3): 257-259.

      [19]Ha F. An Analysis of the Optimal Provision of Public Infrastructure: A Computational Model Using Mexican Data [J]. Journal of Development Economics, 1999, (1): 219-230.

      [20]Guengant A, Josselin M, Rocaboy Y. Effects of Club Size in the Provision of Public Goods: Network and Congestion Effects in the Case of the French Municipalities[J]. Papers in Regional Science, 2002, 5(1): 443-460.

      [21]Inman R P. A Generalized Congestion Function for Highway Travel [J]. Journal of Urban Economics, 1978, 5(1): 21-34.

      [22]Karras G. On the Optimal Government Size in Europe: Theory and Empirical Evidence[J]. The Manchester School, 1997, 65(3): 280-294.

      [23]Kim E. Determinants of Optimal Level of Transportation Infrastructure [J]. Journal of Urban Planning and Development, 2002, (3): 150-163.

      [24]Hwang H, Lee N. Effect of Risk Aversion on the Incentive to Share Information[J]. International Economic Journal, 1992, (4): 423-439.

      [25]Linnemann L, Andreas S. Optimal Government Spending and Unemployment [A]. Tinbergen Institute Discussion Paper,2008, TI 2008-024 /2.

      [26]Reiter M, Weichenrieder A J. Public Goods, Club Goods, and the Measurement of Crowding [J]. Journal of Urban Economics, 1999, (1): 69-79.

      [27]Takahashi T. On the Optimal Policy of Infrastructure Provision Across Regions [J]. Regional Science and Urban Economics, 1998, (2): 213-235.

      [14]Barro S, Ruiz R, Mira J. Multimicroprocessor System for Online Monitoring in a CCU[J]. Medical & Biological Engineering & Computing, 1990, (4): 339-349.

      [15]Barro R, SalaIMartin X. Convergence[J]. Journal of Economic Growth. 1992, 100(2): 223-251.

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      [17]Bergstrom T C, Goodman, et al. Private Demands for Public Goods[J]. American Economic Review, 1973, (3): 280-96.

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