馬林靜 歐陽(yáng)金瓊 王雅鵬
摘要 本文采用2001-2010年全國(guó)30個(gè)省份有關(guān)糧食生產(chǎn)的面板數(shù)據(jù),基于糧食生產(chǎn)區(qū)域分異視角,運(yùn)用隨機(jī)前沿生產(chǎn)函數(shù)模型對(duì)我國(guó)糧食主產(chǎn)區(qū)、主銷區(qū)、平衡區(qū)種糧技術(shù)效率進(jìn)行了測(cè)算,然后將反映農(nóng)村勞動(dòng)力資源變遷的變量納入技術(shù)非效率模型,比較分析了不同區(qū)域農(nóng)村勞動(dòng)力數(shù)量及質(zhì)量變化對(duì)種糧技術(shù)效率的影響。結(jié)果表明:①農(nóng)村勞動(dòng)力非農(nóng)轉(zhuǎn)移對(duì)糧食生產(chǎn)技術(shù)效率的提高有顯著正向積極作用,就區(qū)域影響程度來(lái)看,平衡區(qū)>主產(chǎn)區(qū)>主銷區(qū),說(shuō)明在糧食平衡區(qū)勞動(dòng)力轉(zhuǎn)移對(duì)糧食生產(chǎn)效率有較大的提升作用,意味著在該區(qū)域存在較多的農(nóng)村剩余勞動(dòng)力;②農(nóng)村人力資本水平對(duì)糧食生產(chǎn)技術(shù)效率也具高度顯著的正向影響,但影響力度不大,表明我國(guó)農(nóng)村勞動(dòng)力資源存在著質(zhì)量意義的過(guò)?,F(xiàn)象,同時(shí)也揭示了我國(guó)農(nóng)業(yè)生產(chǎn)技術(shù)進(jìn)步在很大程度上屬于非技能偏態(tài)技術(shù)進(jìn)步;③在技術(shù)效率水平上,全國(guó)及三大區(qū)域都呈現(xiàn)出浮動(dòng)上漲趨勢(shì),效率水平不斷提高,其中以主銷區(qū)平均技術(shù)效率最高,主產(chǎn)區(qū)次之,平衡區(qū)最低。
關(guān)鍵詞 勞動(dòng)力非農(nóng)轉(zhuǎn)移;農(nóng)村人力資本存量;技術(shù)效率;區(qū)域分異
中圖分類號(hào) F326.11 文獻(xiàn)標(biāo)識(shí)碼 A文章編號(hào) 1002-2104(2014)
2004年以來(lái),我國(guó)糧食產(chǎn)量經(jīng)歷了史無(wú)前例的“九連增”,主要得益于兩點(diǎn):一是來(lái)自于生產(chǎn)要素等資源的投入增加,二是生產(chǎn)效率的不斷提高。前者的貢獻(xiàn)是短暫不可持續(xù)的,而后者的貢獻(xiàn)卻是長(zhǎng)足且具有可持續(xù)性的。技術(shù)效率從投入產(chǎn)出角度衡量生產(chǎn)單元能夠多大程度上運(yùn)用現(xiàn)有技術(shù)達(dá)到最大生產(chǎn)能力,是生產(chǎn)效率的集中體現(xiàn)[1]。在城鎮(zhèn)化、工業(yè)化快速發(fā)展的同時(shí),糧食生產(chǎn)要素投入結(jié)構(gòu)和生產(chǎn)管理環(huán)境也在發(fā)生著改變,傳統(tǒng)農(nóng)業(yè)主要依賴勞動(dòng)和土地這類初始資源獲取產(chǎn)出,而現(xiàn)代農(nóng)業(yè)是以運(yùn)用資本和高素質(zhì)勞動(dòng)力等現(xiàn)代要素為主要特征的經(jīng)濟(jì)形式,人力資本水平作為影響產(chǎn)出的內(nèi)生變量被納入到現(xiàn)代農(nóng)業(yè)生產(chǎn)函數(shù)中,用來(lái)揭示產(chǎn)出增長(zhǎng)中貢獻(xiàn)率日益顯著的技術(shù)進(jìn)步的源泉。本文正是基于農(nóng)村勞動(dòng)力資源變革效應(yīng),具體從農(nóng)村勞動(dòng)力數(shù)量和人力資本的雙重變動(dòng)視角下,對(duì)糧食生產(chǎn)效率展開(kāi)研究,擬對(duì)農(nóng)村勞動(dòng)力資源變遷與糧食生產(chǎn)技術(shù)效率之間的關(guān)系作出某種解釋。
學(xué)術(shù)界對(duì)于技術(shù)效率的研究已經(jīng)廣泛開(kāi)展,梳理眾文獻(xiàn),大致包括兩個(gè)方面。一是技術(shù)效率的測(cè)算,比較具代表性的有:黃金波等采用以隨機(jī)前沿生產(chǎn)函數(shù)為代表的參數(shù)方法對(duì)全國(guó)30個(gè)省份的糧食生產(chǎn)技術(shù)效率進(jìn)行了測(cè)算[2];劉寧采用非參數(shù)方法-超效率DEA方法測(cè)算了2008年我國(guó)13個(gè)糧食主產(chǎn)省份的糧食技術(shù)效率[3];二是探索固定視角的技術(shù)效率影響因素,包括家庭稟賦[4]、農(nóng)業(yè)公共投資[5]以及交通基礎(chǔ)設(shè)施建設(shè)[6]等。此外,關(guān)于勞動(dòng)力與技術(shù)效率之間關(guān)系的研究,集中在人力資本方面的文獻(xiàn)較多,主要有:顏敏等采用隨機(jī)前沿生產(chǎn)函數(shù),研究了人力資本結(jié)構(gòu)對(duì)我國(guó)技術(shù)效率的影響[7];傅曉霞等將人力資本定義為地區(qū)人口平均受教育程度,納入到隨機(jī)前沿生產(chǎn)函數(shù)模型中,研究得出人力資本對(duì)地區(qū)技術(shù)效率具有顯著的正向作用[8]。傅強(qiáng)等將人力資本納入SFA分析框架,該指標(biāo)由地區(qū)6歲以上人口平均教育年限代替,研究結(jié)果發(fā)現(xiàn):人力資本在詮釋地區(qū)間效率差異中扮演著及其重要的角色[9]。對(duì)勞動(dòng)力轉(zhuǎn)移的研究集中在對(duì)糧食產(chǎn)出[10]、農(nóng)村經(jīng)濟(jì)[11]、農(nóng)村養(yǎng)老[12]以及農(nóng)村發(fā)展[13]等的影響分析上。
上述研究成果為后續(xù)相關(guān)研究奠定了厚實(shí)的基礎(chǔ)。然而,仍然存在一些空白處和欠缺處:①研究農(nóng)村勞動(dòng)力轉(zhuǎn)移對(duì)生產(chǎn)技術(shù)效率的影響少之又少;②定義人力資本指標(biāo)時(shí)未考慮勞動(dòng)力異質(zhì)性存在的事實(shí);③研究大部分基于全國(guó)宏觀層面,未從區(qū)域分異視角探究不同區(qū)域人力資本對(duì)技術(shù)效率的影響。工業(yè)化、城鎮(zhèn)化背景下農(nóng)村勞動(dòng)力資源,是處在數(shù)量上和質(zhì)量上都在變革的時(shí)代,現(xiàn)代農(nóng)業(yè)的發(fā)展對(duì)投入要素的結(jié)構(gòu)提出了新的要求,傳統(tǒng)的靜態(tài)要素儼然已經(jīng)不能滿足,作為技術(shù)進(jìn)步源泉的人力資本要素在農(nóng)業(yè)產(chǎn)出中扮演越來(lái)越重要的角色,既如此,那么農(nóng)村勞動(dòng)力資源在數(shù)量和質(zhì)量均發(fā)生變化的情況下,糧食生產(chǎn)技術(shù)效率又會(huì)受到什么樣的影響?基于此,本文的實(shí)證研究將從糧食不同生產(chǎn)區(qū)域的層面展開(kāi),第一部分借助隨機(jī)前沿生產(chǎn)函數(shù)模型,嘗試使用糧食生產(chǎn)投入要素和產(chǎn)出要素統(tǒng)一口徑的數(shù)據(jù)對(duì)我國(guó)種糧技術(shù)效率進(jìn)行測(cè)算。第二部分將反映農(nóng)村勞動(dòng)力資源變遷的變量納入到在技術(shù)非效率模型中,詳細(xì)比較分析不同區(qū)域的農(nóng)村勞動(dòng)力資源變遷對(duì)種糧技術(shù)效率的影響結(jié)果。參照農(nóng)村勞動(dòng)力資源的概念,即農(nóng)村地域內(nèi)所有人口具有的體力和腦力的總和,包括數(shù)量和質(zhì)量?jī)蓚€(gè)方面,本文將農(nóng)村勞動(dòng)力資源變遷定義為由勞動(dòng)力轉(zhuǎn)移導(dǎo)致的數(shù)量減少和由人力資本存量增加導(dǎo)致的質(zhì)量提升的雙重集合。
目前官方統(tǒng)計(jì)數(shù)據(jù)中還未有非農(nóng)轉(zhuǎn)移勞動(dòng)力數(shù)量的精確數(shù)值,但是縱觀已有文獻(xiàn),不少研究者已找出多種方法來(lái)計(jì)算勞動(dòng)力外流數(shù)值。參照陸學(xué)藝提出的方法:將城鎮(zhèn)從業(yè)人數(shù)減去城鎮(zhèn)職工人數(shù)得到進(jìn)入城市就業(yè)的“農(nóng)民工”人數(shù),再將鄉(xiāng)村就業(yè)人數(shù)減去農(nóng)業(yè)就業(yè)人數(shù)得到農(nóng)村中非農(nóng)勞動(dòng)力數(shù)量,然后將兩者相加即得到農(nóng)村轉(zhuǎn)移勞動(dòng)力總量[14];何建新構(gòu)建的測(cè)算方法為農(nóng)村實(shí)際從業(yè)勞動(dòng)力數(shù)量與第一產(chǎn)業(yè)即農(nóng)業(yè)實(shí)際從業(yè)勞動(dòng)力數(shù)量之間的差額[15]。考慮到目前統(tǒng)計(jì)數(shù)據(jù)的局限以及數(shù)據(jù)測(cè)算的精準(zhǔn)度,本文認(rèn)為以上計(jì)算方法均存在不小的誤差,基于本文采用的是跨度為10年的面板數(shù)據(jù),能夠反映出不同時(shí)期的變化,且研究目的是從宏觀上把握勞動(dòng)力轉(zhuǎn)移對(duì)糧食生產(chǎn)效率的影響,故決定采取一種新的指標(biāo)來(lái)表示勞動(dòng)力外流的規(guī)模變動(dòng):第一產(chǎn)業(yè)從業(yè)人員占所有產(chǎn)業(yè)從業(yè)人員的比重。從時(shí)間維度來(lái)看,該指標(biāo)每年的變化恰恰反應(yīng)了勞動(dòng)力非農(nóng)轉(zhuǎn)移的趨勢(shì),該比重變小,其相反層面則說(shuō)明農(nóng)村勞動(dòng)力轉(zhuǎn)移到非農(nóng)產(chǎn)業(yè)的數(shù)量增加。
2 實(shí)證分析
2.1 數(shù)據(jù)來(lái)源和計(jì)算方法
本文使用的數(shù)據(jù)為2001-2010年全國(guó)30個(gè)省份(不包括港澳臺(tái)地區(qū))有關(guān)糧食生產(chǎn)投入和產(chǎn)出的面板數(shù)據(jù),考慮到西藏特殊的資源稟賦條件和生產(chǎn)力故將西藏排除在外。另外,根據(jù)各地糧食生產(chǎn)的資源稟賦條件、區(qū)域比較優(yōu)勢(shì)以及消費(fèi)特點(diǎn),將30個(gè)省份劃分為糧食主產(chǎn)區(qū)、主銷區(qū)和平衡區(qū)。相關(guān)數(shù)據(jù)源于歷年的《中國(guó)農(nóng)村統(tǒng)計(jì)年鑒》和《中國(guó)統(tǒng)計(jì)年鑒》,部分變量基于年鑒數(shù)據(jù)計(jì)算而來(lái)。
采用Frontier4.1軟件估計(jì)(3)式和(4)式,方法為三階段最大似然估計(jì)法。首先通過(guò)普通最小二乘法估計(jì)各投入要素的產(chǎn)出彈性等參數(shù),然后采用兩階段格點(diǎn)搜索得到方差比,同時(shí)調(diào)整產(chǎn)出彈性等以及其他參數(shù),最后以此作為初值通過(guò)數(shù)值方法得到最大似然估計(jì)值。
2.2 模型參數(shù)的估計(jì)
2.2.1 投入要素產(chǎn)出彈性分析
結(jié)合表1的估計(jì)結(jié)果,除了主產(chǎn)區(qū)的勞動(dòng)力、機(jī)械總動(dòng)力系數(shù)不顯著外,其他所有變量系數(shù)均在5%或1%的水平上高度顯著。
(1)種糧勞動(dòng)力的產(chǎn)出彈性。首先,從全國(guó)范圍看,勞動(dòng)力的糧食產(chǎn)出彈性為負(fù)值,這與許多現(xiàn)有研究結(jié)論一致[5],毋庸置疑,中國(guó)糧食生產(chǎn)中存在著剩余勞動(dòng)力資源。然后,分區(qū)域來(lái)看,主產(chǎn)區(qū)和平衡區(qū)的農(nóng)村勞動(dòng)力對(duì)于糧食產(chǎn)出的彈性為負(fù),而主銷區(qū)的勞動(dòng)力產(chǎn)出彈性為正。這一結(jié)果清晰的表明三大區(qū)域的種糧勞動(dòng)力對(duì)糧食產(chǎn)出的作用方向呈現(xiàn)較大差異:在主產(chǎn)區(qū)和平衡區(qū),減少勞動(dòng)力的數(shù)量反而能夠提高糧食產(chǎn)出;至于糧食生產(chǎn)處在較弱地位的主銷區(qū),增加勞動(dòng)力資源反而能提高糧食產(chǎn)出,產(chǎn)生這種差異是由于不同區(qū)域投入到糧食生產(chǎn)中的勞動(dòng)力資源數(shù)量不同而導(dǎo)致的。
(2)土地的產(chǎn)出彈性。全國(guó)及糧食主產(chǎn)區(qū)、平衡區(qū)的土地產(chǎn)出彈性為正值,意味著增加糧食播種面積可以有效提高糧食產(chǎn)量;主銷區(qū)的土地產(chǎn)出彈性為負(fù)值,不過(guò)這也并不表明土地作為重要的糧食生產(chǎn)投入要素對(duì)糧食產(chǎn)量的作用是反向的。對(duì)此,可能的解釋是,在數(shù)據(jù)統(tǒng)計(jì)時(shí)間范圍內(nèi),城鎮(zhèn)化、工業(yè)化導(dǎo)致了大量農(nóng)用土地資源流入非農(nóng)用途,致使耕地?cái)?shù)量大幅減少,而同時(shí),政府投資的杠桿傾斜至農(nóng)業(yè)給糧食的生產(chǎn)注入了新的要素資源,這些資源彌補(bǔ)了耕地?cái)?shù)量的絕對(duì)減少,使糧食生產(chǎn)仍能穩(wěn)步上升,因此才會(huì)出現(xiàn)土地要素系數(shù)為負(fù)值。
(3)資本產(chǎn)出彈性。三大區(qū)域和全國(guó)的種糧機(jī)械和化肥的產(chǎn)出彈性均為正值,這表明,增加兩者的投入有利于提高糧食產(chǎn)量??梢钥闯觯Y本要素的作用在當(dāng)前的中國(guó)農(nóng)業(yè)增長(zhǎng)中貢獻(xiàn)較為顯著,新古典經(jīng)濟(jì)學(xué)在構(gòu)造生產(chǎn)函數(shù)時(shí)特別強(qiáng)調(diào)資本要素的突出貢獻(xiàn),因此,現(xiàn)階段的中國(guó)農(nóng)業(yè)的發(fā)展方式可定義為新古典農(nóng)業(yè)發(fā)展方式,這是與工業(yè)化相依隨的過(guò)程,體現(xiàn)了工業(yè)化成果對(duì)農(nóng)業(yè)發(fā)展的積極影響。
2.2.2 技術(shù)非效率模型參數(shù)分析
表2顯示的是全國(guó)及三大糧食產(chǎn)區(qū)技術(shù)非效率模型(式4)的估計(jì)結(jié)果,結(jié)合四個(gè)區(qū)域不同的模型結(jié)果來(lái)看,單側(cè)似然比檢驗(yàn)均拒絕了不存在技術(shù)欠效率(即uit=0)的零假設(shè),表明中國(guó)糧食產(chǎn)出確實(shí)存在無(wú)效效應(yīng);復(fù)合擾動(dòng)項(xiàng)中技術(shù)無(wú)效項(xiàng)所占比例γ值均非常接近于1且高度顯著,這表明,在控制了投入要素以后,模型估計(jì)的誤差絕大部分來(lái)源于技術(shù)無(wú)效率部分。
(1)勞動(dòng)力外流程度。結(jié)合表2可知,除糧食主產(chǎn)區(qū)δ1變量的系數(shù)在95%的水平上顯著,其他區(qū)域該變量的系數(shù)均在99%的水平上顯著,可見(jiàn)區(qū)域內(nèi)勞動(dòng)力外流程度對(duì)種糧技術(shù)效率有很顯著的影響作用。由結(jié)果可知,該指標(biāo)的參數(shù)符號(hào)均為正值,與預(yù)期結(jié)果一致。結(jié)合指標(biāo)的實(shí)際意義:第一產(chǎn)業(yè)就業(yè)人數(shù)占總產(chǎn)業(yè)就業(yè)人數(shù)之比,該比值越大意味著勞動(dòng)力外流程度越低,同時(shí)種糧技術(shù)非效率值越大,換言之,農(nóng)業(yè)勞動(dòng)
力外流能夠促進(jìn)種糧技術(shù)效率的提升。從影響程度方面比較,平衡區(qū)>主產(chǎn)區(qū)>主銷區(qū),對(duì)于平衡區(qū),第一產(chǎn)業(yè)就業(yè)比重減少1%,技術(shù)效率提升1.23%,對(duì)于主產(chǎn)區(qū),第一產(chǎn)業(yè)就業(yè)比重減少1%,技術(shù)效率提升0.85%,對(duì)于主銷區(qū),第一產(chǎn)業(yè)就業(yè)比重減少1%,技術(shù)效率提升0.83%,從全國(guó)范圍看,第一產(chǎn)業(yè)就業(yè)比重減少1%,技術(shù)效率提升0.9%。
結(jié)合表3可知,三個(gè)區(qū)域平均技術(shù)效率水平存在明顯差異,其中,主銷區(qū)的技術(shù)效率水平最高,其次是主產(chǎn)區(qū)。技術(shù)效率代表的是現(xiàn)代農(nóng)業(yè)物質(zhì)的投入水平以及生產(chǎn)者的管理能力等影響技術(shù)使用的要素投入,而主銷區(qū)的經(jīng)濟(jì)發(fā)展實(shí)力決定了其在農(nóng)業(yè)技術(shù)使用方面的優(yōu)勢(shì),因此顯示出較高的技術(shù)效率水平。從全國(guó)層面來(lái)看,我國(guó)糧食生產(chǎn)存在著24.7%的技術(shù)無(wú)效率,技術(shù)無(wú)效率可能緣于兩個(gè)方面,一是由技術(shù)進(jìn)步速度過(guò)快導(dǎo)致的技術(shù)前沿面的位置不斷提高,即技術(shù)效率的衡量基準(zhǔn)不斷提高;二是異質(zhì)性的農(nóng)戶局限于不同的自身稟賦條件而無(wú)法對(duì)創(chuàng)新技術(shù)充分利用,同樣導(dǎo)致技術(shù)效率損失。
從時(shí)序動(dòng)態(tài)演變方面分析,除2003年技術(shù)效率水平普遍低下,之后全國(guó)及三大區(qū)域的種糧技術(shù)效率均呈現(xiàn)不斷上升趨勢(shì),這也是我國(guó)糧食產(chǎn)量“九連增”背后的主要原因。具體來(lái)看,2003年主產(chǎn)區(qū)和主銷區(qū)技術(shù)效率值均為十年中最低值,分別為0.756 4和0.759,結(jié)合當(dāng)時(shí)糧食生產(chǎn)背景,進(jìn)入新世紀(jì)以來(lái)的前三年我國(guó)糧食持續(xù)減產(chǎn),農(nóng)民種糧積極性較低,導(dǎo)致生產(chǎn)效率低下,黨中央政府高度重視糧食安全問(wèn)題,2004年頒布了糧食生產(chǎn)補(bǔ)貼和免除農(nóng)業(yè)稅政策,受中央扶持政策影響,農(nóng)民種糧積極性被激活,技術(shù)效率水平大幅度提高,相比2003年,主產(chǎn)區(qū)和主銷區(qū)技術(shù)效率水平分別增長(zhǎng)了9.13%和5.53%,而全國(guó)層面種糧技術(shù)效率水平增長(zhǎng)幅度為5.33%。
3 結(jié)論和討論
農(nóng)村勞動(dòng)力大規(guī)模的非農(nóng)轉(zhuǎn)移,是一個(gè)改變以勞動(dòng)為基本投入的傳統(tǒng)農(nóng)業(yè)資源配置格局的過(guò)程。在社會(huì)進(jìn)步的背景下,勞動(dòng)力轉(zhuǎn)移對(duì)農(nóng)村居民家庭教育需求和人力資本投資也帶來(lái)了正向激勵(lì)作用,顯現(xiàn)出農(nóng)村勞動(dòng)力規(guī)模減少的同時(shí)農(nóng)業(yè)勞動(dòng)力質(zhì)量提升的“雙面效應(yīng)”。本文正是基于農(nóng)村勞動(dòng)力資源數(shù)量和質(zhì)量雙重變動(dòng)的現(xiàn)實(shí)背景下,對(duì)種糧技術(shù)效率影響作用展開(kāi)研究,得出以下結(jié)論:
(1)農(nóng)村勞動(dòng)力非農(nóng)轉(zhuǎn)移能夠顯著提升糧食生產(chǎn)技術(shù)效率。進(jìn)一步分析原因,一是農(nóng)村勞動(dòng)力非農(nóng)轉(zhuǎn)移并沒(méi)有對(duì)糧食生產(chǎn)產(chǎn)生“資源要素剝奪”效應(yīng),使勞動(dòng)力變成瓶頸性資源,相反,非農(nóng)轉(zhuǎn)移釋放了冗余人力資源依附在農(nóng)業(yè)生產(chǎn)上的壓力,提高了生產(chǎn)資源的配置效率;二是勞動(dòng)力的非農(nóng)轉(zhuǎn)移引發(fā)種糧規(guī)模的調(diào)整和糧食生產(chǎn)結(jié)構(gòu)與組織結(jié)構(gòu)的重組,對(duì)于實(shí)施糧食規(guī)模化、專業(yè)化生產(chǎn)經(jīng)營(yíng)提供了有利條件;三是勞動(dòng)力外流至非農(nóng)產(chǎn)業(yè)增加了農(nóng)村居民家庭收入,為農(nóng)業(yè)生產(chǎn)注入了資金,在不同程度上也會(huì)促進(jìn)新型農(nóng)業(yè)生產(chǎn)技術(shù)的實(shí)施利用等。
(2)對(duì)于不同糧食生產(chǎn)區(qū)域,農(nóng)村勞動(dòng)力非農(nóng)轉(zhuǎn)移對(duì)糧食生產(chǎn)效率的影響程度呈現(xiàn)出差異化:糧食平衡區(qū)>糧食主產(chǎn)區(qū)>糧食主銷區(qū)。在糧食平衡區(qū),勞動(dòng)力轉(zhuǎn)移對(duì)糧食生產(chǎn)技術(shù)效率的提升有最明顯的作用,從現(xiàn)實(shí)角度和技術(shù)效率的定義出發(fā),該顯著作用可能來(lái)源于該區(qū)域還存在較多剩余的農(nóng)村勞動(dòng)力,因此,應(yīng)該加大對(duì)農(nóng)村勞動(dòng)力非農(nóng)轉(zhuǎn)移的有序指導(dǎo)和有效保障工作。
(3)農(nóng)村人力資本水平對(duì)糧食生產(chǎn)技術(shù)效率具有顯著正向作用關(guān)系但影響力度不大。換言之,農(nóng)村人力資本水平的提高能夠在一定程度上促進(jìn)糧食生產(chǎn)效率的提升,之所以作用甚微,也就是說(shuō)勞動(dòng)力質(zhì)量邊際效應(yīng)低下,源于中國(guó)農(nóng)村勞動(dòng)力資源存在著質(zhì)量意義的過(guò)?,F(xiàn)象,同時(shí)也揭示了我國(guó)農(nóng)業(yè)生產(chǎn)技術(shù)進(jìn)步在很大程度上屬于非技能偏態(tài)技術(shù)進(jìn)步。然而,人力資本在農(nóng)業(yè)增長(zhǎng)中的作用是毋庸置疑的?,F(xiàn)階段的中國(guó)農(nóng)業(yè)正處在由傳統(tǒng)農(nóng)業(yè)向現(xiàn)代農(nóng)業(yè)轉(zhuǎn)變的關(guān)鍵過(guò)程,人力資本作為重要的生產(chǎn)投入要素能夠很好的解釋農(nóng)業(yè)產(chǎn)出的增長(zhǎng),人力資本存量越高帶來(lái)的技術(shù)效率越高,這一結(jié)論符合新經(jīng)濟(jì)增長(zhǎng)理論,也預(yù)示著中國(guó)農(nóng)業(yè)正在向內(nèi)生型農(nóng)業(yè)發(fā)展方式轉(zhuǎn)變,盡管該種發(fā)展方式目前只存在于發(fā)達(dá)經(jīng)濟(jì)體中,它是中國(guó)未來(lái)農(nóng)業(yè)的發(fā)展方向和目標(biāo)。
(編輯:尹建中)
參考文獻(xiàn)(References)
[1]李谷成,馮中朝,范麗霞.農(nóng)戶家庭經(jīng)營(yíng)技術(shù)效率與全要素生產(chǎn)率增長(zhǎng)分解(1999-2003年)[J].數(shù)量經(jīng)濟(jì)技術(shù)經(jīng)濟(jì)研究,2007,(8):25-34.[Li Gucheng, Feng Zhongchao, Fan Lixia. An Empirical Analysis on the Technical Efflciencies and the Decomposition of TFP of Farmers Household Management(1999-2003)[J]. Journal of Quantitative & Technical Economics, 2007,(8):25-34. ]
[2]黃金波,周先波.中國(guó)糧食生產(chǎn)的技術(shù)效率與全要素生產(chǎn)率增長(zhǎng):1978-2008[J].南方經(jīng)濟(jì),2010,(9):40-52.[Huang Jinbo, Zhou Xianbo. Technical Efficiency and Growth of Total Factor Productivity of Food Production in China: 1978-2008[J]. South China Journal Economy, 2010,(9):40-52.]
[3]劉寧.基于超效率Output-DEA模型的主產(chǎn)區(qū)糧食生產(chǎn)能力評(píng)價(jià)[J].軟科學(xué),2011,25(3): 79-83.[Liu Ning. Evaluation on the Grain Production Capacity of Major Grain Production Area Based on Superefficiency OutputDEA Model [J]. Soft Science, 2011, 25(3):79-83.]
[4]李谷成,馮中朝,范麗霞.家庭稟賦對(duì)農(nóng)戶家庭經(jīng)營(yíng)技術(shù)效率的影響沖擊:基于湖北省農(nóng)戶的隨機(jī)前沿生產(chǎn)函數(shù)實(shí)證[J].統(tǒng)計(jì)研究,2008,25(1):35-42.[Li Gucheng, Feng Zhongchao, Fan Lixia. An Empirical Analysis about the Effect of Household Endowments on the Technical Efficiency of Farmers Household Management:Evidence from the Farmers of Hubei Province[J]. Statistical Research, 2008, 25(1):35-42.]
[5]汪小勤,姜濤.基于農(nóng)業(yè)公共投資視角的中國(guó)農(nóng)業(yè)技術(shù)效率分析[J].中國(guó)農(nóng)村經(jīng)濟(jì),2009,(5):79-86.[Wang Xiaoqin, Jiang Tao. Rearch on China Agricultural Technical Efficiency Based on Public Investment on Agricultural[J]. Chinese Rural Economy, 2009,(5):79-86.]
[6]李宗璋,李定安.交通基礎(chǔ)設(shè)施建設(shè)對(duì)農(nóng)業(yè)技術(shù)效率影響的實(shí)證研究[J].中國(guó)科技論壇, 2012,(2):127-133.[Li Zongzhang, Li Dingan. Empirical Research on the Effect of Transportation Infrastructure Construction on Agricultural Technical Efficiency [J]. Forum on Science and Technology in China, 2012,(2):127-133-]
[7]顏敏,王維國(guó).人力資本結(jié)構(gòu)對(duì)我國(guó)技術(shù)效率的影響:基于隨機(jī)前沿生產(chǎn)函數(shù)的實(shí)證分析[J].數(shù)學(xué)的實(shí)踐與認(rèn)識(shí),2012,42(10):11-18.[Yan Min, Wang Weiguo. Empirical Test on Technical Efficiency of Human Capital Structure in China Based on Stochastic Frontie[J]. Journal of Mathematics in Practice and Theory, 2012,42(10):11-18-]
[8]傅曉霞,吳利學(xué).技術(shù)效率、資本深化與地區(qū)差異:基于隨機(jī)前沿模型的中國(guó)地區(qū)收斂分析[J].經(jīng)濟(jì)研究,2006,(10):52-61.[Fu Xiaoxia, Wu Lixue. Technical Efficiency, Capital Deepening and Regional Disparity[J]. Economic Research Journal, 2006,(10):52-61.]
[9]傅強(qiáng),靳娜.基于隨機(jī)前沿生產(chǎn)函數(shù)的我國(guó)主要省市人力資本與R&D投資效率實(shí)證檢驗(yàn)[J].技術(shù)經(jīng)濟(jì),2009,28(6):5-10.[Fu Qiang, Jin Na. Empirical Test on Efficiency of Human Capital and R&D Investment in China Based on Stochastic Frontier Production Function[J]. Technical Economics, 2009, 28(6):5-10.]
[10]范東君,朱有志.農(nóng)業(yè)勞動(dòng)力外流對(duì)糧食生產(chǎn)影響研究:基于二元經(jīng)濟(jì)背景[J].河北經(jīng)貿(mào)大學(xué)學(xué)報(bào),2012,33(1):39-43.[Fan Dongjun, Zhu Youzhi. The Outflow of Agricultural Labor Force on Grain Production Affection in the Context of the Dual Economy[J]. Journal of Hebei University of Economic and Business, 2012,33(1):39-43.]
[11]張小娜,沈玲玲.農(nóng)村外流勞動(dòng)力與農(nóng)村經(jīng)濟(jì)發(fā)展[J].廣東財(cái)經(jīng)職業(yè)學(xué)院學(xué)報(bào),2009,8(1):80-84.[Zhang Xioana, Shen Lingling. The Outflow of Agricultural Labor Force and Economic Development[J], Journal of Guangdong College of Finance and Economics 2009,8(1):80-84.]
[12]許馳.農(nóng)村勞動(dòng)力外流對(duì)農(nóng)村家庭養(yǎng)老的影響分析[J].職業(yè)圈,2007,2:74-76.[Xu Chi. Influence the Outflow of Agricultural Labor Force on Family Supporting [J]. Occupational Circle, 2007,(2):74-76.]
[13]陳浩.中國(guó)農(nóng)村勞動(dòng)力外流管理與農(nóng)村發(fā)展[J].農(nóng)村經(jīng)濟(jì)與管理,1997,11(1):38-41.[Chen Hao. The Management of the Outflow of Agricultural Labor Force and Rural Development[J]. Rural Economic and Management, 1997,11(1):38-41.]
[14]郭劍雄,李志俊.勞動(dòng)力選擇性轉(zhuǎn)移下的農(nóng)業(yè)產(chǎn)出增長(zhǎng):非技能偏態(tài)技術(shù)進(jìn)步與質(zhì)量過(guò)剩勞動(dòng)力假說(shuō)及其檢驗(yàn)[J].吉林大學(xué)社會(huì)科學(xué)學(xué)報(bào),2011,51(6):100-110.[Guo Jianxiong, Li Zhijun. Agricultural Output Increase Under the Context of Selective Labor Transfer: A Empirical Test of Hypothesis of Nonskillbiased Technical Change and Qualitysurplus Labor Force[J]. Jilin University Journal Social Sciences Edition,2011,51(6):100-110.]
[15]何建新,舒宏應(yīng),田云.我國(guó)農(nóng)村勞動(dòng)力轉(zhuǎn)移數(shù)量測(cè)算及影響因素分解研究[J].中國(guó)人口·資源與環(huán)境,2011,21(12):148-152.[He Jianxin, Shu Hongying, Tian Yun. Study on Calculation of Rural Labor Force Transfer in China and Influential Factors[J].China Population, Resources and Environment, 2011,21(12):148-152.]
[16]李志俊,郭劍雄.選擇性轉(zhuǎn)移與人力資本深化:理論及實(shí)證[J].思想戰(zhàn)線,2010,36(4):112-117.[Li Zhijun, Guo Jianxiong. Selective Labor Transfer and Human Capital: The Theory and the empirical[J]. Thinking,2010,36(4):112-117.]
[17]白南生,李靖.城市化與中國(guó)農(nóng)村勞動(dòng)力流動(dòng)問(wèn)題研究[J].中國(guó)人口科學(xué),2008,(4):1-10.[Bai Nansheng, Li Jing. Chinas Urbanization and Rural Labor Migration[J]. Chinese Journal of Population Science,2008,(4):1-10.]
[18]盛來(lái)運(yùn).中國(guó)農(nóng)村勞動(dòng)力外出的影響因素分析[J].中國(guó)農(nóng)村觀察,2007,(3):2-15.[Sheng Laiyun. Analysis of the Determinants of Rural Labor Migration in China[J]. China Rural Survey,2007,(3): 2-15-]
[19]李谷成.人力資本與中國(guó)區(qū)域農(nóng)業(yè)全要素生產(chǎn)率增長(zhǎng):基于DEA視角的實(shí)證分析[J].財(cái)經(jīng)研究,2009,35(8):115-128.[Li Gucheng. Human Capital and TFP Growth of Regional Agriculture in China: Empirical Study Based on Data Envelopment Analysis [J]. Journal of Finance and Economics,2009,35(8):115-128.]
[20]Battese G E, Coelli T J. A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data [J]. Empirical Economics,1995,(20):325-332.
[21]Panutat S,Peter S. Estimates of Technical Inefficiency in Stochastic Frontier Models with Panel Data: Generalized Panel Jackknife Estimation [J]. Journal of Productivity Analysis, 2010,34(2):83-97.
Abstract Based on the 2001-2010 panel data about grain production of 30 provinces in China, the random frontier production function model is used to calculate grain production technical efficiencies of the main production area, the main sales area and the balance area. Then, the variables reflecting the influence of the evolvement of rural labor resources are taken into the technical inefficiency model which investigates how the efficiency of food production will be affected by changes of the size and quality of labor resources in different rural regions. The results show that the switch of the rural labor resources to nonagricultural occupations provides a powerful stimulus to the efficiency of food production. And the balance area experiences the strongest effect, followed immediately by the main production area and then the main sales area. It shows that there are more rural surplus labor in the balance area, and transferring surplus labor force has the significant effect on promoting grain production efficiency in this area. In addition, rural human capitals also have a highly positive but limited influence on the efficiency of food production, which reveals that the surplus quality of labor exists, and also indicates the technological progress in China is a largely nonskill technological progress . Furthermore, the technical efficiencies show a tendency to rise steadily throughout China and in three areas above, while the main sales area has the highest technical efficiency, the main production area coming second, and the balance area being the bottom.
Key words switch to nonagricultural occupations; rural human capital stocks; technical efficiency; regional difference
[20]Battese G E, Coelli T J. A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data [J]. Empirical Economics,1995,(20):325-332.
[21]Panutat S,Peter S. Estimates of Technical Inefficiency in Stochastic Frontier Models with Panel Data: Generalized Panel Jackknife Estimation [J]. Journal of Productivity Analysis, 2010,34(2):83-97.
Abstract Based on the 2001-2010 panel data about grain production of 30 provinces in China, the random frontier production function model is used to calculate grain production technical efficiencies of the main production area, the main sales area and the balance area. Then, the variables reflecting the influence of the evolvement of rural labor resources are taken into the technical inefficiency model which investigates how the efficiency of food production will be affected by changes of the size and quality of labor resources in different rural regions. The results show that the switch of the rural labor resources to nonagricultural occupations provides a powerful stimulus to the efficiency of food production. And the balance area experiences the strongest effect, followed immediately by the main production area and then the main sales area. It shows that there are more rural surplus labor in the balance area, and transferring surplus labor force has the significant effect on promoting grain production efficiency in this area. In addition, rural human capitals also have a highly positive but limited influence on the efficiency of food production, which reveals that the surplus quality of labor exists, and also indicates the technological progress in China is a largely nonskill technological progress . Furthermore, the technical efficiencies show a tendency to rise steadily throughout China and in three areas above, while the main sales area has the highest technical efficiency, the main production area coming second, and the balance area being the bottom.
Key words switch to nonagricultural occupations; rural human capital stocks; technical efficiency; regional difference
[20]Battese G E, Coelli T J. A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data [J]. Empirical Economics,1995,(20):325-332.
[21]Panutat S,Peter S. Estimates of Technical Inefficiency in Stochastic Frontier Models with Panel Data: Generalized Panel Jackknife Estimation [J]. Journal of Productivity Analysis, 2010,34(2):83-97.
Abstract Based on the 2001-2010 panel data about grain production of 30 provinces in China, the random frontier production function model is used to calculate grain production technical efficiencies of the main production area, the main sales area and the balance area. Then, the variables reflecting the influence of the evolvement of rural labor resources are taken into the technical inefficiency model which investigates how the efficiency of food production will be affected by changes of the size and quality of labor resources in different rural regions. The results show that the switch of the rural labor resources to nonagricultural occupations provides a powerful stimulus to the efficiency of food production. And the balance area experiences the strongest effect, followed immediately by the main production area and then the main sales area. It shows that there are more rural surplus labor in the balance area, and transferring surplus labor force has the significant effect on promoting grain production efficiency in this area. In addition, rural human capitals also have a highly positive but limited influence on the efficiency of food production, which reveals that the surplus quality of labor exists, and also indicates the technological progress in China is a largely nonskill technological progress . Furthermore, the technical efficiencies show a tendency to rise steadily throughout China and in three areas above, while the main sales area has the highest technical efficiency, the main production area coming second, and the balance area being the bottom.
Key words switch to nonagricultural occupations; rural human capital stocks; technical efficiency; regional difference