地理研究  2016 , 35 (7): 1301-1313 https://doi.org/10.11821/dlyj201607007

研究论文

城市区位条件与企业区位动态研究

刘颖12, 郭琪3, 贺灿飞12

1. 北京大学城市与环境学院,北京 100871
2. 北京大学—林肯研究院城市发展与土地政策研究中心,北京 100871
3. 南开大学经济与社会发展研究院,天津 300071

Urban characteristics and firms' location selection

LIU Ying12, GUO Qi3, HE Canfei12

1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
2. Center for Urban Development and Land Policy, Peking University-Lincoln Institute, Beijing 100871, China3. Institute of Economic and Social Development, Nankai University, Tianjin 300071, China

通讯作者:  通讯作者:贺灿飞(1972- ),男,江西永新人,教授,研究方向为经济地理、产业和区域经济、环境地理。E-mail: hecanfei@urban.pku.edu.cn

收稿日期: 2015-11-26

修回日期:  2016-04-4

网络出版日期:  2016-07-30

版权声明:  2016 《地理研究》编辑部 《地理研究》编辑部

基金资助:  国家自然科学基金国家杰出青年基金(41425001)国家自然科学基金项目(41271130)

作者简介:

作者简介:刘颖(1990- ),女,浙江上虞人,硕士,研究方向为区域经济与产业发展。E-mail: liuyingpku@pku.edu.cn

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摘要

随着新新经济地理理论的发展,企业异质性的研究逐渐受到重视,不同效率企业的区位选择被认为是造成城市生产效率差异的重要原因。验证企业区位选择对城市生产效率的影响,以及探讨企业区位选择的城市影响要素是研究的关键问题。沿用Baldwin和Melitz等学者的研究思路,从企业区位主动选择与被动选择的视角,理解中国城市生产效率的差异及其变化,分析企业区位自选择效应的空间差异。在此基础上,采用2002-2007年的规模以上工业企业面板数据,通过建立基于企业进入、退出区位动态的回归模型,揭示企业区位自选择效应的作用机制和城市影响因素。研究发现:企业区位自选择效应确实存在,不同效率企业的主动选择和被动选择都会影响城市的生产效率。生产率较高的工业企业倾向于选择科技研发水平高、市场潜力大、产业相对集聚的城市,生产率较低的工业企业更容易因城市高昂的要素成本和激烈的行业竞争,尤其是同行企业竞争而被挤出。此外,政府的政策优惠可以吸引高效率企业进入,但这种政策倾斜也会加剧其他企业的退出。因此,提高科技水平、扩大市场规模、促进产业集聚、合理运用政策调控是提高城市竞争力的关键。

关键词: 城市要素 ; 企业异质性 ; 主动选择 ; 被动选择

Abstract

With the development of the "new" New Economic Geography, firm heterogeneity has received considerable attention in academic inquiry, resulting in an extensive literature focusing on firm heterogeneity and firm-level decision-making. It is believed that the location selection effect of firms with different productivity is one of the major factors causing urban productivity variances. Based on selection effect and sorting effect by Baldwin (2006) and Melitz (2008), this paper focuses on firms' location self-selection effect and the effect of firm location on urban productivity in China, to provide empirical evidence on the impact of firms' location self-selection on urban productivity and explore the urban factors behind firms' self-selection decisions. Using firm-level data of China's industries during 2002-2008, this paper seeks to argue that the relationship between firm's location self-section and urban productivity interacts with each other. Empirical results confirm that, on the one hand, both the selection effect and sorting effect of firms' location self-selection had impacts on urban productivity. On the other hand, cities, with relatively high level of technological research and development, larger market scale and higher degree of industry agglomeration, are more attractive to high productive firm, on the contrary, are more likely to crowd out those lower productivity firm. Further analysis reveals that favorable government policy could act as an effective factor in attracting firms with high productivity while in the meantime, may also crowd out firms with lower productivity. Policy makers that seek to improve urban competitiveness in China should pay much more attention to those policies that could help to improve the urban technological level, market scale, and degree of agglomeration.

Keywords: urban characteristics ; firm heterogeneity ; selection effect ; sorting effect

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刘颖, 郭琪, 贺灿飞. 城市区位条件与企业区位动态研究[J]. , 2016, 35(7): 1301-1313 https://doi.org/10.11821/dlyj201607007

LIU Ying, GUO Qi, HE Canfei. Urban characteristics and firms' location selection[J]. 地理研究, 2016, 35(7): 1301-1313 https://doi.org/10.11821/dlyj201607007

1 引言

城市生产效率是衡量城市竞争力的重要指标,越来越多的研究表明,尽管要素投入仍然是经济增长的主要源泉,但生产效率的差异才是区域发展不均衡的主要决定力量[1,2]。传统的集聚经济和新经济地理理论认为,经济活动在地理上的集中能节约成本、提升效率,是解释生产效率空间差异的主要因素,也是提高城市竞争力的重要途径。产业集群内企业间的溢出效应能带来更多的商业化创新产出,推动区域创新,提高城市生产效率。但随着企业异质性理论在区域经济领域的广泛应用,集聚效应对城市生产效率的作用开始受到质疑和挑战。新新经济地理提出高效率企业集聚到大城市或发达地区,而低效率企业挤出到外围低竞争水平区域[3,4]。这种企业区位选择效应被认为是城市企业生产率提高的主要因素,集聚经济的作用长久以来被高估了[5]

Baldwin等学者将自选择效应理论引入到城市生产效率的研究,认为异质性企业自发选择区位是造成城市生产效率差异的主要原因。Baldwin等发现高生产效率的企业偏好在规模较大的市场选址[4]。Melitz等提出大城市的高竞争和高成本可能会挤出低效率企业[6]

因此,不同效率企业区位动态,即高效企业进入、低效企业退出,会促进城市整体生产效率的提升。目前,越来越多的实证研究开始比较企业区位自选择效应和集聚效应对城市生产效率的作用。Saito等分别以智利食品行业和日本纺织业为例,发现选择效应确实存在,且比集聚效应更为重要[7,8]。傅江帆等基于中国电子行业数据对中国城市生产效率差异进行了研究,发现中国大城市正经历着从低效企业被动挤出转向高效企业主动进入的过程[9]。但Combes等却发现企业的自选择效应不能解释生产力的空间差异[10]

那么,企业区位自选择效应在中国是否存在?影响企业区位选择的城市要素有哪些?本文从企业区位动态的微观视角,探讨异质性企业区位选择的影响因素,揭示中国企业的城市选择决策机制,有助于理解造成城市间竞争力差距的内在原因,对于提升中国城市竞争力,缩小城市间差距,推进新型城镇化建设,具有重要现实意义,同时也在提高地区招商引资政策的针对性方面提出重要建议。

2 企业区位自选择效应的理论研究

企业的异质性使得企业在区位选择时存在差异,生产率较高的企业能够经受激烈的竞争从而选择分布在经济中心,以期从大规模的市场中获得规模经济效应;生产效率较低的企业为了避免激烈竞争而居于经济外围,这种企业动态过程叫做“企业区位自选择”。企业区位自选择对城市生产效率的影响主要体现为两种作用机制:主动选择效应和被动选择效应(图1)。

图1   企业区位自选择效应的两种作用机制

Fig.1   Two mechanisms of firms' location self-selection effect

2.1 主动选择机制

受到大城市特定要素的吸引,高效率企业更愿意进入大城市,进而导致大城市平均生产效率的提高。该效应在企业进入城市前发挥作用,使企业主动做出选择,故称为主动选择效应[4]。已有研究表明,对高效率企业来说,对拥有以下三方面特质的城市具有较大吸引力:① 有较高技能的劳动力、较高的科技水平和较好的创新文化;② 宽容的环境能够使创新成果更容易投入市场;③ 城市中激烈的竞争和选择机制能够让拥有更广阔市场的企业变得更有竞争力[11]。具体来讲,城市的特定要素包括技术水平、市场规模、产业集聚等,决定了能够在多大程度上吸引高效率企业,此外政府的区域政策也会对高效率企业是否选择该城市造成影响。

对于高效企业而言,创新能力是其核心竞争力。获取地方创新资源,共享技术信息,依赖区域创新系统获得创新效益,对高效企业区位选址尤为重要[12]。高校、研究所等公共科研机构不仅能直接为企业创新提供相关技术领域前沿的科技知识,还能为企业提供人才储备和交流机会,营造良好的创新环境,是高效企业区位选择的重要因素[13,14]。此外,产业集聚是企业获得知识的另一个重要来源。企业在地域上集中可以通过建立横向或纵向联系实现知识和信息的共享交流,提高研究开发的溢出效益,促进区内企业技术创新效率增加[15]。同时,集聚带来的专业化市场和基础设施共享,可以降低企业成本,有利于企业生存[16]

市场规模是吸引高效率企业的另一个重要因素。Baldwin等发现,高生产效率的企业偏好在规模较大的市场选址,因为当产品可以高度替代时,高生产率的企业能够从与同行业的低生产率企业的竞争中获得巨大收益[4]。Saitco等也指出高效企业的销售能力强,更需要关联的专业化运作,因此产业多样化和市场规模庞大是吸引高效企业的关键因素[7]

政府政策也会对企业的主动区位选择决策产生影响。目前,关于补贴政策能否吸引高效率企业进驻还存在争议。现有的研究普遍认为直接补贴、低价土地和税收减免等政府补贴政策能够变相减少企业生产成本,吸引企业进入。实证研究也表明政府补贴显著影响厂商的选址行为[17,18]。但Baldwin等结合企业异质性研究,发现高效率企业偏好大市场,而低效率企业偏好提供补贴的小市场,政府的补贴政策最终吸引低效企业集中,而高效企业仍集中在大市场[4]。梁琦等在研究中国的企业异质性与地区补贴中也发现,在补贴政策下,欠发达地区更多的是低效率企业进入,而高效率企业逐渐向东部地区集中[19]

2.2 被动选择机制

企业能否在一个地区生存取决于企业的生产效率和城市的市场特性是否匹配,大城市的高成本和高竞争可能会挤出低效率企业,从而提高城市的整体生产效率。由于该效应在企业进入城市后发挥作用,使企业被动做出选择,故称为被动选择效应[6]。在理论模型中,挤出低效率企业的城市特性通常被解释为城市生存成本、市场竞争程度和地方政策等。

当众多经济活动在空间集聚,企业在享受城市经济带来的外部性收益的同时,也必须忍受土地价格上涨、劳动力资源短缺等拥挤成本。随着交通运输成本的下降,土地价格、劳动力成本成为影响企业迁出的主要原因,土地成本高主要引起企业在城市核心区域周围的近距离迁移,而劳动力短缺则是导致企业向其他边缘区域迁移的主要动机[20,21]。高效率企业凭借其较低的生产成本更能容忍大城市的高地价、高劳动成本,而低效率企业为节约生产成本只能迁移到外围。

城市集聚经济带来的高竞争也会挤出低效率企业。企业间的竞争程度会根据市场规模的大小而变化[6]。城市市场规模越大,企业间的竞争越激烈,产品的替代性越多,价格弹性越大。企业之间效率异质性和产品替代弹性,使得高效企业的产品更具有价格竞争力,而低效企业由于缺乏竞争力逐渐被市场淘汰[5,22]。Syverson通过研究美国混凝土产业发现,市场需求密度高的地方,消费者很容易更换生产商,低效率企业难以持续运营[23]。因此,在市场演化中,低效率企业会被高效率的企业挤出市场,迁移至外围低竞争水平区域,依靠贸易障碍生存[3,4,24]

政府补贴政策会加剧这种分类效应。研究发现政府补贴使得高效率企业向中心区域转移,低效率企业则向外围区域转移,从而进一步扩大了区域产业发展的非平衡性[4,19]。此外,政府补贴的介入使得市场机制无法正常运作,造成受补贴企业成本扭曲,而间接挤出未受到补贴的企业。

3 企业区位自选择效应的空间格局

3.1 研究对象选择与数据来源

对生产效率的衡量,传统研究大多采用劳动生产率,但其由于行业差异控制不了技术层面的差距。因此本文采用全要素生产率(TFP)衡量企业和地区的生产效率。本文借鉴Brandt等提出的方法[25,26],对中国企业数据库进行细致的处理,构建面板数据,为规避联立性和样本选择偏差所引起的内生性,采用Olley等提出的估计方法[27],估计企业的全要素生产率,并在地级市层面根据企业从业人数加权得到城市层面的TFP。

本文的基础数据来源于2002-2008年《中国工业企业数据库》。该数据库由国家统计局建立,包含全国国有工业企业以及规模以上非国有工业企业。本文采用中国工业企业数据库中的全部工业企业数据(包括采掘业和制造业企业),共77820个企业,1758808条企业数据。企业匹配方法以Brandt等提出的三阶段方法[25]为基础,参考了Yang等的改进[26],构建2002-2008年工业企业非平衡面板。企业进入是指企业上一年度不在该城市,而于本年度在该城市出现;企业退出是指企业上一年度在该城市,而本年度从该城市消失。由于国有工业企业以及规模以上非国有工业企业从业人数占全部工业企业的90%以上,利用这些企业按照从业人数比例在城市层面加权计算得到的城市TFP,几乎等同于全部工业企业加权得到的城市TFP。

其他解释变量的数据主要来源于对应年份的《中国统计年鉴》《中国区域统计年鉴》《中国城市统计年鉴》及所涉及地区的统计年鉴等。其中,受限于数据的可获得性,城市变量缺少了部分城市的数据,包括少数民族自治区、海南、港澳台地区全部或部分城市(约79个城市或地区)。

3.2 企业区位自选择效应空间格局

在地级市尺度上,中国城市生产效率呈现出明显的空间差异。利用工业企业数据库计算企业TFP,按照从业人数比例,在城市层面加权计算,得到2002年、2007年各城市TFP,如图2所示。从图2可以发现,除中西部一些城市由于企业数量过少和产业差异原因导致城市TFP值异常,高TFP城市主要集中在长三角、珠三角和环渤海三大经济圈内以及四川、重庆、东北等少数地区。三大经济圈作为中国经济发展核心区,拥有优越的区位优势、良好的产业基础和发达的创新资源,是培育高效率企业的温床。四川、重庆、东北等地区一方面作为国有工业企业分布较为集中的地区,相对资金雄厚,政府政策支持力度大,企业的生产效率较高;另一方面老工业基地和三线建设重点地区,产业结构单一,资本密集型产业比例较高,导致全要素生产率较高。与2002年相比,2007年城市的生产率反而有所下降,在珠三角、长三角地区尤为明显。这很可能与这一时期国际市场逐步开放,大量出口加工型中小型工业企业涌入有关。

图2   2002年、2007地级市城市TFP

Fig. 2   TFP of prefecture-level city in 2002 and 2007

具体看不同生产效率企业的区位选择行为,本文将全国所有规模以上工业企业按照TFP从低到高进行排序,取排名前25%的企业作为高TFP企业,后25%的企业作为低TFP企业。可以发现,高TFP的企业更倾向在长三角、珠三角和环渤海经济圈布局。2002年,在三大经济圈的城市,其高TFP企业成立的数量和比例都明显高于其他地区;2007年,三大经济圈,特别是环渤海经济圈的城市,高TFP企业成立的数量有所增加且高于其他地区,但比例有所下降。这印证了上文提到的2007年有较多低效率企业进入,高TFP企业的占比下降,导致城市总体TFP有所下降。此外,川渝地区高TFP企业成立的数量有大幅度的增加,而福建、浙江一些城市高TFP企业成立的数量反而有明显的减少。

而对于企业退出行为,超过40%的城市表现出低TFP企业占所有退出企业的比例大于45%,超过70%的城市表现出低TFP退出企业的比例大于30%,说明低TFP确实更容易退出。在东部城市退出企业中,低TFP企业的数量较大,但比例明显低于中西部地区,是因为东部城市的竞争更为激烈,有更多的企业被“挤出”。对比2002年、2007年的企业退出行为,发现低TFP企业退出的数量明显增加,但比例有所下降,说明城市内部竞争越发激励,企业的被动选择机制变得越发显著。

通过工业企业进入、退出的空间分布(图3图4)可以发现,不同地区的城市TFP成因存在很大差异。科技水平较高、市场规模较大的城市,如上海、深圳、北京等为代表的三大经济圈核心区,存在显著的企业主动选择效应。同时,由于大城市的高成本和高竞争,这些地区也存在显著的企业被动选择效应。产业集聚对企业区位选择的作用影响不一,东部沿海产业集聚地区的高TFP企业进入普遍较多,但浙江、福建和广东的一些城市,新成立企业中高TFP企业的比例明显偏低。此外,地方政策也是影响企业区位选择的重要因素。以四川、重庆、山东等为代表的快速发展地区,企业的主动选择效应十分显著,这在很大程度上与这些地区依靠政策手段引进优质企业有关。

图3   2002年、2007地级市高TFP企业进入情况

Fig. 3   Firms entering of high-leveled TFP firm in 2002 and 2007

图4   2002年、2007地级市低TFP企业退出情况

Fig. 4   Firms entering of low-leveled TFP firm in 2002 and 2007

4 企业区位自选择效应的实证检验

4.1 变量选取与模型设定

为了系统探究企业区位自选择效应的作用机制和影响因素,本文选取2002-2007年全国工业企业的数据进行分析,从企业主动选择效应和企业被动选择效应两个角度建立回归模型。

主动选择效应反映的是城市对高效率企业的吸引,这种吸引力包括城市的科技水平、市场大小、产业集聚、政策扶持等优势。本文采用2002-2007年进入工业企业的TFP为被解释变量,以地级市层面的科技水平、市场水平和集聚水平以及政府对该企业的政策补贴作为解释变量,研究吸引高TFP企业进入的影响因素(表1)。本文采用OLS估计,计量模型建立如下:

yijt=αijt+β1Tjt+β2Mjt+β3Ajt+β4Sijt+β5Zit+β6η+β7γ+εijt(1)

式中:i表示每个新成立企业;j表示企业所在城市;t表示企业所在年份; yijt表示新成立企业的TFP; Tjt表示当年企业进入城市的科技水平矩阵,包括公共科技资源和人力资源; Mjt表示当年企业进入城市的市场水平矩阵; Ajt表示当年企业进入城市的集聚经济矩阵,包括产业专业化与多样化集聚; Sijt表示当年企业进入城市得到的政策优惠; Zjt表示企业自身性质的矩阵,包括企业规模和所有制; ηγ分别表示行业和年份的虚拟变量,用来控制不同行业自身性质带来的TFP固有差异和不同年份TFP的固有差异; εijt是随机误差项。

表1   企业主动选择效应解释变量定义及符号

Tab. 1   Explanations of selection effect model's variables

变量变量符号定义年份预期符号
进入企业TFPTFP新成立企业的TFP2002-2007
科技水平College城市普通高等学校数2002-2007+
Finance城市年科技财政支出2002-2007+
Education城市每万人在校大学生数2002-2007+
Labour城市同行企业从业人数2002-2007+
市场水平NMarket城市国内市场潜力2002-2007+
GMarket城市国外市场潜力2002-2007+
集聚水平Sagg城市同行企业年工业总产值(平减到1998年)2002-2007+
DaSgg城市非同行企业年工业总产值(平减到1998年)2002-2007+
Compete城市同行企业竞争指数2002-2007-
政府政策Subs_inc企业当年补贴收入2002-2007+
Subsidy城市全部工业企业补贴收入2002-2007-
个体变量Size企业当年工业总产值(大:>2000人,
中:200~2000人,小:<200人)
2002-2007+
Ownership企业所有制2002-2007
控制变量Industry行业类别2002-2007
Year企业进入时间2002-2007

注:Nmarket=Pkdik+Pisiπ,Pi表示企业进入地级市的社会消费品零售总额;Pk表示其他地级市的社会消费品零售总额;dik表示i城市到k城市的最短距离;Si表示i城市的面积。Gmarket=fidi,fk表示企业进入地级市的出口交货值;di表示该地级市到最主要进出口口岸的最近距离。Compete=nieiNE,ni表示企业进入地级市的同行企业个数;ej表示该地级市的同行企业从业人数;N表示全国同行企业个数;E表示全国同行企业从业人数。

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被动选择效应反映的是城市对低效率企业的挤出,其主要受到城市生存成本、市场竞争程度和政府政策导向的影响。本文将2002-2007年工业企业下一年是否退出(0/1)作为因变量,以地级市层面的要素成本、政府政策和产业集聚作为自变量,并用企业TFP与这些自变量的乘积作为交叉变量(表2),研究这些因素对不同TFP企业的挤出作用。由于因变量为0和1,本文建立Probit估计模型如下:

Pijt=αijt+β1Cjt+β2Sjt+β3Ajt+β4Cjt×TFPijt+β5Sjt×TFPijt+β6Ajt×TFPijt+β7Zit+β8η+β9γ+εijt(2)

式中:i表示每个观测企业;j表示企业所在城市;t表示企业所在年份; Pijt表示企业下一年是否退出; Cjt是表示当年企业所在城市的要素矩阵; Sjt是表示当年企业所在城市的政策优惠; Ajt是表示当年企业进入城市的集聚经济矩阵; Cjt×TFPijtSjt×TFPijAjt×TFPijt分别表示对应变量与企业TFP相乘的交叉变量; Zit表示企业自身性质的矩阵,包括企业规模和所有制;η γ分别表示行业和年份的虚拟变量,用来控制不同行业自身性质带来的TFP固有差异和不同年份的TFP固有差异; εijt是随机误差项。

表2   企业被动选择效应解释变量定义及符号

Tab. 2   Explanations of sorting effect model's variables

变量变量符号定义年份预期符号
企业退出Prob企业下一年是否退出(0/1)2002-2007
企业TFPTFP企业TFP2002-2007-
要素成本Wage城市市辖区职工平均工资2002-2007+
Landprice城市国有土地单位面积出让价格2002-2007+
集聚水平Sagg城市同行企业年工业总产值(平减到1998年)2002-2007+
Dagg城市非同行企业年工业总产值(平减到1998年)2002-2007+
Compete城市同行企业竞争指数2002-2007+
政府政策Subsidy城市全部工业企业补贴收入2002-2007+
个体变量Size企业从业人数规模(大:>2000人,
中:200~2000人,小:<200人)
2002-2007-
Ownership企业所有制2002-2007
控制变量Industry行业类别2002-2007
Year企业进入时间2002-2007

注:Compete=nieiNE,ni表示企业进入地级市的同行企业个数;ej表示该地级市的同行企业从业人数;N表示全国同行企业个数;E表示全国同行企业从业人数。

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关于上述计量模型,有以下三点说明:

第一,企业的创新能力与企业所属行业和所处时间有很大关系,可能对衡量企业区位自选择效应造成很大干扰。为排除行业特性和时间差异对结果可能造成的干扰,控制行业和年份差异。

第二,由于各类变量之间存在相关性,为避免多重共线性问题造成回归结果失真或难以估计准确,本文将强相关变量(相关性大于0.6)分开进入回归模型。

第三,考虑到模型估计中误差项可能存在异方差等问题,本文在估计时采用异方差稳健的模型(HSK-robust),通过对方差大的观测值赋予较小的权重来解决异方差问题,保证估计结果的一致性。

4.2 回归结果分析

4.2.1 主动选择效应 从企业进入模型来看,工业企业主动选择效应确实存在,受到各类城市因素的影响。模型总体拟合效果很好,通过Wald检验,回归结果如表3所示。

表3   企业主动选择效应模型回归结果

Tab. 3   Regression result of selection effect model

变量变量含义(1)(2)(3)(4)
College高校数量0.0976***
(3.90)
Finance科技财政支出0.0211***
(17.07)
Education在校大学生数0.810
(8.00)
Labour同行职工人数0.309***
(3.57)
NMarket国内市场潜力0.0156***
(43.30)
GMarket国际市场潜力0.0486***
(30.33)
SAgg同行集聚水平0.0888***
(10.99)
SAgg2同行集聚水平二次项-0.00654***
(-8.67)
DAgg非同行集聚水平0.0348***
(19.92)
DAgg2非同行集聚水平
二次项
-0.000656***
(-6.55)
Compete同行竞争水平-0.000194***
(-14.19)
Subs_inc企业所受补贴0.0824***0.0835***0.0819***0.0443***
(10.39)(10.53)(10.31)(10.63)
Subsidy城市补贴支出-0.0177-0.0702***-0.129***-0.128***
(-0.85)(-3.46)(6.71)(-6.26)
Size_middle企业规模(中)-0.185***-0.184***-0.199***-0.198***
(-21.31)(-21.25)(-22.94)(-23.27)
Size_large企业规模(大)0.291***0.297***0.274***0.245***
(7.95)(8.11)(7.47)(6.81)
Industry行业类型includedincludedincludedincluded
Ownership所有制类型includedincludedincludedincluded
Year年份includedincludedincludedincluded
_cons常数项1.073***1.081***1.154***1.313***
(61.96)(63.06)(67.29)(77.35)
N样本数量285094285094285094285094

注:***表示P<0.01,**表示P<0.05,*表示P<0.1,括号内是t统计量。

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回归结果显示,新进入工业企业的TFP与城市的科技水平、市场大小、产业集聚、政策扶持等因素存在相关关系。

第一,高TFP的企业更倾向于进入科技和人才资源优越的城市。其中,进入企业TFP与大学的数量、科技财政支出呈正相关关系,说明高TFP追求好的创新环境和公共支持。进入企业TFP与同行业从业人员数量呈显著的正相关关系,但与大学生的数量无显著关系,说明相比高科技人才资源,熟练的劳动力资源对于高效企业的区位选择更为重要,Hsu等的研究也得到相似的结论[28]。Hsu等将劳动力划分为可移动的高技能劳动力和不可移动的本地低技能劳动力,研究发现,当不可以移动的低技能劳动力的比例更大时,企业的选择效应就更加重要[28]

第二,高效率的企业更倾向于进入市场潜力大的城市,且国外的市场潜力对高TFP企业进入更有吸引力,这是因为高效率企业具有较强的产品竞争力。市场规模较大,产品竞争越完全,高生产率企业的价值实现越充分[4]。开拓海外市场能够为高效率企业带来更大收益。这就解释了为什么高生产效率的企业多集中于沿海地区。

第三,高效率的企业更倾向于进入产业集聚的城市。同行企业的集聚和非同行企业的集聚都能吸引高TFP企业进入,且同行企业的集聚吸引力更强。这是因为产业集聚能通过面对面交流、人才流动、合作开发等形式的知识溢出为企业创造良好的创新环境。但这种促进作用并不是线性关系。本文加入了衡量同行和非同行企业变量的平方项,发现它们呈一种倒U型关系,即适当的产业集聚能促进高TFP企业进入,但随着产业集聚进一步增强,导致企业恶性竞争,反而不利于高效率企业进入。城市同行企业竞争指数也表明,激烈的企业竞争,特别是小企业之间过度的同质化竞争,不利于高生产效率的企业进入。这是因为过度的同行竞争使得企业通过创新获得溢价的目标无法实现[29],创新企业的优势无法体现,不利于创新企业的发展。这很大程度上能解释了为什么浙江、福建、广州一些中小企业集聚城市的高效率企业成立的数量明显要比其他沿海城市少。

第四,政府对企业的直接补贴与企业生产率显著正相关,说明政府补贴能够吸引高TFP企业进入。这与Baldwin等[4,19]的研究结果不同,可能的原因是中国大部分补贴具有针对性,一些补贴只提供给效益好、创新性强的企业。但当政府补贴变量与产业集聚变量同时放入回归模型中,政府补贴对进入企业TFP的作用从0.08下降到0.04,说明产业集聚会影响政策对企业的吸引程度。Devereux等也发现同样结论[18],他们通过英国政府补贴对跨国公司新建企业选址决策的影响发现,企业更愿意在产业集聚的地区投资建厂,如果某区域有同类企业集聚,企业对补贴的反应就会很敏感,此时政府补贴政策将发挥更大的杠杆作用[18]。但城市政府补贴总额与企业生产率呈显著负相关,说明政府干预过多,不利于高效率企业进入。这是因为政府的补贴会造成市场扭曲,且腐败与补贴干预往往同时发生,这些往往不利于高效率企业进入。

4.2.2 被动选择效应 从企业退出模型来看,城市的各类因素会影响工业企业退出,且会挤出生产效率不高的企业。模型总体拟合效果很好,通过了Wald检验,结果如表4所示。

表4   企业被动选择效应模型回归结果

Tab. 4   Regression result of sorting effect model

变量变量含义(1)(2)(3)(4)
Wage城市工资水平0.0928***
(36.26)
TFP×WageTFP与工资交叉项-0.0281***
(-44.28)
Landprice城市地价水平2.605***
(32.60)
TFP×LandpriceTFP与地价交叉项-0.849***
(-32.93)
SAgg同行集聚水平0.0474***
(5.88)
TFP×SAggTFP与同行集聚交叉项-0.0135***
(-4.46)
DAgg非同行集聚水平0.0257***
(27.27)
TFP×DAggTFP非同行集聚交叉项-0.00555***
(-17.57)
Compete同行竞争水平0.00858***
(12.54)
TFP×CompeteTFP与同行交叉项-0.00273***
(-10.02)
Subsidy城市补贴支出0.0486***
(14.15)
TFP×SubsidyTFP与补贴交叉项-0.00764***
(-6.69)
Size_middle企业规模(中)-0.399***-0.397***-0.398***-0.393***
(-125.60)(-125.36)(-125.24)(-123.95)
Size_large企业规模(大)-0.630***-0.638***-0.628***-0.637***
(-63.93)(-64.81)(-63.77)(-64.64)
Industry行业类型includedincludedincludedincluded
Ownership所有制类型includedincludedincludedincluded
Year年份includedincludedincludedincluded
_cons常数项-0.689***-0.668***-0.710***-0.654***
(-55.91)(-54.95)(-53.54)(-53.58)
LR chi241375.6640474.1440765.2641743.43
Log likelihood-438841.98-439292.74-439144.92-438658.1
N样本数量1378923137892313789231378923

注:***表示P<0.01,**表示P<0.05,*表示P<0.1,括号内是t统计量。

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回归结果显示,工业企业退出决策与城市的要素成本、政策扶持及产业集聚因素存在显著的相关关系,而高TFP的企业不容易受到这些因素的影响。即高要素成本、政策扶持和产业集聚等因素会挤出低生产效率的企业,而保留高生产效率的企业。

第一,高要素成本会挤出低TFP企业。企业退出行为与劳动力成本和土地成本呈显著的正相关关系,但与各自的企业TFP交叉项呈显著的负相关,说明高的劳动力成本和土地成本对企业有显著的挤出效应,但对高TFP企业的挤出效应较弱,即更容易挤出低TFP的企业。

第二,产业集聚带来的市场竞争会挤出低TFP企业,且同行产业集聚的挤出作用较非同行产业集聚更为明显。产业集聚能促进市场分类作用有效发挥,市场竞争导致的被动选择效应逐渐显现,最终排挤掉效率低的企业,特别是同行企业的竞争。由于同行企业的产品之间具有很强的可替代性,众多企业在空间上的集聚,使得客户寻找最优产品的成本下降,导致产品竞争力弱的企业很难生存。例如长三角、珠三角地区,中小企业众多,“一村一品、一镇一业”的现象普遍,低效率企业在激烈的竞争中被淘汰,造成城市的生产效率有所提高。

第三,政府对企业个体的直接补贴会减少该企业的退出意愿,但地方干预太强、政府补贴总额过高会挤出企业,特别是低TFP企业。政府补贴政策通过现金、土地、税收等形式对企业进行补贴,能降低企业生产成本,提高企业利润,使得受补贴企业更具竞争优势,会挤出那些未收到补贴的企业。其中,TFP低的企业由于生产技术落后,生产成本高,更容易被挤出。城市政府补贴的比例越高,市场的扭曲程度也就越高。此外,张杰等的研究发现补贴虽然提升了企业利润,但提高企业生产率、促进企业创新的作用并不显著[30]

5 结论与讨论

提高城市生产效率是提高城市竞争力的重要因素,是促进城市发展的决定性力量。传统的研究将企业看作均值的、无差异的个体,忽略了不同效率企业的区位选择对城市生产效率造成的差异。本文从企业区位主动选择与被动选择的视角,采用2002-2007年中国规模以上工业企业数据实证研究发现,工业企业区位自选择效应确实存在,大城市更吸引高效率的企业进入,同时会挤出效率较低的企业。现有的企业区位自选择研究多只关注单个或单方面城市因素的影响,本文综合各类研究,从城市技术水平、市场规模、产业集聚和生存成本等方面研究企业主动、被动选择的城市影响因素,并特别强调政府政策对企业区位选择的影响。研究发现,生产率较高的工业企业倾向于选择科技研发水平高、市场潜力大、产业相对集聚的城市,但若产业过于集聚会由于竞争过于激烈不利于高效率企业进入。且熟练的劳动力资源比高科技人才资源更重要,国外市场潜力比国内市场潜力更重要,同行企业集聚比非同行集聚更重要。生产率较低的工业企业更容易因城市高昂的要素成本(土地成本、劳动力成本等)和激烈的行业竞争,尤其是同行企业竞争而被挤出。特别地,本文发现政府可以通过补贴等形式的政策优惠吸引高效率企业进入,但政府的政策倾斜也会加剧其他企业的退出。但本文是基于规模以上工业企业面板数据的计量分析,属于一般性规律讨论,对于特定个案也存在其他影响企业区位选择的因素。

工业企业区位自选择效应的影响因素和作用机制研究解释了提高城市生产效率的关键要素,对地方政府的政策制定具有重要的启示意义。第一,地方政府要加大科学教育投入,营造良好的科技研发环境,同时注重人才培养,尤其是专业的职业技能培养,为城市的自主创新提供了有力的人才支撑。第二,地方政府要发挥本地优势,完善产业配套,促成产业集群。特别要加大知识产权保护力度,规范市场竞争秩序,防止企业同质化恶性竞争,为创新企业提供良好的市场生存环境。第三,地方政府的政策调控是一把双刃剑,一方面可以直接吸引企业进入,另一方面会导致市场扭曲挤出其他企业。政府应建立严格的实施和审核标准,确保受助企业的高效性,同时要处理好市场与政府的关系,使市场在资源配置中起决定性作用,更好发挥政府的服务和引导作用。

The authors have declared that no competing interests exist.


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https://doi.org/10.1016/j.regsciurbeco.2012.05.004      URL      [本文引用: 2]      摘要

We develop a model of trade and agglomeration that incorporates trade in both intermediate goods and final goods and allows all firms to choose their locations. There are two types of labor: skilled labor, which is mobile, and unskilled labor, which is immobile. Upon choosing its factory site, a final goods firm that is managed by skilled labor can produce these goods using local unskilled labor and a variety of intermediate goods produced by productivity-heterogeneous producers. We characterize world equilibrium and establish the conditions under which industrial agglomeration arises as a stable equilibrium outcome. We show that when the unskilled labor force is small, the role played by the selection of intermediate firms becomes less important, and trade liberalization induces dispersion. When the unskilled labor force is large and the selection effect becomes influential, trade liberalization can generate non-monotonic effects on industrial agglomeration. The dispersion effect of trade liberalization arises when unskilled labor-intermediate input complementarity matters to firm selection to a greater degree. When this is the case, trade liberalization may induce less selective firm entry and cause average productivity to fall.
[29] 张昕, 陈林.

产业聚集、知识溢出与区域创新绩效: 以医药制造业为例的实证研究

. 科技管理研究, 2011, (19): 69-72.

[本文引用: 1]     

[Zhang Xin, Chen Lin.

Manufactory industry agglomeration,knowledge spillover and regional innovation performance

. Science and Technology Management Research, 2011, (19): 69-72.]

[本文引用: 1]     

[30] 张杰, 李克, 刘志彪.

市场化转型与企业生产效率: 中国的经验研究

. 经济学(季刊), 2011, (2): 571-602.

[本文引用: 1]     

[Zhang Jie, Li Ke, Liu Zhibiao.

Market-oriented transition and enterprises productivity in China

. China Economic Quarterly, 2011, (2): 571-602.]

[本文引用: 1]     

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