资源错配对中国工业全要素生产率的多维影响研究
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摘要
研究目标:以2008～2017年中国工业A股上市公司为研究样本,测算资源错配所造成的各所有制、地区、行业层面以及工业总体层面TFP损失,分解工业总体TFP损失,明确类型(所有制、地区及行业)内和类型间的具体贡献。研究方法:构建包含异质性企业的垄断竞争模型,刻画生产要素配置偏离等边际产出原则对不同层面工业TFP的多维度影响,基于反事实分析,进一步分解类型内与类型间的资源错配效应。研究发现:地方国有企业的资源错配程度高于其他所有制;地区的资源错配程度与地区经济发展水平之间存在密切联系,东部和中部的资源错配程度较低;制造业的资源错配程度相对高于采矿业、电力热力燃气及水的生产和供应业;如果达到美国制造业的资源配置标准,中国工业上市公司总体TFP将在现有基础上增加0.35～0.9倍;不同类型(所有制、地区或行业)内部资源错配与不同类型(所有制、地区或行业)之间资源错配大约分别可以解释总体工业上市公司TFP损失的一半,且不同行业之间的错配程度大于不同所有制和不同地区之间的错配。研究创新:在Hsieh和Klenow (2009)提出的资源错配测算方法的基础上,将所有制、地区及行业因素纳入一个统一的分析框架内,同时考虑了类型内和类型间的资源错配效应。研究价值:为进一步推动工业结构改革提供经验证据。
Research Objectives:Based on the dataset of China's industrial A-share listed companies from 2008 to 2017,we measure the TFP loss at the aggregate levels of ownerships,regions,sectors and the whole industry resulted by resources misallocation,and decomposes the overall TFP loss into resources misallocation within types(including types of ownership,region and sector)and between types.Research Methods:We use a standard model of monopolistic competition with heterogeneous firms to illustrate how distortions that drive wedges between the marginal products of capital and labor across firms will lower aggregate TFP.Using counterfactual experiment,we further decompose the overall TFP loss into resources misallocation within types and between types.Research Findings:Locally-administered state enterprises have highest degree of resources misallocation among different ownership types.The degree of misallocation for regions is negatively related to regional economic development,eastern and central regions have lower degree of misallocation than western and northeast parts.Manufacturing sectors have higher degree of misallocation than mining electric heating gas and water sectors.When capital and labor are hypothetically reallocated to equalize marginal products to the extent observed for manufacturing in US,we calculate industrial TFP gains of 0.35～0.9 for Chinese industry.The TFP loss resulted by resources misallocation within types is more or less the same as between types,and the degree of resources misallocation between different sectors is higher than misallocation between different ownerships and different region.Research Innovations:On the basis of Hsieh and Klenow(2009),we integrate ownership factors,industry factors and regions factors into a unified analysis framework,and consider the resources misallocation within and between types at the same time.Research Value:The study provides micro evidence for promoting the reform of industrial structure for further.
Research Objectives:Based on the dataset of China's industrial A-share listed companies from 2008 to 2017,we measure the TFP loss at the aggregate levels of ownerships,regions,sectors and the whole industry resulted by resources misallocation,and decomposes the overall TFP loss into resources misallocation within types(including types of ownership,region and sector)and between types.Research Methods:We use a standard model of monopolistic competition with heterogeneous firms to illustrate how distortions that drive wedges between the marginal products of capital and labor across firms will lower aggregate TFP.Using counterfactual experiment,we further decompose the overall TFP loss into resources misallocation within types and between types.Research Findings:Locally-administered state enterprises have highest degree of resources misallocation among different ownership types.The degree of misallocation for regions is negatively related to regional economic development,eastern and central regions have lower degree of misallocation than western and northeast parts.Manufacturing sectors have higher degree of misallocation than mining electric heating gas and water sectors.When capital and labor are hypothetically reallocated to equalize marginal products to the extent observed for manufacturing in US,we calculate industrial TFP gains of 0.35～0.9 for Chinese industry.The TFP loss resulted by resources misallocation within types is more or less the same as between types,and the degree of resources misallocation between different sectors is higher than misallocation between different ownerships and different region.Research Innovations:On the basis of Hsieh and Klenow(2009),we integrate ownership factors,industry factors and regions factors into a unified analysis framework,and consider the resources misallocation within and between types at the same time.Research Value:The study provides micro evidence for promoting the reform of industrial structure for further.
引文
[1]Banerjee A.,Duflo E.,2005,Growth Theory through the Lens of Development Economics[J],Handbook of Economic Growth,1(A),473~552.
[2]Bartelsman E.,Haltiwanger J.,Scarpetta S.,2009,Cross-Country Differences in Productivity:The Role of Allocation and Selection[R],NBER Working Paper No.15490.
[3]Brandt L.,Biesebroeck J.V.,Zhang Y.F.,2012,Creative Accounting or Creative Destruction?Firm-Level Productivity Growth in Chinese Manufacturing[J],Journal of Development Economics,97(2),339~351.
[4]Brandt L.,Tombe T.,Zhu X.,2013,Factor Market Distortions across Time,Space and Sectors in China[J],Review of Economic Dynamics,16(1),39~58.
[5]Broda C.,Weinstein D.,2006,Globalization and the Gains from Variety[J],Quarterly Journal of Economics,121(2),541~585.
[6]Chenery H.,Robinson S.,Syrquin M.,1986,Industrialization and Growth:A Comparative Study[M],Oxford University Press.
[7]Howitt P.,2000,Endogenous Growth and Cross-Country Income Differences[J],American Economic Review,90(4),829~846.
[8]Hsieh C.T.,Klenow P.J.,2009,Misallocation and Manufacturing TFP in China and India[J],Quarterly Journal of Economics,124(4),1403~1448.
[9]Jones C.I.,2011,Misallocation,Economic Growth,and Input-Output Economics[R],NBERWorking Paper No.16742.
[10]Olley S.,Pakes A.,1996,The Dynamics of Productivity in the Telecommunications Equipment Industry[J],Econometrica,64(6),1263~1297.
[11]Ouyang M.,Peng Y.L.,2015,The Treatment-Effect Estimation:A Case Study of the 2008 E-conomic Stimulus Package of China[J],Journal of Econometrics,188(2),545~557.
[12]Restuccia D.,Rogerson R.,2008,Policy Distortions and Aggregate Productivity with Heterogeneous Plants[J],Review of Economic Dynamics,11(4),707~720.
[13]Romer P.,1990,Endogenous Technological Change[J],Journal of Political Economy,98(5),S71~S102.
[14]Solow R.,1957,Technical Change and the Aggregate Production Function[J],Review of Economics and Statistics,39(3),312~320.
[15]Syverson C.,2011,What Determines Productivity?[J],Journal of Economic Literature,49(2),326~365.
[16]Young A.,1995,The Tyranny of Numbers:Confronting the Statistical Realities of East Asian Growth Experience[J],Quarterly Journal of Economics,110(3),641~680.
[17]白成太、陈光:《上市公司生产效率分析指标构建》[J],《技术经济》2016年第3期。
[18]陈永伟、胡伟民:《价格扭曲、要素错配和效率损失:理论与应用》[J],《经济学(季刊)》2011年第4期。
[19]程仲鸣、夏新平、余明桂:《政府干预、金字塔结构与地方国有上市公司投资》[J],《管理世界》2008年第9期。
[20]方明月:《先天优势还是后天努力---国企级别对企业全要素生产率影响的实证研究》[J],《财贸经济》2014年第11期。
[21]龚关、胡关亮:《中国制造业资源配置效率与全要素生产率》[J],《经济研究》2013年第4期。
[22]简泽:《企业间的生产率差异、资源再配置与制造业部门的生产率》[J],《管理世界》2011年第5期。
[23]李春霞:《产品市场竞争、所有权性质与全要素生产率---来自中国上市公司的经验证据》[J],《财贸研究》2016年第1期。
[24]聂辉华、贾瑞雪:《中国制造业企业生产率与资源误配》[J],《世界经济》2011年第7期。
[25]覃家琦:《战略委员会与上市公司过度投资行为》[J],《金融研究》2010年第6期。
[26]钱雪松、康瑾、唐英伦、曹夏平:《产业政策、资本配置效率与企业全要素生产率---基于中国2009年十大产业振兴规划自然实验的经验研究》[J],《中国工业经济》2018年第8期。
[27]吴敬琏:《推进改革对中国性命攸关》[J],《中国新闻周刊》2013年第24期。
[28]伍晓鹰:《中国经济增长及生产率表现的行业因素:1980~2012年》[A],宋立刚等主编:《中国经济增长的新源泉(第1卷)》[C],社会科学文献出版社,2017。
[29]谢攀、林致远:《地方保护、要素价格扭曲与资源误置---来自A股上市公司的经验证据》[J],《财贸经济》2016年第2期。
[30]谢地、张旺鉴:《谁阻碍了民营经济成长---基于民营经济与外资经济、国有经济关系的观察》[J],《社会科学辑刊》2015年第6期。
(1)这里的s被抽象为一个一般性概念,既可以看作某一种所有制类型,也可以看作某一个地区或行业。
(1)根据式(5)~式(8),得到类型s内企业i的资本和劳动的边际产出分别为MRPKsi=αsPsiYsi/Ksi=(σ/(σ-1))r(1+τKsi)和(1-αs)PsiYsi/Lsi=(σ/(σ-1))ω(1+τLsi),整理可得。
(2)由PsiY1/sσ=PsY1/sσ可得到Asi=κs(PsiYsi)σ/σ-1/(KsiαLsi1-αs),其中κs=(PsYs)1/1-σ/Ps。κs无法直接观测到,参照简泽(2011)的做法,令κs=1,即可得到该式。这里实际是用PsiYsi的σ/(σ-1)次幕来逼近Ysi。
(1)2017年采矿业上市公司共有74家,其中中央和地方国有企业有46家,隶属电力热力燃气及水的生产和供应业的上市公司有104家,其中中央和地方国有企业有81家。
(1)根据HK的研究,1997年美国制造业的资源错配程度与其他年份相比处于较高的水平,选取1997年美国制造业作为基准是为了得到一个较为保守的估算结果。
(1)根据式(19)进行分解时,工业总体TFP损失L采用所有制、地区和行业类型划分下测算值的算术平均数。
(1)资料来源:《中国多地热衷显示产业。或将再酿光伏悲剧》[DB/OL],人民政协网,2014年5月4日,http:/www.rmzxh.com.cn/c/2014-05-04/321800.shtml.
(2)由于反事实分析对工业样本企业的划分要同时从所有制、地区、行业三个层来展开,为了避免层次过多引起混乱,我们不再考虑要素产出弹性的异质性。而是基于工业样本企业整体的要素产出弹性来做反事实分析,即假定as=a。
[2]Bartelsman E.,Haltiwanger J.,Scarpetta S.,2009,Cross-Country Differences in Productivity:The Role of Allocation and Selection[R],NBER Working Paper No.15490.
[3]Brandt L.,Biesebroeck J.V.,Zhang Y.F.,2012,Creative Accounting or Creative Destruction?Firm-Level Productivity Growth in Chinese Manufacturing[J],Journal of Development Economics,97(2),339~351.
[4]Brandt L.,Tombe T.,Zhu X.,2013,Factor Market Distortions across Time,Space and Sectors in China[J],Review of Economic Dynamics,16(1),39~58.
[5]Broda C.,Weinstein D.,2006,Globalization and the Gains from Variety[J],Quarterly Journal of Economics,121(2),541~585.
[6]Chenery H.,Robinson S.,Syrquin M.,1986,Industrialization and Growth:A Comparative Study[M],Oxford University Press.
[7]Howitt P.,2000,Endogenous Growth and Cross-Country Income Differences[J],American Economic Review,90(4),829~846.
[8]Hsieh C.T.,Klenow P.J.,2009,Misallocation and Manufacturing TFP in China and India[J],Quarterly Journal of Economics,124(4),1403~1448.
[9]Jones C.I.,2011,Misallocation,Economic Growth,and Input-Output Economics[R],NBERWorking Paper No.16742.
[10]Olley S.,Pakes A.,1996,The Dynamics of Productivity in the Telecommunications Equipment Industry[J],Econometrica,64(6),1263~1297.
[11]Ouyang M.,Peng Y.L.,2015,The Treatment-Effect Estimation:A Case Study of the 2008 E-conomic Stimulus Package of China[J],Journal of Econometrics,188(2),545~557.
[12]Restuccia D.,Rogerson R.,2008,Policy Distortions and Aggregate Productivity with Heterogeneous Plants[J],Review of Economic Dynamics,11(4),707~720.
[13]Romer P.,1990,Endogenous Technological Change[J],Journal of Political Economy,98(5),S71~S102.
[14]Solow R.,1957,Technical Change and the Aggregate Production Function[J],Review of Economics and Statistics,39(3),312~320.
[15]Syverson C.,2011,What Determines Productivity?[J],Journal of Economic Literature,49(2),326~365.
[16]Young A.,1995,The Tyranny of Numbers:Confronting the Statistical Realities of East Asian Growth Experience[J],Quarterly Journal of Economics,110(3),641~680.
[17]白成太、陈光:《上市公司生产效率分析指标构建》[J],《技术经济》2016年第3期。
[18]陈永伟、胡伟民:《价格扭曲、要素错配和效率损失:理论与应用》[J],《经济学(季刊)》2011年第4期。
[19]程仲鸣、夏新平、余明桂:《政府干预、金字塔结构与地方国有上市公司投资》[J],《管理世界》2008年第9期。
[20]方明月:《先天优势还是后天努力---国企级别对企业全要素生产率影响的实证研究》[J],《财贸经济》2014年第11期。
[21]龚关、胡关亮:《中国制造业资源配置效率与全要素生产率》[J],《经济研究》2013年第4期。
[22]简泽:《企业间的生产率差异、资源再配置与制造业部门的生产率》[J],《管理世界》2011年第5期。
[23]李春霞:《产品市场竞争、所有权性质与全要素生产率---来自中国上市公司的经验证据》[J],《财贸研究》2016年第1期。
[24]聂辉华、贾瑞雪:《中国制造业企业生产率与资源误配》[J],《世界经济》2011年第7期。
[25]覃家琦:《战略委员会与上市公司过度投资行为》[J],《金融研究》2010年第6期。
[26]钱雪松、康瑾、唐英伦、曹夏平:《产业政策、资本配置效率与企业全要素生产率---基于中国2009年十大产业振兴规划自然实验的经验研究》[J],《中国工业经济》2018年第8期。
[27]吴敬琏:《推进改革对中国性命攸关》[J],《中国新闻周刊》2013年第24期。
[28]伍晓鹰:《中国经济增长及生产率表现的行业因素:1980~2012年》[A],宋立刚等主编:《中国经济增长的新源泉(第1卷)》[C],社会科学文献出版社,2017。
[29]谢攀、林致远:《地方保护、要素价格扭曲与资源误置---来自A股上市公司的经验证据》[J],《财贸经济》2016年第2期。
[30]谢地、张旺鉴:《谁阻碍了民营经济成长---基于民营经济与外资经济、国有经济关系的观察》[J],《社会科学辑刊》2015年第6期。
(1)这里的s被抽象为一个一般性概念,既可以看作某一种所有制类型,也可以看作某一个地区或行业。
(1)根据式(5)~式(8),得到类型s内企业i的资本和劳动的边际产出分别为MRPKsi=αsPsiYsi/Ksi=(σ/(σ-1))r(1+τKsi)和(1-αs)PsiYsi/Lsi=(σ/(σ-1))ω(1+τLsi),整理可得。
(2)由PsiY1/sσ=PsY1/sσ可得到Asi=κs(PsiYsi)σ/σ-1/(KsiαLsi1-αs),其中κs=(PsYs)1/1-σ/Ps。κs无法直接观测到,参照简泽(2011)的做法,令κs=1,即可得到该式。这里实际是用PsiYsi的σ/(σ-1)次幕来逼近Ysi。
(1)2017年采矿业上市公司共有74家,其中中央和地方国有企业有46家,隶属电力热力燃气及水的生产和供应业的上市公司有104家,其中中央和地方国有企业有81家。
(1)根据HK的研究,1997年美国制造业的资源错配程度与其他年份相比处于较高的水平,选取1997年美国制造业作为基准是为了得到一个较为保守的估算结果。
(1)根据式(19)进行分解时,工业总体TFP损失L采用所有制、地区和行业类型划分下测算值的算术平均数。
(1)资料来源:《中国多地热衷显示产业。或将再酿光伏悲剧》[DB/OL],人民政协网,2014年5月4日,http:/www.rmzxh.com.cn/c/2014-05-04/321800.shtml.
(2)由于反事实分析对工业样本企业的划分要同时从所有制、地区、行业三个层来展开,为了避免层次过多引起混乱,我们不再考虑要素产出弹性的异质性。而是基于工业样本企业整体的要素产出弹性来做反事实分析,即假定as=a。