信贷资源配置与非周期性产能过剩:微观数据的实证
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摘要
厘清企业产能利用率的微观决定机制是探讨产能过剩长效治理机制的前提。现有研究虽然强调了中国重工业领域产能过剩的非周期性色彩,但缺乏微观数据实证的支持,也缺乏对不同因素实际影响的量化比较。为此,基于中国工业企业数据库的微观数据,选择钢铁行业作为研究样本,综合运用成本函数法的产能利用率测算以及产能利用率变化影响因素的微观计量,验证两个理论假设:制度政策性因素对于我国产能过剩形成具有更加显著的影响;信贷资源配置是企业产能利用率变化的决定变量,主导了我国重工业领域产能过剩的实际演变。进一步实证显示:金融抑制不仅会引发微观企业投资的预算软约束,还会扭曲微观企业行为。由此认为,我国钢铁行业乃至于其他重工业领域的产能过剩问题,改革比调控更加重要,而金融资源分配体制的改革则是重中之重。
Clarifying the microeconomic determining mechanism of the change in capacity utilization rate of enterprises is an important prerequisite for exploring the long-term governance mechanism of overcapacity.Although the existing studies emphasize the noncyclical characteristics of excess capacity in China's heavy industry,most of them are based on macro and industry data,lacking the empirical support for micro data and quantitative comparison of the actual impact of different factors.This paper adopts a micro to macro research approach and chooses steel industry as a typical sample to conduct corresponding empirical tests,based on micro data from China Industry Business Performance Database.Through the calculation of the productivity utilization ratio based on the cost function method and the empirical comparison of various factors affecting the utilization rate of capacity,two theoretical hypotheses are verified:Noncyclical factors have a more significant impact on the formation of overcapacity in China.The allocation of credit resources is a determinant variable of the change in the capacity utilization rate of enterprises,which dominates the actual evolution of excess capacity in the heavy industry in China.Further empirical evidence from different ownership enterprises shows that financial regulation will not only cause soft budget constraint on micro-enterprise investment,but also distort the behavior of the micro enterprise.Therefore,for the issue of overcapacity in China's steel industry and even in other heavy industries,reform is more important than regulation,and the reform of the financial resource allocation system is of the highest priority.
Clarifying the microeconomic determining mechanism of the change in capacity utilization rate of enterprises is an important prerequisite for exploring the long-term governance mechanism of overcapacity.Although the existing studies emphasize the noncyclical characteristics of excess capacity in China's heavy industry,most of them are based on macro and industry data,lacking the empirical support for micro data and quantitative comparison of the actual impact of different factors.This paper adopts a micro to macro research approach and chooses steel industry as a typical sample to conduct corresponding empirical tests,based on micro data from China Industry Business Performance Database.Through the calculation of the productivity utilization ratio based on the cost function method and the empirical comparison of various factors affecting the utilization rate of capacity,two theoretical hypotheses are verified:Noncyclical factors have a more significant impact on the formation of overcapacity in China.The allocation of credit resources is a determinant variable of the change in the capacity utilization rate of enterprises,which dominates the actual evolution of excess capacity in the heavy industry in China.Further empirical evidence from different ownership enterprises shows that financial regulation will not only cause soft budget constraint on micro-enterprise investment,but also distort the behavior of the micro enterprise.Therefore,for the issue of overcapacity in China's steel industry and even in other heavy industries,reform is more important than regulation,and the reform of the financial resource allocation system is of the highest priority.
引文
[1] Mc Elhattan R.Estimating a stable inflation capacity utilization rate[J].Federal Reserve Bank of San Francisco Economic Review,1978,78:20-30.
[2] Shapiro M D,Gordon R J,Summers L H.Assessing the Federal Reserve’s measures of capacity and utilization[J].Brooking Papers on Economic Activity,1989(1):181-241.
[3] Corrado C,Mattey J.Capacity utilization[J].Journal of Economic Perspectives,1997,11(1):151-167.
[4] Dixit B A.The role of investment in entry deterrence[J].The Economic Journal,2010,90:95-106.
[5] Stiglitz J E.Toward a general theory of wage and price rigidities and economic fluctuations[J].American Economic Review,1999,89:75-80.
[6]纪洋,谭语嫣,黄益平.金融双轨制与利率市场化[J].经济研究,2016(6):45-57.
[7]黄桂田,何石军.结构扭曲与中国货币之谜——基于转型经济金融抑制的视角[J].金融研究,2011(7):1-13.
[8]林毅夫.潮涌现象与发展中国家宏观经济理论的重新构建[J].经济研究,2007(1):126-131.
[9]林毅夫,巫和懋,邢亦青.“潮涌现象”与产能过剩的形成机制[J].经济研究,2010(10):4-19.
[10]纪敏,严宝玉,李宏瑾.杠杆率结构、水平和金融稳定——理论分析框架和中国经验[J].金融研究,2017,(2):11-25.
[11]周劲,付保宗.产能过剩的内涵、评价体系及在我国工业领域的表现特征[J].经济学动态,2011(10):58-64.
[12]王文甫,明娟,岳超云.企业规模、地方政府干预与产能过剩[J].管理世界,2014(10):17-46.
[13]国务院发展研究中心《进一步化解产能过剩的政策研究》课题组.当前我国产能过剩的特征、风险及对策研究——基于实地调研及微观数据的分析[J].管理世界,2015(4):1-10.
[14]钟春平,潘黎.“产能过剩”的误区——产能利用率及产能过剩的进展、争议及现实判断[J].经济学动态,2014(3):35-47.
[15]林志帆,赖艳,徐蔓华.货币扩张、资本深化与劳动收入份额下降——理论模型与跨国经验证据[J].经济科学,2015(5):30-43.
[16]王仲兵,刘颖.国有僵尸企业:概念、机理与治理方略[J].地方财政研究,2017(5):45-49+65.
[17]纪志宏,周黎安,等.地方官员晋升激励与银行信贷——来自中国城市商业银行的经验证据[J].金融研究,2014(1):1-15.
[18]王宇.中国高杠杆的成因及治理[J].中国经济报告,2016(3):92-94.
[19]宋国青.利率是车、汇率是马[M].北京:北京大学出版社,2014.
[20]刘晓光,张杰平.中国杠杆率悖论:兼论货币政策“稳增长”和“降杠杆”真的两难吗[J].财贸经济,2016(8):5-19.
[21]马红旗.产能利用率、企业性质与经营效益——基于钢铁企业的实证分析[J].上海财经大学学报,2017(6):31-45.
[22]马红旗,黄桂田,王韧,等.我国钢铁企业产能过剩的成因及所有制差异分析[J].经济研究,2018(3):79-90.
[23]Klein L R.Some theoretical issues in the measurement of capacity[J].Econometrica,1960,28:272-286.
[24]Nelson R A.On the measurement of capacity utilization[J].Journal of Industrial Economics,1989,37:273-286.
[25]Lau L J A.Characterization of thenormalized restricted profit function[J].Journal of Economic Theory,1976(12):131-163.
[26]聂辉华,江艇,杨汝岱.中国工业企业数据库的使用现状和潜在问题[J].世界经济,2012(5),142-158.
[27]谢千里,罗斯基,张轶凡.中国工业生产率的增长与收敛[J].经济学季刊,2008(3):34-51.
[28]刘小玄,李双杰.制造业企业相对效率的度量和比较及其外生决定因素(2000—2004)[J].经济学(季刊),2008(4):843-868.
[29]Jorgenson D W.Capital theory and investment behavior[J].American Economic Review,2002,53:247-259.
[30]程俊杰,刘志彪.产能过剩、要素扭曲与经济波动——来自制造业的经验证据[J].经济学家,2015(11):59-69.
[31]Braguinsky S,Ohyama A,Okazaki T,et al.Acquisitions,Productivity and profitability:evidence from the Japanese cotton spinning industry[J].Ssrn Electronic Journal,2015,105:201-239.
(1)这里用《中国统计年鉴》报告的制造业劳动力年人均工资与企业从业人数之积替代企业工资总额。
(2)2008-2013年的中间投入数据缺失。基于1998-2007年的历史数据,钢铁行业的中间投入比例(中间投入/工业总产值)维持在0.74~0.83之间,呈现出明显的线性趋势,这里运用趋势外推法进行了近似估计。
(3)由于部分样本缺失工业增加值指标,这里采用刘小玄和李双杰(2008)的估算公式进行了推演,即:工业增加值=产品销售额-期初存货+期末存货-中间投入合计+增值税。
(4)来自《中国统计年鉴》,并换算成以1998年为基期的定比价值指数。
(5)来自《中国价格统计年鉴》,用黑色金属材料类购进价格指数表示,并折算成1998年为基期的定比价格指数。
[2] Shapiro M D,Gordon R J,Summers L H.Assessing the Federal Reserve’s measures of capacity and utilization[J].Brooking Papers on Economic Activity,1989(1):181-241.
[3] Corrado C,Mattey J.Capacity utilization[J].Journal of Economic Perspectives,1997,11(1):151-167.
[4] Dixit B A.The role of investment in entry deterrence[J].The Economic Journal,2010,90:95-106.
[5] Stiglitz J E.Toward a general theory of wage and price rigidities and economic fluctuations[J].American Economic Review,1999,89:75-80.
[6]纪洋,谭语嫣,黄益平.金融双轨制与利率市场化[J].经济研究,2016(6):45-57.
[7]黄桂田,何石军.结构扭曲与中国货币之谜——基于转型经济金融抑制的视角[J].金融研究,2011(7):1-13.
[8]林毅夫.潮涌现象与发展中国家宏观经济理论的重新构建[J].经济研究,2007(1):126-131.
[9]林毅夫,巫和懋,邢亦青.“潮涌现象”与产能过剩的形成机制[J].经济研究,2010(10):4-19.
[10]纪敏,严宝玉,李宏瑾.杠杆率结构、水平和金融稳定——理论分析框架和中国经验[J].金融研究,2017,(2):11-25.
[11]周劲,付保宗.产能过剩的内涵、评价体系及在我国工业领域的表现特征[J].经济学动态,2011(10):58-64.
[12]王文甫,明娟,岳超云.企业规模、地方政府干预与产能过剩[J].管理世界,2014(10):17-46.
[13]国务院发展研究中心《进一步化解产能过剩的政策研究》课题组.当前我国产能过剩的特征、风险及对策研究——基于实地调研及微观数据的分析[J].管理世界,2015(4):1-10.
[14]钟春平,潘黎.“产能过剩”的误区——产能利用率及产能过剩的进展、争议及现实判断[J].经济学动态,2014(3):35-47.
[15]林志帆,赖艳,徐蔓华.货币扩张、资本深化与劳动收入份额下降——理论模型与跨国经验证据[J].经济科学,2015(5):30-43.
[16]王仲兵,刘颖.国有僵尸企业:概念、机理与治理方略[J].地方财政研究,2017(5):45-49+65.
[17]纪志宏,周黎安,等.地方官员晋升激励与银行信贷——来自中国城市商业银行的经验证据[J].金融研究,2014(1):1-15.
[18]王宇.中国高杠杆的成因及治理[J].中国经济报告,2016(3):92-94.
[19]宋国青.利率是车、汇率是马[M].北京:北京大学出版社,2014.
[20]刘晓光,张杰平.中国杠杆率悖论:兼论货币政策“稳增长”和“降杠杆”真的两难吗[J].财贸经济,2016(8):5-19.
[21]马红旗.产能利用率、企业性质与经营效益——基于钢铁企业的实证分析[J].上海财经大学学报,2017(6):31-45.
[22]马红旗,黄桂田,王韧,等.我国钢铁企业产能过剩的成因及所有制差异分析[J].经济研究,2018(3):79-90.
[23]Klein L R.Some theoretical issues in the measurement of capacity[J].Econometrica,1960,28:272-286.
[24]Nelson R A.On the measurement of capacity utilization[J].Journal of Industrial Economics,1989,37:273-286.
[25]Lau L J A.Characterization of thenormalized restricted profit function[J].Journal of Economic Theory,1976(12):131-163.
[26]聂辉华,江艇,杨汝岱.中国工业企业数据库的使用现状和潜在问题[J].世界经济,2012(5),142-158.
[27]谢千里,罗斯基,张轶凡.中国工业生产率的增长与收敛[J].经济学季刊,2008(3):34-51.
[28]刘小玄,李双杰.制造业企业相对效率的度量和比较及其外生决定因素(2000—2004)[J].经济学(季刊),2008(4):843-868.
[29]Jorgenson D W.Capital theory and investment behavior[J].American Economic Review,2002,53:247-259.
[30]程俊杰,刘志彪.产能过剩、要素扭曲与经济波动——来自制造业的经验证据[J].经济学家,2015(11):59-69.
[31]Braguinsky S,Ohyama A,Okazaki T,et al.Acquisitions,Productivity and profitability:evidence from the Japanese cotton spinning industry[J].Ssrn Electronic Journal,2015,105:201-239.
(1)这里用《中国统计年鉴》报告的制造业劳动力年人均工资与企业从业人数之积替代企业工资总额。
(2)2008-2013年的中间投入数据缺失。基于1998-2007年的历史数据,钢铁行业的中间投入比例(中间投入/工业总产值)维持在0.74~0.83之间,呈现出明显的线性趋势,这里运用趋势外推法进行了近似估计。
(3)由于部分样本缺失工业增加值指标,这里采用刘小玄和李双杰(2008)的估算公式进行了推演,即:工业增加值=产品销售额-期初存货+期末存货-中间投入合计+增值税。
(4)来自《中国统计年鉴》,并换算成以1998年为基期的定比价值指数。
(5)来自《中国价格统计年鉴》,用黑色金属材料类购进价格指数表示,并折算成1998年为基期的定比价格指数。