扭曲因子、进口中间品价格与全要素生产率——基于非竞争型投入产出网络结构一般均衡模型事后核算方法

基于BF(2020)模型框架,本文构建了嵌入间接税、成本加成和进口中间投入品的非竞争型投入产出网络结构一般均衡模型,并提出了一种扭曲—调整的索洛余值的事后核算和结构分解新方法,进一步利用中国投入产出表数据、WIOD数据库等编制了与模型匹配的社会核算矩阵,实证测算分析了1997—2017年中国全要素生产率及其结构变化。研究表明:(1) 资本和全要素生产率是中国经济增长的主要源泉,且两者存在明显此消彼长的“跷跷板”特征,劳动的贡献相对较小且贡献率呈下降趋势。(2)纯技术效率变化一直是全要素生产率变化主要贡献部分,但总体上呈下降趋势。2007年是其分水岭,受技术模仿后发优势逐步式微的影响,技术进步速度下滑,但2012年后受创新驱动发展战略的影响,纯技术效率逐步提升。(3)扭曲因子配置效率变化对全要素生产率变化的贡献由正转负,进口中间品贸易条件变化对全要素生产率变化的贡献率由负转正。在建立社会主义市场经济体制和加入WTO大背景下,资源配置效率变化促进了全要素生产率。但2007—2012年,受国际金融危机影响,扭曲因子配置效率出现短期恶化并拉低了全要素生产率。

Distortion Factors,Prices of Imported Intermediate Inputs,and Total Factor Productivity:Ex Post Accounting Method Based on General Equilibrium Modelling of the Noncompetitive Input-Output Network Structure

China's economic development since the reform and opening-up in 1978 is remarkable. However, the growth of China's economic development shows slowing trends over the past decade because of the triple pressure of shrinking demand, supply shocks, and weakening expectations. Following the impact of the COVID-19 pandemic, changes have accelerated and China's external environment is now more complex, severe, and uncertain. How to interpret China's economic growth over the past 40 years and the changes in total factor productivity (TFP) and its driving factors? Answering these questions is of great practical significance. Many studies explore TFP. For example, macro-level studies are generally based on the classical Solow residual method to estimate TFP. In these studies, any unobservable factors affecting economic growth can be attributed to TFP; therefore, the classical Solow residual is like a “black box.” It is impossible to accurately understand the determinants of TFP theoretically; thus, there are misunderstandings in the understanding of TFP, which also leads to differences in understanding changes in TFP. Studies of the decomposition of TFP in China lack a unified theoretical model and especially a general equilibrium model of the input-output network structure.Based on the basic framework of Baqaee and Farhi (2020), this paper constructs a general equilibrium model of a noncompetitive input-output network structure with imported intermediate inputs and distortion factors suitable for China's characteristics. The paper then proposes a new method for calculating and decomposing total productivity, which empirically calculates and decomposes changes in TFP. This paper makes two marginal contributions to the literature. First, the theoretical model of the production network structure is expanded. The general Baqaee and Farhi (2020) model is based on the general equilibrium framework of a production network structure with markup. In addition to the markup caused by monopoly power, the structure of China's tax system with indirect tax as the main body obviously differs from that of the United States with direct tax as the main body. Therefore, building a general equilibrium model for a production network structure that considers the impact mechanism of indirect tax is more in line with China's reality. Second, this paper enriches methods for calculating and decomposing TFP. Under the general equilibrium framework, this paper derives a new unified measurement framework for economic growth accounting and TFP decomposition, considers the impact mechanism of terms of trade, and expands the decomposition method for TFP.The results show that capital and TFP are the main sources of China's economic growth and that there is an obvious “see-saw” between the two, but the contribution of labor is relatively small and the rate of contribution shows a downward trend. The change to pure technical efficiency is the main contributor to changes in TFP; however, it shows a downward trend and 2007 is a watershed year. Following the gradual loss of the late development advantage of technology imitation, the speed of technological progress also shows a gradual decline since 2007. After 2012, however, China's pure technical efficiency improves gradually under the influence of the innovation-driven development strategy. The contribution of the change in distortion factor allocation efficiency for TFP changes from positive to negative, while the contribution of the change in the terms of trade for imported intermediate products to TFP changes from negative to positive. Against the background of the establishment of a socialist market economic system and China's entry into the World Trade Organization, the change in resource allocation efficiency promotes TFP. From 2007 to 2012, however, following the global financial crisis and China's “four-trillion investment plan,” distortion factor allocation efficiency deteriorated in the short term and pulled down TFP, but its negative impact decreased after 2012.The following three conclusions are based on these results. First, TFP is not only the main source of improving China's economic growth in the future but also the key to achieving high-quality development. Following the decline in the return on capital caused by the decreasing scale of marginal returns and resource and environmental constraints, it will be difficult to sustain large-scale investments in the future and the contribution of capital to economic growth will decline. Second, the technological progress brought by independent innovation in the future is the main source of TFP improvement. Third, improving the efficiency of resource allocation is still an important source for improving TFP and achieving high-quality development. The practical experience of China's reform and opening-up confirms the important role of improving technical and factor allocation efficiency in rapid economic growth.