【原创】China’s Optimal Industrial Structure...
China’s Optimal Industrial Structure: Theoretical Model and Econometric Estimation
Xiao Xingzhi (肖兴志), Peng Yizhong (彭宜钟) and Li Shaolin (李少林)
Center for Industrial & Business Organization, DUFE, Dalian, China
Abstract: With analysis of producer’s and factor supplier’s dual optimization motives, this paper developed an optimal nominal output growth rate model that can conduct quantified estimation. Result of estimation of China’s optimal industrial structure between 1992 and 2009 indicates that optimal nominal output growth rate model has successfully quantified the impact of major events occurring in the process of China’s economic operation on the level of deviation between actual industrial structure and optimal industrial structure. Quantitative indicators involved in this model can provide industrial policy instruments for the Chinese government in developing and adjusting industrial structure targets, optimizing resource allocation and advancing industrial structure optimization and upgrade.
Key words: optimal industrial structure, optimal growth rate, stochastic discount factor
JEL Classification: C51, D01, E23
1.Introduction
China’s traditional input-, energy- and pollution-intensive model of economic growth has become unsustainable. Fundamental transformation of economic growth model is imperative. As a major means of economic growth transition, optimization and upgrade of industrial structure is a key priority of China’s economic development strategy for current and future periods. Since the 1990s, Chinese academia has carried out extensive studies on China’s industrial structure and developed multiple policy recommendations on industrial structure optimization and upgrade.
In industrial structure characterization, some scholars have employed the concept of “deviance” to examine the equilibrium of China’s industrial structure. They believe that worsening asymmetry between workforce and output value will lead to a greater deviance between the two. Positive deviance of primary industry and negative deviance of secondary industry are major causes of China’s high degree of industry deviance (Xiong et al., 1990). As for the focus point of industrial restructuring, Chinese scholars identified seven industries that are agriculture, energy (mainly electric power), iron and steel, aluminum, raw material (mainly chemical raw materials), transport and communication as strategic industries for industrial restructuring based on the criteria for the selection of China’s strategic industries, and workforce in various industries, level of intensive capital utilization and effect of industries on overall economy (Xie et al., 1990). Another scholar believes that improvement in the aggregate quality of industrial structure is a key issue in adjusting the unreasonable industrial structure while such improvement boils down to structural equilibrium and theoretically explains the relationship of industrial structure equilibrium, which include short-term and long-term, absolute and relative equilibrium of industrial structure (Zhou, 1991). Regarding issues that deserve attention in industry restructuring, on the basis of discussions on the direction and principles of China’s industry restructuring, some scholars believe that the internal structure of China’s tertiary industry is of low level and underdeveloped and that secondary industry lacks the driving effect of high-processing industries. Crude industrial structure led to severe degradation of resources and environment. They also pointed out that China must properly balance countryside industrialization, opening-up and manufacturing upgrade in the process of industry restructuring (Hu, 1999).
With respect to the research on the reasonableness of industrial structure, some scholars calculated such indicators as industry added value’s annual growth rate, labor productivity and capital productivity to reveal the annual share of unreasonableness in China’s industrial structure and calculated the share of unreasonableness in each industry of China between 1990 and 2002; the result shows that China’s industrial structure in 2002 contains 3.11% of unreasonableness (Li et al., 2005). Regarding measurement of industrial structure optimization and upgrade targets, some scholars examined the specific and strategic targets of industrial upgrade in terms of basic completion of industrialization and modernization and identified the directions and pathways for China’s industrial restructuring. They believe that China’s industrial restructuring should be driven by high-tech industries supported by service and manufacturing industries that promote overall upgrade of industrial structure (He, et al., 2008). Regarding the causes of industrial restructuring, by creating a two-industry model, foreign scholars demonstrated at theoretical level that capital accumulation is a major cause of industrial restructuring (Acemoglu et al., 2008). Concerning the pathway of industrial upgrade, some scholars carried out a combination of theoretical and empirical studies. Using panel data of 31 Chinese provinces, municipalities and autonomous regions between 1991 and 2007, they created a model of relationship among technology selection, industrial upgrade and economic growth, under which empirical studies suggest that industrial upgrading can be achieved with selection of reasonable capital intensification and technology (Huang, et al., 2009). Concerning theoretical study on optimal industrial structure, some scholars analyzed the dynamic changes in the optimal industrial structure of a closed economy from theoretical perspective and concluded that continuous increase of capital is an impetus of changes in industrial structure (Ju et al., 2009). As for studies on the influence factors for the shares of industrial structure, foreign scholars studied the correlation between high capital endowment and the scale of capital-intensive industries using empirical methodology based on data of 27 industries from 15 countries. They discovered that actual and nominal output shares and share of employment in capital-intensive industries are in significant positive correlation with initial capital endowment and the speed of capital accumulation (Che, 2010).
On the basis of study and review of numerous literature, we discovered that all this type of studies cannot escape certain limitations described below: first, their model for discussion on endogenous issues of industrial structure stops at theoretical level and can hardly be applied to empirical study (such as Ju et al., 2009’s theoretical model). Second, empirical studies relevant with industrial structure all stop at the revelation of the relationship between realistic industrial structure and other economic variables. Third, studies that depict the level of industrial structure optimization through structural statistics all have the implied premise of certain subjective understanding (i.e. believing that a greater share of output from service industry and high value-added processing industries is always better). In order to overcome the above-mentioned limitations in existing studies, we discuss the determination mechanism of optimal output for each industry by proceeding from the optimization motives of producers and factor suppliers, and trying to develop a quantifiable and applicable theoretical model that can well depict the optimal growth level and optimal industrial structure of China’s each industry. The remainder of this paper structures in three parts: theoretical model description, quantified estimate of China’s optimal industrial structure and conclusions.
2. Theoretical Model Description
2.1 Definition of Industrial Structure
It can be seen from Table 11 and Figure 1, 2 and 3 that actual growth rate and optimal growth rate of primary, secondary and tertiary industries have maintained a relationship of movement in the same direction, which is also observed between China’s actual industrial structure and optimal industrial structure. Optimal growth rates of primary, secondary and tertiary industries demonstrate the following tendency: growth slowed between 1992 and 1997 and even turned negative between 1994 and 1997; restorative growth emerged in 1998 on the basis of 1997 but during 1999 and 2000, primary and secondary industries abruptly entered a downward channel (only tertiary industry experienced a slight growth); primary, secondary and tertiary industries all had steady growth between 2001 and 2005; their growth rates were slashed in 2006 and spiked in 2007; in 2008 and 2009, their growth rates all declined.
Changing patterns in the difference between actual growth rate and optimal growth rate reflect the environment and reality of China’s economic development. For instance, that actual growth rates always exceeded optimal growth rates between 1992 and 1997 indicates that China’s economy was overheating at that time; in 1998, actual growth rates of all industries were below optimal growth rates, which suggest that China’s economy suffered from the Asian Financial Crisis. In 1999 and 2000, actual growth rates exceeded optimal growth rates, which reflect that the expansive policy adopted by the Chinese government in response to the Asian Financial Crisis achieved intended result of slight overheating in the economy; after 2001, actual growth rates had always stayed below optimal growth rates. After 2003, actual growth rates of primary, secondary and tertiary industries had great gaps with optimal growth rates, which reflect the full and severe impact of major events including the SARS of 2003, Wenchuan Mega-earthquake of 2008 and the recent global financial crisis. According to this paper’s theoretical model, we calculated the optimal structures of primary, secondary and tertiary industries and compared their actual structures (see Table 12).
It can be seen from Table 12 and Figure 4, 5 and 6 that the actual share of primary industry was higher than its optimal share prior to 2004 and stayed below optimal share after 2005. This to some extent reflects China’s grain security problem. Actual share of secondary industry failed to reach optimal level prior to 1997 and gradually exceeded optimal level between 1998 and 2008 yet suddenly dropped below optimal level after 2009. Actual share of tertiary industry had been higher than optimal level prior to 1998 and stayed below optimal level between 1999 and 2008 before exceeding optimal level once again in 2009.
Comparative relationship between actual and optimal shares of primary, secondary and tertiary industries clearly depicts the changing patterns in China’s industrial structure: China’s endowment of production factor enabled the share of primary industry to exceed optimal level under a crude, extensive and labor-intensive pattern of development prior to 2004. As rural populations migrate to cities for jobs, the actual share of primary industry declined and stayed below optimal level after 2005, whereas the actual share of secondary industry gradually approached and exceeded optimal share between 1998 and 2008 (accelerating industrialization). Under the impact of global financial crisis in 2008, actual shares of primary and secondary industries both stayed below optimal levels and the actual share of tertiary industry exceeded optimal level (Chinese government adopted policies to expand domestic consumption in fighting financial crisis, providing vigorous demand momentum for tertiary industry).
4. Concluding Remarks
Through joint solution for producer’s profit maximization target and factor supplier’s inter-temporal utility maximization target, this paper has deduced an equation for optimal nominal output growth rates of primary, secondary and tertiary industries. Explanatory variables of the equation include: capital growth rates of industries, Lerner Index and capital market’s stochastic discount factor. In addition, the equation also includes three parameters to be estimated: output elasticity of labor for different industries, consumers’ subjective utility discount factor and risk aversion coefficient. Based on cross-provincial panel data of consumption, price and income of industries between 1992 and 2009, we have estimated the price elasticity of demand for primary, secondary and tertiary industries. Then, based on per capita capital, per capita output and other input-output variables, as well as technical inefficiency explanatory variables such as level of education, institutional factor, and geographic environment, we have estimated the output elasticity of labor for primary, secondary and tertiary industries using stochastic frontier method. Based on such data as total volume of retail sales, SSE and Shenzhen Composite Index, one-year fixed term deposit interest rate, we have estimated China’s social subjective utility discount factor and risk aversion coefficient using GMM approach and thereby calculated China’s capital market stochastic discount factor. Lastly, based on equation of optimal nominal output growth rate at industry level, we estimated optimal nominal output growth rates and optimal industrial structure of China’s primary, secondary and tertiary industries between 1992 and 2009.
Results of the estimation indicate that the actual growth rates and optimal growth rates of industries roughly maintain the relationship of movement in the same direction and the same relationship is maintained between China’s actual industrial structure and optimal industrial structure. Changing patterns in the difference between actual growth rates and optimal growth rates of industries clearly reflect the impact of major events on China’s economy such as economic overheating after 1992, the Asian Financial Crisis that broke out in the second half of 1997, the SARS in 2003 and global financial crisis since 2008. Lastly, we believe that the measurement of industrial structure deviation with benchmark of optimal industrial structure and evaluation of efficiency loss caused by industrial structure deviation are also major topics that deserve in-depth research.
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