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Abstract: China’s recent economic slowdown has provoked academic discussion on what the core driver should be to ensure sustainable and healthy economic growth. To answer this question, it is essential to analyze the resources allocation efficiency. Using the newly-developed spatial panel data model, this paper studies not only the direct effect of resources allocation on local economies, but also the spillover effects on the economies in other regions. We are then able to assess the actual effects of resource factors on China’s economic growth, including labor force, fixed-asset investment (FAI) and technical progress. The conclusions are: 1) during the past 13 years, the labor force has had an insignificant effect on all the three industries; 2) FAI has produced a prominent positive direct effect on secondary industry, but accompanied with even severer negative spillover effects which outweigh the positive ones; however, FAI has had significant direct and total effect on the tertiary industry; 3) technical progress has significant effects on all the three industries. Therefore, the labor force is not the core driver of China’s economic growth, and the demographic dividend is an invalid explanation for China’s economic growth. Instead, fixed-asset investment remains the powerhouse of China’s economic growth, not in the secondary industry but in the tertiary industry. All in all, technical progress is the core driver for healthy economic growth as well as the inevitable path to industrial upgrading in China.
Keywords: resources allocation efficiency, FAI, technical progress, spatial panel model
JEL Classifications : O11
Figure 4 shows the movement of FAI in the past 13 years. The share of FAI in agriculture has declined year by year to only 2.9% of the total in 2010, suggesting extremely limited investment in agriculture despite the attention paid by the central government concerning agricultural related issues. This might be one cause for the widening rural and urban gap. FAI in the secondary industry has fallen slightly from 47% to 42% while that in the tertiary industry has risen from 49% to 55%. The movement shows that the focus of FAI in China has shifted from the secondary industry to the tertiary industry which has received growing support from the government.Based on TFP, Figure 5 presents the change of productivity in China. It is noteworthy that China’s productivity remains very low despite the astonishing economic growth it achieved from 1998 to 2010, a period where the economic aggregate expanded from RMB8.4 trillion to RMB39.8 trillion. Especially in the tertiary industry, where productivity exhibited a downward trend. The productivity results in Figure 5 show that China still follows the extensive growth mode where growth prevails over efficiency, which demonstrates the necessity and urgency for China to tranorm its growth mode (Luo and Zhang, 2009).
To more accurately measure the resources allocation efficiency in different industries, this paper empirically tests the efficiency in the three industries and their direct effects on economic growth on the basis of taking full consideration on correlations of economic activities in different regions of China by applying the newly developed spatial panelmodel. Empirical results present a more realistic picture about how the current industrial layout affects China’s economic growth. In addition, it provides statistical basis for China’s future industrial upgrading and path selection, and clarifies the core driver of China’s economic growth.
3. Spatial Panel Model Setting and Data Selection
Table 4 shows that the estimate of direct impact of number of people employed in the primary industry on economy passes the significance test and the impact is negative, while its indirect impact is insignificant. The direct and indirect impact of number of people employed in secondary and tertiary industries do not pass the significance test, revealing that the main route of regional resource reallocation is not labor force traner and that the number of people employed is not the core reason affecting the development of the secondary and tertiary industries. The elasticity coefficient of number of people employed in primary industry on economic growth is -0.1875, illustrating that an increase in the number of people employed in agriculture would obviously constrain regional agricultural growth. Therefore, at present the key to developing agriculture in China is not hing more farmers stuck to farmland, but releasing more of the agricultural labor force from conventional agriculture to achieve industrialization and modernization of agriculture. The practices of Chinese economic development over the recent years he also proven that reducing the number of people employed in the primary industry through urbanization has become the driving force behind China’s sustained economic growth.
In terms of fixed asset investment, the direct and indirect effects on the primary industry are both insignificant. It means that under the current decentralized mode of agricultural production, increasing FAI in agriculture is not an effective way to promote agricultural growth. A noteworthy fact is that FAI has both positive direct effects and negative indirect effects on the secondary industry, with the elasticity of negative indirect influence at -0.0753, much greater than that of positive direct effects, 0.0475. The integrated effects of FAI on secondary industry is -0.0274, meaning that FAI does boost local industrial growth, but would cause negative spillover effects over economic growth of other regions, resulting in a negative ultimate effects on economic development. Such results indicate that although increasing FAI in the secondary industry would boost the economic growth in the local region, it cannot help overall economic growth, That is to say, it is no longer the case that investment in secondary industry will promote the economy as a whole. In contrast, investment in tertiary industry has a significant positive direct effect on economic growth (0.1135), more than two times higher than in the secondary industry; its indirect effect is not significant and the integrated positive effects are significant, at 0.0943. This shows that boosting investment in the tertiary industry is indeed the most direct and effective way for increasing Chinese economic growth. In more than 30 years from the reform and opening up, China
Meanwhile, increasing FAI in the tertiary industry can effectively promote growth of local economy without any significant negative spillover effects on other regions. Such FAI increases are twice efficient in promoting the local economic growth than the same investment in the secondary industry can achieve, thus resulting in a positive overall effect. Therefore, expanding the investment scale in the tertiary industry is the key to promoting industrial advancement in China. To better coordinate the local and national interests, the central government should formulate relevant policies to confine local government’s inclination of investing more in the secondary industry and guide the limited resources flow to the tertiary industry. Meanwhile, since most players in the tertiary industry are all and medium-sized enterprises that are commonly troubled by financing difficulties, the government should establish a financial system that supports the dev
TFP has significant positive indirect effects and overall effects on the primary industry with a coefficient of elasticity of 0.1137 and 0.1438 respectively. That indicates that although technical progress in agriculture may not he significant positive influence on local economy, throu
At present, we are in the face of new challenges, such as restricted export due to a gloomy global economy. Household consumption relies much on the future expectation of economic prosperity. Therefore, fixed asset investment remains the most effective choice for maintaining growth and guaranteeing prosperity. Obviously, the major concern is what to invest rather than whether or not invest. The Americans started railway construction since late 19th century, which brings changes to not only the U.S., but the entire world as well. We can assume that there must be the problem of overcapacity when the construction was initially completed. Even until today, many railways and expressways in most developed countries are not used at its full capacity. However, isn’t a well-developed transportation network an important feature of a developed country? Without all those infrastructure projects, can they still be developed countries? It is indisputable that infrastructure construction alone does not necessarily create economic prosperity, but without it, the economy definitely doesn’t work. The Chinese central government has given a series of blueprint and development goals which mostly rely on economic growth. In return, the prerequisite of economic growth should be infrastructure construction. China’s healthy economic growth needs FAI, at least for now. At present, construction projects in China are still inadequate. We already saw an oversupply of industry parks and residential apartments, but they still lack well-planned transportation network and infrastructure. The shortage of infrastructure is best evidenced by traffic jams in all major cities of China. Continuing to expand the FAI mainly on railways, roads and infrastructure will not only help maintain economic growth and guarantee economic prosperity in China, but also create domestic demand to guarantee growth in the future. The Chinese central government should provide guidance for investment in order to create better economic development environment and achieve economic prosperity under market mechani. Another benefit is that investment in transportation and infrastructure can partly relieve the problem of overcapacity caused by overheating in the real-estate market, so we may ensure a soft landing, ensure healthy development of China’s economy and achieve industrial upgrading.
Keywords: resources allocation efficiency, FAI, technical progress, spatial panel model
JEL Classifications : O11
1. Introduction
The growth rate of China, the second largest economy in the world, dropped to 7.6% in the second quarter of 2012, the lowest since 2009. The economic slowdown has concerned many economists and triggered an intense discussion on how to maintain healthy economic growth in China. Obviously, to oid any short-sighted policy tools, the discussion should not be limited to short-term economic growth route, but also to the direction of long-term economic growth, i.e. tranorming economic growth pattern and selecting the direction of industrial upgrading as suggested in the 12th Five Year Plan (2011-2015), and then answer the question of what the core driver in long-term healthy economic growth is. Regarding the proportion of the three industries (primary, secondary and tertiary industry), scholars he quite divided opinions. Most argue that the proportion of secondary industry is disproportionately high, thus the focus should be shifted to the tertiary industry. But s源于：查抄袭率毕业www.udooo.com
ome believe that there is still room for lifting secondary industry’s share in GDP; thus industrial upgrading policies should still focus on the secondary industry (Li, et al., 2011). However, the objective of industrial upgrading is to ensure limited resources can be tranerred from inefficient sectors to highly efficient ones in order to maintain sustainable economic growth. It is quite clear that the path for industrial upgrading should be decided upon resources allocation efficiency instead of its share in GDP. In this sense, measuring the resources allocation efficiency in each sector is the groundwork for identifying the core driver for China’s economic growth.摘自：学报论文格式www.udooo.com
As shown in Figure 1 and Figure 2, during the past 13 years, agriculture’s share in GDP declined year by year from 18% to 10% in 2010, its contribution to GDP growth also dropped from 8% to 4%, indicating that the non-agriculturalization level is gradually rising in China. Also, the share and GDP contribution of the secondary industry remains stable at around 46% and 57% respectively, suggesting that the secondary industry is the major driver of China’s economic growth over the years. Finally, the share of the tertiary industry in GDP has increased from 36% to 43%, while its GDP contribution has increased from 32% to 39%, offsetting the gap caused by the primary industry. In conclusion, during the past years, the secondary industry remained relatively stable, while the tertiary industry rose continuously. It is worth noting that stable share and contribution of the secondary industry does not mean stagnation of industry growth, but that the industry maintained growth rate similar to growth rates of GDP. The data above reveals the features of China’s economic growth in the past 13 years, but mainly focuses on the results, and fails to illustrate how resource factors are allocated among different industries. For that reason, we he shown in Figure 3 to 5 the changes of three factors in all the three industries, namely, the number of people employed, FAI and total factor productivity (TFP).源于：论文大纲www.udooo.com
Based on the number of people employed, FAI and TFP, we measured the allocation of the three factor resources (labor, investment and productivity). According to Figure 3, from 2003 to 2010, the share of agricultural employees dropped by 13 percentage points, echoing with the acceleration of urbanization process in China that began in 2003. However, even today, agricultural employees remain China’s largest working group, accounting for 37% of the total population. Meanwhile, the number of people employed in the secondary and the tertiary industry he risen by 5 percentage points and 8 percentage points respectively after absorbing labor released from agriculture.Figure 4 shows the movement of FAI in the past 13 years. The share of FAI in agriculture has declined year by year to only 2.9% of the total in 2010, suggesting extremely limited investment in agriculture despite the attention paid by the central government concerning agricultural related issues. This might be one cause for the widening rural and urban gap. FAI in the secondary industry has fallen slightly from 47% to 42% while that in the tertiary industry has risen from 49% to 55%. The movement shows that the focus of FAI in China has shifted from the secondary industry to the tertiary industry which has received growing support from the government.Based on TFP, Figure 5 presents the change of productivity in China. It is noteworthy that China’s productivity remains very low despite the astonishing economic growth it achieved from 1998 to 2010, a period where the economic aggregate expanded from RMB8.4 trillion to RMB39.8 trillion. Especially in the tertiary industry, where productivity exhibited a downward trend. The productivity results in Figure 5 show that China still follows the extensive growth mode where growth prevails over efficiency, which demonstrates the necessity and urgency for China to tranorm its growth mode (Luo and Zhang, 2009).
To more accurately measure the resources allocation efficiency in different industries, this paper empirically tests the efficiency in the three industries and their direct effects on economic growth on the basis of taking full consideration on correlations of economic activities in different regions of China by applying the newly developed spatial panelmodel. Empirical results present a more realistic picture about how the current industrial layout affects China’s economic growth. In addition, it provides statistical basis for China’s future industrial upgrading and path selection, and clarifies the core driver of China’s economic growth.
3. Spatial Panel Model Setting and Data Selection
3.1 Model Setting
We refer to the method of Elhorst (2012) for spatial panel model setting. Depending on the observational individuals’ interactions in the space, basic spatial model setting can be divided into two types (Anselin et al., 2008): First, the spatial lag model (SAR) with a spatially lagged dependent variable. Second, the spatial lag model (SEM) with the error term complying with spatial autoregression process. However, these two models cannot completely reflect the interactions between adjacent regions, therefore LeSage and Pace(2009) constructed the spatial lag model (SDM) that incorporates both spatially lagged endogenous variable and exogenous variable.3.2 Selection of Sample Data
Based on Solow economic growth theory, we selected the data from 31 provinces, municipalities and autonomous regions from 19981 to 2010. The number of people employed, total FAI and TFP in the three industries are made as the explanatory variables for labor, capital and technical progress, and the regional GDP as the explained variable (see Table 1). TFP is an important indicator for the industrial technical efficiency in a country or region, and provides摘自：论文范文www.udooo.com
a comprehensive look into the effects of technical efficiency and technical progress on economic efficiency. 2源于：论文的标准格式www.udooo.com
LeSage and Place (2009) concluded that the results found by testing the spillover effects of spatial variables with point estimates are biased and proposed using partial derivatives to explain the impact of the changes in variables under different model settings. According to the parameter estimates of SDM model, we can calculate the direct and indirect impact on economy when variables in the three industries change with fixed effects model and random effects model respectively. The gray area (2) in Table 4 outlines the estimates of direct and indirect influence on economic growth when variables in the three industries change with spatial panel data model.Table 4 shows that the estimate of direct impact of number of people employed in the primary industry on economy passes the significance test and the impact is negative, while its indirect impact is insignificant. The direct and indirect impact of number of people employed in secondary and tertiary industries do not pass the significance test, revealing that the main route of regional resource reallocation is not labor force traner and that the number of people employed is not the core reason affecting the development of the secondary and tertiary industries. The elasticity coefficient of number of people employed in primary industry on economic growth is -0.1875, illustrating that an increase in the number of people employed in agriculture would obviously constrain regional agricultural growth. Therefore, at present the key to developing agriculture in China is not hing more farmers stuck to farmland, but releasing more of the agricultural labor force from conventional agriculture to achieve industrialization and modernization of agriculture. The practices of Chinese economic development over the recent years he also proven that reducing the number of people employed in the primary industry through urbanization has become the driving force behind China’s sustained economic growth.
In terms of fixed asset investment, the direct and indirect effects on the primary industry are both insignificant. It means that under the current decentralized mode of agricultural production, increasing FAI in agriculture is not an effective way to promote agricultural growth. A noteworthy fact is that FAI has both positive direct effects and negative indirect effects on the secondary industry, with the elasticity of negative indirect influence at -0.0753, much greater than that of positive direct effects, 0.0475. The integrated effects of FAI on secondary industry is -0.0274, meaning that FAI does boost local industrial growth, but would cause negative spillover effects over economic growth of other regions, resulting in a negative ultimate effects on economic development. Such results indicate that although increasing FAI in the secondary industry would boost the economic growth in the local region, it cannot help overall economic growth, That is to say, it is no longer the case that investment in secondary industry will promote the economy as a whole. In contrast, investment in tertiary industry has a significant positive direct effect on economic growth (0.1135), more than two times higher than in the secondary industry; its indirect effect is not significant and the integrated positive effects are significant, at 0.0943. This shows that boosting investment in the tertiary industry is indeed the most direct and effective way for increasing Chinese economic growth. In more than 30 years from the reform and opening up, China
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has created miraculous, “incredible” achievement with great courage depending on the improvement in industrial capacity (Jin, 2011). But atthe same time we should be keenly aware of the negative factors brought by excessive expansion in the secondary industry and the systematic risks it has generated. Many problems, such as weak external demand, excessive waste of resources, hey pollution, low efficiency and the deterioration of the living environment all exert negative influence on current China’s economic growth. Therefore, it would no longer provide the necessary impetus for sustained economic growth by continuously increasing investment in the secondary industry; instead, greater investment in the tertiary industry is still an effective driving force for future economic growth. In short, the investment should focus on the tertiary industry, not the secondary industry.Why does FAI in the secondary industry in one region trigger serious negative spillover effects in other regions while bringing significant benefits to the local economy? Local governments, propelled by their desire to develop local economies and the performance evaluation system, often launch a portfolio of forable policies to stimulate the development of the secondary industry. As a result, highly similar industrial parks and new industrial districts are constantly built, inevitably resulting in extensive overlapping investment, over-competition and over-capacity. Therefore, FAI in the secondary industry can effectively promote local economic growth, but spread negative spillover effects to other regions which ultimately undermine the overall goal of national economic growth. Obviously, despite the backdrop of economic slowdown, stepping up with FAI in the secondary industry is not wise. To oid the hollowing out of the economy, secondary industry remains the mainstay for China’s healthy economic growth(Zhao, 2011). Nevertheless, we must be wary of excessive competition, vicious competition and over-capacity caused by overlapping construction. To sum up, future secondary industry development should not rely on expanding investment but on advancing technology and improving efficiency instead.Meanwhile, increasing FAI in the tertiary industry can effectively promote growth of local economy without any significant negative spillover effects on other regions. Such FAI increases are twice efficient in promoting the local economic growth than the same investment in the secondary industry can achieve, thus resulting in a positive overall effect. Therefore, expanding the investment scale in the tertiary industry is the key to promoting industrial advancement in China. To better coordinate the local and national interests, the central government should formulate relevant policies to confine local government’s inclination of investing more in the secondary industry and guide the limited resources flow to the tertiary industry. Meanwhile, since most players in the tertiary industry are all and medium-sized enterprises that are commonly troubled by financing difficulties, the government should establish a financial system that supports the dev
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elopment of Es and urge financial intermediary institutions to increase the financing intensity offering to the tertiary industry. The government should especially offer more targeted incentives to guide private capital to the tertiary industry, and more innovative financial institutions should be established to ensure that the tertiary industry be well-funded (Ding et al., 2011).Even with China’s recent economic slowdown, FAI is still a sensitive topic. Many scholars criticizethe past investment-driven economic growth in China. Most of the criticis fall into two categories. First, they blame a disproportionally high FAI ratio in GDP. Second, they blame the recent inflation and over-capacity associated with the RMB4 trillion stimulus package released in 2009. Indeed, scholars he long been concerned that China’s economic growth is heily dependent on FAI. However, the basis of whether to expand FAI should not depend on its share in GDP, but rather on the ailability of good investment opportunities. The truth is that China has not exhausted all the good investment opportunities but made too many wrong choices, especially for the RMB4 trillion investment process. Poor investment decisions make over-capacity the most serious problem restraining China’s economy. For example, by the end of 2011, the total capacity of approved coal-based methanol projects constructed and under construction had reached 60 million tons while the market demand was only around 14 million tons. The same problem exists in the industry of electrolytic aluminum, polysilicon, LCD panels and automobiles. However, we should come out to think such a problem rationally. Without the RMB4 trillion investment in 2009, what would China’s economy be like today? An ad hoc approach is inadvisable, but the stimulus package did help pull through the difficulties. Besides, studies of some scholars he shown that recent inflation might be an imported inflation; its root originating from the spillover effects of the quantitative easing policy in the U.S. There are other concerns in the academia that no country in the world has ever achieved long-term high-speed economic growth by relying heily on investment. But just because it has never been done before does not mean that it’s not possible. China has achieved remarkable economic success during the past three decades, a fact which is also unparalleled history. That does not mean that China should always rely on investment, but under the current economic transition stage and with the current tax-sharing system, abundant state revenue implies that China will continue its FAI growth mode for the fairly long term. In fact, China’s outstanding economic performance in the past proves that investment was the major driver for China’s economic growth and could be still efficient at the current stage.TFP has significant positive indirect effects and overall effects on the primary industry with a coefficient of elasticity of 0.1137 and 0.1438 respectively. That indicates that although technical progress in agriculture may not he significant positive influence on local economy, throu
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gh technology diffusion it has significant spillover effects on the adjacent regions and ultimately strongly promotes overall economic growth. TFP also has significant positive direct effect on the secondary and the tertiary industry with coefficient of elasticity of 0.105 and 0.1498 respectively, showing that technical progress in these two industries will directly stimulate local economic growth. Such a result confirms one of the objective laws of economics that at a later stage of industrialization, production factors such as resources and labor become less and less efficient in promoting economic growth while the technology intensive industry gradually occupies a larger share (Jin, 2011). In conclusion, economic growth can no longer simply rely on cheap labor. The key to changing the economic development pattern is technological progress and production efficiency increase. Fortunately, these two factors he become the core driver of China’s economic growth.5. Conclusion and Policy Implication
China’s recent economic slowdown has provoked academic discussion with the focus on how to ensure sustainable and healthy economic growth. To answer the question, analyzing resources allocation efficiency is essential. However, existing studies can hardly oid biased results by simply comparing industrial layout between China and Western industrialized economies, or ignoring the close economic relationship among different regions by using conventional panel data model. In this paper, we adopt the newly developed spatial panel model to study how regional resources allocation might affect local economies and economies in other regions so as to better understand the real influence of resource factors, including labor, FAI and technical progress on China’s economic growth. The conclusions are: 1) during the past 13 years, the labor force has insignificant effect on all the three industries, meaning that the labor force is not the core driver for China’s economic growth. In this sense, demographic dividend theory is proved invalid for explaining China’s economic growth. 2) FAI has insignificant effects on promoting the development of the primary industry. However, in the secondar摘自：毕业论文题目www.udooo.com
y industry, FAI has produced prominent positive direct effects but even severer negative spillover effects which outweigh the positive one. In the tertiary industry, FAI is positive in both direct and total effect. We conclude that FAI is still effective to drive growth, but investment should be made in the tertiary industry, not the secondary industry. 3) Technical progress has a positive effect on the three industries, much stronger than the other resource factors, suggesting that technical progress is the core driver for healthy and sustained economic growth. Meanwhile, it is the direction of economic development pattern and the inevitable path selection in China.At present, we are in the face of new challenges, such as restricted export due to a gloomy global economy. Household consumption relies much on the future expectation of economic prosperity. Therefore, fixed asset investment remains the most effective choice for maintaining growth and guaranteeing prosperity. Obviously, the major concern is what to invest rather than whether or not invest. The Americans started railway construction since late 19th century, which brings changes to not only the U.S., but the entire world as well. We can assume that there must be the problem of overcapacity when the construction was initially completed. Even until today, many railways and expressways in most developed countries are not used at its full capacity. However, isn’t a well-developed transportation network an important feature of a developed country? Without all those infrastructure projects, can they still be developed countries? It is indisputable that infrastructure construction alone does not necessarily create economic prosperity, but without it, the economy definitely doesn’t work. The Chinese central government has given a series of blueprint and development goals which mostly rely on economic growth. In return, the prerequisite of economic growth should be infrastructure construction. China’s healthy economic growth needs FAI, at least for now. At present, construction projects in China are still inadequate. We already saw an oversupply of industry parks and residential apartments, but they still lack well-planned transportation network and infrastructure. The shortage of infrastructure is best evidenced by traffic jams in all major cities of China. Continuing to expand the FAI mainly on railways, roads and infrastructure will not only help maintain economic growth and guarantee economic prosperity in China, but also create domestic demand to guarantee growth in the future. The Chinese central government should provide guidance for investment in order to create better economic development environment and achieve economic prosperity under market mechani. Another benefit is that investment in transportation and infrastructure can partly relieve the problem of overcapacity caused by overheating in the real-estate market, so we may ensure a soft landing, ensure healthy development of China’s economy and achieve industrial upgrading.
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