Five Year Plan and Supporting Intensity ··········································

3.2.1 The Five Year Plan

The most important and widely influential industrial policy in China is the Five Year Plan, which has been enacted by the central government every five years since the

establishment of the People’s Republic of China11_{. The main goals of the Five Year} Plans are to guide investment and economic activities in the following five years. For example, the aim of the first Five Year Plan issued in 1953 was to guide investment into the establishment of multiple industries in most provinces and districts. Every Five Year Plan lists the industries that are going to be supported in the following five years, and industries which are considered to be important for national defense like metal smelting are supported for most of the Five Year Plans.

Local governments are the executors of the Five Year Plans. After the issue of the Five Year Plan by the central government, local governments like provincial, district, and county make regional plans to support the industries mentioned in the Five Year Plans by the central government. Local governments take all kinds of measures to support these industries, because the development of these industries is one of the important indicators for officers’ promotion.

3.2.2 The 10th Five Year Plan

I study the effects of the 10th _{Five Year Plan on misallocation, profitability and} technology. The reason to focus on the 10th _{Five Year Plan is that firm-level data is only} available from 1998-2005. The 9th and the 10th Five Year Plans span from 1996-2000 and 2001 to 2005, respectively. Therefore, the available data allows me to examine the effects of the 10th Five Year Plan. Moreover, the data are from the Annual Surveys of Industrial Production conducted by the Chinese National Bureau of Statistics. The surveys contain information such as firm’s age, wages, subsidies, industry, location, value-added, tax payments, book value of net depreciation, etc. Based on the official documents of the Five Year Plans and firm’s industry information in the data set, I can identify the 4-digit level industries that are supported by the 9th or the 10th Five Year Plans.

Like most of the recent Five Year Plans, the 10th _{Five Year Plan by the central} government lists the name of supported industries in the official document. Therefore,

11 _{Most of the Five Year Plans were issued every five years since 1953, except there are 3 years gap between the}

with this information, I am able to match the supported industries in the Five Year Plan to the industries and firms in the data set. However, Chinese National Bureau of Statistics used different Chinese Industrial Classifications (CIC) codes to classify industries before and after 2002. The first step is to match the CIC codes of the years 1998-2001 with those of 2002-2005, even though there are only a small portion of industries that changed their codes number. I use the industrial codes of 2002-2005 to recode those in 1998-2001. The next step is to match the industries supported by either the 9th or 10th Five Year Plans to the 4-digit level industries in the data set. I match the date sets by hand for accuracy. After matching, supported industries can be identified, and all firms inside the supported industries are also treated as in the supported group. After matching, there are 194 industries supported by the 10th _{Five Year Plan out of the} total 482 four-digit industries. Moreover, 89 of the supported industries are supported by both the 9th and the 10th Five Year Plans, and 105 of the supported industries are supported by the 10th Five Year Plan only. Specifically, around 53% firms are in the industries supported by the 10th Five Year Plan, and around 33.4% firms are supported by the 10th Five Year Plan only.

A natural question to ask is: why are these industries are supported by the 10th Five Year Plan? From the official documents of the 10th Five Year Plan, the aims to support these industries are to restructure industries and to enhance international competitiveness. Industries like raw materials manufacturing and textiles manufacturing are encouraged to restructure by increasing products variety, improving quality, reducing energy use and pollution, using more advanced technology, etc. Moreover, hi-tech industries such as computer equipment, airplane manufacturing, and optoelectronic materials manufacturing should adopt the world frontier technology to be more internationally competitive.

As an industry or a firm can be supported by both the 9th Five Year Plan, it brings interference to identify the effects of the 10th Five Year Plan on industries’ outcomes. Therefore, in order to identify the effects of the 10th Five Year Plan on misallocation, profitability and technology, I need to eliminate the effects of the 9th Five Year Plan to avoid over-estimation of the effects of the 10th _{Five Year Plan. As mentioned above, the}

available data ranges from 1998 to 2005, which covers the last three years of the 9th Five Year Plan period and the whole five years of the 10th Five Year Plan period. Therefore, industries can be divided into four groups by whether they are supported by the 9th or the 10th Five Year Plans. These four groups of industries are: (1) supported by the 9th Five Year Plan only, (2) supported by the 10th Five Year Plan only, (3) supported by both the 9th and the 10th Five Year Plans and (4) not supported by neither the 9th nor the 10th Five Year Plans.

Only groups (2) and (4) are kept in the date set to identify the effects of the 10th Five Year Plan. The Five Year Plans could potentially affect misallocation of supported industries. Therefore, if industries supported by the 9th _{Five Year Plan are included in} the sample, the estimates could be biased. I exclude industries supported by the 9th _Five Year Plan to avoid these compounding effects.

3.2.3 Supporting Intensity

As executors of the Five Year Plan, local governments might support the targeting industries differently. The importance of the supported industries for the local economy might affect the governments’ supporting strength. For example, if the supported industries happen to be considered pillar industries and contribute most of the value- added for a province or district, local governments could provide more support to those industries.

As industries might obtain difference support, I use the ratio of value-added of supported industries to that of all industries in a province to measure supporting intensity. Higher supporting intensity does not guarantee that the target industries will obtain more support. Figure 3.1 shows support intensities in different provinces in different years. Panel A and B show supporting intensities in provinces before the issue of the 10th _{Five Year Plan. Surprisingly, less developed provinces in the middle and} western regions have higher supporting intensity. Provinces in the eastern coast have relatively lower intensities. After the issue of the 10th Five Year Plan in 2001, a few provinces move to tiers with higher level of intensity, but there are also some provinces

that move to groups with lower level of intensity from 2000 to 2001. By the end of the 10th Five Year Plan in 2005, more provinces have lower levels of intensities, which is also surprising because supported industries should have higher value-added share after receiving support from local governments.

Besides the geographical difference of supporting intensity among provinces, Figure 3.2 shows the change of value-added share for each province from 1998-2005. The supporting intensities in provinces such as Hainan, Xizang, and Ningxia Hui, increased after the issue of the 10th Five Year Plan. However, the supporting intensities of provinces like Beijing, Hubei, Jiangxi and Xinjiang, decreased drastically, and the intensity of some other provinces dropped slightly.

Several possible reasons can explain why supported industries have lower value-added shares in 2005 than 2001. First of all, compared with supported industries, there might be more firms and faster development in not supported industries. Secondly, the Five Year Plan could have had an opposite effect on the value-added of supported industries to the original aim. For example, if most of the support is given to firms with lower productivities, the overall growth rate of the supported industries will lag behind. Moreover, if local governments choose to support those largest state-owned firms, a decrease in competition could lead industries to have lower output.