2.2. Data Collection and Processing
Considering that China’s official statistical data on industrial segmentation were significantly different in 1999, and taking into consideration the availability as well as the comparability of statistics, the relevant data of 34 industrial sub-sectors from 2000 to 2010 are selected in our research (The codes and corresponding names of these 34 industries are presented in
Appendix A (
Table A1)) These data have been derived from the CSY,
China Science and Technology Statistical Yearbook, and
China Energy Statistics Yearbook. The comprehensive data sources and treatment methodologies for the associated variables are described hereafter.
The energy intensity of each industry (unit: tons of coal equivalent per 10,000 yuan) is calculated by the ratio of energy consumption to the industrial added value. Furthermore, the aggregate amount of the energy consumed by different kinds of sectors over the can be obtained from the China Energy Statistical Yearbook (various years). Value-added data between 2000 and 2010 were obtained from the “Main Indicators of Industrial Enterprises above Designated Size by Industrial Sector” in CSY (various years). These data require adjustment to the steady price in the year 2000 by the industrial product price index acquired from the CSY. Nevertheless, because there are no data available on the added value between 2008 and 2010, the data on the cumulative growth rate of the value added that are obtained from the National Bureau of Statistics of China are used for the purpose of estimating the value added between 2008 and 2010.
The indigenous R&D stock is represented by the internal R&D operations of large and medium-sized industrial entities in different sub-sectors. Similar to Huang et al. [
5], the corresponding R&D expenditure data can be obtained from the
China Science and Technology Statistical Yearbook, followed by converting to the base period with the GDP deflator. Subsequently, in accordance with the perpetual inventory theory, we are able to perform the calculation of the R&D capital stock formed by R&D activities in the industrial subsectors over the years to yield:
where
σ indicates the capital depreciation rate that is consistent with the data put to use by Yan [
1] and Huang et al. [
5], where
σ = 9.6% (For the purpose of testing the stability and verifying that our estimated empirical results are credible, the test with
σ = 15% is repeated. The results have been presented in
Appendix B (see
Table A2). As suggested by the comparison carried out, the approximated findings are strong). Furthermore, the R&D capital stock of the base period is calculated in accordance with the method of Yan [
1] for the creation of an entire time series of the capital stock:
where
is a representation of the annual growth rate of indigenous R&D in 2000–2010.
As a result of lacking direct investment, coupled with the trade data from most of China’s industrial sub-sectors and foreign countries (regions), we make use of the CH–LP technology spillover analysis framework for the calculation of the total amount of technology spillovers that China has acquired by means of FDI and trade (FDI is expressed in terms of actual use of foreign investment. The data on imports from other nations (regions) are expressed with regard to the countries of origin and regions of China. The data on exports to other countries (regions) are expressed in terms of the destination countries and regions of China. Owing to the fact that Hong Kong is counted among the largest trade regions in entrepot trade with China’s mainland, the goods exported from China to Hong Kong require adjustments. However, it is also quite difficult to calculate the re-exports accurately. For simplicity, we make an assumption that the total amount of goods that China imports from Hong Kong is equal to that exported to Hong Kong) In accordance with Coe and Helpman [
26] and Van Pottelsberghe de la Potterie and Lichtenberg [
27], the total amount of technology spillovers that China obtained by means of FDI, imports, and exports can be expressed as follows:
Herein, the subscripts n (n = 1, 2, 3, ..., N) as well as t (t = 1, 2, 3, ..., T) represent the foreign country (region) and the year, respectively. Moreover, SFDI, SIM, and SEX are, respectively, the corresponding indications of the technology spillovers that China has acquired by means of the openness in the shape of FDI, imports, and exports. FDInt denotes the total direct investments foreign country (region) n invested in China in year t. IM and EX both are the aggregate import and export commodities between China and its trading partners (or areas). K, S, and Y are the aggregate fixed capital creation of foreign countries (regions), R&D capital stock, and gross domestic product, respectively. Taking into consideration that the major R&D activities worldwide are carried out in some developed countries and there are relationships between China and these countries in terms of investment and trade, the G7 countries, Hong Kong, Singapore, and Korea are selected as China’s key technology spillovers. In addition, the perpetual inventory theory is again applied for the calculation of R&D capital stock for foreign countries (regions).
Subsequent to the calculation of the technology spillovers that China has acquired by means of openness, next we determine the technology spillovers obtained by each industrial sub-sector. We assume that China’s industrial sub-sectors have gained technology spillovers on the basis of the ratio of their FDI, exports, and imports to China’s total. However, only the FDI data on mining, production, power, gas and water generation, and supply sectors are available from the
CSY, so we make use of the ratio of the assets in industrial sector
m’s foreign-funded enterprises to the total assets in all the industrial sectors to denote the percentage of their FDI versus the aggregate in China. Then we are able to present the technology spillovers attained by each industrial sub-sector originating from FDI as follows:
where
m (
m = 1, 2, 3, …,
M) is the industrial sub-sector and
t (
t = 1, 2, 3, …,
T) stands for year.
SFDImt suggests the technology spillover by means of FDI received by the industrial sub-sector
m.
denotes the share of FDI acquired by the whole industrial sector to the total FDI received by China in year
t.
stands for the ratio of the assets in industrial sector
m’s foreign-funded enterprises to the total assets in all industrial sectors. In the same manner, we are capable of expressing the technology spillovers obtained by different kinds of industrial sub-sectors in China by means of exports and imports as follows:
where
IMmt and
EXmt are the total amount of imports and exports of the industrial sector
m at time
t, respectively. The total imports and exports of each industrial sub-sector over the years are from the three-digit industry classification data of the UN Comtrade database in SITC Revision.3 standard and are merged in accordance with the industry classification standard data of the National Bureau of Statistics of China.
Structural change, as represented by the ratio of the assets in a sub-sector to the total assets in the aggregate industrial sectors, is selected as the control variable; the relevant data are from the CSY.
Table 1 gives definitions of the variables put to use in the model and their data characteristics.