Dataset of China's non-competitive constant price input-output tables for 2007 and 2012

The China's Input-Output tables for 2007 and 2012 which were published by the China National Bureau of Statistics are competitive current price input-output tables. Based on these tables, this paper constructs the China's non-competitive constant price input-output data for 2007 and 2012. This dataset is supplementary to Ref. [1]. And we share the raw data about China's IO tables for 2007 and 2012. Furthermore, the new IO tables data which we constructed will also be uploaded.


Experimental design, materials, and methods
The following four steps are used to process the data in this article. The first step is to adjust the sector divisions used in the 2012 IO table (IO2012) based on the 2007 IO table (IO2007). In order to ensure the consistency of the sectors in the IO2007 and IO2012, some sectors have been merged and 40 sectors are retained. The second step is to useRAS method to adjust IO2007 from the current price to the 2012 price. Because there are only 30 sectors that have electricity consumption data. The third step is to merge the 40 sectors of IO2007 and IO2012 to the 30 sectors. The fourth step is to change the competitive IO2007 and IO2012 to non-competitive IO tables.
We use electricity consumption data for various industrial sectors published by the National Bureau of Statistics in 2007 and 2012. In addition, we also use China's IO tables for 2007 and 2012, which were published by the National Bureau of Statistics in 2009 and 2015, respectively. The sector divisions used in the two IO tables are inconsistent, which is shown in Table 1. In IO2007, "Transport, Storage" and "Post" are merged to "Transport, Storage and Post". "Scientific Research and Development" and "Technical Services" are merged to "Scientific Research and Development, Technical Services". There are 40 sectors in the new IO2007. Then the sectors in the IO2012 are adjusted based on this new IO2007. There are also 40 sectors in the new IO2012 (see Tables 2e8). Specifications Table   Subject economics Specific subject area input-output analysis, energy economics Type of data  Note: "[" indicates increment, and "/" indicates final value.

Table 3
Adjustment the column vector of "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector.

Sector adjustment of IO2012
We use the departmental consolidation method of constructing the IDE-JETRO International Input Output table used by Meng et al. (2013) [3]and adjusts the divisions used in the IO2012 based on the IO2007. There are "Manufacture of Artwork, Other Manufacture" sector in the IO2007 and "Other Manufacture" sector in the IO2012. These two sectors are different. It's because that "Manufacture of Artwork" sector is divided into "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector in IO2012. So "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector is also different between the IO2007 and IO2012.

Adjustment procedure
(1) With the help of the China Industry Statistical Yearbook 2013, we could find the industrial sales output value of "Manufacture of Artwork" sector (655.033 billion yuan) and "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector (2716.915 billion yuan) in 2012. The percentage of "Manufacture of Artwork" sector in "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector was 24.11% in 2012. (2) Using the ratio thus derived, the row vector of "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector is expanded to a matrix for intermediate transactions. (3) This ratio is also applied to demarcating the column vector of "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" sector. (4) The "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" thus derived is added on to the table. (5) The row and column vectors of "Papermaking, Printing and Manufacture of Articles for Culture, Education and Sports Activities" are changed to a new one which excluded "Manufacture of Artwork" sector. And "Other Manufacture" sector added "Manufacture of Artwork" sector to form "Manufacture of Artwork, Other Manufacture" sector.     are deleted.

Sector classifications
After sector adjustment of IO2012, the sector divisions of IO2007 and IO2012 IO are the same which includes 40 sectors. Table 9 shows the sector classification.

RAS method for deflating Chinese IO table
In order to focus on real rather than nominal changes in our decomposition analysis, the IO table used should be corrected based on constant prices. The method that has been most widely used for the estimation of IO tables in constant prices is Double Deflation (DD) [4]. Though this method is generally accepted, it still involves certain problems which have been reported in Sevaldson (1976), Wolff (1994), and Dietzenbacher and Hoen (1998) [5e7]. The two main problems can be summarized as follows: First, under this method, an entire row in the IO table is deflated using the price index of gross output. This method ignores the practical situation where price indices are likely to be different within a row of intermediate deliveries, since most sectors produce more than one good, and each sector requires a different mix of these goods as an input. Second, the published IO table available to the normal user is already largely aggregated, meaning that the user can only adjust the IO table in constant prices via deflation after aggregation. Therefore, the aggregation error may influence the accuracy of the deflation.
To encountering the above problems, Dietzenbacher and Hoen (1998) propose an alternative method from the user's viewpoint [7]. Under their method, the intermediate deliveries in constant prices are estimated on the basis of intermediate deliveries in current prices, and the row and column sums in constant prices. This estimation precisely satisfies the requirements for applying the RAS method. And this method performs better than DD.
The RAS-procedure is a biproportional projection method that was developed for "updating" a given matrix (say A 0 , not necessarily square), such that the updated matrix (Ã 1 ) satisfies exogenously given row and column sums. The RAS-method proceeds iteratively. In the first step the rows are adjusted. Each row i is multiplied by a scalar r i such that the i-th row sum equals the prespecified row sum of A 1 . The resulting matrix after step 1 may be denoted asÃ 1 ð1Þ ¼ b r 1 A 0 . In the second step, the columns ofÃ 1 ð1Þ are adjusted so as to satisfy the column sum requirement. This yieldÃ 1 ð2Þ 1 It is likely, however, that the row sum requirements are violated. Therefore the rows are adjusted again; Next, the columns are adjusted again: after the fourth step. It can be shown that under mild conditions the iterative procedure converges. The updated matrix can be written asÃ 1 ¼ b rÃ 0 b s and does not depend on whether the procedure is started with a row adjustment or with a column adjustment. The RAS-method has been applied to estimate next year's coefficients matrix (A 1 ) on the basis of this year's matrix (A 0 ), given next year's row and column sums. In this paper we apply the RASprocedure to estimate the input-output table in constant prices, on the basis of the table in current prices, given the row and column totals in constant prices.
The input-output table in current prices is given in Table 10, the table in constant prices, using the RAS method, in Table 11.
The n Â n matrix Z denotes the intermediate demand matrix, the vector f the final demands (rural household consumption, urban household consumption, government consumption, gross fixed capital formation, changes in inventories and exports), the vector m the imports, the vector e the errors, x denotes the vector with sectoral outputs. v 0 is a row vector, the elements of which are value added of industrial sectors. In Table 11, the subscript d (for deflated) is used to indicate that the corresponding matrices and vector are in constant prices. In this paper we apply the RAS-procedure to estimate the input-output table in constant prices, on the basis of the table in current prices, given the row and column totals in constant prices. In this method, the sectoral outputs (

Price deflators of industrial sectors
Because producer price is used in China's IO table. Relevant producer price indices are used to calculate price deflator of primary industry and secondary industry sectors. 1 Using the following formula to calculate the price deflator of primary industry and secondary industry sectors:   For tertiary industry exclude "Finance" and "Real Estate" sector, we use relevant consumer price indices followLiu Qiyun and Peng Zhilong (2010) [8]. This is because China don't have producer price indices for tertiary industry. The relation between the tertiary industry and the price indices in Table  12. The formulas to calculate the price deflator of these industry sectors are as follows: For "Finance" sector, we take a weighted average of "Consumer Price Index (preceding year ¼ 100)" and "Price Indices for Investment in Fixed Assets (preceding year ¼ 100)" to produce a composite number, which is price deflator of "Finance" sector. The weights are derived from ratio between household consumption expenditure and total investment in fixed assets in the whole country. Data sources: National Bureau of Statistics of China.
For "Real Estate" sector, we use the following formula to calculate its price deflator [9].

Price deflator of value added
The computational process for the value added in current prices is more complex. Firstly, in the same way, the value added deflator r j is defined as the price ratio between the base year value added price and the current value added price, for product j. We could only get 9 value added prices of industrial sectors. They are "Indices of Value-added of Agriculture, Forestry, Animal Husbandry and Fishery Industries", "Indices of Value-added of Industry", "Indices of Value-added of Construction", "Indices of Value-added of Wholesale and Retail Trades", "Indices of Value-added of Transport, Storage and Post", "Indices of Value-added of Hotels and Catering Services", "Indices of Value-added of Financial Intermediation", "Indices of Value-added of Real Estate" and "Indices of Value-added of Others". Among them, "Indices of Value-added of Industry" and "Indices of Value-added of Others" cover 24 and 9 industrial sectors respectively. We use the following formula to calculate value added price deflators [9]. Then these 9 industries' value added in constant price could be got. But "Industry" and "Other" sectors conclude 24 and 9 sub-classification industries and the value added of these sub-classification industries can't be derived from the calculation progress above.
Secondly, we use the price deflators of these sub-classification industries to calculate their value added in constant price, then calculate their proportion structure. Using the value added of "Industry" and "Other" sectors and the sub-classification industries' value added proportion structure, the value added of these sub-classification industries could be computed. Therefore, all these 40 industries' value Thirdly, the final value added vector v 0 d is obtain from the balancing equations. That is, the equality of the row sums and the column sums imply ðx u is 40-element column vector, where all the elements are 1.
and v 0 d can be derived.   Table 14.

Non-competitive IO tables
There are two assumptions: 1. no re-export trade; 2. sector internal product is homogenous. The 2007 and 2012 China's IO tables published by the National Bureau of Statistic are competitive which include imports.
M is the nth-dimension import column vector, where m j represents the total import of the jth department. Z is the n Â n competitive intermediate demand matrix. The z ij terms represent interindustry sales by sector i (also known as intermediate sales) to all sectors j (including itself, when j ¼ i), and z ij includes imports. z ij ¼ z d ij þ z m ij , where z d ij terms represent interindustry sales from the domestic market and z m ij terms represent interindustry sales from overseas market. T is the nth-dimension column vector.
The same proportion (m i . P n p¼1 z ip ) is used to split z m ij from the interindustry sales by sector i,then,