Auxiliary Tables and Figures

Additional file 3

Auxiliary tables and figures

Table S1

Representativeness of theNTSD over 2007-2011

Notes: A1, B1, C1, D1 and E1 are from the NTSD, whereas A2, B2, C2, D2 and E2 are from the National Bureau of Statistics of China. The units of A (A1 and A2), B (B1 and B2) and D (D1 and D2) are all 100 million Chinese RMB. The unit of C (C1 and C2) is 10 thousand persons. Since A1 is mainly reported by taxpayers of the first and second industries in the sample, A2 is output from these sectors. Similarly, for B1 is mostly reported by taxpayers from the second industry in the sample, B2 is valueadded of this sector. C2 does not include rural employment, in that the agricultural taxes have been abolished since 2006. D1 is tax actually paid by taxpayers, but not payable tax. D1 includes 17 of 18 tax categories currently levied in China, i.e., VAT or Value-added Tax, Consumption Tax, Business Tax, Tariff, Private Income Tax, Corporate Income Tax, Resources Tax, Urban Land Use Tax, Land Appreciation Tax, Farmland Use Tax, House Property Tax, Contract Tax, Vehicle Purchase Tax, Vehicle and Vessel Tax, Stamp Tax, Urban Maintenance and Construction Tax, and Tobacco Leaf Tax. The only exception is Tonnage Tax, mainly because of its small scale of revenues that is averagely only 0.04 percent of total tax revenues over 2007-2011. Accordingly, D2 also excludes Tonnage Tax. E2 excludes those in sectors like education, social welfare and public management, most of whom are not taxpayers.

Table S2

Factors Determining Probability of Being TID Beneficiary

Notes: Subsample C of the benchmark sample consists of incumbents in the polluting industries without those who have income required for TID in the last year but have no such income in the current year. Subsample D of the benchmark sample consists of incumbents in the polluting industries without those who have income required for TID in the last two years but have no such income in the current year.For other notes, see Table 3.

Table S3

Effects of ITC and TID on Taxpayer’s other Activities

Note: See Table 5.

Table S4

Robustness Checks on Effects of ITC and TID: Adding Regional Characteristicsor Using Dummies for Age and Size

Notes: All the columns use the specification in equation (2). Columns 1-4 add regional characteristics, while the rest columns control dummies for age and size instead of using logarithm of them. We also try controlling industry and industry-year fixed effects, or using net capital stock, fuel inputs and value added as dependents, and find that the results are similar.For other notes, see Table 5.

Table S5

Robustness Checks on Effects of ITC and TID: Using Ordinary Growth Rate or Natural Logarithm of the Dependent Variables

Notes: All the columns use the Fixed-Effect model similar to equation (2). Columns 1-4 use ordinary growth rate of the dependent variables, while the rest columns use natural logarithm of these variables. We also try controlling industry and industry-year fixed effects, or using net capital stock, fuel inputs and value added as dependents, and find the results are similar to those in this table or Additional file 3: Table S3. For other notes, see Table 5.

Table S6

Strictness of Taxation in China: Evidences from Effective Tax Rate of Corporate Income Tax

Notes: ***, ** and * represent 1%, 5% and 10% significant level respectively.All the columns use the Fixed-Effect model similar to equation (2), and use the sample of incumbents in the full sample (manufacturing firms existing over 2007-2011). The values in parentheses are robust standard errors. Residuals are clustered to groups of province-industry. ETR of CIT refers to the ratio of paid corporate income taxes to total profits. lagROA is one-period lagged ROA. NTB is dummy for firms levied by the national taxation bureaus. SOE are dummy for state-owned enterprises. Noncentral is dummy for firms not affiliated to the central government. The reason why we use Noncentral instead of Central is that all of firms attached to the central government are levied by the national taxation bureaus. So the interactions will be meaningless if we use Central. Columns 1-4 use original value of the dependent variable, while Column 5 usesweighted growth of it. The reason why we mainly use the original value but not weighted growth is that effective tax rate mainly reflect taxation enforcement of the government, but not firms’ activities. We believe that, compared to firms’ activities like capital, employment, energy use or production, taxation enforcement of the government will be less affected by changes in the sample like merger or acquisition between firms. But the main results are robust across the columns, implying that the pattern of the dependent does matter. Except Column 4, in which we concern industry and industry-year fixed effects for a robustness check for Column 3, province and province-year fixed effects are controlled. The results of interest in this table are the parameters of dummy for firms taxed by the NTBs who belong to the central government in both finance and personnel, and dummy for firms not affiliated to the central government, as well as the coefficients for interaction of them. They show two things. One is that the NTBs are more strict executives of taxation than the LTBs (local taxation bureaus who are affiliated to both the State Administration of Taxation in Beijing and subnational governments). The other is that firms attached to the central government are more strictly taxed.

Figure S1

Distribution of Province-level Real Fiscal Spending Per Capita for Environmental Protection over 2009-2011 in China

[Insert Figure S1 Here]

Notes: The data are from China Statistical Yearbooks over 2010-2012. The figure using the data over 2007-2011 is close to this figure.