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How Do Tax Agents Respond to Anti-corruption Intensity?

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Abstract

We examine whether anti-corruption intensity strengthens tax enforcement effectiveness in China. Using hand-collected anti-corruption data and aggregate tax enforcement data, which include the probability of tax audits and tax deficiencies, for a sample of 11,687 firm-year observations from 2012 to 2017, we find that anti-corruption intensity increases the deterrence role and the enforcement role of tax audits. We also identify the fear effect as a possible channel through which anti-corruption intensity affects tax enforcement effectiveness. Overall, the results indicate that anti-corruption intensity can improve a revenue agency’s effectiveness.

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Notes

  1. According to our conversations with some officials, their benefits dropped significantly following implementation of the campaign.

  2. “Princeling” is a term first coined by the media, referring to the offspring of the top politicians. See Page (2011).

  3. The evaluation by local government is also important for tax agents of the SAT.

  4. It is the finance bureau through which local government affects the local tax bureau. A change in local government leadership may have effects on tax enforcement. For example, after the Bo Xilai scandal was exposed, he was removed from the Central Committee of the Communist Party of China in 2012, and the Chongqing government immediately ordered its Bureau of Finance to enhance tax enforcement (21st Century Business Herald, 2013).

  5. Slemrod et al. (2001) conjecture that individual taxpayers claimed more tax benefits to create a more aggressive starting point for negotiations with the tax authority, with the goal of minimizing their tax liability, given that they knew the returns they were about to file would be “closely examined.”.

  6. Chinese officials have different administrative levels. The ranks from the lowest to the highest are as follows: fuke, zhengke, fuchu, zhengchu, futing, zhengting, fubu, zhengbu, fuguo and zhengguo. Futing is approximately the same level as mayor, and can make some major decisions in a province/region.

  7. We focus only on investigated persons at the regional level, rather than the central level. This allows us to test whether local tax enforcement effectiveness changes due to local officials being investigated. We also use the number of investigated officials in a region divided by the total population in that region as the measure of anti-corruption intensity. The results are exactly the same. In addition, the investigated individuals in corruption investigations in China have been found guilty.

  8. Unlike Lin et al. (2018), we focus only on audit probability and audit outcome and not on audit expertise. This is because we test the impact of anti-corruption intensity on tax enforcement effectiveness. Audit expertise is relatively stable and therefore is less likely to be affected by anti-corruption intensity.

  9. In addition to 27 provinces and four province-level municipalities in the Chinese mainland, there are five cities with independent tax and finance planning systems, including Qingdao (in Shandong province), Ningbo (in Zhejiang province), Dalian (in Liaoning province), Xiamen (in Fujian province) and Shenzhen (in Guangdong province).

  10. The yearbook, prepared annually by the SAT, contains detailed information about tax enforcement data for each province and major city in China. The hand-collected tax enforcement data are for overall tax deficiencies, and include all types of taxes.

  11. Interacting two continuous variables could artificially induce multicollinearity. To avoid such artificially induced multicollinearity, we demean (i.e., subtract the sample mean) TE and AC before interacting them (Aiken and West, 1991; Iacobucci et al., 2017).

  12. Tax enforcement data from the China Tax Audits Yearbook ends in 2017.

  13. The sample year ends in 2017, which is the last year for which tax enforcement data are available. The starting years of investigations by the CCDI for all regions in China are from 2012 to 2015. Accordingly, we use two years before and two years after for the parallel trends test.

  14. We also employ DID analysis to test the impact of anti-corruption intensity on tax enforcement effectiveness. Specifically, we use 2012 as a benchmark year to test whether our results hold if we focus on an exogenous shock to political officials. We classify firms in regions whose median anti-corruption intensity over the sample period is above the median for all regions as treatment firms (Treat = 1), and firms in all other regions as control firms (Treat = 0). We then create the time variable Post, which equals 1 for the years 2012 to 2017, and 0 for the years 2005 to 2011. The regression results based on thesetests are just confirm the main results.

  15. We also use beforek (k = 1,2,3) and afterk (k = 1,2,3,4). The results are quite the same.

  16. In the first-stage regression estimates, the F value is 44.80 (74.14) when we use TAR (TDE) as the tax enforcement measure. Therefore, we reject the null hypothesis that these variables are weak instruments. In addition, the Sargan value is 9.15 (p = 0.0103), rejecting the overidentified restrictions criterion.

  17. All the awards are for tax agents’ performance.

  18. For this analysis, we focus on the year of service for which the tax agent is granted the award, not when the actual award is received (usually 2 years later). Therefore, the sample begins in 2012 when the anti-corruption campaign begins, and ends in 2016, the last year for which award information is available (the China Tax Audits Yearbook ends in 2017).

  19. 2005 is the earliest year with tax enforcement data available from the China Tax Audits Yearbook.

  20. We thank for this suggestion from one of the reviewers.

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Funding

The work was supported Humanities and Social Sciences project of China’s Ministry of Education [20YJC630098] and Social Science Foundation of Shaanxi Province [2019S015].

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Authors and Affiliations

  1. School of Economics and Management, Northwest University, Xi’an, China

    Chen Ma

  2. School of Economics and Finance, Xi’an Jiaotong University, Xi’an, China

    Maoyong Cheng

  3. C.T. Bauer College of Business, University of Houston, Houston, TX, USA

    Gerald J. Lobo

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  1. Chen Ma
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Correspondence to Maoyong Cheng.

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Appendix

Appendix

Variables

Definitions

ETR

One-year effective tax rate, defined as annual income tax expense divided by annual pretax income

TAR

Tax audit rate, defined as the number of corporate income tax audits conducted divided by the number of corporate income tax returns filed

TDE

Tax deficiencies, i.e., economic consequences of the tax audits in terms of additional tax payments for tax underreporting, measured by the amount of tax deficiencies settled divided by the amount of regional tax revenues

AC

Anti-corruption intensity, measured as the numbers of investigated persons divided by the total population (million) in that area

ROA

Return on assets, net income divided by total assets

LNA

Firm size, the natural logarithm of the firm’s year-end total assets

LEV

Leverage, total liabilities divided by total assets

PPE

Plant, property, and equipment, net PPE divided by total assets

INTANGI

Intangibles, intangible assets divided by total assets

INV

Inventory, inventory divided by total assets

CASH

Cash holdings, year-end cash holdings divided by total assets

EQINCI

Equity in earnings, equity income divided by total assets

MB

Market value of equity divided by book value of equity

DA

Discretionary accruals estimated from the cross-sectional Jones model

SOE

Ownership structure, state-owned enterprises or non- state-owned enterprises

BIG4

Auditor type, Big 4 auditor or non-Big4 auditor

BSIZE

Board size, the number of board members

INSTITUTION

The Index of Marketization for China’s Provinces, compiled by Wang et al. (2016)

InvestigationAFT

A dummy that equals one in affected province j for both the investigation year t and the following years, and zero for all other years

CHARITYU

The number of charity universities in a province/city, measured as the number of church universities founded by Christian missionaries in each region by 1920

CONCESSION

The incidence of concessions in a province/city, a dummy variable indicating whether there was once a concession or leased territory in the region

AGENTS

The number of the agents being awarded

LNAGENTS

The natural logarithm of the number of the agents being awarded plus 1

RAGENTS

The ratio of the number to total population in that region

IAGENTS

The incidence of agents being awarded, an indicator variable that equals 1 if at least one agent is granted an award in a region-year, and 0 otherwise

IDEPTS

The incidence of departments being awarded, an indicator variable that equals 1 if at least one department is granted an award in a region-year, and 0 otherwise

IAWARD

The incidence of agents or departments being awarded, an indicator variable that equals 1 if at least one agent or one department is granted an award in a region-year, and 0 otherwise

LNGDP

The natural logarithm of GDP

LNPOPUL

The natural logarithm of population

AWARDTYPE

The type of award; equals 2 if the award is at the national level (from the SAT), 1 if the award is at the regional level, and 0 if there is no award

change

Provincial secretary changes, equals 1 if the local provincial secretary changes, and 0 otherwise

TIP-OFF

Number of tip off case divided by the number of total taxpayers in a region

NUMBER

Ratio of number of tax auditors to the number of total tax agents in a region

PARTY

Ratio of number of Communist Party member to the number of total tax auditors in a region

AC1

Alternative anti-corruption intensity, measured as the numbers of investigated persons divided by the total companies in that area

TAXRATE

Nominal tax rate employed by a firm

DTAR

Dummy TAR measure, equals one if TAR (TDE) is above its median, and zero otherwise

DTDE

Dummy TAR measure, equals one if TAR (TDE) is above its median, and zero otherwise

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Ma, C., Cheng, M. & Lobo, G.J. How Do Tax Agents Respond to Anti-corruption Intensity?. J Bus Ethics 190, 137–164 (2024). https://doi.org/10.1007/s10551-023-05398-w

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