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Citizens’ Confidence in Government Control of Corruption: An Empirical Analysis

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Abstract

This study provides a nuanced and interactive analysis of institutional confidence in government. It investigates the drivers of institutional confidence by differentiating them into outcome-based and performance-based modes and examining the interaction between the two modes in influencing confidence levels. Drawing on survey data obtained from three Chinese cities, this study extends the two-dimensional analytical framework to examine public confidence in the government’s control of corruption. The study has the dual purpose of analyzing how citizens differ in their confidence in the government’s anti-corruption efforts and what factors influence their views. The findings indicate that citizens’ confidence in government control of corruption is affected by their perceptions of the level of existing corruption and by the extent to which they are satisfied with their government’s anti-corruption efforts. The findings also reveal that the public’s positive perceptions of anti-corruption performance moderate the negative impact that their perception of corruption has on their confidence in government control of corruption.

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Notes

  1. For example, according to the Corruption Perception Index of Transparency International in 2016, when our surveys were conducted, Mainland China was ranked 77 (scored 41), Taiwan 29 (scored 63), and Hong Kong 13 (scored 77).

  2. In the questionnaire for Changsha, we did not distinguish different levels of government (for example, central government and provincial government) because in Mainland China’s political setting, anti-corruption campaigns have always been carried out as a nationwide endeavor.

  3. The questions in Hong Kong and Changsha did not have “neutral” as an option. This may be a limitation for the data analysis. To take neutral as a response between “common” and “relatively few” is reasonable.

  4. In Tables 1, 2 and 3, models 1–4 employ the ordered logistic regression model and model 5 uses OLS regression. Although the Pseudo R2 values in models 1 through 4 in all tables are quite small, it does not necessarily indicate a low explanatory power of the model, because Pseudo R2 does not equal to R2 in OLS regression (Gujarati 2015). The R2 values in model 5 across the three cities range from 10 to 39%, suggesting a satisfactory model specification.

  5. It should be noted that these two explanatory variables were measured at the ordinal level and the coefficients should be interpreted with caution. By treating the explanatory variables as dummy variables, we reran models 1 and 2 in Tables 1, 2 and 3 and got similar results supporting Hypotheses 1 and 2.

  6. The results also demonstrate that multicollinearity is not serious between corruption perception and anti-corruption performance.

  7. After the mayor of Taipei City, Ko Wen-je, took office, he launched an investigation into his predecessor’s BOT development plan, which included the case of Yuanxiong big egg construction, the development case of Meihe City, the development case of Gemini, the development case of the Songyan cultural creative park, and the case of development for SYNTREND. Those cases have been referred to as “five major cases.” “Are five major cases serious? Ko rectify the five cases,” China Times, May 15, 2015.

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Acknowledgements

The work described in this article was supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Projects No. 11603219 and 11605917) and City University of Hong Kong (Project No. 7005144), and funds from the Department of Asian and Policies Studies at the Education University of Hong Kong.

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Authors and Affiliations

  1. Department of Asian and Policy Studies, The Education University of Hong Kong, HKSAR, China

    Hanyu Xiao

  2. Department of Public Policy, The City University of Hong Kong, HKSAR, China

    Ting Gong

  3. Department of Business Administration, Overseas Chinese University, Taichung, Taiwan

    Chilik Yu

  4. Department of Public Policy and Management, Shih Hsin University, Taipei, Taiwan

    Wen-Jong Juang

  5. Center for Corruption Studies, Hunan University, Changsha, China

    Baishun Yuan

  6. The Institute for Global Public Policy and School of International Relations and Public Affairs, Fudan University, Shanghai, China

    Ting Gong

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  1. Hanyu Xiao
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Correspondence to Ting Gong.

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Appendices

Appendix A

Descriptive statistics from the surveys in Hong Kong, Changsha, and Taipei.

Variable name

Variable code

Observations

Mean

S.D.

Min

Max

Hong Kong

Confidence in government control of corruption

Confidence_fu

911

2.73

0.97

1

5

Perceived corruption level

Corruption

950

2.47

0.74

1

4

Anti-corruption performance

Performance

933

2.52

0.77

1

4

Corruption experience

Co_experience

1025

0.15

0.44

0

2

Collaboration between government and business

Connection

949

0.56

0.50

0

1

Lack of anti-corruption effort

La_anticorruption

949

0.34

0.47

0

1

Lack of transparency

La_transparency

949

0.39

0.49

0

1

Individual greed

Greed

949

0.51

0.49

0

1

General level of tolerance for corruption

Tolerance

1022

1.24

2.32

0

10

Justifiability of corruption in a hypothetical situation

Justifiable

995

1.79

1.09

1

5

Age

Age

1006

52.02

17.32

18

93

Gender

Gender

1025

0.46

0.50

0

1

Level of education

Edu

1023

3.04

1.74

1

6

Income level

Income

990

2.89

2.15

1

7

Changsha

Confidence in government control of corruption

Confidence_fu

794

3.46

1.13

1

5

Perceived corruption level

Corruption

734

2.15

0.67

1

3

Anti-corruption performance

Performance

881

2.95

0.69

1

4

Corruption experience

Co_experience

925

0.63

0.81

0

2

Lack of rule of law

La_law

904

0.44

0.50

0

1

Lack of anti-corruption effort

La_anticorruption

904

0.42

0.49

0

1

Culture of connection

Culture

904

0.38

0.48

0

1

Lack of transparency

La_transparency

904

0.39

0.49

0

1

Level of tolerance for general corruption

Tolerance

918

1.18

2.06

0

10

Justifiability of corruption in a hypothetical situation

Justifiable

925

2.01

1.25

1

5

Age

Age

870

40.56

14.02

18

69

Gender

Gender

925

0.48

0.50

0

1

Level of education

Edu

890

3.45

1.32

1

6

Income level

Income

811

2.93

1.03

1

5

Taipei

Confidence in government control of corruption

Confidence_fu

875

3.49

0.97

1

5

Perceived corruption level

Corruption

773

3.16

1.25

1

5

Anti-corruption performance

Performance

930

3.42

0.72

1

5

General level of tolerance for corruption

Tolerance

1030

1.82

2.21

0

10

Age

Age

1021

50.34

15.83

18

84

Gender

Gender

1069

0.43

0.50

0

1

Level of education

Edu

1051

4.95

1.48

1

7

Income level

Income

937

4.82

2.67

1

9

Party affiliation

Party

1069

0.64

0.91

0

2

Appendix B

The marginal effects that perceived corruption exerted on anti-corruption confidence in Hong Kong, Changsha, and Taipei, with a 95% confidence interval.

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Xiao, H., Gong, T., Yu, C. et al. Citizens’ Confidence in Government Control of Corruption: An Empirical Analysis. Soc Indic Res 152, 877–897 (2020). https://doi.org/10.1007/s11205-020-02456-y

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