Transparency at Work:

Monitoring Corruption with the Government Integrity Index System Lung-Teng Hu, Ph.D.

Assistant Professor Department of Public Policy and Management Shih Hsin University Taipei, Taiwan Director of Knowledge Management TI-Chinese Taipei

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4 Dimensions 13 Constructs 27 Indicators

Objective Indicators & Subjective Indicators 23 municipalities & counties

2

Structure of Government Integrity Index (GII)

4 Dimensions

Input Process Output Impact

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Structure of Government Integrity Index (GII)

13 Constructs

Input

Human Resources Budget Law and Regulations

Process

Procurement Anti-Corruption Audit Public Education on Anti-Corruption

4

Structure of Government Integrity Index (GII)

Output

Complaints Disclosure Misconduct Law Breaking

Impact

Media Report Staff Perception Public Opinion

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Structure of Government Integrity Index (GII)

Government Integrity Index

Objective Indicators

Input Index Output Index Impact Index

Subjective Indicators

Human Resources Budget Law and Regulations Procurement Public education on anti- corruption Complaints Disclosure Misconduct Law Breaking Media report Staff perception Public opinion 6

Structure of Government Integrity Index (GII)



Objective Indicators

: come from official statistics



Subjective Indicators

: come from two surveys •

Public opinion telephone survey

Public Opinion Survey) (hereafter

•

Staff mailing survey

(hereafter Staff Survey) 7

Operationalization of GII Stage 1



Standardization :

from original statistics to standardized Z scores.



Normalization :

multiply each standardized Z score by -1, if necessary • If the statistics look neutral, use their correlations with public opinion survey results to determine the directions 8

Operationalization of GII Stage 2



Combining

normalized standardized scores into sub-dimension scores.

• Weighting method: (1) using consensus by Delphic method, or (2) performing factor analysis for each sub-dimension extract only the first factor then using regression method to get weights 9

Operationalization of GII Stage 3



Combining

sub-dimension scores into dimension scores.

Weighting method: (1) using consensus by Delphic method, or (2) performing factor analysis for each dimension 

Dimension score adjustment

transformation, using linear • SAx = 70 + (10*Sx) 10

Operationalization of GII Stage 4



Combining

dimension scores into final index.

Weighting method: (1) using consensus by Delphic method, or (2) performing factor analysis on six dimension scores 

Final index adjustment

using linear transformation GII = 70 + (10*FI) 11

Features of GII Results

 We have finished our

Beta Version

data from 23 municipalities/counties of GII with • We are working on the second round data collection 

Grouping

rather than ranking

comparison technique

by

multiple

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Citizens’ Assessment on Governmental Integrity in General

40% 30% 20% 10% 0% -10% -20% -30% -40% 0 新竹市 嘉義縣 臺中市 桃園縣 花蓮縣 南投縣 嘉義市 高雄縣 澎湖縣 宜蘭縣 彰化縣 臺南市 新竹縣 臺東縣 屏東縣 苗栗縣 雲林縣 臺南縣 臺中縣 臺北市 臺北縣 高雄市 1 基隆市 2 13

Citizens’ Assessment on Magistrates/Mayors’ Integrity

75% 55% 35% 15% 臺中市 高雄縣 桃園縣 嘉義市 屏東縣 高雄市 新竹市 臺北市 澎湖縣 臺中縣 彰化縣 花蓮縣 雲林縣 宜蘭縣 臺北縣 南投縣 臺東縣 臺南市 臺南縣 苗栗縣 嘉義縣 新竹縣 -5% -25% -45% 0 1 基隆市 2 14

Citizens’ Assessment on Department Chiefs’ Integrity

40% 35% 30% 25% 20% 15% 澎湖縣 宜蘭縣 屏東縣 苗栗縣 臺中縣 彰化縣 新竹市 花蓮縣 嘉義市 臺中市 臺東縣 嘉義縣 高雄縣 桃園縣 新竹縣 臺南市 南投縣 臺北市 臺南縣 臺北縣 雲林縣 10% 5% 0 1 高雄市 基隆市 2 15

Citizens’ Assessment on Public Employees’ Integrity

60% 55% 澎湖縣 新竹縣 宜蘭縣 新竹市 嘉義市 花蓮縣 臺中市 臺南市 50% 45% 嘉義縣 臺中縣 桃園縣 臺南縣 臺東縣 臺北市 彰化縣 高雄縣 屏東縣 南投縣 苗栗縣 基隆市 臺北縣 雲林縣 40% 高雄市 35% 0 1 2 16

85 75 65 55 0

Final Scores in GII Beta Version

嘉義市, 85.7

新竹市, 84.5

澎湖縣, 81.4

屏東縣, 81.2

花蓮縣, 79.8

臺中市, 77.2

嘉義縣, 73.2

臺北市, 70.1

桃園縣, 74.3

高雄縣, 73.6

彰化縣, 72.7

苗栗縣, 71.9

臺東縣, 70.3

宜蘭縣, 69.6

臺中縣, 67.1

新竹縣, 66.8

臺南縣, 65.4

雲林縣, 63.9

南投縣, 62.4

臺南市, 61.1

臺北縣, 60 高雄市, 57.2

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Why grouping?

Think about this… If the score difference between the Last No.4 city/country and the Last No.3 is

50

, while the difference between the Last No.2 and the Last No.1 is

0.5

…

Can we say this ranking is fair??

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Conclusions

 We believe that

•

Using grouping technique rather than ranking method has some advantages: •

taking the concept of “variation” into account,

•

making the assessment results are fairer and more acceptable,

•

minimizing the emotional overreaction or critique from the evaluated objects.

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Conclusions Who has been involved in the GII measurement?



Directly involved:

• Citizens • Public employees 

Indirectly involved:

• • The media (by news reports/coverage) Governments themselves (by official statistics input) 20

Conclusions



Impacts:

• Educating public officials that corruption/integrity can be measured.

• • Promoting the idea of “indicator management” to government-wide Department of Government Ethics.



Challenges:

• Requesting agencies to collect needed data regularly.

Responding rate of staff survey is quite low, probably due to the sensitivity of the issue.

• Need to prevent from the systematic bias occurring from specific departments/local governments.

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