Correction equations for corruption

Correction equations for corruption–perception equations

Institution
---
Parameter

Central
Goverment

Local
Goverment

Juridical
Institutions

Inspections

Police

Army

Educational
Establishm.

Medical
Establishm.

State TV

Privatization
Authorities

Banks

Constant

-0.25

-0.71^b

-0.48^c

-0.15

-0.14

-0.64^b

-0.84^a

-0.68^b

0.15

-0.15

-0.33

[.350]

[.010]

[.073]

[.555]

[.585]

[.014]

[.004]

[.017]

[.562]

[.558]

[.200]

Age

-0.01

0.00

-0.01

-0.02

0.00

0.01

[.420]

[.395]

[.540]

[.410]

[.438]

[.786]

[.312]

[.122]

[.856]

[.979]

[.301]

Age square

0.00

0.00^c

0.00^b

0.00

0.00^b

0.00

[.197]

[.101]

[.138]

[.053]

[.048]

[.217]

[.017]

[.021]

[.563]

[.698]

[.766]

Education 2

-0.33^c

-0.20

-0.28

-0.25

-0.24

-0.19

-0.14

-0.12

-0.13

-0.11

-0.14

[.060]

[.256]

[.108]

[.170]

[.181]

[.271]

[.414]

[.481]

[.499]

[.548]

[.423]

Education 3

-0.44^a

-0.19

-0.27

-0.35^b

-0.38^b

-0.31^c

-0.29^c

-0.27

-0.29

-0.26

-0.18

[.008]

[.269]

[.110]

[.043]

[.029]

[.067]

[.089]

[.110]

[.109]

[.119]

[.280]

Education 4

-0.68^a

-0.34

-0.13

-0.06

-0.10

-0.26

-0.52^b

-0.09

-0.43^c

-0.36

[.003]

[.137]

[.571]

[.796]

[.655]

[.249]

[.271]

[.038]

[.707]

[.053]

[.105]

Education 5

-0.61^a

-0.43^a

-0.39^b

-0.40^b

-0.31^c

-0.40^b

-0.37^b

-0.20

-0.44^a

-0.32^c

[.000]

[.009]

[.017]

[.020]

[.017]

[.063]

[.016]

[.027]

[.254]

[.007]

[.056]

Education 6

-0.61^a

-0.53^a

-0.35^c

-0.49^b

-0.43^b

-0.39^b

-0.44^b

-0.49^b

-0.32

-0.59^a

-0.38^b

[.002]

[.008]

[.073]

[.013]

[.027]

[.042]

[.030]

[.017]

[.107]

[.002]

[.045]

Education 7

-0.75^a

-0.63^a

-0.70^a

-0.72^a

-0.74^a

-0.50^a

-0.61^a

-0.60^a

-0.44^a

-0.73^a

-0.59^a

[.000]

[.002]

[.000]

[.013]

[.000]

Education 8

-0.76^a

-0.49^b

-0.50^b

-0.72^a

-0.71^a

-0.34

-0.62^b

-0.52^b

-0.43^c

-0.49^b

-0.34

[.001]

[.043]

[.033]

[.002]

[.003]

[.134]

[.017]

[.038]

[.067]

[.030]

[.131]

Education 9

-0.67^a

-0.50^a

-0.53^a

-0.65^a

-0.67^a

-0.51^a

-0.59^a

-0.47^a

-0.52^a

-0.81^a

-0.69^a

[.000]

[.003]

[.001]

[.000]

[.002]

[.001]

[.006]

[.004]

[.000]

Gender

0.21^a

0.23^a

0.13^b

0.16^a

0.30^a

0.16^b

0.19^a

0.13^b

0.17^a

0.14^b

[.001]

[.000]

[.037]

[.008]

[.006]

[.000]

[.016]

[.005]

[.019]

[.003]

[.016]

Number
of observations

2097

R²

0.04

0.05

0.07

0.05

0.08

0.05

0.03

0.05

0.04

Fraction of
Correct
Predictions

0.70

0.77

0.73

0.65

0.64

0.65

0.80

0.81

0.60

0.64

0.60

Mean for
dep. var.

0.30

0.24

0.27

0.39

0.40

0.37

0.20

0.19

0.60

0.39

0.44

χ² (chi²)

2.31¹

1.77

1.80

3.02^c

0.12

8.11^a

4.24^b

0.25

13.28^a

159.67^a

76.44^a

P-value

[0.12]

[0.18]

[0.17]

[0.08]

0.73

[0.00]

[0.04]

[0.62]

[0.00]

P-values are in parenthesis. ^a – significant on 1% level, ^b– significant on 5% level, ^c – significant on 10% level

Dependent variable is equal to one if at least one of the variables present in the main equation contains missing observation and zero otherwise.

¹H₀: p₁₂=p₂₁, i.e. probits are not better estimates than naive estimates.