5th UK/Chevening Alumni of Indonesia & Timor-Leste Discussion Forum - Networking Event Series on: Towards Political Elections 2014 Does Corruption Pay in Indonesia? If So, Who are Benefited the Most?
Background Results Corruption in Indonesia Data & Model Anti Corruption Measures 2
Definition Corruption: illegal, immoral or dishonest behaviour, especially by people in positions of power (Cambridge Advanced Learner s Dictionary, 2003) The abuse of public power and influence for private ends (Waterbury,1973) An act in which the power of public office is used for personal gain in a manner that contravenes the rules of the game (Jain, 2001) Corruption includes Bowles (2000): Embezzlement Bribery Extortion Evolution of definition: In 1970s the definition of corruption was limited to public sector UN CAC 2003 acknowledge that corruption may include private sector. According to UN CAC 2003, money laundering also part of corruption and both of them are inseparable. Economic analysis of corruption (Rose- Ackerman, 1975, Bowles, 2000, Polinsky and Shavell, 2001, 2007 etc.). Police corruption (Bowles and Garoupa, 2005) 3
Debates on the Impact of Corruption Negative impact Corruption reduced government ability to regulate market, exacerbate poverty and indirectly reduce investment and earning from tax (Tanzi, 1998). Low level of corruption in a country may improve economic growth and investment in the country (Mauro, 1995). There has been a negative correlation between level of corruption and foreign direct investment in a country (Wei, 2000; Habib dan Zurawicki, 2002). Kuncoro (2004), Rivayani (2011): found that in Indonesia, there was a positive correlation between time spend with government officials and the amount of bribery Positive Impact Efficient grease hypothesis, Leff (1964), Meon and Weill (2005): Corruption might grease the economy in the country where the institution is ineffective. Entrepreneurs from high corruption countries tend to choose other high corruption countries as their destination for FDI (Cuervo-Cazzura, 2006). 4
Characteristics of Corruption Corruption is an extra ordinary crime (UN CAC) Victimless crime The impacts tend to be vast and enormous Corruption is part of organized crime It is difficult to do corruption without involving other parties Similar to other offences, corruption is like a tip of an iceberg Recorded corruption Unrecorded corruption In contrast to conventional offences, it may not be easy to estimate the unrecorded corruption Recorded Corruption Unrecorded Corruption 5
Conventional Offenders The majority come from low income and low education background (Einat, 2004) In many cases they offenced due to fulfilling necesities In many cases offenders were victims of bullying or crimes (Bowles & Pradiptyo, 2005) Offending behaviour is age sensitive (Bowles and Pradiptyo, 2005) The detection rate tend to be high Corruptors They come from high income and high education backgrounds The offending behaviour is not age sensitive The use of sophisticated techniques which may be difficult to prove it The use of power to prevent investigation The detection rate tend to be lower 6
Corruption and Money Laundering 7
Supre me court decisi on High court decisions District court decisions Police referal to prosecutor Police recording system Decision to report the incidence by victims From Offending to Conviction There are many steps that should be taken from offending incidence to conviction It may not be easy to tackle the unobserved heterogeneity owing to the process. Offending behaviour 8
Corruption and Courts Decisions All countries ratified UN CAC should established anti corruption measures: Anti Corruption Act Anti money laundering act Special court for corruption cases Anti corruption agency Anti money laundering agency A sound criminal justice system may reduce the level of corruption in a country (Lambsdorff, 2006). Is this applicable in Indonesia? 9
Background Results Corruption in Indonesia Data & Model Anti Corruption Measures 10
Corruption Perception Index China, 39 Thailand, 37 India, 36 Brunei Darussalam, 55 Malaysia, 49 Singapura, 87 Hong Kong, 77 3.5 3 2.5 2 CPI of Indonesia 1999-2011 1.9 1.9 1.9 1.9 1.9 2 2.2 2.4 2.3 2.6 2.8 2.8 3 Filipina, 34 Indonesia, 32 Vietnam, 31 Kamboja, 22 Laos, 21 Myanmar, 15 0 20 40 60 80 100 1.5 1 0.5 0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 11
Evolution of Corruption in Indonesia Corruption had been flourished during President Suharto s era Authoritarian regime with authoritarian system of government Bureaucrats were the major actor of corruption Post Suharto s era: Regional autonomy (decentralization) Corruptions spread out to regional level Power shifted from bureaucrats to politicians Many corruption involved high profiles politicians Bureaucrats no need politicians to commit corruption, but not vice versa. 12
Power Shifting Post Suharto s Era During Suharto s Regime Bureaucrats Judicary Politicians The process is reminiscence of English Civil War (1642-1651) Incompatibility between government structure and political system!! Post Suharto s Regime Politicians Judicary Bureaucrats 13
Engine: Colt T-120 Incompatibility System of Governance Body = Alphard 14
Complexity of Regulations in Indonesia Complexity No regulation on various aspect in life Some regulations have been designed without sound theoretical background Regulations without sanction Regulation with sanction, however the sanction is not credible Regulation with sanction, however the sanction cannot be enforced. Contoh The use of language in TV, how to handle hazardous goods (cigarette, etc), a lack of traffic sings on the road, etc. Fuel subsidy, budget optimization by Budgetary Council (Banggar) Political Party Act Anti Corruption Act, Forest replanting requirement, etc Retail fuel traders (bensin eceran) 15
The Advancement of Corruption Technique in Indonesia Corruption by members of public Pre Court Decision Police Corruption Pre Court Decision Makelar Kasus (case-broker) Makelar Kasus (casebroker) and Joki Napi (inmate-jockey) may only be found in Indonesia Corruption theory in Law and Economics Literature New Methods of Corruption Corruption by prosecutors and judges Court Decision Corruption in Prison Post Court Decision 16
24 Ways of Extortion in the Judicial System(Kompas, 2010) Police Prosecutor Judge Prison The existence of Markus (Makelar or Makelaar (Dutch) Kasus/ Case Broker) in Indonesia s judicial system Markus are inviduals who have extensive connection and influence in judicial system. They use various methods to change the decisions of the courts (obviously it entails bribery to corrupt officers) The impacts of the Markus: They increase error types I and II in court decisions Error type I: individuals who are guilty was sentenced free Error type II: inocence individuals are sentenced to serve punishment The credibility of CJA is questionable It promotes injustice to the poor or to those who are not wealthy enough to hire a Markus 17
One of the Major Sources of Makelar Kasus Anti Corruption Act Other Acts Is this merely an accidence or it has been designed on purpose? 18
Background Results Corruption in Indonesia Data & Model Anti Corruption Measures 19
Anti Corruption and Corruption Prevention Measures Anti Money Laundering Act (PPATK) 2003 & 2010 Bureaucratic Reformation(2003) Asset Recovery Draft Act (under review) Coruption Erradication Committee(KPK) 2004 Linking corruption and money laundering prosecution Anti Corruption Acts 1999 & 2001 Anti Corruption Programmes Social costs of corruption 20
KPK Multi-Institutions in Tackling Corruption Police Tackling Corruption Prosecutor Office KPK is an ad hoc institution consisting police and professionals. Ideally, KPK deals only with large scale corruption worth Rp 1 Billion ($100,000) or more In reality three insitutions may compete to handle high profile cases KPK has rights to intercept any phone and email communication without court consent. KPK is the only law enforcement agency which has prevention measures on corruption 21
UN Convention Against Corruption Bribery of national and foreign officials and in private sector Embezzlement in public and private sectors Trading of influence Abuse of function Ellicit enrichment Laundering of proceed of crime Concealment Obstruction of Justice Anti Corruptions Act Indonesia Anti Corruption Act Bribery of national officials and judicial officers Embezzlement in public sector Trading in influence Abuse of function Ellicit of enrichment 22
Coverage of Anti Corruption Act Covered by the Act Judiciary International Bodies Beyond the coverage of the Act Private Sector (national) Politicians Private Sector (International) Bureaucrats Corruption NGO 23
Definition of Corruptions According to the Anti Corruption Act Article 2 (Break of Law) Individual Or corporation - Against the law; - Aims to make him/herself or other parties or corporation richer Article 3 (Abuse of Power) - Abusing of the power, opportunity or facilities that entitle to a person owing to his/her positions; - Aims to make him/herself or other Source: Dr Haryono Umar (2009) parties or corporation richer Whom inflicted losses over economy or National budget 24 24
As Indonesia follows continental penal law, all punishments and their intensities should be stated explicitly Indonesia penal law follows the Dutch penal law 1811 The Dutch abolised the code in 1994, but Indonesia has been implementing the code until now Inflation rate in Indonesia is quite high (from 2000-2009 the inflation rate reached 100%) Any value of fines in 1999 only worth 50% from the original value (the deterrence effect is questionable) Complexity The Act does not cover the proceed of crime/ crime post corruption (money laundering, etc) The Act does not cover corruption in a broader sense: Money politic (KUHP 148-150) General election for senators (Act no 12/2003) General election for President (Act no 23/2003) Bribery Act no 11/1980 The Act does not cover corruption conducted by private sector or international bodies in Indonesia 25
Punishment in Anti Corruptions Act Chapter Costs of Corruptions Ch 5 Rp5 million Rp Ch 6 Rp5 million Rp Ch 8 Rp5 million Rp Types of Corruptions Maximum Fines Maximum Imprisonm ent Bribery to civil servants Rp50 million Rp250 million Bribery to judges, prosecutors and judicial staff Embezzlement by Civil Servants Rp150 million Rp750 million Rp150 million Rp750 million 1-5 years 3-15 years 3-15 years Ch 12 Rp5 million Rp Corruptions by Civil Servants Rp200 million Rp 1 billion 4-20 years 26
Appeal System in Indonesia Judicial Review 27
Background Results Corruption in Indonesia Data & Model Anti Corruption Measures 28
PDF Database of Corruption Excel Court Decisions The Supreme Court and KPK Corruption Cases Database of Corruption 1282 cases, 1831 defendants Statistical Softwares This type of database is quite rare in the world The initial version was based on 2001-2009 the Supreme Court s decisions with 549 cases and 831 defendants. The updated version is based on the Supreme Court s decision and KPK s cases from 2001-2012 (1289 cases and 1831 defendants) 29
Classification of Defendants/Offenders Data set consists of 1289 cases, involving 1831 defendants Divided into 5 scales of corruptions Petty [$0,$1000) Small [$1000, $10,000) Medium [$10,000, $100,000) Large [$100,000, $2.5million) Grand [$2.5million, ] 30
Supre me court decisi on High court decisions District court decisions Police referal to prosecutor Police recording system Decision to report the incidence by victims Offending behaviour Caveats of the Database There are many steps that should be taken from offending incidence to conviction The data suffers from unobserved heterogeneity All cases from the Supreme Court were appealed until the Supreme Court Some cases from KPK were terminated either in district courts or high courts. Some of them were appealed to the Supreme Court 31
Given corruption is an extra ordinary crime, do corruptors had been sentenced extra ordinarily? What are factors attributable to the sentencing options chose by judges across different level of courts Do judges thought about minimising social welfare loss when sentencing offenders in corruption cases? Problems Under Indonesia criminal justice system, police, KPK and prosecutor have to follow the guidance of sentencing (in this case anti corruption act). Judges decisions may not be bounded to type and intensity of sentencing options prosecuted or sentenced by lower level of courts. Example: AS were sentenced for 4 years and 6 months imprisonment and 1 million fines by both district and high courts. The supreme court, however, sentenced her: 12 years imprisonment, fines Rp1 billion and compensation order of Rp12.58 billion and $2.35 million!!! 32
Model Various studies on corruption suggested that the optimum deterrence effect emerges by conducting asset confiscation (Rose-Ackerman, 1975, Bowles, 2000, Polinsky and Shavell, 2001, 2007, Bowles and Garoupa, 2004) Becker (1968)the optimum deterrence effect determined by: Detection rate The intensity of punishment Hypothesis: The probability and intensity of punishment = f(cost of corruption) Logistic Regressions: The probability of sentencing a particular punishment = f(age, cost of corruption, gender, dummies of region, dummies of occupation, dummies of scale of corruption, KPK, Police and Prosecutor Post KPK) TOBIT (Tobin s Logistic) Regressions: The intensity of punishment = f(age, cost of corruption, gender, dummies of region, dummies of occupation, dummies of scale of corruption, KPK, Police and Prosecutor Post KPK) 33
Sentencing Options The majority of court s disposals tend to be conventional Little attempts have been done to discover innovatives sentencing options as in developed countries Sentencing options: a) imprisonment; b) fines; c) subsidiary of fines; d) compensation order; e) subsidiary of compensation order; f) parole; g) confiscation of evidence 34
District Court High Court Supreme Court Judicial Review Level of Analysis 1. All defendants Probability of being guilty (exploratory exercise) 2. All offenders Probability of sentencing option Role of prosecutors Intensity of sentencing option Role of prosecutors 3. All cases which were appealed to the Supreme Court Probability of sentencing option Role of district courts sentence Role of judicial review Intensity of sentencing option Role of district courts sentence Role of judicial review 35
Background Results Corruption in Indonesia Data & Model Anti Corruption Measures 36
Distribution of Offenders by Gender & Scale of Corruption 700 600 572 406, 22% 500 400 300 298 347 1425, 78% 200 100 0 42 32 46 69 1 18 0 Petty Small Medium Large Grand Guilty Not Guilty Female Male 37
Age Group Distribution of Offenders Based on Age-Group and Occupation Petty Small Medium Large Grand < 30 1 7 10 1 1 30 39 9 78 97 38 5 40 49 17 132 234 127 12 50 59 15 94 213 142 29 60+ 1 17 60 56 22 Total 43 328 614 364 69 Job Petty Small Medium Large Grand Civil Servant 24 179 279 128 15 SOE 2 11 36 45 14 MP 1 60 163 114 10 Indept. Body 0 0 8 4 10 Private Sector 16 80 132 74 20 38
Distribution of Offenders Based on Region Petty Small Medium Large Grand Greater Jakarta 4 11 43 110 41 Jawa others 11 92 216 93 6 Sumatera 15 95 168 47 5 Kalimantan 2 18 46 42 12 Sulawesi 7 71 80 53 2 Bali & NT 3 27 32 10 1 Maluku & Papua 1 16 33 10 2 39
Explicit Cost vs Financial Punishment (current price) Scale of Corruptions Number of Offenders Explicit Cost of Corruptions [A] Total Financial Punishment Sentenced [B] B:A (%) Petty 43 $19,723 $281,895 1429.30% Small 330 $1.58 million $2,16 million 137.01% Medium 618 $23.37 million $18.90 million 80.86% Large 365 $165.53 million $69.60 million 42.04% Grand 69 $6,176.45 million $570.67 million 9.24% Total 1425 $6,367 million $661.61 million 10.39% 40
Explicit Cost vs Financial Punishment (constant price 2012) Scale of Corruptions Number of Offenders Explicit Cost of Corruptions [A] Total Financial Punishment Sentenced [B] B:A (%) Petty 43 $37,421 $508,808 1359.69% Small 330 $2.73 million $3.59 million 131.50% Medium 618 $41.16 million $32.32 million 78.52% Large 365 $286.54 million $131.99 million 46.06% Grand 69 $16,363.79 million $1,393.12 million 8.51% Total 1425 $16,694.25 million $1,561.53 million 9.35% 41
Length of Imprisonment Sentenced Scale of Corruption Number of Offenders Average Explicit Cost of Corruption Length of Imprisonment Prosecuted (month) [A] Length of Imprisonment Sentenced (month) [B] B/A (%) Petty 43 $458.7 27.53 18.79 68.24% Small 330 $4,784.6 22.53 15.71 69.72% Medium 618 $37,814.7 40.28 26.36 65.44% Large 365 $453,518.5 59.50 38.44 64.60% Grand 69 $89,513,797.7 102.58 67.22 65.53% 42
Prison or 5* Hotel??? This result was based on courts decisions, however the actual length of imprisonment is between 50%- 60% of the sentencing. In many cases, offenders may bribe the prison officers to get special treatments, ranging from having a good meal to having transformed several rooms in prison to be private office and private bedroom with 5 star hotel facilities. In many cases offenders may bribe prison officers to go out from prison and event have a holiday abroad. 43
Explicit Cost vs Financial Punishment in District and the Supreme Courts Scale of Corruption Petty Small Medium Large Grand Avg. corruption (A) $486 $4,811 $36,474 $494,056 $51,010,558 Avg. fin. punishment prosecuted (B) $9,315 $9,358 $43,827 $274,666 $45,210,531 B/A (%) 1915.79% 194.52% 120.16% 55.59% 88.63% Avg. fin. punishment sentenced by DCs (C) $7,565 $6,342 $29,018 $174,704 $5,798,377 C/A (%) 1555.90% 131.83% 79.56% 35.36% 11.37% Avg. fin. punishment sentenced by SC (D) $6,743 $5,896 $28,759 $189,610 $6,444,138 D/A (%) 1386.78% 122.55% 78.85% 38.38% 12.63% 44
Probability of Conviction All Observations District Courts The Supreme Court Marginal Prob. Marginal Effect Prob. Marginal Effect Prob. Effect Age -0.001 0.317 0 0.704-0.001 0.315 Ln(exp_cost) 0.005 0.653-0.008 0.576 0.011 0.372 Gender 0.007 0.842-0.005 0.901 0.015 0.691 D_greaterJKT 0.051 0.206 0.01 0.833 0.042 0.304 D_Jawa_else 0.02 0.429-0.014 0.653 0.027 0.286 D_Kalimantan 0.12 0.002*** 0.02 0.674 0.12 0.001*** D_Sulawesi -0.021 0.466-0.234 0*** 0.064 0.02** D_Bali&NT -0.201 0*** -0.332 0*** -0.07 0.081* D_Maluku&Papua -0.011 0.816-0.19 0.001*** 0.058 0.173 D_SOE 0.047 0.217 0.026 0.553 0.047 0.226 D_Politician -0.043 0.076* -0.027 0.318-0.042 0.093* D_Indept_Body 0.032 0.747 0.137 0.211-0.025 0.815 D_Private 0.019 0.456 0.056 0.046** -0.004 0.884 D_Petty -0.06 0.438-0.111 0.233-0.013 0.864 D_Small 0 1-0.097 0.018** 0.041 0.208 D_Large -0.049 0.193-0.078 0.069* -0.015 0.691 D_Grand -0.153 0.16-0.167 0.148-0.086 0.43 D_P&P_Post_KPK 0.038 0.121 0.05 0.08* 0.025 0.325 D_KPK 0.199 0*** 0.306 0*** 0.076 0.337 DC_Guilty 0.398 0*** D_JudicialReview 0.026 0.406 Cons 0.641 0.167 45 0.367
Corruption cases in Kalimantan are more likely to be convicted than those of in Sumatera Corruption cases in Bali & Nusa Tenggara and in Maluku & Papua are less likely to be convicted than those of in Sumatera In district court level, small and large corruptors are less likely to be convicted than medium corruptors General Conviction Corruption cases prosecuted by KPK are more likely to be convicted There is evidence of improvement (weakly significant) of Police and Prosecutor performance in district court level 46
Length of Imprisonment Length of Imprisonment All offenders Supreme Court s decisions Coef. Prob Coef. Prob Age 0.052 0.337 0.0486 0.324 Ln(exp_cost) -0.5786 0.342 0.4501 0.456 Gender -0.0564 0.976 1.3078 0.46 D_greaterJKT -1.9058 0.312-2.7336 0.141 D_Jawa_else 0.0907 0.944-3.8498 0.001*** D_Kalimantan -4.0671 0.032** -4.1897 0.015*** D_Sulawesi 3.334 0.031** 4.0071 0.01*** D_Bali&NT 1.0389 0.644 2.8768 0.174 D_Maluku&Papua 2.4946 0.299-1.6551 0.467 D_SOE -1.0922 0.56 1.4065 0.418 D_Politician -0.1813 0.88 0.7375 0.547 D_Indept_Body 0.8215 0.835-4.9611 0.176 D_Private 1.2208 0.319 1.7796 0.114 D_Petty -2.9837 0.44-2.2976 0.514 D_Small -2.231 0.186-3.0665 0.059* D_Large 2.5567 0.153 1.3548 0.444 D_Grand 9.0619 0.03** 2.0186 0.615 D_P&P_Post_KPK -0.0864 0.946-0.6746 0.57 D_KPK 9.2979 0*** 8.3018 0.001*** DA_PrisonL 0.5383 0*** DC_PrisonL 0.8421 0*** D_JudicialReview 2.5487 0.069* Cons 12.7053 0.299-4.9455 47 0.682
Imprisonment In every level of court, all offenders were sentenced with imprisonment Thus far there is no evidence on the effectiveness of imprisonment in Indonesia Offenders in Kalimantan and Jawa-else received shorter imprisonment period than those of in Sumatera, in contrast to offenders in Sulawesi. Idealized length of imprisonment: Grand>Large>Medium>Small>Petty Finding: Grand > Large = Medium = Petty > Small Grand corruptors received longer imprisonment in district court level than their medium counterparts Small corruptors received shorter imprisonment than their medium counterparts. Offenders prosecuted by KPK received significantly longer period of imprisonment than other offenders prosecuted by Police and Prosecutor The probability and length of imprisonment in the Supreme Court level has positive correlation with probability and length of imprisonment 48
Fines Probability and intensity of fines All Cases Appealed Cases to the Supreme Court Probability of Fines Intensity of Fines Probability of Fines Intensity of Fines ME Prob Coef. Prob ME Prob Coef. Prob Age 0.0006 0.491 453923.2 0.151 0.0006 0.412 1130653 0.061* Ln(exp_cost) 0.0281 0.008*** 3605519 0.298-0.0026 0.793 6586476 0.366 Gender 0.0402 0.171 1.79E+07 0.101-0.0045 0.855 1.42E+07 0.513 D_greaterJKT -0.0919 0.027** -4.70E+07 0*** -0.0651 0.086* -5.35E+07 0.019** D_Jawa_else 0.0082 0.648-6219944 0.409 0.0307 0.054* -1.13E+07 0.426 D_Kalimantan 0.05 0.08* 4302534 0.693 0.0369 0.154 5197176 0.802 D_Sulawesi 0.0444 0.025** 555066.4 0.951 0.0109 0.609 1068986 0.955 D_Bali&NT 0.064 0.016** 823167 0.949 0.0201 0.422 2.71E+07 0.289 D_Maluku&Papua 0.0246 0.45-6678731 0.632-0.0581 0.143-1.02E+07 0.71 D_SOE 0.0216 0.499 7627904 0.479 0.0291 0.226 2.62E+07 0.212 D_Politician -0.0079 0.684-1.64E+07 0.019** 0.0194 0.268-7268266 0.626 D_Indept_Body -0.2356 0.025-7426909 0.748-0.0957 0.197-1.79E+07 0.697 D_Private 0.0226 0.212 1.03E+07 0.146 0.0142 0.365 5.08E+07 0*** D_Petty -0.0385 0.549-1.04E+07 0.653-0.1679 0.09* -4.37E+07 0.32 D_Small -0.0664 0.027** -5282554 0.592-0.0934 0.005*** -4.12E+07 0.039** D_Large -0.0063 0.864-1.04E+07 0.312 0.0553 0.03** -1.15E+07 0.589 D_Grand -0.0022 0.984-4.80E+07 0.046** 0.0502 0.218-3.77E+07 0.434 D_P&P_Post_KPK 0.0247 0.22 7089108 0.346 0.0209 0.248 6147315 0.673 D_KPK 7027673 0.526 1.32E+08 0*** DA_FineYN 0.0707 0*** DA_FineQ 0.9372467 0*** DC_fineYN 0.6533 0*** DC_fineQ 0.8556726 0*** D_JudicialReview -0.0731 0.01*** 1.84E+07 49 0.284 Cons 0.021-1.27E+08 0.072 0.81-1.99E+08 0.173
Compensation Order All Offenders All Cases Appealed to the Supreme Court ME Prob Coef. Prob ME Prob Coef. Prob Age -0.0003 0.879-0.0019 0.72-0.0029 0.299 0.0018 0.773 Ln(exp_cost) -0.0302 0.185 0.5968 0*** 0.0555 0.101 0.7135 0*** Gender 0.0454 0.519 0.0925 0.626-0.0396 0.688 0.0181 0.934 D_greaterJKT -0.16 0.023** 0.1054 0.601-0.2335 0.035** -0.0324 0.891 D_Jawa_else 0.0641 0.196-0.2263 0.076* -0.0124 0.852-0.2518 0.091* D_Kalimantan -0.1259 0.077* -0.5981 0.004*** -0.2013 0.049** -0.7048 0.003*** D_Sulawesi 0.0514 0.388-0.2455 0.108 0.0611 0.493-0.1717 0.366 D_Bali&NT -0.0244 0.772 0.0008 0.997-0.0426 0.719-0.0866 0.746 D_Maluku&Papua 0.157 0.109 0.0831 0.726 0.0744 0.56 0.0837 0.757 D_SOE 0.1866 0.004*** -0.098 0.584 0.0508 0.591-0.0973 0.641 D_Politician 0.2894 0*** -0.3784 0.002*** 0.191 0.003*** -0.2454 0.103 D_Indept_Body -0.1468 0.305 0.1257 0.816-0.2038 0.317 0.1028 0.868 D_Private 0.2651 0*** 0.2247 0.063* 0.1114 0.069* 0.205 0.135 D_Petty -0.2527 0.073* -0.057 0.892 0.1243 0.489 0.5668 0.246 D_Small -0.0686 0.298-0.5183 0.003*** 0.0809 0.363-0.3183 0.127 D_Large 0.0751 0.274-0.0442 0.809-0.0395 0.699-0.13 0.568 D_Grand 0.1353 0.386 0.8577 0.04** 0.0288 0.898 0.7058 0.14 D_P&P_Post_KPK -0.046 0.344 0.6631 0.001*** -0.0034 0.959-0.2857 0.054* D_KPK 0.1781 0.02** -0.3248 0.008*** -0.0395 0.775 0.504 0.027** DA_COYN 0.7045 0*** DA_COQ 0 0*** DC_COYN 0.8013 0*** DC_COQ 0 0.009*** 50 JR_YN -0.0611 0.463-0.2246 0.191
Fines at SC Idealised Intensity of Fines Grand > Large > Medium > Small > Petty Idealised Probability of Fines Grand > Large > Medium > Small > Petty Intensity of Fines (finding) Grand = Large = Medium = Petty > Small Probability of Fines (finding) Large > Grand = Medium > Petty > Small Compensation Order at SC Idealized Intensity of Compensation Order Grand > Large > Medium > Small > Petty Idealized Probability of Compensation Order Grand > Large > Medium > Small > Petty Intensity of Compensation Order (finding) Grand > Large = Medium = Petty > Small Probability of Compensation Order (finding) Grand = Large = Medium = Small > Petty 51
The total explicit cost of corruption was $16,764 million, however the total financial punishment was $1,561 million (9.35%) Who will pay the excess burden of corruption worth $16,764 million - $1,561 million = $15,203 million? Obviously it is the burden for tax payers. The finding shows that in Indonesia the corruptors have been subsidised by Indonesian people, who tragically are poorer than the corruptors Conclusions Prosecutors and Judges tend to be harser toward petty, small and medium corruptors The probabilities and intensities of receiving punishments do not depend on the social cost of corruptions The deterrence effect of the punishments are questionable Prosecutors and judges have created burden to tax payers as they tend to be lenienced toward large and grand scales of corruptors 52
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