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Is corruption good for your health?

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Presentation by Guilherme Lichand "Is corruption good for your health?" at the SITE Corruption Conference, 31 August 2015.

Find more at: https://www.hhs.se/site

Published in: Economy & Finance
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Is corruption good for your health?

  1. 1. Is  corrup)on  good  for  your   health?   Guilherme  Lichand    Marcos  Lopes      Marcelo  Medeiros                      Harvard  University                        CEPESP/FGV                            PUC-­‐Rio       FighBng  CorrupBon  in  Developing  and  TransiBon  Countries  –  SITE  Conference,  September,  1st    
  2. 2. Every   dollar   that   a   corrupt   official   or   a   corrupt   business   person  puts  in  their  pocket  is   a   dollar   stolen   from   a   pregnant   woman   who   needs   health  care.       In   the   developing   world,   corrup&on   is   public   enemy   number  1”   “  
  3. 3. Even   in   the   case   of   peQy   bribery   or   extorBon,   it   is   relevant   to   ask,   what   is   the   alterna&ve?”   “  
  4. 4. What  are  the  causal  effects  of  corrup)on? •  Experiments:   •  Bertrand,   Djankov,   Hanna   and   Mullainathan   (2004);   Zamboni   and   Litschig   (2013)   •  Natural  experiments:   •  Reinikka  and  Svensson  (2004);  DiTella  and  Schargrodsky  (2003)  
  5. 5. This  paper •  Assesses  the  impacts  of  the  introducBon  of  a  random-­‐audits  program   in  Brazil  on  the  incidence  of  corrupBon  within  Health  transfers;   •  Assesses  how  such  impacts  were  transmiQed  to  Health  outputs  and   outcomes.  
  6. 6. Preview  of  findings •  Random-­‐audits   program   significantly   reduced   procurement   problems;   •  Outputs  and  outcomes  become  worse.   •  Mismanagement   increased   one-­‐to-­‐one   with   the   decrease   in   corrupBon.   •  Sharp   decrease   in   spending   points   to   procurement   staff   being   paralyzed  by  the  risk  of  misprocuring.  
  7. 7. Audit  reports [Ghost   firm]   “When   evalua+ng   the   procurement   process   to   purchase   two   mobile   health   units   in   2002   by   the   municipal   government   of   Dourados,  auditors  found  evidence  of  fraud.  The  only  public  outbidder,   Santa   Maria   Comércio   e   Representações   Ltda.,   did   not   legally   exist   according   to   the   local   branch   of   the   Federal   Revenue   Secretariat   in   Cuiabá,  State  of  Mato  Grosso  do  Sul.  Despite  this  fact,  the  municipal   government   has   concluded   the   public   bid   and   paid   the   company   the   agreed-­‐upon  amount.”  
  8. 8. Audit  reports [Over-­‐invoicing]  “When  analyzing  a  procurement  process  to  purchase   medical   supplies   in   2004,   auditors   found   that   the   municipal   government  of  Poloni  had  paid  higher  prices  for  medica+on  than  the   one   agreed   upon   the   public-­‐bid   contract.   For   example,   according   to   receipt  number  115655  (Procurement  number  2004/01696),  the  correct   price  150  mg  of  the  medica+on  Rani+dine  was  R$  0.18  per  tablet,  but   the  municipality  paid  R$  0.28  per  tablet.  No  further  documenta+on  was   presented   by   the   municipal   government,   and   the   outbidder   Empresa   Soquímica  Laboratórios  Ltda.  embezzled  the  resources.”  
  9. 9. What  is  corrup)on? Table A1 – List of irregularities Panel A: Corruption Category Irregularity Procurement Irregular receipts Procurement Evidence for ghost firms Procurement Contracts not signed or falsified signatures Procurement Favored vendor Procurement Lack of publicity Procurement Documents set with different dates Procurement Other procurement problems Procurement Irregular class Procurement No realization Resource diversion Over-invoicing Resource diversion Off-the-record invoice  
  10. 10. Timeline
  11. 11. Challenges •  An  anB-­‐corrupBon  program,  right  at  the  mid-­‐point  of  mayors’  term,   but…   •  What  about  pre-­‐treatment  data?   •  What  about  a  control  group?   •  Novel  dataset  with:   •  Pre-­‐treatment  data:   •  Auditors  follow  transfers’  paper  trail,  usually  3  years  (but  someBmes  more)  prior  to  the   Bme  of  the  audit.   •  Very  detailed  informaBon  about  each  transfer:   •  In  parBcular,  extent  to  which  there  are  heterogeneous  opportuniBes  for  embezzlement.  
  12. 12. Procurement-­‐intensity •  We   code   the   share   of   acBons   listed   under   Health   Ministry’s   descripBon  of  the  transfer  involving  procurement-­‐related  terms,  such   as:   •  AcquisiBon;   •  Purchase;   •  ModernizaBon;   •  Enlargement;   •  ConstrucBon.   •  High   procurement-­‐intensity   transfers   have   higher   opportuniBes   for   embezzlement.  
  13. 13. Differences-­‐in-­‐differences Corruption Low High Difference [Low - High]procurement- intensity procurement- intensity Before 2003 0.17 0.37 -0.19*** [0.02] [0.03] [0.04] After 2003 0.12 0.12 0.00 [0.01] [0.01] [0.01] Difference [Before - After] 0.05** 0.25*** -0.20*** [0.03] [0.03] (0.03)  
  14. 14. Iden)fica)on  assump)on •  Iden&cal  poten&al  (reported)  outcomes   •  Sufficient  condiBons:   Ø   Parallel  trends  (between  treatment  and  control)  for  actual  outcomes;   Ø   Parallel  trends  for  misreporBng  by  auditors  for  reported  outcomes.  
  15. 15. Corrup)on:  Before  vs.  aFer 18.2%   22.3%   21.6%   37.1%   28.0%   30.6%   14.1%   12.3%   14.3%   15.2%   12.1%   0.0%   5.0%   10.0%   15.0%   20.0%   25.0%   30.0%   35.0%   40.0%   1997   1998   1999   2000   2001   2002   2003   2004   2005   2006   2007  
  16. 16. Differences-­‐in-­‐differences Corruption Low High Difference [Low - High]procurement- intensity procurement- intensity Before 2003 0.17 0.37 -0.19*** [0.02] [0.03] [0.04] After 2003 0.12 0.12 0.00 [0.01] [0.01] [0.01] Difference [Before - After] 0.05** 0.25*** -0.20*** [0.03] [0.03] (0.03)  
  17. 17. Corrup)on 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Low  procurement-­‐intensity High  procurement-­‐intensity
  18. 18. Regression  framework ​ 𝐶 𝑜𝑟𝑟𝑢𝑝𝑡𝑖𝑜𝑛↓𝑗, 𝑚, 𝑡   =     𝛽𝑃𝑜𝑠𝑡𝑃𝑟𝑜𝑔𝑟𝑎​ 𝑚↓𝑡    𝑥   𝑃𝑟𝑜𝑐𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑣​ 𝑒↓𝑗 + 𝑃𝑟𝑜𝑐𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑣​ 𝑒↓𝑗 +​ 𝛼↓𝑚 +​ 𝛼↓𝑡 + 𝛾​ 𝑋↓𝑗, 𝑚, 𝑡 +​ 𝜖↓𝑗, 𝑚, 𝑡   
  19. 19. Results:  Corrup)on (1) (2) (3) (4) (5) Municipal- level [2001-2004] [2001-2004] [1997-2007] [1997-2007] [1997-2007] Post-2003 x -0.178*** -0.169*** -0.167*** -0.196*** -0.195*** High procurement intensity [0.0387] [0.0339] [0.0330] [0.0382] [0.0382] High procurement intensity 0.214*** 0.174*** 0.135*** 0.135*** 0.135*** [0.0394] [0.0405] [0.0384] [0.0384] [0.0389] Procurement intensity 0.0610** 0.0765*** 0.0752*** 0.0728** [0.0304] [0.0290] [0.0289] [0.0294] ln(transfer amount) 0.00379 0.00386 0.00338 0.00295 [0.00478] [0.00367] [0.00372] [0.00368] Second-half of the term x 0.0421** 0.0434** High procurement intensity [0.0208] [0.0207] Second-half of the term -0.239*** -0.279*** [0.0487] [0.0462] Municipality fixed-effects Yes Yes Yes Yes Yes Year fixed-effects Yes Yes Yes Yes Yes Term fixed-effects No No Yes Yes Yes Draw fixed-effects No No No No Yes Observations 1,932 7,072 10,538 10,538 10,538 R-squared 0.555 0.243 0.196 0.196 0.201 Robust standard errors clustered at the municipal level in brackets *** p<0.01, ** p<0.05, * p<0.1 Transfer-level Transfer-level Transfer-level Transfer-level
  20. 20. Diff-­‐in-­‐diff  coefficient  by  year
  21. 21. Diff-­‐in-­‐diff  coefficient  by  draw
  22. 22. Health  outputs  and  outcomes     ​ 𝑍↓𝑗, 𝑚, 𝑡 =​1/​ 𝑛↓𝑗  ∑𝑖↑▒​​ 𝑌↓𝑖, 𝑗, 𝑚, 𝑡 −​¯ˉ 𝑌 ↓𝑖, 𝑗, 𝑡=0 /​ 𝜎↓𝑖, 𝑗, 𝑡=0        ⇒ 𝐸[​ 𝑍↓𝑗, 𝑚, 𝑡=0 ]=0, 𝑉𝑎𝑟[​ 𝑍↓𝑗, 𝑚, 𝑡=0 ]=1     High  procurement-­‐intensity   Low  procurement-­‐intensity   -­‐  Hospital  beds;   -­‐  ImmunizaBon;   -­‐  %  adequate  water;   -­‐  %  adequate  sanitaBon.   -­‐  Coverage  of  Family  Health  program;   -­‐  Medical  consultaBons.  
  23. 23. Regression  framework ​ 𝑍↓𝑗, 𝑚, 𝑡   = 𝛿𝑃𝑜𝑠𝑡𝑃𝑟𝑜𝑔𝑟𝑎​ 𝑚↓𝑡    𝑥   𝑃𝑟𝑜𝑐𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑣​ 𝑒↓𝑗 +​ 𝜃↓𝑗 +​ 𝜃↓𝑚 +​ 𝜃↓𝑡 + 𝜂​ 𝑋↓𝑚, 𝑡 +​ 𝜐↓𝑗, 𝑚, 𝑡       
  24. 24. Z-­‐scores -­‐1.5 -­‐1 -­‐0.5 0 0.5 1 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Low  procurement-­‐intensity High  procurement-­‐intensity
  25. 25. Results:  Z-­‐scores (1) (2) (3) [2001-2004] [1997-2007] [1997-2007] Post-2003 x -0.309*** -0.494*** -0.495*** High procurement-intensity [0.107] [0.0948] [0.103] High proc. intensity x 0.00140 Audit within 100 km in previous year [0.0977] Audit within 100 km in previous year -0.109 [0.0897] Municipality fixed-effects Yes Yes Yes Year fixed-effects Yes Yes Yes Term fixed-effects No Yes Yes Observations 1,870 2,699 2,699 R-squared 0.556 0.513 0.514  
  26. 26. Mechanism (1) (2) (3) Corruption Mismanagement Compliance Post-2003 x -0.150*** 0.153*** -0.00262 High procurement-intensity [0.0346] [0.0446] [0.0294] Audit within 100 km in t-1 x -0.0424** 0.0247 0.0177 High proc. intensity [0.0187] [0.0253] [0.0199] Audit within 100 km in t-1 0.136** -0.116 -0.0198 [0.0652] [0.0734] [0.0314] Municipality fixed-effects Yes Yes Yes Year fixed-effects Yes Yes Yes Observations 7,072 7,072 7,072 R-squared 0.245 0.251 0.301 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1  
  27. 27. Mismanagement  categories (1) (2) (3) (4) (5) (6) Resource diversion Health council problems Performance problems Infrastructure and stock problems Human resources problems Documentation problems Post-2003 x -0.0614** 0.0289* -0.0404 0.156*** 0.0169 0.0906** High procurement-intensity [0.0260] [0.0162] [0.0324] [0.0280] [0.0147] [0.0360] High proc. intensity x -0.0328* 0.0042 0.0188 0.0106 0.0079 0.0414* Audit within 100 km in t-1 [0.0175] [0.00875] [0.0250] [0.0251] [0.0147] [0.0235] Audit within 100 km in t-1 -0.0346 -0.0142 -0.0215 0.0398 -0.00578 -0.0915** [0.0385] [0.0221] [0.0456] [0.0482] [0.0222] [0.0424] Municipality fixed-effects Yes Yes Yes Yes Yes Yes Year fixed-effects Yes Yes Yes Yes Yes Yes Observations 7,072 7,072 7,072 7,072 7,072 7,072 R-squared 0.237 0.125 0.136 0.21 0.124 0.165 Robust standard errors clustered at the municipal level in brackets *** p<0.01, ** p<0.05, * p<0.1
  28. 28. Spending 8 9 10 11 12 13 14 15 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Low  procurement-­‐intensity High  procurement-­‐intensity
  29. 29. Spending ln(transfer amount) (1) (2) (3) Post-2003 x -0.490*** -0.455*** -0.562** High procurement-intensity [0.133] [0.133] [0.272] Number of investigations 0.0234*** 0.0253*** [0.00749] [0.00866] ln(supply of funds by transfer group) -0.0279 [0.0277] Municipality fixed-effects Yes Yes Yes Year fixed-effects Yes Yes Yes Observations 7,072 7,072 5,222 R-squared 0.416 0.419 0.446 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1  
  30. 30. A  simple  decomposi)on ​ 𝑑​ln⁠(​ 𝐶↓𝑡 ) /𝑑   𝑡 = 𝑑​ 𝑙 𝑛(​​ 𝑌↓𝑡 /​ 𝑋↓𝑡  )/𝑑   𝑡 + 𝑑​ 𝑙 𝑛(​​ 𝑋↓𝑡 /​ 𝑇↓𝑡  )/𝑑   𝑡           −0.2      = 𝑑​ 𝑙 𝑛(​​ 𝑌↓𝑡 /​ 𝑋↓𝑡  )/𝑑   𝑡     −        0.5   ⇒ 𝑑​ 𝑙 𝑛(​​ 𝑌↓𝑡 /​ 𝑋↓𝑡  )/𝑑   𝑡 =0.3  
  31. 31. “Big  ideas” •  Procurement  mistakes  might  be  interesBng  to  incorporate  in  a  model       Ø   Capacity-­‐building  intervenBons;   Ø   SelecBve  monitoring:  larger  transfers,  where  incenBves  to  embezzle  are              much  higher;   Ø   InteracBon  with  asymmetric  punishments.   •  “Cap  and  trade”  for  corrupBon       Ø   Different  ciBes  have  different  costs  of  reducing  corrupBon.  

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