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Honorary    Lecture,  IMPPM  Opening  Cerimony,  March  1,  2016     Giancarlo  Spagnolo     U.    Rome  Tor  Vergata,  SITE-­‐Stockholm  School  of  Economics,  EIEF  &  CEPR

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DiscreKon:  definiKons  

 

Cambridge  English  Dic2onary  

the  right  or  ability  to  decide  something  

 Merriam  Webster  

the  right  to  decide  what  should  be  done  in  a  parKcular  situaKon  

 Full  defini2on  

the  quality  of  having  or  showing  discernment  or  good  judgement   ability  to  make  responsible  decision  

 Good,  if  not  abused    

 Necessary  in  important  situaKons  

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Of  course,  discreKon  may  be  abused

 

Need  for  accountability    

 

Cambridge  English  Dic2onary  

a  situaKon  in  which  someone  is  responsible  for  things  that   happen  and  can  give  a  saKsfactory  reason  for  them  

 

No  discreKon,  no  decision,  no  responsibility,  no  accountability      

Rules  limit  discreKon,  hence  may  limit  its  abuse  

but  also  limit  decisions,  responsibility,  and  accountability    

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Pros  of  Rules  

• By  limiKng  discreKon/decisions,  they  reduce  need  for  ex  post   accountability  controls  

• Cheaper  ex  ante  “procedural/bureaucraKc”  controls  instead  

• Simplify  tasks,  reducing  needs  for  judgment,  training,  and  cost   of  personnel  

Cons  

• Lead  to  poorer  outcomes:  rules  are  “stupid”,  rigid,  do  not  adapt   to  local  info/specific  condiKons  

• DemoKvate  skilled  civil  servants:  just  follow  rules!  Poor   selecKon,  moKvaKon,  quality…  

• May  confuse  responsibility/limit  accountability  

In  a  very  corrupt  state,  there  will  be  lots  of  laws  (Tacitus)    

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CompeKKon  as  a  Rule:  Use  Open  AucKons    

 

1. Reduce  discreKon  in  choosing  contractors/risk  of  its  abuse   2. Introduces  new  watchdogs:  compeKtors  

Plus  

Promise  of  large  gains  in  Value  for  Money  (max  Q/P),  at  least  as   measured  at  the  awarding  stage  

 

True  if  contracts  almost  complete,  well  wriben,  well  coordinated   with  the  scoring  rule,  well  managed…  

 

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Limits  to  CompeKKon/Open  AucKons  

 

• Complete  contracKng  condiKons  are  very  ocen  not  met,  as  the   private  sector  shows  (Toyota  vs  GM…  Kelman  1990)  

• Apparent  gains  in  ex  ante  offered  Q/P  may  correspond  ex  post   to  very  low  Q,  or  renegoKaKon,  or  corrupKon  

• Monitoring  Q  much  more  difficult  than  P,  hence  all  under  the   lamp  looking  at  P  alone…  guess  the  results?  

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Buyer  DiscreKon  in  Dynamic  Procurement  

 

If  performance  hard  to  contract,  “quality  depends  on  price”  and   standard  arguments  for  compeKKon  fail  (SKglitz  1989,  Spulber   1990,  Manelli  e  Vincent  1995)    

• In  repeated  procurement  relaKonships,  limited  contractual   governance  ‘completed’  by  relaKonal-­‐reputaKonal  forces   – RelaKonal:  Vendor  RaKng  systems  

– ReputaKonal:  Brand,  Feedback  mech.  (eBay)    

• Rela2onal  governance  needs  discre2on,  acKng  on  non  verifiable   informaKon,  also  to  fight  corrupKon!  (Calzolari-­‐Spagnolo  2009)  

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CompeKKon  as  a  Rule:  Use  Open  AucKons  

 

 

When  important  quality  aspects  not  verifiable,  only  low  quality      ends  up  being  purchased,  and  fall  in  Q  may  dominate  that  in  P   AlternaKves:    

 •  NegoKaKons:    

 introduce  some  discreKon  but  almost  eliminate  compeKKon    allows  higher  quality  but  at  increasing  cost  

 accountability  checks  very  difficult/expensive,  easy  to  abuse    

•  Restricted  aucKons  by  invitaKon:    

 introduces  discreKon  (ability  not  to  invite  some  suppliers)    maintains  substanKal  compeKKon,  less  easy  to  abuse    

 

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PosiKve  Evidence  on  DiscreKon  in  Public  Management  

 

Rasul  and  Rogger  (2016),  study  Nigerian  Civil  Service,  find  that    

• increasing  bureaucrats’  autonomy  is  posiKvely  associated  with   compleKon  rates,    

 

Duflo  et  al.  (2015)  field  experiment  on  environmental  regulaKon   and  its  enforcement  in  India:  finding,  among  other  things,  that    

• regulatory  discre2on  is  highly  valuable,  it  allows  the  regulator  to   beber  target  inspecKons  at  extreme  polluters,    

 

Bandiera  et  al.  (2009):  waste  in  the  procurement  of  Italian  goods   and  services  is  substanKally  smaller  for  more  autonomous  public   purchasing  authoriKes  that  enjoy  more  discreKon.    

 

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Evidence  on  AucKons  vs  NegoKaKons  in  Public  Proc.  

 

Vellez  (2011)  on  Italian  Health  procurement,  mulKlateral  

compeKKve  negoKaKons,  no  difference  in  price  with  aucKons    

Chever  and  Moore  (2012)  on  construcKon  of  housing  in  France.  

They  find  that  negoKaKons  acer  an  informal  aucKon  are   associated  with  lower  costs  relaKve  to  open  aucKons.    

   

Lalive,  Schmutzler  and  Zuelenher  (2015):  procurement  of  rail   services  in  Germany,  hand  collected  data  

•  aucKons  improve  surplus  (service  &  prices)  of  30%;  

•  surplus  would  have  increased  by  16%  on  negoKated  lines;  

•  administraKve  costs  of  carrying  out  aucKons.  

     

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Evidence  on  Open  vs  Restricted  AucKons  in  Public  Proc.  

 

Beber  comparison  to  isolate  the  effects  of  discreKon,  as  more   compeKKon  is  maintained.  

Pros  

Coviello,  Guglielmo  e  Spagnolo  (2011/2016)  analyze  works  in   Italy  2000-­‐2006  using  EU  threshold,  causal  evidence  (RDD):  

•  DiscreKon  (>  restricted  but  compeKKve  aucKons,  min  15   invited)  increases  repeated  buyer-­‐seller  interacKon  

•  Does  not  worsen  outcome  (prices,  delays,  renegoKaKons)  

•  For  some  specificaKons,  it  seems  to  improve  delivery  Kme   AddiKonal  evidence  (propensity  score  matching)  

•  well  performing,  large,  non-­‐local  firms  selected  again  

Good  effects  of  discreKon  appear  to  at  least  compensate  bad  

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Open  vs  Restricted  AucKons  in  Public  Proc.  cont’d

  More  Pros    

Chever,  Saussier  and  Yvrand-­‐Billon  (2014)  study  180  contracts  by   a  local  public  buyer  of  social  housing  2006-­‐2009,  show  that    

•  restricted  aucKons  lead  to  same  outcomes  as  open  but  lower   transacKon  costs,  and  no  signs  of  abuse  of  discreKon  

Kang  and  Miller  (2015)  esKmate  proc.  model  where  extent  of   compeKKon  is  opKmally  chosen  by  public  buyers,  and  find  that    

•  limiKng  compeKKon  need  not  result  in  higher  proc.  costs.    

Con  

Gurakar  and  Meyerson  (2016):  increased  use  of  restricted   aucKons  in  Turkey  works  led  to    

•  higher  costs  and    

•  higher  winning  probability  for  AKP-­‐affiliated  firms  

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Open  vs  Restricted  AucKons  in  Public  Proc.:  Cons  

                   

Palguta  and  Pertold  (2013),  Check  proc.  data,  EU  reform  2006  

•  Restr.  Auct.  è  value  manipulaKons  to  stay  below  threshold  

•  Outcomes:  anonymous  firms  win  more  ocen,  at  higher  prices   Hypothesis  

Illegal  discreKon  (through  strategic  bunching)  has  worse  effects?  

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Transparency  and  data  for  ex  post  performance   evaluaKon  are  essenKal  to  foster  the  posiKve   effects  of  discreKon  (see  Saussier  &  Tirole  2015)

example    

Public  Procurement  Thresholds     and  Data  in  Sweden

 

 

 

Report  for  Konkurrensverket  by     SITE-­‐Stockholm  School  of  Economics  

Team:  Roman  Bobilev,  Andrea  Guglielmo,  Elena              Paltseva,  Giancarlo  Spagnolo

 

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–  An  exploratory  study  of  Public  Procurement  in      (Italy  and)  Sweden  which  focuses  on:    

(i) strategic  ”bunching”  of  tenders  below  regulatory   thresholds,  with  illegal  increase  in  discreKon;  

(ii) the  heterogeneity  of  contracKng  authoriKes’  

organizaKon  and  behavior  in  public  procurement;  

(iii) procurement  data  availability,  also  in  comparison  to   some  other  European  countries.    

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                Ch.  2  

 

Bunching  and  Outcomes:  and  example  from  Italian   procurement  of  public  works  

Discre0on  and  Public  Procurement   Giancarlo  Spagnolo  

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•  Database  from  the  former  Italian  Authority  for  the   Surveillance  of  Public  Procurement  (AVCP)    

•  All  the  public  works  awarded  in  Italy  between  2000  and   2005  with  values  greater  than  or  equal  to  150,000  Euro  

•  For  each  contract,  we  observe  the  number  of  bidders,  the   winner's  rebate,  the  project  value,  the  idenKty  of  the  

winning  bidder,  the  type  of  work,  the  final  cost,  the  date   of  delivery,  and  the  type  and  locaKon  of  the  public  

administraKon  

•  Focus  on  a  subsample  between  200k  and  500k  Euro.  

Data  as  in  Coviello,  Guglielmo  e  Spagnolo  (2011)  

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Approach  

•  Focus  on  heterogeneity  in  sorKng  behavior  across  different   contracKng  authoriKes,  and  the  impact  of  it  on  

procurement  outcomes  

•  First,  we  compare  the  behavior  of  a  “Big  Player”  to  other   contracKng  authoriKes  

•   Second,  we  compare  the  contracKng  authoriKes  according   to  their  level  of  corrupKon,  social  capital  and  judicial  

efficiency  

(19)

Aggregate  data  –  not  much  apparently  

(20)

Taking  heterogeneity  into  account…  

(21)

StaKsKcs  for  “Big  Player”    

 “Big  Player”  vs.  other  administraKons:  

 

• Fewer  delays  

• Fewer  deviaKons  from  the  iniKally  planned  costs  

• Smaller  probability  to  award  to  local  bidders    

• Higher  probability  of  previous  suppliers  winning  bids  

• “TrabaKva  Privata”  used  more  below  threshold  (20%  vs  9%)  

• Less  delays  and  same  costs  with  “TrabaKva  Privata”  

 

(22)

Other  staKsKcs  

•  Areas  with  higher  corrupKon  

–  More  bidders  and  more  substanKal  rebates  

–  “TrabaKva  Privata”  is  used  less  ocen  below  threshold    

•  Areas  with  higher  social  capital  

–  More  bidders  and  more  substanKal  rebates,  no  maber   with  what  procedure  or  value  

–  “TrabaKva  Privata”  is  used  more  ocen  below  threshold    

•  Areas  with  beber  judicial  efficiency     –  Fewer  rebates  and  fewer  bidders  

–  Past  winners  win  more  ocen,  fewer  delays  

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Conclusion    

•  “Big  Player”  likely  to  bunch  and  use  discreKon  more  ocen  

•  “Big  Player”  more  efficient,  beber  results  

Consistent  with  posi2ve  use  of  illegally  obtained  discreKon    

•  Use  of  open  aucKons  and  (apparent)  compeKKon  not   associated  to  beber  performance  and  less  corrupKon   (post-­‐aucKon  phase  appears  therefore  crucial…)  

•  The  type  of  administraKon  plays  a  crucial  role  

(24)

Ch.3      

Accessing  bunching  below  threshold  in  Sweden    

Discre0on  and  Public  Procurement   Giancarlo  Spagnolo  

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Sweden  

 

Can  we  assess  the  effect  of  the  thresholds  in  Sweden?  

•  Specifically,  we  look  at  the  EU  Public  Procurement  direcKves  -­‐  

Procurement  tenders  with  the  expected  value  above  the   threshold  should  be  procured    according  to  EU-­‐wide  rules    

–  Contract  noKces  published  at  EU-­‐wide  website  TED   (Tenders  Electronic  Daily)  

–  More  detailed  data  requirements,  etc.    

•  Main  ques0on:  Is  there  an  evidence  of  strategic  behavior  in   procurement  due  to  thresholds?    Is  there  impact  on  

procurement  outcomes?  Does  it  depend  on  the  type  of  the   buyer?  

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Public  procurement  data  in  Sweden  

Swedish  procurement  data  on  tender  value:  

• Above  EU  thresholds  –  TED  database  

–  Compliance  is  very  poor,  see  next  slide   –  Expected  tender  value  cannot  be  uKlizes  

• Below  EU  thresholds    -­‐    VISMA  database    

–  Covers  around  80%  of  public  procurement  deals  in  Sweden   –  Also  includes  the  data  reported  through  TED  

–  However,  expected  value  is  NOT  collected    

•  it  may  sKll  be  somewhere  in  pdf  documents,  but  not  for   systemaKc  analysis  

–  Also,  data  is  on  tenders,  not  on  individual  lots  –  difficult  to   measure  compeKKon  

–  Outcome  data  is  not  collected  

(27)

•  Underreported  for  both  es0mated  and  actual  value,  also  in   comparison  to  other  EU  member  states.  

•  IdenKty  of  buyer  mabers:  Swedish  public  enKKes  more  likely  to  report   the  values  are  those    

•  in  the  central  administraKon  and  public  uKliKes  sectors,    

•  procuring  for  the  goods  and  services  within  the  financial  and   insurance  services  and  architecture  and  construcKon  services   industries.    

 

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•  The  data  on  es0mated  value  also  looks  non-­‐reliable  

–  likely  due  to  misunderstanding  or  different  interpretaKon  of  the  EU  regulaKon  

•  Example:  distribuKon  of  winner  rebate  

•  BoBom  line:  

–  EsKmated  value  data  for  Sweden  cannot  be  used  for  empirical  analysis    

–  There  is  a  need  in  clarificaKon  of  the  EU  procurement  regulaKon  to  public  enKKes   in  Sweden    

–  Perhaps,  also  a  need  for  beber  alignment  between  the  EU  legislaKon  and  different   cross-­‐country  procurement  pracKces  .    

(29)

•  Data  issues  (e.g.,  we  have  to  use  final,  as  opposed  to  esKmated,   procurement  value)  

–  Our  measures  of  bunching  are  imprecise    

•  SKll,  we  find  signs  of  bunching  under  the  EU  thresholds!  

–  Confirmed  by  both  histograms  and  McCrary  density  disconKnuity   tests  (see  next  slides)  

 

•  Bunching  depends  again  on  the  idenKty  of  the  buyers  

–  Supplies  and  services:  staKsKcally  significant  bunching  for  central   governments  

–  Public  works:  (close  to  significant)  bunching  for  other  authoriKes  

•  data  here  incomplete:  many  of  public  works  procurement   tenders  –  of  Traffikverket  -­‐    are  not  in  VISMA  

(30)

Bunching  in  Sweden  

•  Histogram  analysis  

(31)

•  McCrary  density  disconKnuity  tests  

 

•  BoBom  line:  

–  Evidence  of  strategic  bunching  in  public  procurement  in   Sweden  

–  More  and  beber  data  would  be  needed  for  a  thorough   analysis  of  the  effect  of  this  bunching  

(32)

Conclusions  

•  Increase  in  discreKon  may  have  good  or  bad  effects,  depending   on  insKtuKonal  environment  (France-­‐Italy  vs  Turkey)  

•  Rules  constraining  discreKon  easily  avoided,  then  illegal  gain  in   discreKon,  for  the  good  or  for  the  bad  (Italy  vs  Check  Republic)  

•  Same  happening  in  Sweden,  but  no  data  to  evaluate  effects    discreKon  needs  data  for  ex  post  accountability  checks!!  

•  Different  types  of  contracKng  authoriKes  behave  rather   differently  in  public  procurement.    

•  Complex  problem,  simple  rules  subopKmal  in  most  cases.  

•  Transparency  and  data  for  ex  post  performance  evaluaKon  are   essenKal  to  foster  the  posiKve  effects  of  discreKon  (Saussier  &  

Tirole  2015)  

References

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