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Adjusting Development Outcomes by Risk (2011 Evaluation Week)
 

Adjusting Development Outcomes by Risk (2011 Evaluation Week)

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Risk-Adjusted Expected Development Outcome of Private Sector Investment Projects, Presentation at the 2011 Evaluation Week

Risk-Adjusted Expected Development Outcome of Private Sector Investment Projects, Presentation at the 2011 Evaluation Week

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  • Definition: Dictionary of Fianncial and Investment termshttp://www.investopedia.com/terms/r/raroc.asp
  • This is multiple factor model: factor model assumes return is sensitive to the movements of various factors. The model attempts to capture the major forces that systemically move the outcomes. - refers to unexplained by the model, unique or specific to the project that is uncorrelated to the factors in the model.
  • C:\\data\\XPSR_Oct9_2011_newextract.xlsx
  • C:\\data\\xpsr_ida_nonida.xlsx
  • C:\\Users\\hhatashima\\Documents\\RAP2011\\RAEDO\\IICCR_countrycoded_2011_ext.xlsx
  • C:\\data\\XPSR_Oct9_2011_newextract.xlsx

Adjusting Development Outcomes by Risk (2011 Evaluation Week) Adjusting Development Outcomes by Risk (2011 Evaluation Week) Presentation Transcript

  • Adjusting Development Outcomes by RiskRisk-Adjusted Expected Development Outcome of Private Sector Investment Projects IEG Evaluation Week October 24, 2011 Hiroyuki Hatashima IEG Private Sector Evaluation 1
  • Outline of the presentation• Performance measurement vs risk• Drivers of development outcome for IFC investment projects• Model based on drivers• Two applications of the model ‒ Performance assessment ‒ Expected development outcomes 2
  • Performance measurement vs risk • Risk is measurable possibilities of losing or not gaining value • Risk-return trade-off as the basis of investment management (if you don’t want risk, don’t expect return) • For fair comparison, the return has to be compared to the risk undertaken. 3
  • Private Sector Development Outcome Development Outcome = Overall effect on country’s development Business Economic Envi. & Social Private Sector Performance Performance Performance Development Gov’t, taxpayers Demo. effects, employees, linkages, corp. gov, Neighbors & customers, investment climate Financiers Environment suppliers & new entrants 4
  • Model based on Development Outcome Results DriversDO = f + )+( 5
  • Risk factors influencing development outcomes Coeff. Signif. at Risk Factors Description against 5% DO Experience, financial capacity,Sponsor Risk commitment and reputation of -0.21 Yes sponsors (1=high risk, 0=low risk) Business competitiveness in theMarket Risk market, distortions (1=high risk, 0=low -0.14 Yes risk)Changes in Changes in Country Risk indicatorsCountry between approval and evaluation (i.e. 0.009 YesBusiness 5 years) (score @ eval – score @Climate approval) “greenfield” (high risk) vs. expansionProject Type -0.06 No project (1=greenfield, 0=expansion)Based on 2000-2010 XPSR Evaluation, N=655Coefficient against DO in multiple variable regression. R2=0.09 6
  • Regression results of all drivers Factors Coefficient Signif. at 5% Sponsor Risk -0.11 Yes Market Risk -0.12 Yes Changes in Country Business Climate 0.005 Yes Project type -0.07 No Screening, appraisal & structuring work 0.33 Yes quality Supervision & administration work quality 0.28 Yes IFC role and contribution 0.46 YesBased on 2000-2010 XPSR Evaluation, N=655Coef. for multiple variable regression. R2=0.37 7
  • Two applications of the model 1. Performance assessment • Outcomes with focus on IFC Work Quality, taking risks 2. Likely outcomes • Based on existing risks and work quality scenarios 8
  • Use of model 1: Performance Assessment• Focusing on IFC controllable factors, given risks taken• Which is the best performing region, adjusted by risk, focusing on WQ improvement? Region Development Outcome high % Southern Europe & Central Asia 87% Middle East & North Africa 80% Latin America & Caribbean 79% Sub-Saharan Africa 74% South Asia 72% East Asia & Pacific 62% Central & Eastern Europe 60% IFC overall 73% 9
  • Two Work Quality scenarios for comparison DO= f (Risks + Work Quality) +Scenarios: Potential BenchmarkWQ Perfect WQ = 100% High WQ ratings of previousassumptions WQ across the board periodsRisks Actual project risksIndicator Model-generated maximum expected success ratemeans possible DO rating expected to outperform, adjusted by the embedded project risk factors.Comparison Indicate gaps to potential Reflecting WQ changeswith actual based on existing risksoutcome 10
  • Gaps between actual and potential/benchmark = risk adjusted outcome indicators Region Actual Potential Benchmark Southern Europe 87% 90% 85% & Central Asia Middle East & 80% 86% 59% North Africa Latin America & 79% 92% 83% Caribbean Sub-Saharan 74% 88% 56% Africa South Asia 72% 90% 62% East Asia & Pacific 62% 89% 55% Central & Eastern 60% 90% 83% Europe IFC overall 73% 89% 72% 11
  • MENA & AFR outcomes stood out, adjusted by risks/Work Quality. MENA 25 SS AFR 20 S Asia 15 EAP 10 (Benchmark-Actual) IFC 5 (Potential – Actual) 0 SECA-40 -30 -20 -10 -5 0 LAC -10 -15 CEE -20 -25 12 -30
  • INFRA (AFR/LAC/EMENA) andFM (AFR/LAC) outcomes stood out 15 INF AFR/LAC (Benchmark-Actual) MAS Asia 10 INF Asia INF EMENA FM AFR/LAC 5(Potential – Actual) IFC MAS EMENA 0-30 -25 -20 -15 -10 -5 0 5 FM Asia MAS AFR/LAC -5 FM EMENA -10 -15 13
  • Use of model 2: likely outcomesIDA – Non IDA gap in recent years: will it continue? XPSR Development Outcome 90% 80% 70% 60% 50%DO high % 40% Non IDA 30% IDA 20% 10% 0% Evaluation Year 14
  • What’s behind the gap? • Project Risks – IDA more riskier than non IDA Sponsor Risk Market Risk 70% 90% 60% 80% 50% 70%High Risk % High Risk % 40% 60% 50% 30% 40% 20% 30% NonIDA 10% 20% IDA 0% 10% 0% Approval Year Approval Year 15
  • What’s behind the gap?• Changes in Country Business Climate - IDA lower than non IDA 20 15Changes in IICCR s cores 10 5 IDA non-IDA 0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 -5 -10 16 Evaluation year
  • What’s behind the gap? Appraisal WQ and Roles dropped in IDA Appraisal Work Quality Supervision Work Quality90% 100%80%70% 80%60% 60%50%40% 40%30%20% 20%10% 0% 0% Evaluation Year Evaluation Year Role and Contribution 100% 90% 80% 70% 60% 50% 40% 30% Non IDA 20% IDA 10% 0% 1996-98 1997-99 1998-00 1999-01 2000-02 2001-03 2002-04 2003-05 2004-06 2005-07 2006-08 2007-09 2008-10 17
  • Prospects for coming years• Assume 08-10 XPSR WQ (IDA average)• Actual risk of 2006-09 approvals (except country risk – changes so far) – what will be the likely results? Sponsor Risk Market Risk 70% 90% 60% 80%High Risk % 50% 70% 60% 40% 50% 30% 40% 20% 30% 20% NonIDA 10% 10% 0% 0% IDA 1995-97 1996-98 1997-99 1998-00 1999-01 2000-02 2001-03 2002-04 2003-05 2004-06 2005-07 2006-08 2007-09 Approval Year Approval Year 18
  • Changes in country business climate so far • IDA – Not dropping sharply as non-IDA Changes in IICCR Score between approval and evaluation (or approval and most recent score for 2006-2010 approvals = 2011-15 maturity) 20 15Changes in IICCR score 10 5 IDA non-IDA 0 -5 -10 Evaluation Year (approval + 5 years) 19
  • Future prospects: IDA-non IDA gap will narrow • If above WQ assumptions hold Development Outcome (incl. projection) 90% 80%Development Outcome High % 70% 60% 50% 40% Non IDA 30% IDA 20% 10% 0% Evaluation year = Predicted by the model 20
  • Summary• Project performance = need to separate factors controlled by institution vs risks• Multi-factor Model can generate success rates that = can treat as benchmarks for performance measurement; = can indicate future outcomes, given risks and work quality assumptions 21
  • Adjusting Development Outcomes by RiskRisk-Adjusted Expected Development Outcome of Private Sector Investment Projects IEG Evaluation Week October 24, 2011 Hiroyuki Hatashima IEG Private Sector Evaluation 22