Monitoring Road Works Contracts and Unit Costs in Sub-Saharan Africa for Enhanced Governance

1
Monitoring Road Works Contracts and Unit Costs
in Sub-Saharan Africa for Enhanced Governance
Tanzania Roads Fund Board

• Cesar Queiroz
• Consultant, former World Bank
• Highways Adviser
• Dar es Salaam, Tanzania
• July 2, 2012

Construction and Maintenance Unit Costs Workshop
2
OUTLINE

• Building a new dataset of road works contracts of
  Bank-financed projects in Sub-Saharan Africa
• Analyzing trends and key indicators
• Examining red flags
• Explaining what drives road construction costs
  issues addressed by project implementing agencies
• Enhancing accountability and attaining a higher
  degree of control of corruption in World
  Bank-financed projects in the road sector
• Conclusions

3
A SPECIALIZED DATABASE

• 109 completed and on-going road and bridge works
  contracts
• 76 supervision consultancy contracts for relevant
  road works
• Signed between 1999 and 2007
• From 22 projects financed by the World Bank
• Range of works contracts From US595,518 to
• US58,436,429

• For 13 countries in Sub-Saharan Africa
• Congo
• Democratic Republic of Congo
• Ethiopia
• Ghana
• Kenya
• Malawi
• Mauritania
• Mozambique
• Madagascar
• Nigeria
• Tanzania
• Uganda
• Zambia

4
DATABASE SET OF COST INDICATORS

• Road Works Unit Costs
• in 2007 US

• Road Works Costs
• for 7-m wide, 2-lane road equivalent
• in 2007 US/km

Rehabilitation/Reconstruction Upgrade to Paved Periodic Maintenance Regravel Inter-Urban Urban Rural Access EngineersEstimate Contract Price Actual Cost
Asphalt Concrete (/m3) Portland Cement Concrete (/m3) Base Gravel, Crushed stone, Bituminous (/m3) Subbase Gravel, Crushed Stone (/m3) Earthworks Soft, Hard (/m3) Surface treatment Single, Double (/m2)
5
DATABASE SET OF BIDDING INDICATORS

• Contracts with Pre-qualification

• Contracts without Pre-qualification

• Number of applicants for pre-qualification
• Number of pre-qualified firms
• Number of firms buying bidding documents
• Number of bidders
• Number of bidders accepted for detailed
  examination

• Number of firms buying bidding documents
• Number of bidders
• Number of bidders accepted for detailed
  examination

• Bid Amounts
• Name and Nationalities of All Bidders

6
DATABASE SET OF OTHER INDICATORS

• DATES
• Bid Opening Date
• Contract Signing Date
• Contract Completion Date
• Delays in Completion of Work

• SUPERVISION CONSULTANCY
• Names and Nationalities of Supervision
  Consultants
• Supervision Contract Amount
• Actual Supervision Contract Amount

7
KEY STATISTICAL TRENDS

• The road sector contracting of Bank-financed
  operations is characterized by a limited number
  of firms dominating large-scale works
• The market is split between African firms and
  mainly Chinese and European contractors
• The largest contracts are generally awarded to
  international contractors, in particular Chinese

• Percentage of Contracts by Geographical Group

• Share of Contract Totals by Geographical Group

8
KEY TRENDS BIDDING PATTERNCONTRACTS WITH
PRE-QUALIFICATION

• About half of the pre-qualified firms do not bid
• The overall number of pre-qualified firms to bid
  for large works seems competitive (more than 6
  firms on average). However, the actual
  participation in tenders is quite low

• Average Number of Pre-qualified Firms, Bidders,
  and Bidders Accepted for Detailed Examination

9
KEY TRENDS BIDDING PATTERNCONTRACTS WITHOUT
PRE-QUALIFICATION

• Half or more firms buying bidding documents do
  not bid in the reviewed contracts in Mozambique,
  Madagascar, DRC, Zambia, and Malawi

• Average Number of Firms Buying Bidding
  Documents, Bidders, and Bidders Accepted for
  Detailed Examination, by Country

10
KEY TRENDS BIDDING PATTERNCONTRACT VALUE AND
ENGINEERS ESTIMATE

• Several road works contract values exceed the
  engineers estimate by more than 30 percent

• Difference between Contract Values and
  Engineers Estimates, Averages and Ranges

11
KEY TRENDS BIDDING PATTERNBID OPENING AND
CONTRACT SIGNING DATES

• Extensions of the original bid validity period
  seem to be a norm
• Only the DRC, Congo, and Madagascar have the
  contracts awarded within the original period of
  validity of bids (90 or 120 days in the sample)

12
KEY TRENDS IMPLEMENTATIONCOST OVERRUNS

• Contract cost increase during implementation is
  substantially high in some of the countries in
  the sample

• Cost Overruns, Averages and Ranges by Country

13
KEY TRENDS IMPLEMENTATIONCOST OVERRUNS (contd)

• Cost overruns vary across the countries. The
  highest number of contracts with cost overruns is
  in Nigeria where almost 43 percent of all the
  reviewed contracts increased their value by more
  than 15 percent. Mozambique and Ghana had cost
  overruns in 30 percent of the contracts in the
  sample
• Percentage of Contracts with Cost Overruns of
  more than 15 by Country

14
KEY TRENDS IMPLEMENTATIONTIME OVERRUNS

• The delays in completion of work reaches up to a
  year and half
• Average Delay in Completion of Work in Months,
  by Country

15
KEY TRENDS ROAD WORKS COST PER KM OF A 7-M WIDE,
2-LANE ROAD
16
KEY TRENDS ROAD WORKS COST PER KM OF A 7-M WIDE,
2-LANE INTER-URBAN ROAD

• A wider range of the average costs per km is
  observed for the re-gravel and periodic
  maintenance works the range is relatively
  narrower for the upgrade to paved and
  rehabilitation/reconstruction works
• Cost per km of a 2-Lane Road by Type of Work for
  Inter-Urban Roads (2007 US/km)

17
KEY TRENDS UNIT COSTSASPHALT CONCRETE AND
PORTLAND CEMENT CONCRETE (2007 US/M3)

• Large variations are observed in the unit costs
  of road works across the countries in the sample

18
KEY TRENDS UNIT COSTSBASE AND SUBBASE (2007
US/M3)
19
KEY TRENDS UNIT COSTSEARTHWORKS AND SURFACE
TREATMENT (2007 US)
20
KEY STATISTICAL TRENDS BY GEOGRAPHICAL GROUP OF
CONTRACTORS

• The African firms outperform the Chinese and
  European contractors in several indicators
  related to the procurement process but
  underperform in the implementation
• Statistical Averages by Geographical Groups

21
KEY TRENDS BY GEOGRAPHICAL GROUP OF CONTRACTORS
COST PER KM

• The African firms have a cost advantage over the
  Chinese and European firms in the sample, when
  implementing rehabilitation or reconstruction
  works or upgrading a road to pavement standards
• Cost per km of a 2-Lane Road Equivalent by
  Geographical Group and Type of Work (2007 US)

22
LEADING ROAD WORKS CONTRACTORS

• A Chinese contractor carried out about 19 of
  Bank-financed road works in the sample (in
  financial terms)
• The total value of road works contracts in the
  sample is about US 1.5 billion
• Leading Contractors by Awarded Contract Totals

23
SUPERVISION CONSULTANCY CONTRACTS RATIOS

• The supervision contract amounts vary between 3
  and13 of the respective road works contract
  amounts in the countries reviewed
• Ratio of Supervision Contract Amounts to Road
  Works Contract Amounts

24
SUPERVISION CONSULTANCY CONTRACTS COST PER KM

• There is a wide range between the average costs
  of supervision per kilometer of similar road
  works across the countries
• Average Cost of Supervision per km of a 2-Lane
  Road by Country (2007 US)
•  

25
SELECTION OF RED FLAGS

• The following is a set of red flags that was
  selected under the study
• Period between bid opening and contract signing
  is more than 7 months
• Cost increases by more than 20 during
  implementation
• Time overrun is more than 30 of the originally
  contracted period
• Contract value is more than 20 above the
  Engineers Estimate
• Half or more firms buying bidding documents do
  not bid
• 20 or more of pre-qualified firms do not bid
• Difference between winning bid and next lowest
  bid is within 2
• Difference between contract price and read-out
  bid price is more than 10
• Winning bid is not the lowest bid accepted for
  detailed examination
• Only one or two bidders
• Cost per km for similar works and unit road works
  costs are higher than the 75 percentile

26
EXAMINATION OF RED FLAGS

• An inventory of risks was performed for each road
  works contract using a checklist of red flags
• The presence of red flags does not prove that
  corrupt or fraudulent practices have taken place
  in the procurement and implementation of a
  contract
• A red flag is rather a warning signal of a
  potential procurement and implementation problem
  that may justify further investigation
• Conversely, the absence of red flags does not
  imply that fraud or corruption did not occur

27
RED FLAGS FREQUENCY IN THE SAMPLE OF 109
CONTRACTS
28
RED FLAGS FREQUENCY BY COUNTRY
29
RED FLAGS NORMALIZED BY NUMBER OF CONTRACTS IN
EACH COUNTRY
30
RED FLAGS NORMALIZED BY NUMBER OF CONTRACTS IN
EACH COUNTRY AND WBI CONTROL OF CORRUPTION INDEX
31
RED FLAGS IN THE CONTRACTS WITH COMPLAINTS
RECEIVED BY INT

• The Department of Institutional Integrity (INT)
  received complaints on 14 contracts from the
  sample of 109 road works contracts (13 of total)
• The nature of complaints was mainly related to
  allegations of bidder collusion or bid rigging,
  paying bribes, and bidding irregularities
• The pattern of red flags in the contracts with
  complaints received by INT slightly differs from
  the overall pattern observed across all the
  contracts in the sample

32
RED FLAGS PATTERN IN THE CONTRACTS WITH
COMPLAINTS RECEIVED BY INT
33
RED FLAGS ROAD WORKS UNIT COSTS

• Frequency of Red Flags for Unit Costs in the
  Contracts with Complaints Received by INT in
  Comparison with other Contracts in the Sample

34
SELECTED ISSUES AS ADDRESSED BY PROJECT
IMPLEMENTING AGENCIES

• Reasons for high bids
• The effect of increase in prices of fuel, power,
  materials, and equipment on major cost items of
  contracts
• A fixed price contract that is not subject to
  price adjustment
• Supply and demand effect
• Potential collusion by bidders
• Inadequate prediction of major market forces by
  the engineers estimate
• Perception of risks incorporated by bidders in
  their bid prices (e.g., provisions of extended
  contract procurement cycle time associated with
  price inflation risks)
• Other factors (e.g., a delayed delivery of goods
  due to congestion and transport problems, the
  high cost of input taxes, political instability
  and insecurity)

35
OTHER SELECTED ISSUES

• Reasons for low response to invitation to bid
• Increased demand for contractors services
• Insecure areas in a post-conflict country (DRC)
• Reasons for cost overruns
• Global trend of rising oil prices
• Labor cost increase and impact of other
  regulatory measures (taxation)
• Unsatisfactory contractor performance
• Time lag between design and contract execution
  dates
• Time extensions

36
RECOMMENDED ACTIONS

• The following is a set of selected
  recommendations geared to enhance accountability
  and attain a higher degree of control of
  corruption in Bank-financed projects in the road
  sector in Sub-Saharan Africa
• Consider establishing a tighter timeframe for
  contract signing. A stricter adherence to the
  Banks procurement guidelines should be observed
  that provide for an extension of bid validity if
  justified by exceptional circumstances
  (Procurement Guidelines). A delayed bid
  evaluation process provides opportunities for
  corrupt practices and back-door negotiations.
• Allow using a selection procedure of
  post-qualification in bidding for large works
  instead of pre-qualification. Knowledge of other
  pre-qualified firms carries a potential risk of
  collusion. Also, other firms may choose not to
  bid due to a potential collusion of
  well-connected companies.

37
RECOMMENDED ACTIONS

• Create a system to monitor and assess
  contractors and consultants performance.
  Tracking of information on contractors and
  consultants in the road industry in the region
  could mitigate risks of misjudging on
  qualifications of firms as well as ensure due
  diligence on poor performers. The rankings of
  major contractors and consultants could identify
  strong performers who could be encouraged to bid
  or hired through direct contracting in case of
  emergencies.
• Strengthen the monitoring over the procurement
  and implementation processes to enhance detection
  of the risks to integrity. It is important to
  generate the data to increase accountability.

38
CONCLUSIONS

• It is critical to continue collecting data on the
  procurement and implementation processes of the
  road sector contracts to allow comparison of cost
  trends, bidding competition, and performance in
  the road sector. A standard framework (including
  a template) has been developed within this study
  to provide the platform for monitoring and
  evaluation of prices, bidding data, and
  contractors information to help improve
  governance.
• Capturing costs and unit price information of
  road works is important for evaluation of the
  trends across countries and regions. Empirical
  evidence could be built on such indicators as
  price increases relative to the engineers
  estimates, cost increases, and key roads input
  costs to investigate the sources of increased
  costs and possible factors behind the increase in
  bid prices.

39
CONCLUSIONS

• Assessing bidding behavior is essential for
  measuring the level of competition and road works
  activity financed by the Bank. Verifying the
  extent of competition in the bidding environment
  is an important tool for procurement decisions.
  Detailed bidding data could facilitate measuring
  if the procurement process is affected by
  collusion and bid rigging through detection of
  patterns and red flags in the structure of bids
  and firms.
• Measuring performance more consistently would
  help to address inefficiencies that arise in the
  current procurement and implementation practices.
  This would ensure that irregularities are
  properly captured in the observed trends in a
  specific country or area. It is important to link
  the performance measures to contractors and
  consultants as well as project implementing
  agencies for accountability.

40
Thank you!
41
References

• Monitoring Road Works Contracts and Unit Costs
  for Enhanced Governance in Sub-Saharan Africa.
  World Bank Transport Paper No. TP-21. 2008.
  http//siteresources.worldbank.org/INTTRANSPORT/Re
  sources/336291-1227561426235/5611053-1229359963828
  /tp_21.pdf
• Monitoring Road Works Contracts and Unit Costs
  for Enhanced Governance in Europe and Central
  Asia. World Bank Transport Paper No. TP-33.
  2011. http//go.worldbank.org/9XN7FBUCD0
• Prediction model for the cost of road
  rehabilitation and reconstruction works. 2nd
  International Conference on Road and Rail
  Infrastructure, Dubrovnik, Croatia, 7-9 May 2012.
  http//www.grad.hr/cetra/ocs/index.php/cetra/cetra
  2012

42
AttachmentAn example of a regression model to
predict the cost of road works
Source Prediction model for the cost of road
rehabilitation and reconstruction works. 2nd
International Conference on Road and Rail
Infrastructure, Dubrovnik, Croatia, 7-9 May 2012
http//www.grad.hr/cetra/ocs/index.php/cetra/cetra
2012
43
Example of a regression model to predict the cost
of road rehabilitation and reconstruction
Y - the dependent variable Xi - independent
variables p - the number of independent
variables e - the residual error ?i -
regression coefficients, and ?0 - a constant
44
Methodology

• Data sample covered 94 completed or on-going road
  works contracts in Europe and Central Asia
• The correlation between independent variables was
  tested
• Four diagnostic methods were used for testing the
  dataset for outliers
• Analyses of the (square) residuals
• Standardized residuals
• Cooks distance
• Leverage matrix
• A backward analysis was used based on the removal
  of the variable with the highest p-value

45
Resulting regression models
Independent variable Coefficient Model 1 Model 2
Constant 9.912 11.088
Country specific variables TICPI 0.256
Country specific variables Climate 0.606 0.639
Country specific variables GNI 1.406x10-4
Project specific variables of local bidders -7.815x10-3 -6.662x10-3
Project specific variables Duration 0.064 0.044
Project specific variables Ln (road length equivalent) -0.367 -0.268
Project specific variables AC cost (/m3) 0.425 0.221
Dependent variable Ln (cost/km) Ln (cost/km) Ln (cost/km) Ln (cost/km)
p-value lt 0.01, p-value lt 0.05, p-value lt
0.1
46
Comparison of predicted and actual cost per km
47
Resulting regression models
Statistics Model 1 Model 2
R2 0.831 0.835
Adjusted R2 0.803 0.807
Standard error of the estimate 0.2782 0.2753
F value 29.506 30.258
Sample size 43 43
48
Cesar QueirozRoad and Transport Infrastructure
ConsultantFormer World Bank Highways AdviserTel
1 301 755 7591queiroz.cesar_at_gmail.comWashington
, DC, USA