Stake sm es in pp ippc 2014 dublin
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SMEs participation and success in Public Procurement
Johan Stake Södertörn University
IPPC 2014/08/14
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Summary
• SMEs stressed as important by the EU Commission and by local governments – procurement area of improvement
• Model SME participation by using count data model, estimating the number of bids by SMEs
• Model SME success in bidding by multinomial logit model
• Guidelines issued – do they have any effect? – Including many part contracts increase participation by small and
micro firms
– Evaluating quality (+) all firms participation, (-) probability of winning for small firms compared to large firms
– Value (+) participation for all except micro firms, (-) probability of winning for micro and small firms
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Background
• SMEs • 0-9 employees – proprietorships and micro firms
• 10-49 employees – small firms
• 50-249 employees – medium-sized firms
• >249 employees – large firms
• Account for 99 percent of all firms in EU – 52 % of total turnover
– Secured 33 % of total procurement value 2006-2008 (SBA 2011)
• European Commission adopted ”Small Business Act” to recognize SME’s local key players and employers
• Public procurement one addressed area – intention of increasing SME participation
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Background
• All firms should compete on equal terms (Directive 2004)
• Several countries use set-asides and quotas: USA, Canada, India, South Africa.
• Reasons for non-participation – Too complicated - economies of scale in bidding
– Time-consuming – administrative capacity constraints
– Contracts too large
• EU Commission issued guidelines on measures to increase SME participation (2008)
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”Best practices”
• EU Commission and SCA have published similar documents of best practices
• Gathering market information pre advertisement
• Rapidly answering questions when procuring
• Advertising early on
• Avoiding too large and extensive contracts – Low administrative costs vs more bidders?
– Divide procurements into smaller lots where possible
• Evaluating economically most preferential bid – SME proposed sector of innovation and growth
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Previous research
• Myerson (1981) and Lafonte and Tirole (1987) on optimal auction design attracted research in public procurement auctions
• Manelli and Vincent (1995) addresses the problem where the quality is unknown ex ante
• Using mechanism-design, Morand (2003) concludes set-asides are not optimal for preferential treatment
• Report by GHK (2010) found that higher value decreases SME’s probability to win, and that evaluating quality surprisingly decreases the probability of SME’s winning
• Krasnokutskaya & Seim (2011) on SME probability of winning in highway auctions when preferential treatment is used
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The data
• 20 procurements (if applicable) collected from 40 weighted and randomly selected authorities, counties and municipalities during 2007-2008
• 652 procurements, 11 236 bids
• 121 procurements use 1067 part contracts, total of 1610 contracts
• Many different goods and services, heterogenous dataset
• Mean value of contracts 21 million SEK
• Median value 1.5 million SEK
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58 % (937) contracts use evaluation of quality
Value ranges from 30 000 SEK to 4.35 billion SEK
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Bidding statistics
TABLE 1. STATISTICS ON ENTERPRISE SIZE AND BIDS
Enterprise Employees
No. of
bids
Percent
of bids
Winning
bids
Percent of
winning bids
Winning
probability
Proprietorships 0-1 2 912 25.92 579 20.35 19.88
Micro 2-9 2 206 19.63 443 15.57 20.08
Small 10-49 2 342 20.84 787 27.65 33.60
Medium 50-249 1 310 11.66 462 16.23 35.27
Large >249 2 466 21.95 575 20.20 23.32
Total -- 11 236 100 2 846 100 --
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1% of firms win 20% of procurements
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Modelling participation
• Estimate number of SME bids (count data) using a negative binomial model
• Possible endogeneity due to unobserved variables influencing SMEs decision to submit bids
• Use coarsened exact matching to improve causal inference – Finds matches to improve analysis of treatment effect
• Estimation will focus on evaluation of quality
𝜆 𝑖 = 𝑒𝐵 𝑋 = (𝛽1 + 𝛽2𝑷𝒂𝒓𝒕 + 𝛽3ln(𝑉𝑎𝑙𝑢𝑒) + 𝛽4𝑄𝑢𝑎𝑙 + 𝛽5𝑇ℎ𝑟𝑒𝑠 + 𝛽7𝑀𝑊 + 𝛽8𝑿 + 𝜀𝑖)
CPV codes are used as controls
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Micro firms Small firms
Medium-
sized firms All firms Large firms
Part procurements 0.989*** 1.009*** 0.986** 0.998 0.990
(0.00345) (0.00250) (0.00657) (0.00260) (0.00684)
ln(Value in 100000 SEK) 0.953 0.963 1.051 1.029 1.178***
(mean=0) (0.0407) (0.0388) (0.0468) (0.0260) (0.0499)
Threshold 0.862 1.089 1.212 1.019 1.201
(0.125) (0.152) (0.204) (0.0832) (0.220)
Evaluation of quality 1.285* 1.378** 1.078 1.290*** 1.578***
(0.173) (0.183) (0.175) (0.106) (0.239)
Multiple winners 1.788*** 1.810*** 2.041*** 1.921*** 2.083*
(0.315) (0.360) (0.499) (0.348) (0.873)
Constant 1.232e+12 0 0 2.129e+13 155,690
(2.348e+14) (0) (0) (2.323e+15) (3.348e+07)
Alpha 0.100*** 0 0 0.0503*** 0.0491
(0.0454) (0) (0) (0.0231) (0.148)
(Not concave)
Observations 816 816 816 816 816
CPV controls Y Y Y Y Y
Year control Y Y Y Y Y
chi2 - - - - -
p - - - - -
Coefficients in incidence rate ratios ; seEform in parentheses; *** p<0.01, ** p<0.05, * p<0.1 11
Results for participation Note: coefficients are in incidence-rate ratios (multiplicative)
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Modelling probability to win
• Estimate probability of winning using MNL model
• Modelled as procurer choosing between different firms to maximize utility
• Four different outcomes, choice of firm is: • Micro
• Small
• Medium
• Large
• All firms have the same basic probability of winning (1/n)
• Same variables as participation estimation except multiple winners
• Observation=contract, clustered on procurement
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Probability of winning Coefficients in relative risk ratios
Negative effects
Positive effects
Multinomial logit Micro Small Medium
(default)
Large
2-4 part procurements 1.171 1.499 0.490 -
(0.520) (0.737) (0.292)
5-10 part procurements 1.925* 1.632 1.315 -
(0.764) (0.856) (0.570)
>10 part procurements 2.964** 4.815** 0.943 -
(1.518) (2.997) (0.556)
ln(Value) 0.862* 0.865* 1.055 -
(0.0760) (0.0761) (0.101)
Threshold 0.517 0.625 0.584* -
(0.239) (0.241) (0.191)
Evaluation of quality 0.626 0.323*** 0.715 -
(0.181) (0.106) (0.279)
Bidratio micro firms 1 (0) - - -
Bidratio small firms - 1 (0) - -
Bidratio medium firms - - 1 (0) -
Observations 1,006 1,006 1,006 1,006
CPV controls X X X X
Log-Likelihood -843.8 -843.8 -843.8 -843.8
Chi2 55057 55057 55057 55057
p 0 0 0 0
Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1
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Summary
• Evaluating quality significantly increases participation for micro, small and large firms – More firms are willing to submit bids because they might know
that they are not the cheapest but have a chance due to good quality
• Including relatively many part procurements increases probability of micro and small firms to win contracts – No significant effect on medium-sized firms
• A larger procurement value decreases micro and small firms probability to submit a winning bid
• Evaluation of quality decreases small firms probability to win – Micro firms significant at 89% level
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