SMEs participation and success in Public Procurement

Johan Stake Södertörn University

IPPC 2014/08/14

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

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

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)

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

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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