1. Public Procurement of
Homogeneous Goods:
an Empirical Study
Jan Soudek & Jiří Skuhrovec, Charles University, 8/2014
Honza.soudek@gmail.com , jskuhrovec@gmail.com
2. Outline
• Introduction
• Motivation & literature review
• Hypotheses & model
• Data description
• Results & discussion
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3. INTRODUCTION: SIZE OF THE MARKET
& INSTITUTIONAL FRAMEWORK
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4. Public procurement to GDP (2011)
Source: OECD: Government at glance 2013
In case of CZ, it is app. 16% of GDP
(excluding SOE and utilities, then it would be around 25%)
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0%
5%
10%
15%
20%
25%
5. Institutional framework
• 3 basic procedures of tendering
• Open – The most transparent, everyone can apply for
that procurement
• Restricted – Procurer chooses potential suppliers
• Negotiated – Procurer can ask just one firm to supply
it‘s demands.
• 2 basic formats
• Sealed bid auction - send an envelope
• Electronic auction - a tool allowing repetitively adjust
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6. Procurement (auction) theory
• Procurement procedure:
• standardized, trading mechanism
• subject of trade is known ex ante
• Thus auction theory is applicable
Evaluation process
Bid 3
Bid 1
Bid 2
Winner
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8. Motivation
• What determines the final price in public procurement?
Market price? Sure, but what about:
• Chosen procedure
• Competition
• Auction format
• Our goal: show where institutional and procedural
characteristics matter in the public procurement.
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9. Previous research on matter
• Domberger et al (1995): „The Determinants of Price and Quality in Competitively
Tendered Contracts “ EJ 1995
• Model:
• Conclusion:
• While competition reduced price significantly, quality of service was maintained or even
enhanced.
• The evidence does not support the hypothesis that efficiency gains are traded off for
lower quality.
• Bandeira et al (2008): „Active and passive waste in Government spending:
Evidence from a policy experiment“ AER 2009
• Model:
• Conclussion:
• Some public bodies pay systematically more than others for observationally equivalent
goods and such price differences are sizeable;
• Differences are correlated with governance structure: the central administration pays at
least 22% more than semi-autonomous agencies (local government is at an intermediate
level)
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10. Theoretical background -
Auction theory says:
• Assuming standard auction with interdependent
signals:
• With # of bidders the price (in average) goes down
(Bower (1993), Bulow&Klemperer (1996))
• Open procedure = competition leads to better results
than negotiation (Bulow &Klemperer (1996))
• Electronic auction = English auction results are at least
as good as first price sealed bid auction - regular
„envelope“ procedure (Milgrom&Weber (1982))
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11. Our research hypotheses
H1: The final unit price of the procurement is affected
by the type of procurement procedure.
H2: The final unit price of the procurement is a
decreasing function of an number of bidders.
H3: The usage of electronic auction is decreasing the
final unit price of the procurement.
H4: The final unit price of the procurement is affected
by the type of the contracting authority.
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12. Model
1. In order get comparable prices, only PP of homogeneous goods is
analyzed – electricity, gas
We can get the unit prices and compare them with actual market
price (1 year forward contract)
Moreover, we compare with estimated value per unit – which
captures for potential heterogeneity of tendered goods and for
procurers willingness to pay
2. We use a natural logarithmic form of final unit price as a dependent
variable to capture relative effects
3. To control for possible „wasteful behavior“, we use zIndex;
a composite index that rates procurers according to quality and transparency
of all their procurement competitions over given period of time.
𝑙𝑜𝑔 𝑓𝑖𝑛𝑎𝑙 𝑢𝑛𝑖𝑡 𝑝𝑟𝑖𝑐𝑒 = 𝛼 + 𝛽1 𝑙𝑜𝑔 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑢𝑛𝑖𝑡 𝑝𝑟𝑖𝑐𝑒 +
𝛽2 𝑙𝑜𝑔 𝑚𝑎𝑟𝑘𝑒𝑡 𝑢𝑛𝑖𝑡 𝑝𝑟𝑖𝑐𝑒 + 𝛽3 𝐷𝑈𝑀𝑀𝑌 𝑝𝑟𝑜𝑐𝑒𝑑𝑢𝑟𝑒 + 𝛽4 𝐷𝑈𝑀𝑀𝑌 𝑒𝑙𝑒𝑐𝑡𝑟𝑜𝑛𝑖𝑐 𝑎𝑢𝑐𝑡𝑖𝑜𝑛 +
𝛽5 𝐷𝑈𝑀𝑀𝑌 𝑎𝑢𝑡ℎ𝑜𝑟𝑖𝑡𝑦 + 𝛽6 𝑏𝑖𝑑𝑑𝑒𝑟𝑠 + 𝛽7 𝑧𝐼𝑛𝑑𝑒𝑥 + 𝛽8 𝑡𝑖𝑚𝑒 + 𝜖
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18. Results
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Dependent variable:
log(final price/kWh)
Electricity Gas
Explanatory variable OLS ß Robust SE OLS ß Robust SE
log (estimated price/kWh) 0.43 (0.09) *** 0.41 (0.11)***
log (market price/kWh) 1.03 (0.19) *** 0.15 (0.09)*
Open procedure -0.07 (0.04)* 0.08 (0.06)
electronic auction -0.12 (0.03)*** -0.15 (0.06)**
number of bidders -0.015 (0.008)* -0.03 (0.01)*
Constant -0.10 (0.07) -0.11 (0.08)
R-squared 0.54 0.52
Table 2: Electricity & gas procurement results, note: dropped dummy is negotiated procedure
19. Results - regression with
insignificant variables
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Dependent variable:
log(final price/kWh)
Electricity Gas
Explanatory variable OLS ß Robust SE OLS ß Robust SE
log (estimated price/kWh) 0.41 0.1*** 0.49 0.11***
log (market price/kWh) 1.01 0.23*** 0.1 0.12
Open procedure -0.08 0.04* -0.03 0.018
electronic auction -0.16 0.04*** -0.13 0.07*
number of bidders -0.016 0.008* 0.09 0.07
zIndex -0.14 0.94 0.27 1.01
Time 0.00003 0.00004 0.00009 0.00010
State owned enterprises -0.016 0.07 0.28 0.17
Public bodies 0.002 0.09 0.19 0.19
Regional auth. 0.06 0.08 0.2 0.18
Constant 0.13 0.17 -0.48 0.25*
R-squared 0.55 0.59
Table A-1: Electricity & gas procurement results – including Procurers, note: dropped dummies are
negotiated procedure and regional authorities
20. Discussion
• Final price rises by 0.4 % with 1 % rise in estimated price. Signalling?
• Open procedure reduces cost of electricity by 7 % in average, for gas it is insignificant.
• E-auction reduces cost of electricity by 12 % in average (cumulative with Open
procedure!), gas by 15 %.
• Additional bidder causes in average a 1 % fall in the final price of the electricity and
1.5 % fall in final price of gas
• We did not find any statistically significant difference in final prices with respect to the
various types of contracting authority.
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21. Policy implications
• Buyer should identify the estimated price well, not
overshoot. It signals:
• price expectation
• willingness to pay.
• Electronic auction shows to be most efficient. Use it.
• 12 % average price reduction
• Low additional procedure costs (10.000 CZK = 400 €)
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