BIDDING FOR PUBLIC INFRASTRUCTURE PROJECTS IN FIRST-PRICE
SEALED BID AUCTIONS OF DUTCH MUNICIPALITIES: WELFARE
IMPLICATIONS OF MINIMUM REQUIREMENTS
February 21, 2011
This Version: May 11, 2011
Sander Hardeman1 and Arno J. van der Vlist2*
1
2
Economic Institute for Construction and Housing, Amsterdam, The Netherlands
Department of Economic Geography, Faculty of Spatial Sciences, University of
Groningen, The Netherlands. E-mail: [email protected]
_____________
*
Corresponding author
1
BIDDING FOR FIRST-PRICE SEALED BID INFRASTRUCTURE TENDERS
OF DUTCH MUNICIPALITIES: WELFARE IMPLICATIONS OF MINIMUM
REQUIREMENTS
ABSTRACT. This paper adds to the empirical literature on first-price sealed bid public procurement
tenders by considering the welfare implications of minimum requirements in public procurement tender
designs. Minimum requirements may relate to experience, financial qualifications and technical
qualifications, and limit those firms which are eligible to bid. In the paper, we argue that firms do not
randomly bid for work, and that the decision to bid to an extent depends on the procurement design. If
this is true, changes in the procurement design will affect participation and hence the outcome of the
first-price sealed bid public procurement tender process. Whether setting minimum requirements
results in improved welfare depends on both the outcome and the transaction costs. We consider here
first-price sealed bid infrastructure procurement tenders with a range of minimum requirements. Using
information on firms' bidding behaviour in response to public procurement tenders issued by Dutch
municipalities for infrastructure projects, this paper shows empirically that the specific procurement
design affects a firm’s likelihood of participating and that this has implications for the size of the bid.
Setting more stringent minimum requirements results in fewer and higher bids. Our analysis indicates
that the welfare implications of setting minimum requirements varies with the ex post project size. For
small works, a reduction in minimum requirements -by setting minimum requirements equal to the
level of the first quartile rather than the median- leads to an average decrease in welfare of 0.7 per cent
of the project size. For large works, a similar reduction leads to an increase in welfare of 7.0 per cent of
the project size. Our welfare analysis indicates that if infrastructure procurement tenders set optimal
minimum requirements this will increase welfare by up to 4 per cent of total value, or €10.9 million on
500 projects worth a total of €317 million.
Keywords: first-price sealed bid auction, public procurement, infrastructure works
JEL-code: J33, J41, R29
2
1. INTRODUCTION
In this paper, we investigate the consequences of setting minimum requirementsi in tender
designs for public infrastructure work procurement for both the bidding process and the
tender outcome. This question is related to a large theoretical body of literature on first-price
sealed bid auctions that attempts to explain the relevance of procurement design. The
theoretical literature indicates that these aspects are of vital importance to public procurement
governance and to sustaining competition (for a literature review, see Klemperer, 2004).
Further, the literature indicates that public procurement tender design is of practical
importance since it affects the degree of competition and the value for money in public
procurement tendering practice. The literature on the public procurement of infrastructure
indicates an apparent concern over limited competition among firms (De Silva et al., 2003;
Estache and Iimi, 2008; 2009a). The effect of competition tends to be that fewer bidders for
infrastructural works results in higher bids (De Silva et al., 2009). This is particularly relevant
in markets characterised by an inelastic demand, a limited number of bidders and repeated
price competitions or multimarket contacts (see Gupta, 2002) for private value tenders (see
De Silva et al., 2009). Setting minimum requirements may prevent some firms from bidding.
The OECD general guidelines (OECD, 2010) for public procurement tendering (contrary,
however, to the ADB guidelines (ADB, 2010)) therefore stress not creating obstacles to
participation. Nevertheless, from a social welfare perspective, setting minimum requirements
might be an optimum situation given that firms preparing bids incur transaction costs (see
Solino and Santos, 2010). The empirical literature on infrastructure procurement that focuses
on competition and procurement outcome has largely ignored the welfare implications of
setting minimum requirements in public procurement tender design. This neglect of tender
design for the first-price sealed bid procurement of infrastructure is rather surprising given the
specific characteristics of the market, and the largely standardised and fully specified
procurement prescriptions (in which the materials and working drawings are fully described,
and available to all bidders). This paper contributes to a deeper understanding of minimum
requirements from a welfare perspective. In the current paper, we first show that a firm’s
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decision to participate depends on the design of the public infrastructure procurement tenders.
Our second, and most significant, finding is that our results indicate that setting minimum
requirements does lead to higher bids and thus to higher expenditure on infrastructure. Armed
with these results, we present the welfare implications associated with setting minimum
requirements in the design of public procurement tenders. The paper is structured as follows.
Section 2 outlines the typical design of public procurement tenders for infrastructure. Section
3 then provides the theoretical background, followed by Section 4 which describes the data
we collected. In Section 5, we present the empirical model used to analyse the extent to which
the procurement design affected the decision by firms to bid. In this, we jointly model the
participation and bidding decisions within a Heckman selection framework. Next, Section 6
presents results of our estimations of the welfare implications, with minimum requirements
discussed in Section 7. Finally, Section 8 offers concluding remarks.
2. MINIMUM REQUIREMENTS IN DUTCH PUBLIC PROCUREMENT TENDERS
The Dutch tender design for the public procurement of infrastructure includes a choice of the
type of procedure to be followed, the award criteria and certain minimum requirements.
Figure 1 indicates the various options in the procurement designs.
Figure 1 here
Figure 1 indicates that the procurement process design starts with the choice of which type of
procedure to follow: open procurement, restricted procurement or other procurement
approaches such as competitive dialogue and negotiations. First, a choice has to be made
between open, restricted and other procurement forms. If an open procurement is chosen, then
a choice has to be made between lowest price and most economically advantageous award
criteria. The former means that the contract will simply be awarded to the lowest bidder. In
the latter, the contracting authority places a value on a number of pre-specified criteria,
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covering quality aspects such as planning, pollution reduction or other social goals, and the
contract will be awarded to the contractor who makes the most economically advantageous
bid. Subsequently, minimum requirements can be added relating to experience, financial
qualifications and technical requirements (see also ADB, 2010).
Required experience qualifications – requirements relating to experience generally include a
specified number of infrastructure works previously completed by the firm within a given
time frame. Experience requirements can vary in the number of works, the project type and
the time span.
Financial qualification requirements – financial qualifications relate to the financial
performance of the firm. The most common financial stipulation requires the annual turnover
of the bidding company to be above some threshold, usually averaged over the last three
years.
Technical qualification requirements – these requirements relate to a firm’s production
process standards. The stipulated minimum requirements relate to specific certificates, usually
ISO 9001 (certifying that formalised business processes are being applied) or VCA
(concerning the health and safety aspects of operations).
3. THEORETICAL BACKGROUND
In this paper, we are considering a market in which municipalities’ procurement officers
announce open public first-price sealed bid (or lowest price) infrastructure procurement
tenders with varying minimum requirements. These announcements typically include bid
documents such as specifications and drawings, reports of investigations into site conditions
and information on minimum requirements. Upon receipt, each firm in the market decides
whether or not to bid for the infrastructure project. Firms may decline to bid because either
they are not eligible or, when eligible, for other reasons. Each eligible firm that decides to bid
submits a sealed bid before a specified deadline. The tender-specific construction costs are
firm-specific because of differences in distance to location, and degree of utilisation of
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capacity. The capacity or size of the firm may determine construction costs because large
firms are more often vertically integrated and self-supporting in terms of physical inputs such
as gravel, asphalt and concrete for civil engineering works. Minimum requirements do
influence the decision to bid, but note that they inherently neither raise construction costs for
the infrastructure project, nor necessarily the ex post quality of the work. As such, minimum
requirements can be considered as amounting to eligibility rulesii. As first-price sealed bid
procurement tenders typically fully specify the materials, with fully described working
drawings available to bidders, minimum requirements do not alter the ex ante quality of the
work either. Further, since a list of recipients is not available to bidders, the degree of
competition is unknown ex ante. Furthermore, neither a reservation price nor an entry fee is
announced, nor any engineering cost estimates provided. In first-price sealed bid public
procurement procedures, the firm with the lowest price is awarded the project.
The strategy of firm i = 1…I for tender t = 1…T is to set its bid value bit so as to maximise
the expected profits, denoted by π it (bit ) . Clearly, a higher bid is associated with a higher
mark-up (bit − cit ) over construction costs, cit , but also associated with a lower probability of
being successful, ϕ (bit ) . In determining the bid value, a firm makes a trade-off between the
mark-up over construction costs, and the probability of winning. Formally, the decision can
be expressed by:
(3.1)
Max
b
π it (bit ) = (bit − cit )ϕ (bit ) .
The optimal bid value bit* is determined by the first order condition, and hence
∂π it (bit ) / ∂bit = 0 or
(3.2)
ϕ (bit ) + ϕ ' (bit )(bit − cit ) = 0 with ϕ ' (bit ) = ∂ϕ (bit ) / ∂b .
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It can be shown that, for private value tenders, a competition effect exists, with
ϕ (bit ) + ϕ ' (bit )(bit − cit ) = 0 , and the expected revenue from the first-price sealed bid for
'
tender t, denoted by ϕ (bit ) = ∂ϕ (bit ) / ∂b , is such that ∂Ε[b* ] / ∂I < 0 (see De Silva et al.,
2009).
Proposition 1: Minimum requirements reduce the number of bidders raising the bid value.
Proof. The introduction of minimum requirements amount to a truncation of the distribution
of potential bidders with N < I such that expected revenue of the tender is such that
Ε N < I [b* ] > Ε I [b* ] . ■
Proposition 2: The welfare implication of setting minimum requirements is ambiguous.
Proof. The change in social welfare, ∆SW , associated with a change in the number of bidders
N < I , is such that
(3.3)
∆SW (bit ) = ∆Ε(b*) − ∆TC ,
with ∆TC the change in transaction costs involved in preparing a bid associated with a
change in the number of bidders. As ∂Ε(b*) / ∂I < 0 and ∂TC / ∂I > 0 the resulting effect is
ambiguous. ■
We test for the central hypothesis conditional on a set of regressors. A summary of the
hypothesised signs regarding the influence of the parameters, based on a literature review, is
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given in Table 1, both for the determinants of participation and for bids in infrastructure
procurement tenders.
Table 1 here
From Table 1, it seems that setting technical requirements decreases participation (Estache
and Iimi, 2009a) with bids decreasing in terms of the number of bidders (Gupta, 2002; De
Silva et al., 2009; Estache and Iimi, 2009a). Further, on the basis of the literature we
hypothesise that increasing market opportunities, as indicated by a larger backlog (unfinished
work), or a rising number of permits issued, decreases participation and increases bid values
(see Gaver and Zimmerman, 1977; De Silva et al., 2009). Also, repeated competition, or socalled multimarket contacts, increases the value of bids (Gupta, 2001).
4. DATA AND VARIABLES
The data on infrastructure procurement tenders were collected from files on public
procurement tenders for infrastructure works at municipalities in the Netherlands. These
tenders are officially announced in newspapers and on the Internet. The data include
information on the name, address and contact details of the contracting authority, the agency
that can provide further information, procedural information on minimum requirements and
tender attributes of the civil work such as the type of work, location and duration. In addition,
the data stored include information on the number of bidders, details of the bidders and the
associated bids. The data we extracted related to public open first-price sealed bid (i.e. lowest
price) procurement tenders for civil work posted by Dutch municipalities between January
2009 and May 2010. In total, in that period, Dutch municipalities organised 2,025 public
procurements that included infrastructure projects. For this paper, we selected works for
which we could obtain full information on the procurement design, the bidding process and
the bidders. As such, we considered bids from contractorsiii only, excluding the bids from
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agricultural service suppliers or landscape engineering consultancies for which we do not
know the overall population or any information on the sizes of the firmsiv. Through this
process, we ended up with information on 3,369 bids from 466 contractors related to 500
procedures from 157 municipalitiesv. Total ex post value of the 500 tenders was €317 million.
Information on the backlog of work in the infrastructure sector in the Netherlands comes from
CBS statistics. Descriptive statistics of the data are given in Table 3.
Public procurement tenders by municipalities for infrastructural work mostly relate to typical
infrastructure works such as bridges and roads. Indeed, from Table 3, one observes that over
70 per cent of public procurement tenders are related to infrastructure such as bridges,
tunnels, roads and cable-laying. The remainder relate to other landscaping and real estate
development-related projects. These works typically relate to spatial transformations,
generally reconfiguring agricultural land for other uses. For our analyses, we divided the 500
tendering procedures into three types based on CPV45 categories.
The data in Table 3 indicate the heterogeneity in the infrastructure tenders ex post (in terms of
bid value). The distribution of the sizes of infrastructure works ex post is given in Figure 2.
From Figure 2, one observes that the majority of tenders (six out of ten) are between
€200,000 and €750,000. Three out of ten tenders are over €750,000 with the maximum ex
post size being €8,876,000.
Figure 2 here
In terms of analysis, the significant variance in the bid values raises concerns regarding
heterogeneity in terms of size within each type of work. To allow for this heterogeneity
within the work types, we constructed four type-specific size groups. That is, for each type of
work, we constructed four size groups with the size boundaries set such that roughly the same
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number of tenders fell within each category. Note that, since ex ante information on the
estimated value of projects is generally unavailable as engineering cost estimates are typically
not announced, we classified works into these various type-specific size classes based on the
median bid value. The result is a classification into small, medium, large and very large
projects by type. Table 4 gives a breakdown of the bids by type and size class.
Table 4 here
Further, note that there is significant heterogeneity in the degree of competition as reflected in
the number of bidders. From Table 3, one observes that the mean number of bidders is 11,
with the number of bidders ranging from 1 to 23 for individual tenders. Figure 3 gives the
distribution of number of bidders for the sample. Here, one observes that the distribution of
the number of bidders is skewed. Note also, that for one in ten tenders less than four firms
bid, raising concern regarding the level of competition (see Porter and Zona, 1993; Gupta,
2002). In six out of ten tenders, four to eleven firms bid. More than eleven firms bid for three
out of ten tenders, and this raises concerns about the associated transaction costs. The median
number of bidders was seven.
The locations of firms bidding suggest a spatially segmented market. The distribution of
distancevi is given in Figure 4. Here, one observes a distance decay function, with the
probability of bidding decreasing with distance. The mean distance was 35 kilometres, with a
median distance of 30 kilometres. Less than 5 per cent of the bids were from contractors
based more than 70 kilometres from the workvii.
Figure 4 here
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Potentially, the number of firms bidding may relate to the business cycle or the number of
market opportunities currently available, as reflected in the backlog and in the number of
forthcoming public procurement tenders. The backlog (as unfinished work in number of
months) for the infrastructure sector is given in Figure 5. Here one observes a dip in April
2009 and one in January 2010. The number of forthcoming public procurement of
infrastructure works is given in Figure 6. Here one observes dips in July 2009 and in January
2010.
Figure 5 and 6 about here
A firm’s bid value may potentially relate to limited competition among bidders through
repeated price competitions or multimarket contacts. Multimarket contacts among firms arise
when firms repeatedly come up against the same competitors in tendering procedures. Here,
we use a measure for multimarket contacts proposed by Gupta (2001), denoted by REL, for
tender t with
i=I
(4.1)
RELt
∑
=
i =1
RELi
I
with RELi = Nbi / Npi , where Nbi is the total number of different firms competing with
firm i=1…I over all public procurement tenders firm i is participating in, and Npi the total
number of bids in all of the public procurement tenders that firm i is bidding for in the
observation period. As such, if firm i faces the same competitors in all the procurements it is
bidding for, Nbi is limited to the number of competitors, Npi increases with the number of
procurement tenders, and the indicator will approach 0. Conversely, if firm i faces different
competitors in all the procurements it is bidding for, both Nbi and Npi are equal to the total
number of bids in all procurement tenders together and REL equals 1. Our analysis
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summarised in Table 3 indicates that for ten public procurement tenders, firms on average
come up against 49 different firms (REL = 0.44) out of 112 bidders, i.e. if they bid in response
to ten public procurement tenders where on average 11.2 bids are submitted each. The full
distribution of REL is given in Figure 7. From Figure 7 one observes that multimarket
contacts are abundant. The probability mass on the very left indicates that if bidders
participate in ten public procurement tenders, they would on average, come up against 25
different firms (out of in total 112 bidders). Further, one observes that the probability of
meeting all different competitors in all public procurement tenders a firm is bidding for is 0.
Finally, we describe the minimum requirements for bidding in response to public procurement
tenders, the subject we are particularly interested in. We describe, in turn, the minimum
requirements set relating to experience, financial requirements and technical qualifications.
Required experience
Experience qualifications relate to previous work on similar projects and are specified in
terms of a number of projects, of a specific type and within a given time span. The minimum
experience requirements become harder to satisfy as the number of projects demanded
increases, their specificity increases and the allowed time frame decreases. Here, the
multidimensional nature of the experience requirements is summarised in a single measure r
that indicates the minimum experience requirements relative to the number of public
procurement tenders issued in the period of observation. Formally:
(4.2)
r ( size, type, q, period ) =
q
,
period × h( size, type)
where q is the required number of projects of a given size in period, h(.) is the number of
public procurement tenders issued of a given size and type, and period the time span
considered. Equation (4.1) is such that
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∂r (.) / ∂q > 0 , ∂r (.) / ∂h(.) < 0 and ∂r (.) / ∂period < 0 . The lower the proportion of
existing projects that meets the specified requirements, the harder it becomes to satisfy the
experience qualification requirements.
The required number of projects q varies between zero and three. On average, the size of the
required reference projects is 68% of the ex post project size. For small projects, below
€100,000, the average required project size is 73% of the ex post project size, for projects
above €2 million, it is only 36%. While the reference project size, relative to the tendered
project, decreases with project value, meeting the requirement becomes harder simply
because there are fewer large projects on which potential bidders could have worked in the
past, captured by h(.). From Figure 8, one can observe that eight out of ten projects are larger
than €200,000 and we could see this as a reference if the minimum requirement is set at
€200,000 with no specific types of work experience being required. If requirements with
regard to the type of work are added, then only two to four out of ten projects of this size will
potentially qualify as ‘experience’. If the size threshold were to be set at €1 million, only one
out of ten projects would qualify as relevant experience.
Five years is commonly seen as a reference period, and this would result in a corresponding
r(.) of 2.4 if previous experience on two projects is required, each with a value of at least €1
million and without a further specification of the type of work.
This multidimensional nature of the experience requirements is summarised in a single
measure r that indicates the minimum experience requirements relative to the number of
public procurement tenders issued in the period of observation. From Figure 9 one can
observe that minimum experience requirements r(.) increases with project size. Seven out of
ten projects with an ex post project value below €100,000 set experience requirements at an
equivalent r(.) value below 2.0, which, for example, for a Type-I project would correspond to
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accomplishing three similar projects worth at least €100,000 each in the past three years. Five
out of ten projects with an ex post project size above €2 million set experience requirements
at an equivalent r(.) value of above 5.0, corresponding to having accomplished one project of
any type costing more than €2 million in the last five years.
Financial Requirements
From Figure 10 one observes that financial qualification requirements included in tenders, in
terms of the annual turnover relative to the project size, decrease with the ex post project size.
Small projects set rather strict minimum requirements. Six out of ten tender specifications for
work up to €100,000 set minimum requirements in terms of annual turnover. The median
minimum requirement is 300-400 per cent of the project size. Two out of ten procurements
ask for over 500 per cent. For the very large projects, the median minimum annual turnover
requirement is much smaller at 100-200 per cent of the project size.
Figure 9 here
Technical requirements
Technical qualification requirements relate to a firm’s production process standard. From
figure 11 one observes that the share of procurement tenders with technical requirements
increases with project size. In projects with an ex post value of less then € 100,000, five out of
ten tenders requires technical qualifications. In projects with a value of more than € 1 million,
seven out of ten procurement tenders require technical qualifications.
Figure 10 here
5. EMPIRICAL MODEL
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We now formulate a framework to model the effect on bidding behaviour of setting minimum
requirements in open public procurement tenders. We test whether having minimum
requirements in first-price sealed bid public procurement tender designs results in fewer
bidders and in a higher bid value. Note that the bid bit of bidder i=1…I and public
procurement tender t=1…T are only observed for those firms actually bidding, with both the
decision to participate yit* and the observed bid bit* latent variables. Using a Heckman sample
selection model based on these two latent variables (Heckman, 1979), the empirical model for
bidder i=1…I and public procurement tender t=1…T is:
(5.1)
yit* = f ( MIN t , X it ) + ε 1it
(5.2)
bit* = g ( Z it ) + ε 2it
where the tender-specific minimum requirements are denoted by MIN t , and vectors of
observable and exogenous variables denoted by X it , and Z it for the participation and
bidding equations, respectively. The error terms are assumed to be ε 1 ~ N (0, σ ) and
ε 2 ~ N (0,1) with correlation ρ the correlation between ε 1 and ε 2 . Estimation results that
address whether minimum requirements reduce the number of bidders raising the bid value of
Proposition 1 are discussed in Section 6.
The estimates from the model defined in (5.1) and (5.2) will be used in the welfare analysis of
setting minimum requirements in public procurement tendering procedures of Proposition 2.
For this, we predict participation and expected outcome for various representative public
infrastructure procurement tenders. As we assume no relationship between minimum
requirements and ex post work quality in first-price sealed bid tenders, the welfare analyses
relate to changes in the mean bid and changes in transaction costs associated with various
minimum requirements of equation (3.3). We consider three representative procurement
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tenders: a small tender (€150,000), a medium-sized tender (€700,000) and a large tender
(€2,500,000). For each of these representative tenders, the change in transaction costs
associated with a change in the number of bidders is compared to the change in the mean bid
value. The welfare effects are presented in Section 7.
6. ESTIMATION RESULTS
In Table 5, we now present the estimation results for the effect of setting minimum
requirements on firms' bidding behaviour. The Wald Chi square test statistic suggests joint
significance of the model.
Table 5 here
From Table 5 one observes that the estimation results for the Participation model indicate that
setting minimum requirements discourages some firms from bidding. This is in line with the
findings of Estache and Iimi (2009a) who considered the effect of technical qualification
requirements. Our results allow us to generalise their result as the various minimum
requirements we set consistently indicate a statistically significant negative effect on
participation. Hence, the higher the minimum experience requirements, the lower the number
of bidders. The same holds true for minimum financial requirements and technical
qualifications. Thus, minimum requirements form an effective control and regulate entry into
public tendering processes and thus are an important moderator in open public tender design.
Note that the insignificance of lambda (t=1.642) indicates that unobserved factors that makes
participation more likely do lower the bid value, yet statistically insignificant from no
effectviii.
The results of the Participation model further indicate that distance matters. Firms do not
randomly participate in first-price sealed bid infrastructure procurement tenders. Consistent
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with the literature, we find that the greater the distance to the offered work the lower the
participation rate (see De Silva et al., 2009). One explanation is that the volume-intensive and
thus costly production inputs such as sand and concrete may create an increasing
disadvantage with distance to the job. It may also relate to the disutility of commuting for
blue collar workers (see Van Ommeren et al., 2006). Firms at longer distance to the work may
thus expect to have a comparative disadvantage and consequently decide not to participate.
The important implication of this is that competition is limited across space and relate to
geographic submarkets that partly overlap (for a theoretical exposé see, Beckman, 1999).
Market opportunities also play a role. We find that a rising backlog of work can be associated
with significantly lower participation rates. This supports the literature that finds a negative
effect of a backlog on participation, although we would add that the literature is not
unambiguous, which may relate to the type of tender being considered or the measure used.
De Silva et al. (2009) found a negative effect of backlog on participation for bridges and other
civil work tenders, but not for road tenders (see also Estache and Iimi, 2009a; 2009b). The
literature suggests that a backlog may have no effect or a negative effect, but positive
relationships have not been found. From a substantive point of view this makes sense. Civil
engineering firms can be divided into firms that specialise in supervision, planning and
project management (for which large backlogs do not make any difference to their bidding
strategy as most work is subcontracted to other firms), and those firms that specialise in the
actual construction of roads and tenders (for which a large backlog can be associated with
reduced participation given their limited construction capacity) (see Pries and Janzen, 1995).
Another important finding is that the number of procurement tenders issued has a statistically
significant negative effect on the decision to participate. This may relate to a firm’s limited
capacity to prepare bids in a given time span. Future research could consider this in greater
detail as it suggests that, in reality, municipalities may be competing for bidders. As such,
municipalities may wish to consider regionally coordinating public infrastructure tenders to
use construction capacity efficiently.
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We will turn now to the effect of setting minimum requirements on bidding behaviour using
the Bidding model. In considering this in more detail, we focus on the number of bidders
parameter. The number of bidders is the market aggregate of all the individual firms’
decisions to participate. The estimation results are shown in the lower half of Table 5 and
indicate that there is a negative and statistically significant effect of the number of bidders on
the associated bid value. This finding is in line with our theorising where we argued that
minimum requirements reduce competition and raise bids. As such, setting minimum
requirements has implications for welfare at large. Hence, even if a municipality’s
procurement officer is largely indifferent to the choice of tender design, as no direct link
between minimum requirements and ex post quality has been suggested in the literature,
society at large is clearly not indifferent. These welfare issues will be considered in Section 7.
The results further indicate that bids increase with distance. This implies that firms at greater
distances have higher costs, and indeed a comparative disadvantage, compared to firms that
are relatively close by. Note that the literature is again ambiguous on the interplay between
distance and bid. Bajari and Ye (2003) and De Silva et al. (2009) find a positive relationship
for road projects, but no effect of distance on bids for bridge works.
Further, the results indicate that greater sectoral backlogs are associated with higher bids. This
makes sense. If backlogs are approaching the full capacity of contractors, marginal costs will
increase thereby raising the associated bids observed. The relationship between firms having
multimarket contacts and bid value seems to be positive if anything, although the result is not
statistically different from there being no effect.
7. WELFARE EFFECTS
To determine the welfare effects of changing minimum requirements we consider our three
representative public procurement tenders. For each of these tenders we start from the median
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minimum requirements (see Figure 3). We then create two scenarios: Scenario A where there
is a decrease in the minimum requirement in terms of technical and financial requirements to
the level of the first quartile, and Scenario B where there is a similar increase to the level of
the third quartile. These scenarios are further outlined in Table 6, and the results of our
welfare analyses are given in Table 7.
Table 6 here
Table 7 here
The figures in Table 7 indicate that the welfare implications associated with setting minimum
requirements vary with project size. For small works, a reduction in minimum requirements
leads to a decrease in welfare equivalent to 0.7 per cent of project size. For large works a
similar reduction leads to an increase in welfare of 7.0 per cent of project size. Our welfare
analysis indicates that, if infrastructure procurement tenderers were able to set optimal
minimum requirements given our scenarios, this would increase welfare by an average of 4.0
per cent of project valueix, or €10.9 million on the €317 million value of the 500 projects
considered.
8. CONCLUSIONS
The relationship between the design of public procurement tenders and the bidding outcome
has attracted a lot of theoretical attention in auction literature. In that literature, empirical
studies on the welfare effects of tender design in European infrastructure procurements are
thin on the ground. The first aim of this paper was to show that tender design matters. Firms
do not randomly bid for work: the decision to bid depends to an extent on the tender and the
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minimum requirements listed. The second aim of the paper was to demonstrate the interplay
between public procurement tender design and tender outcome. By analysing data on firstprice sealed bid public procurement tenders for infrastructure works by Dutch municipalities
between January 2009 and May 2010, we were able to statistically show that setting
increasingly severe minimum requirements does deter firms from bidding. This is what one
would intuitively expect. Furthermore, we find that setting minimum requirements leads to
higher bid values as a result of there being fewer bidders. Hence, even if municipal
procurement officers may be largely indifferent to the procurement tender design, as no direct
link between minimum requirements and ex post has been suggested in the literature, society
at large is certainly not indifferent. We therefore conclude that the design of municipalities’
public procurement tenders has strong implications for public policy regarding the provision
of public goods to taxpayers. Our welfare analysis indicates that the welfare implications of
setting minimum requirements vary with the project size. For small works, a reduction in the
minimum requirements -by setting minimum requirements equal to the level of the first
quartile rather than the median- leads to a decrease in welfare equivalent to 0.7 per cent of
project size. For large works a similar reduction leads to an increase in welfare of 7.0 per cent
of project size. Further, our analysis indicates that if infrastructure procurement tenders were
able to set optimum minimum requirement this would increase welfare by up to 4.0 per cent
of total value, amounting to €10.9 million on the €317 million value of tenders in the 500
projects investigated. If this value applied to all the infrastructure goods and services publicly
procured within the EU, which accounted for 2.5 per cent of the €12,000 billion GDP in 2009
- this would amount to a welfare gain of some €12 billion annually.
20
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21
TABLES AND FIGURES
Figure 1 Alternative Public procurement designs
22
De Silva et al.
(2009) (asfalt)
De Silva et al.
(2009) (bruggen)
Estache & Iimi
(2009a)
Estache & Iimi
(2009b)
Participation
Participation
Number of
participants
Participation
Table 1 Review of the literature on Infrastructure Procurement Participation
Dependent variable
Independent variable
Technical requirements
-Engineering cost estimate
+
o
+++
o
Size of the work
Number of project components
-o
Multiple physical properties (e.g. length,
+/o/- o/-lanes)
Number of days to complete the project
-++
o
Type of work
+/o/Size of the firm
++
++
Backlog
o
----/o o
Distance to work
----Bidders with on-going projects in region
+++
++
Number of plan holders
---Seasonally unadjusted unemployment rate
o
Three month average of the real volume of o
o
projects
Three month average of the number of o
o
building permits
+ o – indicate sign of the relationship. + indicates a significant positive effect, o = no
significant effect, - a significant negative effect. +/o/- indicate a varying effect. A single
+/- indicates significance at 10%, ++/-- indicate significance at 5% and +++/--- indicate
significance at 1%.
23
De Sliva et al.
(2003)
Gupta (2001)
Winning bid
Estache & Iimi
(2009a)
Bid
Bid
De Silva et al.
(2009) (bridges)
Bid
Bid/Cost estimate Bajari & Ye
(2003)
De Silva et al.
(2009) (roads)
Bid
Table 1 Continued - Review of the literature on Infrastructure Bidding behaviour
Dependent variable
Independent variable
Technical requirements
+++
Engineering cost estimate
+++ +++ +++
++
+++
Size of work
Number of items
+++ +++
Multiple physical properties (i.e. length, lanes)
+/o/Number of days to complete the project
+
o
Type of work
+/o/New bidder
-Multimarket contacts among firms
+++
Backlog
o
++
+++ ++
Backlog competitors
o
o
Distance to the work
++
o
+++ o
Distance of competitors to the work
+
o
Spatial concentration of work
Bidders with on-going projects in region
o
o
Number of bidders
-o
-o
--Seasonally unadjusted unemployment rate
o
-+++
Three-month average of the real volume of o
o
projects
Three-month average of the number of building o
+++
permits
+ o – indicate sign of the relationship. + indicates a significant positive effect, o = no
significant effect, - a significant negative effect. +/o/- indicate varying effects. A single +/indicates significance at 10%, ++/-- indicate significance at 5% and +++/--- indicate
significance at 1%.
24
Table 3 Descriptive statistics
Variable
Mean
St Dev
Min
Max
720,135
11.2
35
6.3
0.02
224
0.44
704,257
4.2
33
0.18
0.14
439
0.12
48,950
1
0
6
0
1
0,22
8,876,000
23
265
6.7
1
1,463
0.98
0.06
0.19
0
5.0
Project Type
Bridges, tunnels, flyovers and .48
other civil work tenders.
Cable infrastructure,
.24
highway and road tenders.
Other landscaping and water .28
management-related tenders.
Number of tenders: 500
Bidders
Bid (in euro)
Number of bidders
Distance (in kms)
Backlog (sectoral in months)
Firm bid in combination (0/1)
Size of the firm (in fte)
REL Multimarket contact among
firms
Financial Threshold (x € 1
mil/fte)
Number of bids: 3.369
All firms
Distance (km)
96
55
0
371
Size of the work (in euro)
731,462
745,079 61,250 8,604,155
Number of days for completion 132
125
15
1,346
(days)
Backlog (sector, in months)
6.3
0.17
6
6.7
Size of the firm (in fte)
74
244
1
1,463
Experience requirements
0.80
8.37
0
522
Financial requirements (x € 1 0.29
0.63
0
10.0
mil/fte)
Technical requirements
0.65
0.48
0
1
Number
of
procurements 54
17
4
116
upcoming week
Number
of
procurements 183
44
66
324
upcoming month
Number of observations: NT=1,146 firms x 500 procurements = 573,000
25
Table 4. Number of first price sealed bid public procurement tenders by Type and Size class
Size class 1 Size class 2
Size class 3
Size class 4 Total
CPV45 Types
Bridges, tunnels, flyovers < 324,800
and other civil work tenders
60
< 525,750
< 873,600
<3,267,000
59
60
59
Cable infrastructure,
highway, and road tenders
<352,600
<532,000
<943,350
<2,704,000
30
30
30
30
Other landscaping and <306,000
water management-related
tenders
36
<541,000
<855,450
<3,161,000
35
36
35
142
Total
124
126
124
500
126
238
120
25%
Share of procurem ent tenders
20%
15%
10%
5%
>7,500
5,000-7,500
3,000-5,000
2,000-3,000
1,500-2,000
1,000-1,500
750-1,000
500-750
300-500
200-300
150-200
100-150
75-100
50-75
0-50
0%
Project value (x € 1,000)
Figure 2 Distribution f(b) of value (ex post) of infrastructure and real estate first-price sealed
bid public procurement tenders
26
12%
Share of procurem ent tenders
10%
8%
6%
4%
2%
0%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
N um ber of bidders
Figure 3 Distribution of the number of bidders per first-price sealed bid public procurement
tender
12%
Share of procurem ent tenders
10%
8%
6%
4%
2%
05
510
10
-1
15 5
-2
20 0
-2
25 5
-3
30 0
-3
35 5
-4
40 0
-4
45 5
-5
50 0
-5
55 5
-6
60 0
-6
65 5
-7
70 0
-7
75 5
-8
80 0
-8
85 5
-9
90 0
95 95
10 100
010 105
511 110
011 115
512 120
012 125
513 130
013 135
514 140
014
5
0%
D istance (km )
Figure 4 Distribution of the bidders’ distance in kilometres from the work
27
6,8
6,6
Backlog (m onths)
6,4
6,2
6
5,8
m ei-10
apr-10
m rt-10
feb-10
jan-10
dec-09
nov-09
okt-09
sep-09
aug-09
jul-09
jun-09
m ei-09
apr-09
m rt-09
feb-09
jan-09
5,6
Figure 5 Sectoral Backlog in months, over time
Figure 6 Number of public procurement tenders issued in forthcoming week (blue) and
forthcoming month (black), over time
28
25%
Share of procurem ent tenders
20%
15%
10%
5%
REL
Figure 7
tenders
Distribution REL of multimarket contact among firms in % of procurement
100%
90%
Share of tenders issued
80%
70%
60%
50%
40%
30%
20%
10%
0%
≥ 100
≥ 200
≥ 500
≥ 1,000
≥ 2,000
≥ 5,000
Project value (x € 1,000)
A lltypes
Figure 8
Type I
Type II
Type III
Distribution S = [1-F(b)] of value (ex post), by Type
29
0.95-1
0.9-0.95
0.85-0.9
0.8-0.85
0.75-0.8
0.7-0.75
0.65-0.7
0.6-0.65
0.55-0.6
0.5-0.55
0.45-0.5
0.4-0.45
0.35-0.4
0.3-0.35
0.25-0.3
0.2-0.25
0.15-0.2
0.1-0.15
0.05-0.1
0-0.05
0%
100%
80%
60%
40%
20%
0%
<100
100-200
200-500
500-1,000
1,000-2,000
>2,000
Project value (x € 1,000)
0
0-0,5
0,5-1
1-2
2-5
>5
Figure 9
Minimum required experience r(.) in % of procurement tenders in size class
(vertical axis), by project size class (horizontal axis)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
<100
100-200
200-500
500-1,000
1,000-2,000
>2,000
Project value (x € 1,000)
N o requirem ent
0-100%
100-200%
200-300%
300-400%
400-500%
>500%
Figure 10
Minimum financial requirements in % of annual turnover (vertical axis), by
project size class (horizontal axis)
30
80%
Share of procurem ent tenders
70%
60%
50%
40%
30%
20%
10%
0%
<100
100-200
200-500
500-1,000
1,000-2,000
>2,000
Project value (x € 1,000)
ISO 9001
V CA
Technicalrequirem ents
Figure 11
Minimum technical requirements in % of procurement tenders (vertical axis),
by project size class (horizontal axis)
31
Table 5 Estimation results for the Heckman selection model o
Coefficient
St error
PARTICIPATION MODEL
Minimum requirements
Experience requirements
Experience requirements2
Financial requirements
Financial requirements2
Technical Requirements
Tech Requirements x LOG Size of the
work
LOG Distance
Backlog
LOG
Number
of
procurements
upcoming week
LOG
Number
of
procurements
upcoming month
Constant
-0.117
2.2E-4
-1.243
0.132
-1.505
0.123
***
***
***
***
***
***
0.016
0.3E-4
0.058
0.007
0.170
0.013
-0.480 ***
0.030
-0.080 ***
0.006
0.042
0.020
-0.044
0.027
0.136
0.357
BIDDING MODEL
LOG Number of bidders
LOG distance
LOG time to complete project
Backlog
Dummy for firm bidding in combination
LOG firm size
REL Multimarket contacts among firms
Constant
-0.099
0.038
-0.131
0.106
0.237
-0.006
0.019
10.86
-0.190
0.297
-0.056
Log-likelihood
W ~ χ (18)
-17459
20842
N
N censored
572992
569631
ρ
σ
λ
2
***
**
***
***
***
***
*
***
0.013
0.015
0.009
0.030
0.037
0.004
0.048
0.211
0.112
0.007
0.034
o
Including dummies for type and size class of work
*, **, *** significance at 10, 5 and 1%, respectively
32
Table 6 Scenarios for minimum requirements for three different project sizes
Reference Scenario
Scenario A
Scenario B
Low (25%)
High (75%)
A decrease in:
An increase in:
Size of technical
financial
technical
financial
technical
financial
the work requirement requirement requirement requirement requirement requirement
(in euro)
150,000
1.07
440,000
0.76
111,000
2.17
765,000
700,000
2.03
1,750,000
1.41
1,160,000
3.66
2,450,000
2,500,000 3.94
3,650,000
0.76
0
14.00
5,550,000
* Low and High Scenarios relate to minimum requirements set at 25% and 75% of the specific
size as indicated by Figure 9. Reference Scenario relates to minimum requirements set at 50%
(median).
33
Table 7 Welfare effects of changing minimum requirements for three representative projects
Size of
the work
(in euro)
Transaction costs
Scenario A
Scenario B
Low(25%)
High(75%)
(in %)
150,000
€2,000
-0.7
0.3
700,000
€2,875
0.8
-1.0
2,500,000
€3,750
7.0
-2.9
* Low and High Scenarios relate to minimum requirements set at 25% and 75% of the specific size
as indicated by Figure 9. Reference Scenario relates to minimum requirements set at 50%
(median). See Table 6.
i
Throughout the paper we use the terms ‘minimum requirements for eligibility’ and ‘eligibility or qualification
requirements’ interchangeably. We do not refer to selection criteria as these are only allowed in a distinct type of
procedure (restricted public procurements).
ii
Hence minimum restrictions are exogenous to the bidder (contrary to the view of Estache and Iimi, 2009a).
iii
The population of firms includes only those construction firms that are registered at Cordares Pensions, for
which we have detailed information on firm size.
iv
We also analysed the bidding behaviour of these firms to see whether their bidding behaviour was significantly
different from the specialised civil engineering firms and found no significant differences.
v
In our empirical analysis we ended up using 3,369 out of 4,792 bids, by of 466 out of 1,146 contractors, for 500
out of 2,025 procedures issued by 157 out of 410 municipalities.
vi
The distance to work is calculated after geocoding the address of the location of the firm and the location of the
contracting authority.
vii
Note that the Netherlands is approximately 300 km from North to South, and 200 km from East to West.
viii
Note that excluding minimum criteria let to a significant selection effect.
ix
The average welfare effect of 4% relates to the weighted average of 0.3, 0.8 and 7.0 associated with an increase
in minimum requirements for small works and an decrease in minimum requirements for a middle-sized or large
work for given size distribution in Figure 2.
34