Estimating the Benefits from the Procurement … · 2/1/2006 · Directives econometrically by identifying and measuring relationships between improved ... procurement processes and

Estimating the Benefits from the Procurement Directives

A Report for DG Internal Market

Europe Economics Chancery House

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13 May 2011


TABLE OF CONTENTS

COUNTRY CODES ................................................................................................. I

EXECUTIVE SUMMARY ........................................................................................ IIIntroduction ....................................................................................................................................... iiBackground ....................................................................................................................................... iiMethodology ..................................................................................................................................... iiiData .................................................................................................................................................... ivResults ................................................................................................................................................ v

1 INTRODUCTION .......................................................................................... 1

2 BACKGROUND ........................................................................................... 3Public Procurement in the EU ......................................................................................................... 7

3 MODEL AND HYPOTHESES .................................................................... 10The Initial Estimated Total Value ................................................................................................ 10Procurement-Related Indicators .................................................................................................. 11The Models ..................................................................................................................................... 13Interpretation of the Models ......................................................................................................... 14Incorporating EMAT data .............................................................................................................. 16Estimation Challenges .................................................................................................................. 16

4 DATA .......................................................................................................... 19Description of the MAPPs/TED Dataset ...................................................................................... 19Description of Dataset ................................................................................................................... 20Descriptive Statistics for SP Dataset .......................................................................................... 24Representativeness of Sample .................................................................................................... 34

5 RESULTS ................................................................................................... 37The Outcomes Model .................................................................................................................... 37Number of Bidders Regression ................................................................................................... 46

6 CONCLUSION ........................................................................................... 52

APPENDIX 1: DETAILS ON CONSTRUCTION OF DATASETS ....................... 54Building the master dataset (D) ................................................................................................... 54Further exclusions ......................................................................................................................... 55Numbers of Observations ............................................................................................................ 56


APPENDIX 2: CPV CODES ................................................................................. 60

APPENDIX 3: GENERAL DESCRIPTION (SP SAMPLE) .................................. 61

APPENDIX 4: DEPENDENT VARIABLES (SP SAMPLE) ................................. 72Explanatory Variables ................................................................................................................... 75Indicator Variables ......................................................................................................................... 77

APPENDIX 5: EMAT PRICE WEIGHTS (SP SAMPLE) ..................................... 80

APPENDIX 6: MODELS AT EU LEVEL .............................................................. 82

APPENDIX 7: OUTCOME MODEL AT MS LEVEL ............................................ 89Outcome Model Results................................................................................................................ 89

APPENDIX 8: NUMBER OF BIDDERS MODEL AT MS LEVEL ....................... 97

Country codes

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COUNTRY CODES

AT Austria BE Belgium BG Bulgaria CY Cyprus CZ Czech Republic DE Germany DK Denmark EE Estonia EL Greece ES Spain FI Finland FR France HU Hungary IE Ireland IT Italy LT Lithuania LU Luxembourg LV Latvia MT Malta NL Netherlands PL Poland PT Portugal RO Romania SE Sweden SI Slovenia SK Slovakia UKUnited Kingdom

ACKNOWLEDGEMENT

We are grateful to the participants of the Workshop on the Evaluation of Public Procurement Legislation (14-15 April 2011) for comments and suggestions on this study.

Executive Summary

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EXECUTIVE SUMMARY

Introduction

1 The main aim of this work is to measure the benefits arising from the Procurement Directives econometrically by identifying and measuring relationships between improved procurement practice and the final values of specific awards of contracts in relation to the estimated values of contracts before tendering (savings). We also explore the relationship between improved procurement practice and the number of bidders. In both cases, we control for variations in other variables. The work is based on the MAPPs database.

Background

2 The literature relating to public procurement practices has developed along the design of procurement processes and the empirical quantification of the effects of different procurement practices. The design literature recognises several tools and strategies for its effective implementation. Several aspects have been investigated such as the type of auction and subdivision of contracts into lots, usefulness of open versus negotiated procedures, the impact of centralised purchases, dealing with contracts which include a quality component or mechanisms for dissuading collusion or preventing corruption. These aspects have been incorporated into the Directives and we estimate the effects of such procurement practices in our models. On the other hand, there are a number of studies that have also looked empirically at the effects of different procurement practices on the costs and value of winning bids or in encouraging participation or competition, and have generally found evidence of favourable outcomes for procuring authorities. These studies have been used to inform our methodological approach.

3 Public procurement legislation in the EU is aimed at creating a common market by ensuring free movement of goods, persons, services and capital, and promoting effective competition in the Internal Market. Harmonised rules are thought to lead to greater transparency, participation, objectivity and non-discrimination in procurement markets. It is believed that this increases competition and cross-border trading, resulting in a better price/quality ratio for public authorities (i.e. a more efficient use of public funds), while it increases the productivity in the industry and improves the participation and access to such markets by SMEs.

4 The volume of procurement in the EU is significant (17.1 per cent of GDP in 2008), although very little of it is published in the EU official journal (18.2 per cent of total public procurement in 2008). However only 1.6 per cent of contracts are awarded to suppliers

Executive Summary

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based outside the MS of the awarding authority (11 per cent if sales through subsidiaries are included).1

Methodology

5 The study is based on an econometric analysis of the relationships between procurement practices and procurement outcomes. Procurement practices are measured using indicator variables deriving from the MAPPs database. We analyse their associations with two outcome variables: final award values (in relation to estimated values before tendering, the initial estimated total value or IETV), and the number of bidders.

Procurement related indicators

6 The Directives identify different measures aimed at opening the procurement markets:

(a) Transparency: An authority may publish a Prior Information Notice (PIN) to notify potential contractors of forthcoming procurement. The Directives then mandate the publishing of a Contract Notice (or invitation to tender, ITT) except under some special circumstances; and a Contract Award Notice (CAN) after the award of the tender. Finally, authorities must provide feedback if requested to unsuccessful bidders. The MAPPs database is derived from published CANs and does not contain information on feedback, but it does contain information on the publishing of PINs and ITTs that we use in our analysis.

(b) Openness: Authorities are mandated to use either the open2 or restricted3 procedures. Under exceptional circumstances, the use of non-standard procedures4 is allowed. The MAPPs database contains information on the procedure used.

(c) Aggregation: The Directives mention and allow procurement though a centralised purchasing authority. The MAPPs database contains information on this.

7 Based on the information identified, we have constructed six indicator variables: pin (reflecting the publication of a PIN), itt (publication of an ITT), opn (use of the open procedure), rst (use of the restricted procedure), ext (use of non-standard procedures under extenuating circumstances) and cen (aggregated purchasing).

1 European Commission (2011) Green Paper on the modernisation of EU public procurement policy. Towards a more efficient European Procurement Market, COM(2011) 15 final.

2 This is open to all bidders. 3 This is a two stage process with a shortlist of qualifying bidders being identified first stage and then full bids being submitted by

those identified in the second stage. 4 These include negotiated without competition, accelerated negotiated, accelerated restricted, competitive dialogue and negotiated

with competition.

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The models

Outcome model

8 This model postulates a relationship between final award value and procurement-related indicators. We also control for other factors that might be related to final award value by including additional variables in the regression. These include the estimated value and dummies for CPV codes, years and type of authority.

9 With EMAT data, where there are non-price elements involved, we expect that the benefits of the Directives are distributed between price and non-price characteristics. An estimate of the effect of the Directives only on price might thus underestimate the total effect. To capture the overall effect, we allow the indicators to vary by the weight accorded to price.

10 We would expect to find that good procurement practices (such as publishing PINs and ITTs, or using open procedures) would be associated with lower final award values.

Number of bidders model

11 This model postulates a relationship between the number of bidders and the (non-weighted) procurement indicators, again controlling for other factors. This would give us an insight into how improved procurement practices have affected realised competition. We would expect to find good procurement practice associated with a higher number of bidders.

Estimation challenges

12 We expect to face several challenges during the course of our analysis, such as heteroskedasticity, truncation, endogeneity and model misspecification. We deal with these problems in manners consistent with econometric best practice.

Data

13 The MAPPs database includes all notices published in the European public procurement journal Tenders Electronic Daily (TED) since 1993. Contracting authorities are required to send notices to the Office for Official Publications or publish them on their buyer profiles, from where they are taken by the Office for Official Publications for publication. The relevant information on contract award notices (CAN) are contained in Standard Forms 3 (relating to works, services and supplies) and 6 (utilities).

14 For this work, we use only a subset of variables present in the MAPPs database. The extract we received covers all the contracts recorded in the MAPPs database for all MS for the years 2006-09. Our main analysis is based on the sample that excludes specific awards for which we do not have either an initial estimated total value (IETV) or a final or estimated price, and for which we cannot determine the weight assigned to price in the evaluation criteria.

Executive Summary

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15 The sample contains information on 175,167 specific awards. The distribution of these specific awards across MS is uneven, with PL accounting for about 50 per cent of them. The distribution of the value of procurement is less uneven, with PL accounting for the largest share, followed by IT, EK and ES. This reflects differences in average specific award sizes. The number and value of awards increases through time, and also differs across CPV codes, with medical equipment, pharmaceuticals and personal care products having the most awards but construction work showing the highest value of procurement.

16 There are a large number of very small awards, with the number of awards decreasing as size increases. There are large differences across MS: countries like DK, UK, IE and SE have a higher density of larger contracts, while some like CZ, FR, PT and SI are highly skewed towards extremely small contracts. In terms of bidders, most specific awards involve just 1 bidder, followed by 2, 3, 4 and decreasing with size. There are again large differences across MS.

17 Most contracts are awarded by bodies governed by public law (31 per cent), followed by other (24 per cent) and local authorities (21per cent). Looking at the MS level we see that in most large countries like UK, DE, FR and IT the largest share belongs to local authorities. In small countries like CY, MT and LU, the share of central government is very high. By type of contracts, we see that the largest share is supplies, followed by services and works. Some MS (like LU, FR and AT) have a significantly larger proportion attributed to works than the EU average.

18 In terms of transparency, most specific awards relate to contracts which publish only an ITT (60 per cent). Over a quarter of contracts publish neither an ITT nor a PIN. Some MS publish much less than others: in RO, NL and EE more than 50 per cent of specific awards are not published whereas in MT almost all are published in some form.

19 In terms of openness, the use of the standard procedures (open and restricted) is most popular, with predominance of the open procedure (except for UK). The use of other procedures varies across MS, accounting for extremely high proportions in EE, SK, LV, HU and LT.

20 In terms of aggregation, a very small proportion of specific awards are procured in an aggregated manner. The proportion is small at the MS level as well, with some variations.

21 The sample is not representative of overall EU procurement or of all MAPPs data as there are significant observations excluded and the distribution of the key variables are different. However, the regression results may be extrapolated to the overall population with reasonable confidence, because exclusion of observations seems to be at random (or at least not correlated with the dependent variables of our models) so that there are no obvious sample selection problems.

Results

22 Based on our modelling exercises, we find that good procurement practice in general has a beneficial effect on procurement outcomes.

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The Outcome Model

23 We find that in terms of transparency, publishing an ITT is most beneficial as it is associated with benefits roughly equivalent to a 1 per cent reduction in award value compared to the IETV. In terms of procedure, the open procedure increases estimated savings by 3 per cent.

The Number of Bidders Model

24 We find that the open procedure is the most effective in attracting more bidders, with the increase in the number of bidders being as much as 46.4 per cent when combined with the publishing of both an ITT and a PIN.

Applicability

25 Our results show the positive and significant effects of procurement disciplines related to increasing openness and transparency. It should be noted that these findings do not mean that savings can be found across all contracts. As we have seen, the literature on design notes that in some cases it may be more efficient, because of particular characteristics of the contract, to use a negotiated or restricted procedure. Our results should be understood in this context, and in particular should be taken acknowledging the fact that savings will be realised in cases where the procurement disciplines can be used to remove an existing barrier, but they may have less of an effect if the optimal design calls for some specific procedure.

Future work

26 The MAPPs database provides a comprehensive dataset of procurement practices in the EU. It can be an interesting instrument to investigate, characterise and monitor the procurement practices across the different MS. It provides a unique tool which can be used to investigate the current procurement practices in the EU, the compliance by MS and the evolution of the effects over time. The public procurement market is large in the EU and all these issues are worth investigating in order to appraise the effect of competition in procurement in the Internal Market.

Introduction

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1 INTRODUCTION

1.1 Recent discussion among policy makers regarding the costs and benefits of public procurement legislation in the EU has called for a debate of public procurement rules. As part of this, an EC Green Paper was published on 27 January 2011 discussing the issues. The present work is framed within this context and it is aimed at quantifying the benefits of public procurement based on published contract award notices contained in the TED/MAPPs database.

1.2 The Request for Quotation for the present work dated called for the following tasks to be undertaken:

(a) Analysis of indicators relating to good procurement practice;

(b) Analysis of intermediate relationships between procurement practice and outcomes;

(c) Addressing the robustness of the estimated relationships;

(d) Incorporation of all EU Member States and contracts awarded on the Economically Most Advantageous Tender (EMAT) criteria;

(e) Studying the interpretation of the initial estimated total values;

(f) Analysis of the extent to which inferences from the models may be generalised; and

(g) Review of the literature of the benefits of procurement from a theoretical perspective.

1.3 The aim of the study is therefore to measure the benefits arising from the Procurement Directives econometrically by identifying and measuring relationships between improved procurement practice and the final values of specific awards of contracts. The analysis is based on a comparison between final contract values and the expected values of the same contracts.

1.4 We also explore the relationship between improved procurement practice and the number of bidders, which provides insight of an indirect relationship whereby procurement practices influence the number of bidders, which in turn influences the final values of contracts. In both cases, we control for variations in other variables.

1.5 The study takes the MAPPs data as its starting point. It must be noted that the quality and reliability of the results are constrained by the quality and reliability of these data.

1.6 The report is structured as follows:

(a) Section 2 reviews the literature relating to the benefits of improved procurement practice and provides a background account of the state of procurement in the EU.

(b) Section 3 sets out the methodology used for the econometric exercise.

Introduction


(c) Section 4 introduces and describes the data used in the study.

(d) Section 5 contains results.

(e) Section 6 concludes.

1.7 Material supplementary to the main text is provided in the appendices.

Background


2 BACKGROUND

2.1 Procurement is the purchase of goods and services by public and private enterprises. Efficiency in procurement has long been recognised as a way to obtaining the desired goods or services at the lowest price or, more generally, at the best value for money.5

2.2 The most common practices of procurement involve some form of tender or auction, and it is believed that, under these, efficient procurement outcomes can usually be achieved in situations where there are enough firms in the procurement market to sustain reasonable competition. In cases with a reduced number of firms, more sophisticated arrangements are necessary to prevent practices such as collusion, bid-rigging, fraud and corruption, which hinder the achievement of efficient outcomes. Public procurers also face the additional challenge of preventing political favouritism where contracts are allocated according to loyalty or support rather than on the grounds of efficiency.

2.3 There has been a growing literature relating to public procurement practices. A substantially larger bulk of research has been devoted to the design of procurement processes in order to achieve efficient outcomes under different circumstances. Another strand of literature has recently been developing around the empirical quantification of procurement outcomes under different type of practices. We will review them in turn.

Procurement design

2.4 The procurement design literature recognises several tools and strategies for its effective implementation. Several aspects have been investigated such as the type of auction and subdivision of contracts into lots, usefulness of open versus negotiated procedures, the impact of centralised purchases, dealing with contracts which include a quality component or mechanisms for dissuading collusion or preventing corruption. We will review briefly some recent contributions in this field. This will be useful to introduce and understand some of the tools and strategic terms used later in our analysis.

2.5 The sealed bid format has traditionally been the preferred form of procurement, although recently some variants have been introduced. Drawing on the auction theory literature, Albano et al. (2006b)6 conclude that sealed bids are preferred when bidders face some certainty and high knowledge on the goods or services provided. In other circumstances where the conditions of provision of the contract are uncertain a dynamic auction performs better because it allows participants to learn along the process. A two-stage sealed bid format is also preferred in cases where there are risks of participants to exaggerated bids which make the fulfilment of the contract impossible or below certain standards.

5 See OECD (1999) Competition Policy and Procurement Markets. 6 Albano, Gian Luigi, Dimitri, Nicola, Pacini, Riccardo and Spagnolo, Giancarlo Information and competitive tendering in Dimitri,

Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p143-167.

Background


2.6 One of the main instruments to increase procurement efficiency has been the division of the contract into specific lots or awards. However, in cases where lots have strong positive complementarities it has been shown that these should be allowed to be bundled into particular lot groups (Grimm et al., 20067 and Dimitri et al., 20068).

2.7 Several authors describe the advantages and disadvantages of negotiated versus open auctions in relation to the complexity of the auction. In cases where projects are simple and well specified Bajari and Tadelis (2006)9 argue that competitive tendering is efficient. On the contrary, where projects are complex, specifications are incomplete, accurate monitoring is not possible and / or the expertise of the supplier is required at the initial design stage, negotiations may be more efficient due to the increased scope for information exchange. It has also been shown that in cases with incomplete contracts and moral hazard issues scoring-based auctions perform better than bargaining (Asker and Cantillon, 2010)10.

2.8 The degree of centralisation of procurement has also been the subject of some research. Dimitri, Dini and Piga (2006)11 review the relevant literature and conclude that centralisation offers net benefits when procurement involves standardised, strategic, urgent or very essential products. Also, centralisation is more likely to be beneficial when ICT has been adopted. Further, centralisation facilitates coordination in the development of networks and increases bargaining power of the purchasing authority. However, other circumstances can lead to centralisation being inefficient, such as high transport costs, local knowledge of dynamic market conditions and high costs of information sharing.

2.9 In situations where both price and quality matter, the efforts have been directed to find an optimal award mechanism (Asker and Cantillon, 2010). However, it is acknowledged that implementation of such contracts is complex and requires full information about the bidding environment. Other authors (Dini, Pacini and Valletti, 2006)12 have advocated a scoring rule such that a point awarded on non-price characteristics is monetarily equivalent to a point awarded on price.

7 Grimm, Veronika, Pacini, Riccardo, Spagnolo, Giancarlo and Zanza, Matteo Division into specific awards and competition in procurement in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p168-192.

8 Dimitri, Nicola, Pacini, Riccardo, Pagnozzi, Marco and Spagnolo, Giancarlo Multi-contract tendering procedures and package bidding in procurement in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p193-219.

9 Bajari, Patrick and Tadelis, Steve Incentives and award procedures: competitive tendering vs. Negotiations in procurement in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p121-139.

10 Asker, John and Cantillon, Estelle (2010) Procurement when price and quality matter RAND Journal of Economics, Vol 41, No 1, p1-34.

11 Dimitri, Nicola, Dini, Frederico and Piga, Gustavo When should procurement be centralised? in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds)(2006) Handbook of Procurement, Cambridge: Cambridge University Press, p47-81.

12 Dini, Frederico, Pacini, Riccardo and Valletti, Tomasso, Scoring rules in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p293-321.

Background


2.10 Albano et al. (2006c)13 and Kovacic et al. (2006)14 investigate different ways to dissuade collusion in procurement settings. As a result they come up with different recommendations for procurement design, including setting longer contract lengths, delaying information disclosure, using an aggressive reserve price, avoiding second-lowest price competitive tendering, simultaneous as opposed to sequential procurement, allow for certain precautions in the case of dynamic auctions and certain rules about the permissibility of bidding consortia.

2.11 Lengwiler and Wolfstetter (2006)15 look specifically at corruption other than collusion. To combat bid-rigging securing electronic auctions with a sealed-bid second-price or an open bid format is suggested. To combat distortion of quality rankings in cases where there is a quality dimension involved the following is proposed. Firstly, proposals should use secure electronic bid submission and the financial bid should be standardised. Secondly, evaluation of the technical bid should be made by randomly drawing evaluators from a large pool and making sure they have no conflicts of interest. The evaluation process should give consideration to the use of the median evaluators scores rather than the mean and checking for outlying scores.

Measuring effects of improved procurement practice on procurement outcomes

2.12 A number of studies have looked at the effects of different procurement practices on the costs and value of winning bids or in encouraging participation or competition.

(a) The effects of improved transparency are estimated to have reduced public procurement cost by up to 8 per cent in the Mie Prefecture of Japan (Ohashi, 200916). The study uses data containing information on all public-works projects offered for tender by the Mie government from March 2001 to March 2004 (winning and other submitted bids) and compares procurement outcomes in a difference in difference approach after improved transparency requirements came into force in mid-2002.

(b) In a study using survey data on procurement practices by New York State school districts, Duncombe and Searcy (2007)17 conclude that the use of competitive bidding, purchasing calendars, central warehouses, and bidders lists were associated with significant cost savings.

13 Albano, Gian Luigi, Buccirossi, Paolo, Spagnolo, Giancarlo and Zanza, Matteo Preventing collusion in procurement in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006c) Handbook of Procurement, Cambridge: Cambridge University Press, p347-380.

14 Kovacic, William E, Marshall, Robert C, Marx, Leslie M and Raiff, Matthew E Bidding rings and the design of anti-collusive measures for auctions and procurements in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p381-411.

15 Lengwiler, Yvan and Wolfstetter, Elmar Corruption in procurement auctions in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006) Handbook of Procurement, Cambridge: Cambridge University Press, p412-429.

16 Ohashi, Hiroshi (2009) Effects of transparency in procurement practices on government expenditure: a case study on municipal public works Review of Industrial Organization, Vol 34, No 3, p267-285.

17 Duncombe, William and Searcy, Cynthia (2007) Can the use of recommended procurement practices save money? Public Budgeting and Finance, Vol 27 No 2, p68-87.

Background


(c) Bids data from the Texas Department of Transportation relating to asphalt and bridge construction projects from August 1998 to August 2007 are used in the study by De Silva, Jetischko and Kosmopoulou (2009)18 to demonstrate that encouraging participation in public procurement auctions lead to lower bids when costs were predominantly known to the different bidders, but had no statistically significant effect when costs were predominantly of an uncertain nature.

(d) Using the results of a stakeholder survey, Europe Economics (2006)19 estimates that the introduction of the procurement Directives in the then 15 MS increased the value for money of procurement subject to the Directives by between 2.5 and 10 per cent from 1992 to 2003. There was also an increase in administrative costs of about 0.7 per cent.

2.13 Some other studies have looked at the effects different auctions format had on participants. Albano et al. (2006a)20 shows that sealed bid procedures are better at encouraging participation when participants are heterogeneous in their costs of fulfilling the contract or the certainty they face about characteristics of the goods or services required. Further, the study also shows that other practices, such as increasing the number of lots, are also associated with more participation. A recent study found that the use of electronic auctions increased the number of suppliers for at least one in five companies, with only a small fraction experiencing reductions (Nepeleski, 2009).21 The study also found firm characteristics to be important in determining the impact of ICT on firms sourcing strategies.

2.14 Finally, Bajari, McMillan and Tadelis (2008)22 looked at the advantages and disadvantages of negotiated versus open auctions using data on non-residential building projects in Northern California between 1995 and 2000. The study found that the use of negotiations was positively related to project complexity, negatively to buyer experience and positively to the number of potential bidders.

A short summary of the literature reviewed

2.15 The literature on procurement recommends using some form of tender or auction which is advertised publicly to the potential bidders. It also recommends the division of contracts into lots, using open or negotiated procedures (depending on the situation), the net

18 De Silva, Dakshina G, Jeitschko, Thomas D and Kosmopoulou, Georgia (2009) Entry and bidding in common and private value auctions with an unknown number of rivals Review of Industrial Organization, Vol 35, Issue 1,p73-93.

19 Europe Economics (2006) Evaluation of Public Procurement Directives http://ec.europa.eu/internal_market/publicprocurement/docs/final_report_en.pdf

20 Albano, Gian Luigi, Dimitri, Nicola, Perrigne, Isabelle and Piga, Gustavo Fostering participation in Dimitri, Nicola, Piga, Gustavo and Spagnolo, Giancarlo (eds) (2006a) Handbook of Procurement, Cambridge: Cambridge University Press, p267-292.

21 Nepelski, Daniel The impact of e-procurement on the number of suppliers (2009) Transformations In Business & Economics, Vol 8, No 16, p72-85.

22 Bajari, Patrick, McMillan, Robert and Tadelis, Steven (2008) Auctions versus negotiations in procurement: an empirical analysis The Journal of Law, Economics, & Organization, Vol 25, No 2, p375-399.

Background


benefits of centralising purchases and how different mechanisms are required in situations where both price and quality are needed.

2.16 Interestingly, all these aspects have been incorporated into the Directives and it is at the core of our research to investigate the effect on the final value of advertising or increasing the participation of players in procurement bids, the relevance of open versus negotiated procedures and the impact of centralised purchases while separating the effects for contracts which include a quality component. We estimate the effects of such procurement practices in our models for procurement outcomes and number of bidders.

2.17 A number of studies have also looked at the effects of different procurement practices on the costs and value of winning bids or in encouraging participation or competition, and have generally found evidence of favourable outcomes.

Public Procurement in the EU

2.18 Public procurement legislation in the EU is aimed at creating a common market by ensuring free movement of goods, persons, services and capital, and promoting effective competition in the Internal Market.23 The guiding principles24 by which these aims are sought to be achieved are:

(a) Equal treatment of all economic operators;

(b) Transparent behaviour;

(c) No discrimination based on nationality.

2.19 The Procurement Directives emphasize the coordination of national procedures in order to guarantee that these principles are achieved. The harmonised rules regarding advertising, procedures, deadlines, selection and award criteria and reporting are thought to lead to greater transparency, participation, objectivity and non-discrimination in procurement markets. It is believed this would increase competition and cross-border trading, resulting in a better price/quality ratio (value for money) for public authorities, while increasing the productivity in the supplying industries and improving the participation and access to such markets by SMEs. A more efficient use of public funds coupled with competitive industries would have obvious economic benefits for the economy.

Historical evolution of procurement Directives

2.20 The regulation of procurement in the EU has a long history.25 Initially, regulation was based on Directives 66/683/EEC and 70/32/EEC which disallowed rules giving

23 These objectives are laid out in Articles 2 and 3 of the Treaty of Rome (1957). 24 These are laid out in Articles 2 and 3 of the Public Sector Directive 2004/18/EC. 25 For a detailed description, see Bovis, Christopher H (2007) EU Public Procurement Law, Cheltenham: Edward Elgar Publishing.

Background


preferential treatment to national products/supplies, or prohibiting the procurement of foreign products/supplies. These were followed by Directives 77/62/EEC, 80/767/EEC and 71/305/EEC which aimed at coordinating procedures for supply, utilities and works contracts, respectively.

2.21 Following the European Commissions 1985 White Paper on the completion of the Internal Market and the Single European Act of 1986, further directives were introduced for setting the rules for award procedures, requiring prior publication of notices and details of awards, making national technical standards mutually recognisable and clarifying exempted sectors, and removing international barriers in the utilities sector while harmonising the rules relating to services.26

2.22 Following calls for simplification and modernisation, these were updated into the following directives (the Directives, henceforth).

(a) The Utilities Directive 2004/17/EC, which governs utilities procurement;

(b) The Public Sector Directive 2004/18/EC, which governs works, supplies and services procurement; and

(c) The Directive 2007/66/EC, which governs remedies.

Procurement in the EU volume and publication in the OJEU

2.23 The volume of the procurement market in Europe is very significant, though not all of it is published in the Official Journal of the European Union (OJEU).

2.24 According to Eurostat data, public procurement amounted to 2,134 bn, or 17.1 per cent of EU GDP in 2008. By comparison to its GDP, the ratio of procurement varies by MS (Table 1). Some MS like CY (where procurement accounts for 10.6 per cent of GDP) and EL (9.3 per cent) are well below the EU average, whereas others like CZ (25.2 per cent), NL (26.6 per cent) and SK (24.4 per cent) are above the EU average. All the large MS are close to the EU average.

2.25 In 2008, only 18.2 per cent of EU public procurement contracts were published in the OJEU. There are wide disparities by MS (Table 1): some of the New MS like BG (52.2 per cent), CY (44.5 per cent), EE (45.3 per cent) and LV (61.1 per cent) publish a very high proportion of procurement, whereas others like LU (9.1 per cent), MT (8 per cent) and NL (7.1 per cent publish just a small proportion. Among the large MS, most are close to or above the EU average, but DE (7.1 per cent) stands out as publishing a very small proportion of procurement.

26 See Directive 88/295/EEC, Directive 89/440/EEC, Directive 90/351/EEC, Directive 92/50/EEC, Directive 89/995/EC, Directive 92/13/EC, Directive 93/36/EEC, Directive 93/37/EEC, Directive 93/38/EEC.

Background


Table 1: EU Procurement by MS in 2008

MS Value ( bn) GDP (%) Published (% of contracts) AT 54.5 19.2 12.5 BE 52.2 15.1 23.8 BG 5.9 16.7 52.2 CY 1.8 10.6 44.5 CZ 37.3 25.2 21.0 DE 421.1 17.0 7.1 DK 35.9 15.4 19.5 EE 2.9 18.1 45.3 EL 22.1 9.3 30.0 ES 164.0 15.1 23.9 FI 31.3 17.0 23.6 FR 342.0 17.6 21.1 HU 21.3 20.0 26.0 IE 28.1 15.6 16.0 IT 219.7 14.0 16.4 LT 5.6 17.3 20.8 LU 5.6 14.2 9.1 LV 3.6 15.7 61.1 MT 0.9 14.9 8.0 NL 158.9 26.6 7.1 PL 68.2 18.8 38.3 PT 28.8 16.8 14.9 RO 28.0 20.1 36.9 SE 62.1 18.6 18.8 SI 5.8 15.5 32.8 SK 15.8 24.4 15.2 UK 340.3 18.7 23.5

Total 2,134.4 17.1 18.2 Source: Europe Economics calculations on Eurostat data. Note: Rounding errors in totals.

Model and Hypotheses


3 MODEL AND HYPOTHESES

3.1 As seen, the conceptual framework of procurement regulation identifies a relationship between improving procurement disciplines and procurement outcomes. In doing so it implicitly recognises that markets are not perfectly competitive and that there is room for improving procurement outcomes. In addition, the Directives are aimed at reducing the search costs of players who can potentially bid in larger procurement markets. However, if the Directives imposed an excessive administrative cost on suppliers (greater than the benefits they aim at), then their implementation would raise contract values rather than lower them.

3.2 The underlying factors affecting the increase in openness and transparency can be interpreted as coming from two different sources. On one hand, an improvement in procurement disciplines could stem from political action and regulation aimed at opening the procurement markets (the Directives). On the other hand, such improvement could come from other factors which are independent (although they may be related in some indirect way) of the political measures or have not been made compulsory by EU law.

3.3 We have not been able to identify the source of changes in procurement disciplines. This will become important in interpreting the results because, although we can see the effects of different procurement tools, we cannot disentangle the effects strictly derived from the compliance with the Directives, as some of the measures envisaged are voluntary.

3.4 It is also worth noticing that the analysis is not a comparison between regulated and non-regulated tenders, as by definition, all the records included in the analysis are covered by the Directives. The exercise is therefore useful to compare different degrees of openness, all of which are envisaged under the Directives. In doing so, and because of limitations of the data, we are only focusing on the benefits which are quantifiable, and this implies looking at the differences in contracted values or prices compared to the initial estimated total value ( IETV). There may be other intangible benefits related to increases in quality, better tailored services, or innovative solutions which are not recorded in the data and hence are not quantifiable in this study.

The Initial Estimated Total Value

3.5 The focus of our analysis is the relationship between the initial estimated total value (IETV) stated by the awarding authority and the final award price. A crucial issue in this relationship is the interpretation that different players make of the estimated value. As this cannot be identified from the data used, we consulted a number of EU procurement experts and asked how these values are constructed in practice.27

27 The contact list was suggested by the Commission Services. We received responses from Piotr-Nils Gorecki (SIGMA), Stuart Broom (European PPP Expertise Centre), sa Edman (Public Procurement Committee 2010), Dr Gian Luigi Albano (Consip S.p.a.) and Dr Michael Fruhmann (Bundeskanzleramt-Verfassungsdienst), for which we are extremely grateful.



3.6 The responses received suggest that these values are not maximum values (as a result of budget allocations, for example), but expectations of what the authority would have to pay for the contract. These estimates are constructed using several methods which, among others are based on:

Prevailing market conditions;

Published price lists;

Past experiences of the authority; and

Past experiences of other authorities.

3.7 Different authorities use different methods of deriving IETVs, and the same authority may use different methods for different contracts. Thus, there is no common method even at the MS level.

Procurement-Related Indicators

3.8 The Directives identify different measures aimed at opening the procurement markets. Our work looks at whether the differences in such measures across awarding authorities have any impact in the observed final values of procurement contracts relative to the IETV. We now define different indicators introduced in or related to the Directives.28

Transparency

3.9 There are four aspects related to transparency, three of which are mandated by the Directives:29

(a) A Prior Information Notice (PIN) may be issued to notify companies of a forthcoming procurement by the authority. This is not compulsory, and not publishing a PIN does not amount to non-compliance with the Directives. Information regarding any PINs published is requested in the Standard Forms and is therefore a variable contained in the MAPPs database.

(b) A Contract Notice (or invitation to tender, ITT) must be published in the OJEU for all contracts above specified thresholds before the award (exemptions do exist for certain types of contracts as set out in Articles 29, 30 and 31, and Annex II B of Directive 2004/18/EC and Annex XVII B of Directive 2004/17/EC). Contract notices are effectively an announcement of a contract that is being commissioned to which

28 As a measure of market opening, we also investigated the accessibility of different markets, which we defined as whether the publication of an ITT is in a national or another EU common language (e.g. English, French, German ) or whether submission of tenders is accepted in other EU languages. This could be understood as a measure increasing the ability of foreign nationals to participate in the tendering process. Unfortunately, we have been unable to use this measure as this information is not obtainable from the MAPPs database.

29 Chapter VI, Title II of Directive 2004/18/EC.



interested parties can respond. Again, this information is recorded in the MAPPs database.

(c) A Contract Award Notice (CAN) must be published in the OJEU containing the contract value (or the values of the highest and lowest bids) and the name of the winning bidder after the award. The MAPPs dataset is derived from published CANs, and so by definition all the included observations are associated with a published CAN.

(d) Feedback must be given to unsuccessful bidders if it is requested. The MAPPs database, however, does not contain any information on this.

Award criteria

3.10 Procuring authorities must award tenders to the bid that either:30

(a) Has the lowest price; or

(b) Is economically most advantageous, in which case the criteria of evaluation must be clearly specified.

3.11 This information is recorded in the MAPPs database. However, as will be seen, because of problems in the coding of this indicator, analysis including economically most advantageous tenders (EMAT) is limited in our study.

Openness

3.12 Generally, authorities are obliged to use one of two standard procedures:31

(a) Open procedures open to all bidders

(b) Restricted procedures involve a two-stage process. The first stage selects a shortlist of qualifying bidders. In the second stage, identified bidders are invited to submit full bids.

(c) Non-standard procedures: these may be used under special circumstances, and may include negotiated without competition, accelerated negotiated, accelerated restricted, competitive dialogue and negotiated with competition.

3.13 The procedure used is recorded in the MAPPs database.

30 Article 53 of Directive 2004/18/EC. 31 Chapter V, Title II of Directive 2004/18/EC.



Aggregated purchasing

3.14 The Directives mention and allow procuring through a centralised purchasing authority.32 We understand that this practice is encouraged as it is believed that aggregating purchases leads to a better outcome for procuring authorities. The MAPPs database records whether procurement was undertaken on behalf of other purchasing authorities.

The Models

3.15 We propose two different models for analysing the impact of the directives. We look at the effects on procurement outcomes and number of bidders in the tendering process.

Outcomes

3.16 Our model builds on models proposed in the literature which essentially relate the procurement outcomes (y) to various indicators.33

ln(y) = 0 + 1ln(y*) + 2kDTk + 3kDOk +4DP +5ln(N) + 6kDCk + 7kDYk + 8kDAk + 9kDNk + , (1)

where

ln(y) is the dependent variable and will be modelled as the natural logarithm34 of winning bid values (i.e. the total final value of the contract or the price for the awarded contract). As a parallel approach, we also consider savings (i.e. the difference between estimated and final value as a proportion of estimated value) as the dependent variable. However, as will be seen the results of both type of models are very similar.35

ln(y*) is the natural logarithm of the initial estimated total value (IETV) stated by the awarding authority.

DTk represents a set of variables that refer to the different transparency indicators. These are indicators that measure the publication of ITTs and PINs. The ITT indicator is 1 if an ITT was published (and 0 otherwise). The PIN indicator is 1 if a PIN was published. An indicator of extenuating factors (EXT) is 1 if there was a suitable justification provided for non-publication, or if it fell under the exemptions envisaged by Directives.

32 Article 11 of Directive 2004/18/EC. 33 In the equation, k indexes the different variables. For instance, in 1kDTk, k takes three different values, one each for ITT, PIN and

non-standard procedures. In the ninth term, 8kDAk, k takes seven values, each corresponding to each type of awarding authority. 34 We use a log-log model for convenience. Here, the dependent variable as well as the explanatory variable (in our case, the

estimated value) are transformed to logarithms. The advantage of this specification is that the estimated parameters have an easy and direct interpretation as elasticities (i.e. it assumes a constant elasticity over all values of the data set).

35 The model proposed in equation (1) is very similar to an equivalent savings approach if the coefficient on the estimated value (5) is equal to 1. In such case the left-hand side of equation (1) would reduce to ln(y/y*), which can be seen as a measure of relative spending closely related to the measures of savings defined earlier.



DOk represents a set of dummy variables that refer to the different openness indicators. The open procedure indicator is 1 if the open procedure is used. The restricted procedure indicator is 1 if the restricted procedure is used. The use of any other procedure corresponds to both the open and restricted procedure indicators having values of 0.

DPk represents a dummy indicating whether or not public purchasing is aggregated centrally or locally. This aggregation indicator is 1 if the purchase was made on behalf of other authorities and 0 otherwise.

ln(N) is the number of bidders in logarithms.

The remaining set of dummy variables are represented by a D followed by a character, where C indicates dummy variables for different CPV codes, Y indicates years, A indicates type of authority and N indicates an award to a foreign contractor. Finally represents an error term and the remaining k are parameters associated to the different set of k variables.

Number of bidders

3.17 We also analyse and explain the relationship between increased procurement disciplines on competition. We hence run regressions seeking to explain the number of bidders (N), which will act as an indicator of the degree of competition, in the following way:

N = f (ln(y*), DTk, DOk, DPk, DCk, DYk, DAk, DNk; k, ). (2)

3.18 For estimation, and following our earlier analysis, we propose to use a model in logarithms for the dependent variable N and a negative binomial36 for the link function f(.). The remaining variables are defined as before.

Interpretation of the Models

3.19 Here we outline our a priori expectations regarding the pattern of dynamics in the models.

The outcomes model

3.20 The expected effects of the key explanatory variables on the outcome variable y are as follows:

ln(y*) is expected to be linked very strongly with the value of the winning bid ceteris paribus, because the magnitude of y* captures the scale of the contract.

DTk is expected to have a positive impact on outcomes: we expect an increase in transparency to reduce prices of the winning bid, ceteris paribus. This is because

36 Negative binomial regressions are used when the dependent variable is represented by counts (i.e. taking only positive and discrete values).



publication of prior information would make information about the contract more freely available, thus enlarging the pool of potential bidders and hence increasing competition. Also, we might expect publication to reduce search costs for contractors, thus reducing the cost of bidding and again increasing the number of bidders for such contracts.

DOk is expected to have positive effects: those specific lots awarded using open or restricted procedures would be expected to have lower prices compared to specific contracts awarded on other procedures. This is because the pool of potential bidders would be larger for procedures that are open to all eligible contractors, thus leading to greater competition.

DP is expected to have positive effects procurement outcomes, ceteris paribus. This is due to aggregation of purchases leading to greater volumes (often associated with lower prices) as well as an increase in bargaining power of contracting authorities.

The number of players bidding in a contest may be expected to reduce the value of the winning bid ceteris paribus if the procurement process is under increased competition (number of bids) from additional bidders. In many situations, the number of players is not likely to be disclosed to the contestants bidding. However, it is likely that players learn from past experiences and are able to make rational predictions about the number of bidders participating in the bidding contest. This number of bidders predicted by participants (Ne) is not observed, but we do observe the number of bidders that finally participated, N. We believe N is likely to be correlated with the expected number of bidders since Ne = E[N] so that the latter can be used as a proxy for the expected number of bidders. We estimate models including the number of bidders (to see how much of the effect of the Directives feeds through an increase in competition) and we also estimate models excluding this variable in order to estimate the direct effect of the indicators on the final values. In this second case the indicators would be capturing all the net direct effects of the Directives.

Certain a priori expectations may also be defined with respect to the other variables. We might expect some CPV codes to be associated with higher or lower prices, given the characteristics of the goods or service that fall within those CPV codes. We might also expect lower prices for local authority contracts and high prices for central authority contracts, as local authorities tend to have smaller budgets and would require smaller quantities of goods or services than their central counterparts which can make use of their size in negotiation prices.

The number of bidders

3.21 The expected effects of the key explanatory variables in the number of bidders model is similar to those described for the outcome variable y. Most notably, DTk and DOk, are



expected to increase the number of bidders as information about contracts is made freely available to a larger pool of contestants.

Incorporating EMAT data

3.22 When dealing with EMAT data, the objects of the contract are not undifferentiated homogeneous products, but there is a significant non-price element involved. In such cases, one would expect the benefits from improved procurement practice to be distributed among both price and non-price outcomes. Any estimation of the effect of the directives based on the price alone could underestimate the effect of increased procurement disciplines.

3.23 It may be that the benefits of procurement are distributed in the same proportion as the criteria weights. This would mean that if an authority places 50 per cent weight on price, the cost savings that derive from publishing an ITT measured in cash terms would be only half as much as those that derive from contracts in which price is the sole criterion37 (the additional non-price benefits coming from higher delivery standards or quality, which are unobservable in our dataset).

3.24 To capture this idea, we allow the procurement-related indicators to vary according to the weights that are attached to price. This is done by constructing indicators that are interacted with EMAT price weights which range from zero to one. Hence, if the indicator effect is captured by the parameter k for contracts awarded on price only, the same effect for EMAT contract with a price weight of 0.5 would result in 0.5*k (so that the estimates of k are not distorted by the evaluation criteria weights). Procurement-related indicator variables interacted with weights are denoted by adding the suffix p to the variable. A description of the weight values that we have been able to extract from EMAT data is presented in Appendix 5: EMAT Price Weights (SP Sample).

Estimation Challenges

3.25 The current specification presents several challenges, these are described briefly below.

Estimation across MS

3.26 Our estimation approach starts with a pooled sample which includes all MS. To allow for differences between MS our strategy is as follows:

(a) In the pooled model, we first introduce dummy variables to allow MS-specific differences. Dummy variables would also be interacted with relevant coefficients to allow different MS-specific slopes.

37 For example: if there were a 5 per cent improvement in quality and a 5 per cent reduction in price, on a 100 contract the savings in cash would be 5, which is half of total savings.



(b) In cases where significant differences are found between MS we estimate separate models for different groups of MS.

Truncation

3.27 We exclude observations beyond certain threshold levels38 that we suspect to be outliers which make, by construction, the distribution of the dependent variable not normal but with truncated tails. As most models based on OLS regressions are likely to be misspecified in these circumstances, we experiment with models that correct for this problem by using truncated regression models.

Testing for heteroskedasticity

3.28 In all cases, we carry out the standard BreuschPagan (1979)39 and CookWeisberg (1983)40 tests for heteroskedasticity, which test whether the dispersion of the error terms changes with the value of the dependent variable. Where we find evidence of heteroskedasticity, we run regressions using methods pioneered by Huber (1967)41 and White (198042, 198243) designed to correct for this problem.

Endogeneity

3.29 The main concern regarding endogeneity is that N may be affected by unobserved factors (as shown in equation 2) that also affect the winning bid values (y in equation 1). If these were the case, the estimates in equation 1 would be biased. The hope, however, is that y* would act as a proxy for most unobservable factors, and so N would not be correlated with the errors in equation 1.

3.30 To test the endogeneity of N we run instrumental variable regressions and test whether the estimated coefficients differ systematically between the regressions without instruments. We use tests proposed by Hausman (1978)44.

3.31 At issue is which type of instruments to use. We use a variable related to the number of bidders in similar contracts in other time periods. For each observation, we use the number of bidders in its same CPV code and MS, averaged over the previous year. By construction, the instruments are correlated with N (as they relate to the same CPV level

38 Details are given in Section 4: Data. 39 Breusch, Trevor S and Pagan, Adrian R (1979) A simple test for heteroscedasticity and random coefficient variation

Econometrica, Vol 47, p1287-1294. 40 Cook, R Dennis and Weisberg, Sanford (1983) Diagnostics for heteroscedasticity in regression Biometrika,Vol 70, p1-10. 41 Huber, Peter J (1967) The behavior of maximum likelihood estimates under nonstandard conditions in Vol. 1 of Proceedings of

the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Berkeley: University of California Press, p221-233. 42 White, Halbert (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity

Econometrica, Vol 48, p817-838. 43 White, Halbert (1982) Maximum likelihood estimation of misspecified models Econometrica, Vol 50,p1-25. 44 Hausman, Jerry A (1978)Specification tests in econometrics Econometrica, Vol 46, p12511271.



as the observation) and because they refer to the previous year they are uncorrelated with the error terms in equation 1.

3.32 We also estimate separate models which exclude the number of bidders from the regressions.

Testing for model specification

3.33 For the linear regressions we use the Pregibon (1979)45 linktest, which tests whether linear combinations of predicted values after a regression have any further explanatory power in explaining the dependent variable.

3.34 In order to ensure the models are correctly specified we introduce the following variations:

(a) The use of estimation methods robust to heteroskedasticity.

(b) Estimation with models including MS specific effects (fixed effects and allowing for different slopes on different parameters).

(c) Inclusion of different explanatory variables.

(d) Inclusion of squared terms for some variables to allow for non-linear relationships.

(e) We introduce an interactive term for indicator variables to allow for differences in the price weight criteria in EMAT data.

(f) The use of models for truncated data.

45 Pregibon, Daryl (1979) Data analytic methods for generalized linear models, PhD thesis, University of Toronto.

Data


4 DATA

4.1 In this section we first present a brief description of the TED / MAPPs database, on which our study is based. We then provide an overview of the construction of the sample used in our analysis together with descriptive statistics. Finally, we assess the representativeness of the samples.

Description of the MAPPs/TED Dataset

4.2 The MAPPs database includes all notices published in the European public procurement journal Tenders Electronic Daily (TED) since 1993. TED is the online version of the 'Supplement to the Official Journal of the European Union' and contains all published active notices.

4.3 At present, contracting authorities are required to send notices to the Office for Official Publications or publish them on their buyer profiles, from where they are taken by the Office for Official Publications for publication. These notices may be any one of the 13 Standard Forms given in Commission Regulation (EC) No 1564/2005.46 The relevant information on contract award notices (CAN) are contained in Forms 3 and 6:

(a) Standard Form 3 relates to all purchases covered under the Procurement Directives from individual MS as well as EU institutions. It provides information both for the contracts as a whole, as well as the various specific awards (corresponding to the lots of the tender) that were commissioned within the overall contract. Examples of the information collected in Standard forms 3 are given in Table 2 below.

(b) Standard Form 6 relates to procurement by utilities and contains information of the price paid, country of origin, whether the contract was awarded to a tenderer submitting a variant and whether tenders were excluded for being abnormally low. Examples of the information collected in Standard 6 are given in Table 2 below.

46 On 21st October 2005 new standardised forms were introduced for recording the notices. At this time, the Publication Office switched into the new forms and all notices sent to TED electronically after this date were published in the new format. These standardised forms were intended to be the sole medium for publishing notices from 1 February 2006 onwards (at the latest).

Data


Table 2: Information available in Standard Forms 3 and 6

Awarding authority information - Name and address or authority - Postal code of authority - Type of authority (SF3 only) and main activity - Whether the authority was purchasing on behalf of other authorities

Contract information - Notice number - Title of contract - Type of contract (i.e. works, supplies or services) - NUTS Code47 - Framework agreement / dynamic purchasing system - Short description of contract - Location of works, delivery or of performance - Common Procurement Vocabulary (CPV) code - Total final value of contract

Procurement procedure - Type of procedure (e.g. open, restricted etc.) and the justification if a negotiated procedure is used - Award criteria (i.e. the lowest price or the most economically advantageous tender) - Weighting if economically most advantageous approach used - Whether electronic auction used - Whether a prior information notice was published and the notice number in the Official Journal of the European Union

(OJEU) - Information on the appeals procedure, including body responsible for appeals

Specific award information - Specific award number - Date of decision - Number of offers received - Name and address of winner - Date of dispatch of notice

Specific award values - Initial estimated total value of contract - Total final value of contract (or highest and lowest offers received - Length of contract - Price paid for bargain purchases (SF 6 only) - Country of origin of product or service (SF 6 only) - Whether the contract was awarded to a tenderer who submitted a variant (SF 6 only) - Whether tenders were excluded for being abnormally low (SF 6 only)

Specific award structure - The proportion / value of work being undertaken by a subcontractor

Annex D - Justification for award of contract without prior notification

Source: Commission Regulation (EC) No 1564/2005.

Description of Dataset

4.4 On receipt of the data, DG Internal Market undertakes a detailed process for conforming the data from different formats. This involves several algorithms and procedures that

47 The Nomenclature of Territorial Units for Statistics (NUTS) was established by Eurostat in order to provide a single uniform breakdown of territorial units for the production of regional statistics for the European Union.

Data


choose the best value automatically from the various estimates, final values and other relevant data such as VAT rates and currencies provided.48 Because of the intensive process required in unifying the data, these are only available from 2006 to 2009.49

4.5 Since there is no obligation that each field in a Standard Form must be filled for the notice to be published, there are many fields in the standards forms that are often left empty by the authorities/entities.50 Data are therefore often missing for different type of variables and this has an effect on the sample we use in our analysis. In few instances we have also encountered anomalous observations which, after examination, we consider as errors in the data and we subsequently exclude in our analyses.

4.6 For this work, we use only a subset of variables present in the MAPPs database. The master dataset containing all the information received by us from the MAPPs extractions we call the Population dataset (D). Each observation corresponds to a unique specific award. It covers all the contracts recorded in the MAPPs database for all MS for the years 2006-09.

4.7 From this, we exclude anomalous observations, as well as observations for which we do not have a total final value or an estimated value at the specific award level. This is the minimum information we need to be able to run basic versions of either of our models. We call this the Savings sample (S).

4.8 We may carry out three further restrictions, depending on characteristics of the data. These are:

(a) Including only those observations where the weight assigned to price in the tender evaluation criteria51 are available (the SP sample). This will be necessary if we find that the effect of procurement practices on final value is different depending on how important price is as an evaluation criterion.

(b) Including only those observations that were above the OJEU publication thresholds (the ST sample). This will be necessary for testing whether the dynamics between procurement practices and outcomes work differently above and below the publication thresholds.

(c) Both of the above (the STP sample).

48 There is also a manual checking process on high values of aggregated contract totals, although the same process is not undertaken for single contracts individually.

49 Data pre-2006 were collected using forms following a different format and are thus not comparable. 2010 data had not at the time of this work gone through the process.

50 In addition there may be missing records, as the Publication Office only publishes notices that have at least the most important information such as the object of the procurement, the contracting authority, etc.

51 For specific awards awarded on the lowest price criterion, this is 100%. For specific awards awarded on EMAT criteria, this is the weight assigned to price.

Data


4.9 Our analysis is based on the SP sample, i.e. the sample where we exclude specific awards, where we do not have a final or estimated price, and where we cannot determine the weight assigned to price in the evaluation criteria. It includes contracts both above and below the OJEU publication thresholds.

4.10 Further details regarding the construction of these datasets can be found in Appendix 1: Details on Construction of Datasets.

Description of Key Variables

4.11 We use a range of indicator variables to quantify the effects of measures related to transparency, openness and centralisation measures introduced by the Directives.

4.12 There are four possibilities related to publication of previous information of contracts: a PIN is published, and ITT is published, or both PIN and ITT are published. For each contract, these are measured with dummy variables (trans_itt_only, trans_pin_only, trans_both) and they relate to contracts for which there was no publication of any kind.

4.13 We also identify four possibilities for the type of procedure used: open, restricted and contracts for which the use non-standard procedures is justified (either because they refer to contracts awarded without prior publication of ITT in OJEU for being cases listed in Annex D as II-B services, or exemptions or outside the scope of directive; or because there is a justification, Annex D, for using negotiated procedures). For each contract, these are measured with dummy variables (proc_opn, proc_rst, proc_ext) and they related to contracts for which non-standard procedures were used (accelerated restricted, competitive dialogue, negotiated with competition, accelerated negotiated, negotiated without competition) or non-standard procedures were used without being exempt or no justification was given.

4.14 The variable for centralised purchases is recorded as a dummy variable (cen) which identifies whether the contract authority is purchasing on behalf of others contracting authorities, compared to a situation when it is not.

4.15 We provide short descriptions of the key variables in our dataset in Table 3.

Data


Table 3: Description of key variables

Name Short description Long description Dependent variables lntfv Final value (ln) The (natural logarithm of the) final award value of the specific award in Euros num Number of bidders The number of offers received for the specific award

Indicator variables trans_pin_only PIN 1 if there was a previous notice of a forthcoming procurement, 0 otherwise. This relates to

standard forms 1, 4, 7 and 8 and includes Prior information notice and Notice on a buyer profile and in the case of utilities Periodic indicative notice and Qualification system excluding calls for competition (as provided by the Commission services).

trans_itt_only ITT 1 if a contract notice was published, 0 otherwise. This relates to standard forms 2, 4, 5, 7, 11, 9, 10, and 12 and includes Contract notice; Contract notice Utilities; Contract notice Contracts to be awarded by a concessionaire who is not a contracting authority; Simplified contract notice on a dynamic purchasing system; Public works concession; Design contest notice; PIN+ITT includes both. In the case of utilities it includes Periodic indicative notice and Qualification system with calls for competition.

trans_both ITT + PIN 1 if both ITT and PIN are published proc_opn Open procedure 1 if the open procedure was used; 0 otherwise proc_rst Restricted procedure 1 if the restricted procedure was used; 0 otherwise proc_ext Extenuating circumstances 1 if a non-standard procedure was used and under special circumstances, 0 otherwise.

The extenuating circumstances included the following: all the CPV codes related to the contract fell under the exemptions (except where an ITT was published regardless) or if a justification was provided under Annex D for non-publication of a contract notice.

cen Centralisation 1 if the contract authority is purchasing on behalf of others contracting authorities p Price weight suffix Indicator variable with p suffix indicates interaction with the weight assigned to price in the

tender evaluation criteria

Control variables lnest Estimated value (ln) The initial estimated total value of the specific award in Euros lnnum Number of bidders (ln) The number of offers received for the specific award (control for outcome regressions) msd_** MS dummies 1 if the authority was located in a given country; 0 otherwise cpv** High level CPV 1 if the contract related to a given high level CPV code (as defined by the first two digits of

the eight digit CPV code); 0 otherwise aad_gov Authority type 1 if the awarding authority was the central government; 0 otherwise aad_loc Authority type 1 if the awarding authority was a local authority; 0 otherwise aad_uti Authority type 1 if the awarding authority was from the water, energy, telecoms or transport sectors; 0

otherwise aad_law Authority type 1 if the awarding authority was a body governed by public law; 0 otherwise aad_agn Authority type 1 if the awarding authority was a national or federal agency / office; 0 otherwise aad_agr Authority type 1 if the awarding authority was a regional or local agency / office; 0 otherwise aad_oth Authority type 1 if the awarding authority was of any other type; 0 otherwise yrd* Year 1 if the contract was awarded in a given year; 0 otherwise fgn Overseas award 1 if the specific award was awarded to an overseas contractor; 0 otherwise

Source: Europe Economics.

Data


Descriptive Statistics for SP Dataset

4.16 Here we provide a discussion of the key features of the savings dataset excluding EMAT data (SP dataset), which we will use to carry out the regressions based on procurement outcomes. Graphs additional to those presented in the main text can be found in Appendix 3: General Description (SP Sample), Appendix 4: Dependent Variables (SP Sample) and Appendix 5: EMAT Price Weights (SP Sample).

General description

4.17 The SP dataset contains information on 175,167 specific awards. The distribution of these specific awards (Figure 1) across MS is uneven, with PL accounting for about 50 per cent of them. We are aware that the high number of specific awards in PL is due to a national legislation which for some sectors mandates the publication of all contracts if the sum total of procurement over a certain time period exceeds the threshold.52

4.18 As regards the value of procurement (Figure 1), this distribution is less uneven. PL accounts for the largest volume of procurement in our sample, but IT is a close second. UK and ES are third and fourth, respectively. This can be explained by the different average specific award sizes, which is highest by far in the UK and, given its current legislation, smallest in MT, LT and PL (average contract sizes are provided in Figure 18 of Appendix 3: General Description).

52 Act of 29 January 2004 Public Procurement Law, Journal of Laws of 2004 No. 19, item 177.

Data


Figure 1: Procurement by MS

0 20,000 40,000 60,000 80,000Number of specific awards

PLIT

FRESRODECZUKHUSKSI

ELLTCYBELVATFI

NLDKSEPTBGIE

MTEELU

Number of specific awards by MS

0 10,000 20,000 30,000 40,000Total specific award value ( '000,000)

PLIT

UKESCZDEFRELROHUSKBESI

NLDKSEATFI

LVCYIE

PTLT

BGEELUMT

Total value of procurement by MS

4.19 The number of specific awards by year shows a steady increase until reaching 60,000 specific awards in 2009, but rate of increase diminishes over time. The value of procurement jumps from 2006 to 2008, and then stays static for 2009, at a total value of around 70 billion (Figure 2).

Data


Figure 2: Procurement by year

0

20,000

40,000

60,000N

umbe

r of s

peci

fic a

war

ds

2006 2007 2008 2009

Number of specific awards by year

0

20,000

40,000

60,000

80,000

Tota

l spe

cific

aw

ard

valu

e (

'000

,000

)2006 2007 2008 2009

Total value of procurement by year

4.20 The distribution of contracts is very different across CPV codes53. Medical equipment, pharmaceuticals and personal care products (CPV 33) accounts for the largest number of specific awards, but the total value of these is quite small (Figure 3). This is driven almost entirely by the large number and small total value of contracts in this CPV code in PL. The CPV accounting for the most value by far is Construction work (CPV 45), and this holds true in all the large MS (MS level graphs are presented from Figure 21 to Figure 29 in Appendix 3: General Description (SP Sample)).

53 Descriptions of CPV codes are provided in Appendix 2: CPV Codes.

Data


Figure 3: Total procurement in different CPV codes

0 10,000 20,000 30,000 40,000 50,000Number of specific awards

3345779071341579305044666085723991384280323124184855433564

0929322146373161951706575377641

Note: As some specific awards refer to more than oneCPV code, several specific awards are counted twice

Number of specific awards inhigh level CPV codes

0 20,000 40,000 60,000 80,000 100,000Total specific award value ( '000,000)

453390716650603455918572307964443277

03193156539424818924335707538802476516322147319164137

Total value of procurement inhigh level CPV codes

Dependent variables

4.21 Looking at the distribution of specific award values, we find a large number of very small specific awards, with the number of specific awards progressively decreasing as specific award size increases (Figure 4). There are large differences across MS: countries like DK, UK, IE and SE have a higher density of larger contracts, while some like CZ, FR, PT and SI are highly skewed towards extremely small contracts. In fact, the PL distribution is the most skewed, confirming the earlier observations of large numbers of extremely small contracts. Several country level distributions are bi-modal, indicating that large numbers of contracts tend to be published at around two main values (Figure 30 and Figure 31 in Appendix 4: Dependent Variables (SP Sample)).

Data


Figure 4: Final and estimated values

0 100,000 200,000 300,000 400,000 500,000Value ()

Density Final value Estimated value

Note: Only includes specific awards with estimated or final values less than 500,000

Distributions of final and estimated values: histograms and kernel density estimates

5 10 15 20Natural logarithm of value

Final value Estimated value

Kernel density estimates of distributions ofnatural logarithms of final and estimated values

4.22 Looking at the distribution of the number of bidders (Figure 5), we see that most specific awards involve just 1 bidder, followed by 2, 3, 4 and decreasing with size. However, there are again large differences across MS: for example, in DE, FI and IE the most common number is 3, in the UK it is 4. On the other hand, there is a very high density of 1 bidder specific awards in LT, PL and SK (Figure 32 in Appendix 4: Dependent Variables (SP Sample)). The high frequency of low number of bidders is a feature of the sample we use in the analysis and this does not correspond to the frequencies of the population. In the next subsection we argue that this has no impact on the regressions results if the observations excluded from the analysis are at random (or without relationship to the parameters of interest).

Data


Figure 5: Number of bidders

0 10 20 30Number of bidders

Note: Only includes specific awards with less than 30 bidders

Distribution of number of bidders

Explanatory variables

4.23 Looking at the type of awarding authority, we see that the most contracts are awarded by bodies governed by public law (31%), followed by other (24%) and local authorities (21%) (Figure 6). There are some interesting country-level differences. The share of bodies governed by public law in PL contracts is extremely high, and this drives the EU aggregate share to a large extent. Looking at the MS level we see that in most large countries like UK, DE, FR and IT the largest share belongs to local authorities. In small countries like CY, MT and LU, the share of central government is very high.

Data


Figure 6: Awarding authority type

12%

21%

8%

31%

24%

1%3%

Central government

Local authoritiesWater, energy, telecomsand transport sectors

Body governed by publiclawOtherNational or federalagency/office

Local or regionalagency/office

Type of awarding authority

0

10

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30

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80

90

100

Per

cent

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of s

peci

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AT BE BG CY CZ DE DK EE EL ES FI FR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK

Type of awarding authority by MS

Central government

Local authoritiesWater, energy, telecomsand transport sectors

Body governed by publiclawOtherNational or federalagency/office

Local or regionalagency/office

4.24 By type of contracts, we see that the largest share is supplies, followed by services and works (Figure 7). This is to be expected, given the relatively high threshold level for works contracts. There are, again, significant differences at the MS level: some countries (UK, SE and EL) mirror the EU level shares closely and have the most specific awards being related to service contracts; while some others (like LU, FR and AT) have a significantly larger proportion attributed to works.

Data


Figure 7: Contract type

37%

53%

9%

Services Supplies Works

Type of contract

0

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Per

cent

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AT BE BG CY CZ DE DK EE EL ES FI FR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK

Type of contract by MS

Services Supplies Works

Indicator variables

4.25 The three sets of indicator variables (transparency, openness and centralisation), are shown in Figure 8.

4.26 In terms of transparency, we find that most specific awards relate to contracts which publish only an ITT (60%). A significant proportion (10%) publish both ITT and PIN, while only in very few instances only a PIN is published (2%). Over a quarter of contracts publish neither an ITT nor a PIN. There are interesting country level differences. Some MS publish much less (both ITT and PIN) than others: in RO, NL and EE more than 50% of specific awards are not published (FR is close to 50%) whereas in MT almost all are

Data


published in some form. Also, SK has the highest incidence of both an ITT and a PIN being published (roughly 40%).

4.27 In terms of openness, we find that the use of the standard procedures (open and restricted) is most popular, with predominance of the open procedure (84% compared to 5%). The use of the open procedure is much preferred to the restricted procedure in all MS, except for UK which has a very high incidence of the use of the restricted procedure (around 55%). Moreover, the use of other procedures varies across MS, accounting for extremely high proportions in EE (almost 60%), SK, LV, HU and LT.

4.28 In terms of aggregation, we find that a very small proportion of specific awards are procured in an aggregated manner. The proportion is small at the MS level as well, with some

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Estimating the Benefits from the Procurement … · 2/1/2006 · Directives econometrically by identifying and measuring relationships between improved ... procurement processes and