Article & Essay


  • DATE WRITTEN : 2020-11-03
  • WRITER : MinSoo
  • VIEW : 1579
In the past few years, a significant number of civil damages lawsuits have been litigated following the prosecution of various public construction bid-rigging cases in Korea. Between 2009 and 2011, during the administration of former President Myung-Bak Lee, a massive number of large-scale civil engineering and environmental infrastructure projects were commissioned in the form of competitive bids by the Public Procurement Service (¡°PPS¡±). However, after a new administration came to office in 2013, feasibility studies were carried out for the engineering projects commissioned under the previous administration, and multiple bid-rigging schemes came to light involving projects commissioned not only by the PPS, but also local governments and public corporations. The number of bid-rigging cases involving construction companies sanctioned by the Korea Fair Trade Commission (¡°KFTC¡±), which was 0 in 2011, 4 in 2011 (22 companies, KRW 129.2 billion), and 2 in 2013 (4 companies, KRW 1.9 billion), went up to 18 in 2014 (42 companies, KRW 849.6 billion).

In the past, the number of damages claims filed in Korea was relatively small compared to the number of bid-rigging cases sanctioned by the competition authority. For example, the number of bid-rigging violations fined by the KFTC was 26, 34, and 24 in 2010, 2011, and 2012 respectively (KFTC, 2013), but only 4 of those cases had led to trial court rulings on damages by June 2014 (Song, 2016). However, the rapid increase in public-sector bid-rigging cases in 2014 led the PPS to establish guidelines on when and how to pursue damages claims, and to act as the plaintiff in damages claims for bid-rigging in public sector construction projects commissioned by government agencies, including some local governments and public corporations, or to support the litigation efforts of the commissioning agencies. This led to a significant increase in the number of damages claims being filed with regard to bid-rigging schemes involving public construction projects.

In damages claims related to bid-rigging, an expert appraiser appointed by the court submits his/her estimate of the damages incurred, which serves as the basis for the court¡¯s determination of the damage amount, while the parties submit opinions from their own respective experts on the appraisal results. And a wide variety of issues on estimation of damages have been raised and argued by court-appointed appraisers and expert witnesses for both plaintiffs and defendants in recent damages litigation involving public construction bid-rigging. In the following sections, I will address some of those issues including (i) how to reflect the product quality of highly differentiated products, (ii) how to calculate the but-for-price in bid-rigging cases, and (iii) how to deal with bid ¡®dumping¡¯ or abnormally low bids (ALBs).

Product Quality of Highly Differentiated Products
In lawsuits seeking damages for bid-rigging in public-sector construction projects, there have been attempts to quantify damages on the basis of simple comparisons with the bid rates for a small number of other construction projects of the same category as the project in dispute or, in the case of multi-section constructions projects, the winning bid rates for adjacent construction zones that were not subject to bid-rigging . There have been also attempts to compare the winning bid price of the project in dispute with ¡°normal costs¡± calculated based on the project design . However, most damages calculation studies in Korea applied the yardstick method, which uses an econometric analysis to compare the project where bid rigging occurred with other similar projects where bid-rigging did not occur.

In a typical product market, the standard market is defined in terms of similar products that were not subject to the cartel, such as similar products of non-cartel members or products exported by cartel members. However, in a construction project, the construction work involved in each tender is a highly differentiated product that is unique in nature, which makes it difficult to compare with construction work commissioned in other tenders. The bid project characteristics commonly adopted by academic papers and by court appraisers and parties¡¯ expert witnesses in estimating damages includes, among others, type of project, bidding system, size of project, project capacity, and the distance between the work site and the vendor. Among the explanatory variables of winning bids, design score deserves particular attention. In bids with technical proposals such as Design Build or Turnkey contracts and Design-Build Bridging contracts, design is an important factor in addition to cost when selecting winning bidders, which means a bidder with excellent design capacity can have a high chance of winning the bid even with a relatively high bid price. Therefore, when estimating the but-for-price or the but-for-bid rate, the characteristics of the project and the design capacity of the bidders can serve as a proxy for construction quality and be included as an explanatory variable of winning bids.

While the absolute design score of the winning bidder is important, the relative score in comparison to competing bidders can actually be more meaningful. The relative design score of the winning bidder can be calculated in a variety of ways, and in actual appraisals, the following methods have been used: (a) the design score of the winning bidder relative to the average design score (winning bidder¡¯s design score - average design score of bidders), (b) the ratio of the winning bidder¡¯s design score relative to the average design score {(winning bidder¡¯s design score - average design score) / average design score}, and (c) the design score relative to the runner-up score (winning bidder¡¯s design score - highest design score among unsuccessful bidders), with the results sometimes being weighted based on the degree to which the design score is reflected in selecting the winning bidder.

Unobserved Bidding Strategies in Bid-Rigging Cartels

In general, when calculating cartel damages, a price equation is derived using transaction data from products that were not subject to the cartel and the but-for-price is calculated by applying coefficient estimates to the explanatory variables of the cartel products. The problem with bid-rigging cartels, however, is that product quality as well as the characteristics of the tender process can change depending on whether there is a cartel. For example, if there is a limited number of construction companies capable of carrying out large-scale infrastructure construction projects and the majority of these construction companies participate in a cartel, the number of bidders would be fewer than there would have been in a competitive situation. Also, if the construction companies get together to determine the winning bidder in advance, and had others place straw bids, the design quality would be lower than if there had been competition. If a bid-rigging cartel not only changes the winning bid price but also structurally affects bidder strategies, it may not be appropriate to estimate the but-for-price based on data directly reflecting the characteristics of the rigged tender.

One of the suggested methods to resolve this issue is to replace the characteristics of the collusive tender with the values that would have been observed if there was no collusion, i.e., the ¡°but-for-characteristics.¡± For example, in the ¡°Expert Report on Damages Associated with Bid-rigging in Four Major Rivers Project¡±, a formula for calculating the number of bid participants was derived from non-collusive tender data, and the ¡°but-for-number of participants¡± was estimated for the collusive tenders in dispute . However, this method can be subject to criticism that it may make the estimation less efficient and exacerbate the measurement error problem for variables by excluding the collusive tender data from the estimation process.

The ¡°Expert Report on Estimated Damages Associated with Bid-rigging in the Unbuk Sewage Treatment Plant Project¡± and the ¡°Expert Report on Estimated Damages Associated with Bid-rigging in the West Sea Line (Hongseong-Songsan) Double-track Train Zone 5 Project Involving Four Bidders¡± used both collusive data and non-collusive data and used a collusion dummy variable to reflect the characteristics of both datasets. Instead of adjusting the value of the characteristics of the collusive tender, an interaction term for the value of the characteristics and the collusion dummy was included, thereby setting the coefficient of the characteristics for the collusive tender (such as number of bid participants and design score, which can be influenced by the strategy of bid participants) differently from the coefficient for the non-collusive tender.

There have been additional discussions surrounding other proposals such as matching methods, which use variables other than those that can be affected by collusion to match collusive and non-collusive tenders , but as of yet there is no consensus on how to reconstruct the but-for-characteristics of a bid.

Treatment of Outliers
Treatment of outliers is an age-old problem in statistical analysis. The reason why attention is paid to outliers in bid-rigging cartel cases involving construction projects is because non-collusive data may contain observed values that are unlikely to be seen in a normal competitive situation. For example, construction firms occasionally bid below cost to build their track record for certain types of construction work or to achieve their annual contract target. Also, they may choose win the bid at a low price but then lower the quality or renegotiate with the project owner for additional fees, in which case abnormally low bids (¡°ALBs¡±) can be observed. On the other hand, abnormally high bids can also be observed when there are collusive tenders that go undetected.

Some of the expert reports on damages claims in Korea use statistical methods to eliminate outliers. For example, in the ¡°Expert Report on Damages Associated with Bid-rigging in Four Major Rivers Project¡±, outliers were defined as when the absolute value of the residuals of the regression analysis was no less than three times the standard error of the residuals, and were eliminated from the analysis . The ¡°Expert Report on Damages Associated with Bid-rigging in Bank Reinforcement Project for Farming Reservoirs¡± and the ¡°Expert Report on Gyeongin Canal Facility Construction Project¡± identified excessively influencing observations using Cook¡¯s distance and eliminated those observations.

However, it is open to debate as to whether it is appropriate to identify and eliminate outliers by statistical means without analyzing the cause behind those outliers (ALB or undetected collusion). Econometrics text books recommend presenting the results of an analysis both with and without outliers, as it is not always desirable to eliminate outliers unless there is clear evidence of their cause, such as data input error.

Min Su Park(Sungkyunkwan University, Dep. of Economics)