The empirical results of this paper, which compiles bidding data from a variety of Ontario municipalities over time, suggest that restricting tendering to a select group of firms on the basis of their workers’ affiliations will lead to higher costs for municipalities than if they tendered their projects to all qualified bidders, with the strong possibility that municipalities will pay a substantial magnitude more.
Theoretical considerations as well as results from the general literature suggest that restrictive bidding should widen the gap between the lowest winning bid and the benchmark bids as well as increasing the dispersion across bids. Conversely, the competitive pressures from open bidding should reduce the gap between the lowest winning bid and the benchmark bids as well as reducing the dispersion across bids—essentially fostering the law of one price.
Our empirical analysis confirms these expectations. No matter which benchmark is used (the runner-up bid, the average bid, the maximum bid) or the coefficient of variation, in the period when Hamilton was on restricted bidding, that restricted bidding was associated with a statistically significant wider gap between Hamilton and the various open bidding regimes, as well as greater dispersion across bids (row 4 in table 3). The magnitude was also very large, effectively doubling the gap that prevailed in the open bidding regimes.
These substantial impacts highlight that restricted bidding reduces the competitive pressures that can otherwise discipline the bidding process toward a competitive norm—that provides municipalities with best value. Our results support the theory that restricting competition on public projects leads to upward pressure on prices paid for construction by municipal governments. It lends further support to the rationale behind the almost universal adoption of procurement and policies by public bodies that encourage or require open competition on public projects.
THE IMPACT OF RESTRICTIVE TENDERING IN MUNICIPAL CONTRACTING IN ONTARIO
This report is the fifth in a series of Cardus Construction Competitiveness Monitor (CCCM) reports, which examines the effect of restrictive tendering on public construction projects in Ontario. The particular type of restriction studied is one whereby bidding on public construction projects is limited, by law, to firms associated with a particular union. As noted in the first paper, by Brian Dijkema, Ontario Municipal Construction Markets (2012), a clause in the construction section of Ontario’s Labour Relations Act inadvertently restricted tendering on many construction contracts in cities and municipalities, school boards, and Crown corporations to a small subset of unionized contractors. The second paper, by Stephen Bauld and Brian Dijkema with James Ton, Hiding in Plain Sight: Evaluating Closed Tendering in Construction Markets (2014), noted how such restrictions work counter to widely accepted procurement practices and public policies governing procurement more generally. It focused on the negative aspects of the restrictions on competition associated with restricted tendering and on the positive aspects of the enhanced competition associated with a more open bidding process. The third paper, by Brian Dijkema, Tuning Up Ontario’s Economic Engine: Competitive Construction in the City of Toronto (2015), provides a critical assessment of a 2008 staff report for the city of Toronto that provided an estimate of only a 1.7 percent cost increase from the tendering that was restricted to union contracts in construction in Toronto. Their paper discussed related studies that suggest the cost increase for Toronto would be more in the neighbourhood of 20 to 30 percent and perhaps as high as 40 percent. The fourth report, Restrictive Tendering: Protection for Whom?, By Brian Dijkema and Morley Gunderson (2016), reviewed the literature on the impact of restrictive tendering as well as outlining the methodologies and data requirements that would be necessary to estimate the impact of restricted tendering. This fifth report builds on that previous report by providing empirical evidence on the impact of restricted tendering in municipal government contracts in construction in Ontario.
The earlier report by Dijkema and Gunderson (2016) highlighted a wide range of factors that motivate the empirical analysis of this report. They discussed the importance of cost containment in public tendering arising from various factors:
- Pressures to reduce deficits.
- Increased infrastructure spending fuelled by increased pressures on existing infrastructure, including the age of infrastructure and population growth.
- Recent corruption scandals in the tendering process including in Toronto.
- Growing public attention to the importance of an open, transparent bidding process to offset collusive behaviour among contractors.
They also highlighted the negative consequences of restrictions on the bidding process that give monopoly or oligopoly power to a small number of bidders. These include the following:
- Higher prices (i.e., higher bids) knowing that there are fewer competitors that may bid lower.
- Fewer of the services consumed (e.g., construction infrastructure projects) given the higher prices.
- Less innovation and efficient practices because of less incentive to cut costs since they can be awarded the contracts at their higher costs. There is need for more infrastructure, but limited funds constrain growth.
- More discrimination because the contractors are under less pressure to cut costs by hiring the best people for the job.
- Devoting resources toward protecting their privileged positions and deterring new entry.
- Engaging in collusive bid-rigging.
- Expensive litigation in situations where tenders have not been conducted under an open, fair, and transparent basis.
- Extensive resources devoted to “defensive bulletproofing” RFPs (adding criteria that transfer greater risk onto contractors) and the tendering process to protect against potential liability.
- More complex contracting process caused by bulletproofing RFPs, which in turn can deter smaller contractors from bidding.
Dijkema and Gunderson (2016) also documented that the negative consequences of tendering not being conducted on an open, transparent, and competitive basis have been recognized extensively in public documents, the general academic literature on competition, and both domestic and international procurement guidelines. Because of these concerns and the importance of these issues, they called for empirical evidence of the effect of restrictions on the public tendering process. This report is a response to that call. It provides evidence of the effect of restrictions on tendering in municipal government contracts in construction in southern Ontario.
The report is organized as follows: We begin with brief discussion as to how restricted tendering in municipal government affects public construction contracts in Ontario. We then discuss the methodology used to estimate the impact of restricted tendering on various outcomes of the bidding process, before discussing the data used to estimate those impacts. Following this, we present the empirical results and discuss the implications of the evidence.
HOW RESTRICTED TENDERING OCCURS IN MUNICIPAL CONSTRUCTION CONTRACTS IN ONTARIO
As discussed in Dijkema (2012) the restrictive tendering we describe is the inadvertent consequence of labour law that forces governments to receive bids only from contractors affiliated with a particular subset of construction unions that are organized on a craft basis. These differ from non-union firms as well as other construction unions that are organized on an industrial or “wall-to-wall” basis (e.g., the Building Union of Canada, CUPE, CLAC, or Unifor, which also represent workers in the trades). These industrial unions bargain for all trades within a company, and they bargain on a company-by-company basis. In contrast, the craft unions and their contractors are subject to separate province-wide collective agreements that prevail for each trade, and which contain centralized wage schedules. Further, these province-wide collective agreements contain subcontracting clauses that prevent those who are signatory from contracting or subcontracting work to firms that have a different affiliation from the general contractor even if they are unionized with another union.
This situation occurs because labour relations in construction in Ontario are governed under a separate construction section of the Ontario Labour Relations Act. Labour Board decisions have interpreted the meaning of a “construction employer” broadly to include government bodies that contract out their projects through the tendering process, as virtually all do. This allows unions to organize a government entity (e.g., a municipality like Hamilton, Toronto, or the Region of Waterloo; a Crown corporation like Ontario Power Generation; or the Toronto District School Board) as if it were a private, for-profit contractor like, for instance, Ellis Don. This gives rise to restricted tendering not simply because they are now unionized, but because they become subject to the province-wide collective bargaining agreement, which contains clauses that disallow a given contractor from contracting or subcontracting to firms that are not associated with that particular union. For example, the city of Hamilton, which is organized by the Carpenters’ Union, can only tender projects for which carpentry work is involved to firms affiliated with the Carpenters’ Union. In effect this prevents firms whose workers affiliate with other unions like the Labourers International Union, as well as companies whose workers affiliate with alternative construction unions, or those whose workers choose not to affiliate with any union. The ultimate effect is that vast swaths of public construction work are placed under restrictions that are imposed not for procurement best practices, but because of an unrelated piece of labour law intended to achieve a separate and unrelated objective. Workers who exercise their right to affiliate with other unions, or no union, are forbidden to work on a public project because of that choice. In effect, only a subset of the population is able to bid on work that is paid for, and built on behalf of, the whole population.
RESTRICTED MUNICIPALITIES IN ONTARIO
As indicated in Dijkema and Gunderson (2016), our ideal comparison between restricted and open contracting regimes would involve comparing a measure of cost per unit of standardized or homogeneous output in the two regimes. An example of such a cost comparator would be public schools where there exist widely accepted standards for the cost of construction per square foot. This would allow us to cleanly test our expectation that costs would be higher under restricted regimes than those with open bidding regimes. Unfortunately, such standardized cost information is not available to us, at least at this stage. The recent Ontario Labour Board decision in 2016 whereby the Greater Essex County District School Board was deemed a “non-construction” employer may provide the possibility of such measurement in the future.
As an alternative, we use a number of measures that are available to examine the effect of reduced competition on the bidding process. We discuss those measures below.
Competition should foster bids that are closer to each other—effectively, the law of one price. In a competitive bidding environment, where equally qualified firms have equal access to a given market, bid prices will converge on the lowest price, as all firms attempt to provide the lowest price that enables them to win the job while meeting the parameters set by the project owner. This implies that competitive open bidding should lead to bids that are closer to each other and to the winning bid; conversely restrictive bidding should lead to bids that are further from each other and further from the winning bid.
To test this hypothesis, we created four outcome measures that would reflect the closeness of the bids. They are as follows:
- (Yw−Yn )/Yn where Y denotes the dollar value of the bid, the subscript w denotes the winning bid, and the subscript n denotes the benchmark of the runner-up bid, which is almost always the next-lowest bid.
- (Yw−Ya )/Ya where Y denotes the dollar value of the bid, the subscript w denotes the winning bid, and the subscript a denotes the benchmark of the average value of the bids.
- (Yw−Ym)/Ym where Y denotes the dollar value of the bid, the subscript w denotes the winning bid, and the subscript m denotes the benchmark of the value of the maximum or highest bid.
- Coefficient of Variation (CV), or the standard deviation divided by the mean, as a measure of overall dispersion or variation across all bids. Dividing the standard deviation by the mean effectively controls for the magnitude of the bids and ensures that the measure is “unit free.”
Since Yw, the winning bid, is the lowest bid (in all but few cases), each of the measures would be negative, reflecting the percent amount that the winning bid is lower than each of the other benchmarks. All measures are in percent terms so they can be compared across contracts of different sizes.
Given the law of the lowest price discussed above, the expectation is that competitive open bidding would reduce the gap or difference between the winning bid and each of the other benchmarks. Conversely, restricted bidding would increase the gaps leading to larger negative numbers.
We test this hypothesis by estimating the bid gap between the winning bid and each of these benchmark bids in Hamilton, a municipality that shifted from open to restricted bidding, and remained on restricted bidding for a time period that was sufficiently long for its impact to be detected (October 2005 to December 2011). These bid gaps are then compared to the gaps in twelve other open-bidding comparison group municipalities combined over the same time period. The twelve comparison group jurisdictions are contiguous or close to Hamilton with its restricted bidding. They are Brantford, Durham/Dufferin, Elgin, Guelph, Haldeman/ Norfolk, Halton, Niagara, Oxford, Peel, Perth, York, and Middlesex. Figure XYZ visualizes the geographical locations of these regions.
Hamilton is the only municipality in our data set that has restricted bidding over a time period that could reasonably reflect its effect on bid gaps. The Region of Waterloo also shifted from open to restricted bidding, but the post-restricted bidding period was insufficiently long (only eighteen contracts in the first eighteen months after shifting to restricted bidding) for its effect to be detected. Toronto and Sault Ste. Marie also have restricted bidding, but sufficient information on it was not available to us.
Our methodology involves comparing the various gaps between the winning bid and the various benchmark bids (runner-up, average, and maximum) as well as the CV, under the restricted bidding regime in Hamilton, compared to the gaps in the twelve comparison-group open bidding regimes in that time period. The expectation is that the gaps would be smaller in the open regimes since competition should reduce the gaps— the law of one price.
The differences in the bid gaps could be due to factors other than their being an open versus restricted bidding regime. To control for this possibility, we also estimate the gaps between Hamilton and the twelve open comparator jurisdiction in the pre-treatment time period when neither are affected by restricted bidding. This should capture the effect of factors other than restricted bidding that could affect the gaps. This pre-treatment gap that is affected by factors other than restricted bidding is then subtracted from the post-treatment gap that can affect both these factors and restricted bidding to get a purer estimate of the effect of restricted bidding alone.
We have less confidence in this “netting out” procedure for two reasons. First, the pre-intervention period in Hamilton is less than two years (January 2004 to August 2005) and involves few contract observations (twenty-six in the restricted jurisdiction of Hamilton and fifteen in the comparison jurisdictions). Second, it assumes that whatever factors affect the restricted jurisdiction and the open jurisdictions in the short pre-treatment period will continue to have their same effect in the post-treatment period. This could be reasonable if there was a longer pre-treatment period and their patterns were similar over that longer period, but it is not reasonable based on such a short pre-treatment time period. In essence, our ability to use the pre-treatment period to net out the effect of other factors will have to wait the availability of data for a longer pre-treatment period, which, because of the nature of public record keeping is very difficult to procure. As such, we will rely more heavily on the post-treatment-period data for comparisons between the restricted jurisdiction of Hamilton and the open-bidding comparison jurisdictions, recognizing fully the possibility that those differences could be due to other factors that we cannot control for at this stage.
An alternative way to present the analysis is to compare the difference in outcomes in the restricted jurisdictions after it shifted to restricted bidding compared to the period before they shifted, with this difference compared to the change in outcomes in the jurisdictions with open bidding. This is the conventional before-and-after comparison between jurisdictions that received a treatment (in this case moving to restricted bidding) compared to a comparison group of jurisdictions that remained on open bidding and did not move to restricted bidding.
In our presentation of the results we prefer the comparison based on the difference in the outcomes in the restricted jurisdictions minus the open bidding jurisdictions in the post-treatment period when restricted bidding is in place, less the difference in the pre-treatment period. This is so because in the case of Hamilton our data provides a reasonable time period when restricted bidding is in place (October 2005 to December, 2011), but a very short time period (January 2004 to September 2005) when both Hamilton and the comparison jurisdictions had open bidding. In essence, our pre-treatment-period differences are likely measured with considerable imprecision, while our post-treatment period is measured with more precision. As such, we have more confidence in the differences in the post-treatment period, and hence it is informative to have them measured on their own, recognizing that this difference may reflect the effect of other factors that are netted out by other factors that can only be measured with imprecision by the differences in the short pre-treatment periods.
The restricted jurisdiction Hamilton had information on the winning bid and each of the benchmark bids for 227 contracts spread over the six-plus-year post-treatment period October 2005 to December 31, 2011. The comparison group with open bidding had 53 contracts over that same period. As such, our comparison of restricted versus open bidding in the post-treatment period involved 280 contracts as observations. Prior to that period, Hamilton was on open bidding, but we have information for only 26 contracts in Hamilton and 15 in the comparison jurisdictions in the less-than-two-year pre-treatment period of January 2004 to August 2005. The post-treatment period refers to when Hamilton was on restricted bidding (the treatment), and the pre-treatment period refers to when it was on open bidding. The treatment or shift from open to restricted bidding occurred in September 2005. That month was left off the analysis since the shift to restricted bidding occurred in that month. The small number of contracts in the short pre-treatment period for Hamilton means that we have little confidence in the before-and-after comparisons for that jurisdiction.
For a small number of projects, information was missing on some of the middle bids. This was relevant only for our calculation of the average of the bids and the CV; they did not affect our calculation of the runner-up bid or the maximum-bid benchmarks. To provide an estimate of the missing bids to use in our calculation of the mean and CV, we conducted the following steps (done for only fourteen of our observations):
- Estimate the missing interval by subtracting the lowest bid for which information is available from the highest bid for which information is available.
- Divide by the number of missing bids plus 1. This is the same as the number of missing sub-intervals.
- Add that to the lowest bid available to estimate the first missing bid.
- Again, add that to the first missing bid to get an estimate of the second missing bid.
- Continue the process until all missing bids are estimated.
Table 1 provides a summary picture of the number of contracts in Hamilton both before (26 contracts) and after it shifted to restricted bidding (227 contracts in the shaded area) compared to the number of contracts in the twelve comparison-group jurisdictions both before (15 contracts) and after the time period September 2005 (53 contracts) when Hamilton shifted to restricted bidding. As indicated, the small number of contracts in the brief pre-treatment period means that we have little confidence in using them as a comparison group for before-and-after comparisons for Hamilton or to compare Hamilton and the comparison groups in the pre-treatment period.
The data are drawn from a variety of sources, including public bidding websites such as biddingo.com (a procurement portal used by most, if not all, municipalities in Ontario, as well as the provincial government, and Crown corporations), municipal procurement office records, and the records of contractors who agreed to share historical bidding data. All data (including those from contractors) are part of the public record, and the vast majority of the observations are from municipal procurement offices.
Prior to discussing the empirical results, it is useful to define some of the symbols that will be used in the subsequent presentation of the results. They are set out in table 2.
Note: B denotes % difference in the winning bid and benchmark, for example, runner-up (since the winning bid is lower than the runner-up the gap is negative); subscript r denotes restricted jurisdiction; subscript o denotes open bidding jurisdiction; subscript a denotes the post-treatment period when restricted bidding was in place for the restricted jurisdiction; subscript b denotes the pre-treatment period when open bidding was in place for all jurisdictions.
Table 3 gives our results for the different benchmarks: column 1 for the winning bid less the runner-up bid; column 2 for the winning bid less the average bid; column 3 for the winning bid less the maximum bid; and column 4 for the CV as a measure of overall dispersion. The presentation is complicated by the fact that the bid gaps are negative numbers since the winning bid is lower than the benchmark bids (runner-up, average, maximum).
RESULTS: WINNING BID LESS RUNNER-UP BID
We will discuss our results from column 1 in table 3 in considerable detail, since once that pattern is outlined it tends to apply to the other outcomes.
The first row of the first column of table 3 indicates that on average, across all bids, the winning bid was 11.4 percent lower than the runner up (i.e., mean (Yw−Yn )/Yn = -0.114). This includes the time period when Hamilton was on open bidding as well as on restricted bidding, as well as the comparison jurisdictions that were on open bidding over that same time period (January 2004 to December 2011).
The second row of the first column indicates that when Hamilton shifted to restricted bidding, the post-treatment gap between the lowest bid and runner-up bid was an above-average -0.131 (i.e., 13.1 percent). This is consistent with the expectation that restricted bidding reduces the competitive pressures that otherwise would make the runner up closer to the winning bid. In this case, the gap between the winning bid and the runner up became above average.