Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

PUBLICATION NO. FHWA-HRT-22-082 JUNE 2023 

Analysis of Material Source Mergers 

and Acquisitions on Project Delivery 

Quality and Costs
FOREWORD

There has been a concern that mergers and acquisitions (M&As) within industries that produce, 

supply, and install aggregates and plant-produced materials for transportation projects may result 

in reduced competition and higher prices for public sector construction projects. This report 

documents research undertaken to analyze relationships and trends that occur when M&As take 

place in materials supply. The study presents strategies that selected States have employed to 

minimize adverse impacts and protect taxpayers from unfair pricing and anticompetitive 

behaviors. These State department of transportation (DOT) practices may limit adverse impacts 

to competitive market share distribution, bid pricing, and overall project costs.

This report also examines multiyear collections of State DOT construction materials bid prices 

and processes to monitor and analyze State DOT practices for bidding and letting projects. The 

research team reviewed data covering a 10-yr period between 2006 and 2016 to explore trends 

across 31 States. Nine case studies provided additional information to understand better the state 

of the practice for assessing bid prices and monitoring industry activities. The report and 

accompanying technical brief (FHWA-HRT-22-081) offer insights into the challenges associated 

with determining price impacts of M&A activity in the construction materials industry.

Jean Nehme, Ph.D., P.E.

Director, Office of Infrastructure Research

and Development 

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

(USDOT) in the interest of information exchange. The U.S. Government assumes no liability for 

the use of the information contained in this document. 

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential to the 

objective of the document. 

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. Standards 

and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its 

information. FHWA periodically reviews quality issues and adjusts its programs and processes to 

ensure continuous quality improvement. 
TECHNICAL REPORT DOCUMENTATION PAGE

1. Report No.

FHWA-HRT-22-082

2. Government Accession No. 3. Recipient’s Catalog No.

4. Title and Subtitle

Analysis of Material Source Mergers and Acquisitions on 

Project Delivery Quality and Costs

5. Report Date

June 2023

6. Performing Organization Code:

7. Author(s)

Hannah Silber (ORCID: 0000-0003-0211-7934) and Jason 

Bittner (ORCID: 0000-0002-7920-8773)

8. Performing Organization Report No.

9. Applied Research Associates Inc.

6314 Odana Road Suite 11

Madison, Wisconsin 53719

10. Work Unit No.

11. Contract or Grant No.

DTFH6117C00002L

12. Sponsoring Agency Name and Address

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report; February 2017–May 2020

14. Sponsoring Agency Code

HRDI-20

15. Supplementary Notes

The Contracting Officer’s Representative was Matthew Corrigan (HRDI-20; ORCID: 0000-0002-1230-8462).

16. Abstract

State departments of transportation (DOTs) have expressed concern about mergers and acquisitions (M&As) 

occurring within the industries that produce, supply, and install aggregates and other materials for transportation 

projects. In particular, State DOTs have suggested the possibility that these construction industry M&As impact

price and competition. This research effort targeted a data analysis- and case study-focused approach to find and 

understand relationships or trends that occur with M&As. The study also presents activities selected States have 

employed to minimize adverse impacts and protect taxpayers from unfair pricing and anticompetitive behaviors.

These State DOT practices limit the adverse impacts of competitive market share distribution, bid pricing, and 

overall project costs. This study also examined multiyear collections of State DOT construction materials bid 

prices and processes to monitor and analyze State DOT practices for bidding and letting projects.

17. Key Words

Mergers and acquisitions, pricing impacts, 

construction costs, road-building materials, market 

share, competition

18. Distribution Statement

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161.

http://www.ntis.gov

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

223 

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized.
ii

 

 

 

 

 

 

 
iii

TABLE OF CONTENTS

EXECUTIVE SUMMARY .......................................................................................................... 1

Background ............................................................................................................................. 1

Purpose of the Report ............................................................................................................. 1

Goal of the Research ............................................................................................................... 1

Details of Approach ................................................................................................................ 1

Important Results ................................................................................................................... 1

CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW ......................................... 3

Review of How the FTC/U. S. DOJ Horizontal Merger Guidelines Have Been Applied 

to Mergers in the Highway Materials and Construction Fields ......................................... 8

Critical Findings of the Literature Review and Legal Guidance ....................................... 8

CHAPTER 2. DATA PROCESSING AND ANALYSIS ......................................................... 11

CHAPTER 3. STATE ASSESSMENTS ................................................................................... 15

Data Processing ..................................................................................................................... 15

AASHTO Region 1 ................................................................................................................ 16

Massachusetts ................................................................................................................... 16

New York .......................................................................................................................... 20

Pennsylvania ..................................................................................................................... 23

Vermont ............................................................................................................................ 27

AASHTO Region 2 ................................................................................................................ 30

Arkansas ............................................................................................................................ 30

Florida ............................................................................................................................... 34

Georgia .............................................................................................................................. 36

Louisiana ........................................................................................................................... 40

North Carolina .................................................................................................................. 42

South Carolina .................................................................................................................. 45

Tennessee .......................................................................................................................... 49

Virginia ............................................................................................................................. 52

West Virginia .................................................................................................................... 56

AASHTO Region 3 ................................................................................................................ 59

Illinois ............................................................................................................................... 59

Indiana............................................................................................................................... 63

Michigan ........................................................................................................................... 66

Minnesota .......................................................................................................................... 70

Missouri ............................................................................................................................ 73

Ohio................................................................................................................................... 77

Wisconsin .......................................................................................................................... 80

AASHTO Region 4 ................................................................................................................ 84

Arizona .............................................................................................................................. 84

California .......................................................................................................................... 87

Colorado ............................................................................................................................ 91

Idaho ................................................................................................................................. 94

Montana ............................................................................................................................ 98

Nebraska ......................................................................................................................... 101
iv

Nevada ............................................................................................................................ 105

New Mexico .................................................................................................................... 107

Oklahoma ........................................................................................................................ 110

Oregon............................................................................................................................. 113

Utah ................................................................................................................................. 117

CHAPTER 4. UNIT PRICE ANALYSIS ............................................................................... 121

CHAPTER 5. CHALLENGES AND OBSERVATIONS ...................................................... 127

Selecting Appropriate Bid item numbers ......................................................................... 127

Desired Parameter Availability ......................................................................................... 127

Inconsistent Bid item number Use..................................................................................... 127

CHAPTER 6. STATE OBSERVATIONS .............................................................................. 131

State Case Studies ............................................................................................................... 131

Case Study Interview Questions ..................................................................................... 132

Legal Analysis...................................................................................................................... 132

Identifying M&A Activity and Determining Processes to Address It ............................ 133

Proactive Monitoring ...................................................................................................... 133

Index Uses ....................................................................................................................... 134

Estimation Processes ....................................................................................................... 134

Tracking Firm Information ............................................................................................. 135

Regional Monitoring ....................................................................................................... 135

Unbalanced Bid Analysis ................................................................................................ 135

Tracking Cost Indexes .................................................................................................... 135

Diminishing Negative Impacts of M&A Activity ............................................................. 136

Bid Analysis .................................................................................................................... 136

Increasing Competition ................................................................................................... 136

Project Bundling and ACM ............................................................................................ 137

APPENDIX A. ANALYSIS OF MATERIAL SOURCE M&AS ON PROJECT 

DELIVERY QUALITY AND COSTS—LITERATURE AND MARKET REVIEW 

SUMMARY ............................................................................................................................... 139

Introduction ......................................................................................................................... 139

Material Costs ..................................................................................................................... 139

Case Studies ......................................................................................................................... 140

Methods of Analysis ............................................................................................................ 142

Data Availability ................................................................................................................. 143

Database Compilation ........................................................................................................ 143

APPENDIX B. CASE STUDY INTERVIEW QUESTIONS ................................................ 145

General ................................................................................................................................. 145

Prime Contractor Makeup ................................................................................................. 145

M&A Activities.................................................................................................................... 145

Material Suppliers .............................................................................................................. 146

Competition Issues and Concerns ..................................................................................... 146

Bidding Process ................................................................................................................... 146

Bid Analysis ......................................................................................................................... 146

Average Unit Prices ............................................................................................................ 147
v 

Other .................................................................................................................................... 147

APPENDIX C. CASE STUDIES ............................................................................................. 149

Case Studies Overview ....................................................................................................... 149

Arizona ................................................................................................................................. 149

Case Study Background .................................................................................................. 149

Quantitative Analysis ...................................................................................................... 150

Qualitative Analysis ........................................................................................................ 152

Summary ......................................................................................................................... 154

Colorado............................................................................................................................... 154

Case Study Background .................................................................................................. 154

Quantitative Analysis ...................................................................................................... 155

Qualitative Analysis ........................................................................................................ 161

Summary ......................................................................................................................... 163

Georgia ................................................................................................................................. 163

Case Study Background .................................................................................................. 163

Quantitative Analysis ...................................................................................................... 164

Qualitative Analysis ........................................................................................................ 165

Summary ......................................................................................................................... 167

Missouri ............................................................................................................................... 167

Case Study Background .................................................................................................. 167

Quantitative Analysis ...................................................................................................... 168

Qualitative Analysis ........................................................................................................ 170

Summary ......................................................................................................................... 172

Ohio ...................................................................................................................................... 172

Case Study Background .................................................................................................. 172

Quantitative Analysis ...................................................................................................... 173

Qualitative Analysis ........................................................................................................ 175

Summary ......................................................................................................................... 177

Oklahoma............................................................................................................................. 177

Case Study Background .................................................................................................. 177

Quantitative Analysis ...................................................................................................... 178

Qualitative Analysis ........................................................................................................ 180

Summary ......................................................................................................................... 181

Oregon .................................................................................................................................. 181

Case Study Background .................................................................................................. 181

Quantitative Analysis ...................................................................................................... 182

Qualitative Analysis ........................................................................................................ 188

Summary ......................................................................................................................... 190

Tennessee ............................................................................................................................. 191

Case Study Background .................................................................................................. 191

Quantitative Analysis ...................................................................................................... 191

Qualitative Analysis ........................................................................................................ 194

Summary ......................................................................................................................... 196

Wisconsin ............................................................................................................................. 196

Case Study Background .................................................................................................. 196

Quantitative Analysis ...................................................................................................... 197
vi 

Qualitative Analysis ........................................................................................................ 201

Summary ......................................................................................................................... 202

ACKNOWLEDGMENTS ........................................................................................................ 203

REFERENCES .......................................................................................................................... 205
vii 

LIST OF FIGURES

Figure 1. Chart. Types of mergers. ................................................................................................. 4

Figure 2. Diagram. Types of acquisitions. ...................................................................................... 4

Figure 3. Equation. HHI formula. ................................................................................................... 8

Figure 4. Map. AASHTO regions in the United States (Historical MapChart 2022). .................. 11

Figure 5. Map. Wisconsin region map (Wisconsin DOT n.d.b.). ................................................. 14

Figure 6. Graph. Concrete bid price trends—Massachusetts 2006–2016. .................................... 17

Figure 7. Graph. Asphalt bid price trends—Massachusetts 2006–2016. ...................................... 18

Figure 8. Graph. Aggregate bid price trends—Massachusetts 2006–2016. ................................. 19

Figure 9. Graph. Concrete bid price trends—New York 2006–2016. .......................................... 21

Figure 10. Graph. Asphalt bid price trends—New York 2006–2016. .......................................... 22

Figure 11. Graph. Aggregate bid price trends—New York 2006–2016. ...................................... 23

Figure 12. Graph. Concrete bid price trends—Pennsylvania 2006–2016. ................................... 24

Figure 13. Graph. Asphalt bid price trends—Pennsylvania 2006–2016. ..................................... 25

Figure 14. Graph. Aggregate bid price trends—Pennsylvania 2006–2016. ................................. 26

Figure 15. Graph. Concrete bid price trends—Vermont 2006–2016............................................ 28

Figure 16. Graph. Asphalt bid price trends—Vermont 2006–2016.............................................. 29

Figure 17. Graph. Aggregate bid price trends—Vermont 2006–2016. ........................................ 30

Figure 18. Graph. Concrete bid price trends—Arkansas 2006–2016. .......................................... 31

Figure 19. Graph. Asphalt bid price trends—Arkansas 2006–2016. ............................................ 32

Figure 20. Graph. Aggregate bid price trends—Arkansas 2006–2016. ........................................ 33

Figure 21. Graph. Concrete bid price trends—Florida 2006–2016. ............................................. 35

Figure 22. Graph. Asphalt bid price trends—Florida 2006–2016. ............................................... 36

Figure 23. Graph. Concrete bid price trends—Georgia 2006–2016. ............................................ 37

Figure 24. Graph. Asphalt bid price trends—Georgia 2006–2016. .............................................. 38

Figure 25. Graph. Aggregate bid price trends—Georgia 2006–2016. .......................................... 39

Figure 26. Graph. Concrete bid price trends—Louisiana 2006–2016. ......................................... 41

Figure 27. Graph. Aggregate bid price trends—Louisiana 2006–2016. ....................................... 42

Figure 28. Graph. Concrete bid price trends—North Carolina 2006–2016. ................................. 43

Figure 29. Graph. Asphalt bid price trends—North Carolina 2006–2016. ................................... 44

Figure 30. Graph. Aggregate bid price trends—North Carolina 2006–2016. .............................. 45

Figure 31. Graph. Concrete bid price trends—South Carolina 2006–2016. ................................. 46

Figure 32. Graph. Asphalt bid price trends—South Carolina 2006–2016. ................................... 47

Figure 33. Graph. Aggregate bid price trends—South Carolina 2006–2016. .............................. 48

Figure 34. Graph. Concrete bid price trends—Tennessee 2006–2016. ........................................ 50

Figure 35. Graph. Asphalt bid price trends—Tennessee 2006–2016. .......................................... 51

Figure 36. Graph. Aggregate bid price trends—Tennessee 2006–2016. ...................................... 52

Figure 37. Graph. Concrete bid price trends—Virginia 2006–2016. ........................................... 53

Figure 38. Graph. Asphalt bid price trends—Virginia 2006–2016. ............................................. 54

Figure 39. Graph. Aggregate bid price trends—Virginia 2006–2016. ......................................... 55

Figure 40. Graph. Concrete bid price trends—West Virginia 2006–2016. .................................. 57

Figure 41. Graph. Asphalt bid price trends—West Virginia 2006–2016. .................................... 58

Figure 42. Graph. Aggregate bid price trends—West Virginia 2006–2016. ................................ 59

Figure 43. Graph. Concrete bid price trends—Illinois 2006–2016. ............................................. 60

Figure 44. Graph. Asphalt bid price trends—Illinois 2006–2016. ............................................... 61
viii

Figure 45. Graph. Aggregate bid price trends—Illinois 2006–2016. ........................................... 62

Figure 46. Graph. Concrete bid price trends—Indiana 2006–2016. ............................................. 64

Figure 47. Graph. Asphalt bid price trends—Indiana 2006–2016. ............................................... 65

Figure 48. Graph. Aggregate bid price trends—Indiana 2006–2016............................................ 66

Figure 49. Graph. Concrete bid price trends—Michigan 2006–2016. ......................................... 67

Figure 50. Graph. Asphalt bid price trends—Michigan 2006–2016. ........................................... 68

Figure 51. Graph. Aggregate bid price trends—Michigan 2006–2016. ....................................... 69

Figure 52. Graph. Concrete bid price trends—Minnesota 2006–2016. ........................................ 71

Figure 53. Graph. Asphalt bid price trends—Minnesota 2006–2016. .......................................... 72

Figure 54. Graph. Aggregate bid price trends—Minnesota 2006–2016. ...................................... 73

Figure 55. Graph. Concrete bid price trends—Missouri 2006–2016. ........................................... 74

Figure 56. Graph. Asphalt bid price trends—Missouri 2006–2016. ............................................. 75

Figure 57. Graph. Aggregate bid price trends—Missouri 2006–2016. ........................................ 76

Figure 58. Graph. Concrete bid price trends—Ohio 2006–2016. ................................................. 78

Figure 59. Graph. Asphalt bid price trends—Ohio 2006–2016. ................................................... 79

Figure 60. Graph. Aggregate bid price trends—Ohio 2006–2016................................................ 80

Figure 61. Graph. Concrete bid price trends—Wisconsin 2006–2016. ........................................ 81

Figure 62. Graph. Asphalt bid price trends—Wisconsin 2006–2016. .......................................... 82

Figure 63. Graph. Aggregate bid price trends—Wisconsin 2006–2016. ...................................... 83

Figure 64. Graph. Concrete bid price trends—Arizona 2006–2016. ............................................ 85

Figure 65. Graph. Asphalt bid price trends—Arizona 2006–2016. .............................................. 86

Figure 66. Graph. Aggregate bid price trends—Arizona 2006–2016. .......................................... 87

Figure 67. Graph. Concrete bid price trends—California 2006–2016.......................................... 88

Figure 68. Graph. Asphalt bid price trends—California 2006–2016............................................ 89

Figure 69. Graph. Aggregate bid price trends—California 2006–2016. ...................................... 90

Figure 70. Graph. Concrete bid price trends—Colorado 2006–2016. .......................................... 92

Figure 71. Graph. Asphalt bid price trends—Colorado 2006–2016. ............................................ 93

Figure 72. Graph. Aggregate bid price trends—Colorado 2006–2016. ........................................ 94

Figure 73. Graph. Concrete bid price trends—Idaho 2006–2016. ................................................ 95

Figure 74. Graph. Asphalt bid price trends—Idaho 2006–2016. .................................................. 96

Figure 75. Graph. Aggregate bid price trends—Idaho 2006–2016. ............................................. 97

Figure 76. Graph. Concrete bid price trends—Montana 2006–2016............................................ 99

Figure 77. Graph. Asphalt bid price trends—Montana 2006–2016............................................ 100

Figure 78. Graph. Aggregate bid price trends—Montana 2006–2016. ...................................... 101

Figure 79. Graph. Concrete bid price trends—Nebraska 2006–2016. ........................................ 102

Figure 80. Graph. Asphalt bid price trends—Nebraska 2006–2016. .......................................... 103

Figure 81. Graph. Aggregate bid price trends—Nebraska 2006–2016. ..................................... 104

Figure 82. Graph. Asphalt bid price trends—Nevada 2006–2016. ............................................. 106

Figure 83. Graph. Aggregate bid price trends—Nevada 2006–2016. ........................................ 107

Figure 84. Graph. Concrete bid price trends—New Mexico 2006–2016. .................................. 108

Figure 85. Graph. Asphalt bid price trends—New Mexico 2006–2016. .................................... 109

Figure 86. Graph. Concrete bid price trends—Oklahoma 2006–2016. ...................................... 111

Figure 87. Graph. Asphalt bid price trends—Oklahoma 2006–2016. ........................................ 112

Figure 88. Graph. Aggregate bid price trends—Oklahoma 2006–2016. .................................... 113

Figure 89. Graph. Concrete bid price trends—Oregon 2006–2016. ........................................... 114

Figure 90. Graph. Asphalt bid price trends—Oregon 2006–2016. ............................................. 115
ix

Figure 91. Graph. Aggregate bid price trends—Oregon 2006–2016. ......................................... 116

Figure 92. Graph. Concrete bid price trends—Utah 2006–2016. ............................................... 118

Figure 93. Graph. Asphalt bid price trends—Utah 2006–2016. ................................................. 119

Figure 94. Graph. Aggregate bid price trends—Utah 2006–2016. ............................................. 120

Figure 95. Graph. Bid price versus unit price. ............................................................................ 121

Figure 96. Map. Case study States (Historical MapChart 2022). ............................................... 131

Figure 97. Equation. HHI of hypothetical industry. ................................................................... 134

Figure 98. Graph. Price trends—aggregate base class 2. ............................................................ 151

Figure 99. Graph. Price trends—asphaltic concrete 3⁄4-inch mix. ............................................... 152

Figure 100. Graph. Price trends—emulsified asphalt slow setting. ............................................ 157

Figure 101. Graph. Price trends—structural backfill class 1. ..................................................... 158

Figure 102. Graph. Price trends—concrete pavement 6-inch. .................................................... 159

Figure 103. Graph. Colorado employment statistics (Bureau of Labor and Statistics 2023). .... 160

Figure 104. Graph. Gross domestic product growth in Colorado (Bureau of Economic 

Analysis 2023). .................................................................................................................. 161

Figure 105. Graph. Price trends—aggregate surface course. ...................................................... 165

Figure 106. Graph. Unit price per ton versus bid price per ton of asphalt in 2016 

(MoDOT 2022). ................................................................................................................ 169

Figure 107. Graph. Price trends—base concrete. ....................................................................... 170

Figure 108. Graph. Price trends—6-inch non-reinforced concrete pavement. ........................... 174

Figure 109. Graph. Price trends—aggregate base. ..................................................................... 175

Figure 110. Graph. Price trends—asphalt concrete. ................................................................... 179

Figure 111. Graph. Bid price variation—1-inch aggregate base. ............................................... 183

Figure 112. Graph. Price trends—70-22 asphalt in HMAC (item No. 0745-0640000M). ......... 186

Figure 113. Graph. Price trends—64-22 asphalt in HMAC (item No. 0745-0620000M). ......... 186

Figure 114. Graph. Price trends—70-22 asphalt in HMAC without dollar/penny bids. ............ 187

Figure 115. Graph. Price trends—asphalt cement (TC) (item No. 403-02). .............................. 193

Figure 116. Graph. Price trends—item 455.0105 for 2006–2015. ............................................. 199
x 

LIST OF TABLES

Table 1. Analysis States. ............................................................................................................... 12

Table 2. State individual analysis example. .................................................................................. 13

Table 3. Regional analysis example.............................................................................................. 13

Table 4. Concrete price data—Massachusetts. ............................................................................. 18

Table 5. Asphalt price data—Massachusetts. ............................................................................... 19

Table 6. Aggregate price data—Massachusetts. ........................................................................... 20

Table 7. Concrete price data—New York..................................................................................... 21

Table 8. Asphalt price data—New York....................................................................................... 22

Table 9. Aggregate price data—New York. ................................................................................. 23

Table 10. Concrete price data—Pennsylvania. ............................................................................. 25

Table 11. Asphalt price data—Pennsylvania. ............................................................................... 26

Table 12. Aggregate price data—Pennsylvania. ........................................................................... 27

Table 13. Concrete price data—Vermont. .................................................................................... 28

Table 14. Asphalt price data—Vermont. ...................................................................................... 29

Table 15. Aggregate price data—Vermont. .................................................................................. 30

Table 16. Concrete price data—Arkansas. ................................................................................... 32

Table 17. Asphalt price data—Arkansas. ..................................................................................... 33

Table 18. Aggregate price data—Arkansas. ................................................................................. 34

Table 19. Concrete price data—Florida. ....................................................................................... 35

Table 20. Asphalt price data—Florida. ......................................................................................... 36

Table 21. Concrete price data—Georgia. ..................................................................................... 38

Table 22. Asphalt price data—Georgia. ....................................................................................... 39

Table 23. Aggregate price data—Georgia. ................................................................................... 40

Table 24. Concrete price data—Louisiana.................................................................................... 41

Table 25. Aggregate price data—Louisiana. ................................................................................ 42

Table 26. Concrete price data—North Carolina. .......................................................................... 43

Table 27. Asphalt price data—North Carolina. ............................................................................ 44

Table 28. Aggregate price data—North Carolina. ........................................................................ 45

Table 29. Concrete price data—South Carolina. .......................................................................... 47

Table 30. Asphalt price data—South Carolina. ............................................................................ 48

Table 31. Aggregate price data—South Carolina. ........................................................................ 49

Table 32. Concrete price data—Tennessee. .................................................................................. 50

Table 33. Asphalt price data—Tennessee. .................................................................................... 51

Table 34. Aggregate price data—Tennessee. ............................................................................... 52

Table 35. Concrete price data—Virginia. ..................................................................................... 54

Table 36. Asphalt price data—Virginia. ....................................................................................... 55

Table 37. Aggregate price data—Virginia. ................................................................................... 56

Table 38. Concrete price data—West Virginia. ............................................................................ 57

Table 39. Asphalt price data—West Virginia. .............................................................................. 58

Table 40. Aggregate price data—West Virginia........................................................................... 59

Table 41. Concrete price data—Illinois. ....................................................................................... 61

Table 42. Asphalt price data—Illinois. ......................................................................................... 62

Table 43. Aggregate price data—Illinois. ..................................................................................... 63

Table 44. Concrete price data—Indiana. ...................................................................................... 64
xi 

Table 45. Asphalt price data—Indiana. ........................................................................................ 65

Table 46. Aggregate price data—Indiana. .................................................................................... 66

Table 47. Concrete price data—Michigan. ................................................................................... 68

Table 48. Asphalt price data—Michigan. ..................................................................................... 69

Table 49. Aggregate price data—Michigan. ................................................................................. 70

Table 50. Concrete price data—Minnesota. ................................................................................. 71

Table 51. Asphalt price data—Minnesota. ................................................................................... 72

Table 52. Aggregate price data—Minnesota. ............................................................................... 73

Table 53. Concrete price data—Missouri. .................................................................................... 75

Table 54. Asphalt price data—Missouri. ...................................................................................... 76

Table 55. Aggregate price data—Missouri. .................................................................................. 77

Table 56. Concrete price data—Ohio. .......................................................................................... 78

Table 57. Asphalt price data—Ohio. ............................................................................................ 79

Table 58. Aggregate price data—Ohio. ........................................................................................ 80

Table 59. Concrete price data—Wisconsin. ................................................................................. 82

Table 60. Asphalt price data—Wisconsin. ................................................................................... 83

Table 61. Aggregate price data—Wisconsin. ............................................................................... 84

Table 62. Concrete price data—Arizona. ..................................................................................... 85

Table 63. Asphalt price data—Arizona. ....................................................................................... 86

Table 64. Aggregate price data—Arizona. ................................................................................... 87

Table 65. Concrete price data—California. .................................................................................. 89

Table 66. Asphalt price data—California. .................................................................................... 90

Table 67. Aggregate price data—California. ................................................................................ 91

Table 68. Concrete price data—Colorado. ................................................................................... 92

Table 69. Asphalt price data—Colorado. ..................................................................................... 93

Table 70. Aggregate price data—Colorado. ................................................................................. 94

Table 71. Concrete price data—Idaho. ......................................................................................... 96

Table 72. Asphalt price data—Idaho. ........................................................................................... 97

Table 73. Aggregate price data—Idaho. ....................................................................................... 98

Table 74. Concrete price data—Montana. .................................................................................... 99

Table 75. Asphalt price data—Montana. .................................................................................... 100

Table 76. Aggregate price data—Montana. ................................................................................ 101

Table 77. Concrete price data—Nebraska. ................................................................................. 103

Table 78. Asphalt price data—Nebraska. ................................................................................... 104

Table 79. Aggregate price data—Nebraska. ............................................................................... 105

Table 80. Asphalt price data—Nevada. ...................................................................................... 106

Table 81. Aggregate price data—Nevada. .................................................................................. 107

Table 82. Concrete price data—New Mexico............................................................................. 109

Table 83. Asphalt price data—New Mexico............................................................................... 110

Table 84. Concrete price data—Oklahoma. ................................................................................ 111

Table 85. Asphalt price data—Oklahoma. .................................................................................. 112

Table 86. Aggregate price data—Oklahoma. ............................................................................. 113

Table 87. Concrete price data—Oregon. .................................................................................... 115

Table 88. Asphalt price data—Oregon. ...................................................................................... 116

Table 89. Aggregate price data—Oregon. .................................................................................. 117

Table 90. Concrete price data—Utah.......................................................................................... 118
xii 

Table 91. Asphalt price data—Utah............................................................................................ 119

Table 92. Aggregate price data—Utah. ...................................................................................... 120

Table 93. Bid price versus unit price—Wisconsin. .................................................................... 122

Table 94. Number of plants by type—major cement firm. ......................................................... 125

Table 95. Unit price versus contract price for firm L—Wisconsin. ........................................... 129

Table 96. Unit price versus contract price for firm K—Wisconsin. ........................................... 129

Table 97. Reinforced concrete pavement (item 0755-0109000J) bid prices. ............................. 184

Table 98. Emulsified asphalt concrete mixture bid prices. ......................................................... 185

Table 99. Bid price statistics for item 305.011, 2006-2016. ....................................................... 198

Table 100. Bid price statistics for item 455.0105, 2006-2016. ................................................... 199
xiii

LIST OF ABBREVIATIONS

AASHTO American Association of State Highway Transportation Officials 

ACMs alternative contracting methods 

ADOT Arizona Department of Transportation 

ArDOT Arkansas Department of Transportation 

CCI construction cost index 

CDOT Colorado Department of Transportation 

CPCC California Portland Cement Company (CalPortland) 

CWT hundredweight 

CY cubic yard

DBE disadvantaged business enterprise 

DOJ Department of Justice

DOT department of transportation 

DOTD Department of Transportation and Development 

FDOT Florida Department of Transportation 

FHWA Federal Highway Administration

FTC Federal Trade Commission 

GDOT Georgia Department of Transportation 

GDP gross domestic product 

HCCI Highway Construction Contract Information 

HHI Herfindahl-Hirschman Index

HMA hot-mix asphalt 

HMAC hot-mix asphalt concrete 

IDOT Illinois Department of Transportation

ITD Idaho Transportation Department 

LF linear feet

M&As mergers and acquisitions 

MassDOT Massachusetts Department of Transportation 

MDOT Michigan Department of Transportation 

MnDOT Minnesota Department of Transportation 

MoDOT Missouri Department of Transportation 

NDOT Nebraska Department of Transportation

NOVA Northern Virginia 

NYSDOT New York Department of Transportation 

ODOT Oregon Department of Transportation 

PennDOT Pennsylvania Department of Transportation

PG performance grade

RAMP Responsible Acceleration of Maintenance and Partnerships 

SCDOT South Carolina Department of Transportation 

SY square yard 

TDOT Tennessee Department of Transportation 

USGS United States Geological Survey

VTrans Virginia Department of Transportation 

WisDOT Wisconsin Department of Transportation 

1 

EXECUTIVE SUMMARY

BACKGROUND 

State departments of transportation (DOTs) have regularly expressed concern about the effects of 

mergers and acquisitions (M&As) within the industries that produce, supply, and install 

aggregates and other materials for transportation projects. State DOTs have reported market 

share changes in the companies that bid their projects, pricing increases, or other anomalies in 

the projects they let to contract. State DOTs also might notice a decrease in bidders for certain 

project types or other supply chain differences that might occur because of recent M&As of the 

companies involved with supplying and bidding their contracts. 

PURPOSE OF THE REPORT

This research report presents the findings of the investigation into the effects of M&As involving 

companies that supply construction materials for State DOT transportation projects. In an effort 

to identify significant consolidation, this study analyzed material pricing data from 31 States by 

sorting bid data for every year beginning with 2006 through the third quarter of 2016. These 

findings were then compared against known company mergers or acquisitions and analyzed for 

construction materials price sensitivity.

GOAL OF THE RESEARCH

The research goal was to find relationships or trends that occur with M&As. The study also 

aimed to present information on what States have done to monitor and assess activity that can be 

adverse to competitive market share distribution, bid pricing, and project costs, as well as how 

they have done so. 

DETAILS OF APPROACH 

Bid and project data from 31 States were sorted to include materials of interest, including 

concrete, asphalt, aggregate, and granular backfill materials. Projects were matched to prime 

contractors and total project costs to investigate price anomalies and consolidation activity. By 

analyzing each individual State, disproportionately high project costs were identified and 

compared against historical prices and engineering estimates. Based on the data obtained from 

these findings, supplemented by literature and legal case reviews, nine States were chosen for 

further indepth case study. The data analysis and case studies are presented for information 

exchange. Challenges experienced during this project included appropriate bid item number 

selection, desired data availability, and inconsistent bid item number use. Subject-matter experts 

were needed to assist in the bid item number selection and comparisons across States. Due to 

variations in file formats, initial data sorting was done manually, which was very timeconsuming. 

IMPORTANT RESULTS

Two primary steps were taken to monitor negative impacts of M&A activity identified through 

this study. First, States had to systematically identify the M&A activity taking place, and second, 
2 

they had to assess the impact (if any) of this activity on pricing, competition, and market share. 

To identify M&A activity, States should proactively monitor for consolidation activity, use a 

standardized estimation process to generate bid estimates for projects, track firm names over 

time to aid in identifying consolidation, utilize regional monitoring, have a set process for 

analyzing unbalanced bids, and track cost indexes over time. Because not all merger activity has 

a negative impact, once M&A activity is identified, the impacts must be documented and 

tracked, which can be done through bid analysis. Measures should be taken to increase 

competition, if necessary. Such measures could include controlling material supplies at the State

level, bidding smaller lettings more often, or utilizing project bundling.
3 

CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW

Mergers and acquisitions (M&As) receive regular attention across divergent industries in the 

U.S. economy. In most scenarios, synergy and efficiency drive many consolidations. Normal 

corporate growth, as well as attempts to increase market share and widen market access, 

comprise other primary drivers. 

A synergistic combination of business activities can increase performance and decrease costs of 

doing business. For the most part, a business will attempt to merge with another business that has 

complementary strengths and weaknesses. Other reasons for consolidation could include 

diversifying their portfolio, added geographic coverage, and targeting a focused market. In the 

latter, companies seeking to sharpen focus often merge with companies that have deeper market 

penetration in key complementary areas of operation. Many consolidations improve business 

operations and quality without adversely affecting competition. 

M&A activity, particularly in the transportation materials and construction industry, is 

infrequently analyzed, yet it can significantly affect competition, market control, and pricing. 

The Federal Highway Administration (FHWA) has a role in ensuring cost competitiveness in the 

transportation industry. While in many cases collaboration between firms with similar goals and 

corporate growth in a healthy market motivates consolidations, attempts to increase market share 

and efforts to target wider market access may provide reasons for concern or additional 

monitoring. Companies may engage in consolidation activity with those other entities that 

contain complementary strengths and assets, or to increase the diversity of what they can offer to 

the market.

At times, however, M&A activity results in the elimination of cost brackets, harms competition, 

creates inequitable market control, or results in price increases. Any of these occurrences within 

the transportation materials and construction industry can alter bidding processes, consumer 

behaviors, and market attributes. 

This study’s final report examines a series of State department of transportation (DOT) 

construction materials bid prices and provides processes for monitoring and analyzing State DOT 

practices for bidding and letting projects. In addition, a set of nine case studies was developed to 

better understand the state of the practice for assessing bid prices and monitoring industry 

activities. The final report and accompanying technical brief offer insights into the challenges 

associated with determining price impacts of M&A activity in the construction materials industry

(Corrigan, Bittner, and Silber 2022). 

Due to the potentially harmful byproducts of M&A activity, transportation professionals need to 

be aware of consolidation activities and their immediate and long-term influences. Figure 1 and

figure 2 outline the M&A activity types that occur, as well as potential motives and results, 

respectively. 
4 

Source: FHWA. 

Figure 1. Chart. Types of mergers.

Source: FHWA. 

Figure 2. Diagram. Types of acquisitions.

A 2006 American Association of State Highway and Transportation Officials (AASHTO) survey 

found that 11 of 38 participating States identified M&A activity as a prime driver behind bid 

price increases and competition decreases (FHWA 2006). Similarly, in a 2015 AASHTO survey 

Types of 

Mergers 

Horizontal 

Between companies 

operating and 

competing in the 

same industry

Motive: reducing 

competitors 

Vertical 

Between companies 

operating in the same 

industry but different 

stages of 

production/distribution 

Motive: control over all 

phases of 

production/marketing 

Congeneric 

Between companies 

operating in same 

industry but not the 

same products 

Motive: increase 

market share and 

diversify products 

Conglomerate 

Between companies 

engaged in different 

activities and not 

related vertically or 

horizontally 

Motive: diversification 

and management 

synergy 
5 

completed by the Subcommittee on Construction of 32 member States, 17 expressed concerns 

about negative impacts of merger activity on bid prices.1 Since due diligence regarding fair 

bidding processes is necessary, further investigation into M&A activity—particularly for

roadway construction material sources—on project costs is needed to examine these effects 

across different States.

Industry experts identify several issues associated with consolidations beyond pricing. For 

instance, extensive purchasing of pits, quarries, and mineral rights in large, “controlled” 

geographic areas by large contractors is forcing smaller contractors without access to these 

materials to drop their bidding efforts. Contractors that do not have access to materials in these 

large, controlled geographic areas cannot be competitive on projects within those areas, mainly 

due to the costs of moving truck materials into work sites within that controlled area. Larger 

contractors have political influence on local zoning boards, which tend to block new contractors 

from setting temporary asphalt plants on land within the local area. Purchasing smaller 

companies in larger, controlled geographic areas creates subsidiaries or standalone divisions. In 

many States, smaller companies commonly become divisions of the larger company, and only 

one division within that larger company will bid on a given project, leading many times to a 

single bid. 

Anecdotally, larger contractors underbid within areas where they know a smaller competitor may 

have an advantage to keep the smaller contractor out of the market. Multiple contractors

sometimes form short-term partnerships to bid a project as a single entity. This practice has been 

evident when comparing bids in regional areas across Wisconsin and other States in the 

Midwest.

2 Another related issue is the increased use of exclusive subagreements. By using 

subagreements, larger contractors with market power attempt to control subcontractors who are 

exclusive, only quoting to their firm. 

The research team completed a literature review that provided a preliminary analysis of existing 

studies on this topic. The research team reviewed dozens of additional news media stories, 

website information, and trade magazine articles. In several cases, as data were collected, the 

research team communicated directly with transportation officials in subject States. This 

collected information helped shape the literature review, guided the data collection efforts, and 

refined the most relevant topics for project analysis and organization. The study’s literature 

review was arranged in three primary categories: material costs, case studies, and preferred 

analysis methods. The resulting full document is attached as appendix A. 

In addition, the research team reviewed dozens of legal cases and information from ongoing 

litigation. The researchers based their review on identifying cases and court filings that expand 

on Copperweld Corp. v. Independence Tube Corp. (“Copperweld”) (Burger and Supreme Court 

of the United States 1983). Copperweld held that coordinated activity of a parent and its wholly 

owned subsidiary must be viewed as that of a single enterprise for purposes of the Sherman 

Antitrust Act. These scenarios—whereby acquisitions occur to encourage limiting the number or 

geographic reach of prospective bidders—held the most promise for identifying any relationships 

1

AASHTO Survey on Merger and Acquisition Activity; reported during Subcommittee on Construction, conference 

call in August 2015, and personal correspondence between authors and Marc Mastronardi in December 2017. 2

Conversation with Donald Miller, P.E., former Wisconsin DOT Chief Construction Engineer, on February 23, 

2015. 
6 

between M&A and actual costs. According to the court’s precedent, a parent company and its 

wholly owned subsidiary(ies) have complete unity of interest and are, therefore, protected. 

Copperweld’s influence on industry consolidations proved substantial. However, as shown in 

this report, direct impact on pricing for construction materials cannot be easily identified. 

Several important elements have set court precedent. Individual names are available here only to 

illustrate the facts in these cases.

• U.S.A. v. Vulcan Materials Company and Florida Rock Industries, Inc., case 

07-cv-02044, D.C. District Court, 2007 (coarse aggregate) (“Vulcan Materials”) (U.S.A.

v. Vulcan Materials Company and Florida Rock Industries 2008):

In Vulcan Materials Co., the court was asked to review the merger of two large aggregate 

producers, Florida Rock Industries, Inc. and Vulcan Materials Co. Perhaps the most 

interesting aspect of this case is how the court defined the applicable geographic markets. 

It identified individual quarries that Florida Rock Industries, Inc. owned and then 

determined what geographic areas the individual quarries served, given the transportation 

limitations for aggregate. Thus, the geographic markets were several, were narrow 

(northwest Atlanta, south Atlanta, southwest Atlanta), and were based on the locations of 

the quarries, customers, and logistical constraints. 

In many of these narrow geographic markets, Florida Rock Industries, Inc. and Vulcan 

Materials Co. were two of only three or four premerger competitors. Postmerger, the 

combined entity would have controlled more than 50 percent of the market share in most 

of the geographic markets. Accordingly, the court ordered divestiture of several mines 

and quarries. 

• U.S.A. v. Martin Marietta Materials, Inc., case 14-cv-01079, D.C. District Court, 2014 

(Department of Justice [DOJ]) (complaint filed June 14, 2014) (“Martin Marietta I”) 

(U.S.A. v. Martin Marietta Materials, Inc., and Texas Industries, Inc. 2014): 

This case involved Martin Marietta Materials, Inc., which distributes aggregate to 

construction companies in 29 States. Martin Marietta Materials, Inc. was set to merge 

with Texas Industries, Inc., a major regional aggregate supplier. The DOJ was concerned 

with anticompetitive effects in Dallas, TX. This case is interesting because of how it 

defines the relevant product market. Generally, the DOJ, Federal Trade Commission 

(FTC), and U.S. courts identify the relevant product market as simply “aggregate.” 

However, Texas DOT tests aggregate, and, if the aggregate passes, it becomes “qualified” 

for State DOT projects. The DOJ and the court considered “DOT qualified aggregate” a 

separate product market than “aggregate” and found that, for State DOT projects (and 

other projects that required DOT-qualified aggregate), aggregate was not a substitute. 

Given that this study’s focus is State DOT projects, the monitoring State agencies may 

consider using this narrower product market definition. The court required substantial 

divestitures from the merged entity, including several quarries and multiple rail yards. 
7 

• U.S. v. Cemex S.A.B. de C.V. and Rinker Group Limited, case 07-cv-00640, D.C.

District Court, 2007 (DOJ) (“Cemex DOJ”) (U.S. v. Cemex 2009):

This DOJ challenge to the merger of Cemex S.A.B. de C.V. and Rinker Group Ltd. 

involved three different product markets spread across various geographic regions, 

including both Florida and Arizona. Analytically, this case outlines how courts deal with 

mergers involving national (or international) suppliers—they identify all relevant product 

and geographic markets and resolve all issues collectively. This case is also noteworthy 

for its detailed discussion of the ready-mix concrete industry and its discussion of the 

product market for concrete block. Although concrete block is outside this study’s scope, 

it has many of the same market characteristics as other road-building materials, such as 

high transportation costs, homogeneity, and high barriers to entry. If the FTC/DOJ is 

dealing with a large company that supplies both ready-mix concrete and aggregate, the 

concrete block product market may also be implicated in a merger. Ultimately, the court 

required the merged entity to divest several ready-mix concrete plants, several concrete 

block plants, and several aggregate plants. 

• U.S. v. Oldcastle Northeast, Inc. et al., case 396-cv-01749 District Court of Connecticut,

1996 (DOJ) (complaint filed September 3, 1996) (U.S. v. Oldcastle Northeast et al.

1996): 

Oldcastle Northeast, Inc. involved the merger of two of the largest asphalt producers in 

the greater Hartford, CT, area. Highlighting the importance of transportation costs and 

vertical integration in the asphalt industry, the complaint also emphasized that the two 

merging entities “are the only producers of asphalt in the greater Hartford area that own 

their own sources of aggregate for manufacturing asphalt for highway projects.” This 

latter fact was important in the court’s unilateral effects analysis. Previously, other 

asphalt producers could purchase their aggregate from either of the merging entities. 

Because the merged entity would have controlled all aggregate quarries, it allowed the 

merged entity to unilaterally decrease output in both the aggregate and asphalt product 

markets. Accordingly, the court ordered divestiture of a major aggregate quarry to supply 

competing asphalt manufacturers. The court also ordered divestiture of several asphalt 

plants. 

• Cemex, S.A. de C.V., FTC docket No. C-4131 (2005) (FTC 2005): 

This case challenged the proposed merger of Cemex, S.A. de C.V. and RMC Group, 

PLC, due to anticompetitive effects in the ready-mix concrete product market around 

Tucson, AZ. This case is interesting because Cemex, S.A. de C.V., preemptively agreed 

to divest substantial assets to a competitor, California Portland Cement Company

(CalPortland®) (CPCC). In reviewing the proposed merger and divestiture, the FTC had 

to determine whether CPCC would be able to compete in Tucson, AZ, thereby offsetting 

the competitive effects of the merger. Focusing on CPCC’s widespread presence in the 

western United States, vertical integration, and experience in the ready-mix concrete 

business, the FTC approved the merger and divestiture. This case illustrates the 

limitations with market entry in the road-building industry to offset anticompetitive 

effects. Here, Cemex, S.A. de C.V., was required to find a vertically integrated, 
8 

regionally powerful competitor for the FTC to accept the merger. Many geographic 

locations do not have more than one viable competitor ready to enter the market.

REVIEW OF HOW THE FTC/U. S. DOJ HORIZONTAL MERGER GUIDELINES

HAVE BEEN APPLIED TO MERGERS IN THE HIGHWAY MATERIALS AND 

CONSTRUCTION FIELDS

The Horizontal Merger Guidelines are a set of internal rules promulgated by the Antitrust 

Division of the DOJ in conjunction with the FTC (U. S. Department of Justice and Federal Trade 

Commission 2010). The rules provide guidance regarding the extent to which the DOJ and FTC 

will scrutinize or challenge a merger based on potential anticompetitive effects.

Section 7 of the Clayton Act, section 1 of the Sherman Act, and section 5 of the Federal Trade 

Commission Act establish the Federal antitrust laws applicable to mergers (Clayton Antitrust Act 

1914; Sherman Antitrust Act 1890; Federal Trade Commission Act 1914). Section 7 of the 

Clayton Act prohibits any merger for which the effects “may be substantially to lessen 

competition.” The primary concern of section 7 is the creation (or enhancement) of market 

power. The unifying theme of the Horizontal Merger Guidelines “is that mergers should not be 

permitted to create, enhance, or entrench market power or to facilitate its exercise” (U. S.

Department of Justice and Federal Trade Commission 2010).

The guidelines are organized into 13 different sections. Of the 13 guidelines, the following have 

been consistently applied to M&As in the road-building industry: evidence of adverse 

competitive effects; targeted customers and price discrimination; market definition; market 

participants, market shares, and market concentration; unilateral effects; coordinated effects; and 

market entry analysis (U. S. Department of Justice and Federal Trade Commission 2010). 

CRITICAL FINDINGS OF THE LITERATURE REVIEW AND LEGAL GUIDANCE

A number of critical findings resulting from the literature and legal reviews were completed 

under this study. One principal finding is that States can monitor M&A activity for its impact on 

market share. A primary tool to calculate strength of market share (and to determine if the 

market is noncompetitive) is the Herfindahl-Hirschman Index (HHI) (figure 3) (U.S. Department 

of Justice 2018). The formula for HHI is: 

Figure 3. Equation. HHI formula. 

Where si = the market share percentage of firm i, expressed as a whole number, not a decimal.

The index is used by the DOJ to determine competition. The closer a market is to a monopoly, 

the higher the market’s concentration (and the lower its competition). If, for example, the 

industry contained only one firm, then that firm would have 100-percent market share, and the 

HHI would equal 10,000, indicating a monopoly. If thousands of firms were competing, each 

would have a market share of almost 0 percent, and the HHI would be close to 0, indicating 

nearly perfect competition. As a general rule, mergers that increase the HHI by more than 

200 points in highly concentrated markets raise antitrust concerns, as they are assumed to 
9 

enhance market power under section 5.3 of the Horizontal Merger Guidelines (U. S. Department 

of Justice and Federal Trade Commission 2010). 

A substantial problem, however, with HHI is that defining a market and considering market 

share can arise from geographic factors. This problem can occur when companies within an 

industry have roughly equal market shares, but they each operate only in specific areas of the 

country, so that each firm, in effect, has a monopoly within the specific marketplace in which it 

does business. In many of the States assessed, companies dominated particular regions, although, 

overall, the market contained a fair number of participants. Hence, no quantifiable impacts on 

construction material pricing occurred. 

Retrospective analyses of merger effects are rarely conducted. One leading voice on this issue is 

Dennis Carlton, a prominent economics professor at the University of Chicago Booth School of 

Business. Professor Carlton has articulated several concerns with the current state of the data and 

analysis relating to merger effects (Carlton 2009). Nonetheless, during the course of this study, 

our research team identified several resources that addressed the retrospective analysis of 

mergers in general, in the asphalt industry, and in other industries with local geographic markets. 

More details are provided in appendix A, which is a literature review. Many academics have 

raised concerns about the methodology, modeling, and data quality that have been “widely noted 

as impediments to evaluating mergers and merger control” (Kwoka 2013). Despite these 

methodological concerns from existing studies, Kwoka reviewed hundreds of mergers and 

studies from 2003 to 2013 to assess the impact that mergers had on prices, as well as the 

effectiveness of the various potential remedies. Kwoka noted that “price increases characterized

merger outcomes in all cases, regardless of the policy action taken” (Kwoka 2013). Essentially, 

his argument is that all studies showed some increase in pricing. However, the amount of the 

increase varies considerably by the type of policy action taken. Critical to Kwoka’s analysis, 

however, is the fact that none of the observed information exclusively demonstrated price 

increases directly attributed to the merger activity. 

Furthermore, Kwoka noted, “Transactions opposed outright by the antitrust agencies are found to 

average a 1.86-percent increase,” while “[t]hose subject to divestiture result in a price increase of 

6.66 percent” (Kwoka 2013). Mergers that promoted “conduct or conditions remedies have 

substantially larger price increases—12.82 percent for all transactions, 16.01 for true mergers.” 

Kwoka states, “Notably, transactions that were cleared outright are found to result in price 

increases averaging 7.40 percent, little different from the most effective remedy, divestiture.” 

Professor Kwoka’s findings also suggest “entry conditions would appear to be of critical 

importance in cases cleared by the agencies.” He concludes that “merger control policy in the 

United States has been considerably more permissive of concentration and the study of mergers” 

than suggested by the Horizontal Merger Guidelines. One additional item of note was that “a 

very large fraction of carefully studied mergers shows that those mergers resulted in higher 

prices, even when a remedy was imposed” and that the “studied remedies imposed on 

problematic mergers do not appear generally effective in preventing postmerger price increases 

with nonstructural remedies substantially less effective than divestitures.” This finding was not 

readily shown in the bid data used for this study. 

In her economics dissertation, one chapter of which studies mergers in the asphalt industry, 

Duplantis (2010) modeled three common forms of predictive anticompetitive effects with 
10 

observed data from three asphalt supplier mergers in Michigan to determine the accuracy of each 

modeling type. The three modeling types analyzed were a coordinated effects model using the 

postmerger change in HHI, calculated from revenue from winning bids; a unilateral effects 

model using price effects predicted from a first/second analysis; and a unilateral effects model 

using the price effects from a spatial model of competition. The finding of Dr. Duplantis’ 

research is that none of the models really work—“there are no clear winners.” The observed 

postmerger pricing effects that Dr. Duplantis uses as her comparative baseline found that one 

merger, which was not preemptively challenged but was found post hoc to be anticompetitive by 

the DOJ, resulted in an 18-percent price increase for asphalt in the 2 yr after the merger. 

Strikingly, the 18-percent price increase for asphalt in the 2 yr after the merger regressed to 

statistically insignificant levels over the next 4 yr. The other two mergers did not result in 

statistically significant price increases. This outcome has emerged as a common theme 

throughout the published and observed research and mirrors this study’s findings. 

These findings in the existing literature provided the basis for the research team’s continued 

emphasis on M&A activity. Most literature held that, where market entry is possible, 

anticompetitive effects resulting from mergers dissipate quickly. To assess this observation, the 

research team explored data analysis and case studies described in greater detail in the following 

chapters.

FHWA is ultimately responsible for ensuring the bidding process associated with Federal-aid 

funding employs fair competition. FHWA’s regulations require States to “assure opportunity for 

free, open, and competitive bidding” (Code of Federal Regulations 2020). This requirement 

dictated the need for a study of material source M&As on project delivery quality and costs. 

The following chapters provide an overview of the work completed in this study and describe the 

findings of data processing, case studies, preliminary analysis, challenges and observations, and 

overall findings.
11 

CHAPTER 2. DATA PROCESSING AND ANALYSIS 

Consolidation activity within construction firms can have widespread and long-lasting effects on 

the industry, as well as on pricing. A single firm that acquires many smaller firms in a 

geographic area may gain an advantage in that area, which can affect material producers. For 

example, a geographic region with six plants producing hot-mix asphalt (HMA) and sealant 

materials may suffer as a result of M&A activity: if one firm begins controlling that area and 

only sources to one or two of the six plants, the others will lose valuable business. Location is a 

large contributing factor in supplier selection for firms, as some materials cannot be transported 

beyond a certain radius because they would be too costly to transport beyond some fixed 

distance.

To assess the effects of M&A activity, the team examined data across the United States to

identify significant consolidation. To begin this study, the team identified 31 States as the initial 

analysis target, with 22 marked as optional analysis States. Ultimately, only the initial 31 were 

reviewed in great detail, as the data available for the study did not demonstrate clear changes in 

pricing and item bid information. 

The 31 primary States chosen for analysis are listed with their associated AASHTO region, as 

depicted in figure 4 and table 1. Analysis of these States required sorting the bid data for every 

year beginning with 2006 through the third quarter of 2016. Only projects including typical 

highway project materials were included for each State for each year.

Original map © 2021 MapChart. Modified by FHWA (see Acknowledgments section). 

Figure 4. Map. AASHTO regions in the United States (Historical MapChart 2022). 
12 

Table 1. Analysis States. 

AASHTO 

Region States Selected 

1 Massachusetts, New York, Pennsylvania, and Vermont

2 Arkansas, Florida, Georgia, Louisiana, North Carolina, South Carolina, 

Tennessee, Virginia, and West Virginia 

3 Illinois, Indiana, Michigan, Minnesota, Missouri, Ohio, and Wisconsin

4 Arizona, California, Colorado, Idaho, Montana, Nebraska, Nevada, New 

Mexico, Oklahoma, Oregon, and Utah 

Bid price data were mined by Oman Systems, Inc., from State DOT bid prices posted on State 

websites provided by FHWA.1 Winning projects were sorted to include only those with materials 

of interest, which were materials commonly appearing in road-building projects, including 

asphalt, structural concrete, aggregate, and granular backfill materials. For each State, the exact 

items varied, e.g., one State may have up to 3,000 items with concrete in the item name or 

description. The projects containing these bid item numbers were then sorted by date for each 

analysis year (first quarter of 2006 through the third quarter of 2016). Sorting by date allowed 

the projects to be matched with the corresponding contractor information in Bid Express®, as 

Bid Express lists bid information in calendar order for each year (Bid Express 2021). The goal 

was to match each project containing the sorted items by their project number and bid date to 

find the contractor name and the total project costs for each project, coupled with individual bid 

item numbers. Historical bid data from some individual State archives were used, as well as 

online resources such as Bid Express to locate the contractors and project costs. This process was 

completed for 2006–2016 for each State. Besides project cost and contractor name, the final 

curated data entry for each project included pay items, descriptions, quantity, units and settled 

price for each selected item, bid date, project type, county, and region, if applicable.

Curated data examples are provided in this report. The entire dataset was provided to FHWA. 

The data are arranged by State and sorted by project identification number. 

After this initial analysis was completed, a secondary State-by-State investigation was 

conducted. For each State included, each individual project was listed by year in separate 

analysis sheets that included the project cost, contractor name, county, and individual State

DOT-defined regions. Once each project was identified, the average project cost was calculated 

for every year as a starting point for comparison. Furthermore, each individual project cost was 

compared against the average cost to determine the percent cost above the average cost for each 

project for every year. This cost was identified to determine whether individual projects were out 

of expected cost ranges.

Table 2 shows an example (using data from Wisconsin) of this State-by-State investigation. The 

data identify the projects for each year with winning bid project costs that were greater than the 

average for that particular year. Any projects with winning bid project costs that were more than

100 percent greater than the average cost for that year were selected to analyze the percentage of 

all projects per year that had costs greater than the average.

1

FHWA does not collect this bid price information.
13 

Table 2. State individual analysis example. 

Contractor 

Project Cost

(Dollars)

Average

(Dollars)

Average

(Percent) County Region

A 15,190,116.42 3,079,825.71 493 Monroe 5

B 1,479,226.23 3,079,825.71 48 Dodge 5

C 393,338.20 3,079,825.71 13 Monroe 5

D 2,264,001.25 3,079,825.71 74 Outagamie 2

D 4,508,636.78 3,079,825.71 146 Marinette 2

E 309,063.23 3,079,825.71 10 Pierce 3

F 2,410,220.10 3,079,825.71 78 St. Croix 3

G 186,527.49 3,079,825.71 6 Trempealeau 3

H 6,336,493.88 3,079,825.71 206 Milwaukee 4

I 81,496,581.63 3,079,825.71 2,646 Milwaukee 4

J 992,526.34 3,079,825.71 32 Jefferson 5

C 399,186.85 3,079,825.71 13 Monroe 5

K 264,144.30 3,079,825.71 9 Vernon 5

L 167,587.53 3,079,825.71 5 Crawford 5

M 649,158.42 3,079,825.71 21 Dane 5

Additionally, the projects were also analyzed by region. Table 3 shows an example for the 

Wisconsin data. In this example, the first step is to identify how the State agency (often the 

DOT) defines the regions or districts of the State. For Wisconsin, the State is divided into five 

unique regions labeled by geographic location: north central, northeast, northwest, southeast, and 

southwest (figure 5). For States that divide regions by name, such as Wisconsin, each region is 

assigned a numerical identifier to allow for sorting in Excel®. The projects in this example were 

assigned a region number based on the county, which is identified in the original data provided 

through Oman Systems, Inc., and supplemented by research team review of information posted 

on State DOT websites. Lists showing which counties are included in each region are available 

from State DOT websites. Finally, the number and percentage of projects occurring in each 

region per year were analyzed to identify any regional market share changes across the analysis 

period. 

Table 3. Regional analysis example. 

Region Key Identification No. Projects (No.) Projects (Percent)

North central 1 51 11.89

Northeast 2 76 17.72

Northwest 3 76 17.72

Southeast 4 126 29.37

Southwest 5 100 23.31
14 

© n.d. Wisconsin DOT. Modified by FHWA 

(see Acknowledgments section). 

Figure 5. Map. Wisconsin region map (Wisconsin DOT n.d.b.).

By analyzing each individual State for proportions of projects winning bids that were greater 

than the average project cost for the year, years with disproportionally high projects costs can be 

identified compared with a performance metric (in this case, project costs). Regional analysis can 

also aid in identifying if market shares are skewed in individual States. If so, the analysis can 

identify what companies are operating in those regions, as well as what companies and material 

producers and providers have control in those areas. Three States were chosen to highlight the 

analysis work that took place: Wisconsin, Colorado, and Florida. State-specific procedures, data, 

and results are described in chapter 3. 

Unit price data can also be of interest. Many State DOTs keep records of historical unit price 

data for all bid item numbers included in lettings, sorted by date range. These data were

requested for States of interest, including Wisconsin and Florida. As listed previously in this 

chapter, items of interest identified in the project included granular backfill, aggregate, concrete 

pavement, and asphalt pavement. These items were selected from the historical unit price 

datasets for comparison against actual unit prices of those items in bids for corresponding years, 

as obtained from the dataset, coupled with information from specific State websites. 
15 

CHAPTER 3. STATE ASSESSMENTS

This chapter provides introductory information for each State, along with additional analysis if 

available. The team also collected information on consolidations and merger activity in each 

State to compare against the State-provided bid information. Comprehensive surveys and 

telephone interviews with State DOTs were not conducted for this study. When possible, after 

completing internet-based research, research team members discussed their general observations 

concerning the available data.

The research team divided the targeted States by AASHTO regions. Based on team

conversations and internet-based research, they identified available data sources and 

consolidation activity in requisite States. 

In many cases, the available data provided through Oman Systems, Inc., were not complete 

enough to conduct substantial trend analyses. Item labels and unit prices were presented 

inconsistently in their data. When possible, the research team obtained some information from 

State websites and publicly available resources.

DATA PROCESSING

A cohesive process was developed for the data analysis for all 31 States to ensure consistency in 

the analysis results. This process is described step by step as follows: 

1. The raw data sheet for 1 yr (e.g., 2006) was opened. Filters were added for each column 

(State, pay item, description, quantity, unit, price, job number, bid date, county, and 

project type). 

2. The State column was filtered to select one State (e.g., Virginia).

3. The description column was sorted to select concrete, asphalt, and aggregate items. This 

project limited analysis to concrete, asphalt, and aggregate construction materials alone. 

A different project could be developed to look at other project component costs, 

including engineering, geotechnical, signs, and testing equipment. 

4. This selection was then copied and pasted into its own spreadsheet file. 

5. Step 1 through step 3 were repeated with each year’s raw data sheet, and each selection 

was pasted into the State-specific spreadsheet in chronological order. 

6. Within each State-specific sheet, the research team attempted to identify the most 

frequently occurring specific item for three material categories (concrete, asphalt, and 

aggregate). The more data points available for analysis, the more significant any results 

would be. However, in some States, no one item was used often enough to yield 

meaningful analysis. This challenge is described in more detail in chapter 5. 

7. The data for each specific item selected within one State were separated by year. The 

following values were calculated for the one item for each year: average price for the 

year, maximum price for the year, minimum price for the year, and standard deviation. 
16 

8. A graph of each specific item’s average price versus year was created for each State, 

resulting in two to three graphs per State (because some States only yielded two items for 

detailed analysis).

9. A table for each specific item was then created to display average price, maximum price, 

minimum price, and standard deviation for each year, resulting in two to three graphs and 

a corresponding table associated with each graph for every State. 

10. Any unusual prices were flagged for further analysis, such as very high average or 

maximum prices, very low average or minimum prices, or large standard deviations. 

11. Further analysis was conducted of unusual prices, which involved finding the item in the 

State’s data sheet. From here, it was determined how often the unusual price(s) occurred. 

The job number, bid date, and county for these prices were identified. Then the job 

number and bid dates were used to find more details on this project through a 

combination of the State’s website and Bid Express. 

12. The project location was also investigated to see if transportation costs or proximity to 

large urban areas perhaps played a role in the price. Anecdotal information gathered from 

the State were analyzed to assess if other factors contributed to the price, such as possible 

M&A activity, material shortages, or economic conditions. 

On completion of these steps, our team provided additional data review of individual practices, 

such as collection of information on contractors “skewing” their bids: that is, placing high unit 

bids on items that would overrun DOT estimates and placing low unit bids on items that would 

underrun them. Such “penny bidding” was represented throughout the data and is shown in the 

accompanying tables. In many cases, these individual bid item number prices make quantitative 

assessments of M&A activity impossible.

In compliance with the Paperwork Reduction Act (1995) and in concert with direction from the 

FHWA project manager, the States were contacted to discuss what data might be available to 

assist in the study and for general awareness of M&A activity. 

AASHTO REGION 1

This section presents States located in AASHTO region 1: Massachusetts, New York, 

Pennsylvania, and Vermont.

Massachusetts

Massachusetts DOT (MassDOT) was contacted by phone and email; no formal script was 

followed. A general inquiry was made regarding consolidation and bid activity within the State

during the analysis period of 2006 through the first three quarters of 2016. No formal 

questionnaire was developed for these informal contacts. The research team discussed with 

MassDOT the availability of additional bid price information and general concerns about the 

competitiveness in their State. Anecdotal evidence provided by MassDOT showed consolidation 

activity within the paving and aggregate industry around 2000 when a major firm bought several 

smaller paving firms and aggregate sources. The impact of this activity was felt in the eastern 

part of the State (districts 3, 4, 5, and 6), where less aggregate was available. However, whether 

costs were impacted due to this merger was not clear, and activity since then did not raised 
17 

concerns. Bid data for Massachusetts for 2006 through the third quarter of 2016 were used for 

analysis. Analysis of this bid data confirmed no evidence of price increases due to this 

acquisition. 

A total of 136 contractors were included in the bid data for this analysis period. MassDOT also 

provided weighted bid price data, as well as mean and median bid prices by item and by district 

for all items included in the data provided by Oman Systems, Inc., and supplemented by research 

team review of information posted on State DOT websites. Some variability across districts was 

seen in mean and median bid pricing for items such cement concrete and asphalt products. This 

variability can be attributable to material source location in the State. For example, districts 3, 4, 

5, and 6 in the eastern part of the State had less aggregate available than did the western part of 

the State. 

Figure 6, figure 7, and figure 8 show the bid price trends for three materials: 30-MPa, 40-mm,

335-kg cement concrete (item No. 901), HMA (item No. 460), and gravel borrow (item No.

151), respectively. Below each figure, additional pricing data to support the graphical 

information are provided (table 4, table 5, and table 6, respectively).

Figure 6 shows the average price of this particular concrete item (item No. 901) in Massachusetts 

during the analysis period. Moderate variation can be seen in the average price from year to year, 

with a general increase in average price from 2014 onward. Table 4 shows more detailed pricing 

information by year. Detailed analysis showed that multiple high prices in each year drove the 

average prices up, which is also reflected in the standard deviation for each year. The team 

looked up the projects with high prices on the MassDOT website; however, no overt causes or 

patterns were discovered for the higher prices. 

Source: FHWA. 

CY = cubic yard. 

Figure 6. Graph. Concrete bid price trends—Massachusetts 2006–2016. 
18 

Table 4. Concrete price data—Massachusetts.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 27 539.73 1,100.00 200.00 274.7

2007 23 812.99 3,287.59 133.00 658.3

2008 45 690.37 2,000.00 149.09 386.5

2009 31 631.47 2,000.00 137.00 428.1

2010 33 611.04 1,700.00 95.00 333.8

2011 29 536.35 1,271.52 100.00 266.3

2012 31 754.88 1,780.00 110.00 422.6

2013 33 651.92 1,500.00 50.00 370.7

2014 35 586.79 2,000.00 50.00 385.6

2015 32 758.29 1,900.00 100.00 432.4

2016 33 1,009.50 2,000.00 125.00 517.1

Next, the price trends for a specific asphalt item were investigated. Figure 7 shows the price 

trends for a specific asphalt item (item No. 460) in Massachusetts during the analysis period. 

Table 5 provides some additional price information. As can be seen, the prices for this asphalt 

item remained relatively consistent throughout the period except for a slight increase in 2015. 

However, this higher price only occurred once in one project. 

Source: FHWA. 

Figure 7. Graph. Asphalt bid price trends—Massachusetts 2006–2016. 
19 

Table 5. Asphalt price data—Massachusetts.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum

Price 

(Dollars)

Standard 

Deviation

2006 41 81.67 195.00 48.30 28.7

2007 73 99.69 240.00 55.03 36.1

2008 125 101.72 500.00 45.00 63.1

2009 134 102.20 310.00 45.00 42.0

2010 98 101.37 250.00 62.00 41.1

2011 86 99.14 250.00 46.00 37.7

2012 25 119.13 225.00 46.00 43.9

2013 6 152.33 250.00 115.00 46.8

2014 1 112.50 — — —

2015 1 325.00 — — —

2016 0 — — — —

—No data.

Lastly, the price trends for an aggregate item in Massachusetts were analyzed. Figure 8 and 

table 6 show price data information for a specific aggregate item (item No. 151) throughout the 

analysis period. Similar to the asphalt data, no significant fluctuations took place throughout the 

analysis period, which is reflected in the low standard deviation values. A general increase in 

average prices occurred toward the end of the analysis period; however, this increase is small and 

likely due to regular inflation of prices over time. 

Source: FHWA. 

Figure 8. Graph. Aggregate bid price trends—Massachusetts 2006–2016. 
20 

Table 6. Aggregate price data—Massachusetts.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 48 25.00 81.00 0.76 14.7

2007 75 26.25 114.68 1.00 18.1

2008 114 32.59 100.00 1.00 16.0

2009 109 31.40 70.00 0.10 14.7

2010 113 26.77 150.00 0.01 19.7

2011 95 26.67 62.00 0.01 14.6

2012 62 27.21 85.00 1.00 14.1

2013 76 25.50 65.00 0.01 13.7

2014 101 29.16 115.00 0.01 19.0

2015 100 31.77 100.00 0.01 18.2

2016 68 34.84 125.00 0.01 24.2

New York

In New York, one large firm serves many major construction markets in ready-mix concrete as 

well as asphalt. Since 2013, this firm has gained approximately 15 acquisitions of ready-mix 

concrete plants in the New York City metropolitan area, as well as Washington, DC. New York 

State DOT’s (NYSDOT’s) Engineering Division provided weighted average item price reports, 

as well as regional and statewide average awarded price reports. These reports, used in tandem 

with the aforementioned dataset, provided analysis of the pricing of ready-mix concrete items in 

awarded bids for the previous 5 yr.

NYSDOT divides the State into 11 unique regions; region 11 includes the New York City 

metropolitan area. To assess the effects of the major acquisitions that happened in the previous 

5 yr, ready-mix concrete items were targeted for this region specifically to identify any trends in 

pricing. Prices for these concrete items in the bid data were higher than reported unit prices in 

region 11 compared with other regions: where a ready-mix concrete item in another region may 

see prices within $100.00 of the reported unit price; in region 11 the same item was often higher.

Figure 9, figure 10, and figure 11 show the bid price trends for three materials: concrete for 

structures class HP (item No. 555.09), asphalt concrete 37.5-mm F9 Superpave® (item No.

402.3789016), and aggregate (item No. 623.0551), respectively. Below each figure, additional 

pricing data to support the graphical information are provided (table 7, table 8, and table 9, 

respectively).

As can be seen in figure 9 and table 7, the standard deviations for this concrete item (item No.

555.09) was large, indicating a large deviation of values from the mean. This deviation is also 

reflected in the large differences between minimum and maximum price; for example, in 2007, 

the maximum price was $11,468.30, whereas the minimum price bid was $328.76. Further 

analysis of the bids containing this item in 2007 revealed that this maximum price only occurred 

once. Without the $11,468.30 item, the standard deviation of the remaining data for 2007 was 

786.2, which is significantly smaller, indicating that this high price incident was impacting the 

average price and standard deviation of the data for this item for 2007. 
21 

Source: FHWA. 

Figure 9. Graph. Concrete bid price trends—New York 2006–2016. 

Table 7. Concrete price data—New York.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 35 1,050.06 3,822.77 382.28 781.4

2007 45 1,212.67 11,468.30 328.76 1,730.5

2008 28 1,011.58 3,058.22 292.27 665.2

2009 77 1,010.79 3,822.77 324.94 769.9

2010 27 1,016.05 4,900.00 411.66 904.1

2011 31 986.10 8,000.00 1.00 1344.2

2012 52 1,056.88 3,500.00 240.00 681.2

2013 39 1,327.42 4,000.00 330.00 907.7

2014 42 1,672.81 5,900.00 405.00 1,330.5

2015 40 1,545.00 10,000.00 475.00 1,631.9

2016 14 1,934.86 6,952.00 190.00 1,634.6

Similarly, in 2011 there was a minimum bid price of $1.00. Further analysis of the bids 

containing this item in 2011 revealed that this minimum price of $1.00 occurred only once, 

indicating this one low priced item could be impacting the average price and standard deviation. 

Next, the price trends for an asphalt item in New York were investigated. Figure 10 shows one 

noticeable spike in the bid price of a specific asphalt item (item No. 402.198901). However, 

table 8 shows that the actual data for this item were somewhat limited: the item is not used in 

each of the analysis years, and, in the years it is present, it is only present several times. The 

price spike is due to the higher price of $220.00 per ton in 2010 and only occurred once in the 

data.
22 

Source: FHWA. 

Figure 10. Graph. Asphalt bid price trends—New York 2006–2016. 

Table 8. Asphalt price data—New York.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 2 74.84 90.72 58.97 15.9

2008 0 — — — —

2009 2 98.50 127.01 70.00 28.5

2010 1 220.00 — — —

2011 1 165.00 — — —

2012 0 — — — —

2013 1 170.00 — — —

2014 0 — — — —

2015 2 185.00 200.00 170.00 15.0

2016 0 — — — —

—No data.

Lastly, price trends for an aggregate item in New York were analyzed. Similar to the asphalt 

data, the aggregate data were also limited for New York during the analysis period. The 

aggregate item that occurred the most during the analysis period was item No. 623.0551 (named 

“aggregate” in New York). While the graph in figure 11 seems to indicate price fluctuations, the 

data in table 9 show the variation in price is very low, as indicated by the low standard deviation 

values.
23 

Source: FHWA. 

Figure 11. Graph. Aggregate bid price trends—New York 2006–2016. 

Table 9. Aggregate price data—New York.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 8 17.63 21.77 14.15 2.5

2007 5 16.15 18.14 14.52 1.3

2008 0 — — — —

2009 1 18.60 — — —

2010 0 — — — —

2011 0 — — — —

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Pennsylvania 

Pennsylvania DOT’s (PennDOT’s) Bureau of Project Delivery reported that, while some M&A

activity had occurred between the analysis years 2006–2016, some larger companies also 

experienced some splitting. None of the activity seen raised concerns about increased bid prices, 

the number of bids, or total project costs, and the State did not alter contract language or add 

additional statutes or bidding processes to control for any cost effects. 

Data provided to the research team as well as historical unit price data provided by PennDOT 

allowed for analysis of average item prices, weighted average prices, low and high prices, and 

the number of times the item occurred in a letting during the year of interest. Overall, bid prices 

were within small ranges of report unit prices for the material items of interest, including 
24 

aggregate, asphalt, and concrete. Most of the State’s concrete and asphalt suppliers were located 

in the eastern region of the State. In comparison, aggregate suppliers were located primarily in 

the eastern or western areas, leaving the middle of the State relatively void of suppliers. Some 

transportation costs associated with projects in the central region were to be expected based on 

this distribution of materials.

Figure 12, figure 13, and figure 14 show the bid price trends for three materials: class AA 

cement concrete (item No. 1001-0001), SP asphalt mix dense graded HMA base (item No.

0309-0437), and No. 1 coarse aggregate (item No. 0703-0020), respectively. Below each figure, 

additional pricing data to support the graphical information are provided (table 10, table 11, and 

table 12, respectively).

As can be seen in figure 12 and table 10, there is a high maximum price in 2014 of $18,250.00. 

The minimum bid price for this specific concrete item in 2014 was $135.00, and the average 

price was $1,544.62. This high maximum bid price is reflected in the standard deviation of 

2,160.8. Further analysis of the 2014 data for this concrete item revealed that this maximum 

price only occurred once in the data for that year.

Source: FHWA. 

Conc = concrete.

Figure 12. Graph. Concrete bid price trends—Pennsylvania 2006–2016. 
25 

Table 10. Concrete price data—Pennsylvania.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum Price 

(Dollars)

Standard

Deviation

2006 69 1,726.17 7,885.00 311.57 1,458.1

2007 63 1,622.84 4,900.00 440.63 949.1

2008 68 1,362.68 4,000.00 336.00 828.9

2009 96 1,558.94 5,500.00 425.00 979.3

2010 88 1,359.99 7,294.00 260.00 904.9

2011 62 1,376.70 4,680.00 269.00 869.2

2012 55 1,424.38 5,500.00 150.00 942.8

2013 52 1,254.76 3,672.00 107.00 703.3

2014 72 1,544.62 18,250.00 135.00 2,160.8

2015 45 1,412.24 4,500.00 350.00 886.3

2016 35 1,674.35 8,530.00 8.00 1,447.8

Next, the price trends for an asphalt item in Pennsylvania were analyzed (figure 13 and table 11). 

There was one higher maximum price for this specific asphalt item (item No. 0309-0437) in 

Pennsylvania in 2010, which drove the average price for that year higher. The spike seen in 

figure 13 indicates this high price. 

Source: FHWA. 

Asph Mx DSN = asphalt mix dense graded. 

Figure 13. Graph. Asphalt bid price trends—Pennsylvania 2006–2016. 
26 

Table 11. Asphalt price data—Pennsylvania.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 52 105.01 600.00 35.00 89.7

2007 53 141.04 600.00 46.83 123.4

2008 56 147.90 1,005.00 44.05 139.8

2009 62 141.31 578.81 51.15 109.3

2010 43 192.97 1,550.00 51.90 239.1

2011 39 133.23 440.40 61.50 81.9

2012 37 130.00 500.00 50.00 100.2

2013 39 126.03 304.62 51.80 55.2

2014 41 134.35 325.00 60.50 67.0

2015 25 123.39 240.00 56.00 48.8

2016 1 65.00 — — —

—No data.

Lastly, the price trends for an aggregate item were analyzed. Figure 14 shows the bid price trends 

for a specific aggregate item in Pennsylvania (item No. 0703-0020). Table 12 gives additional 

price information, including maximum and minimum prices for each year and the standard 

deviation. Prices remained consistent throughout the analysis period. 

Source: FHWA. 

Figure 14. Graph. Aggregate bid price trends—Pennsylvania 2006–2016. 
27 

Table 12. Aggregate price data—Pennsylvania.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 61 59.20 315.00 13.00 55.4

2007 96 65.25 600.00 1.00 85.8

2008 96 55.17 260.00 0.01 34.1

2009 155 55.72 500.00 0.01 45.1

2010 164 48.72 190.00 0.01 24.3

2011 119 48.93 150.00 3.00 22.9

2012 152 53.53 314.00 25.00 27.5

2013 120 51.91 150.00 21.64 21.2

2014 129 53.40 200.44 0.01 27.8

2015 119 58.50 160.00 0.10 28.3

2016 82 64.69 247.00 20.00 37.5

Vermont

Vermont DOT (VTrans) reported a total of 175 locations within the State as well as some in 

neighboring States, including New Hampshire, that were approved sources for HMA and 

portland cement concrete. Locations of these suppliers are evenly distributed throughout 

Vermont and mostly concentrated along interstate corridors, including I–91 and I–89. Aggregate 

suppliers in the State are also relatively evenly spread from north to south along major interstate

corridors.

A total of 674 projects took place during the analysis years. No major or significant 

consolidation activity of firms in the State was brought to the attention of VTrans, and no 

significant pricing effects were observed.

Figure 15, figure 16, and figure 17 show the bid price trends for three materials: concrete high 

performance (item No. 501.34), emulsified asphalt (item No. 404.65), and aggregate surface 

course (item No. 401.1), respectively. Below each figure, additional pricing data to support the 

graphical information are provided (table 13, table 14, and table 15, respectively).

Figure 15 shows the price trends for a specific concrete item in Vermont (item No. 501.34). 

Prices fluctuated throughout the analysis period with a general increase in average price in

2013-2016. The high maximum prices caused larger standard deviation values, shown in 

table 13; however, no significant anomalies were found. 
28 

Source: FHWA. 

Figure 15. Graph. Concrete bid price trends—Vermont 2006–2016. 

Table 13. Concrete price data—Vermont.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 15 819.29 1,820.00 500.00 326.9

2007 12 729.81 1,450.00 500.00 259.1

2008 27 903.03 3,000.00 443.44 565.3

2009 27 720.54 1,720.00 267.59 316.4

2010 11 745.02 1,100.00 500.00 220.1

2011 14 632.80 1,200.00 378.00 189.3

2012 8 573.64 1,000.00 325.00 199.6

2013 12 541.69 821.50 300.00 123.2

2014 13 803.27 1,700.00 505.00 363.9

2015 13 849.74 2,000.00 400.00 407.4

2016 6 1,314.33 3,000.00 650.00 888.8

Next, the asphalt price trends were analyzed for a specific asphalt item (item No. 404.65) in 

Vermont. Figure 16 shows the asphalt price trends for item No. 404.65 in Vermont during the 

analysis period. Prices showed a decreasing trend over this period with several spikes in the 

average price in 2006, 2008, and 2011. However, table 14 shows that the maximum price for this 

item was highest in those same years, which impacts the average price. This finding is also 

reflected in the larger standard deviation for those 3 yr.
29 

Source: FHWA. 

CWT = hundredweight.

Figure 16. Graph. Asphalt bid price trends—Vermont 2006–2016. 

Table 14. Asphalt price data—Vermont.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 39 226.80 1,600.00 10.00 298.3

2007 37 129.16 800.00 22.87 154.5

2008 37 190.27 1,250.00 2.00 236.8

2009 60 151.98 929.86 1.00 148.3

2010 39 112.22 593.25 1.54 116.7

2011 26 183.18 1,000.00 3.30 217.4

2012 16 111.56 550.00 18.00 124.6

2013 25 107.75 325.00 44.00 70.9

2014 24 82.68 220.00 8.50 37.0

2015 28 76.10 145.00 33.98 30.6

2016 15 50.20 102.00 10.00 35.5

Finally, an aggregate item for Vermont was analyzed: aggregate surface course (item No. 401.1). 

The price trends are shown in figure 17, and more detailed price information is provided in 

table 15. Prices of this aggregate item rose steadily over time but overall remained consistent.
30 

Source: FHWA. 

Figure 17. Graph. Aggregate bid price trends—Vermont 2006–2016. 

Table 15. Aggregate price data—Vermont.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 9 36.62 57.34 22.94 9.7

2007 6 35.29 43.00 26.76 6.0

2008 18 50.41 250.00 26.00 49.0

2009 15 44.21 163.62 19.11 33.3

2010 7 41.39 55.00 33.00 7.6

2011 10 45.79 100.00 30.00 21.9

2012 8 58.69 159.63 32.88 40.1

2013 14 52.55 95.00 32.00 20.3

2014 10 45.68 100.00 26.00 19.6

2015 18 50.72 75.00 30.00 14.2

2016 8 81.20 213.98 10.00 66.4

AASHTO REGION 2

This section presents States located in AASHTO region 2: Arkansas, Florida, Georgia, 

Louisiana, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia. 

Arkansas 

One major merger took place in Arkansas in 2014 during which a large company bought out 

another. However, the Arkansas DOT (ArDOT) did not report any significant effects on bid 

prices following this consolidation. Limited sources of aggregate, however, had an impact on 

prices, particularly in the southern part of the State. These pricing impacts were not due to any 

merger or acquisition activity, and the pricing impacts have remained stable for some time. 

ArDOT also reported that Arkansas uses primarily HMA within the State, and that not much 
31 

concrete paving is utilized. This usage was reflected in the bid data provided to the research 

team.

Arkansas region 2 (located in south central and southeastern Arkansas) has a major lack of 

aggregate. Most aggregate in the State comes from a quarry near Little Rock, AR, which is 

owned by a firm that also owns two HMA paving companies. Within the region, only one other 

paving company exists, and it must purchase aggregate from the controlling firm. Due to these 

conditions, prices on aggregate in region 2 are often 20 percent higher than in other areas of the 

State. Some of these pricing discrepancies are due to high transportation costs; however, the 

ArDOT does have some concerns regarding aggregate pricing in this area.

Other parts of the State are believed to have sufficient competition with both in-State and 

out-of-State firms, as well as sufficient aggregate and material suppliers. One strategy to address 

the pricing concerns for HMA in region 2 has been to bundle several HMA projects together into 

a single letting in hopes that increased volume will attract other pavers to bid. After examination 

of the data, it appeared that a variety of firms were awarded bids containing HMA materials.

Figure 18, figure 19, and figure 20 show the bid price trends for three materials: class S 

concrete–roadway (item No. 802016), asphalt (performance grade [PG] 64-22) in asphalt 

concrete hot-mix surface course (1⁄2-inch) (item No. 407332), and aggregate base course (class 7) 

(item No. 303107), respectively. Below each figure, additional pricing data to support the 

graphical information are provided (table 16, table 17, and table 18, respectively).

Figure 18 shows the price trends for a specific concrete item (item No. 802016) for Arkansas. 

Table 16 shows more detailed price information for the analysis period. The concrete item price 

showed a steady increase from 2012 through the end of the analysis period, but no major price 

anomalies were found. 

Source: FHWA. 

Figure 18. Graph. Concrete bid price trends—Arkansas 2006–2016. 
32 

Table 16. Concrete price data—Arkansas.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 16 598.06 950.00 325.00 186.2

2008 24 575.88 1,575.00 404.82 229.2

2009 43 533.66 1,090.00 300.00 156.3

2010 34 514.81 920.00 210.00 138.3

2011 33 526.17 1,080.00 287.00 159.4

2012 24 546.13 1,001.20 199.82 179.7

2013 25 578.18 2,127.10 318.00 338.8

2014 29 668.44 1,500.00 400.00 250.9

2015 22 808.29 3,227.95 360.00 581.5

2016 25 896.68 4,300.73 450.00 733.9

—No data.

Next, the price trends for a specific asphalt item were analyzed. Figure 19 shows the price 

information for a specific asphalt item (item No. 407332). As reflected in the graph and in 

table 17, this item was not used in 2011–2016. 

Source: FHWA. 

Figure 19. Graph. Asphalt bid price trends—Arkansas 2006–2016. 
33 

Table 17. Asphalt price data—Arkansas.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 69 412.14 800.00 120.00 161.7

2007 83 416.11 1,790.00 111.52 216.5

2008 71 701.03 1,760.00 120.00 381.6

2009 100 493.58 1,250.00 108.86 217.7

2010 21 624.15 1,463.40 120.00 313.9

2011 0 — — — —

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Finally, the price trends for a specific aggregate item (item No. 303107) were analyzed. 

Figure 20 shows the bid prices for this aggregate item throughout the analysis period. The item 

was used in all years, which yielded a longer available period for analysis. Prices fluctuated 

throughout the analysis period, but no major anomalies were identified. Additionally, maximum 

and minimum bid prices did not vary significantly from the average, which is reflected in the low 

standard deviation values shown in table 18. 

Source: FHWA. 

Figure 20. Graph. Aggregate bid price trends—Arkansas 2006–2016. 
34 

Table 18. Aggregate price data—Arkansas. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 73 21.02 80.00 8.50 11.3

2007 82 26.19 200.00 9.00 23.8

2008 81 25.51 140.00 10.85 15.0

2009 99 25.45 135.00 11.80 15.8

2010 91 21.05 45.15 10.85 6.0

2011 114 24.31 110.00 10.52 14.2

2012 70 22.56 50.00 11.00 8.8

2013 101 24.41 79.80 9.61 11.5

2014 113 29.76 187.50 11.85 20.5

2015 104 32.10 110.00 14.60 15.8

2016 85 30.15 63.20 14.75 10.8

Florida

Several acquisitions and company name changes took place in Florida during the 2006–2016 

period. However, Florida DOT (FDOT) reported that there was still adequate competition in the 

State and that consolidation activity within the asphalt industry was minimal. No initial concerns 

were voiced regarding bid pricing effects, and action by FDOT to address M&A activity was not 

necessary. Florida is divided into seven districts. During the analysis period, between 81 and 153 

unique firms awarded bids each year. 

In 2007, a major company acquired another firm, which at the time was a leading producer of 

aggregate, cement, and concrete. However, the effects of this activity were not seen in the 

material prices in Florida following the merger. The purchasing firm has facilities in 21 States, as 

well as Mexico and the Bahamas, and has a wide distribution network, but these market shares 

did not show a correlation with price trends or activity within the State during the analysis 

period. Another acquisition took place in late 2015 of an aggregate supplier in the western part of 

the State. Examination of aggregate pricing following this activity yielded no significant changes 

and no significant digressions or variations from the reported unit price for aggregate items. Data 

from Florida did not reflect any significant changes in pricing, although substantial acquisition 

activity occurred in the concrete and asphalt industries. 

Figure 21 and figure 22 show the bid price trends for two materials: concrete class II

superstructure (item No. 40024) and miscellaneous asphalt pavement (item No. 3391), 

respectively. Below each figure, additional pricing data to support the graphical information are

provided (table 19 and table 20, respectively).

Figure 21 shows the price trends for a specific concrete item (item No. 40024). Price fluctuations 

were observed throughout the analysis period, which is also reflected in the data shown in 

table 19. Several years had high maximum bid prices, which impacted the average price for the 

corresponding year, but no anomalies were identified. Also, no fluctuations were linked to 

merger or acquisition activity. 
35 

Source: FHWA. 

Figure 21. Graph. Concrete bid price trends—Florida 2006–2016. 

Table 19. Concrete price data—Florida.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 23 1,378.80 4,500.00 580.00 1,015.6

2007 23 1,444.46 3,499.44 591.00 976.9

2008 14 815.74 1,006.00 620.00 113.8

2009 20 1,055.63 4,500.00 366.84 1,038.9

2010 15 626.15 1,226.44 375.00 236.5

2011 11 680.90 1,177.00 300.00 255.8

2012 12 567.83 883.92 375.00 154.5

2013 20 712.57 1,670.00 450.00 276.8

2014 21 698.11 1,250.00 461.78 195.5

2015 10 894.64 3,096.03 375.00 754.8

2016 17 768.88 1,676.00 478.67 293.6

Next, asphalt price trends were analyzed for one specific asphalt item (item No. 3391). Figure 22

shows the price fluctuations for this asphalt item across the analysis period. In 2011, a price 

spike that is visible in the graph is attributed to the very high maximum bid price of $11,333.30 

in that year; this deviation is also apparent in the high standard deviation value for that year, 

shown in table 20. 
36 

Source: FHWA. 

Figure 22. Graph. Asphalt bid price trends—Florida 2006–2016. 

Table 20. Asphalt price data—Florida.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 80 322.21 4,140.00 100.00 450.9

2007 81 377.89 2,700.00 85.00 496.0

2008 75 264.16 2,000.00 108.27 237.9

2009 72 226.23 1,000.00 79.70 174.8

2010 94 207.88 1,000.00 82.30 126.3

2011 74 355.12 11,333.30 80.24 1,289.3

2012 54 253.41 3,100.00 76.75 411.9

2013 83 263.20 1,000.00 1.04 147.4

2014 74 271.70 1,500.00 5.00 220.3

2015 69 302.51 1,650.00 10.00 273.2

2016 47 356.47 1,750.00 103.62 304.2

Georgia

Data revealed that 152 unique firms were awarded bids on projects in Georgia in 2006–2016. 

Unit price data for all bid item numbers across the analysis period were not available; however, 

Georgia DOT (GDOT) does publish an asphalt cement price index. These data include awarded 

contracts beginning in 2009 and report the State’s base asphalt prices. Data in this set were

compared against bid prices for asphalt products in the dataset; no major anomalies were 

observed. 

Many of the State’s concrete and asphalt suppliers are located in the northwestern region, while 

many of the aggregate material locations are near the Atlanta, GA, area, as well as out of State. 

Some major firms supplying materials to multiple States—including Tennessee, Georgia, 
37 

Florida, and others in the area—also provide materials to many projects included in the data 

provided through Oman Systems, Inc., and supplemented by research team review of 

information posted on GDOT websites in 2006–2016. Two of these large firms, which are 

affiliated with one another, were awarded close to 100 of the total bids across the analysis period 

in the State. Three major firms that control large market shares in multiple States in the region 

largely control aggregates within Georgia. Pricing effects were not seen during analysis of the 

data provided to the research team. However, the perceptions of firms and suppliers in the State

on the effects of this activity on competition are unknown. 

Figure 23, figure 24, and figure 25 show the bid price trends for three materials: class A concrete 

(item No. 500-3101), asphalt concrete 12.5-mm porous European mix GP 2 (item No. 400-3624), 

and aggregate surface course (item No. 318-3000), respectively. Below each figure, additional 

pricing data to support the graphical information are provided (table 21, table 22, and table 23, 

respectively). 

Figure 23 shows the price trends for a specific concrete item (item No. 500-3101) in Georgia. 

Prices decreased slightly between 2008 and 2011 before they began to rise again. One noticeable 

price spike is evident in the graph for 2015. In table 21, this price spike is attributed to the high 

average bid price for that year.

Source: FHWA. 

Figure 23. Graph. Concrete bid price trends—Georgia 2006–2016. 
38 

Table 21. Concrete price data—Georgia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 103 752.69 3,120.00 0.87 408.7

2007 81 685.26 2,000.00 149.09 310.5

2008 36 562.63 1,344.56 146.00 304.9

2009 58 471.37 1,200.00 140.00 200.4

2010 37 470.76 1,081.61 121.22 224.9

2011 34 479.29 938.80 133.00 226.8

2012 39 534.40 1,217.00 100.00 253.3

2013 71 684.29 3,200.00 210.00 422.4

2014 42 841.48 5,000.00 110.00 736.1

2015 46 1,132.56 3,570.00 244.00 606.1

2016 21 959.34 1,780.00 275.00 450.0

Next, asphalt bid prices were analyzed for a specific asphalt item (item No. 400-3624). Figure 24

shows mild price fluctuations in 2006–2011 before prices rose steadily for the remainder of the 

analysis period. As can be seen in table 22, there were not as many bids for this asphalt item.

Source: FHWA. 

Ton-G = Metric tons. 

Figure 24. Graph. Asphalt bid price trends—Georgia 2006–2016. 
39 

Table 22. Asphalt price data—Georgia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 9 104.13 149.50 77.62 19.1

2007 9 99.56 150.00 70.70 20.6

2008 1 80.94 — — —

2009 6 123.07 330.00 71.41 92.9

2010 6 110.87 175.00 77.17 31.6

2011 3 91.17 99.25 83.66 6.4

2012 3 105.40 117.69 98.50 8.7

2013 4 124.71 168.00 96.49 26.9

2014 9 132.13 190.29 95.00 32.9

2015 0 — — — —

2016 1 175.00 — — —

—No data.

Finally, bid price trends were analyzed for a specific aggregate item (item No. 318-3000). As can 

be seen in figure 25 and table 23, several low bids of this specific aggregate item (item No.

318-3000) occurred throughout the analysis period. Both 2008 and 2015 contain $0.01 bids. In 

2009 and 2016, there was a low bid price of just over $1 and one that was exactly $1, 

respectively. Since there were only several of these low bid prices, they were not driving the 

yearly average prices down dramatically. As can be seen from the standard deviation column, the 

bid prices for this aggregate item did not vary much from the mean.

Source: FHWA. 

Aggr Surf Crs = aggregate surface course.

Figure 25. Graph. Aggregate bid price trends—Georgia 2006–2016. 
40 

Table 23. Aggregate price data—Georgia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 88 26.24 106.71 10.89 12.6

2007 82 25.59 65.00 13.65 8.8

2008 48 22.43 55.00 0.01 9.3

2009 61 19.20 40.00 1.10 6.9

2010 33 17.54 36.20 10.07 5.7

2011 43 19.64 50.00 10.00 7.3

2012 49 19.92 51.64 5.00 8.1

2013 63 23.68 47.91 10.18 8.2

2014 45 26.53 100.00 14.00 13.1

2015 33 30.19 70.55 0.01 12.5

2016 20 26.84 43.00 1.00 7.4

Louisiana

A total of 228 unique firms were awarded bids in Louisiana during the analysis period of 

2006-2016. Louisiana DOT and Development (DOTD) divides the State into nine districts. The 

locations of aggregate plants in the State are relatively evenly spread throughout. Concrete plants 

are concentrated toward the eastern region of the State, whereas asphalt plants are evenly spread

throughout the State. The State does have some major firms that dominated the market 

throughout the analysis period and continue to thrive today. One such firm was awarded a total 

of 594 of the 2,215 projects in 2006–2016, accounting for almost 27 percent of the total projects 

awarded. However, data did not show any significant effects on pricing due to this activity. 

Weighted averages for contract items are available from the Louisiana DOTD and provide 

information including items, number of bid item numbers per quarter, minimum and maximum 

bid prices for that quarter, and average unit prices. Comparison of the bid item number prices 

against unit prices showed that the bid item number price was not significantly different from the 

reported unit prices. Unit price analysis was done for aggregate, concrete, and asphaltic 

materials, and similar variability was seen across all item types.

Figure 26 and figure 27 show the bid price trends for two materials: class A concrete (item 

No. 805-01-F) and aggregate surface course (item No. 401-02), respectively. Below each figure, 

additional pricing data to support the graphical information are provided (table 24 and table 25, 

respectively).

Figure 26 and table 24 show the limited bid price data available for this concrete item (item 

No. 805-01-F). Finding one specific item that was used in multiple years for all items in 

Louisiana was challenging. To analyze data of only one specific item at a time, items were 

selected even though they were only used for several years during the analysis period. Even 

though these items were not used beyond 2009, the price information for 2006–2009 is still 

valuable to analyze for potential price anomalies. In the case of this concrete item in Louisiana, 

no price anomalies were identified, although the maximum and minimum bid prices had a 

relatively large range, resulting in larger standard deviation values. 
41 

Source: FHWA. 

Figure 26. Graph. Concrete bid price trends—Louisiana 2006–2016. 

Table 24. Concrete price data—Louisiana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 25 869.67 1,500.00 450.00 322.9

2007 22 1,127.42 2,741.40 450.00 615.1

2008 34 1,115.66 4,500.00 550.00 827.1

2009 3 927.76 1,223.29 560.00 275.6

2010 0 — — — —

2011 0 — — — —

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, a specific aggregate item (item No. 401-02) was analyzed. Again, data were only 

available for this item for 2006–2009. In that time, average prices showed a general increase 

(figure 27 and table 25). This item had a smaller range between the maximum and minimum bid 

prices and less variation of price from the average price.
42 

Source: FHWA. 

Figure 27. Graph. Aggregate bid price trends—Louisiana 2006–2016. 

Table 25. Aggregate price data—Louisiana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 98 58.84 250.00 1.00 40.6

2007 139 63.67 598.00 0.01 60.8

2008 136 69.81 382.28 0.01 46.8

2009 29 94.14 400.00 21.00 69.2

2010 0 — — — —

2011 0 — — — —

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

North Carolina 

Most of the State’s aggregate plants are operated by several large, multistate firms and are 

concentrated in the Raleigh, NC, area. Suppliers of concrete and asphalt products are relatively 

spread out throughout the State. A major multistate firm purchased a materials company that was 

supplying aggregates, asphalt paving materials, and ready-mix concrete to areas of Virginia, as 

well as the coastal Carolinas in 2016. Another firm purchased three asphalt paving companies in 

the State in 2011 and another asphalt paving company in the State in 2015. One major vertically 

integrated firm headquartered in the Raleigh, NC, area is a lead producer of concrete, asphalt, 

and aggregates. This major firm both mines and manufactures materials in Raleigh, Durham, 

Wake Forest, Butner, Kittrell, Woodsdale, and Zebulon, NC. In total, 2,029 projects were let in 
43 

the State during the analysis period of 2006–2016. Analyzing pricing effects before and after the 

asphalt paving company purchases in both 2011 and 2015 revealed no significant pricing 

differences and no significant bid price differences compared with unit pricing data. 

Figure 28, figure 29, and figure 30 show the bid price trends for three materials: class A concrete 

(item No. 8182000000), ultrathin HMA B (item No. 1839110000), and aggregate base course

(item No. 1121000000), respectively. Below each figure, additional pricing data to support the 

graphical information are provided (table 26, table 27, and table 28, respectively).

Figure 28 shows the price trends for a specific concrete item in North Carolina (item 

No. 8182000000). Table 26 shows more detailed price information, including the maximum and 

minimum bid price for each year. Item No. 8182000000 appeared in bids in all years of the 

analysis period, providing ample data for analysis. This concrete item had moderate price 

fluctuations throughout this period, with a moderate range between the maximum and minimum 

bid prices, leading to slightly high standard deviations. 

Source: FHWA. 

Figure 28. Graph. Concrete bid price trends—North Carolina 2006–2016. 

Table 26. Concrete price data—North Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 18 754.35 1,500.00 450.00 238.9

2007 44 868.05 1,450.00 535.19 231.1

2008 115 890.92 2,500.00 500.00 267.2

2009 59 720.50 1,306.00 427.25 169.3

2010 57 727.31 1,500.00 375.00 198.3

2011 33 772.83 1,500.00 522.50 201.1

2012 71 843.32 3,000.00 450.00 336.8

2013 56 917.29 1,600.00 560.00 250.2

2014 27 829.34 1,300.00 568.43 172.4

2015 38 893.11 1,550.00 0.00 377.8

2016 28 984.88 1,715.17 565.00 262.8
44 

Next, a specific asphalt item (item No. 1839110000) was analyzed. Figure 29 and table 27 show 

the price trends for this item for the years it appeared in the dataset (2006–2011). During this 

time, the prices of this item steadily decreased and had low variation. 

Source: FHWA. 

Figure 29. Graph. Asphalt bid price trends—North Carolina 2006–2016. 

Table 27. Asphalt price data—North Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 4 46.18 63.50 33.50 11.2

2007 11 45.61 62.69 31.30 7.1

2008 5 44.23 55.00 34.50 6.5

2009 8 42.09 48.50 34.00 5.0

2010 2 39.12 45.00 33.25 5.8

2011 3 36.17 49.50 18.00 13.3

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, a specific aggregate item (item No. 1121000000) was analyzed. Figure 30 shows one 

notable price spike in 2012. In table 28, this year had a high maximum bid price of $1,420.87 

and the highest standard deviation in price. Further investigation into the project containing this 

high bid price did not reveal any apparent reason for the high price. 
45 

Source: FHWA. 

Figure 30. Graph. Aggregate bid price trends—North Carolina 2006–2016. 

Table 28. Aggregate price data—North Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 22 27.70 58.00 19.00 9.1

2007 39 31.26 100.00 18.17 14.2

2008 71 29.37 50.92 12.88 7.9

2009 47 24.12 60.00 12.23 8.8

2010 48 25.04 65.00 0.00 11.9

2011 45 21.94 37.00 0.00 9.9

2012 51 55.59 1,420.87 0.00 193.6

2013 57 30.16 93.23 0.00 17.4

2014 48 26.62 45.00 0.00 10.1

2015 33 27.74 49.70 0.00 10.2

2016 17 37.55 100.00 22.00 17.8

South Carolina

Within South Carolina, many of the asphalt and concrete suppliers are located in the 

northwestern region. Many of the State’s aggregate suppliers operate out of Charleston and 

Columbia, SC, with some major multistate firms operating in the region. South Carolina DOT

(SCDOT) contains unit price adjustment clauses for various construction materials, including 

asphalt, to help alleviate estimation errors due to price fluctuations. The State is divided into four 

regions: Upstate, Midlands, Pee Dee, and Lowcountry. Special contract language has not been 

adopted to alleviate pricing effects. The data provided through Oman Systems, Inc., and 

supplemented by the research team review of information posted on State DOT websites did not 

reveal pricing anomalies that could be correlated with any consolidation activity within the State. 
46 

A total of 151 unique contractors were awarded bids on projects during the analysis years, and a 

total of 2,004 projects containing material items of interest took place. Recently, SCDOT was

provided with a sustainable, increased revenue source from the General Assembly Act 40, which 

was passed by the General Assembly and became effective July 2017 (South Carolina 

Government 2021). As a part of this increased funding, the 10-yr plan for the State includes 

many construction projects, such as highway improvement, bridge replacement, road resurfacing, 

and interstate widening. This large influx of construction projects, likely utilizing many of the 

material items of interest, will provide a variety of new data for any future analyses. 

Figure 31, figure 32, and figure 33 show the bid price trends for three materials: concrete for 

structures class 4000 (item No. 7011400), HMA surface course type C (item No. 4030340), and 

aggregate No. CR-14 (item No. 3022000), respectively. Below each figure, additional pricing 

data to support the graphical information are provided (table 29, table 30, and table 31, 

respectively).

Figure 31 shows the price trends for one specific concrete item in South Carolina during the 

analysis period (item No. 7011400). Prices fluctuated throughout this period with a general 

increase after 2013. Table 29 shows relatively high standard deviation values for this item and 

large ranges between the maximum and minimum bid prices. 

Source: FHWA. 

Figure 31. Graph. Concrete bid price trends—South Carolina 2006–2016. 
47 

Table 29. Concrete price data—South Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 16 968.82 3,471.54 350.00 775.2

2007 27 776.16 2,500.00 424.40 511.3

2008 8 863.49 2,900.00 498.43 772.8

2009 28 695.92 2,335.00 361.97 398.4

2010 18 530.32 1,006.65 400.00 131.6

2011 18 866.70 5,000.00 117.70 1197.8

2012 9 792.00 2,100.00 480.00 490.2

2013 23 696.20 2,440.00 280.00 468.9

2014 38 876.21 3,000.00 109.00 624.9

2015 31 932.98 4,300.00 400.00 648.9

2016 14 1,327.34 3,750.00 785.00 793.8

Next, the price trends for one specific asphalt item (item No. 4030340) were analyzed. Figure 32

shows the price trends for this asphalt item. Small spikes can be seen in 2011 and 2013. Table 30

shows higher maximum bid prices in these years ($500.00 and $555.00, respectively). Further 

investigation revealed only one project in 2011 with a bid price of $500.00 per ton, and, 

similarly, 2013 contained only one project with a bid price of $555.00 per ton. 

Source: FHWA. 

Figure 32. Graph. Asphalt bid price trends—South Carolina 2006–2016. 
48 

Table 30. Asphalt price data—South Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 27 55.98 125.00 36.98 18.2

2007 81 56.05 159.55 28.50 25.4

2008 83 54.81 170.00 28.54 22.8

2009 144 55.87 200.00 30.00 25.3

2010 109 56.35 199.00 32.04 29.8

2011 68 63.76 500.00 34.25 58.7

2012 50 49.21 175.00 28.30 23.9

2013 100 67.75 555.00 30.00 67.5

2014 115 67.37 360.00 27.25 58.1

2015 124 61.88 305.00 35.81 38.1

2016 57 73.88 381.25 41.37 61.9

Lastly, price trends for one specific aggregate item (item No. 3022000) were analyzed. This item 

was not used in all years of the analysis period, as reflected in figure 33 and table 31. For the 

years it was available, prices did not deviate greatly, and no abnormalities were identified. 

Source: FHWA. 

Figure 33. Graph. Aggregate bid price trends—South Carolina 2006–2016. 
49 

Table 31. Aggregate price data—South Carolina.

Year

Data 

Points

Average Price 

(Dollars)

Maximum Price 

(Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 7 33.86 52.00 24.00 11.8

2009 1 36.05 — — —

2010 1 25.00 — — —

2011 0 — — — —

2012 0 — — — —

2013 2 41.00 55.00 27.00 14.0

2014 1 20.00 — — —

2015 0 — — — —

2016 1 38.98 — — —

—No data.

Tennessee

Tennessee DOT (TDOT) saw some consolidation activity during the analysis period. One firm 

made a purchase that resulted in a controlling share in the supply and cost of river sand in the 

Nashville, TN, market. This activity was brought to the attention of the U.S. DOJ Antitrust 

Division. Another firm purchased a company, including their quarries and pits, located in the 

eastern part of the State, which resulted in a controlling market share in this area. Another firm 

purchased several local, family owned, ready-mix plants in the middle of Tennessee. 

Approximately 15 yr earlier, another firm conducted similar purchasing activity. As a result of 

these acquisitions, these two firms own approximately 75 percent of the approved ready-mix 

plants in the middle and eastern parts of the State. 

Another purchase made between 2010 and 2015 resulted in one firm controlling a majority of the 

market share of precast pipe and drainage structures. TDOT reported some concerns over the 

effects of this purchase activity on bid pricing and competition; however, no changes to contract 

language or statues were made as a result. Precast pipe and drainage structure items in the data 

provided through Oman Systems, Inc., and supplemented by research team review of 

information posted on State DOT websites were then compared with unit price data reported by 

TDOT to examine any pricing effects due to the merger activity. This analysis revealed that bid 

prices for these items were not significantly higher than the unit price reported by TDOT: most 

were less than or around $50 higher than the reported unit price. Additionally, a variety of firms 

were seen in the bid data, suggesting that one firm apparently did not hold market control over 

the others. 

Figure 34, figure 35, and figure 36 show the bid price trends for three materials: class A concrete 

(item No. 604-01.01), asphalt concrete mix (PG 64-22) bituminous plant mix base hot mix (item 

No. 307-01.08), and mineral aggregate type A base grading D (item No. 303-01), respectively. 

Below each figure, additional pricing data to support the graphical information are provided 

(table 32, table 33, and table 34, respectively).
50 

Figure 34 shows the price trends for one specific concrete item (item No. 604-01.01). As can be 

seen in the graph and in table 32, prices fluctuated throughout the analysis period, but no major 

abnormalities were identified.

Source: FHWA. 

Figure 34. Graph. Concrete bid price trends—Tennessee 2006–2016. 

Table 32. Concrete price data—Tennessee.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 29 612.03 1,894.67 340.00 320.2

2007 23 494.87 895.00 100.00 164.4

2008 27 513.21 905.00 217.37 182.6

2009 32 502.23 1,156.51 223.37 212.5

2010 25 480.79 800.00 275.00 137.2

2011 25 466.59 1,006.66 250.00 175.1

2012 13 585.89 1,375.00 350.00 292.7

2013 19 616.18 951.00 360.00 156.8

2014 18 567.08 1,120.00 302.89 212.3

2015 20 592.25 1,150.00 250.00 184.6

2016 11 743.14 2,000.00 306.00 433.1

Next, price trends for one specific asphalt item (item No. 307-01.08) were analyzed. Figure 35

shows one noticeable price spike in 2012. Table 33 shows a very high maximum bid price of 

$4,200.00 in 2012 for this item. Further analysis did not reveal any identifiable cause for this 

high price. 
51 

Source: FHWA. 

Figure 35. Graph. Asphalt bid price trends—Tennessee 2006–2016. 

Table 33. Asphalt price data—Tennessee.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 96 86.26 382.00 34.88 53.8

2007 104 90.17 576.85 40.00 64.3

2008 80 99.19 248.34 29.00 46.8

2009 163 91.37 300.00 35.00 45.3

2010 150 103.74 490.00 45.10 57.7

2011 126 119.90 550.00 49.25 78.5

2012 94 191.46 4,200.00 46.00 459.1

2013 93 110.65 750.00 50.00 88.4

2014 97 127.35 830.00 45.00 113.0

2015 95 120.12 1,150.00 47.32 131.7

2016 90 148.03 2,500.00 50.00 267.6

Lastly, price trends for one specific aggregate item (item No. 303-01) were investigated. 

Figure 36 shows the price trends for this item throughout the analysis period. Prices fluctuated 

with an overall rising trend throughout the period. As shown in table 34, this item contained

relatively low standard deviation values. 
52 

Source: FHWA. 

Figure 36. Graph. Aggregate bid price trends—Tennessee 2006–2016. 

Table 34. Aggregate price data—Tennessee.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 167 19.06 134.00 8.80 11.6

2007 187 20.38 123.00 5.00 12.4

2008 151 23.51 100.00 9.19 15.6

2009 260 21.51 95.00 9.00 10.6

2010 227 23.34 75.58 5.00 10.2

2011 215 24.35 126.00 3.25 14.0

2012 164 27.28 150.00 5.00 19.4

2013 177 24.66 150.00 8.33 17.0

2014 188 29.00 505.00 10.00 36.9

2015 141 28.59 163.22 12.00 18.0

2016 143 28.18 82.00 10.00 13.4

Virginia

Some consolidation activity took place in various regions of Virginia; however, not many took 

place during the analysis period. Some M&A activity took place in 2017 and some in the 1990s, 

which is outside the period that data were made available to the team. Consolidation of a 

concrete plant in the Culpeper, VA, region took place in 2012, but the plant soon closed. Thus, 

further analysis was not possible. One aggregate plant in the Culpeper region, based in 

Stevensburg, VA, was sold in 2002. However, this activity did not affect aggregate prices for 

projects following the sale. 

In the Northern Virginia (NOVA) region of the State, a total of six consolidation activities took 

place in the asphalt industry just before the analysis period, including 2002, 2003, 2004, and 

2006. Asphalt product prices in the NOVA region across the analysis period remained relatively 
53 

constant: two projects had a significantly higher bid item number price for asphalt in 2011 and 

2013 for projects in Prince William County. No activity with the firms or with asphalt suppliers 

in the area took place during those periods that would explain the higher prices and fluctuation, 

which was likely due to transportation costs. 

Figure 37, figure 38, and figure 39 show the bid price trends for three materials: concrete class

A3 (item No. 65013), asphalt concrete TY BM-25.0A (item No. 10642), and aggregate base 

material type I, No. 21B (item No. 10128), respectively. Below each figure, additional pricing 

data to support the graphical information are provided (table 35, table 36, and table 37, 

respectively).

Figure 37 and table 35 show the price fluctuation of a specific concrete item (item No. 65013) in 

Virginia during the analysis period. Despite moderate fluctuations, no price anomalies were 

identified.

Source: FHWA. 

Figure 37. Graph. Concrete bid price trends—Virginia 2006–2016. 
54 

Table 35. Concrete price data—Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 22 527.09 1,000.00 284.13 171.9

2007 19 642.42 950.00 452.40 137.4

2008 9 678.06 1,500.00 342.94 343.5

2009 14 584.89 1,312.78 320.00 239.1

2010 21 611.59 1,635.00 312.00 328.7

2011 19 796.20 3,460.00 385.00 746.2

2012 21 541.13 940.00 242.00 211.3

2013 32 822.88 2,500.00 350.00 389.7

2014 32 786.51 1,590.00 445.00 292.6

2015 29 781.02 1,200.00 370.00 232.9

2016 8 856.85 1,500.00 329.79 367.7

Next, the price trends for a specific asphalt item (item No. 10642) were analyzed. Figure 38 and 

table 36 show one price spike in 2011 and a general increasing trend after 2012. The average 

price was higher in 2011, but the maximum and minimum prices were not significantly different 

from those for other years. The highest maximum bid price occurred in 2015 at $2,215.00 per 

ton. This high price only appeared once in the data for 2015, and no apparent cause of the higher 

price was identified.

Source: FHWA. 

Figure 38. Graph. Asphalt bid price trends—Virginia 2006–2016. 
55 

Table 36. Asphalt price data—Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 15 103.17 236.25 51.00 58.4

2007 31 101.04 250.00 18.00 60.9

2008 52 116.01 400.00 54.40 66.9

2009 64 103.10 595.00 49.50 81.2

2010 79 111.09 420.00 52.00 77.4

2011 89 158.33 500.00 56.00 88.2

2012 90 128.00 400.00 62.43 62.8

2013 110 139.47 495.00 58.00 84.9

2014 83 143.19 425.00 61.79 81.9

2015 95 177.16 2,215.00 55.00 224.9

2016 30 206.77 550.00 50.61 158.4

Lastly, price trends for a specific aggregate item (item No. 10128) were analyzed. Figure 39

shows the price trends for this item. One price spike is apparent in 2015. Table 37 shows a high 

maximum price of $1,000.00 in 2015. Further analysis revealed that only one project had a bid 

price of $1,000.00 per ton for this item. Several years had minimum prices of $1.00 and $0.01. 

As noted in the subsection, Inconsistent Bid Item Number Use, at the beginning of this chapter, 

dollar and penny bids can impact average prices, and, as seen in table 37, the standard deviations 

for those years are also higher. For each year with low minimum bid prices, the minimum only 

appeared once per year (one $1.00 per ton price in 2013, one $0.01 per ton price in 2014, and 

one $0.01 per ton price in 2015). 

Source: FHWA. 

Matl = material.

Figure 39. Graph. Aggregate bid price trends—Virginia 2006–2016. 
56 

Table 37. Aggregate price data—Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 94 24.63 88.00 10.00 12.9

2007 87 30.34 300.00 11.71 33.8

2008 95 27.83 125.00 10.89 18.1

2009 66 27.76 100.00 8.00 18.2

2010 88 27.16 120.00 12.91 15.9

2011 81 34.74 169.95 5.25 26.1

2012 88 31.86 250.00 14.25 26.5

2013 114 30.47 100.00 1.00 13.1

2014 101 30.97 90.00 0.01 13.5

2015 96 45.57 1,000.00 0.01 99.9

2016 33 36.29 100.00 0.01 21.9

West Virginia

West Virginia DOT was contacted by email in an attempt to set up a case study interview. 

However, due to an active antitrust investigation at the time of inquiry, information on 

consolidation activity was not available. A major materials provider of aggregate, HMA, and 

concrete products has multiple locations in West Virginia. This supplier also owns plants and 

supplies materials in many other States. Overall aggregate and concrete suppliers in West 

Virginia are spread through the State. However, many projects during the analysis period relied 

on asphalt paving materials instead of concrete. Another major firm with multiple locations in 

multiple States accounts for a large share (approximately one-sixth) of the State’s asphalt 

suppliers. 

Despite the large market control by some major firms operating in this region of the country, 

pricing fluctuations year to year were not unusual. Some higher costs were seen for projects 

located near Fayetteville and Charleston, WV, likely due to shortened timelines to complete 

projects, which often lead to increases in pricing. A total of more than 500 unique contractors 

were included in the bidding data. Unit prices for bid item numbers by year were used to identify 

any anomalies in bid item number prices. However, items of interest across all years’ prices of 

bid item numbers were consistent with unit prices reported by the State. 

Figure 40, figure 41, and figure 42 show the bid price trends for three materials: class B concrete 

(item No. 601002-001), HMA base course (item No. 401001-001), and aggregate base course 

stone or gravel (item No. 307005-001), respectively. Below each figure, additional pricing data 

to support the graphical information are provided (table 38, table 39, and table 40, respectively).

Figure 40 shows the price trends for a specific concrete item in West Virginia (item 

No. 601002-001). The average price fluctuated throughout the analysis period with a general 

increasing trend. Table 38 shows two higher maximum bid prices of $10,000.00 in 2008 and 

2014. 
57 

Source: FHWA. 

Figure 40. Graph. Concrete bid price trends—West Virginia 2006–2016. 

Table 38. Concrete price data—West Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 97 918.27 3,850.00 130.00 692.6

2007 84 1,045.99 9,746.00 190.00 1,252.1

2008 113 1,169.65 10,000.00 200.00 1,249.8

2009 82 856.70 3,400.00 150.00 670.5

2010 98 814.15 2,900.00 120.00 577.6

2011 69 964.11 4,500.00 140.00 827.2

2012 65 1,022.38 3,200.00 160.00 633.1

2013 31 1,211.27 3,725.00 395.00 875.9

2014 55 1,310.01 10,000.00 168.00 1,488.2

2015 31 1,137.43 5,800.00 430.00 931.9

2016 18 1,341.20 5,000.00 135.00 1,179.3

Next the price trends for a specific asphalt item (item No. 401001-001) were investigated. 

Figure 41 and table 39 show the price trends for a specific asphalt item (item No. 401001-001) in 

West Virginia. The item did not appear in any bids in 2013 or 2016. Overall, price fluctuations 

were moderate, and no anomalies were identified.
58 

Source: FHWA. 

Figure 41. Graph. Asphalt bid price trends—West Virginia 2006–2016. 

Table 39. Asphalt price data—West Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 167 104.15 615.00 39.50 82.1

2007 215 91.43 500.00 38.37 59.6

2008 331 96.79 500.00 47.10 56.9

2009 169 111.61 500.00 48.63 70.2

2010 272 99.99 500.00 1.00 55.7

2011 142 99.23 250.00 57.35 34.4

2012 5 179.88 350.00 84.00 93.8

2013 0 — — — —

2014 2 162.50 175.00 150.00 12.5

2015 1 133.00 — — —

2016 0 — — — —

—No data.

Finally, the price trends for a specific aggregate item (item No. 307005-001) were analyzed.

Figure 42 shows the average prices for this item across the analysis period. Prices showed a 

generally increasing trend. Although prices were relatively consistent, several years had penny 

bids, as shown in table 40. These penny bids can impact average price and standard deviation by 

increasing the range between maximum and minimum bid price. 
59 

Source: FHWA. 

Figure 42. Graph. Aggregate bid price trends—West Virginia 2006–2016. 

Table 40. Aggregate price data—West Virginia.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 297 30.73 125.00 6.00 14.3

2007 209 31.99 150.00 0.01 15.8

2008 346 36.63 175.00 0.01 19.0

2009 206 41.84 200.00 0.01 23.9

2010 201 36.73 150.00 0.01 16.1

2011 170 42.36 250.00 1.00 24.1

2012 115 50.10 400.00 10.00 52.4

2013 170 39.58 135.00 0.01 15.9

2014 215 43.94 155.00 0.01 17.8

2015 176 50.25 600.00 0.01 53.7

2016 168 52.59 500.00 0.01 55.7

AASHTO REGION 3

This section presents States located in AASHTO region 3: Illinois, Indiana, Michigan, 

Minnesota, Missouri, Ohio, and Wisconsin. 

Illinois

Evidence gathered from Illinois DOT (IDOT) revealed no significant consolidation activity, 

including M&As. Several HMA pavers in central Illinois joined into one operating company in 

approximately 2006, and IDOT did not feel that this merger caused any significant impacts on 

pricing. HMA pavers in southern Illinois receive a large number of single bids due to the limited 

availability of HMA pavers in that region, but the impact on costs has not been investigated. The 

Cook County area (district 1) has seen a trend toward joint ventures, which have impacted 
60 

competition. However, the only major consolidation occurred in the reinforced concrete pipe 

industry. 

In the past, several smaller companies were producing pipe, but during the analysis period larger 

suppliers purchased these smaller companies. This activity resulted in only several suppliers 

providing pipe. Cost impacts from this activity have not been tracked, but IDOT believes that 

prices may have increased as a result. Impact on competition in district 1 is difficult to attribute 

to consolidation activity, as many jobs in the metropolitan area of Chicago, IL, include very tight 

timelines, which increase costs.

Figure 43, figure 44, and figure 45 show the bid price trends for three materials: concrete 

structures (item No. 50300225), HMA surface course mix including N50 (item No. 40603310), 

and aggregate surface course type B (item No. 40200800), respectively. Below each figure, 

additional pricing data to support the graphical information are provided (table 41, table 42, and 

table 43, respectively).

Figure 43 and table 41 show price trends for a specific concrete item in Illinois (item No.

50300225). A high maximum bid price of $16,666.70 was identified in 2015. The average price 

in 2015 was also higher, as indicated in the spike on the graph. No cause for this high maximum 

price was identified.

Source: FHWA. 

Figure 43. Graph. Concrete bid price trends—Illinois 2006–2016. 
61 

Table 41. Concrete price data—Illinois.

Year

Data 

Points

Average 

Price 

(Dollars)

Maximum 

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 209 975.34 6,650.00 290.00 1,014.8

2007 171 861.29 4,000.00 50.00 579.2

2008 206 904.92 5,700.00 150.00 680.7

2009 200 826.85 3,100.00 190.00 479.8

2010 203 898.14 6,000.00 265.11 773.8

2011 209 760.60 4,300.00 100.00 520.5

2012 132 722.11 2,900.00 1.00 416.1

2013 196 813.72 3,600.00 300.00 525.4

2014 164 989.78 9,255.47 300.00 1,149.6

2015 146 1,163.24 16,666.70 200.00 1,593.8

2016 61 944.64 6,555.00 0.32 852.8

Next, price trends were analyzed for a specific asphalt item (item No. 40603310). Figure 44

shows the price trends for this asphalt item. The item did not appear in the data in 2006. One 

noticeable price spike is seen in 2015 in the graph. Table 42 shows that both the average price 

and the maximum bid price were highest in 2015 ($222.96 and $6,600.00 respectively). 

Source: FHWA. 

Figure 44. Graph. Asphalt bid price trends—Illinois 2006–2016. 
62 

Table 42. Asphalt price data—Illinois.

Year

Data 

Points

Average 

Price 

(Dollars)

Maximum 

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 196 101.97 562.00 42.64 70.6

2008 176 132.76 560.00 0.01 89.6

2009 306 121.38 4,000.00 27.60 238.8

2010 309 120.04 800.00 49.97 91.6

2011 181 124.48 490.00 15.40 75.8

2012 71 116.33 500.00 11.00 66.3

2013 105 110.90 312.90 54.03 52.1

2014 128 109.56 515.00 56.25 64.4

2015 75 222.96 6,600.00 3.65 748.5

2016 45 126.52 980.00 48.75 138.5

—No data.

Lastly, price trends for a specific aggregate item (item No. 40200800) were investigated. 

Figure 45 shows moderate fluctuations across the analysis period with a general increase in 

prices toward the end of the period. The standard deviations shown in table 43 are small, with the 

largest occurring in 2014 due to the higher maximum bid price of $700.00 per ton. 

Source: FHWA. 

Figure 45. Graph. Aggregate bid price trends—Illinois 2006–2016. 
63 

Table 43. Aggregate price data—Illinois.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 139 28.11 117.36 0.01 18.2

2007 121 35.82 285.75 4.20 33.6

2008 122 33.92 203.00 2.20 25.2

2009 143 50.14 235.00 0.01 43.2

2010 169 49.21 379.04 0.01 46.6

2011 104 47.27 305.23 14.00 47.7

2012 74 41.15 145.26 15.00 28.4

2013 107 34.73 137.45 12.00 19.7

2014 127 59.26 700.00 11.59 93.0

2015 82 46.78 234.61 13.93 33.4

2016 54 58.03 308.12 13.00 51.8

Indiana

A total of 272 unique firms were awarded 3,192 projects containing materials of interest in

2006-2016. A major firm operating in the State purchased aggregate suppliers in several other 

States during the analysis period. This activity did not show any pricing effects on aggregate in 

projects in Indiana. Aggregate backfill bid prices were generally within $50.00 of the unit price 

reported by Indiana DOT and well below the high prices published. Similar trends were observed 

for other materials, including asphalt and concrete products. 

Most of the State’s asphalt and concrete suppliers are based near the Indianapolis, IN, area with 

other locations in close proximity to major routes, including I–65 and I–69. Aggregate supplier 

locations were observed to be more widespread, with one major firm operating in the State

owning several locations. From fiscal year 2005 to fiscal year 2015, a large number of projects 

were let and completed in the State, including roadway construction and reconstruction, bridge 

rehabilitation and replacement, and highway safety improvement projects. 

Figure 46, figure 47, and figure 48 show the bid price trends for three materials: concrete 

superstructure (item No. 704-51002), asphalt material (item No. 406-05520), and compacted 

aggregate No. 53 base (item No. 301-07448), respectively. Below each figure, additional pricing 

data to support the graphical information are provided (table 44, table 45, and table 46, 

respectively).

Figure 46 and table 44 show the price trends for a concrete item in Indiana (item No.

704-51002). From 2012 to the end of the analysis period, average prices increased, with the 

highest identified in 2015 and 2016. 
64 

Source: FHWA. 

Figure 46. Graph. Concrete bid price trends—Indiana 2006–2016. 

Table 44. Concrete price data—Indiana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 63 629.23 3,000.00 300.00 368.9

2007 59 678.82 3,500.00 329.12 563.7

2008 66 706.06 2,100.00 346.40 320.2

2009 89 561.68 2,000.00 275.60 235.4

2010 81 685.09 8,000.00 1.00 861.1

2011 73 618.96 5,400.00 276.90 613.6

2012 55 567.72 1,430.00 317.00 187.1

2013 69 685.15 1,600.00 341.55 248.9

2014 88 864.77 4,500.00 400.00 610.1

2015 90 1,088.60 5,000.00 435.00 717.0

2016 25 1,444.80 5,000.00 475.00 1,016.9

Next, asphalt prices were analyzed for Indiana during the analysis period. Figure 47 shows the 

average prices of a specific asphalt item (item No. 406-05520). Prices remained relatively 

consistent and steadily increased over time, except for one price dip in 2011. Average price as 

well as maximum bid price were lower in 2011. However, the minimum prices for every year 

were penny bids, as shown in table 45. 
65 

Source: FHWA. 

Figure 47. Graph. Asphalt bid price trends—Indiana 2006–2016. 

Table 45. Asphalt price data—Indiana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 242 298.82 3,000.00 0.01 313.6

2007 218 344.57 4,000.00 0.01 340.0

2008 273 387.33 2,500.00 0.01 305.4

2009 493 398.08 3,000.00 0.01 357.2

2010 317 407.66 3,800.00 0.01 415.1

2011 194 371.74 1,347.96 0.01 258.2

2012 181 428.89 5,750.00 0.01 598.2

2013 217 472.19 5,000.00 0.01 526.8

2014 235 497.47 5,800.00 0.01 537.9

2015 236 483.84 5,000.00 0.01 511.7

2016 71 460.79 1,267.00 0.01 265.4

Finally, price trends for a specific aggregate item (item No. 301-07448) were analyzed. 

Figure 48 and table 46 show the price fluctuations for this item across the analysis period. Prices 

did not vary greatly but increased after 2013. Again, penny and dollar bids were identified, 

which impact average prices.
66 

Source: FHWA. 

Figure 48. Graph. Aggregate bid price trends—Indiana 2006–2016. 

Table 46. Aggregate price data—Indiana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 170 23.89 100.00 3.40 14.5

2007 164 22.29 60.00 0.01 9.2

2008 182 22.50 75.00 0.01 11.4

2009 262 24.42 600.00 0.20 38.8

2010 213 23.49 198.36 0.01 21.4

2011 163 22.53 167.83 1.00 15.7

2012 135 26.51 479.58 0.01 41.4

2013 177 23.38 117.45 1.00 14.6

2014 203 29.56 500.00 0.22 38.7

2015 220 33.43 266.18 0.32 27.4

2016 65 36.72 245.00 11.00 37.4

Michigan

Some consolidation activity in the asphalt industry resulted in an almost 18-percent price 

increase in the Kalamazoo, MI, area within the 2-yr period following the merger in the early 

2000s (Duplantis 2010). Any lasting pricing effects can be largely attributed to the geographic 

effects of this merger. After the aforementioned merger, one firm owned and/or operated six 

asphalt plants in five different counties located in southern Michigan. Thus, projects in other 

areas of the State using asphalt products from this firm saw higher project costs due to material 

transportation costs. 

Analysis of the data for Michigan bids during the 2006–2016 period did not reveal any 

significant pricing anomalies for materials of interest. Michigan DOT (MDOT) also provided 

weighted average item pricing reports, which contained item identifications, regions, year, and 
67 

quarter used; how many contracts the item appeared in; average quantities in each contract; 

average awarded bid prices; and average prices of the lowest three bidders. For items such as 

HMA, asphaltic material, concrete, and aggregates, the unit price data provided by MDOT 

revealed that most bids included prices that were within a small range of the reported unit prices. 

Most of the State’s asphalt plants are located in the eastern part of State. Therefore,

transportation costs for projects further west or in the northern areas of the State are generally 

higher, resulting in higher overall project costs. Projects with reduced timelines also see 

increases in total costs. Most of the State’s aggregate sources are in the southern half of the State

but are spread relatively evenly from west to east. Concrete plants are fairly evenly distributed 

across the whole State, with one location in the far north. 

Figure 49, figure 50, and figure 51 show the bid price trends for three materials: substructure 

concrete (item No. 7067010), HMA 13A (item No. 5020034), and aggregate base (item No.

3020001), respectively. Below each figure, additional pricing data to support the graphical 

information are provided (table 47, table 48, and table 49, respectively).

Figure 49 and table 47 show the limited data available for a concrete item (item No. 7067010) in 

Michigan. This item did not appear in the data in 2008–2010 or 2013–2016. For the years it was 

identified in the data, the prices were varied, but no anomalies were identified. 

Source: FHWA. 

Figure 49. Graph. Concrete bid price trends—Michigan 2006–2016. 
68 

Table 47. Concrete price data—Michigan.

Year

Data 

Points

Average 

Price 

(Dollars)

Maximum 

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 105 452.65 2,000.00 0.01 293.7

2007 14 397.39 1,325.00 50.00 295.8

2008 0 — — — —

2009 0 — — — —

2010 0 — — — —

2011 3 460.00 530.00 350.00 78.7

2012 8 370.00 800.00 100.00 212.3

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Next, price trends for an asphalt item (item No. 5020034) were analyzed. Figure 50 shows the 

price trends for this item. The item did not appear in the data after 2012. For the years it was 

analyzed, prices were relatively consistent, which is reflected in the standard deviations shown in 

table 48. 

Source: FHWA. 

Figure 50. Graph. Asphalt bid price trends—Michigan 2006–2016. 
69 

Table 48. Asphalt price data—Michigan.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 230 58.64 535.00 0.01 40.9

2007 236 58.33 186.00 35.93 24.0

2008 151 67.10 232.30 35.82 26.5

2009 158 66.32 350.00 36.82 36.3

2010 209 61.26 227.20 45.25 18.3

2011 112 64.32 250.00 45.30 26.6

2012 1 62.06 — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, price trends for an aggregate item (item No. 3020001) were analyzed. Figure 51 and 

table 49 show the increasing trend in average price for this aggregate item across the analysis 

period. Prices had very little variation, despite some penny bids in 2008, 2012, 2013, and 2014. 

Source: FHWA. 

Figure 51. Graph. Aggregate bid price trends—Michigan 2006–2016. 
70 

Table 49. Aggregate price data—Michigan.

Year

Data 

Points

Average 

Price 

(Dollars)

Maximum 

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 106 16.21 85.00 5.25 9.8

2007 125 14.49 50.00 5.00 7.9

2008 80 15.00 54.00 0.01 8.8

2009 87 16.88 100.00 5.00 15.2

2010 100 16.30 65.00 5.50 9.7

2011 64 18.95 300.00 6.00 35.9

2012 68 17.05 100.00 0.01 12.8

2013 93 19.00 280.00 0.01 28.6

2014 80 19.73 65.00 0.01 12.8

2015 66 22.27 87.00 9.00 13.2

2016 71 21.23 65.00 1.00 10.6

Minnesota

Minnesota’s aggregate, asphalt, and concrete suppliers are all largely concentrated near the twin 

cities (Minneapolis and St. Paul). A total of approximately 2,000 projects took place during the 

analysis period of 2006–2016. Examining the price trends of key items revealed relatively stable 

average bid prices for asphalt and aggregate throughout the 10-yr period. The average bid prices 

of concrete materials showed a gradual increase in price, reaching an all-time high in 2016, with

the lowest price occurring in 2006. 

Analysis of the bid prices of key materials also included comparison with unit price data 

provided by Minnesota DOT (MnDOT). These data included items numbers and descriptions, 

units, quantities, dollars, average prices, and the number of contracts utilizing the item in that 

particular year. Prices of items such as aggregate, concrete, and asphalt during the 10-yr period 

were found to be consistent with unit prices provided by MnDOT. Minnesota’s Construction 

Cost Index (CCI) revealed annual price trends for surfacing began to rise steadily starting in

2004, which may explain the rising prices of concrete materials in the bids. Concrete surfacing 

also showed a gradual cost index increase from 1986 to 2009. 

Figure 52, figure 53, and figure 54 show the bid price trends for three materials: structural 

concrete (3Y43) (item No. 2411501/03243), asphalt cement (item No. 2350609/00020), and 

aggregate base class 5 (item No. 2211501/00050), respectively. Below each figure, additional 

pricing data to support the graphical information are provided (table 50, table 51, and table 52, 

respectively).

Figure 52 shows the price trends for a specific concrete item in Minnesota (item No.

2411501/03243). Three spikes are visible in the graph in 2008, 2011, and 2014. Table 50 shows 

the higher average prices, as well as the higher maximum prices for these years, which can 

impact the averages.
71 

Source: FHWA. 

Figure 52. Graph. Concrete bid price trends—Minnesota 2006–2016. 

Table 50. Concrete price data—Minnesota.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 3 470.00 575.00 375.00 81.9

2007 7 458.57 735.00 350.00 128.2

2008 9 738.02 2,950.00 324.94 784.8

2009 9 478.84 714.75 307.00 135.9

2010 9 770.20 1,700.00 125.00 436.5

2011 5 1,151.30 2,500.00 375.00 833.6

2012 5 663.32 1,400.00 270.00 392.7

2013 9 644.98 1,500.00 392.84 337.2

2014 6 1,166.83 3,350.00 355.00 1,033.8

2015 8 759.14 1,510.00 240.00 409.4

2016 0 — — — —

—No data.

Next, prices for a specific asphalt item (item No. 2350609/00020) were analyzed. Figure 53 and 

table 51 show the price information for this item, which did not appear in the data after 2013. For 

the years the item was available for analysis, prices increased, and the variation in price 

remained low to moderate.
72 

Source: FHWA. 

Figure 53. Graph. Asphalt bid price trends—Minnesota 2006–2016. 

Table 51. Asphalt price data—Minnesota.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 1 275.00 — — —

2007 2 392.50 410.00 375.00 17.5

2008 2 488.14 558.53 417.75 70.4

2009 4 474.75 500.00 449.00 20.9

2010 5 537.60 575.00 500.00 30.1

2011 1 559.15 — — —

2012 2 703.65 727.31 680.00 23.6

2013 3 607.00 626.00 585.00 16.9

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, prices for an aggregate item (item No. 2211501/00050) were analyzed. Figure 54 shows 

moderate changes to the average price across the analysis period, with an increase toward the end 

of the period. Variation was low, as reflected in the standard deviation values shown in table 52. 
73 

Source: FHWA. 

Figure 54. Graph. Aggregate bid price trends—Minnesota 2006–2016. 

Table 52. Aggregate price data—Minnesota.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 11 18.09 35.38 8.70 7.6

2007 12 15.88 36.00 6.50 9.9

2008 9 28.55 76.00 11.00 18.1

2009 11 19.13 61.50 9.40 14.4

2010 17 22.21 75.00 9.25 16.5

2011 8 24.23 50.00 9.50 13.1

2012 6 22.94 40.00 14.00 9.2

2013 9 23.27 48.26 13.00 11.1

2014 6 17.03 25.11 11.60 4.2

2015 4 25.77 37.00 16.00 7.7

2016 2 37.00 50.00 24.00 13.0

Missouri

Missouri requires a minimum of 40 percent of the work be performed by the prime contractor. 

This percentage can be adjusted to the minimum FHWA amount of 30 percent, if required. 

Missouri DOT (MoDOT) chooses to impose the higher requirement for its prime contractors. 

Kansas City, St. Louis, and Springfield, MO, are large urban areas that are considered separately 

due to some unique provisions such as night paving. Obtaining aggregate in these urban areas 

has become difficult because older quarries in the urban areas of the State are drying up as a 

result of large commercial projects. Since 2010, MoDOT has seen a major national aggregate 

producer sell most of its presence to a local company, and many quarries were consolidated as a 

result. This new firm also specializes in paving. A few quarries are now owned individually, but 

several contractors own groups of quarries. However, MoDOT monitors the competition. 
74 

Regarding trends in these mergers and bid characteristics (including number of bidders and 

changes in prices), the number of bidders is tracked as a performance measure. 

Analysis of the bid prices of key materials also included comparison with unit price data 

provided by MoDOT. These data included numbers and descriptions, units, quantities, dollars, 

average prices, and the number of contracts utilizing the item in that particular year. Prices of 

items such as aggregate, concrete, and asphalt during the 10-yr period were found to be 

consistent with unit prices provided by MoDOT.

Figure 55, figure 56, and figure 57 show the bid price trends for three materials: base concrete

(item No. 9029100), asphaltic concrete mixture PG 64-22 (SP125C mix) (item No. 4030101), 

and type 5 aggregate for base (4 inches thick) (item No. 3040504), respectively. Below each 

figure, additional pricing data to support the graphical information are provided (table 53, 

table 54, and table 55, respectively).

Figure 55 shows the price trends for a specific concrete item (item No. 9029100) in Missouri 

during the analysis period. The item did not appear in the data in 2006–2008. For the years it was 

available, prices fluctuated moderately and climbed toward the end of the analysis period. This 

activity is reflected in larger standard deviations shown in table 53. 

Source: FHWA. 

Figure 55. Graph. Concrete bid price trends—Missouri 2006–2016. 
75 

Table 53. Concrete price data—Missouri. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 0 — — — —

2009 37 1,199.72 3,480.00 455.05 517.9

2010 37 1,149.81 3,050.00 497.28 588.6

2011 35 1,303.73 2,797.00 670.00 545.1

2012 29 1,548.77 5,000.00 805.00 1,088.3

2013 35 1,292.93 2,600.00 175.00 545.2

2014 45 1,680.41 12,451.60 600.00 1,826.8

2015 31 1,379.41 3,125.85 1.00 642.6

2016 17 1,676.55 4,300.00 689.00 814.9

—No data.

Next, a specific asphalt item (item No. 4030101) was analyzed. Figure 56 shows the price 

variation for this item during the analysis period. As can be seen in the graph and in table 54, the 

item was not in the data in 2006, 2007, or 2008. During the years it was available for analysis, 

average prices were higher in 2012 and 2013 ($93.60 per ton and $89.89 per ton, respectively). 

The maximum observed bid price occurred in 2013. No apparent cause for this higher price was 

identified.

Source: FHWA. 

Figure 56. Graph. Asphalt bid price trends—Missouri 2006–2016. 
76 

Table 54. Asphalt price data—Missouri. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 0 — — — —

2009 23 89.61 240.00 48.56 56.9

2010 20 79.77 237.10 26.25 58.5

2011 3 60.03 74.90 52.20 10.5

2012 10 93.60 160.00 49.93 37.4

2013 16 89.89 440.00 47.70 91.9

2014 5 60.74 84.95 52.07 12.2

2015 6 65.39 79.00 50.00 9.2

2016 16 59.47 105.00 39.31 20.1

—No data.

Finally, an aggregate item (item No. 3040504) was investigated. Figure 57 shows the price 

trends for this item during the analysis period. The item was not used before 2009. From 2009 

through to the end of the analysis period, the prices rose steadily and overall had low deviation, 

as reflected in table 55. 

Source: FHWA. 

SY = square yard 4 inches thick. 

Figure 57. Graph. Aggregate bid price trends—Missouri 2006–2016. 
77 

Table 55. Aggregate price data—Missouri. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 0 — — — —

2009 62 6.86 26.30 2.15 4.0

2010 36 7.40 30.00 2.65 5.4

2011 43 7.97 35.00 3.65 5.3

2012 43 6.45 20.00 2.90 3.5

2013 77 8.01 65.07 2.85 8.1

2014 73 9.11 32.70 1.50 6.2

2015 48 13.01 200.00 3.80 28.3

2016 32 13.89 127.95 3.50 23.1

—No data.

Ohio

Most of Ohio’s asphalt suppliers are located in the Cincinnati, OH, area, with some located in the 

State’s northeast near Pennsylvania. The State’s concrete suppliers are largely located near 

Columbus, OH, and the aggregate suppliers are relatively evenly distributed throughout the 

State. Competition in the State is relatively varied, and no initial concerns regarding pricing of 

materials due to consolidation activity were made known. Prices of aggregate, concrete, and 

asphalt products across the analysis period of 2006–2016 showed no abnormal price fluctuations. 

Figure 58, figure 59, and figure 60 show the bid price trends for three materials: class S concrete 

superstructure (item No. 511E34400), asphalt concrete base PG 64-22 (item No. 301E46000), 

and aggregate base (item No. 304E20000), respectively. Below each figure, additional pricing 

data to support the graphical information are provided (table 56, table 57, and table 58, 

respectively).

Figure 58 and table 56 show the average prices for a concrete item (item No. 511E34400) in 

Ohio across the analysis period. There was a large range between minimum and maximum price, 

with a very high maximum price of $10,000.00 per cubic yard (CY) in 2008. The item did not 

appear in the data after 2013.
78 

Source: FHWA. 

Figure 58. Graph. Concrete bid price trends—Ohio 2006–2016. 

Table 56. Concrete price data—Ohio.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 11 835.81 2,425.00 284.00 596.6

2007 15 1,447.72 4,000.00 600.00 832.7

2008 13 1,908.62 10,000.00 640.00 2,464.8

2009 17 796.52 1,355.82 399.40 248.5

2010 25 1,433.06 5,050.00 495.00 913.4

2011 23 1,191.06 3,400.00 230.00 801.7

2012 14 1,052.75 2,500.00 400.00 727.9

2013 16 1,527.56 4,081.00 450.00 1,039.5

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Figure 59 shows the price trends for an asphalt item (item No. 301E46000) in Ohio during the 

analysis period. Prices rose across the period with moderate variation, as shown in figure 59 and 

table 57. No significant anomalies were identified.
79 

Source: FHWA. 

Figure 59. Graph. Asphalt bid price trends—Ohio 2006–2016. 

Table 57. Asphalt price data—Ohio.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 199 157.17 1,250.00 59.00 121.5

2007 190 154.35 750.00 50.00 93.8

2008 213 177.69 1,000.00 78.30 114.3

2009 195 198.05 650.00 65.00 110.5

2010 224 183.02 800.00 82.00 107.5

2011 309 231.47 1,473.00 40.00 150.1

2012 186 213.59 875.00 80.00 103.1

2013 243 212.98 1,100.00 65.00 130.2

2014 220 215.27 1,000.00 63.00 109.1

2015 260 216.70 717.00 75.00 101.2

2016 152 238.19 1,115.00 3.50 149.7

Finally, prices for an aggregate item (item No. 304E20000) were analyzed. Like asphalt, prices 

for this aggregate item increased over time, as shown in figure 60 and table 58. Variation in price 

was low throughout the analysis period, and no price anomalies were identified.
80 

Source: FHWA. 

Figure 60. Graph. Aggregate bid price trends—Ohio 2006–2016. 

Table 58. Aggregate price data—Ohio.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 256 49.13 300.00 20.00 32.1

2007 251 46.47 200.00 8.00 20.9

2008 264 52.26 500.00 15.00 40.5

2009 253 51.71 200.00 15.00 27.1

2010 293 52.73 725.00 1.00 47.5

2011 373 64.16 300.00 5.00 37.8

2012 250 63.93 1,061.71 15.00 74.4

2013 321 61.00 425.00 8.00 37.3

2014 310 61.99 300.00 22.00 28.1

2015 347 70.89 350.00 20.00 38.6

2016 205 77.96 450.00 27.60 44.4

Wisconsin 

Wisconsin DOT (WisDOT) was contacted via a combination of phone and email regarding 

perceptions and anecdotal evidence surrounding the pricing effects of M&A activity. Beyond 

this anecdotal evidence, the research team analyzed data for every quarter in 2006–2015 and for 

the first three quarters of 2016. Identifying contractor and pricing data for Wisconsin was 

relatively simple, as the project numbers were sequential, based on date. WisDOT was also very 

responsive to requests for additional data, including historical unit price data for the analysis 

period (2006−2016). The number of contractors included in the dataset ranged from 56 to 115 

per year during this period. 

While the unit price data provided were exhaustive, identifying contractors who used items of 

interest during the analysis period to compare with unit price data for those years was 
81 

time-consuming and challenging. Trends of total project prices and bid item number prices in 

comparison to relevant unit prices yielded no significant price deviations attributable to 

identified merger or acquisition activity. Many average bid item number prices across all years 

were higher than unit prices. However, bid prices for singular firms across the analysis period 

were also compared with unit prices; similar results were found. An individual firm’s bid item 

number prices, as well as average bid item number prices across all firms using that item, were 

found to be higher than the unit prices reported by WisDOT. 

A majority of projects awarded in Wisconsin took place in the northwest and southwest regions 

of the State. Additionally, these regions saw the greatest disparity in the number of firms 

awarded bids compared with the northeast and north central regions. WisDOT reported no 

concerns when asked about M&A activity, as well as how these activities affected bid prices, bid 

quantity, and project costs. Similarly, Wisconsin did not report altering contract language or 

statutes to address or minimize any merger or acquisition activity effects on pricing.

Figure 61, figure 62, and figure 63 show the bid price trends for three materials: concrete 

pavement 9 inches (item No. 415.009), asphaltic material PG 64-28 (item No. 455.012), and base 

aggregate dense 11⁄4 inches (item No. 305.012), respectively. Below each figure, additional 

pricing data to support the graphical information are provided (table 59, table 60, and table 61, 

respectively).

Figure 61 and table 59 show the price trends for a concrete item (item No. 415.009) in Wisconsin 

during the analysis period. Prices remained consistent with little variation, despite two slightly 

higher average and maximum prices in 2013 and 2014. 

Source: FHWA. 

Figure 61. Graph. Concrete bid price trends—Wisconsin 2006–2016. 
82 

Table 59. Concrete price data—Wisconsin.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 35 38.61 110.00 17.20 21.0

2007 26 34.98 72.00 17.95 14.8

2008 29 39.38 81.50 24.54 13.2

2009 37 37.76 75.00 22.85 11.0

2010 41 34.83 90.00 18.00 13.2

2011 24 34.71 59.30 21.35 10.0

2012 14 43.68 95.00 26.69 16.4

2013 13 54.83 226.92 29.51 50.1

2014 31 58.50 400.00 30.00 64.4

2015 19 45.00 81.00 33.10 10.8

2016 15 45.10 72.65 29.01 11.8

Figure 62 shows the price trend for an asphalt item (item No. 455.012) in Wisconsin. Observed 

prices of this asphalt item decreased over time. Several low minimum prices ($1.20 and $1.00) 

were observed, which impacted the average prices and the deviation, as shown in table 60. 

Source: FHWA. 

Figure 62. Graph. Asphalt bid price trends—Wisconsin 2006–2016. 
83 

Table 60. Asphalt price data—Wisconsin.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 54 375.22 615.00 100.00 145.4

2007 51 408.44 1,000.00 100.00 187.3

2008 52 496.98 1,033.00 120.00 272.6

2009 57 416.69 4,150.00 1.20 545.9

2010 81 289.59 890.00 15.00 231.2

2011 47 206.61 750.00 1.00 163.1

2012 29 270.45 1,800.00 15.00 338.8

2013 35 290.85 1,225.00 15.00 293.7

2014 27 185.83 770.00 10.00 223.9

2015 56 158.70 685.00 1.00 224.4

2016 7 119.57 475.00 1.00 154.9

Lastly, figure 63 and table 61 show the price trend for an aggregate item (item No. 305.012) in 

Wisconsin. Prices for this aggregate item remained consistent throughout the analysis period, 

except for a high average and maximum price in 2015. In 2015, the average price was $17.88 per 

ton-gallon and the maximum price was $423.70 per ton-gallon. 

Source: FHWA. 

Figure 63. Graph. Aggregate bid price trends—Wisconsin 2006–2016. 
84 

Table 61. Aggregate price data—Wisconsin.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 210 10.15 59.00 4.78 4.5

2007 218 10.37 85.00 4.28 6.9

2008 223 11.27 38.00 6.11 4.1

2009 262 11.76 51.10 4.67 5.0

2010 293 11.73 50.00 3.30 5.6

2011 211 11.35 49.00 5.73 4.7

2012 129 13.08 59.36 5.20 7.7

2013 133 12.52 45.00 0.01 6.3

2014 186 15.04 75.00 0.01 8.5

2015 209 17.88 423.70 0.01 30.9

2016 165 15.24 122.55 0.01 10.0

AASHTO REGION 4

This section presents States located in AASHTO region 4: Arizona, California, Colorado, Idaho, 

Montana, Nebraska, Nevada, New Mexico, Oklahoma, Oregon, and Utah. 

Arizona

Research on data and information from Arizona DOT (ADOT) revealed that they were not 

informed of much M&A activity during the analysis period of 2006–2016. Neither contractors 

nor suppliers brought any issues or concerns regarding consolidation activities to the attention of 

ADOT for corrective action or legislation. While personnel were observed to move between 

companies, and some contractors suffered due to the economic recession, the construction 

industry and particularly the concrete pipe industry were fairly stable.

Within the materials of interest, Arizona saw the most acquisition activity for aggregates, with 

companies purchasing sources or exclusive rights to control supply in certain geographic areas. 

However, none of this activity caused ADOT to investigate it further. Limited aggregate sources 

in the north central district of the State near Flagstaff, AZ, as well as disruptions in aggregate 

availability resulted due to issues pertaining to the lease agreements with the Bureau of Land 

Management regarding selling aggregate. Despite these supply disruptions, no direct effects on 

pricing were observed. 

Data revealed a total of 1,090 projects during the analysis period of 2006–2016. Unit price data 

for bid item numbers of interest were also made available on ADOT’s website. These prices 

were used to analyze how trends in bid item number prices fluctuated over the years compared 

with State-reported unit prices. As was common in most States, some drops in prices and number 

of projects were seen during the 18-mo economic recession from 2008 moving into 2010. 

Figure 64, figure 65, and figure 66 show the bid price trends for three materials: structural 

concrete (class S) (item No. 6010002), asphaltic concrete (structural) (item No. 4090003), and 

aggregate base (item No. 3030022), respectively. Below each figure, additional pricing data to 

support the graphical information are provided (table 62, table 63, and table 64, respectively).
85 

Figure 64 and table 62 show the price trends for a specific concrete item in Arizona (item 

No. 6010002). While moderate price fluctuations were observed with a general drop in prices 

between 2008 and 2011, no price anomalies were identified. 

Source: FHWA. 

Figure 64. Graph. Concrete bid price trends—Arizona 2006–2016. 

Table 62. Concrete price data—Arizona.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 27 662.89 1,300.00 200.00 232.1

2007 103 453.96 1,500.00 190.00 211.0

2008 103 480.26 1,300.00 230.00 165.1

2009 60 327.69 650.00 165.00 112.7

2010 166 332.19 900.00 142.00 111.2

2011 35 341.69 610.00 155.00 134.2

2012 28 398.81 2,500.00 155.00 430.2

2013 48 503.89 2,000.00 210.00 268.6

2014 36 519.81 1,200.00 203.00 204.6

2015 46 432.89 1,800.00 200.00 265.1

2016 15 525.67 700.00 370.00 109.5

Next, the price trends for a specific asphalt item (item No. 4090003) were analyzed. Figure 65

shows the price variations for this asphalt item during the analysis period. Three spikes are 

apparent in the graph in 2008, 2011, and 2015. Table 63 shows higher average bid prices for 

these 3 yr, as well as higher maximum bid prices and higher standard deviation values. 
86 

Source: FHWA. 

Figure 65. Graph. Asphalt bid price trends—Arizona 2006–2016. 

Table 63. Asphalt price data—Arizona.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 16 126.50 500.00 35.00 107.2

2007 35 150.39 619.00 35.00 128.1

2008 20 182.46 1,200.00 54.30 238.9

2009 32 103.00 200.00 47.92 36.4

2010 51 114.19 320.00 60.00 64.7

2011 27 169.39 600.00 59.00 139.1

2012 22 149.23 460.00 60.00 89.9

2013 21 121.40 373.00 61.00 66.0

2014 40 143.84 327.00 75.00 66.2

2015 51 164.39 730.00 55.00 149.3

2016 29 135.13 325.00 55.00 67.9

Lastly, a specific aggregate item (item No. 3030022) was investigated. Figure 66 and table 64

show the price variation for this item throughout the analysis period. Prices varied, but deviation 

was moderate, and no anomalies were identified in the data.
87 

Source: FHWA. 

Figure 66. Graph. Aggregate bid price trends—Arizona 2006–2016. 

Table 64. Aggregate price data—Arizona.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 24 92.84 313.00 31.00 87.6

2007 56 50.88 159.00 20.90 30.1

2008 36 54.23 200.00 14.00 39.4

2009 49 49.49 381.00 14.27 66.7

2010 70 42.98 140.00 9.00 28.9

2011 44 66.90 480.00 18.60 75.2

2012 33 53.58 215.00 18.60 36.7

2013 24 57.13 228.00 20.25 51.9

2014 58 74.20 250.00 14.00 58.3

2015 64 69.79 421.00 23.00 59.4

2016 41 64.99 275.00 25.00 49.5

California

In 2014, a major multistate firm purchased a Texas-based supplier of aggregates, cement, and 

concrete products, which affected the market in both Texas and California. In 2015, another 

major firm purchased a ready-mix concrete supplier in the San Francisco, CA, area. Another 

multistate firm controlling large market shares in California as well as Florida purchased a total 

of four aggregates companies, including some in the San Francisco and San Diego, CA, areas in 

2014. 

A total of 5,542 projects took place in California during the analysis period of 2006–2016. Due 

to the significant activity in the San Francisco, CA, area (district 4 in the State) in these years, 

prices of ready-mix concrete and aggregates were investigated to assess any pricing effects due 
88 

to the acquisition activity. Overall, average prices of aggregates were lower within San Francisco 

County than in other counties in the State, likely due to availability. After the acquisitions in 

2014, only one project used aggregate. This project did list a higher price for the aggregate 

materials. However, the higher price was within a $50.00 range of the State’s reported adjusted 

unit price for that year. This finding suggests that fluctuations in pricing cannot be attributed to 

the acquisition activities that occurred in 2014 and 2015. Future analyses, including additional 

years beyond these sale dates, could be conducted to better assess the impacts of this activity on 

pricing. 

Figure 67, figure 68, and figure 69 show the bid price trends for three materials: minor concrete 

(minor structure) (item No. 510502), HMA (type A) (item No. 390132), and class 2 aggregate 

base (item No. 260201), respectively. Below each figure, additional pricing data to support the 

graphical information are provided (table 65, table 66, and table 67, respectively).

Figure 67 and table 65 show the price trends for a specific concrete item in California (item 

No. 510502). Overall, prices for this concrete item were relatively high in California, with high 

maximum bid prices observed, particularly in 2006, 2008, 2013, 2014, and 2015. Further 

analysis of the bids containing these higher prices did not reveal anything abnormal. 

Source: FHWA. 

Figure 67. Graph. Concrete bid price trends—California 2006–2016. 
89 

Table 65. Concrete price data—California.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 160 2,265.89 13,979.9 191.14 1,833.9

2007 0 — — — —

2008 173 1,855.31 10,000.00 300.00 1,476.1

2009 158 1,504.87 6,280.00 196.66 1,017.8

2010 163 1,713.91 8,000.00 109.84 1,177.8

2011 143 1,780.01 6,200.00 107.28 1,084.9

2012 126 1,679.57 5,900.00 325.00 986.9

2013 112 1,882.68 10,000.00 554.25 1,482.5

2014 135 1,952.24 10,000.00 185.00 1,202.4

2015 135 2,264.21 16,000.00 250.00 1,656.9

2016 81 2,613.36 8,800.00 343.00 1,655.3

—No data.

Next, prices for an asphalt item (item No. 390132) were analyzed. Figure 68 and table 66 show 

the price variation for this item during the analysis period. Prices rose steadily after 2011 with 

one notable price spike in 2015. The average price was higher in 2015, and the spread between 

maximum and minimum price was large, resulting in a higher standard deviation. 

Source: FHWA. 

Figure 68. Graph. Asphalt bid price trends—California 2006–2016. 
90 

Table 66. Asphalt price data—California. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 137 145.98 600.00 69.00 87.2

2009 198 133.91 650.00 0.01 99.8

2010 198 148.06 1,000.00 48.00 137.9

2011 197 134.53 700.00 59.00 90.2

2012 130 161.94 800.00 50.00 122.2

2013 186 163.02 800.00 66.00 115.3

2014 184 174.23 4,000.00 61.00 307.3

2015 277 218.32 3,420.00 49.00 372.5

2016 167 175.01 1,258.00 55.00 170.8

—No data.

Lastly, prices for a specific aggregate item (item No. 260201) were analyzed. This item did not 

appear in the data for every year of the analysis period: it was only available for analysis in 2006 

and 2008–2013. For the years this item did appear in the data, prices generally decreased over 

time with moderate variation, as seen in figure 69 and table 67. 

Source: FHWA. 

Figure 69. Graph. Aggregate bid price trends—California 2006–2016. 
91 

Table 67. Aggregate price data—California.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 168 89.76 600.18 25.99 77.1

2007 0 — — — —

2008 154 79.43 500.00 22.00 65.5

2009 149 66.87 536.00 16.06 60.9

2010 135 68.43 476.00 10.70 67.7

2011 118 71.97 480.00 15 60.1

2012 41 69.18 300.00 12 64.7

2013 1 50.00 — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Colorado 

Between 83 and 130 firms were awarded bids in Colorado in 2006–2016. Throughout this

period, the State saw approximately a third of these projects with total project costs that were 

higher than average. The effects of the economic recession were felt in Colorado, which had a 

drop in employment rates and a drop in project cost during 2009–2012. A majority of projects 

occurred in Colorado’s region 1, which includes the Denver, CO, metropolitan area.

Unit price data were also available from Colorado DOT (CDOT) and were analyzed against bid 

price data supplied by FHWA. Some projects in the construction cost data book from CDOT also 

included data regarding the number of total bidders and the comparison between these prices and 

the engineering estimates. Engineering estimates were largely lacking from the initial data for 

this project provided through Oman Systems, Inc., and the inclusion of limited engineering 

estimate data for Colorado allowed for some additional analyses. For example, in 2006, 

12 projects included the low bid and other bidders with costs of 10 percent greater than the 

engineering estimate. Also, for three projects the low bid was greater than 15 percent over the 

engineering estimate.

Comparison of bid prices of items against unit price as reported for the corresponding year by 

CDOT did not yield any significant discrepancies. Items such as aggregate, asphalt, and concrete 

saw prices fluctuate generally by $50 in either direction from the unit price reported by CDOT. 

Data were also available showing item unit prices, engineering estimates, average bid, and 

awarded bid prices by item and project for each year. These data were valuable: e.g., for one 

project completed in 2011, a specific item such as HMA used in the project could be identified in 

the data. From here, the weighted average for the year of the engineering estimate ($58.83 per 

ton), average bid price ($63.22 per ton), and the awarded bid price ($56.90 per ton) could be 

observed. Most price fluctuations were not unusual and could not be linked to any significant 

consolidation activity within the State. Instead, they were likely due to the location of materials 

and the transportation costs.

Figure 70, figure 71, and figure 72 show the bid price trends for three materials: concrete class B 

(item No. 601-01000), hot bituminous pavement (asphalt) (item No. 403-00720), and aggregate 
92 

base course (class 6) (item No. 304-06000), respectively. Below each figure, additional pricing 

data to support the graphical information are provided (table 68, table 69, and table 70, 

respectively).

Figure 70 and table 68 show the price trends for a specific concrete item in Colorado (item No.

601-01000). Prices for this item varied throughout the analysis period with a notable dip in 2010 

and higher average prices in 2014 and 2015. The maximum observed bid price in 2014 and 2015 

was also higher than that for other years. 

Source: FHWA. 

Figure 70. Graph. Concrete bid price trends—Colorado 2006–2016. 

Table 68. Concrete price data—Colorado.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 12 560.91 1,764.00 150.00 424.1

2007 14 868.74 1,910.00 165.00 512.7

2008 18 764.70 1,400.00 177.81 384.0

2009 16 595.49 1,840.00 110.00 399.4

2010 13 294.52 840.00 75.00 202.9

2011 16 576.27 1,500.00 200.00 326.9

2012 11 537.68 2,020.13 100.00 528.8

2013 9 636.70 1,146.48 321.88 280.1

2014 15 1,458.61 8,343.45 125.00 1,916.6

2015 10 1,343.97 4,350.00 300.00 1,232.0

2016 6 999.11 1,975.00 360.00 543.0

Next, the price trends for an asphalt item (item No. 403-00720) were analyzed. Figure 71 and 

table 69 show a general increase in price over time with two lower price averages in 2009 and 

2013. Several minimum bid prices were significantly lower than the other bids, resulting in 

larger deviations.
93 

Source: FHWA. 

Figure 71. Graph. Asphalt bid price trends—Colorado 2006–2016. 

Table 69. Asphalt price data—Colorado.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 93 185.42 695.00 60.35 121.9

2007 71 191.04 1,521.00 10.00 217.1

2008 79 177.64 770.00 69.70 112.2

2009 71 141.94 412.00 20.00 67.2

2010 76 153.29 800.00 10.00 112.6

2011 76 184.90 1,500.00 84.00 171.1

2012 51 187.67 710.00 84.47 115.5

2013 66 167.67 536.75 50.00 84.7

2014 70 205.21 625.00 105.40 95.7

2015 61 210.60 550.00 92.00 80.6

2016 29 258.83 750.00 117.00 137.2

Finally, prices for an aggregate item (item No. 304-06000) were analyzed. Figure 72 and table 70

show the price changes for this item throughout the analysis period. Higher prices were observed 

in 2007 and 2012 with increasing prices after 2014. In 2007, the average price and the maximum 

price were both higher than for surrounding years. In 2012, the average price and maximum 

price were also higher than for surrounding years, but the minimum observed bid price remained 

consistent. Prices then rose in 2015 and 2016 with higher average prices and higher maximum 

bid prices. The standard deviation was highest in 2007, 2012, and 2016. The number of 

observations was lowest in 2016, likely because the data did not contain all of 2016. 
94 

Source: FHWA. 

Figure 72. Graph. Aggregate bid price trends—Colorado 2006–2016. 

Table 70. Aggregate price data—Colorado.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 35 28.29 110.00 12.00 18.8

2007 31 41.77 333.33 8.71 56.2

2008 35 25.16 57.31 13.00 9.3

2009 29 23.55 70.00 10.00 13.4

2010 35 21.30 50.00 0.12 10.2

2011 35 24.62 80.00 11.83 12.5

2012 24 32.97 180.00 12.10 39.4

2013 33 24.24 65.00 5.00 11.6

2014 34 26.17 54.00 10.00 10.9

2015 37 39.29 166.40 15.61 27.0

2016 17 54.73 137.00 14.75 38.2

Idaho

During the analysis period of 2006–2016, a total of 112 unique firms were awarded a total of 

597 projects utilizing the material items of interest. The Oman Systems, Inc., data were used to 

analyze any consolidation activity of interest, bid item number pricing trends, and material 

supplier locations in the State. Aggregate, concrete, and asphalt suppliers in the State are 

generally located in the south near Idaho Falls, Twin Falls, and Boise, ID. Also, availability of 

these materials in the north near Spokane, WA, is limited. 

Average bid item number prices of asphalt remained relatively consistent from year to year, 

except for a slight price drop in 2011–2013 and again in 2016. Concrete prices also saw a slight 

drop in 2016; these drops are likely due to the exclusion of the fourth-quarter data in 2016, as it 

was not yet available. Besides 2016, average bid prices for structural concrete were also 
95 

relatively stable, showing small fluctuations in most years. Bid price data were then compared 

against unit price data available from Idaho Transportation Department. Unit price data included 

item numbers, quantities, unit prices, price averages from the three lowest bids, and associated 

project numbers. Prices of materials were consistent with unit prices reported by ITD. The higher 

prices of structural concrete in 2007 and 2008 were also investigated and found to be similar to 

unit prices for concrete in that year.

Figure 73, figure 74, and figure 75 show the bid price trends for three materials: concrete class

40-B schedule No. 1 (item No. 502-140A), PG 64-34 asphalt cement for Superpave HMA (item 

No. S405-35A), and 19-mm aggregate TY B for base (item No. 303-022A), respectively. Below 

each figure, additional pricing data to support the graphical information are provided (table 71, 

table 72, and table 73, respectively).

Figure 73 and table 71 show the price information for a concrete item (item No. 502-140A) in 

Idaho. Average price did not vary greatly, but there were large ranges between maximum and 

minimum bid prices, resulting in larger standard deviations. 

Source: FHWA. 

Figure 73. Graph. Concrete bid price trends—Idaho 2006–2016. 
96 

Table 71. Concrete price data—Idaho. 

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 10 681.21 1,050.00 495.00 185.9

2007 7 717.86 1,030.00 401.39 228.6

2008 14 756.50 1,460.00 385.00 244.2

2009 19 575.84 1,000.00 268.00 183.5

2010 14 624.39 1,816.00 279.48 364.4

2011 6 626.17 1,611.00 1.00 494.9

2012 12 600.95 950.00 161.00 207.6

2013 13 567.93 766.35 375.00 124.3

2014 9 525.83 800.00 320.00 124.5

2015 9 607.18 1,050.00 400.00 196.9

2016 5 622.00 850.00 425.00 135.9

Next, the prices of an asphalt item (item No. S405-35) were investigated. This item did not 

appear in the data for every year of the analysis period; it was only available for 2007–2011, as 

shown in figure 74. Even in the years it was available, the number of times the item appeared 

each year was relatively low. Average prices varied, and two minimum prices of $0.01 (penny 

bids) were observed in 2009 and 2010, which impacted both the average prices and standard 

deviations in those years, as seen in table 72. 

Source: FHWA. 

Figure 74. Graph. Asphalt bid price trends—Idaho 2006–2016. 
97 

Table 72. Asphalt price data—Idaho.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 1 485.00 — — —

2008 4 882.25 1,312.00 692.00 250.3

2009 11 652.56 1,060.00 0.01 416.8

2010 7 504.29 740.00 0.01 321.1

2011 1 690.00 — — —

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, an aggregate item (item No. 303-022A) was analyzed. Prices for this item remained 

consistent with one observable high average price in 2009, as seen in the spike in figure 75. 

Table 73 shows the higher average price for this year ($52.09 per ton) and a higher maximum bid 

price ($943.22 per ton) compared with other years.

Source: FHWA. 

Figure 75. Graph. Aggregate bid price trends—Idaho 2006–2016. 
98 

Table 73. Aggregate price data—Idaho.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 22 42.31 200.00 10.00 43.0

2007 28 24.04 63.00 10.89 14.5

2008 42 28.62 165.00 10.00 27.7

2009 40 52.09 943.22 9.00 148.5

2010 59 20.67 65.00 7.59 11.6

2011 19 22.23 40.00 7.50 9.9

2012 26 16.25 36.00 7.55 6.8

2013 28 20.61 50.00 8.25 9.9

2014 29 27.55 148.50 8.00 24.8

2015 33 27.46 100.00 8.33 17.9

2016 26 19.58 55.00 8.33 9.8

Montana 

In Montana, a majority of the material suppliers of concrete, asphalt, and aggregate are 

distributed throughout the State and concentrated near major interstates, including I–94, I–15, 

and I–90. The data provided to the research team were analyzed to identify trends in pricing for 

key materials during the 10-yr period of 2006–2016. Prices of asphalt cement PG 64-28 saw a 

steady increase from 2006 until 2011; from 2010 to 2013 prices dropped slightly before 

beginning to rise again. 

Structural concrete prices remained stable throughout the analysis period; prices of concrete 

materials per CY saw several small price increases in 2008 and 2011. Lastly, crushed aggregate 

average bid prices remained consistent throughout the entire period except for one slight price 

increase in 2016. Montana DOT’s construction cost studies were investigated to identify any 

concerns or actions taken related to pricing effects of consolidation activities. While some 

concerns were voiced regarding cost estimation techniques, risk and contingency planning, and 

letting and award schedules, no pricing effects of M&A activity were outlined. 

Figure 76, figure 77, and figure 78 show the bid price trends for three materials: concrete class 

DD (item No. 551175000), asphalt cement PG 64-28 (item No. 402088000), and crushed 

aggregate course (item No. 301270000), respectively. Below each figure, additional pricing data 

to support the graphical information are provided (table 74, table 75, and table 76, respectively).

Figure 76 shows the price variation for a concrete item (item No. 551175000) in Montana during 

the analysis period. Two spikes are seen on the graph in 2008 and 2011. Table 74 shows higher 

average prices in both of these years, as well as higher maximum bid prices. Further analysis of 

these higher prices did not reveal any abnormalities. 
99 

Source: FHWA. 

Figure 76. Graph. Concrete bid price trends—Montana 2006–2016. 

Table 74. Concrete price data—Montana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 17 427.03 600.18 344.05 81.5

2007 8 508.48 688.10 363.16 113.8

2008 13 690.12 1,452.65 344.05 283.0

2009 21 489.82 840.00 185.34 149.8

2010 8 533.75 1,070.38 344.05 213.4

2011 5 718.25 1,299.74 382.27 334.6

2012 2 535.19 649.87 420.50 114.7

2013 2 482.66 605.92 359.41 123.2

2014 1 571.51 — — —

2015 1 607.94 — — —

2016 0 — — — —

—No data.

Next, an asphalt item (item No. 402088000) was analyzed. Similar to the concrete item, this item 

did not appear in the data in 2016. Prices rose in 2006–2011 before decreasing slightly through 

2015, as reflected in figure 77 and table 75. 
100 

Source: FHWA. 

Figure 77. Graph. Asphalt bid price trends—Montana 2006–2016. 

Table 75. Asphalt price data—Montana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 11 396.25 526.17 308.44 60.5

2007 8 443.63 540.10 349.27 53.3

2008 10 565.02 889.04 368.72 178.6

2009 19 602.02 680.39 544.31 48.2

2010 10 587.21 648.86 498.95 50.0

2011 3 733.39 777.00 653.17 56.8

2012 2 717.74 720.48 715.00 2.7

2013 2 713.69 747.00 680.38 33.3

2014 1 675.85 — — —

2015 1 633.00 — — —

2016 0 — — — —

—No data.

Lastly, an aggregate item (item No. 301270000) in Montana was analyzed. Prices fluctuated 

throughout the analysis period, as seen in figure 78, and no data for this item were available in 

2016. Higher prices were seen in 2007 and 2008, as well as in 2013, but overall prices were 

consistent with low variation, which is reflected in table 76. 
101 

Source: FHWA. 

Figure 78. Graph. Aggregate bid price trends—Montana 2006–2016. 

Table 76. Aggregate price data—Montana.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 33 24.85 57.34 11.47 12.3

2007 26 30.62 160.56 12.23 27.7

2008 26 29.55 64.99 11.47 16.1

2009 45 22.24 76.45 10.86 11.9

2010 20 19.23 61.16 10.80 11.0

2011 11 21.07 30.60 12.23 5.7

2012 6 20.32 35.00 12.04 7.2

2013 7 27.32 37.12 14.53 7.6

2014 3 24.73 30.23 16.82 5.7

2015 2 24.06 27.06 21.06 3.0

2016 0 — — — —

—No data.

Nebraska

Aggregate suppliers in Nebraska are largely located near Omaha, NE, and the surrounding 

metropolitan area. Concrete suppliers are generally spread throughout the east and northeast of 

the State and in close proximity to major interstates, including I–80 and I–29. Asphalt suppliers 

in the State are concentrated along I–80, which runs east-west through the State. 

Data were used to identify trends and anomalies in bid prices of key items, including aggregate, 

concrete, and asphalt materials, during the analysis period of 2006–2016. Prices of aggregate 

remained very stable throughout the period, although aggregate (item No. 8008.5) did not appear 

in bid data in 2008. Average bid prices of 8-inch concrete pavement (item No. 3075.32) slowly 

increased across the 10-yr period at a steady rate. Asphalt concrete (item No. 9005.23) average 
102 

bid prices, on the other hand, saw a slow decrease in prices per ton from 2006 to an all-time-low 

price in 2016. Unit price summary data from Nebraska DOT (NDOT) were examined to compare 

these price trends with pricing data reported for the corresponding years. This analysis revealed 

that prices seen in the bid data were consistent with the unit prices reported by NDOT.

Figure 79, figure 80, and figure 81 show the bid price trends for three materials: 8-inch concrete 

pavement class 47B-3500 (item No. 3075.32), asphaltic concrete type SPS (item No. 9005.23), 

and aggregate for microsurfacing (item No. 8008.5), respectively. Below each figure, additional 

pricing data to support the graphical information are provided (table 77, table 78, and table 79, 

respectively).

Figure 79 shows the price trends for a concrete item in Nebraska (item No. 3075.32). Prices rose 

during the analysis period with three higher average prices observable on the graph: $51.43 per 

square yard (SY) of 8-inch-thick concrete in 2008, $63.35 per SY in 2012, and $74.06 per SY in 

2015, as shown in table 77. 

Source: FHWA. 

Figure 79. Graph. Concrete bid price trends—Nebraska 2006–2016. 
103 

Table 77. Concrete price data—Nebraska.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 6 30.25 38.20 21.26 5.2

2007 7 42.94 51.25 39.00 4.3

2008 7 51.43 100.00 36.00 21.4

2009 9 42.27 65.00 35.80 8.9

2010 20 37.15 55.00 24.21 6.8

2011 7 40.93 50.00 30.40 6.8

2012 4 63.35 90.00 32.50 26.8

2013 22 53.10 86.00 30.00 14.3

2014 23 54.69 80.00 27.00 14.5

2015 18 74.06 210.00 29.50 40.8

2016 8 62.90 83.07 42.10 12.6

Next, the prices for an asphalt item were analyzed (item No. 9005.23). Figure 80 shows the price 

variation for this asphalt item during the analysis period. Average prices went up after 2010 with 

two higher average prices in 2013 ($31.08 per ton) and 2015 ($30.59 per ton). Table 78 shows 

higher maximum prices and standard deviation in 2013 and 2015, but the overall standard

deviation in price was low for this item.

Source: FHWA. 

Figure 80. Graph. Asphalt bid price trends—Nebraska 2006–2016. 
104 

Table 78. Asphalt price data—Nebraska.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 20 17.53 22.70 13.31 2.5

2007 16 20.76 27.68 15.35 3.8

2008 12 21.98 38.00 17.53 5.5

2009 38 20.68 42.05 14.08 4.9

2010 17 20.47 50.14 11.85 8.1

2011 49 21.21 43.40 14.00 4.8

2012 34 22.80 33.04 17.00 4.0

2013 31 31.08 129.54 17.01 22.0

2014 24 28.18 45.00 14.84 7.6

2015 25 30.59 89.00 16.00 16.9

2016 22 26.85 61.90 15.00 10.0

Lastly, an aggregate item (item No. 8008.5) was investigated. Figure 81 shows the price 

variation for this item. As can be seen in the graph and verified in table 79, the item did not 

appear in the data in 2008. For the other years, the standard deviation for the price of this 

aggregate item was very low.

Source: FHWA. 

Figure 81. Graph. Aggregate bid price trends—Nebraska 2006–2016. 
105 

Table 79. Aggregate price data—Nebraska.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 9 23.73 44.50 15.00 10.4

2007 7 20.77 25.00 16.00 2.7

2008 0 — — — —

2009 3 25.00 27.00 23.00 1.6

2010 2 31.60 36.00 27.20 4.4

2011 2 24.60 28.00 21.20 3.4

2012 3 30.50 38.00 21.00 7.1

2013 8 38.00 61.00 20.00 12.4

2014 1 35.00 — — —

2015 2 30.50 40.00 21.00 9.5

2016 2 24.00 30.00 18.00 6.0

—No data.

Nevada 

A major multistate firm in the markets of Nevada and Utah purchased a ready-mix concrete and 

aggregate supplier in 2016. Data provided in the Oman Systems, Inc., dataset ended with the 

third quarter of 2016, and, thus, pricing effects of this activity were not apparent. Nevada DOT 

resources were also investigated to identify if any special contract language was in use to 

alleviate any pricing or competition effects of consolidation activity within the State. Bidding 

requirements and statutes appeared normal, including prequalification of bidder requirements, 

contents of proposal forms stipulations, and examination of relevant plans and work sites.

A total of 57 unique firms were awarded 247 total projects containing materials of interest during 

the analysis period of 2006–2016. The State’s aggregate, concrete, and asphalt suppliers are 

largely located in the far southern area of the State and the northwestern area of the State. The 

middle areas of the State experience higher costs due to transportation of materials from supplier 

locations. While populations in the middle of the State are sparse, roadways do run throughout. 

Another unique feature of Nevada is that it contains 32 Indian reservations and colonies of 

varying size. 

Figure 82 and figure 83 show the bid price trends for two materials: emulsified asphalt type 

SS-1H (item No. 405 0516) and type 1 class B aggregate base (item No. 302 0500), respectively. 

Below each figure, additional pricing data to support the graphical information are provided 

(table 80 and table 81, respectively).

Figure 82 shows the price trends for an asphalt item (item No. 405 0516) in Nevada. Finding 

items that appeared in the data for every year of the analysis period in Nevada was challenging. 

Even though this asphalt item did not appear in the data after 2011, the price information was 

still selected for analysis. One high maximum price of $6,000.00 per ton was observed in 2009, 

and multiple penny bids were present in several years, as seen in table 80, which impacted 

average price and the standard deviation. No tangible reason for these price fluctuations was 

identified.
106 

Source: FHWA. 

Figure 82. Graph. Asphalt bid price trends—Nevada 2006–2016. 

Table 80. Asphalt price data—Nevada.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 18 371.33 770.00 0.01 263.3

2007 10 338.20 550.00 100.00 146.4

2008 17 378.62 980.00 0.01 353.9

2009 35 449.20 6,000.00 0.01 982.9

2010 24 504.03 1,230.00 0.01 384.5

2011 17 387.29 1,200.00 0.01 382.1

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, an aggregate item (item No. 302 0500) was analyzed. Similar to the asphalt item, this 

item did not appear in the data after 2011, as seen in figure 83 and table 81. For the years of data 

that were available for analysis, the price fluctuated slightly, but no abnormalities were 

identified.
107 

Source: FHWA. 

Figure 83. Graph. Aggregate bid price trends—Nevada 2006–2016. 

Table 81. Aggregate price data—Nevada.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 19 37.97 153.00 5.00 36.9

2007 8 18.63 67.30 5.00 18.6

2008 11 27.94 75.00 4.00 18.9

2009 20 27.61 170.00 0.01 42.6

2010 21 27.63 78.00 2.00 22.4

2011 16 20.29 70.00 0.01 16.3

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

New Mexico

New Mexico DOT divides the State into six unique regions; however, some counties overlap 

these regions, which made comparison between regions complicated. A total of 68 unique firms 

were awarded bids, ranging from 25 to 82 per year. In comparison to other States analyzed 

during the project, New Mexico had significantly fewer projects per year. Years with the highest 

project costs included 2006, 2008, and 2012. Project distribution across regions saw relatively 

stable fluctuation throughout the analysis period of 2006–2016. 

Before the analysis period, a major construction firm in the State acquired a subsidiary firm from 

the Oklahoma City, OK, area; however, no major consolidation activity was observed during the 
108 

10-yr analysis period. During the economic recession, the State saw a significant drop in 

construction industry jobs: in 2007 the State had 60,000 construction industry jobs and had not 

yet regained that number in 2017 for which the number of jobs was reported as 46,000. The 2017 

value was the highest since mid-2009 during the height of the economic downturn. Within the 

State, higher project costs were observed in the Albuquerque, NM, area, likely due to shortened 

project timelines, which tend to drive costs higher. 

Figure 84 and figure 85 show the bid price trends for two materials: structural concrete class A 

(item No. 511000) and asphalt material (item No. 407000), respectively. Below each figure, 

additional pricing data to support the graphical information are provided (table 82 and table 83, 

respectively).

Figure 84 shows the price variation for a concrete item (item No. 511000) in New Mexico. Two 

noticeable peaks in price are observed on the graph in 2007–2008 and in 2014. Table 82 shows 

higher average prices and higher maximum prices for these years, resulting in larger spreads 

between maximum and minimum price and larger standard deviations. 

Source: FHWA. 

Figure 84. Graph. Concrete bid price trends—New Mexico 2006–2016. 
109 

Table 82. Concrete price data—New Mexico.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 46 551.95 1,000.00 190.00 172.2

2007 30 902.44 10,000.00 336.00 1,699.8

2008 39 942.75 5,000.00 211.43 1,024.9

2009 37 539.27 1,361.85 31.20 272.8

2010 37 577.20 1,400.00 200.00 291.2

2011 28 475.63 1,100.00 310.00 144.1

2012 19 531.95 1,000.00 340.00 197.5

2013 24 617.02 2,000.00 306.00 331.4

2014 23 1,074.54 8,848.00 245.00 1,743.4

2015 19 787.14 3,317.00 192.00 701.9

2016 17 873.72 2,640.00 400.00 601.8

Lastly, an asphalt item (item No. 407000) was analyzed. Similar to other States, New Mexico 

only yielded two items for analysis (concrete and asphalt). Figure 85 and table 83 show the price 

trends for this asphalt item. Moderate deviation occurred in prices throughout the analysis 

period, but no significant anomalies were identified in the data. 

Source: FHWA. 

Figure 85. Graph. Asphalt bid price trends—New Mexico 2006–2016. 
110 

Table 83. Asphalt price data—New Mexico.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 51 430.02 2,285.00 150.00 320.7

2007 36 312.65 500.00 150.00 92.7

2008 56 572.29 1,600.00 200.00 246.9

2009 54 488.29 950.00 350.00 106.9

2010 65 519.75 958.72 315.73 147.5

2011 39 556.85 2,000.00 400.00 283.1

2012 51 543.12 1,000.00 263.02 141.1

2013 39 549.12 1,100.00 150.00 188.5

2014 40 593.88 1,108.35 400.00 186.5

2015 24 490.98 700.00 6.30 135.5

2016 20 483.35 965.00 300.00 181.9

Oklahoma

A major firm purchased a ready-mix concrete and aggregate source in the Oklahoma region in 

2012. Another change in the Oklahoma market occurred in 2014 when a new mining operation 

of aggregate was opened by a major firm operating primarily in the midwest region. This same 

firm also purchased a sand and gravel supplier in 2015. A slight increase in prices of aggregate 

products was seen in the State after the mining operation was opened in 2014, but the price 

differences across projects were very low.

Unit price data provided by Oklahoma DOT included items, regions, number of bids, quantities, 

average awarded prices, and average of the three lowest bidders’ pricing for items of interest. 

When aggregate unit prices were analyzed against aggregates bid prices contained in the data 

provided through Oman Systems, Inc., and supplemented by the research team’s review of 

information posted on State DOT websites, price fluctuations were found to be minor. However, 

some regions of the State did see higher prices of aggregate materials after the opening of the 

mining operation in 2014. These regions included region 4 (north central Oklahoma, including 

Grant, Kay, Garfield, Noble, Kingfisher, Logan, Payne, Canadian, and Oklahoma Counties), 

region 5 (southwestern Oklahoma, including Dewey, Blaine, Custer, Roger Mills, Beckham, 

Washita, Greer, Kiowa, Harmon, Jackson, and Tillman Counties), and region 6 (northwestern 

Oklahoma, including Cimarron, Texas, Beaver, Harper, Ellis, Woodward, Woods, Major, and 

Alfalfa Counties). These price differences could be attributed to transportation costs of aggregate 

materials from the eastern regions of the State or from sources from neighboring States, 

including Texas. 

Figure 86, figure 87, and figure 88 show the bid price trends for three materials: class C concrete 

(item No. 509(D) 0325), SP asphalt concrete type S4 (item No. 411(S4) 5960), and aggregate 

base (item No. 303 5912), respectively. Below each figure, additional pricing data to support the 

graphical information are provided (table 84, table 85, and table 86, respectively).

Figure 86 and table 84 show the price trends for a concrete item (item No. 509(D) 0325) in 

Oklahoma. Prices rose over time, with lower prices observed in 2009 and 2010 and one higher 

average price in 2012, as indicated by the spike in the graph. The maximum price of $9,000.00 
111 

per CY observed in 2012 caused the average price to be higher. This amount was the highest 

observed price for this material. 

Source: FHWA. 

Figure 86. Graph. Concrete bid price trends—Oklahoma 2006–2016. 

Table 84. Concrete price data—Oklahoma.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 161 244.37 743.47 100.00 80.3

2007 142 278.51 600.00 110.14 84.3

2008 137 325.25 1,500.00 175.00 147.3

2009 174 283.76 750.00 100.00 93.9

2010 178 255.02 636.00 100.00 80.6

2011 159 288.64 1,000.00 100.00 119.6

2012 122 386.22 9,000.00 100.00 793.1

2013 161 337.71 1,706.59 100.00 171.8

2014 139 374.82 1,485.00 100.00 202.5

2015 141 372.75 1,345.00 150.00 185.5

2016 100 358.14 1,200.00 100.00 161.3

Second, an asphalt item (item No. 411(S4) 5960) was analyzed. This item did not appear in the 

data after 2011. For the years it was observed in the data, prices remained relatively consistent, 

with low variation and no anomalies, which is reflected in figure 87 and table 85. 
112 

Source: FHWA. 

Figure 87. Graph. Asphalt bid price trends—Oklahoma 2006–2016. 

Table 85. Asphalt price data—Oklahoma.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 157 75.25 380.00 40.12 40.3

2007 140 76.64 350.00 37.16 40.1

2008 150 99.24 350.00 49.50 47.1

2009 203 81.48 630.00 35.00 49.8

2010 195 87.46 695.00 22.00 58.6

2011 23 81.91 167.81 46.55 30.0

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Lastly, an aggregate item (item No. 303 5912) was investigated. Figure 88 and table 86 show the 

price trends for this item for the years it was present in the data (2006–2011). During this time, 

price deviation was very low, and prices remained consistent except for a slight decrease in 

average price in 2009 and 2010. 
113 

Source: FHWA. 

Figure 88. Graph. Aggregate bid price trends—Oklahoma 2006–2016. 

Table 86. Aggregate price data—Oklahoma.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum

Price (Dollars)

Standard 

Deviation

2006 7 28.46 40.00 21.49 5.9

2007 24 30.47 50.00 20.00 8.6

2008 22 30.25 55.00 18.00 8.1

2009 27 26.24 45.00 9.15 7.2

2010 23 26.42 46.20 16.55 7.7

2011 3 29.27 41.00 20.00 8.7

2012 0 — — — —

2013 0 — — — —

2014 0 — — — —

2015 0 — — — —

2016 0 — — — —

—No data.

Oregon

Information from Oregon DOT (ODOT) revealed that most M&A activity in the State occurred 

prior to 2006. Activity during the analysis period of 2006–2016 included two major firms 

purchasing some aggregate source companies and suppliers. ODOT is able to offer State sources 

of materials in the eastern part of the State, while in the western part of the State private sources 

provide fairly robust competition. Currently, ODOT does have mechanisms in place to assess 

unbalanced bids; however, contract language has not been altered to account for M&A activity 

within the State. 
114 

The State is divided into five regions. Between 43 and 141 projects were awarded each year, and 

a total of 170 unique firms were involved in the projects across the analysis period. Regions 2 

and 3 saw higher project costs during the analysis period. Oregon has quarry and/or gravel pits 

located in every county. Columbia, Crook, Douglas, Jackson, and Linn Counties contain a larger 

number of materials pits compared with the other counties. These counties are in regions 2, 3, 

and 4, located in the western and central part of the State. Wheeler, Wallowa, Sherman, 

Jefferson, Hood River, Gilliam, and Coos Counties contain the fewest material pit locations. 

Figure 89, figure 90, and figure 91 show the bid price trends for three materials: 37-inch asphalt 

concrete pavement (item No. 0748-0119000J), PG 64-22 asphalt in HMA concrete (HMAC)

(item No. 0745-0620000M), and aggregate base (item No. 0640-0100000M), respectively. 

Below each figure, additional pricing data to support the graphical information are provided 

(table 87, table 88, and table 89, respectively).

As can be seen in figure 89 and verified in table 87, this concrete item (item No. 0748-0119000J) 

was not used in Oregon in 2006, 2007, 2008, 2013, or 2016. However, it was still selected for 

analysis to assess potential M&A activity through price anomalies. For the years the item was 

used, price was variable. The sharp decrease seen in the graph toward the end of the analysis 

period is likely due to the low average bid price in 2015. This price drop can be attributed to a 

penny bid in 2016, which skews the average price. 

Source: FHWA. 

Figure 89. Graph. Concrete bid price trends—Oregon 2006–2016. 
115 

Table 87. Concrete price data—Oregon.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 0 — — — —

2007 0 — — — —

2008 0 — — — —

2009 4 58.50 103.00 37.00 26.1

2010 5 63.60 138.00 35.00 38.9

2011 4 48.75 85.00 20.00 25.6

2012 1 75.00 — — —

2013 0 — — — —

2014 1 96.00 — — —

2015 3 42.34 70.00 0.01 30.4

2016 0 — — — —

—No data.

Next, an asphalt item (item No. 0745-0620000M) was analyzed. Figure 90 shows an overall 

decreasing trend in bid prices with several visible spikes in prices in 2008 and 2012. However, as 

can be seen in table 88, the minimum bid prices for this asphalt item indicate the data contain 

both dollar and penny bids. These bids caused large gaps between the maximum and minimum 

bid prices, which have impacted the average prices.

Source: FHWA. 

Figure 90. Graph. Asphalt bid price trends—Oregon 2006–2016. 
116 

Table 88. Asphalt price data—Oregon.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 10 285.72 703.00 1.00 225.4

2007 13 267.75 470.00 1.00 161.5

2008 17 390.15 901.25 1.00 257.0

2009 27 215.85 580.00 0.01 236.0

2010 22 136.85 510.00 0.01 211.3

2011 18 146.06 583.00 0.01 236.0

2012 15 286.73 770.00 1.00 310.0

2013 20 57.15 630.00 0.01 170.5

2014 21 119.27 780.00 0.01 248.3

2015 16 166.38 600.00 0.01 247.6

2016 13 127.16 510.00 0.01 193.2

Finally, an aggregate item (item No. 0640-0100000M) was analyzed. Lastly, the bid price trends 

for an aggregate item (item No. 0640-0100000M) in Oregon are shown in figure 91. The trend 

for the price data for this aggregate base item generally increased throughout the analysis period. 

The minimum prices in table 89 show penny bids in the data (2010), as well as higher maximum 

prices for this aggregate item (2009 and 2010). However, when average prices across the 

analysis period are reviewed, these prices appear to be relatively similar and consistent with 

other aggregate items used in the State.

Source: FHWA. 

Figure 91. Graph. Aggregate bid price trends—Oregon 2006–2016. 
117 

Table 89. Aggregate price data—Oregon.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 59 22.72 55.00 10.00 9.9

2007 50 36.78 170.00 11.22 27.6

2008 61 31.36 110.00 10.36 17.0

2009 94 30.48 165.00 7.00 19.4

2010 76 35.34 178.00 0.01 27.6

2011 63 32.51 75.00 10.50 14.5

2012 42 29.18 87.00 4.00 13.1

2013 69 36.42 105.00 4.50 16.3

2014 60 36.22 120.00 10.80 21.8

2015 49 37.93 100.00 14.00 19.7

2016 31 37.27 125.00 10.85 22.5

Utah

A major multistate firm in the markets of Nevada and Utah purchased a ready-mix concrete and 

aggregates supplier in 2016. Data in the Oman Systems, Inc., dataset ended with the third quarter 

of 2016, and, thus, pricing effects of this activity were not apparent. Most of the State’s concrete 

and asphalt suppliers are located in the north central region; aggregate suppliers, including sand 

and gravel, are also located in the north central region of the State. Three price anomalies were 

found during initial data processing: in 2010, 2011, and 2012 the average bid prices per CY of 

aggregate were approximately $12,000.00, $3,000.00, and $15,000.00, respectively. These 

amounts seem unusually high, especially compared with amounts in previous years (which were 

around $45.00 per CY). In 2012, one project had an aggregate price that was greater than

$950,000.00 per CY. Further inspection of the individual project revealed other pricing 

inconsistencies that appeared to be due to an error in unit selection (e.g., CY instead of lump 

sum).

The other abnormally high prices for aggregate found in 2010 and 2011 were also inspected. 

Again, one project saw costs much higher than any other projects billing aggregate for that year. 

All projects with pricing abnormalities occurred in Washington County, and the same firm was 

awarded all three abnormally high projects. Further analysis of this firm revealed that a 

multistate major firm purchased the original company in 2009. Following this purchase, the 

Utah-based firm continued to operate out of Draper, UT, but worked on many joint ventures with 

the purchasing firm subsidiaries, particularly out of California. 

Figure 92, figure 93, and figure 94 show the bid price trends for three materials: concrete class B 

(AE) portland cement (item No. 03310003P), HMA–1⁄2 inch (item No. 27410050), and granular 

borrow (item No. 20560015), respectively. Below each figure, additional pricing data to support 

the graphical information are provided (table 90, table 91, and table 92, respectively).

Figure 92 shows the price trends for a concrete item (item No. 03310003P) in Utah. As can be 

seen in the graph, a major price spike is observed in 2012. Table 90 shows the average price in 

2012 to be $69,000.00 per CY, which is the only time that item appears in the data for 2012. 

Further analysis of this high price (job No. S-0007(11) with a bid date of October 4, 2012, in 

Washington County) revealed that this price was the only occurrence of a price per CY of greater 
118 

than $20,000.00. No additional information about this price was identified. Washington County 

is located in the southwestern corner of Utah, and other price abnormalities were identified 

associated with projects bid in this county. 

Source: FHWA. 

Figure 92. Graph. Concrete bid price trends—Utah 2006–2016. 

Table 90. Concrete price data—Utah.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 2 10,841.50 20,000.00 1,683.00 9,158.5

2007 0 — — — —

2008 0 — — — —

2009 1 3,500.00 — — —

2010 1 91.80 — — —

2011 2 8,600.00 10,280.00 6,920.00 1,680.0

2012 1 69,000.00 — — —

2013 3 164.29 380.00 56.41 152.5

2014 0 — — — —

2015 4 154.19 295.00 50.78 88.3

2016 2 98.00 98.00 98.00 0.0

—No data.

Next, the price trends for an asphalt item (item No. 27410050) were analyzed. Prices for this 

item, shown in figure 93 and table 91, were consistent throughout the analysis period, with a 

general increasing trend after 2013. 
119 

Source: FHWA. 

Figure 93. Graph. Asphalt bid price trends—Utah 2006–2016. 

Table 91. Asphalt price data—Utah.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 19 92.52 250.00 38.00 47.5

2007 22 103.20 224.00 59.00 45.8

2008 33 106.20 315.00 51.00 53.1

2009 57 107.02 180.00 60.00 34.3

2010 61 100.92 216.00 45.46 36.0

2011 60 85.54 200.00 52.78 26.2

2012 36 102.96 326.00 67.00 49.2

2013 52 99.22 375.00 49.50 56.5

2014 28 99.35 260.00 64.75 43.7

2015 33 120.01 250.00 65.00 52.9

2016 29 135.33 800.00 58.00 136.3

Finally, an aggregate item (item No. 20560015) was analyzed. Figure 94 shows the price 

variation for this item. Prices decreased from 2006 until 2010 where they reached a low average 

price of $17.37 per CY. Prices then rose to a peak average price of $33.32 per CY in 2012 and 

showed an increasing trend again at the end of the analysis period. Table 92 shows low standard 

deviation values for this aggregate item, indicating most prices did not vary greatly from the 

calculated average bid price per CY. No abnormal prices were identified for this item during the 

analysis period. 
120 

Source: FHWA. 

Figure 94. Graph. Aggregate bid price trends—Utah 2006–2016. 

Table 92. Aggregate price data—Utah.

Year

Data 

Points

Average Price 

(Dollars)

Maximum

Price (Dollars)

Minimum Price 

(Dollars)

Standard 

Deviation

2006 22 30.91 55.00 13.50 11.3

2007 20 24.87 67.00 8.45 13.4

2008 26 23.76 52.75 3.50 9.9

2009 30 20.81 50.27 7.76 10.9

2010 30 17.37 38.00 8.00 8.0

2011 31 19.60 47.30 9.26 7.6

2012 21 33.32 140.00 8.90 30.7

2013 26 29.41 83.65 4.50 16.5

2014 40 29.25 79.00 12.00 13.4

2015 23 30.11 52.22 12.25 10.6

2016 20 34.32 75.00 14.5 17.5
121 

CHAPTER 4. UNIT PRICE ANALYSIS

Many State DOTs keep a record of historical unit price data for all bid item numbers included in 

lettings, sorted by date range. As noted in chapter 3, the research team explored various materials 

to determine whether trends in unit prices could be attributed to M&A activity. Items identified 

as being of interest in the project included granular backfill, aggregate, concrete pavement, and 

asphalt pavement. These items were selected from the historical unit price datasets for 

comparison against actual unit prices of those items in bids for corresponding years, as obtained 

from the data provided by Oman Systems, Inc., and supplemented by research team review of 

information posted on State DOT websites. 

For each year of bid item number data, the average, maximum, minimum, median, and the firstand third-quartile costs were calculated for each item. For example, in Wisconsin, for item 

455.0105, PG 58-28 paving grade asphalt binder, the values were calculated by year. In 2006, the 

average bid item number cost of item 455.0105 was $317.98 per ton, with a maximum and 

minimum cost of $490.00 and $100.00 per ton, respectively. The median cost was computed to 

be $339.50 per ton with a first- and third-quartile cost of $265.00 and $410.00, respectively. Unit 

price for 2006 as reported by WisDOT was $215.78 per ton. Each firm that included item 

455.0105 in their bid in 2006 was assigned a number. The bid item number prices for each firm 

that included 455.0105 in their project bids were then graphed against the reported unit price. An 

example of this graphical information is shown in figure 95. Firms are identified by a number to 

protect the identity of individual companies within each State. 

Source: FHWA. 

Figure 95. Graph. Bid price versus unit price. 

Corresponding average and quartile data for each item can also be presented in tabular form for 

all 10 yr, as shown in table 93.
122 

Table 93. Bid price versus unit price—Wisconsin. 

Item 455.0105 Unit 2006 2007 2008 2009 2010 2011 2012 2013 2014

Unit price

(dollars) Ton 215.78 308.56 386.31 295.37 248.39 172.17 165.98 120.71 184.85 

Bid prices

(dollars) 

Average 317.98 312.46 472.54 349.88 275.84 224.40 155.15 184.53 200.91

Maximum 490.00 481.24 875.00 620.00 700.00 630.00 645.00 800.00 1,000.00

Minimum 100.00 100.00 100.00 96.00 10.00 90.00 10.00 5.00 1.00

Median 339.50 357.00 500.00 460.00 125.00 100.00 100.00 100.00 100.00

Quartile 1 265.00 212.50 360.00 112.50 100.00 100.00 100.00 100.00 100.00

Quartile 3 410.00 390.00 677.50 520.00 547.00 461.50 100.00 250.00 250.00
123 

The graphical format (figure 95) of the data provides for easier identification of abnormalities, 

including significant spikes above or below the unit price for that year. Much variation in the 

asphalt bid price is seen for 2006. Table 93 reflects that the average bid price is above the unit 

price reported for that year, as is the median. It also reveals that, for item 455.0105, the average 

bid price is higher than the unit price every year, except for 2012. The frequency of the price 

spikes above the unit price line is less in 2012 than in 2006, and the frequency of price drops 

below the unit price line is greater in 2006 than in 2012. 

By using the data provided by the State DOT and supplemented by the research team review of 

information collected from Wisconsin, these spikes can be attributed to specific projects, regions, 

and firms within Wisconsin. Here, five identifiable spikes indicate asphalt bid prices that are 

significantly more than the unit price reported by the State DOT. Of these five price 

abnormalities, four occurred in projects let in Brown County, located in the northeast region of 

the State. The fifth spike occurred in Door County, also located in the northeast region of the 

State. Two of the five were projects won by the same contractor based in Manitowoc, WI (also 

located in the northeast region), while the other three were unique (based in the southwest, 

southeast, and northwest regions).

These price spikes can then identify firm- or plant-related activities taking place during the years 

showing abnormalities. In the example of the exorbitant asphalt prices (item 455.0105), five 

northeast region projects in 2012 could be related to transportation of asphalt from elsewhere in 

Wisconsin, as Brown County created a plan to begin producing its own asphalt within the county 

in 2014. This activity could be related to a desire to lower project costs by reducing 

transportation of asphaltic materials within the county. Brown County’s proposed asphalt 

initiative in 2014 was projected to save $700,000.00 in costs per year, including savings in 

production time and transportation costs. Data in the initiative also identified that, without the 

plant, the county would need to add approximately $225,000.00 to the 2014 budget to account 

for transportation of asphalt from outside of the county, as well as increases in project timelines 

due to production times. Use of the unit price data allows for an efficient and logical progression 

from the processed data provided through Oman Systems, Inc., and supplemented by research 

team review of information posted on State DOT websites to the identification of price spikes. 

This identification allows for further analysis of key activities contributing to these price spikes, 

which can be accomplished through the use of another dataset provided by the DOJ. 

Other State-by-State data on material source locations were provided by DOJ. These data include 

plant types, associated parent companies, previous owners and sold dates, as well as locations 

within the State. The addition of these data to the project has been valuable: identifying plant 

locations and company history coupled with unit price comparisons helped match spikes in the 

unit prices of materials with any relevant changes in material availability due to merger activity. 

Part of this effort involved mapping the locations of plants used in projects for individual States.

Plant location data allow for efficient identification of material locations: compared against 

project locations, disparities in pricing can be better understood. States acquiring materials from 

plants generally outside of the State or located some distance away from the projects could 

explain the higher prices. Transportation of materials, as well as extensions to project timelines 

due to production and transportation times of materials, may account for abnormally high prices 
124 

in certain projects unrelated to any merger activity. Following unit price analysis for key items, 

use of the DOJ dataset allowed for this deeper analysis to be completed for States of interest.

The worldwide aggregate industry is largely dominated by a handful of major players. In the 

United States, three major companies are among the leading suppliers of asphalt, aggregates, 

cement, ready-mix concrete, and paving and construction services. General information about 

each company is provided in the paragraphs below. A deeper dive into the geographical 

information on these major companies, such as the many locations where they operate, as well as 

when these locations were acquired via merger, acquisition, or other means, and then 

cross-checking that information with any abnormal year-over-year unit price fluctuations would 

provide conclusions about the effects of M&A on price and market share. 

For example, one firm, based in Atlanta, GA, is one of the top vertically integrated suppliers of 

aggregates, asphalt, ready-mix concrete, and paving services in the United States, with 

operations at more than 1,300 locations nationwide. It has locations in Massachusetts, Rhode 

Island, Connecticut, Maine, New Hampshire, and Vermont. Similarly, another notable merger in 

July 2015 further defined the industry and created another industry leader. With a strong 

presence in the United States since the 1950s, the purchasing firm’s family of companies is the 

number one building materials and solutions provider in the world and the leading cement 

producer in the United States. Currently, this company is headquartered in Chicago, IL, with 

subsidiaries across 43 States operating under multiple names. 

Lastly, a major cement supplier has been active in North America since 1977 when it purchased 

another cement company. The purchased firm was originally founded in 1897 in Pennsylvania 

and began as a single mill producing portland cement. The purchasing firm acquired its Canadian 

operations in 1993 and then acquired the other company in 2007. Today, the broad geographic 

footprint and wide range of products positions the firm favorably to supply construction projects 

throughout the United States and Canada. 

Acquisition of the other firm in the second half of 2016 further strengthened this major cement 

supplier’s presence in the United States. A subsidiary operates in both the United States and 

Canada. Originally set up in 1866, the subsidiary company started producing cement in 1872 and 

changed its name in 1989. The major cement supplier serves its cement customers in the United 

States through 13 strategically located cement plants and a strong distribution terminal network. 

The company produces a variety of products, including gray, white, custom-colored, and slag 

cement. While the majority of the cement produced is used in the production of ready-mix 

concrete, it is also used in the manufacturing of precast concrete products, such as pipes and 

blocks, and in the oil well industry. 

As part of the acquisition of another material supplier in 2007, the firm also gained a dense 

network of sand, gravel, and hard stone production sites in the United States. With facilities 

located in key markets throughout the country, the material plants serve these markets through an 

effective logistics network of distribution terminals, railcars, and barges. The 2007 deal also gave 

the company a strong ready-mix concrete presence in the United States as well as many asphalt 

production sites. The current plants are shown in table 94. 
125 

Table 94. Number of plants by type—major cement firm. 

Plant Type No. of Plants

Cement 13

Grinding 2

Ground granulated blast furnace slag 3

Cement terminals 53

Aggregates 182

Aggregates terminals 12

Ready-mix concrete 128

Asphalt 51

127 

CHAPTER 5. CHALLENGES AND OBSERVATIONS

Challenges and observations associated with this work are discussed in the following sections. 

SELECTING APPROPRIATE BID ITEM NUMBERS 

It became evident from the beginning that selecting the relevant bid item numbers from the large 

datasets for each project to match the materials that were analyzed in this study would be 

challenging. Subsequently evaluating these items against impacts from known mergers or 

acquisitions also proved cumbersome. Subject-matter experts in estimating, construction, and bid 

letting assisted in evaluating the data and bid item number selection process. Second, matching 

these data items with contractor and price information found through State DOT websites and 

collected data, as well as online from Bid Express, required manual interventions (Bid Express 

2021). Disorganization of the data available on Bid Express as well as the variety of data formats 

provided by State DOTs (ranging from Excel spreadsheets to PDF documents to text files) made 

the initial data matching difficult and time-consuming. 

DESIRED PARAMETER AVAILABILITY

Information not included in the dataset that would have provided additional analysis capabilities 

included the total number of bidders and the pricing breakdown of other bids compared with the 

winning bidder’s pricing. While these data could be filled in manually using apparent bid data 

for each letting from the Bid Express internet bidding database, doing so for all the datasets 

would have had a serious impact on the project’s schedule and cost (Bid Express 2021). That 

being said, access to this larger amount of data would have allowed for a more thorough analysis 

of the winning bid prices against other competitors and likely a greater level of identification of 

abnormal pricing of individual bids. Deeper examination into these abnormal bid amounts could 

have included an analysis of all bid item numbers within the bid, followed by unit price analysis. 

INCONSISTENT BID ITEM NUMBER USE

Many State DOTs keep records of historical unit price data for all bid item numbers included in 

lettings, sorted by date range. These data were requested for States of interest and were relatively 

easy to obtain and process. Items of interest include granular backfill, aggregate, concrete 

pavement, and asphalt pavement. These items were selected from the historical unit price 

datasets for comparison against actual unit prices of those items in bids for a period of 

corresponding years, as obtained from the data provided through Oman Systems, Inc., and 

supplemented by research team review of information posted on State DOT websites. 

This bid item number use is also complicated by the use of skewed bidding or “penny bids” on 

items across the dataset. In almost every State the team reviewed, this approach provides for 

average prices that may be varied across the years without reflecting actual market conditions for 

that bid item number. Another major challenge associated with this analysis was identifying 

which combination of contractor and item number would yield data for a majority of the analysis 

period (2006-2016). There is no initial sorting that allows for identifying contractors using a 

particular item of interest that is reported in both the Oman Systems, Inc., and State DOT unit 

price data across most of the 10-yr analysis period. Consequently, time spent may yield 
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contractors that did not use the items of interest at all or only used them for 1 or 2 yr, and, thus, 

analysis for that contractor across the whole 10-yr period was not possible. 

Finding a contractor that used a particular item that is in the State’s unit price data for at least 6 

of the 10 yr was time-consuming and was accomplished mostly by pulling information from the 

dataset and associated check work. Some insights were considered, including identifying very 

common or popular items, such as PG 58-28 paving grade asphalt binder in Wisconsin, which 

yielded three contractors who used this item in projects over multiple years in the analysis 

period. In retrospect, the above-mentioned analysis could potentially be streamlined using a 

different analysis methodology, such as using an experienced computer program coder to write 

scripts that could replicate these data sorting and matching processes in much less time, yielding 

more time for analysis of data trends and individual State case studies.

Two examples of this challenging sorting process are shown in table 95 and table 96: one in 

which the unit price analysis was successful (yielding at least one contractor that used a 

particular item for multiple years) and one that was not successful (not yielding any contractors 

that used the item for more than a few years or for several nonconsecutive years).

The example in table 95 shows an instance in which two conditions exists: an item of interest 

(item 455.0105 asphaltic material PG 58-28) is included in the unit price data provided by 

WisDOT, and one contractor used the item of interest in multiple projects over multiple 

consecutive years in the analysis period of 2006–2016. Thus, analysis yielded the data shown in 

table 95, including the average, maximum, minimum, and median bid prices for this item for 

each year. The unit price as reported by WisDOT is also shown. Based on these data, the average 

bid price of the item is seen to be higher than the unit price for every year except for 2012. 

Additionally, both the unit price and bid price of the item increased in 2007–2009 and then 

generally decreased in 2010–2014. Several cases of minimum bidding, however, are evident, as 

the price fluctuates between $10.00 per ton and $695.00 per ton. 

In contrast, the second example in table 96 shows an instance where only one of the conditions 

exists: an item of interest (item 305.0110 base aggregate 3⁄4-inch) for this project is included in 

the unit price data provided by WisDOT, but contractors did not use the item of interest in 

projects across consecutive years. Table 96 shows some price data available for one contractor. 

As can be seen for 2009 and 2011–2016, no contractors used the item in any projects in 

Wisconsin. Contractor K used the item in limited projects: one project in 2006 and in 2008 and 

two projects in 2007 and in 2010. This data limitation makes the identification of any trends in 

the data difficult to identify and less significant due to low sample size.
129 

Table 95. Unit price versus contract price for firm L—Wisconsin. 

Item 455.0105: Asphaltic 

Material PG 58-28 Unit 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Unit price (dollars) Ton 215.78 308.56 386.31 295.37 248.39 172.17 165.98 120.71 184.85 NA

Bid prices (dollars) 

Average 328.75 371.43 522.44 499.00 355.00 357.50 100.00 335.00 381.25 186.25

Maximum 425.00 420.00 735.00 513.00 570.00 630.00 100.00 615.00 695.00 625.00

Minimum 100.00 290.00 130.00 485.00 100.00 100.00 100.00 10.00 100.00 10.00

Median 352.50 371.00 567.00 499.00 520.00 350.00 100.00 357.50 365.00 55.00

NA = not applicable.

Table 96. Unit price versus contract price for firm K—Wisconsin. 

Item 305.0110: Base 

Aggregate 3⁄4-inch Unit 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Unit price (dollars) Ton 8.34 9.79 10.89 11.05 12.52 11.49 11.43 12.54 13.30 14.41

Bid prices (dollars) 

Average 8.65 8.98 15.88 NA 15.95 NA NA NA NA NA

Maximum 8.65 10.89 15.88 NA 17.95 NA NA NA NA NA

Minimum 8.65 6.57 15.88 NA 13.95 NA NA NA NA NA

Median 8.65 10.89 15.88 NA 11.49 NA NA NA NA NA

NA = not applicable.

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CHAPTER 6. STATE OBSERVATIONS

The research team synthesized findings to provide guidance for State DOTs regarding 

identifying and assessing M&A activity. Case studies were conducted on nine selected States. 

Using the data, case law, literature, and case study interview results, a general set of 

recommended practices was identified.

The information generated from case study results is based on input from case study participants, 

subject-matter expert observations, literature review, and preferred practices discussed by States. 

STATE CASE STUDIES

Additional case studies on selected States were completed to glean further insights on State

practices for M&A monitoring, project estimating, and bid letting. Nine States were selected: 

Arizona, Colorado, Georgia, Missouri, Ohio, Oklahoma, Oregon, Tennessee, and Wisconsin, 

shown in figure 96. Originally, West Virginia was selected, but declined to participate due to 

ongoing litigation. 

Original map © 2021 MapChart. Modified by FHWA (see Acknowledgments section). 

Figure 96. Map. Case study States (Historical MapChart 2022). 

The objective was to gain further State-specific information on the state of the practice and gain 

insights from selected States. The scope included analysis of the market and economic conditions 

of the local and State transportation region to assess the impact of supply on costs and quality. 

Case studies were conducted as in-person interviews of representatives from each State and 
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included questions on prime contractor makeup; M&A activities in the State in aggregate, 

asphalt, and concrete areas; material supplier information; competition issues or concerns; 

bidding processes and analysis; unit prices; and general advice or observations. 

In general, firm sizes across these States range from small, family owned firms to large, publicly 

traded firms. While some States noted a decline in the number of firms, the number was 

generally stable. While limited proactive monitoring of M&A activity is a regular practice in the 

States, all States reported having some information available to assist. Most States are familiar 

with providing information for screening when necessary. Some consolidation activity occurred

among suppliers in the early 2000s, but there has not been much recent activity. Some issues 

have arisen due to land use restrictions and zoning, but overall competition appears to be healthy. 

Case Study Interview Questions 

To address the issues associated with challenges identified in the quantitative analysis, the 

overall research effort explored several case studies. The questions discussed in these case 

studies were approved by the FHWA Project Manager/Contracting Officer’s Representative and 

are included in appendix B.

LEGAL ANALYSIS

A desk scan was also completed to review prior merger cases in markets related to the 

transportation industry. The research team completed a review of State case information and 

news reports. The goal was to identify issues, antitrust incidents, and related activities. A review 

was conducted of how the U.S. DOJ and the FTC Horizontal Merger Guidelines were applied to 

these mergers in the highway materials and construction fields (U. S. Department of Justice

2012; U. S. Department of Justice and Federal Trade Commission 2010). Current antitrust and 

economics literature was also analyzed, including a retrospective merger activity analysis. 

The purpose of the legal analysis was to provide resources and documentation for prioritizing 

possible State and Federal enforcement and monitoring efforts in markets related to highway 

materials and construction providers. Case law ultimately determines actions taken, and most 

markets do not have viable spare competitors. Another issue contributing to the impacts of M&A 

activity is the narrowing of product definitions (such as “aggregate” versus “qualified 

aggregate”). From case law, some trends were identified. Road-building materials are almost 

universally regarded as homogenous products, and, accordingly, courts routinely focused on 

evidence of postmerger control of output capacity when assessing anticompetitive effects. 

Similarly, narrow geographies contribute to product costs as well. Product costs may be affected 

by high transportation costs, barriers to entry, and high sunk costs. No cases were found where 

the potential entry or creation of a new entity was sufficiently realistic to offset anticompetitive 

effects. Rather, market entry was only feasible when an established competitor was able to 

purchase divested assets. Market share can be determined using the HHI by determining 

individual firms’ market shares in the relevant product and geographical market, squaring those 

shares, and adding them together. This process gives proportionately greater weight to larger 

market shares, and, in general, an HHI score of greater than 2,500 reflects a highly concentrated 

market likely to trigger interest from the FTC and the U.S. DOJ. A merger resulting in an 
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increase in HHI of 100–200 points is also likely to raise competitive concerns sufficient to 

warrant agency scrutiny. For this study, the research team did not compute market share based 

on the regional data provided. Individual contractors were identified and assessed by projects 

won, but individual supplier information was not discussed. Based on the analysis and

recommendation of State and subject-matter experts, the researchers believe this to be a 

potentially useful strategy for States to explore, but it will require additional data. 

Price increases accompanied merger outcomes in all cases, regardless of the policy action taken. 

However, the amount of the increase varied considerably by the type of policy action taken. A 

Michigan-based researcher found that one merger resulted in an 18.0-percent immediate increase 

in price, but two other studies found no statistical increase (Duplantis 2010). Additionally, that 

study found that a 6.0-percent lower price emerged for each doubling in the number of bidders, 

and 5.6-percent lower prices were found for each doubling in the quantity of asphalt. Conditions 

that contributed to agency review included an increase in concentration that led to a moderately 

or highly concentrated market, a market that showed signs of vulnerability to coordinated 

conduct, and concern that the merger would enhance vulnerability. 

IDENTIFYING M&A ACTIVITY AND DETERMINING PROCESSES TO ADDRESS IT

During the course of our data review and the case studies, the team identified specific 

recommendations and key indicators for States. Two primary steps need to be taken when

monitoring the impacts of M&A activity: first, States must identify that the activity is taking 

place; and, second, they must assess the impacts (if any) this activity is having on pricing, 

competition, and market share.

A recommended approach and process for States to use would include monitoring proactively, 

calculating index values, tracking firm information, revising estimation practices, exploring 

regional differences, tracking bid prices, and exploring unbalanced bids. 

Guidance for identification of M&A activity is discussed in the following subsections. Many 

States reported limited proactive monitoring of M&A activity and reported further investigation 

only when prices rose dramatically above estimates.

Proactive Monitoring

Learning and documenting are half the battle. Even if no M&A activity has been identified in 

previous years, States should continually monitor for it via the methods mentioned noted in the 

individual case studies, with particular notice to Oklahoma. Proactive monitoring allows for 

more complete datasets and earlier identification of abnormalities in pricing and competition, 

whether they are related to M&As. Early identification of abnormalities in bidding practices or 

pricing will allow States to investigate root causes, which may include material shortages or land 

use restrictions. By monitoring and collecting these data, a more complete dataset can also be 

created. More complete, standardized, and high-quality data allow for possible future 

applications in predictive modeling to detect M&A activity and related impacts.

Among the preferred practices that our team identified are close coordination with professional 

trade associations and assessment of industry health by monitoring company names and certified 

bidder lists. These two steps allow State agencies to identify market entrants. In many cases, 
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name changes and ownership changes are synonymous. This monitoring is particularly important 

in cases with subsidiary or joint ownership activities. 

Index Uses

The HHI is a commonly accepted measure of market concentration, regardless of industry. It is 

calculated by squaring the market share of each firm competing in a market and then summing 

the resulting numbers. It can range from almost 0 up to 10,000. The U.S. DOJ uses the HHI for 

evaluating potential merger issues and assigning mitigation techniques. A market (consider 

aggregates broadly) with an HHI of less than 1,500 is considered to be a competitive 

marketplace, an HHI of 1,500–2,500 to be a moderately concentrated marketplace, and an HHI 

of 2,500 or greater to be a highly concentrated marketplace. 

The primary disadvantage of the HHI stems from the fact that it is such a simple measure that it 

fails to take into account the complexities of various markets. For the HHI to be properly used, 

other factors must be taken into consideration, and markets must be very clearly defined.

The formula for the index is simple to compute and can be shown by calculating market shares. 

Consider the following hypothetical industry with four total firms: 

• Firm 1 market share = 40 percent. 

• Firm 2 market share = 30 percent. 

• Firm 3 market share = 15 percent. 

• Firm 4 market share = 15 percent. 

The HHI is calculated as shown (figure 97): 

Figure 97. Equation. HHI of hypothetical industry. 

While a score of 2,950 shows an already highly concentrated industry (only four firms), a merger 

between firm 1 and firm 2 would substantially alter the landscape and could warrant additional 

scrutiny. If the two firms combined, the new HHI index score would be 5,350, and changes 

greater than 200 points typically justify additional attention.

Estimation Processes

Variation exists in the estimation processes used to generate bid estimates for projects. Neither 

FHWA nor AASHTO encourages all States to use the same procedures. States that create an 

in-house estimation team responsible for following the estimation process and generating the 

estimations can assist in examination of unbalanced bids. This practice allows local expertise to 

be developed. FHWA (2018) has guidelines in place for preparing engineer estimates, including 

the following methods: actual cost approach, historic data approach, and the combination 

approach. These methods can provide an engineering estimate to which to compare bid prices. 

However, improvement in the estimation of individual components is needed to provide a full 

picture of pricing before, during, and after M&A activities. Based on the case studies, the 
135 

research team found that estimators use historical price information as the starting point for 

making their estimates. This practice provides for limited ability to reassess based on current 

market conditions. 

The cost approach method considers factors related to actual performance of the work, including 

cost of labor, equipment, and materials; production rates; and profit. Historical data methods are 

less preferred as they provide a more lagging measure of prices; however, these methods are less 

time-consuming to develop, as long as competitive bid prices are used to build the estimates. 

When M&A activity is viewed, material cost is an item potentially most vulnerable to changes. 

Regular tracking of material costs by State DOTs can improve the accuracy of these estimates, 

especially when the actual cost approach for generation is used. 

Recently, some State DOTs have developed risk-based estimating methods to account for many 

of the uncertainties in the project delivery and contracting processes. Chapter 5 of AASHTO’s

Practical Guide to Cost Estimating provides an overview of these procedures (AASHTO 2013). 

Tracking Firm Information

It is vital for States to understand the makeup of firms bidding on projects. Many States reported 

having consistent pools of firms bidding on projects across years. Tracking firm names over time 

can aid in identifying merger activity. In addition to firm names and size, understanding where 

contractors are located, what their specializations are, and what projects they work on can help 

States identify competition issues. Use of project software such as AASHTOWare® Project

SiteManagerTM or something similar can also allow States to track project status over the project 

lifetime and evaluate contractor performance (AASHTO 2021). 

Regional Monitoring 

Many States are divided in regions or districts for DOT purposes. Each region may have its own 

unique struggles or challenges with, e.g., competition or material sourcing. For States with very 

diverse regions or districts, monitoring can be broken up into regional offices, where each region 

creates a team responsible for M&A monitoring and tracking. 

Unbalanced Bid Analysis

A key indicator of M&A activity impacts includes abnormal pricing during bidding. Some States 

reported already using unbalanced bid analysis. FHWA’s regulatory policy for Award of 

Contract and Concurrence in Award requires States to examine the unit bid prices of the apparent 

low bid for reasonable conformance with the engineer's estimated prices (Code of Federal 

Regulations 2020). A bid with extreme variations from the engineer’s estimate, or where obvious 

unbalancing of unit prices has occurred, must be evaluated. Where obvious unbalanced bid item 

numbers exist, the State’s decision to award or reject a bid must be supported by written 

justification.

Tracking Cost Indexes

Construction cost indexes are a useful tool for tracking trends of prices over time and comparing 

these trends with those seen in bid pricing. Most construction indexes use cost of inputs, 
136 

including labor, material, and equipment, when developing the data. The cost indexes can 

measure price movement for key objects over time or by location. By tracking cost indexes for 

key materials (Wisconsin, e.g., tracks 100 items), usually common bid item numbers, a State can 

identify more easily if a bid price change is due to M&A activity or other sources. 

DIMINISHING NEGATIVE IMPACTS OF M&A ACTIVITY

Not all M&A activity has negative impacts on a market. After identifying that activity exists, it is 

equally important to use a clear and systematic process for assessing the impacts of this activity 

to determine whether the effects are negative. During the case studies, several States observed 

that associations or agencies such as AASHTO and other trade associations were a reliable 

source of information on M&A tracking and impacts. In addition, agency oversight of State data 

and activity can allow for merger effects to be identified throughout the United States. The

limited geographic bounds of State construction activities make most State DOT construction 

activities less transparent to neighboring States.

Bid Analysis

If a State has identified M&A activity as the source of bidding, pricing, or competition issues, 

several key steps can be taken. First, the State should complete an analysis of any bids identified 

as unbalanced. Identifying abnormalities in bid pricing not caused by material shortages can 

allow the State to better understand factors driving the price up (or down). Part of this price 

analysis should include collaboration and comparison with neighboring States. The steps in the 

following subsections also assist in rectifying noncompetitive landscapes. 

Increasing Competition 

Second, on completion of the bid analysis, the State should work to identify which areas of the 

State or which projects are affected (e.g., all projects involving aggregates, all projects in the 

southeast region). This step will identify where the competition issues are experienced. If an area 

is identified as having minimal bidders or suppliers, four main options should be considered to

mitigate these impacts:

• Control material supplies at the State or agency level. 

• Bid smaller lettings more often. 

• Utilize project bundling. 

• Utilize alternative contracting methods (ACMs). 

If a pricing concern leads to identification of an area with minimal bidders and suppliers due to 

recent M&A activity, the State could consider providing publicly owned or State-controlled 

sources for those project materials. This practice can also be beneficial in areas where zoning 

restrictions or urban settings have limited competition for certain materials.

Areas with minimal bidders can also be aided by bidding projects more often (weekly or 

biweekly) instead of monthly, such as to provide more bidders by allowing more companies to 

bid a higher number of proposals in these smaller lettings. Holding more frequent lettings allows 

the frequency of awards to be increased, thus allowing more bidders to maintain their bonding 
137 

capacity to bid on more projects and increase overall competition. Breaking projects apart into 

smaller projects can increase the number of bidders for cases in which a low number of bids are 

received on larger projects. During the case study interviews, Oregon reported having success 

utilizing this method.

Project Bundling and ACM

Project bundling is another method States can use to increase competition in an area with 

minimal competition or bidding by incentivizing contractors to move into an area in which they 

may not currently work. Bundling projects together from different geographical regions allows 

for competition on a combined bid package as opposed to bidding on a smaller project where 

M&A activity has created geographical market share issues. Bundling can also occur at the bid 

item number level within a project to increase competition on individual bid item numbers. This 

option is useful if past bidding analysis has identified limited bidders on particular bid item 

numbers. Competition can also be increased by using ACMs. Additional work sponsored by 

FHWA is providing guidance in these areas (FHWA 2022). National Highway Institute training 

is also under development to support ACMs and project bundling. 

In certain situations, project bundling could potentially limit competition by removing the ability 

of smaller contractors to deliver projects when more are added to the mix. This potential needs to 

be considered further. 

139 

APPENDIX A. ANALYSIS OF MATERIAL SOURCE M&As ON PROJECT DELIVERY 

QUALITY AND COSTS—LITERATURE AND MARKET REVIEW SUMMARY

INTRODUCTION

In this task, the team completed a review of recent guidance, research, and after-action reports on 

M&As within the construction materials industry. The research effort focused on identifying and 

synthesizing the scope, specific industry segments, policy, processes, and regulatory information 

to determine the challenges and influences these consolidations have. 

MATERIAL COSTS

Within the world of construction, cost of materials and operations can be affected by many 

factors, including land availability, design constraints, materials and required equipment 

availability, and overhead. Site-specific factors such as climate, soil types, grade, and local 

regulations may also affect the types of materials used. The prices of various construction 

materials (e.g., asphalt, concrete, backfill, and aggregate) may vary from region to region as well 

as throughout and across years. The Associated General Contractors of America has worked 

extensively to compile construction price and cost indexes from data acquired from the U.S.

Bureau of Labor Statistics (Associated General Contractors of America 2022). While costs of 

processed goods such as concrete block, ready-mix concrete, and precast concrete saw yearly 

increases, this trend was predicted to continue into 2017 with a 2- to 3-percent increase in overall 

construction costs (Cavalcante 2016). 

Additionally, construction company M&As may affect material pricing, especially if the activity 

results in one company controlling a majority of projects within a particular State. M&A is a 

term that broadly describes a consolidation of companies or assets. Mergers take place when two 

or more firms combine to form a single entity, often run by a single management team. In merger 

activity, shareholders of smaller entities are able to increase overall net worth through the merge. 

Additionally, mergers tend to save on costs usually associated with acquisitions due to the lack 

of asset purchasing. In contrast, acquisitions occur when a company purchases significant 

amounts of another company’s assets, usually for the purpose of restructuring the acquired 

company (Sassine 2004). Horizontal M&As are of particular interest for this study, as they 

involve M&A activity by firms operating in the same industry—in this case, construction. 

Vertical M&A activity is also of interest, as it involves merging with, or acquisition of, a 

supplier or customer company (Sassine 2004). Conglomerates, consolidations, and sell-offs also 

occur in the construction industry, with conglomerate M&A activity occurring the most. 

Construction firms looking to reduce dependence on some unstable source of revenue may 

choose to merge with or acquire companies in different sectors (Sassine 2004). 

While many factors drive M&A activity, geographical expansion and competition consolidation 

are large driving forces behind many construction M&As and are areas where analysis is needed 

to determine whether these M&A activities are affecting prices.

Within the construction industry, M&As may affect material pricing as well as total project costs 

of winning bids. Similarly, market trends may also impact mergers. One such example is the 

M&A activity within the U.S. domestic airline industry. Passenger demand for airline travel 
140 

fluctuates depending on factors such as the economy and national events (Jackson 2015). Several 

airline M&A activities occurred in response to this changing market environment in an effort to 

improve competitive positioning. As a result, fewer but larger airlines exist in a monopoly-like 

structure.

Research regarding airline M&A activity indicates that it has measurable effects that are

reflected in stock prices and market power (Jackson 2015). Anecdotal evidence gathered from 

various States revealed that some State DOTs are concerned that M&A activity has raised bid 

prices and reduced competition. This concern is particularly true in States where one or more 

larger entities purchase several smaller entities, resulting in these few, larger entities having a 

majority of the market share.

Data also suggest that low market valuation can make a firm or entity a target for M&A activity. 

Investigation of this phenomenon, sometimes referred to as the “trigger effect,” has shown that 

decreases in valuation can lead to up to a 7-percent increase in the likelihood of an acquisition 

occurring (Edmans, Goldstein, and Jiang 2012). According to the Edmans article, these decreases 

in valuation are attributable to a variety of factors, including mispricing, mismanagement, or 

existing monopolization of a market by other entities, particularly if the entity of interest is 

relatively new or small. Acquiring firms may also experience poor postmerger returns, especially 

in the case of firms that acquire smaller targets (Franks, Harris, and Titman 1991). Similarly, 

regarding the effects of M&A activity on shareholders, data support the conclusion that the size 

of the acquisition affects market returns (Choi and Russell 2004). 

Construction growth increased in 2015, and this trend continued into 2016. Additionally, M&A 

activity reached record levels in 2015 across the United States and was expected to continue to 

grow (Cavalcante 2016). With regard to merger activity, the U.S. DOJ and FTC stipulate that 

merger activity should not create or enhance market power, which often occurs if a merger 

results in price increases, product output reduction, or diminished innovation, or brings undue 

harm to customers (U.S. Department of Justice and Federal Trade Commission 2010). The 

elimination of competition between merging parties may also result in a shift in market power, 

adverse effects such as the elimination of competition, or the increase in the risk of coordination 

among rival entities.

CASE STUDIES

One case study involving merger activity in the asphalt industry in Michigan examined the price 

effects resulting from the acquisition of three firms in the Michigan asphalt market by a larger 

firm between 1999 and 2001 (Duplantis 2010). Of the three mergers, one in the Kalamazoo area

had the most significant impact on pricing of asphalt in the market. Based on available Michigan 

bidding data, that merger was estimated to have raised prices by almost 18 percent in the 

Kalamazoo, MI, area within the 2-yr period following the merger (Duplantis 2010). In 

comparison, the other two mergers did not yield statistically significant differences in pricing 

following those merger activities.

Geographic factors also come into consideration in the analysis of M&A activity on material 

prices. As some materials are limited in how far they can be transported from their origin plant, 

the distance of plants may hinder a firm’s ability to be involved in a certain project. After the 
141 

three aforementioned mergers in Michigan, one firm owned or operated six asphalt plants in five 

counties in southern Michigan. Considering the geographic variables in the price effects, along 

with the dollar values for both total project costs and asphalt used in the respective project, the 

HHI can estimate market concentration based on the comparative size distribution of firms. An 

HHI will be close to zero in a market that contains a large number of relatively equal size firms. 

The maximum value for an HHI is 10,000 and occurs when a single firm controls a market (U. S.

Department of Justice and Federal Trade Commission 2010).

In the Michigan case where there was limited impact, a merger resulted in a change in HHI of 

only 250. In contrast, the change in HHI resulting from another detailed merger was greater than

1,700, indicating a large increase in material prices following the merger (Duplantis 2010). The 

DOJ and FTC place a large weight on postmerger price increases, which they consider to be 

adverse effects for customers. Thus, a merger with indications of price increases are examined to 

determine if the merger will result in anticompetitive effects (U. S. Department of Justice and 

Federal Trade Commission 2010). 

Relative market shares and concentration in the market before and after merger activity are also 

of great interest. Any M&A activity within a market that results in a large increase in 

concentration in the market can be presumed to enhance the market power. Post-M&A effects 

may also include share price increases within 1–4 yr after the M&A activity (Carrillo 2001). 

Data suggested that construction spending in the United States was expected to increase between 

2017 and 2020, despite a slight decreasing trend in December 2016 that was likely due to 

abnormally high spending in the prior month (Baker Tilly Capital 2017). 

Analysis of 202 construction projects involving key materials of interest (asphalt, concrete, 

aggregate, backfill, and sealant) in Wisconsin in 2016 revealed that, of these 202 projects, which 

occurred in 56 counties, 49 firms were winning bidders. However, more than 58 percent of the 

total projects were won by just 11 of the 49 firms involved. Additionally, 2 of the 11 firms were 

operating as divisions of a single firm along with two divisionary firms. These two diversionary 

firms won 5 percent of the total projects. 

WisDOT divides the State into five distinct regions, as noted in figure 5. Of the 11 firms 

controlling over half of the market, all 5 regions are represented, with some firms having a strong 

presence in multiple regions. One firm, which won 5 percent of the total projects analyzed in 

2016, has a presence in the north central, northeast, and southwest regions. Additionally, while 

these 11 firms had winning bids on 8–17 projects, the remaining 38 firms only had winning bids 

on, at a maximum, 6 projects, with the average being 2.2 winning project bids per firm. This 

apparent geographic control of the State by a small number of firms suggests that market shares 

may be affected.

One case study in Hawaii involving M&A activity that resulted in a similar market share 

occurred in 1985 involved a concrete industry consolidation of three firms (Schumann, Rogers, 

and Reitzes 1992). The State of Hawaii already experienced difficulties in the local cement 

market, as many buyers at the time chose to purchase cement from foreign suppliers due to the 

relatively low cost to ship cement products via water compared with land. In this case, the 

merger was not challenged, despite the creation of a monopoly in the cement industry of Hawaii 

(Schumann, Rogers, and Reitzes 1992). Following this merger, cement prices fell and then 
142 

remained below the premerger levels; however, imports of cement increased substantially after 

1982 and continued at higher levels postmerger as well. The consolidation of cement entities in 

Hawaii resulted in lower prices, while the high level of imported cement products prevented the 

consolidated firm from monopolizing the market in Hawaii (Schumann, Rogers, and Reitzes 

1992). 

METHODS OF ANALYSIS

To assess the potential effects of merger activity on market prices and market shares, an 

assessment of the market structure is required. Most markets are not a perfect monopoly, nor do 

they contain firms in perfect competition (Schumann, Rogers, and Reitzes 1992). Additionally, 

when a firm does raise prices, the reactions of the rivals of that firm have a significant impact on 

whether customers switch to other producers after the price increase. Due to the complex nature 

of market definition and subsequent price effects, the analysis of these price effects tends to be 

equally complex. 

When methods of analysis on these price trends following M&A activity are considered, 

statistical modeling can assist in revealing revenue yields based on demand, costs, and market 

concentration characteristics (Schumann, Rogers, and Reitzes 1992). In the studies examined by 

the FTC, a reduced-form price equation was developed for each industry without consideration 

of market concentration in favor of separating effects of discrete events such as M&A activity. In 

the case of the Hawaii merger and the subsequent effects on the market structure and pricing, 

limited data availability required multiple assumptions to be made during the modeling process 

(Schumann, Rogers, and Reitzes 1992). When data availability is limited, modeling constraints 

become more restrictive, and often the assumptions lead the model results to the conclusion that 

production is not affected by merger activity. Although this may not be unreasonable, more 

precise estimates with greater inclusivity of relevant information are ideal. 

Despite the isolation of specific M&A activities, the geographic market structure should come 

into play. Often, the geographic location of a firm or producer is an important factor in the 

determination of the effects of M&A activity on prices. Some products, such as asphalt, are 

limited by how far they can be transported due to temperature constraints. Other products may 

have similar constraints based on the cost of transportation. Thus, M&A activity that 

significantly alters a market concentration of a specific geographic location can affect market 

behavior and prices significantly (Choi and Russell 2004). 

A similar consideration is the use of weighted average cost indexes when doing a statewide or 

multistate analysis. Weighted average cost indexes allow the analysis to better exclude price 

changes caused by underlying differences in the costs of various products and materials. Cost 

differences are likely preexisting and not caused or affected by M&A activity and, thus, are not 

the object of analysis. Furthermore, the price changes due to or following M&A activity may not 

become apparent or statistically significant until 2–5 yr following a merger (Duplantis 2010). 

Some States use visualizations of data created in ArcGIS® regarding producer and supplier plant 

locations with the State, aggregated by type—aggregate (red), HMA (green), precast (purple), 

prestressed (blue), and ready mix (orange) (EsriTM 2019). Clicking on a dot gives the user the 

active plant’s name, type of plant, identification number, region code, latitude and longitude, and 
143 

the address. The use of this visualization across multiple years, as well as year to year, assists in 

understanding the potential effects and repercussions of M&A activity in a given State. The 

number of active plants, as well as their locations and the type of supplies produced, can aid in 

the analysis of market control and regional availability of products. 

DATA AVAILABILITY

Bid price data for most States are available through public websites and often include current as 

well as historical bid tabs. Some States also post their bid tab information on commercial bidding 

services sites, whereas others may archive their own bid tab data and may be willing to provide 

the data for analysis. AASHTO member State data can also be of use, as AASHTO has existing 

datasets built into its project estimating software (AASHTOWare ProjectTM Estimation) that can 

be analyzed to extract pertinent information as needed (AASHTO 2021). States may have 

electronic data, including total bid prices and pay item bid prices, aggregated by project level or 

State/county levels, whereas other States may not have any of these data readily available. 

FHWA also stores some bid tab information to use to calculate the National Highway CCI, 

which includes State-by-State item prices by quarter for various construction projects 

(FHWA 2021b). 

DATABASE COMPILATION

The research team prepared data analyses on 31 States, as presented in the original proposal. 

Price averages per year for each category for each State were identified. This procedure showed

which States and which years had prices outside of 1 or 2 standard deviations, or if any outliers 

were presented. Complete information was compiled in an Excel format for each State. 

With the cooperation of individual State data holders, requests were made to access information 

on ownership and on asphalt and material plant and pit locations on a State-by-State basis. These 

data, provided by the individual States to the DOJ under a screening tool (U.S. Department of 

Justice 2015) were used to complement potential market and price variations identified in the 

completed dataset for the 30 States.

An option exists to expand the data collection effort to all 52 jurisdictions recognized in the 

Federal system. The database expansion will allow for more details that are unavailable in the 

smaller sampling of States.

145 

APPENDIX B. CASE STUDY INTERVIEW QUESTIONS

The interview questions used for the case studies (appendix C) that were conducted on nine 

selected States are as follows.

GENERAL

1. State interviewed. 

2. Name of interviewer. 

3. Name of person(s) interviewed. 

4. Date of interview. 

PRIME CONTRACTOR MAKEUP

5. What is your general makeup of prime contractors? Do you have lists or compilations of 

those firms?

6. How many firms are prequalified to bid in the functional areas that prequalified are given 

ratings in? Do you analyze changes in these numbers over the years? 

7. Do prime contractors tend to specialize in functional areas in your State and use a lot of 

subcontractors, or do they perform multiple functions themselves? Has this changed over 

the years?

8. Do prime contractors tend to use the same subcontractors over time?

9. How often do “subs” also bid as “primes” on the same jobs? 

M&A ACTIVITIES

10. Do you monitor the M&A activity in your State in regard to companies that provide 

aggregates, asphalt, and concrete to your projects? Please describe in detail.

11. Have you noticed any trends or correlation between these M&As and changes in the 

number of bidders or changes in annual average unit prices or individual project bid 

prices?

12. Has any agency (State, FHWA, DOJ, etc.) studied M&As in your State, and if so did they 

report out findings to you? 

13. Has there been discussion or actions in your State to remedy or limit the effects of M&A 

activities on competition and bid pricing? 

14. Where do you believe the responsibility for regularly reviewing M&A activity and its 

influences on bid pricing should rest?
146 

MATERIAL SUPPLIERS

15. Describe how aggregates, asphalt, and concrete materials are obtained by prime 

contractors to be incorporated into State DOT Projects? Do primes supply a lot of their 

own materials for the projects they are awarded, or do they rely on outside independent 

suppliers for these materials?

16. Has this material supply changed significantly over the last 10 yr? If so, have you noticed 

any changes in the related individual project bid prices or annual average unit prices for 

the items that incorporate these materials supplied?

17. Were there any shortages of materials during this time that may have affected bid prices?

COMPETITION ISSUES AND CONCERNS

18. Are there other issues that concern your State about competition relating to these 

materials such as local zoning decisions and/or strategic real estate acquisitions?

19. Have you had any suspensions or debarments in your State relating to the bidding and/or 

securing materials for the supply of aggregates, asphalt, and concrete incorporated into 

your projects? 

20. Where there any changes in the economy locally, nationally, or worldwide that affected 

your bids? 

BIDDING PROCESS

21. Do you have a bid manual that describes in detail the process you use for bidding your 

State DOT roadway and bridge projects, including information below? Could you share it 

with us? 

22. Do you have urban or rural areas that need to be considered separately? 

23. How difficult is it to obtain aggregate and other inputs in any of these areas? 

BID ANALYSIS 

24. Do you have a systematic/electronic/software process to evaluate bids prior to award? If 

so, could you share this tool/guidelines with us? 

25. Do you have an unbalanced bid analysis process? 

26. What’s your percent of single bids? Has it changed over the years?

27. Do you keep track of the number of bids per proposal and analyze that data for trends 

over time?

28. What are your major bid item numbers for asphalt, aggregate, and concrete? Can you sort 

the largest bidders in each of these items by firm and by year?
147 

29. What is your first step if you notice a bid item number seems out of alignment?

30. Have you ever encountered complementary bidding? If so, what was your response to 

this?

AVERAGE UNIT PRICES

31. Do you calculate and publish statewide average unit prices annually for each component 

of a job? Do you have this data for the past 5–8 yr? 

32. Do you have statewide historical bid data from the past 5–8 yr? 

33. Do you analyze this data year over year and for extended periods to identify trends in bid 

pricing and note significant changes in bid pricing over time? 

34. If you note significant changes, do you research these changes and try and determine root 

causes?

OTHER

35. What else can you tell us about things that are occurring in your State that can help us 

understand a potential correlation between M&As and changes in competition, market 

share, and bid pricing? 

36. Do you have any studies or reports of this nature that you could share with us or describe 

to us (if they’re confidential in nature)? 

37. Are you aware of any DOT lawsuits with firms doing business in these bid item 

numbers?

38. Have you received complaints about anticompetitive bidding? Mergers or acquisitions? 

39. Has your State through any body, DOT, State AG, USDOJ Antitrust Division, 

investigated or brought a possible enforcement action?

40. Are you aware of any reported decisions in your State about these things? 

41. What advice do you have for States who are looking into these issues? 

149 

APPENDIX C. CASE STUDIES

CASE STUDIES OVERVIEW

This research project helped develop an understanding of the ways in which transportation 

construction industry mergers, acquisitions, or other consolidations impact the cost and quality of 

highway construction. The research project examined current conditions, barriers, and program 

issues related to competition in the highway material supply industry and used this information 

to create recommendations for appropriate changes and monitoring actions in public agency 

policy and administration. This research project investigated the challenges, costs, and risks 

associated with mergers, acquisitions, and other consolidations that impact material supply 

related to highway construction and maintenance. The scope of the research project involved 

collecting, organizing, and analyzing data from various regional and local transportation 

agencies and other data sources within the United States. The goal was to gain State-specific 

information on the state of the practice and to gather insights from selected States through a 

series of case studies. The effort also included the analysis of market and economic conditions of 

the State transportation region to assess the impact of supply costs and quality. 

ARIZONA

Case Study Background 

The research team reviewed documentation in advance pertaining to ADOT bidding and letting 

processes and conducted a site visit in November 2018. Participants included the State 

construction engineer, the assistant State construction engineer, and the deputy State engineer for 

statewide operations in the Infrastructure Delivery and Operations Division. Resident engineers 

in the southeast and north central districts provided supplemental information. The Arizona AZ 

UTRACS Registration is a business registration required for all firms that wish to work on 

federally funded transportation projects in Arizona (ADOT 2022). This registration is required 

for prime contractors, prime consultants, subcontractors, subconsultants, disadvantaged business 

enterprises (DBEs), and small-business concerns. All contractors must register with the site to be 

included on a bidder’s list. 

The ADOT Roadway Design Section prepares roadway technical design and construction 

documents for projects as well as technical expertise and design information during the design 

development and construction phases. ADOT roadway review supports delivery by reviewing 

scoping documents, permits, plans, specifications, and estimates to ensure they are constructible, 

cost-effective, and in compliance with the appropriate policies, standards, and procedures. All 

ADOT project development efforts incorporate project objective and need statements that 

document the performance objectives for the project and address practical design methodology 

that results in the most cost-effective design solution meeting the project objectives. ADOT

generally encourages a DBE participation level of approximately 4–6 percent. In many cases, the 

actual DBE participation rate is 8–11 percent. 

Most large contractors in the south central region own their own quarries and asphalt plants. The 

medium-sized contractors rely on the commercial plants in the area that operate independently. 

Most large and small prime contractors depend on commercial batching plants. In the southeast 
150 

and southwest regions, few prime contractors own their own quarries or plants, and few additions 

to quarries or asphalt plants have been added in the past several years. No shortages have been 

reported in recent years, even with increases in project development. 

ADOT regularly tracks bid unit price item histories and publishes searchable information on its 

Estimated Engineering Construction Cost website (ADOT n.d.a.). This system is also their 

primary system for estimating costs. ADOT did note that several industry mergers have occurred

in the Flagstaff region that influence the northern regions. These mergers resulted in the 

discontinuation of a supply of ground tire rubber by weight of total binder. The “new” suppliers 

have created some uncertainty in the markets according to ADOT representatives. ADOT is 

monitoring these recent acquisitions. 

ADOT has reported typical price increases consistent with market fluctuations. In the northern 

region, the price of asphalt binder has been greater than the price of other materials. No specific 

studies of the acquisitions have been made to date. However, a current research study is 

underway that is looking at the costs of the 10 largest State projects and identifying individual 

differences in particular bid item numbers.

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.1

 Projects containing bid item numbers of interest were 

extracted, sorted by date, and matched with contractor names and total project costs. Initial 

analyses aimed to explore bid item number price trends throughout the analysis period to identify 

any anomalies. Additionally, projects were analyzed by State region to assess any geographical 

influences on awarded projects. Within the materials of interest, aggregates are the area where

Arizona has seen the most acquisition activity, with companies purchasing sources or exclusive 

rights to control supply in certain geographic areas. However, none of this activity caused ADOT 

to look more deeply into it. Limited aggregate sources in the north central region of the State 

near Flagstaff, as well as disruptions in aggregate availability, have been experienced due to 

issues pertaining to the lease agreements with the Bureau of Land Management regarding selling 

aggregate. Despite these supply disruptions, no direct effects on pricing have been observed. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, and 

specifically for these items:

• Aggregate base class 1 (ADOT bid item No. 3030021). 

• Aggregate base class 2 (ADOT bid item No. 3030022). 

• Aggregate base class 3 (ADOT bid item No. 3030023). 

1

Data were mined by Oman Systems, Inc., and from State DOT bid prices posted on State websites or collected 

directly from State transportation agency sources. 
151 

• Aggregate subbase class 4 (ADOT bid item No. 3030024). 

• Aggregate subbase class 5 (ADOT bid item No. 3030025). 

• Aggregate subbase class 6 (ADOT bid item No. 3030026). 

• Asphaltic concrete, 3⁄4-inch mix end product (ADOT bid item No. 4160002). 

• Asphaltic concrete, 3⁄4-inch mix (ADOT bid item No. 4060006). 

• Asphaltic concrete, 1⁄2-inch mix special mix (ADOT bid item No. 4060015). 

• Asphaltic concrete, 1⁄2-inch mix end product (ADOT bid item No. 4160001). 

• Asphaltic concrete, 3⁄4-inch mix end product special mix (ADOT bid item No. 4160004). 

• Asphaltic concrete, 3/8-inch mix (ADOT bid item No. 406001).

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects for which the item was in use, 

whereas others did not. For example, some selected items yielded five or fewer projects using the 

item across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Aggregate Base Class 2 

The price trends for aggregate base class 2 (item No. 3030022) were analyzed for the analysis 

period. This item appeared 474 times during the analysis period; the minimum observed price 

was $9.00/CY, and the maximum observed price $480.00/CY, with a mean price of $60.59/CY

and a median price of $43.07/CY. The standard deviation in price was $56.20/CY. Figure 98

shows the price trends for aggregate base class 2.

Source FHWA.

Figure 98. Graph. Price trends—aggregate base class 2. 
152 

As can be seen in figure 98, several price spikes occur during the analysis period. On 9/25/2009 

a price of $381.00/CY was observed on project No. 2006076. The maximum price of 

$480.00/CY was observed on 10/28/2011 on project No. 2010125. Lastly, on 6/19/2015, a price 

of $421.00/CY was observed on project No. 2015027. 

Asphaltic Concrete 3⁄4-inch Mix

The price trends for asphaltic concrete 3⁄4-inch mix (end product) (item No. 4160002) were 

analyzed for the analysis period. This item appeared 57 times during the analysis period; the 

minimum observed price was $21.00/ton, and the maximum observed price was $58.30/ton with 

a mean price of $38.63/ton and a median price of $39.25/ton. The standard deviation in price was 

$10.43/ton, which is relatively small. Figure 99 shows the price trends for the analysis period. 

Source FHWA.

Figure 99. Graph. Price trends—asphaltic concrete 3⁄4-inch mix. 

As can be seen in figure 99, all price deviations for this item were relatively small during the 

analysis period, although a slight increase seems to have occurred in overall prices from 2011 to 

2016. 

In conclusion, while the quantitative analysis revealed instances of mathematically unbalanced 

bid prices, no apparent link to merger/acquisition activity was evident in that area.

Qualitative Analysis

Bidding Process and Analysis

ADOT publishes a Preparing the Bid and Other Bid Requirements Guidebook to encourage 

openness in its bidding process (ADOT n.d.b.). The guide emphasizes unit pricing and references 
153 

searchable historical price index published by ADOT, which includes pricing for all bid item 

numbers.

ADOT regularly compares bid item number prices with Colorado, New Mexico, and Nevada. 

Asphalt binder shortages in New Jersey and Wisconsin have influenced pricing in Arizona. 

Arizona has approximately 140 active projects, which include roughly 20–30 percent of the 

projects being completed at the local level (managed by ADOT). Projects in the Maricopa 

Association of Governments and Pima Association of Governments regions generally have 

higher unit prices, but review processes are the same. 

Healthy competition exists for projects. A project with fewer than four bids is rare, although 

ADOT reported some recent cases where only a single bid was received. In each case, the bid 

was given additional scrutiny and was awarded. ADOT undertakes a complete bid item analysis 

if the bid is outside of the engineer’s estimates by 15 percent. All estimates are based on 

historical costs. If the costs of a bid are close to or near the historical costs, additional scrutiny is 

not provided by ADOT personnel. Most contractors use their own sources for aggregates, 

asphalt, and concrete materials. Steel prices and concrete prices have been increasing, generally 

associated with fuel costs. Costs of trucking have substantially increased. 

Bid tabs are considered confidential until a job is awarded and then become public information. 

After award, a copy is sent to each bidder on the project. This process helps keep the entire 

contractor community informed. With the reliance on historical costs, the engineering estimates 

are also regularly reviewed to ensure few surprises occur in bid pricing. 

M&A Activity

While no formal monitoring of M&A activity in the State has been completed, several recent 

consolidations and mergers have occurred. These consolidations and mergers have been more 

evident in the northern part of the State and have influenced the availability of certain materials, 

although cost information is not evident. ADOT will continue to monitor the activity 

anecdotally. The influence on costs is not yet available. Labor costs are increasing but not as 

quickly as right-of-way acquisition costs, making new roadway alignments more challenging for 

ADOT’s overall development process. The growth of the State has required substantial new 

investments in capacity expansion projects. 

Interviewer Observations

ADOT was able to provide a good industry snapshot and economic condition assessment and 

regularly engages with the contractor community through trade associations. The construction 

materials industry in Arizona is healthy, with strong bid participation across the State. ADOT

regularly monitors bid item number prices and the impact on supply of certain binders and 

materials following the acquisition of smaller firms. They recommend strong public outreach to 

explain costs of projects as well as the time frame for project completions.

A more formalized and documented analysis of M&A activity would be important for the State. 

Engineering estimates rely exclusively on historical costs and, as such, provide limited 

opportunities to capture influences of the changes over time. Since the recent M&A activity is 
154 

still too recent to be reflective in a long-term trend, the research team recommends regular 

documenting of the bids emerging from these items. 

Summary

The objective of this case study was to quantify how construction industry mergers, acquisitions, 

or other consolidations are impacting the cost and quality of highway construction in the State of 

Arizona. ADOT regularly tracks bid unit price item histories and publishes searchable 

information, which is also the primary system used for estimating costs. ADOT did note that 

several industry mergers have occurred in the Flagstaff region that influence the northern 

regions. These mergers resulted in the discontinuation of a supply of ground tire rubber by 

weight of total binder. The “new” suppliers have created some uncertainty in the markets 

according to ADOT representatives. ADOT is monitoring these recent acquisitions. 

Overall, no significant price deviations were observed from the bid data during the analysis 

period, and ADOT has reported typical price increases consistent with market fluctuations. In the 

northern region, the price of asphalt binder has been greater than the price of other materials. No 

specific studies of the acquisitions have been made to date. 

COLORADO

Case Study Background 

The research team reviewed documentation in advance pertaining to CDOT’s bidding and letting 

processes and conducted a site visit in December 2018. Participants included the State materials 

engineer, the contracts manager for the engineering support group, project estimators, and the 

State contracts and markets analyst. Colorado’s various regions exhibit substantial differences in 

geology and geotechnical characteristics, and the Rocky Mountains divide up the various 

regions: the Front Range contains regions 1, 2, and 4 and covers a corridor running roughly 

along I–25, the Western Slope contains region 3, and the Central Mountains contain region 5. 

There are some counties that cross the three general geographic divisions. CDOT has 297 

prequalified contractors in its database in a record that is available online (CDOT 2022b). The 

State holds lettings every Thursday, and responses are generally strong, with at least three bids 

on nearly all projects. Occasionally, projects in remote regions have fewer than three bidders 

engaged. The industry is regularly assessed by both State and trade association representatives 

with a healthy mix of large and small firms.

CDOT’s Construction Contracts Team website includes documentation of rules and works 

through annual renewal processes (CDOT 2022a). Most firms are family owned, with a few 

publicly traded national firms that have a local presence. As with most States, many specialty 

firms regularly submit bids only on particular projects, with regional bidding evident in the 

Western Slope and Front Range regions. Many of the same smaller subcontractor firms appear 

on multiple teams during the bidding, if there is a specialty service. This situation is regularly 

monitored for any impact on pricing. In the Western Slope region, suppliers of aggregates are 

limited. With a limited number of aggregate quarries, several instances have occurred where 

access issues have raised prices. In the Front Range region, many quarries are available, so there 
155 

are fewer issues. In the past, Colorado owned many of its own quarries to help alleviate the 

concerns in the Western Slope region. 

CODOT reported that most contractors use their own sources for aggregates, asphalt, and 

concrete materials, but they do lease materials as well when necessary. Approximately 

70 percent of the contractors have their own quarries and coordinate work in that manner. Over 

the last 10 yr, material supplies have been challenged by issues associated with land use pressure 

and local resistance to opening new aggregate quarries. CDOT indicated that its contractor 

community makes extensive use of mobile asphalt plants. Polymer shortages in 2008–2009 

substantially increased prices in some mix designs that resulted in higher bid prices. CODOT 

noted some fly ash shortages have also occurred since it was included in more mix designs. 

Three cement producers serve most of the State, but concrete projects account for only 5 percent 

of all projects statewide. Concrete suppliers vary considerably across the State and range in 

capacity and output. Dozens of firms provide concrete across the State for vertical and horizontal 

construction. Varying grades of materials are also evident among concrete suppliers. 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.2

 Projects containing bid items of interest were extracted, 

sorted by date, and matched with contractor names and total project costs. Initial analyses aimed 

to explore bid item price trends throughout the analysis period to identify any anomalies. 

Additionally, projects were analyzed by region to assess any geographical influences on awarded 

projects. Unit price data were also available from CDOT and were analyzed against bid price 

data. Some projects in the construction cost data book from CDOT also included data regarding 

the number of total bidders and the comparison between these prices and the engineering 

estimates. Engineering estimates were largely lacking within the initial data collected for this 

research project as they were not readily available. The inclusion of limited engineering estimate 

data for Colorado allowed for some additional analysis. For example, in 2006, 12 projects 

included the low bid and other bidders with costs of 10 percent over the engineering estimate, 

and for 3 projects the low bid was greater than 15 percent over the engineering estimate. 

Observations of bid prices of items against unit price as reported for the corresponding year by 

CDOT did not yield any significant discrepancies. Items included in the analysis presented in 

chapter 2 for aggregate, asphalt, and concrete items saw prices fluctuate generally within $50 

above or below the unit price reported by CDOT. Data were also available showing item unit 

prices, engineering estimates, average bid, and awarded bid prices by item and project for each 

year. These data were extremely valuable; for example, for one project completed in 2011, a 

specific item such as HMA used in the project could be identified in the data. From here, the 

weighted average for the year of the engineering estimate ($58.83/ton), average bid price 

($63.22/ton), and awarded bid price ($56.90/ton) could be observed. Most price fluctuations 

were not unusual and could not be linked to any significant consolidation activity within the 

State. Fluctuations were instead likely due to location of materials and transportation costs.

2

Ibid. 
156 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, and 

specifically for these items:

• Structure backfill class 1 (bid item No. 206-00100). 

• Structure backfill class 2 (bid item No. 206-00200). 

• Structure backfill at specification (bid item No. 206-00050). 

• Structure backfill flow-fill (bid item No. 206-00065). 

• Emulsified asphalt slow setting (bid item No. 411-10255). 

• Asphalt cement performance grade PG 58-28 (bid item No. 411-03352). 

• Asphalt cement performance grade PG 58-34 (bid item No. 411-03355). 

• Asphalt cement performance grade PG 64-22 (bid item No. 411-03354). 

• Asphalt cement performance grade PG 64-28 (bid item No. 411-03342). 

• Asphalt cement performance grade PG 76-28 (bid item No. 411-03345). 

• Concrete pavement, 6-inch (bid item No. 412-00600). 

• Concrete pavement, 8-inch (bid item No. 412-00800). 

• Concrete pavement, 91⁄2-inch (bid item No. 412-00950). 

• Concrete pavement, 10-inch (bid item No. 412-01000). 

• Concrete pavement, 101⁄2-inch (bid item No. 412-01050). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects for which the item was in use, 

whereas others did not. For example, some selected items yielded five or fewer projects using the 

item across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Emulsified Asphalt Slow Setting

The price trends of emulsified asphalt slow setting (item No. 411-10255) were analyzed across 

the analysis period. The item appeared 559 times; the minimum observed price was $0.01/gal,

and the maximum observed price was $55.00/gal, with a mean price of $4.04/gal and a median 

price of $3.00/gal. The standard deviation in price was $4.58/gal. Figure 100 shows the price 

variation of this item over the analysis period. 
157 

Source: FHWA.

Figure 100. Graph. Price trends—emulsified asphalt slow setting. 

As can be seen in figure 100, there is one noticeable price spike, which is the maximum observed 

price of $55.00/gal. This spike occurred on project No. C20264, which had a bid date of 

2/5/2015 and took pace in Eagle County. Eagle County is located in region 3 of the State. 

Structural Backfill Class 1

The price trends of structural backfill class 1 (item No. 206-00100) were analyzed across the 

analysis period. The item appeared 255 times; the minimum observed price was $8.00/CY, and 

the maximum observed price was $300.00/CY, with a mean price of $44.80/CY and a median 

price of $32.81/CY. The standard deviation in price was $37.15/CY. Figure 101 shows the price 

variation of this item over the analysis period. 
158 

Source: FHWA.

Figure 101. Graph. Price trends—structural backfill class 1. 

As can be seen in figure 101, there are two noticeable price spikes, one on 2/8/2007 with the 

maximum price of $300.00/CY and one on 11/29/2012 with a price of $280.00/CY. The 

maximum price occurred on project No. C15968R in Mineral County, which is located in the 

southwest part of the State in region 5. The $280.00/CY price occurred on project No. C18955R 

in El Paso and Pueblo Counties, which are located in the central area of the State in region 2. 

This project was identified as a bridge project. No corresponding merger or acquisition activity 

could be traced to these increased costs.

Concrete Pavement 6-inch

The price trends of concrete pavement 6-inch (item No. 412-00600) were analyzed across the 

analysis period. The item appeared 81 times; the minimum observed price was $9.00/SY, and the 

maximum observed price was $1500.00/SY, with a mean price of $91.40/SY and a median price 

of $52.00/SY. The standard deviation in price was $179.39/SY. Figure 102 shows the price 

variation of this item over the analysis period. 
159 

Source: FHWA.

Figure 102. Graph. Price trends—concrete pavement 6-inch. 

The maximum observed price is the main visible price spike seen in the figure 102; this spike 

occurred in project No. C18996 bid on 2/21/2013 in Jefferson and Douglas Counties. Jefferson 

and Douglass Counties are located in the central area of the State in region 1. 

Challenges

Similar to challenges experienced with other State data, Colorado had items with disparate 

naming and item numbers. For emulsified asphalt, item No. 411-10255 includes items named 

emulsified asphalt slow set, emulsified, emulsified pavement slow set, and emulsified asphalt 

(slow setting). The same issue occurred with concrete pavement. Bid item No. 412-00600 yields 

four items: concrete pavement 6 inch, concrete, concrete class 6, and concrete pavement (6 inch).

Similarly, the item “concrete” yields 25 unique pay items with disparate units (each, SY, CY, 

and linear feet (LF)). While the quantitative analysis revealed instances of mathematically 

unbalanced bid prices, no apparent link to merger/acquisition activity was evident in that area.

Colorado’s Economy 

Aside from the bid data analysis, considerations were made regarding market health and overall 

economy conditions in Colorado during the analysis period. As can be seen in figure 103, 

Colorado experienced a drop in employment during the 18-mo recession experienced in the 

United States beginning in 2008. During this time, employment in Colorado dropped similarly to 

the national rate. Moving toward 2016, employment increased in Colorado slightly above the 

national average, with the exception of one significant drop toward the end of 2016. In 

June 2017, Colorado had the lowest unemployment rate in the United States at 2.3 percent. 
160 

Data source: Bureau of Labor Statistics. Graph source: FHWA. 

Figure 103. Graph. Colorado employment statistics (Bureau of Labor and Statistics 2023). 

When this information was pieced together with the project cost data, the drop in overall project 

costs between 2009 and 2012 seen in the data are consistent with the economic recession and its 

aftermath. The State Demography Office also reported an increase in Colorado’s population 

between 2012 and 2017. 

The construction sector also had just over a 5.0-percent increase, second only to the information 

sector (figure 104). Within the construction sector are three major subdivisions: residential, 

nonresidential, and nonbuilding (water treatment, highway work, etc.). Total employment in the 

construction industry in Colorado showed a 0.4-percent year over year decrease in 2017. In 

2016, the gross domestic product (GDP) for the construction industry accounted for 5.8 percent 

of Colorado’s total nominal GDP (Colorado State Demography Office 2022). Reports indicate 

that the construction industry remains healthy; however, a decline in residential construction has 

led to an overall slowing in the industry. 
161 

Data source: Bureau of Economic Analysis. Graph source: FHWA.

Figure 104. Graph. Gross domestic product growth in Colorado (Bureau of Economic 

Analysis 2023). 

Qualitative Analysis

Bidding Process and Analysis

CDOT uses AASHTOWare Project BidsTM software to facilitate the bidding process (AASHTO 

n.d.). Advertisements are updated every 2 w. This software product allows bidders to receive all 

proposal item schedules and tracks disadvantaged business enterprise elements. It also provides 

estimated cost tracking. All projects are submitted using Bid Express (2021). CDOT does 

publish plan holders lists before each project bid opening. Bid results are also published on the 

same site. 

CDOT did not express concerns to the research team about competition in its industry. They do 

have concerns about the public’s desire to have new quarries established—one of the reasons that 

CDOT has discontinued many of its internally controlled quarries. There is an emerging trend to 

require night work in urban areas, which makes asphalt production more expensive and which 

results in increased citizen complaints about the nighttime operations. CDOT did not report any 

issues with suspensions or debarments and noted that there have been some issues related to 

competition when economic times are strong and resort areas are looking for additional project 

work. 
162 

On average, proposals have more than four bids each, with few single bids. When analysis 

reveals bids out of alignment, the regional team is contacted to investigate details such as 

accuracy of bid information. When confirmation on the item in question is received, the bid is 

then analyzed using the unbalanced bid analysis process. The estimators are then brought into the 

discussion to determine any next actions. Ultimately, the region is responsible for the project and 

can decide to reject or award a bid following the additional scrutiny. Generally, the regions will 

also consider contractor capacity when reviewing bid information and discrepancies between bid 

prices and engineer’s estimates.

M&A Activity

Colorado does not formally track merger and acquisition activity in the State. However, in some 

instances the State adjusted specifications to broaden the number of aggregate providers that 

would be acceptable to improve competition. CDOT also noted that there have been a number of 

changes following tariff activities (namely on steel imports). Several years ago (outside of the 

scope of this review), there were instances of some potential bidding impropriety. These 

instances were addressed through self-monitoring and trade association inputs. 

By statute, CDOT must review all bids against their engineer’s estimate and complete additional 

review if there is a difference of greater than 15 percent before award. This review applies only 

on projects above $1 million. No more than 20- to 30-percent of bids go to the second level of 

justification and review under this statute. As such, bid items are not addressed individually in 

normal review (they are reported, however, and used in the engineer’s estimates for future 

projects).

In the past, CDOT has used its review of pricing to look at impacts of merger activity and 

changed some specifications to accommodate additional competitors. CDOT officials

participating in the case review noted that this review resulted in stable pricing for these items.

The contractor’s trade association works diligently to ensure that the industry maintains a 

positive reputation with CDOT and, as such, vocalizes concerns as needed. In one case, the 

industry took steps to get more competitive bids following an acquisition among aggregate 

suppliers. In this particular case, a voluntary effort to expand the bidding pool allowed prices to 

remain stable and inside the awardable range noted in the prior paragraph. The CDOT staff 

monitors its bidding process and will reject bids that are outside of the range, even on highpriority projects. 

Interviewer Observations

The Colorado Project Development Office recommends use of floating start dates for projects to 

allow for a strong, consistent project-letting schedule. CDOT recognized that their biggest 

challenges arose when projects were stacked together with limited contractor availability. CDOT 

also utilized incentive programs to increase the number of projects that contractors were able to 

work on concurrently, but this approach is not used frequently. Less than 20 percent of bids 

trigger additional review or concerns regarding bid item pricing or schedule adherence. 

One of the largest intervening factors in the ability to get projects out quickly came through the 

Responsible Acceleration of Maintenance and Partnerships (RAMP) program, which better 
163 

coordinated project expenditures and available funding, resulting in projects being initiated more 

quickly. Under the RAMP program, CDOT funded multiyear projects based on year of 

expenditure, rather than saving funding for the full amount of a project before construction 

began. The result saw that overall bid prices increased due to increases in demand. The program 

did not see an increase in new entrants to the CDOT market, and the agency recognized that it 

paid a premium on many projects as staffing was constrained among the contractor community. 

One additional observation was that CDOT felt strongly about engaging the trade associations 

and having self-monitoring. These practices allow the industry to police its own activities and 

encourage additional entrants. CDOT also noted that its ballot measures for infrastructure could 

increase the volume and timeline for new projects. The RAMP program results indicated that 

prices were higher during this period of new capital expenditures. 

Summary

The objective of this case study was to quantify how construction industry mergers, acquisitions, 

or other consolidations are impacting the cost and quality of highway construction in the State of 

Colorado. Colorado has substantial differences among its varied regions, with the Rocky 

Mountains dividing the State into three distinct areas (Front Range, Western Slope, and Central 

Mountains regions). Observations of bid prices of items against unit price as reported for the 

corresponding year by CDOT did not yield any significant discrepancies. Aggregate, asphalt, and 

concrete items saw prices fluctuate generally within $50 above or below the unit price reported 

by CDOT. Data were also available showing item unit prices, engineering estimates, average bid, 

and awarded bid prices by item and project for each year. Colorado does not formally track 

M&A activity in the State. However, in some instances the State has adjusted specifications to 

broaden the number of aggregate suppliers that would be acceptable to improve competition.

GEORGIA

Case Study Background 

In Georgia, many concrete and asphalt providers are located in the northwestern region of the 

State, while many of the aggregate materials locations are near the Atlanta metro area and out of 

State. Some major firms supplying materials to multiple States, including Tennessee, Georgia, 

Florida, and others in the area, also provided materials to many projects completed in Georgia 

between 2006 and 2016. Additionally, GDOT reported that prime contractors bidding on projects 

in the State range from small to very large and include family owned, multigenerational firms. 

Firms are allowed to bid on projects under $2.0 million without prequalification; however, every 

2 yr the number of firms prequalified to bid in functional areas is analyzed. While most firms 

have a specialization area, prime contractors perform multiple functions and must meet a 

30-percent prime requirement. The use of subcontractors varies from firm to firm. 

Although, during the recession in 2008, the number of prequalified bidders dipped lower; the 

number is now growing. In particular, bridge firms are growing in response to available funding, 

and firms are diversifying to add new skill sets to their qualifications, allowing them to compete 

for more work and increase their market share. The State’s DBE program includes firms 

representing a broad cross section of work types. GDOT is working to address an 
164 

overconcentration in DBE trucking as part of its project development process. Overall, the State 

is primarily using asphalt pavement with 90-percent asphalt and 10-percent concrete pavements 

on projects. 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.3

 Projects containing bid item numbers of interest were 

extracted, sorted by date, and matched with contractor names and total project costs. Initial 

analyses aimed to explore bid item number price trends throughout the analysis period to identify 

any anomalies. Additionally, projects were analyzed by region to assess any geographical 

influences on awarded projects. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items in the data may be related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for these items:

• Plain portland cement concrete pavement class 1 concentration, 10-inch thick (GDOT bid 

item No. 430-0200). 

• Plain portland cement concrete pavement class 1 concentration, 12-inch thick (GDOT bid 

item No. 430-0220). 

• Plain portland cement concrete pavement class 1 concentration, 11-inch thick (GDOT bid 

item No. 430-0210). 

• Aggregate surface course (GDOT bid item No. 318-3000). 

• Additional mechanically stabilized earth backfill (GDOT bid item No. 627-1180). 

• Grade aggregate base course, 10-inch (GDOT bid item No. 310-5100). 

• Grade aggregate base course, 12-inch (GDOT bid item No. 310-5120). 

• Grade aggregate base course, 14-inch (GDOT bid item No. 310-5140). 

• Grade aggregate base course, 4-inch (GDOT bid item No. 310-5040). 

• Grade aggregate base course, 6-inch (GDOT bid item No. 310-5060). 

• Grade aggregate base course, 8-inch (GDOT bid item No. 310-5080). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, whereas

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

3

Ibid. 
165 

Aggregate Surface Course 

The price trends for aggregate surface course (item No. 318-3000) were completed for the 

analysis period. The item appeared a total of 565 times; the minimum observed price was 

$0.01/ton, and the maximum observed price was $106.71/ton, with a mean observed price of 

$23.50/ton and a median observed price of $21.00/ton. The standard deviation in price was 

$10.22/ton (figure 105). 

Source FHWA.

Figure 105. Graph. Price trends—aggregate surface course. 

As can be seen in figure 105, there are two noticeable price spikes during the analysis period. 

The maximum price of $106.71/ton was observed on 12/15/2006 in project No. B12684-06 in 

Wheeler County, which is located in district 5 in the eastern area of the State. The second price 

spike of $100.00/ton was observed on 2/21/2014 in project No. B14343-14 in Fulton County, 

which is located in the northwestern area of the State near the city of Atlanta.

In conclusion, while the quantitative analysis revealed instances of mathematically unbalanced 

bid prices, no link to merger/acquisition activity in that area was apparent. 

Qualitative Analysis

Bidding Process and Analysis

GDOT does not use an official bid manual; however, future projects to be let are published 

18 mo ahead of time online, and a letting occurs every third Friday of each month. For projects 

greater than $2.0 million, prequalification is required; Bid Express and AASHTOWare Project 

SiteManager are used during the letting process (Bid Express 2021; AASHTO 2021). Prime

contractors are required to perform a minimum of 30 percent of the work (70 percent on 

resurfacing projects). Urban and rural areas are not considered separately. Urban areas such as 
166 

Atlanta, Savannah, Augusta, Macon, Chattanooga, Columbus, and Valdosta involve their 

metropolitan planning organizations in the bidding process. Bids are evaluated before award 

through the use of an elaborate multitiered manual process completed in conjunction with several 

committees. This process is also used to analyze unbalanced bids. Single bids are rare in Georgia 

and remained as such during the 10-yr analysis period. GDOT does not track the total number of 

bids per proposal, but experience suggests the total is an average of four to six bids per proposal. 

When bids or bid item numbers are identified as out of alignment with the engineer’s estimates 

(±10 percent), an estimation committee completes a manual review of the bid before passing the 

analysis on to an upper-level bid committee for final decisions.

While total bids per proposal are not tracked, the State does track and calculate average unit 

prices for each component of projects and has data for the past 5–8 yr. Statewide historical bid 

data for this period are also available, but the historical bid price data are not used to form 

current bid estimates. Significant changes in bid item number costs are analyzed if the 

occurrence lasts for over 12 mo. 

M&A Activity

M&A activity in the State is not generally monitored, but if a potentially significant merger or 

acquisition takes place, the agency may investigate further. No noticeable trends or correlations 

between any M&A activity and changes in number of bidders or annual average unit prices have 

been observed, and the prices on individual project bids have not been tied to M&A activity. 

GDOT does not feel that regularly reviewing M&A activity and any corresponding influences on 

bid pricing and reporting the data to the DOJ and industry stakeholders are their responsibility. 

However, no relevant data have been collected or observed. 

In terms of material suppliers, aggregates, asphalt, and concrete materials are incorporated into 

State DOT projects by quoted bid prices. Prime contractors do not own their own source 

materials but instead rely on independent aggregate suppliers. Material supplies and bid prices 

have remained relatively consistent over the past 10 yr, and while the State saw a fly ash 

shortage in 2004, no aggregate shortages were experienced during the analysis period. During 

this period, however, Georgia saw a growth in contractors due to a growth in their program, 

which added new funding of more than $1.0 billion per year in State-only fuel taxes. 

Two mergers were completed in the State in the last 14 yr in the aggregate market due to 

increasing program opportunities. However, this merger activity did not result in any issues with 

competition or bid price increases. While Georgia is not aware of any current lawsuits with firms 

or complaints regarding anticompetitive bidding, GDOT does recommend that States create an 

in-house estimation team for tracking such issues. Mergers may also lead to lower prices due to 

gains in efficiency. 

Interviewer Observations

Bidders are prequalified, but not by work type. GDOT has a prequalification list that is evaluated 

every 2 yr. In the recession of 2008, the number of prequalified bidders dipped lower, but the 

number is now growing. As mentioned in the Case Study Background section for Georgia, 

bridge firms are growing in response to additional funding, and firms are diversifying to be able 
167 

to compete for more work. Firms accept and use low quotes from subcontractors even when they 

compete against their own in-house estimates. Competitive aggregate sources outside of the State

are brought in, and a large private industry uses the aggregate sources as well.

Summary

The objective of this case study was to quantify how construction industry mergers, acquisitions, 

or other consolidations are impacting the cost and quality of highway construction in the State of 

Georgia. M&A activity in the State is not generally monitored, but if a potentially significant 

merger or acquisition takes place, the agency may investigate further. Two mergers were 

completed in the State in the last 14 yr in the aggregate market due to increasing program 

opportunities. However, this merger activity did not result in any issues with competition or bid 

price increases.

No noticeable trends or correlations between any M&A activity and changes in number of 

bidders or annual average unit prices have been observed, and the prices on individual project 

bids have not been tied to M&A activity.

MISSOURI

Case Study Background 

In the State of Missouri, some categorical qualifications exist for prime contractor makeup, and 

prequalified firms are listed by statute. Firm size varies from $15,000 to $150 million in annual 

revenue. The State has a mixture of small and national firms, and most are privately owned. 

Firms also include a large number of family owned, multigenerational firms. In general, 

approximately 200 to 300 firms are prequalified to bid based on given ratings in various 

functional areas. The changes in prequalification data are not closely scrutinized by MoDOT 

staff. While prime contractors do not tend to specialize in functional areas, general firms use 

many subcontractors; these relationships between prime contractors and subcontractors are 

generally based on regional characteristics, logistics, and specialization areas. At times, 

subcontractors also bid as prime contractors on the same job, especially in the northwest area of 

the State. 

Methods for obtaining materials such as aggregates, asphalt, and concrete vary, depending on if 

the prime firm owns the quarries. MoDOT has changed aggregate specifications such that some 

firms in several areas of the State cannot meet the high-end mix requirements. In the past 10 yr, 

quarries have consolidated, resulting in fewer family owned, independent quarries. As for 

individual project bid prices and annual average unit prices, MoDOT has made changes by 

bundling jobs to obtain more competition. MoDOT reported that, in general, aggregate prices 

have gone up over time, which could be due to national trends. Because of the rivers in the State, 

river sand is readily available, and no local shortages of other construction materials during the 

analysis period were noted. 
168 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed for Missouri.4 From these data, projects containing bid 

item numbers of interest were extracted, sorted by date, and matched with contractor names and 

total project costs. Initial analyses aimed to explore bid item number price trends throughout the 

analysis period to identify any anomalies. Additionally, projects were analyzed by region to 

assess any geographical influences on awarded projects. Statewide average unit prices are also 

calculated and published annually for each component of a job. The unit price data are available 

from MoDOT online and are built into the system to use as analysis. Unit price data from the 

past 5-8 yr have shown the steady effect of inflation as well as inconsistencies during the 

economic recession in 2008 when contractors left the State and competition suffered. Since that 

time, prices have risen due to inflation and the return of competition to the State. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for the following items:

• Bituminous pavement mixture PG 64-22 BP-1 (MoDOT bid item No. 4011209). 

• Bituminous pavement, 10-inch (MoDOT bid item No. 4010103). 

• Asphaltic concrete pavement SP125C, 11-inch (MoDOT bid item No. 4030404). 

• Bituminous pavement, 6-inch (MoDOT bid item No. 4010106). 

• Bituminous pavement, 8-inch (MoDOT bid item No. 4010101). 

• Asphaltic concrete mixture PG 70-22 (SP095CLP mix) (MoDOT bid item No. 4030011). 

• Asphaltic concrete mixture PG 64-22 (SP250E mix) (MoDOT bid item No. 4030301). 

• Asphaltic concrete mixture PG 64-22 (SP250C mix) (MoDOT bid item No. 4030306). 

• Backfill (MoDOT bid item No. 2026040). 

• Base concrete (MoDOT bid item No. 9029100). 

• Concrete pavement, non-reinforced, 10-inch (MoDOT bid item No. 5021110). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use while 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

The following subsections provide information on the bid-item analysis for bituminous pavement 

mixture PG 64-22 BP-1 as an illustrative example.

4

Ibid. 
169 

Bituminous Pavement Mixture PG 64-22 BP-1 

From the unit price data from 2016, item 4011209 (bituminous pavement mixture PG64-22 

BP-1) had an average quantity of nearly 17,000 tons with an average unit price of $51.14. The 

high bid price was $64.00, and the low bid price was $46.90. The item was used in eight bids. 

From the data mined by Oman Systems, Inc., and from State DOT bid prices posted on State

websites or collected directly from State transportation agency sources, the average unit price in 

projects was $111.51: the highest recorded price per ton of item 4011209 was $619.50, and the 

lowest price per ton was $41.21.5 Figure 106 shows the prices compared to the average annual 

unit price reported by MoDOT. 

Source: FHWA.

Note: MoDOT bid prices are posted on their website.

Figure 106. Graph. Unit price per ton versus bid price per ton of asphalt in 2016 

(MoDOT 2022). 

Base Concrete

The price trends of base concrete (item No. 9029100) were examined for the analysis period. 

During this time, this bid item number appeared 136 times. The minimum observed price was 

$1.00/CY and the maximum observed price was $5,000.00/CY, with a mean observed price of 

$1,362.31/CY and a median observed price of $1,138.50/CY. The standard deviation in price 

5

Ibid. 
170 

during the analysis price was $719.71/CY. Figure 107 shows these price trends for the analysis 

period. 

Source FHWA.

Figure 107. Graph. Price trends—base concrete. 

The minimum observed price of $1.00/CY occurred in project No. 150220-F05 with a bid date of 

2/20/2015 for a total quantity of 6.3 CY. This project occurred in St. Louis County, which is 

located in the St. Louis District in the eastern area of the State. The maximum observed price of 

$5,000.00/CY appeared twice in the data, but both are associated with the same project (project 

No. 120727-H01) bid on 7/27/2012 with a quantity of 0.4 CY in Bollinger County. Bollinger 

County is located in the southeast district in the southeastern area of the State. While the 

quantitative analysis revealed instances of mathematically unbalanced bid prices, there was no 

apparent link to merger/acquisition activity in that area.

The research team identified several cases where wide fluctuations in bid prices were evident. 

These fluctuations may be a result of unbalanced bidding on some projects. 

Qualitative Analysis

Bidding Process and Analysis

Bidding information is published with a link, but no formal manual exists, as the engineering 

policy guide covers this. Electronic bidding is used for the process and plans, and specifications 

books are all located online. Future projects are published with a letting schedule of 3-mo look 

ahead as well as a 1-yr surface transportation improvement plan. Lettings occur every month on 

Fridays at 11 A.M., and lettings are advertised in newspapers as well as Bid Express (2021). 

Eligible bidders are not published per proposal but are published if they opt to be. As for the 
171 

prime requirement, MoDOT requires a minimum of 40 percent of the work be performed by the 

prime contractor, which can be adjusted to the minimum FHWA amount of 30 percent, if 

required. MoDOT chooses to impose the higher requirement of its prime contractors. Kansas 

City, St. Louis, and Springfield are large urban areas that are considered separately due to 

concerns for night paving and other unique provisions. Obtaining aggregate in these urban areas 

is becoming difficult due to older pits in the urban areas of the State drying up as a result of large 

commercial use.

Oman Systems, Inc., software is used for bid evaluation in conjunction with human analysis 

(Oman Systems, Inc. 2023). While MoDOT does look at unbalanced bids, these data are not a 

major concern. If a problem arises, they analyze why the imbalance has occurred. The State does 

not have many single bids (only about 2 percent), and single bids are not historically tracked. 

However, the number of bids per proposal is analyzed over time, and trends are investigated by 

area and work type. Asphalt bids are combined, and alternate pavements are bid based on ranges 

where mix and thickness types are specified, making these bids hard to track. If an incoming bid 

seems out of alignment with the engineer’s estimates, the first step is to investigate if an error has 

occurred. This investigation is carried out via a multiple-group review, and the contractor may be 

interviewed. MoDOT estimation staff will also look into how the price was developed. 

M&A Activity

Within the last 5 yr, MoDOT has seen APAC® sell most of its presence to a local company, and 

many quarries were consolidated as a result. This new firm also specializes in paving. A few 

quarries are now owned individually, but several contractors own groups of quarries. The

competition is monitored. Regarding trends in these mergers and bid characteristics (including 

number of bidders and changes in prices), the number of bidders is tracked as a performance 

measure. Earthwork projects receive more than five or six bidders, whereas paving projects only 

receive three to four bidders. Small bridge projects, however, are quite competitive. Asphalt 

projects are relatively regional out of fixed plants, whereas larger firms use mobile plants (about 

half depend on mobile plants). Oftentimes, MoDOT will bundle jobs to create competition, 

especially in asphalt, by combining several smaller projects into a collective, single project 

bundle. Project bundling offers a comprehensive and accelerated delivery solution for addressing 

strategic program goals. It streamlines design, contracting, and construction; allows agencies to 

capitalize on economies of scale to increase efficiency; and supports greater collaboration during 

project delivery and construction. MoDOT uses project bundling procurements to award a single 

contract for multiple projects, thus enticing additional bidders. Generally, MoDOT studies the 

M&A activity in the State itself, and currently there are no actions taking place to limit M&A

activity.

Informally, the effects of M&A activity on bid pricing are observed to gauge what is happening 

within the industry. Activity is monitored indirectly, and the MoDOT construction office

approves job mix formulas for asphalt. The State does not do much concrete pavement work, so 

a spike in bid prices may correlate to asphalt, since aggregate areas are often consolidated. 

Opening new pits is difficult in the urban areas of the State, and, thus, areas such as St. Louis and 

Kansas City are using older quarries. Zoning and air quality standards for these quarries create 

issues as older quarries may have trouble complying with new standards. No suspensions or 

debarments have occurred in the State relating to bidding or material supplies. Regarding 
172 

economic changes, prices for cement and liquid asphalt have influenced discussions within the 

State. The State has not received complaints about anticompetitive bidding and has not 

conducted any investigations into these areas, nor is MoDOT aware of any reported decisions in 

the State about antitrust. 

Interviewer Observations

Large commodities influence the correlation between M&A activity and changes in competition, 

market share, and bid pricing. The cost of equipment necessary to start a construction business is 

prohibitive, which results in fewer competitive firms. 

Also, labor workforce shortages and expectations shift with changes in the market for workers, 

especially when new industries emerge quickly, such as shale oil drilling. Some transient asphalt 

paving is done, but this type of work is not beneficial for attracting workers. Night work in urban 

areas can cause traffic disruptions and raises noise complaint concerns. MoDOT has worked to 

increase the diversity of the workforce by including workforce diversity goals into projects. 

For States looking into M&A activity and the subsequent effects on pricing and competition, 

MoDOT recommends understanding the information ownership and contractor makeup and 

contractor locations. Transparency of information is also important, as is an understanding of 

what the project entails, necessary specifications, night work in urban areas, and other 

project-specific information. This type of information is tied into the bundling process that 

MoDOT relies on. MoDOT does not attempt to influence M&As in any way, but rather stays 

neutral and observes the process and aftermath effects. At this time, no concerns were expressed 

to the research team about these effects on competitive bid prices.

Summary

In the State of Missouri, firm sizes vary and include a mixture of small and national firms, as 

well as a large number of family owned, multigenerational firms. In general, the changes in 

prequalification data are not heavily analyzed. While prime contractors do not tend to specialize 

in functional areas, general firms use many subcontractors; these relationships between prime 

contractors and subcontractors are generally based on regional characteristics, logistics, and 

specialization areas. The State reports that large commodities influence the correlation between 

M&A activity and changes in competition, market share, and bid pricing. MoDOT recommends 

understanding the information ownership and contractor makeup and where contractors are 

located, as well as transparency of information for monitoring M&A activity and price effects.

OHIO

Case Study Background 

In the State of Ohio, prime contractors are prequalified following Ohio’s published thresholds for 

liability, insurance, and other requirements. Approximately 300 contractors bid on projects 

regularly. In the past 14 yr, the number of bidding prime contractors has not changed 

dramatically. Most firms are family owned, but there are some publicly traded firms and many 

family owned, multigenerational firms. Ohio DOT does keep a record of prequalification 

information from every year. For the past 20 yr, most firms have been general contractors that 
173 

have expertise; subcontractors are also used. Prime contractors often work with the same 

subcontractors over time as relationships build and strengthen. Occasionally, subcontractor firms 

will bid as prime contractors and vice versa. Some suppliers own their own quarries in Ohio and 

may even own multiple quarries. Most larger asphalt firms also own their own quarries, while 

managing smaller quarries with some leasing activity. Most large companies own quarries, 

which is more profitable, and these larger companies also own their own asphalt terminals. 

Concrete sources come from ready mix plants, typically located such that transport is about 1 h 

to any job site. Generally, concrete is not a major material in use for pavements in Ohio. 

Opening new quarries in Ohio is difficult due to zoning, and material redistribution yards are 

now appearing in the eastern part of the State. In the western part of the State, the quality of the 

quarries allows them to have stone available to ship to the east, where higher quality aggregate is 

more difficult to obtain. While no shortage has occurred, the transportation costs of material is 

high, although the State is unsure as to whether this affects bid prices.

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed for Ohio.6

 From these data, projects containing bid item 

numbers of interest were extracted, sorted by date, and matched with contractor names and total 

project costs. Initial analyses aimed to explore bid item number price trends throughout the 

analysis period to identify any anomalies. Additionally, projects were analyzed by region to 

assess any geographical influences on awarded projects. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items in the data may be related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials based 

on the original research project design, specifically for the following items:

• Concrete base, 10-inch (Ohio DOT bid item No. 305E14000). 

• Non-reinforced concrete pavement, 10-inch (Ohio DOT bid item No. 452E14010). 

• Reinforced concrete pavement, 10-inch (Ohio DOT bid item No. 451E15000). 

• Non-reinforced concrete pavement, 11-inch (Ohio DOT bid item No. 452E14100). 

• Reinforced concrete pavement, 11-inch (Ohio DOT bid item No. 451E15500). 

• Non-reinforced concrete pavement, 13-inch (Ohio DOT bid item No. 452E15010). 

• Non-reinforced concrete pavement, 6-inch (Ohio DOT bid item No. 452E10000). 

• Aggregate base (Ohio DOT bid item No. 304E20000). 

• Aggregate base as per plan (Ohio DOT bid item No. 304E20001). 

• Asphalt concrete base PG64-22 (Ohio DOT bid item No. 302E46000). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, while 

6

Ibid. 
174 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

6-inch Non-Reinforced Concrete Pavement

The price trends of 6-inch non-reinforced concrete pavement (item 452E10000) were analyzed 

for the analysis period. The item appeared a total of 71 times during this period. The minimum 

observed price was $29.55/SY, and the maximum observed price was $378.69/SY with a mean 

observed price of $57.52/SY and a median observed price of $50.00/SY. The standard deviation 

in price was $42.02/SY. Figure 108 shows these price trends during the analysis period. 

Source FHWA.

Figure 108. Graph. Price trends—6-inch non-reinforced concrete pavement. 

As can be seen in figure 108, this maximum price of $378.69/SY is the only significant price 

spike during the analysis period. This price was observed in project No. 120087 with a bid date 

of 2/9/2012 in Union County with a total quantity of 5 SY. Union County is located in Ohio 

DOT district 6 in the central area of the State. 

Aggregate Base 

The price trends of aggregate base (item No. 304E20000) were analyzed for the analysis period. 

The item appeared a total of 3,123 times during this period. The minimum observed price was 

$1.00/CY, and the maximum observed price was $1,061.71/CY. The mean observed price was 

$59.51/CY with a median observed price of $50.00/CY and a standard deviation price of 

$41.67/CY. Figure 109 shows the price trends for this item during the analysis period. 
175 

Source FHWA.

Figure 109. Graph. Price trends—aggregate base.

The minimum observed price of $1.00/CY occurred in project No. 100210 on 4/15/2010 with a 

total quantity of 50 CY This project was in Brown County, located in Ohio DOT district 9 in the 

south central area of the State. 

The maximum observed price of $1,061.71/CY occurred in project No. 120087 on 2/9/2012 with 

a total quantity of 1 CY. This project was in Union County, located in Ohio DOT district 6 in the 

central area of the State. The other higher price observed was $725.00/CY, which occurred in 

project No. 100185 on 4/8/2010 with a total quantity of 4 CY. This project was in Clinton 

County, located in Ohio DOT district 8 in the southwestern area of the State. The research team 

identified no corresponding merger or acquisition activity in this area during this period. In 

conclusion, while the quantitative analysis revealed instances of mathematically unbalanced bid 

prices, there was no apparent link to merger/acquisition activity in that area.

Qualitative Analysis 

Bidding Process and Analysis 

Ohio DOT uses AASHTOWare software as well as Bid Express, an online information service 

for bidding provided by Infotech, Inc., but no internal manual exists (AASHTO 2021; Bid 

Express 2021). Two years of potential projects are published, and projects are let every 2 w, with 

an annual average of 22 to 23 lettings per year (with some special lettings). The State law

requires advertisement of lettings in the newspapers for 2 w. Prime contractors in Ohio are 

required to perform a minimum of 50 percent of the work, but at times it may be adjusted down 

to 30 percent with FHWA approval in accordance with defined policies. FHWA requires a 
176 

minimum of 30 percent. Several rural areas are considered single-bid areas for asphalt; 

additionally, unique aggregate areas in Cleveland acquire materials from Canada. Aggregate 

sources are plentiful in the western part of the State, but scarcer in the east, which causes some 

additional transportation costs to be required in that part of the State. Ohio DOT’s analysis of 

their price information finds higher costs of materials for projects in the eastern part of the State

as a result. Ohio DOT uses the AASHTOWare software’s data analytics to evaluate bids before

award.

For irregular bids, Ohio DOT looks at low bids relative to the engineer estimate and then 

compares them to other projects as well as historical data. Ohio DOT benchmarks this 

information against the engineer estimate and looks for bid anomalies or deviations that could be 

causing the issue. There is a low percentage of single bids (approximately 2–3 percent). Major 

bid item numbers are used per unit (SY for concrete and CY for asphalt). If bids appear out of 

alignment with expected engineer estimates, the item of work is analyzed and the project 

manager in the district is contacted. Sometimes contractors will be contacted as well to find the 

source of the imbalance. Complementary bidding is rare and hard to prove. Ohio DOT calculates 

and publishes average unit prices annually and calculates construction cost indexes to analyze 

trends. Every 6 mo, any significant changes are analyzed to identify root causes. 

M&A Activity

Ohio DOT uses AASHTOWare Project SiteManager Construction Management System to

monitor M&A activity (AASHTO 2021). When Ohio DOT adds a new firm, the competition

field changes. The State has many portable plants that move around. These buy-outs are for 

plants and parts as opposed to consolidation of asphalt companies; the consolidation side does 

not have much activity in the asphalt industry. More than 10 yr ago, some large acquisitions and 

some smaller firms were consolidated in the last 10 yr due mostly to firm owners retiring. Two 

plants at the same location have since become joint ventures, and both are large firms. They 

decided to close one plant and consolidate into a joint venture. The joint venture firms still 

compete in areas other than the venture functional area. The State does not utilize much concrete 

pavement for projects beyond bridges and small incidental work, such as sidewalks.

Ohio DOT reported that in the asphalt industry, national binder price fluctuations drive the prices 

of the material, but these fluctuations have not been linked to any merger or acquisition activity. 

In rural areas, Ohio DOT noted that asphalt providers face limited competition, which could lead 

to higher prices. The concerns over expensive asphalt pricing were reported by Ohio DOT to the 

DOJ, but no updates are available at this time. Currently, no policies exist within the asphalt area 

to remedy concerns about the high prices; some project bundling has taken place to effect 

competition by combining single-bid counties in separate districts for multiple bids. Ohio DOT

believes that monitoring M&A activity and the subsequent effects on asphalt pricing should be 

done close to where the work is taking place, and most of this monitoring is done internally. 

Zoning and permitting of quarries is an issue for Ohio DOT. There are a fixed number of 

quarries; therefore, hauling and distribution centers pop up quite often. Economically, there have 

been oil shortages and housing and fracking industry issues within the State that have affected 

bids. Ohio DOT reported that the competing workforce requirements for fracking and fossil fuel 

extraction have been cited as possible cost factors for past project activities.
177 

Interviewer Observations

Costs seem affected by factors such as supply and demand, and at times aggregate shortages 

occur due to high use, which is usually a short-term issue. Firms augment their aggregate sources 

to meet specifications, and much material swapping among firms takes place. Smaller firms then 

struggle, as they cannot keep their aggregate supplies within specifications, and monitoring this 

process it costly for them. Again, Ohio has mostly asphalt pavements within the State, and 

concrete is mostly used in projects for bridges, curbs, and gutters. 

Summary

In the State of Ohio in the past 14 yr, the number of bidding prime contractors has not changed 

dramatically. Most firms are family owned, multigenerational firms, with some publicly traded 

firms. Ohio DOT does keep a record of prequalification information from every year. Some 

suppliers own their own quarries in Ohio and may even own multiple quarries. Opening new 

quarries in Ohio is difficult due to zoning. While no shortages have occurred, material

transportation costs are high. The State is unsure whether this circumstance affects prices. Ohio 

DOT believes that monitoring M&A activity and the subsequent effects on asphalt pricing 

should be done close to where the work is taking place, and most of this monitoring is done 

internally. Costs seems most affected by supply and demand, as well as occasional shortages.

OKLAHOMA

Case Study Background 

The research team reviewed documentation in advance pertaining to the Oklahoma DOT bidding 

and letting processes, and a site visit was conducted in February 2019. Participants included the 

State construction engineer, assistant State construction engineer, an office engineer/division 

engineer, Oklahoma DOT materials division engineer, and the assistant division engineer, 

materials. This case study summarizes that visit and describes Oklahoma DOT’s approaches to 

understanding and evaluating the construction materials industry in their State. 

In the State of Oklahoma, trends of total project prices from 2006 to 2016 and bid item number 

prices in comparison to relevant unit prices yielded no significant price deviations attributable to 

merger or acquisition activity. Additionally, initial contacts with the State showed no significant 

concerns regarding pricing effects of M&A activity. Just over 250 pre-qualified firms are

available for bidding projects in Oklahoma (252 as of May 2019). More than two-thirds of these 

firms would be categorized as small- to medium-sized companies. Oklahoma DOT does not 

track whether these firms are publicly traded, but attendees noted that most are family owned, 

multigenerational firms. Several national firms do have a presence in Oklahoma. This market is 

relatively steady, with three to four new entrants each year and some minor reduction due to 

retirements and consolidations. 

Contractors generally maintain some common areas of expertise or regional focus. Large 

pavement jobs attract the most bidders and can attract a cross section of companies from across 

other regions. The Oklahoma DOT Office of Construction monitors and collects industry 

information on an anecdotal basis. This information includes some recent acquisitions by 

pavement companies of bridge contractors and some similar acquisitions by structural 
178 

contractors of paving companies entering into the paving business. Oklahoma DOT does not 

report a regular process of tracking entrants into their prequalified programs. If a name change 

occurs, it is entered in the AASHTOWare Project SiteManager Construction Management 

System software that Oklahoma uses (AASHTO 2021). 

Oklahoma DOT is currently unaware of any current studies of M&A activity in the State. The 

Materials Division approves aggregate and sand sources and maintains an approved list of 

quarries and their source locations on the Oklahoma website (Oklahoma DOT n.d.a.). A list of 

asphalt plants is also maintained (Oklahoma DOT 2022). Asphalt plants must be reinspected 

every year, per Oklahoma DOT Asphalt Plant Inspection Policy. 

Oklahoma has reported a shortage of acceptable fly ash over the years, but no reported shortages 

in other construction materials. Oklahoma is very plentiful in high quality material sources and 

often exports aggregates to Kansas and Texas. The State has three cement plants, and the case 

study participants generally viewed availability of products as exceptional. Some individual 

designs for structures relied on a single provider for prestressed beams. However, a design 

change in the early 2000s eliminated the shortages associated with this particular design. 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed for Oklahoma.7

 From these data, projects containing bid 

item numbers of interest were extracted, sorted by date, and matched with contractor names and 

total project costs. Initial analyses aimed to explore bid item number price trends throughout the 

analysis period to identify any anomalies. Additionally, projects were analyzed by region to 

assess any geographical influences on awarded projects. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for the following items:

• Asphalt concrete type S2 (PG 64-22 OK) (Oklahoma DOT bid item No. 411(S2) 5930). 

• Asphalt concrete type S3 (PG 70-28 OK) (Oklahoma DOT bid item No. 411(S3) 5940). 

• Asphalt concrete type S4 (PG 64-22 OK) (Oklahoma DOT bid item No. 411(S4) 5960). 

• Unclassified backfill (Oklahoma DOT bid item No. 501(D) 6353). 

• Controlled low-strength material backfill (Oklahoma DOT bid item No. 501(G) 6309). 

7

Ibid. 
179 

• Asphalt concrete, 4-inch (22) (Oklahoma DOT bid item No. 411 4520). 

• Asphalt concrete, 6-inch (23) (Oklahoma DOT bid item No. 411 4540). 

• Portland cement concrete for pavement (Oklahoma DOT bid item No. 414(I) 5275). 

• Granular backfill BR-1 (Oklahoma DOT bid item No. 501(F) 6352). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, while 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Asphalt Concrete Type S4 (PG-64-22 OK) 

Asphalt concrete type S4 (item No. 411(S4) 5960) appeared 872 times during the analysis 

period. The minimum observed price during this time was $22.00/ton, and the maximum 

observed price during this time was $695.00/ton, with a mean observed price of $83.87/ton and a 

median observed price of $70.95/ton. The standard deviation in price during this period was 

$48.71/ton. Figure 110 shows these price trends for the analysis period, which for this item is 

only between 2006 through 2011. This item was not used in 2012–2016. 

Source FHWA.

Figure 110. Graph. Price trends—asphalt concrete. 

The minimum price of $22.00/ton with a quantity of 1,053 tons occurred in a project (job 

No. 100461) bid on 7/22/2010 in Washita and Custer Counties. Washita and Custer Counties are 

located in Oklahoma DOT division 5 in the eastern area of the State. The maximum price of 
180 

$695.00/ton with a quantity of 25.5 tons occurred in a project (job No. 100040) bid on 1/28/2010 

in Marshall County. Marshall County is located in Oklahoma DOT division 2 in the south central 

area of the State. The other high price of $630.00/ton with a quantity of 5 tons occurred in a 

project (job No. 90556) bid on 9/17/2009 in McClain County. McClain County is located in 

Oklahoma DOT division 3 in the central area of the State. In conclusion, while the quantitative 

analysis revealed instances of mathematically unbalanced bid prices, there was no apparent link 

to merger/acquisition activity in that area. 

Qualitative Analysis

Bidding Process and Analysis

Oklahoma prepares estimates based on item prices and quantities. They use a weighted average 

item price report by item, region, and quarter to determine prices during the prior 18-mo period. 

This engineer’s estimate is furnished in compliance with 61 O.S.§ 116 B (OK Stat. 2022). The 

engineer’s estimate is composed of units expressed as mathematical averages for work units that 

may be required for a project. The mathematical averages are derived by adding dollar amounts 

bid for work under a specific item code over the preceding 18 mo within a specific field division 

and dividing the resultant total by the number of bids included. The resultant average unit 

amount does not and is not intended to portray difficulties or resources, which may be required 

to perform any specific unit of work on any specific project. 

A two-person team analyzes bids independently. These reviewers compared recommendations 

after the bid opening. A small number of projects receive single bids: often every project will 

have four to five bids. Additional review and scrutiny is triggered if bids are 10 percent lower or 

5 percent higher. In some cases, projects may be rebid rather than awarded if there is a large 

difference between the estimate and bid prices. Oklahoma strongly discourages “penny bids” and 

will review these bid item numbers closely for unbalanced bidding. 

Historical data on bidding are available on the Oklahoma DOT website, spanning at least 5 yr by 

every month of lettings (Oklahoma DOT n.d.b.). In general, the Construction Division will watch 

prices and not intervene unless some level of unacceptable pricing is noted. Some cases where 

there have been large differences have been explained by revisiting engineering estimates against 

the actual prices.

M&A Activity

While no formal monitoring of M&A activity in the State is completed, name changes do 

occasionally occur and are usually identified in the prequalification list generation input into the 

AASHTOWare Project SiteManager product (AASHTO 2021). 

Generally, Oklahoma did not identify name changes as a major issue. The agency noted that 

competition remains vigorous, and prices have not changed dramatically, even in cases where 

there were consolidations. New entrants to the market and some external pressures from 

out-of-State contractors have assisted Oklahoma DOT in keeping costs contained to consistent 

levels with surrounding States and national benchmarks. 
181 

Interviewer Observations

Oklahoma has stable sources of construction materials and regularly monitors pricing changes in 

its bid processes. Abnormalities are identified quickly, and additional research is completed as 

needed. A stable contractor pool provides a variety of services, and very few bids attract limited 

competition. Urban and rural contractors across the regions exhibit economic health, and the 

results provide strong labor markets. Some concerns arise in specialty contract areas, such as 

commercial drivers. When markets for oil and gas rise, costs of projects increases as commercial 

drivers’ license holders become scarce or more expensive.

Summary

In the State of Oklahoma, trends of total project prices from 2006 to 2016 and bid item number 

prices in comparison to relevant unit prices yielded no significant price deviations attributable to 

merger or acquisition activity. Additionally, initial contacts with the State showed no significant 

concerns regarding pricing effects of M&A activity. Oklahoma is currently unaware of any 

current studies of M&A activity in the State. The Materials Division approves aggregate and 

sand sources and maintains an approved list of quarries and locations. Despite a shortage of 

acceptable fly ash over the years, the State has no reported shortages in other construction 

materials. Oklahoma is plentiful in high-quality material sources and often exports aggregates. 

OREGON

Case Study Background 

During the initial research project analysis (before the formal case study interview described 

herein), investigation into consolidations in Oregon revealed that most M&A activity in the State

occurred more than 14 yr ago. In addition, this activity was not captured in the dataset built by 

the researchers under this research project, which included an analysis period from the first 

quarter of 2006 through the third quarter of 2016. Activity during the analysis period included 

two major firms purchasing aggregate source companies and suppliers. The ODOT offers State

sources of materials in the eastern part of the State, whereas the western part of the State has 

robust competition from private sources. 

The State of Oregon is divided into five regions. Between 43 and 141 projects were awarded 

each year of the study period, and 170 unique firms were awarded contracts during the analysis 

period. Regions 2 and 3 (in the western portion of the State) saw higher project costs during the 

analysis period than other regions in the State. The State of Oregon has quarry and/or gravel pits 

located in every county; Columbia, Crook, Douglas, Jackson, and Linn Counties contained a 

larger number of quarries than the remaining counties. These counties are in regions 2, 3, and 4, 

which are located in the western and central part of the State. Wheeler, Wallowa, Sherman, 

Jefferson, Hood River, Gilliam, and Coos Counties contain the fewest quarry locations. The 

initial analysis of market conditions and supplier status (condition of the supplier in terms of 

market share, size, or location that would explain any advantages or correlations to higher costs 

for bid materials discussed) did not provide a clear explanation for the higher costs outside of the 

more urbanized and densely populated areas in the western part of the State. The data analyzed 
182 

in this case study did not reveal any significant pricing anomalies, as described in the 

Quantitative Analysis section below. 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.8

 Projects containing bid item numbers of interest were 

extracted, sorted by date, and matched with contractor names and total project costs. Initial 

analyses aimed to explore bid item number price trends throughout the analysis period to identify 

any anomalies. Additionally, projects were analyzed by region to assess any geographical 

influences on awarded projects. For example, in 2009, more than one-third of projects took place 

in region 2 of the State (35.8 percent); primary commercial exports from region 2 include gravel, 

concrete, and asphalt mixtures, indicating robust supplies of these materials. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for these items: 

• Emulsified asphalt concrete mixture (ODOT bid item No. 0735-01000000M). 

• PG 64-22 asphalt in HMAC (ODOT bid item No. 0745-0620000M). 

• PG 70-22 asphalt in HMAC (ODOT bid item No. 0745-0640000M). 

• Reinforced concrete pavement (ODOT bid item No. 0755-0109000J). 

• Reinforced concrete pavement, 6-inch (ODOT bid item No. 0755-0111000J). 

• Reinforced concrete pavement, 8-inch (ODOT bid item No. 0755-0113000J). 

• Reinforced concrete pavement, 9-inch (ODOT bid item No. 0755-0114000J). 

• Reinforced concrete pavement, 10-inch (ODOT bid item No. 0755-0115000J). 

• Reinforced concrete pavement, 12-inch (ODOT bid item No. 0755-0117000J). 

• Plant mix aggregate base (ODOT bid item No. 0641-0107000M). 

• Aggregate base (ODOT bid item No. 0640-0100000M). 

• 1⁄4-inch aggregate base (ODOT bid item No. 0641-0108000M). 

• 1⁄2-inch aggregate base (ODOT bid item No. 0641-0110000K). 

• 1-inch aggregate base (ODOT bid item No. 0641-0115000M). 

• 11⁄2-inch aggregate base (ODOT bid item No. 0641-0117000M). 

• 2-inch aggregate base (ODOT bid item No. 0641-0119000M). 

• 21⁄2 inch aggregate base (ODOT bid item No. 0641-0121000M). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, while 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

8

Ibid. 
183 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Of these aggregate items, 1-inch aggregate base, 11⁄2-inch aggregate base, and 21⁄2-inch aggregate 

base items yielded enough items for comparative analysis. The 1-inch aggregate base (item 

No. 0641-0115000M) was used in 25 unique projects across all 10 yr of the analysis period, 

except for 2012, which is ideal for price trend analysis. Twenty-two of these bids used the unit of 

tons for the 1-inch aggregate base, whereas three used cubic yards. Due to these discrepancies, 

the cubic yard items were converted into tons and price per ton using the conversion factor of 

1.5 tons per cubic yard. Quantity versus bid price was analyzed, and no apparent correlations 

surfaced between these two values. A sample variance of $78.86 occurs among all 25 projects 

bid prices. 

Figure 111 shows the bid price variation of 1-inch aggregate base across the 10-yr analysis 

period. A major price spike was seen in early 2010, where the bid price went up to $55/ton. The 

United States Geological Survey (USGS) reports included in the FHWA article, Wherefore Art 

Thou Aggregate Resources for Highways?, indicated that production and use of aggregates 

declined during the economic downturn between 2008 and 2010, whereas aggregate demand and 

production in 2007 was quite high (Meininger and Stokowski 2011). The USGS also indicated 

that, as of 2011, the State of Oregon had trap aggregate resources in the State as well as access to 

some granite sources in neighboring States. The team was unable to determine a specific reason 

for the price spike. The USGS also reported that many sources of aggregate in parts of the 

Pacific Northwest do not meet physical and durability requirements, which may limit use and 

require the State to seek other sources. 

Source: FHWA.

Figure 111. Graph. Bid price variation—1-inch aggregate base. 

ODOT, which has nearly 700 aggregate sources statewide (including both quarries and gravel 

and sand sites), also focuses heavily on extracting materials sustainability with the goal to 
184 

reduce, reuse, and recycle materials to proactively monitor material availability for construction 

and maintenance work. Through the State’s sustainability efforts, the State analyzed aggregate 

resources and worked to protect these supplies from competing land uses and protect the natural 

resources within the State. 

Challenges

Reinforced Concrete Pavement

Selecting relevant bid item numbers from the large, unsorted dataset to match the materials being 

analyzed was challenging. The dataset was built by merging Oman Systems, Inc., and State

website bid data, and subject matter experts were needed to assist in the bid item number 

selection process. Similar bid item numbers were labeled in many different ways in the 

State-supplied data. Although items such as “structural concrete” were of interest for analysis 

and comparison, within the Oregon data, “structural concrete” does not appear in bid tabulations. 

In Oregon, more than 20 unique bid item numbers were determined to be structural concrete 

items. To explore price trends of these bid item numbers across years, individual items were 

selected; however, if an individual bid item number was not used in each of the 10 analysis 

years, assessing price trends covering gaps, varying geographies, and other factors was difficult. 

As an example, Oregon uses the bid item number “reinforced concrete pavement” (item 

No. 0755-0109000J). During the analysis period, this bid item number was used in four winning 

projects won by four different contractors: two in 2007, one in 2008, and one in 2009. Table 97

shows the bid prices for this item, as well as the quantities used in the projects.

Table 97. Reinforced concrete pavement (item 0755-0109000J) bid prices. 

Bid Date Quantity (SY)

Bid Price

(Dollars) Project County

Total Bid Cost

(Dollars)

5/24/07 576.0 79.00 Linn 11,988,520.40

10/11/07 735.3 90.00 Baker 12,487,827.25

3/13/08 231.0 120.00 Lane 9,393,792.92

6/18/09* 1155.0 54.00 Lane 405,082.00

6/18/09* 930.0 88.00 Lane 405,082.00

*These two lines are part of the same project.

Linn and Lane Counties are in ODOT region 2, and Baker County is in ODOT region 5. The 

highest bid price for reinforced concrete pavement occurred on the project in October 2007. This 

project also used the smallest quantity of reinforced concrete pavement. 

Emulsified Asphalt Concrete Pavement 

Another example of the challenge of analyzing trends involves the item “commercial asphalt 

concrete pavement” (item No. 0740-0100000M). This item was used in three unique projects 

won by three unique contractors, all in the spring and summer of 2015. 

Also, within the data are similar items, such as “emulsified asphalt concrete mixture” (item 

No. 0735-010000M), which appears seven times in seven unique projects won by five 
185 

contractors (one contractor won three of the projects using this item during the analysis period). 

These seven projects were bid in 2006, 2007, 2008 (three projects), 2009, and 2014. Across these 

years is a sample variance of $6.23 among all seven projects’ bid prices and no apparent trend in 

prices over time (i.e., prices were not steadily rising or falling, and prices did not have an 

apparent spike). Prices did not appear to vary based on quantity of the item in the bid, as seen in 

table 98. Additionally, with so few items across a 10-yr period, assessing trends with such small 

sample sizes is difficult. While there does seem to be a correlation between item quantity and bid 

price in table 98 (i.e., least quantity has highest bid price and highest quantity has lowest bid 

price), with four projects and five total items, the sample size remains quite small.

Table 98. Emulsified asphalt concrete mixture bid prices.

Bid Date

Quantity 

(Ton-G)

Bid Price

(Dollars) Project County

Total Bid Cost

(Dollars)

1/26/06 29,500 14.85 Union 4,735,680.28

2/22/07 62,000 19.60 Deschutes 4,967,314.00

2/14/08* 15,720 12.92 Grant 2,498,481.50

2/28/08* 16,000 12.93 Harney 4,494,046.46

4/17/08* 16,000 14.91 Harney, Grant 4,568,615.02

4/16/09 74,000 14.95 Harney 5,562,894.75

10/30/14 43,000 18.00 Malheur 4,485,994.50

*Bids awarded to the same contractor

Union, Grant, Harney, and Malheur Counties are in ODOT region 5, and Deschutes County is in 

ODOT region 4. While the counties in which the projects took place are available in the data, the 

supplier information for any bid item numbers in the dataset is not available or included in the 

dataset. Therefore, it is not clear if transportation to the site is a factor in the costs. Without 

substantial effort for supplier tracking, such granular analysis is not possible on price data alone. 

Two other asphalt items were also analyzed to find bid item numbers that occurred more often in 

the dataset: PG 70-22 asphalt in HMAC (bid item No. 0745-0640000M), which appeared 

170 times in the dataset during the analysis period, and PG 64-22 asphalt in HMAC (bid item 

No. 0745-0620000M), which appeared 192 times in the dataset during the analysis period. Both 

of these items had frequent price variations during the analysis period, but both showed an 

overall downward trend in pricing when trend lines were produced on the graphs as shown in 

figure 112 and figure 113. 
186 

Source: FHWA. 

Figure 112. Graph. Price trends—70-22 asphalt in HMAC (item No. 0745-0640000M). 

Source: FHWA. 

Figure 113. Graph. Price trends—64-22 asphalt in HMAC (item No. 0745-0620000M). 

These price variations were analyzed to determine whether any could be attributable to merger or 

acquisition activity. Many of the apparent drops in price were found to be due to $1.00 and 

penny bids. For the 70-22 asphalt, for 88 of the 170 times the item appeared, it was bid at 

$1.00/ton or less; 18 of the projects with these $1.00/ton or less bids had project costs over the 

average project cost for projects using this item. For the 64-22 asphalt, for 107 of the 192 times 

the item appeared, it was bid at $1.00/ton or less; 25 of the projects with these $1.00/ton or less 

bids had project costs over the average project cost for projects using this item. The $1.00/ton 

and less bids were removed to assess the price trends without these low prices; when this 
187 

assessment done for the 70-22 asphalt, the trend in prices appears to increase over the analysis 

period, as would be expected due to inflation. 

As can be seen in figure 114, the item is still bid at a low price in several instances. Ultimately, 

these variations were determined to be unrelated to M&A activity. While the quantitative 

analysis revealed instances of mathematically unbalanced bid prices, no apparent link to M&A

activity in that area occurred. 

Source: FHWA.

Figure 114. Graph. Price trends—70-22 asphalt in HMAC without dollar/penny bids. 

Oregon’s Economy 

Information about the state of the economy and labor market in Oregon during the analysis 

period was also investigated to see if any economic factors could be linked to items seen in the 

data. Many States experienced major economic repercussions due to the recession and global 

economic downturn from December 2007 to June 2009. Oregon’s Office of Economic Analysis 

examines four main sources for job data: the monthly payroll employment survey, the monthly 

household survey, monthly withholding tax receipts, and the quarterly census of employment and 

wages. 

Each industry’s pre-recession peak varied somewhat based on variation in the economic impacts 

of the recession. For example, the construction industry began losing jobs earlier than other 

industries and earlier than the recession’s official start date, according to the National Bureau of 

Economic Research (Lehner 2023). Due to the housing bubble during the recession, materials 

such as wood, construction, and mining were negatively affected, and the effects on material 

prices during those years are important to consider. Additionally, transportation equipment 

manufacturing suffered the worst job cuts. No usable correlation with this data and the case study 

data was found. 
188 

Due to the inconclusiveness of these quantitative analyses, the focus shifted to a more qualitative 

understanding of the impacts of merger activity and how the State of Oregon monitors for, and 

addresses, these impacts. Additionally, a better understanding of the qualitative side of the 

project can aid in future data collection and database development to support future exploration 

into M&A indicators and impacts. 

Qualitative Analysis

The data for Oregon did not reveal any major price anomalies or evidence of consolidation 

activity. For this reason, a more qualitative investigation became the focus of the case study 

interview. While the data may not display any major trends associated with consolidation 

activities, the State of Oregon may have other measures and methods for identifying competition 

issues.

Bidding Process and Analysis

Contractors in Oregon run the gamut from small, family owned firms to large mega-firms. Some 

large contractors that were once small were publicly traded, and some are multigenerational. The 

State at one time had more than 400 prequalified contractors but has seen a steady decline of 

unique bidders over the years to around 90 today. Most prime contractors specialize in one or 

two functional areas, and prime contractors usually use the same subcontractors over time. 

Subcontractors do not often also bid as prime contractors on the same jobs, but it has happened. 

The State does analyze unbalanced bids.

Materials quotes are generally obtained from the nearest producers or suppliers or are created 

through work with subcontractors by developing the cost of supplying material from 

ODOT-offered publicly owned or controlled sources. Prime contractors do supply materials 

themselves, generally through the use of subcontractors for crushing; otherwise, they use major 

suppliers’ quotes for their bids. Material supply has not changed much in the last 10 yr, but in the 

mid-2000s quite a few acquisitions influenced material supply. In addition, a decrease in supply 

in some areas has occurred as existing sources have been depleted, and the identification and 

permitting of new sources has been much more difficult. In areas where major companies come 

in and buy smaller suppliers, some changes have occurred in project bid prices and annual 

average unit prices. However, data collected for this project were not conclusive in documenting 

M&A activity impacts on competition. Increased land use restrictions make permit aggregate

sites difficult, and Portland, OR, is an area where materials are transported by barges due to this 

issue (mostly gravel). 

The list of future projects to be let is published on the ODOT website (Oregon.gov. n.d.a.). 

Twenty-five bid openings per year occur, on average, that are spread out sporadically throughout 

the year (between zero and three lettings per month) on Thursdays. The prequalification 

requirements and process are found via the prime contract prequalification link on the Bid and 

Awards page of the website, and lettings are advertised 3 w prior to bid closing (complex jobs 

may be advertised earlier) (Oregon.gov. n.d.b.). ODOT has been using Bid Express since 2008 

and are trying to move to 100-percent electronic bids; proposals under $1 million are still 

50-percent paper bids. Prime contractors are required to do 30 percent of the work with their own 

forces. The Portland, OR, urban area and the rural areas of the southwest and far eastern part of 
189 

the State are often considered separately. Urban areas tend to have more development and zoning 

restrictions that limit aggregate mining operations. Aggregates and gravel have to be transported 

by barge into the Portland area.

In rural areas, exclusive farm use zoning and more environmental restrictions and regulations 

have limited areas of permitted mines. Rural areas have more land available, but big suppliers 

can buy up smaller firms in these rural areas, which creates bid competition areas as well. Due to 

this issue, ODOT has provided State-owned aggregate source options on many projects in both 

the southwest and eastern areas to increase the availability of aggregates to all contractors 

bidding in these areas. 

ODOT uses FHWA’s Guidelines on Preparing Engineering Estimates, Bid Reviews, and 

Evaluation as general guidelines for bid evaluation prior to award (FHWA 2021a). During the 

case study interview, ODOT reported having an extensive homegrown software system that is 

used for bid analysis and the Federal guidelines policy (Oregon.gov 2022). The makeup of single 

bids varies, and, in general, a slight increase in single bidders has been seen, as the number of 

unique prime bidders has declined over the years. Specifically, the number of single bidders can 

rise in areas of supplier consolidation, and then it can decrease as State-provided sources are 

implemented to increase competition. There are on average 4 bids per proposal for about 

110 proposals per year. 

If a bid seems irregular (under or over the engineer’s estimate by more than a certain threshold or 

considerably different than other competitive bids), it will be reviewed. Bid item numbers are 

automatically reviewed if the price is ±25 percent of the engineer-estimated bid price and if the 

total dollar amount for an item is ±$20,000 of the engineer-estimated bid total for that item. If a 

proposal comes in significantly over the estimate, ODOT has a confidential process to evaluate it 

for award, rejection, or rebid. Statewide average unit prices are calculated and published 

annually, and the past 5–8 yr of data are available. Additionally, ODOT has statewide historical 

bid data reports dating back to 2007 available on request. An in-house software system is used to 

analyze data and identify trends in bid pricing. Many problems in this area have been traced back 

to M&A activity in various regions of the State. 

M&A Activity

ODOT is reactive when unit prices go up. The agency tries to determine the cause (such as 

reduced number of bidders, reduced number of suppliers, or other factors), and the State’s 

Material Source Program was initially set up to manage a network of publicly owned or 

controlled material sources across the State. As part of that program, the State looks at 

distribution of sites, evaluates ownership, and uses history to offer viable publicly owned or 

controlled sources for use on projects. This program unofficially tracks mergers of aggregate 

suppliers based on information in the news or information provided by contractors or permitting 

agencies. Their effort is not focused on price increases or the number of bidders, but rather aims 

to get a better understanding of the market and who the players are. Trends and correlations 

between M&A activity and changes in bidders have been noticed when suppliers of aggregates 

buy up smaller firms and minimize the numbers of suppliers/bidders. ODOT noted that many 

times these larger firms buy smaller firms and do not change the name, so the smaller firms can 
190 

raise supply costs and stay under the radar. ODOT has worked with the DOJ on some M&A

activity analysis and supplies information to the DOJ as requested. 

When M&A activity limits supply to only one or a few suppliers and unit pricing is affected, 

ODOT has (where practical) attempted to offer publicly owned or controlled material sources to 

stimulate competition. While not always used, the existence of a publicly controlled materials 

source available to all bidders has sometimes resulted in lower material costs. Local zoning has 

disallowed quarries or asphalt plants to open in various areas, which affects competition. The 

process to permit a material source in Oregon can be very time- and cost-intensive. Acquisitions 

were focused on companies that had large reserves; many small companies cannot afford to 

negotiate the land use process associated with permitting of a new source. 

ODOT has studied bid prices and mining permits issued by the Oregon Department of Geology 

and Mineral Industries to see if there are correlations. In general, where there are fewer permits, 

there can be a higher price structure. This result occurs many times in rural areas where local 

suppliers have been bought and consolidated the supply, thereby leading to minimal land 

available for new companies looking to apply for mining permits. ODOT reported a lawsuit with 

a firm doing business in construction material supply items about 10 yr ago involving a 

bid-rigging case, but no recent complaints have been received about anticompetitive bidding or 

cost issues. Striping companies were also investigated, and the Secretary of State audited ODOT 

to investigate penny bids 2 yr ago; ODOT is now looking at combining asphalt concrete and mix 

asphalt items to combat these penny bids. Some methods ODOT has used to deal with these 

issues include providing publicly owned or controlled aggregate sources for projects in areas 

with minimal bidders and minimal suppliers. They have also bid projects more often (weekly or 

biweekly) instead of monthly, which has provided more bidders, as measured by the trends after 

this change was made (mainly due to bonding companies allowing more companies to bid most 

proposals in the smaller lettings).

Interviewer Observations

ODOT indicated that companies have spent much money in the last 10 yr targeting acquisitions 

to secure material reserves to position themselves to better control market pricing in key areas of 

projected future transportation growth. Five to eight agencies bid their own projects. ODOT is 

unique in that the agency has an extensive homegrown software system that is used for bid 

analysis; this software could be used to look into M&A activity correlations and tracking. 

ODOT also expects the new AASHTOWare software suite will provide a greater ability to 

research bid data for investigating and understanding the effects of M&A activity (AASHTO 

2021). This analysis would be especially useful in areas that have minimal sources or minimal 

competition and could be a good organization model and provide example processes that other 

States could use to increase competition and keep prices in balance. 

Summary

The objective of this case study was to quantify how construction industry mergers, acquisitions, 

or other consolidations are impacting the cost and quality of highway construction in the State of 

Oregon. During the initial analysis (before the case study interview), investigation into 
191 

consolidations in Oregon revealed that most M&A activity in the State occurred more than 14 yr 

ago and was not captured in the dataset built. The data used in this project did not reveal any 

significant pricing anomalies. Due to the inconclusiveness of these quantitative analyses, the 

focus shifted to a more qualitative understanding of the impacts of merger activity and how the 

State of Oregon monitors and addresses these impacts. 

ODOT is reactive when unit prices go up. The agency tries to determine the cause, and the 

Material Source Program unofficially tracks mergers of aggregate suppliers based on information 

in the news or information provided by contractors or permitting agencies. When M&A activity 

limits supply to only one or a few suppliers and unit pricing is affected, ODOT has (where 

practical) attempted to offer publicly owned or controlled material sources to stimulate 

competition. The material source information is not available in the bid data, so determining the 

source of individual bid item numbers is not possible. ODOT has also addressed competition 

issues by bidding projects more often (weekly or biweekly).

TENNESSEE

Case Study Background 

During the analysis period from the first quarter of 2006 through the third quarter of 2016, 

TDOT has seen some merger and consolidation activity in construction materials. In June 2017, 

Martin Marietta announced the acquisition of Bluegrass Materials Co., which has 33 locations 

across the mid-Atlantic and Southeast United States, including locations in Chattanooga and 

Calhoun, TN. As the data for this study are from 2006 to 2016, the impact of these changes has 

not yet been determined. TDOT has also provided detailed mapping of quarry locations and 

producer facilities available on its website (TDOT n.d.b.). 

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.9

 Projects containing bid item numbers of interest were 

extracted and sorted to attempt to match the data with contractor names and total project costs. 

This step was challenging for the Tennessee data due to the lack of bid dates in the data. Initial 

analyses aimed to explore bid item number price trends throughout the analysis period to identify 

any anomalies. Additionally, projects were analyzed by State region to assess any geographical 

influences on awarded projects. 

TDOT has seen some consolidation activity during the analysis period. One firm made a 

purchase that resulted in a controlling share in the supply and cost of river sand in the Nashville 

market. This activity was brought to the attention of the DOJ Antitrust Division. Another firm 

purchased a company, including their quarries and other facilities, located in the eastern part of 

the State, which resulted in a controlling market share in this area. Another firm purchased 

several local family owned, ready-mix plants in the middle part of Tennessee; approximately 

15 yr prior, another firm performed similar purchasing activity. The results of these acquisitions 

are that these two firms own approximately 75 percent of the approved ready-mix plants in the 

9

Ibid. 
192 

middle and eastern parts of the State. Another purchase made within the past several years 

resulted in a majority of the market share of precast pipe and drainage structures being controlled 

by one firm. TDOT reported some concerns of the effects of this activity on bid pricing and 

competition, but no changes to contract language or statues were made as a result. Precast pipe 

and drainage structure items in the dataset were then compared to unit price data reported by 

TDOT to examine any pricing effects due to the merger activity. This analysis revealed that bid 

prices for these items were not significantly higher than the unit price reported by TDOT; most 

were right around or up to $50 higher than the reported unit price. Additionally, a variety of 

firms were seen in the winning bid data, suggesting that one firm does not hold market control 

over the others. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for these items:

• Portland cement concrete pavement, 8-inch (TDOT bid item No. 501-01.02). 

• Portland cement concrete pavement, 10-inch (TDOT bid item No. 501-01.03). 

• Portland cement concrete pavement (TDOT bid item No. 501-01.06). 

• Portland cement concrete pavement replace (TDOT bid item No. 501-01). 

• Portland cement concrete pavement (plain), 14-inch (TDOT bid item No. 501-01.07). 

• Fine aggregate no. 10 backfill (TDOT bid item No. 771-05.86). 

• Fine aggregate no. 10 backfill (TDOT bid item No. 771-13.56). 

• Asphaltic concrete surfaces (hot mix) grade E (TDOT bid item No. 411-01.07). 

• Asphalt cement (tack coat (TC)) (TDOT bid item No. 403-02). 

• Asphalt cement (BPMB-hot mix) grading A (TDOT bid item No. 307-01.02). 

• Asphalt cement (BPMLC-hot mix) grading C (TDOT bid item No. 307-01.11). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, while 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Asphalt cement (TC) (bid item No. 403-02) appears 18 times across the analysis period in 

18 unique projects. Figure 115 shows the trend in prices of this item over the analysis period. 

The data for Tennessee contain 5-digit codes for bid date instead of a day/month/year format, 

making ascertaining when projects occurred difficult. 
193 

Source FHWA.

Figure 115. Graph. Price trends—asphalt cement (TC) (item No. 403-02).

The average bid price per ton of asphalt cement is $427.29/ton, and the median bid price is 

$399.99/ton, with a minimum bid price of $1.00/ton and a maximum bid price of $1,100.00/ton. 

The deviation in prices for this item is $330.37/ton. The minimum price of $1.00/ton appeared 

twice in the dataset on two projects: 3 tons at $1.00/ton in Dickson County, and 38 tons at 

$1.00/ton in Dyer, Henry, and Weakley Counties. 

Dickson County is located in region 3 of the State; Dyer County, Henry County, and Weakley 

Counties are all located in region 4 of the State. The maximum price of $1,100.00/ton appeared 

once in the dataset on one project: 2 tons at $1,100.00/ton in Shelby County. Shelby County is 

located in region 4 of the State. 

Challenges

The main challenge in the Tennessee data is that the bid dates are listed as 5-digit numbers 

instead of dates. There appeared to be no logical mapping of these numerical codes that could be 

used to match them to specific dates. The job numbers were used to identify the contractor 

names and total costs. This feature made the initial matching process as well as subsequent 

sorting by date range efforts difficult. Additionally, like many other States, Tennessee has data 

items with similar names and different item numbers, making analysis difficult as the differences 

between these items is unclear. For example, as seen in the item list, two items have the name 

“fine aggregate no. 10 backfill” with two unique item numbers, as well as two items have the 

name “fine aggregate no. 10 bedding/backfill” with have two unique item numbers. 

In conclusion, while the quantitative analysis revealed instances of mathematically unbalanced 

bid prices, no links to merger/acquisition activity were apparent in that area.
194 

Qualitative Analysis

Bidding Process and Analysis

Within Tennessee, prime contractor firms vary from small to large, with 8–10 large, publicly 

traded prime firms that consistently bid. The State also has some family owned, 

multigenerational firms that bid. There are 800 prequalified firms; fewer than 50 percent of these 

firms bid with TDOT, as many get prequalified to meet bid requirements for other local 

municipality or government agency bids. TDOT has 35 work classification codes listed on the 

final page of the prequalified contractors list, which is available on the DOT’s website (TDOT 

n.d.a.). Contractors are required to check which work classification(s) applies to their company. 

TDOT does not analyze changes in these classifications and does not assign dollar amounts in 

selected classifications. They instead rely on bonding companies to govern the amount of work 

they will bond for any given contractor. Contractors are limited in prequalification only if 

performance issues exist, sanctions exist, or if the contractors self-limit themselves. Many 

grading contractors have bridge divisions, some with asphalt paving capabilities. Prime 

contractors are required to perform 30 percent of the contract with their own forces, and many 

prime contractors use the same subcontractors over time, depending on location, type of work, 

and past work experience. Sometimes subcontractors also bid as prime contractors on the same 

jobs, depending on job type. For example, a bridge replacement may need a subcontractor that 

can pave, but the paving subcontractor may also do the bridge work and bid as a prime. 

As for materials, most bidders secure quotes from the geographically nearest producers and 

suppliers. TDOT noted that the selections then have to trickle down to suppliers (e.g., HMA

producers will purchase liquid asphalt from suppliers). Some prime contractors also own quarries 

for aggregates, and some prime contractors also have their own ready-mix operations. Over the 

last 14 yr, no noticeable change in the supply of aggregates, HMA, or concrete has occurred. 

However, the suppliers have changed, and fly ash shortages have occurred. Seeing changes in 

bid prices for raw materials is difficult since bid item numbers are inclusive of several items 

(e.g., labor, equipment, materials, overhead). Fly ash shortages during the 10-yr analysis period 

may have affected bid prices.

TDOT publishes a bid manual on their website, which also includes a 3-yr plan for future 

projects to be let (Nashville DOT and Multimodal Infrastructure 2021). Each year about eight or 

nine regular lettings occur approximately every 7 w on Fridays. TDOT requires all prime 

contractors (except mowing and litter removal contractors) to be licensed with the Tennessee 

Department of Commerce and Insurance, Board for Licensing Contractors, not for bidding, but 

before a contract is awarded. Contractors self-proclaim the functional areas they want to bid in 

during the prequalification process. Eligible bidders are not published in a list. TDOT uses Bid 

Express during the letting process and moved to AASHTOWare bidding in 2019 to expedite the 

process (Bid Express 2021; AASHTO 2021). Some rural areas experience less competition, 

which is generally not an issue. 

For bid analysis, a systematic software process is used to create a bid tab. Small groups meet to 

go over proposals for award, and area engineers assist in the evaluation of bids in their area to 

make recommendations at the group meeting. TDOT’s policy on construction contract awards 
195 

addresses unbalancing and provides examples of both mathematically and materially unbalanced 

bids; however, no other process other than reviewer evaluation occurs. The policy on unbalanced 

bids is listed on the bidding website. In a letting in December 2018, 29 percent of proposals were 

single bids; the percentage is usually higher in the February through March lettings when most 

resurfacing projects are let. Single-bid proposals average about 8–10 percent over the 

engineering estimate, and some areas with single asphalt plant sources receive more single bids. 

Bid data are tracked, but fluctuations in cost of materials (especially bituminous materials) can 

distort analysis of data trends, especially in the number of bids per proposal. HMA, aggregate 

base, concrete pavements, and structural concrete are major bid item numbers. If a bid item 

number seems out of alignment with the engineer’s estimates or other bidders submitting on that 

opportunity, the quantity is checked, and bidders are contacted and queried about bid details of 

the item(s) in question. Complementary bidding has been encountered, but it is speculative and 

not much can be done to address it. Average unit prices for the past 5–8 yr are available online, 

as well as in an internal average price program that can be used (TDOT n.d.c.). Historical bid 

data from the past 5–8 yr are also available, but these data are not generally analyzed unless a 

need is identified. In the past, structural concrete was identified as an item of interest, and soon 

rebar is due to be reviewed because of new tariffs.

M&A Activity

M&A activity is monitored. For example, sand supplier Hunter Materials was acquired by Pine 

Bluff Materials, Vulcan bought US Aggregates, Bluewater bought Vulcan/US Aggregates 

through a DOJ agreement, and Bluewater bought Hoover in middle Tennessee. Both M&As and 

increases in prices of rock products have occurred over the past few years. However, data to 

define this relationship have not been found. The State has found that rising prices often follow 

M&A activity, but this activity is not necessarily the cause. TDOT has worked with the DOJ on 

some M&As, and general discussions on how to minimize impacts on competition and pricing 

have taken place. However, bids are only rejected if costs are excessive. Projects have been 

bundled to attract other bidders and to create competition (free enterprise versus

monopolization). The State feels that producing good estimates and compiling average unit 

prices across years for bid analysis and year-over-year comparisons is important. 

Local zoning has disallowed quarries or asphalt plants to open in areas that would affect 

competition. The interview noted that zoning boards may allow some new quarries or asphalt 

plants that are connected in some way to existing uses, but not others that are located near new 

aggregate sources. Therefore, maximum competition has not taken place. Hurricane Katrina in 

2005 affected bids, and recent shortages on electrical contractors due to Hurricane Maria in 2017 

have also affected bids. Tariffs and embargos have also affected steel prices, but there have been 

no issues with cement supply. 

Overall, TDOT believes that competition is good, and while occasional rumors about 

anticompetitive bidding have surfaced, no complaints have been received. In the interview, it 

was noted that there was an incident of the U.S. DOJ versus US Aggregates/Vulcan and 

Bluewater in 2017; the Vulcan acquisition of US Aggregates was approved with conditions 

including the divestitures of key holdings (material sources) in key areas. TDOT was allowed to 
196 

give opinions on the competition issues due to this acquisition, which helped the DOJ identify 

key divestitures they required to allow the acquisition to occur. 

Some ideas that TDOT have used included breaking projects up to increase competition on a 

smaller set of projects rather than one large project. Alternative bids have been used as well, such 

as for hot-in-place versus cold-in-place asphalt. TDOT has also tried bundling projects to get 

contractors to move into an area that has minimal competition.

Interviewer Observations

A few large firms have bought up many smaller firms in the aggregates, concrete, and asphalt 

paving industry, but much of this activity was more than 14 yr ago. Tennessee reported little 

difficulty in meeting realistic average percent variance goals compared with State-estimated 

project pricing. The State has very few concrete paving jobs, as most of the pavement build in 

the State is asphalt. What little concrete is used is in urban areas and ramps. Contractors can 

volunteer to participate in constructability reviews during the design phase, typically after 

50 percent of the design is complete. These results are then published to aid in material needs 

planning for future lettings. The State has completed about six or seven design-build projects and 

two construction manager/general contractor projects. 

Summary

During the analysis period from the first quarter of 2006 through the third quarter of 2016, the 

TDOT has seen some consolidation activity. One firm made a purchase that resulted in a 

controlling share in the supply and cost of river sand in the Nashville market. Other purchases 

caused some concerns on the effects on bid pricing and competition, but no changes to contract 

language or statues were made as a result. Most of the consolidation activity was more than 14 yr 

ago. Bid data are tracked, but fluctuations in cost of materials (especially bituminous materials) 

can distort analysis of data trends, especially in the number of bids per proposal. 

TDOT has used a variety of strategies to increase competition. In some cases, they have broken 

up projects to increase competition on a smaller set of projects. Alternative bids have been used 

as well, such as hot-in-place versus cold-in-place asphalt. TDOT has also tried bundling projects 

to get contractors to move into an area that has minimal competition.

WISCONSIN

Case Study Background 

In the State of Wisconsin, trends of total project prices during the analysis period from the first 

quarter of 2006 through the third quarter of 2016 and bid item number prices compared to 

relevant unit prices yielded no significant price deviations attributable to merger or acquisition 

activity. Initial contacts with the State showed no significant concerns regarding pricing effects 

of M&A activity. During the case study interview with WisDOT, further investigation into the 

bidding process, contractor makeup, bidding analysis, and M&A activity was completed. 

WisDOT reported having a variety of firms, including some family owned, multigenerational 

firms in specialty areas such as concrete and bridge construction. From year to year, the number 

of prequalified bidders in one functional area does not vary much, and the ratings given are 
197 

identified on the prequalification lists published on the WisDOT website (Wisconsin DOT 

n.d.c.). 

Many prime contractors tend to specialize in functional areas, but several firms do cross over to 

work in other areas. Generally, firms utilize a large number of subcontractors, but in recent years 

firms have become more flexible in specialization areas to meet the 30-percent prime 

requirement. During selection of subcontractors, cost is the greatest determination factor, and at 

times joint ventures do occur to meet the 30-percent prime requirement.

Quantitative Analysis 

Data Analysis 

Data from 2006 to 2016 were analyzed.10 Projects containing bid item numbers of interest were 

extracted, sorted by date, and matched with contractor names and total project costs. Initial 

analyses aimed to explore bid item number price trends throughout the analysis period to identify 

any anomalies. Additionally, projects were analyzed by region to assess any geographical 

influences on awarded projects. Identifying contractor and pricing for Wisconsin was relatively 

simple, as the project numbers were sequential based on date. WisDOT was also responsive to 

requests for additional data, including historical unit price data, for the analysis period. The 

number of contractors included in the dataset ranged from 56 to 115 per year during this time 

period. 

Data for items of interest were sorted from the larger database and analyzed for any trends. Bid 

prices, quantities, and counties where work occurred were considered. While the data included 

multiple items for each material (e.g., 10 or more unique items may be in the data related to 

structural concrete), many were not used on projects across enough years to provide trend 

information. This analysis process was repeated across many sets of construction materials, 

specifically for these items:

• Base aggregate dense, 3⁄4-inch (WisDOT bid item No. 305.011). 

• Base aggregate dense, 3⁄4-inch base aggregate (WisDOT bid item No. 305.0115). 

• Base aggregate dense, 11⁄4-inch (WisDOT bid item No. 305.012). 

• Base aggregate dense, 11⁄4-inch (WisDOT bid item No. 305.0125). 

• Base aggregate dense, 3-inch (WisDOT bid item No. 305.013). 

• Asphaltic material PG58-28 tack coat gal 31.0 (WisDOT bid item No. 455.0105). 

• Asphaltic material PG64-28 (WisDOT bid item No. 455.012). 

• Asphaltic material PG64-28P (WisDOT bid item No. 455.014). 

• Asphaltic material PG64-28P GAL (WisDOT Bid item No. 455.024). 

• Concrete pavement, 8-inch (WisDOT bid item No. 415.008). 

• High early strength (HES) concrete pavement, 8-inch (WisDOT bid item No. 415.108). 

• Concrete pavement, 9-inch (WisDOT bid item No. 415.009). 

10Ibid. 
198 

• HES concrete pavement, 9-inch (WisDOT bid item No. 415.109). 

• Concrete pavement, 71⁄2-inch (WisDOT bid item No. 415.0075). 

• Asphaltic concrete pavement type E-0.3 (WisDOT bid item No. 460.11). 

For each State, bid item numbers of interest were selected for price trend analysis. Of the items 

of interest, some yielded multiple years and multiple projects where the item was in use, while 

others did not. For example, some selected items yielded five or fewer projects using the item 

across the analysis period. Stronger trend information is gleaned with larger sample size; 

therefore, larger sample size items (items yielding more results) were selected for detailed 

analysis in this case study. 

Base aggregate 3⁄4-inch (item No. 305.011) appeared 1,689 times during the analysis period. The 

average, median, deviation, and quartile prices for the entire analysis period are shown in 

Table 99. 

Table 99. Bid price statistics for item 305.011, 2006-2016. 

Average 

Price

($/ton)

Deviation 

($/ton)

Min. Price

($/ton)

25th

Percentile

($/ton)

Median 

Price

($/ton)

75th

Percentile

($/ton)

Max. Price

($/ton)

16.24 10.45 0.01 11.00 14.10 18.00 150.00

The minimum price of $0.01/ton appeared quite low; this low price/ton appeared three total 

times in the bid data: 

• 6,100 tons at $0.01/ton bid on 5/13/14 in Jackson County. 

• 8,500 tons at $0.01/ton bid on 3/10/15 in Brown County. 

• 5,300 tons at $0.01/ton bid on 4/14/15 in Dane County. 

Jackson County is located in the northwest region of the State, Brown County is located in the 

northeast region of the State, and Dane County is located in the southwest region of the State. 

The maximum price of $150.00/ton appeared twice in the bid data: 

• 2 tons at $150.00/ton on 5/11/10 in Milwaukee County. 

• 10 tons at $150.00/ton on 7/14/15 in Dane County. 

Milwaukee County is located in the southeast region of the State and Dane County is located in 

the southwest region of the State. 

Asphaltic material PG58-28 tack coat gal 31.0 (item 455.0105) appeared 1,046 total times in the 

bid data during the analysis period. The average, median, deviation and quartile prices for the 

entire analysis period are shown in Table 100. 
199 

Table 100. Bid price statistics for item 455.0105, 2006-2016. 

Average 

Price

($/ton)

Deviation 

($/ton)

Min. Price

($/ton)

25th

Percentile

($/ton)

Median 

Price

($/ton)

75th

Percentile

($/ton)

Max. Price

($/ton)

279.56 210.42 1.00 100.00 150.00 468.25 1000.00

Figure 116 shows the price trends of item 455.0105 across the analysis period. 

Source: FHWA.

Figure 116. Graph. Price trends—item 455.0105 for 2006–2015. 

The minimum price of $1.00/ton appeared seven times in the dataset: 

• 35 tons at $1.00/ton bid on 1/14/14 in Milwaukee County. 

• 1,880 tons at $.100/ton bid on 5/13/14 in Fond Du Lac County. 

• 1,595 tons at $1.00/ton bid on 4/14/15 in Dodge County. 

• 1,384 tons at $1.00/ton bid on 7/14/15 in Washington County. 

• 143 tons at $1.00/ton bid on 9/15/15 in Washington County. 

• 155 tons at $1.00/ton bid on 9/15/15 in Washington County. 

• 1,254 tons at $1.00/ton bid on 11/10/15 in Washington County. 

Milwaukee and Washington Counties are located in the southeast region of the State, Fond Du 

Lac County is located in the northeast region of the State, and Dodge County is located in the 

southwest region of the State. The maximum price of $1,000.00/ton appeared one time in the 
200 

dataset: 1 ton at $1,000.00/ton bid on 3/11/14 in Dane County. Dane County is located in the 

Southwest region of the State. 

Challenges

A similar challenge was experienced for multiple items of interest in Wisconsin. This challenge 

is shown by example for concrete items.

During the analysis period, there were 30,963 concrete items. During data analysis, this large 

volume of concrete items made it difficult to determine which concrete items appeared in the 

dataset enough for a robust analysis. Additionally, the item name “concrete” is used in the 

dataset for 12 unique pay item numbers with different units. For example, the following pay 

items are all labeled simply as “concrete” in the description but appear to all be unique items. 

The item number is shown along with the reported unit: 

• Item No. 517.1010.S (square feet). 

• Item No. 603.8 (LF). 

• Item No. 603.8125 (LF). 

• Item No. 416.101 (CY). 

• Item No. 415.041 (SY). 

• Item No. 517.1015.S (square feet). 

• Item No. 620.01 (SY). 

• Item No. 620.03 (SY). 

• Item No. SPV.0090-298 (LF). 

• Item No. SPV.0090-299 (LF). 

• Item No. SPV.0090-300 (LF). 

• Item No. 509.15 (SY). 

If the database was searched for more specific concrete items, the naming still proved to be 

problematic. Sorting for “concrete pavement” and looking for different sizes yielded 12 similar 

items, including 6 with the same description but different pay item numbers: 

• Special concrete pavement, 12.5-inch (SPV.0180O). 

• Special concrete pavement, 12-inch special high early strength (SPV.0180C). 

• 01. Concrete pavement, 121⁄2-inch (SPV.0180-348). 

• Concrete pavement, 12-inch special (SPV.0180-243). 

• Concrete pavement, 12-inch special (SPV.0180-150). 

• Concrete pavement, 12-inch special (SPV.0180-152). 

• Concrete pavement, 12-inch special (SPV.0180-329). 

• Concrete pavement, 12-inch special (SPV.0180-207). 

• Concrete pavement, 12-inch special (SPV.0180-145). 

• Concrete pavement, 121⁄2-inch SY (415.0125). 

• 0009. Concrete pavement, 12-inch special **p** (SPV.0180-316). 

• 0105. Concrete pavement, 12-inch special (SPV.0180-1063). 
201 

These occurrences in the dataset were encountered frequently and made price trend and anomaly 

analysis challenging. In conclusion, while the quantitative analysis revealed instances of 

mathematically unbalanced bid prices, there was no apparent link to M&A activity in that area.

Qualitative Analysis 

Bidding Process and Analysis 

A bid manual published via the Highway Construction Contract Information (HCCI) website 

includes a published list of future projects to be let, the number and frequency of lettings during 

the year, the prequalification process, advertisements for lettings, a published list of eligible 

bidders per proposal (which bidders can opt out of), and a published list of plan holders per 

proposal (Wisconsin DOT n.d.a.). The letting process is conducted electronically using Bid 

Express (2021). Urban and rural areas are not considered separately. Bids are evaluated before

award using AASHTOWare BAMS/DSSTM (AASHTO 2023). Unbalanced bid analysis is 

conducted using an internal access database where anything that is over by 5 percent or under by 

10 percent is analyzed and then passed onto a leadership team for a final decision. Single bids are 

tracked; in 2018 about 16 percent of bids were single bids, which is standard from year to year. 

Most contractors use their own sources for aggregates, asphalt, and concrete materials, but they 

do purchase materials from suppliers as well. Prime contractors often supply their own materials 

but use subcontractors for other work and will look for competitive locations for sources if 

applicable. Over the last 10 yr, material supplies have not changed significantly. No changes in 

individual project bid prices or annual average unit prices have been identified since the asphalt 

consolidation in the State 20 yr ago. Currently, the southeast region of the State is experiencing 

supply versus demand issues due to the arrival of FoxConn. 

On average, proposals have three to four bids per proposal. When analysis reveals bids out of 

alignment with engineer estimates, the regional team is contacted to investigate details such as 

accuracy of bid information. When confirmation on the item in question is received, the bid is 

then analyzed using the unbalanced bid analysis process. The HCCI posts lists including 

statewide average unit prices for all bid item numbers, and this information is available for the 

preceding 5–8 yr. Historical statewide bid data are also available, and construction cost indexes 

track these data and look for trends in bid pricing as well as any significant changes in bid 

pricing over time. If significant changes are identified, the cause is investigated further. 

M&A Activity

While no formal monitoring of M&A activity in the State is completed, name changes do 

occasionally occur and are usually identified in the prequalification list generation. Bid price 

changes are tracked, but not regarding M&A activity. Thus, no correlations between the two 

have been identified. While many prime contractors supply their own aggregates, they do at 

times lease or buy from other firms when it aids in competitive pricing. Timeframe concerns 

exists for zoning approval for local quarries or portable plants. Additionally, Foxconn influences 

the sand mining for fracking sand, and some concerns of antitrust of aggregate sourcing did 

occur where exclusive agreements existed that could be considered antitrust concerns. Despite 
202 

these concerns, WisDOT has not experienced any concerns about M&A activity in relation to 

correlations with this activity and competition, market shares, or bid pricing. 

Interviewer Observations

WisDOT’s unbalanced bid analysis process is robust, and many in the industry consider it a 

model for other States to follow. FHWA provides a link to WisDOT’s procedure as an example 

process. Other States have expressed great interest in this process. Tracking the construction cost 

index (in Wisconsin 100 items are tracked), asphalt index, concrete index, and structures index is 

done in a manner similar to the process used by the Ohio DOT. Materials specifications are 

written and disseminated statewide, and these specifications can be tailored as needed.

Summary

In the State of Wisconsin, trends of total project prices during the analysis period from the first 

quarter of 2006 through the third quarter of 2016 and bid item number prices compared to 

relevant unit prices yielded no significant price deviations attributable to merger or acquisition 

activity. Additionally, initial contacts with the State showed no significant concerns regarding 

pricing effects of M&A activity. During the case study interview, further investigation into the 

bidding process, contractor makeup, bidding analysis, and M&A activity was completed.

While M&A activity in the State is not formally monitored, name changes do occasionally occur 

and are usually identified in the prequalification list generation. Bid price changes are tracked, 

but not regarding M&A activity. Thus, no correlations between the two have been identified. 

Additionally, no major price anomalies in the data analysis were discovered. 
203 

ACKNOWLEDGMENTS

This document would not have been possible without the participation of many dedicated State

construction engineers and their teams. In particular, we wish to acknowledge the input of the 

States of Georgia, Wisconsin, Missouri, Ohio, Arizona, Colorado, Oklahoma, and Tennessee for 

their access and contributions to this report. 

The map in figure 4 was created using MapChart to show the AASHTO regions (Historical 

MapChart 2022). 

The original map in Figure 5 is the copyrighted property of Wisconsin DOT and was modified to 

enhance the boundaries between regions. 

The map in figure 96 was created using MapChart to show the case study States (Historical 

MapChart 2022). 

205 

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HRDI-20/06-23(WEB)E Recycled

Recyclable

Recommended citation: Federal Highway Administration,

Analysis of Material Source Mergers and Acquisitions 

on Project Delivery Quality and Costs

(Washington, DC: 2023) https://doi.org/10.21949/1521910