The State of Minority- and Women- Owned ... - Cleveland.com

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Anecdotal Evidence of Disparities in the City of Cleveland’s Market Area Table 8.6. Prevalence of Disparate Treatment Facing M/WBEs, by Type of Business Dealing Business Dealings Applying for commercial loans Applying for surety bonds Applying for commercial or professional insurance Hiring workers from union hiring halls Obtaining price quotes from suppliers or subcontracts Working or attempting to obtain work on public sector prime contracts Working or attempting to obtain work on public sector subcontracts Working or attempting to obtain work on private sector prime contract Working or attempting to obtain work on private sector subcontracts Receiving timely payment for work performed Functioning without hindrance or harassment on the work site Joining or dealing with construction trade associations Having to do inappropriate or extra work not required of comparable non-M/WBEs Having to meet quality, inspection, or performance standards not required of comparable non- M/WBEs In any one of the business dealings listed above Source: See Table 8.2. African American Hispanic Asian Native American Total Minority Nonminority Female Total M/WBEs 44.6% 4.6% 0.0% 22.5% 29.7% 9.0% 11.9% (4.71) (0.37) (0.00) (1.15) (4.08) (1.93) (2.99) 43.5% 15.8% 0.0% 21.3% 28.6% 2.7% 7.9% (4.36) (1.11) (0.00) (1.30) (3.92) (0.74) (2.23) 11.5% 19.6% 26.8% 0.0% 13.6% 1.0% 4.0% (2.44) (1.61) (1.79) (0.00) (2.98) (0.43) (1.75) 0.0% 100.0% 0.0% 0.0% 0.1% 0.0% 0.1% (0.00) (0.00) (0.00) (0.00) (1.88) (1.24) (1.85) 34.1% 4.9% 10.4% 0.0% 14.3% 1.6% 4.1% (5.59) (1.05) (1.58) (0.00) (4.59) (1.18) (2.82) 23.7% -3.0% -4.7% 0.4% 13.5% -10.4% -0.9% (2.94) (-0.26) (-0.44) (0.02) (2.16) (-2.02) (-0.19) 22.3% 1.1% -8.1% -4.7% 11.9% -10.0% -1.9% (2.58) (0.09) (-0.66) (-0.25) (1.76) (-1.78) (-0.36) 42.2% 8.4% 17.3% 12.3% 29.6% 4.7% 11.1% (4.79) (0.73) (1.26) (0.67) (4.31) (0.97) (2.61) 23.8% 7.9% 15.0% 10.1% 19.4% 3.3% 7.9% (3.07) (0.70) (1.12) (0.56) (3.11) (0.69) (1.91) 29.7% -1.1% 11.5% 17.0% 19.2% -3.1% 3.8% (3.60) (-0.09) (0.84) (0.87) (3.00) (-0.64) (0.86) 21.7% 16.0% 3.5% 0.0% 15.2% 8.1% 8.3% (2.97) (1.22) (0.30) (0.00) (2.62) (2.02) (2.47) 0.7% 0.3% 0.0% 0.0% 0.1% 0.0% 0.0% (1.26) (0.50) (0.00) (0.00) (0.66) (0.08) (0.34) 44.2% 14.0% 13.0% 33.3% 30.2% 7.6% 9.3% (4.85) (1.29) (1.11) (1.70) (4.34) (2.18) (3.25) 12.6% 4.7% 5.4% 0.0% 7.9% 2.2% 2.7% (3.22) (1.00) (0.98) (0.00) (2.88) (1.40) (2.21) 36.5% 9.1% -4.6% 0.2% 22.0% 3.7% 9.0% (4.39) (0.68) (-0.32) (0.01) (3.31) (0.72) (1.91) Note: Reported estimates are derivatives from Probit models with specification such as in Table 8.5, columns (2). T-statistics are in parentheses. T-statistics of 1.96 (1.64) or larger indicate that the result is significant within a 95 (90) percent confidence interval. Adverse results with T-statistics of 1.96 or higher are boldfaced. Adverse results with T-statistics of 1.64 or higher are boldfaced italicized. NERA Economic Consulting 276
Anecdotal Evidence of Disparities in the City of Cleveland’s Market Area 4. Impact of Current Business Environment on Ability to Win Contracts The survey asked questions about some common features of the business environment to determine which factors were perceived by M/WBEs as serious impediments to obtaining contracts. As Table 8.7 makes clear, substantial percentages of both M/WBEs and non-M/WBEs report that certain factors, such as “Late notice of bid/proposal deadlines,” “Large project sizes,” and “Bonding requirements” make it harder or impossible for firms to obtain contracts. Among non- M/WBEs, for example, 42.7 percent reported that late notice of bid/proposal deadlines made it harder or impossible for them to win contracts, 32.3 percent reported that large project sizes made it harder or impossible for them to win contracts, and 31.3 percent reported that bonding requirements made it harder or impossible to win contracts. The comparable figures for M/WBEs, however, at 58.9, 46.5, and 45.6 percent, respectively, are much greater than for non- M/WBEs. Indeed, as Table 8.7 shows, M/WBEs reported more difficulty on 7 out of the 9 factors about which they were polled. NERA Economic Consulting 277
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The State of Minority- and Women- O
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About the Project Team NERA Economi
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Notice This report sets forth the i
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Contents C. Race and Gender Dispari
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List of Tables Table 4.5. Services
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List of Tables Table 5.14. Disparit
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List of Tables Table 7.10. M/WBE Ut
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List of Tables Table 8.10. Percent
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List of Tables Table AC.32. Industr
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C. Defining the Relevant Markets Ex
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Table A. Overall Current Availabili
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Executive Summary disparity analysi
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Executive Summary • A greater sha
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Executive Summary Table C. Utilizat
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Contracting Category/ M/WBE Type Ex
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Executive Summary contract performa
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I. Introduction Introduction The Ci
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Legal Standards for Government Affi
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B. Preparing the Master Contract/Su
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Defining the Relevant Markets Table
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• Franklin County, OH (Columbus)
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NAICS Industry Group NAICS Descript
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Defining the Relevant Markets In AE
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NAICS Industry Group 8112 5412 5324
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NAICS Industry Group Source: See Ta
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NAICS Industry Group 4233 NAICS Des
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M/WBE Availability in the City of C
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NAICS Industry Group M/WBE Availabi
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Detailed Industry Group Navigationa
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Table 4.24. Detailed M/WBE Availabi
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Detailed Industry Group M/WBE Avail
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Detailed Industry Group General Med
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Detailed Industry Group Machine Sho
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Detailed Industry Group Products Me
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Table 4.28. Detailed DBE Availabili
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Table 4.30. Detailed DBE Availabili
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Market-Based Disparities in Busines
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VI. Statistical Disparities in Capi
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B. Theoretical Framework and Review
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Statistical Disparities in Capital
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D. Qualitative Evidence Statistical
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Table 6.7. Types of Problems Facing
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Table 6.9. Determinants of Loan Den
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Table 6.10. Alternative Models of L
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Table 6.13. Models of Interest Rate
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1. Qualitative Evidence Statistical
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) Prejudice against women. c) Preju
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Table 6.19. Determinants of Loan De
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Table 6.21. Models of Interest Rate
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Page 244 and 245: 2. Differences in Loan Denial Rates
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Page 308 and 309: The City of Cleveland’s Cleveland
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Page 334 and 335: References Fairlie, R. W. (1999),
Page 336 and 337: References Ladd, H. F. (1998), “E
Page 338 and 339: References U.S. Census Bureau (2004
Page 340 and 341: Appendix A. Glossary Demand-side: R
Page 342 and 343: Appendix A. Glossary NSSBF or SSBF.
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Appendix B. Master M/WBE Directory
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Appendix B. Master M/WBE Directory
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Appendix C. Detailed Utilization, A
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NERA Economic Consulting Barton Cre
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