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David G Blanchflower - One of the best experts on this subject based on the ideXlab platform.

  • discrimination in the small business credit market
    The Review of Economics and Statistics, 2003
    Co-Authors: David G Blanchflower, Phillip B Levine, David J Zimmerman
    Abstract:

    This paper uses data from the 1993 National Survey of Small Business Finances to determine the extent to which minority-owned small businesses face constraints in the credit market beyond those faced by white-owned small businesses. First, we present qualitative evidence indicating that black- and white-owned firms report similar concerns about the factors that may affect their businesses except that blacks are far more likely to report problems with credit availability. Second, we conduct an econometric analysis of Loan denial probabilities by race and find that black-owned small businesses are almost three times more likely to have a Loan Application denied. Even after controlling for the differences in credit-worthiness and other factors that exist between black- and white-owned firms, blacks are still about twice as likely to be denied credit. A series of specification checks indicates that this gap is unlikely to be largely attributed to omitted variable bias. Third, we conduct a similar analysis regarding interest rates charged to approved Loans and find black-owned firms pay higher interest rates as well. Finally, even these results are likely to understate differences in credit access because many potential black-owned firms are not in operation due to the lack of credit and those in business may be too afraid to apply. These results indicate that the racial disparity in credit availability is likely caused by discrimination.

David J Zimmerman - One of the best experts on this subject based on the ideXlab platform.

  • discrimination in the small business credit market
    The Review of Economics and Statistics, 2003
    Co-Authors: David G Blanchflower, Phillip B Levine, David J Zimmerman
    Abstract:

    This paper uses data from the 1993 National Survey of Small Business Finances to determine the extent to which minority-owned small businesses face constraints in the credit market beyond those faced by white-owned small businesses. First, we present qualitative evidence indicating that black- and white-owned firms report similar concerns about the factors that may affect their businesses except that blacks are far more likely to report problems with credit availability. Second, we conduct an econometric analysis of Loan denial probabilities by race and find that black-owned small businesses are almost three times more likely to have a Loan Application denied. Even after controlling for the differences in credit-worthiness and other factors that exist between black- and white-owned firms, blacks are still about twice as likely to be denied credit. A series of specification checks indicates that this gap is unlikely to be largely attributed to omitted variable bias. Third, we conduct a similar analysis regarding interest rates charged to approved Loans and find black-owned firms pay higher interest rates as well. Finally, even these results are likely to understate differences in credit access because many potential black-owned firms are not in operation due to the lack of credit and those in business may be too afraid to apply. These results indicate that the racial disparity in credit availability is likely caused by discrimination.

Phillip B Levine - One of the best experts on this subject based on the ideXlab platform.

  • discrimination in the small business credit market
    The Review of Economics and Statistics, 2003
    Co-Authors: David G Blanchflower, Phillip B Levine, David J Zimmerman
    Abstract:

    This paper uses data from the 1993 National Survey of Small Business Finances to determine the extent to which minority-owned small businesses face constraints in the credit market beyond those faced by white-owned small businesses. First, we present qualitative evidence indicating that black- and white-owned firms report similar concerns about the factors that may affect their businesses except that blacks are far more likely to report problems with credit availability. Second, we conduct an econometric analysis of Loan denial probabilities by race and find that black-owned small businesses are almost three times more likely to have a Loan Application denied. Even after controlling for the differences in credit-worthiness and other factors that exist between black- and white-owned firms, blacks are still about twice as likely to be denied credit. A series of specification checks indicates that this gap is unlikely to be largely attributed to omitted variable bias. Third, we conduct a similar analysis regarding interest rates charged to approved Loans and find black-owned firms pay higher interest rates as well. Finally, even these results are likely to understate differences in credit access because many potential black-owned firms are not in operation due to the lack of credit and those in business may be too afraid to apply. These results indicate that the racial disparity in credit availability is likely caused by discrimination.

Francis J. Greene - One of the best experts on this subject based on the ideXlab platform.

  • The determinants of online Loan Applications from small businesses
    Journal of Small Business and Enterprise Development, 2007
    Co-Authors: Liang Han, Francis J. Greene
    Abstract:

    Purpose – The purpose of this paper is to examine both the characteristics of the business customers and the types of venture which make use of online Loan Applications. Despite the growth in the use of technology in banking and the advent of online banking, little research has been conducted on the factors underlying online Loan Application behaviour amongst business banking customers.Design/methodology/approach – A multivariate analysis is conducted on a USA dataset to empirically test the hypotheses derived in this paper. The empirical evidence is drawn from the US Survey of Small Business Finances, which contains 3,561 sample ventures, representing 5.3 million small businesses in the USA.Findings – The paper finds that online Loan behaviour is largely determined by the characteristics of the entrepreneur, rather than that of the venture. It is also found that factors that trust, evident in the length of the relationship between the applicants and their primary lender, is important. Moderating these ef...

Yuanyi Pan - One of the best experts on this subject based on the ideXlab platform.

  • supervised discretization with gk τ
    Procedia Computer Science, 2013
    Co-Authors: Wenxue Huang, Yuanyi Pan
    Abstract:

    Abstract When data are high dimensional and mix-typed while response variable is categorical, an effective executable profile consists of categorical or categorized variables with easily understandable statistics. Many data mining technologies require categor- ical variables; many have better results by changing continuous variables to categorical variables. Discretizing a continuous variable can be accomplished in either a supervised way or an unsupervised or conventional way. We propose a supervised discretizing method using the Goodman-Kruskal tau (or GK-τ) maximization as the discretization optimization criterion. This optimization is probabilistic averaging effect oriented. An experiment with financial Loan Application is designed to show the improvement after the discretization. Some technical concerns during the discretization are discussed in this article as well.

  • ITQM - Supervised Discretization with GK − τ☆
    Procedia Computer Science, 2013
    Co-Authors: Wenxue Huang, Yuanyi Pan
    Abstract:

    Abstract When data are high dimensional and mix-typed while response variable is categorical, an effective executable profile consists of categorical or categorized variables with easily understandable statistics. Many data mining technologies require categor- ical variables; many have better results by changing continuous variables to categorical variables. Discretizing a continuous variable can be accomplished in either a supervised way or an unsupervised or conventional way. We propose a supervised discretizing method using the Goodman-Kruskal tau (or GK-τ) maximization as the discretization optimization criterion. This optimization is probabilistic averaging effect oriented. An experiment with financial Loan Application is designed to show the improvement after the discretization. Some technical concerns during the discretization are discussed in this article as well.