The role of human capital in loan officers' decision policies.

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(1.) In this article we controlled for two CEO characteristics by research design. Business education and CEO character were held constant across the hypothetical businesses assessed.

(2.) Given that we are using metric conjoint analysis it is not necessary to test for intransitivity in pair comparison data.

(3.) Curvilinear relationships for the human capital variables were also investigated and none were found to be significant.

Volker Bruns is an Senior Associate at Hubner Schlosser & Cie, Corporate Finance in Munich, Germany and affiliated with the department of Finance at the Jonkoping International Business School, Sweden.

Daniel V. Holland is Assistant Professor of Entrepreneurship at Jon M. Huntsman School of Business at Utah State University.

Dean A. Shepherd is Professor and Randall L. Tobias Chair in Entrepreneurial Leadership, Kelley School of Business, Indiana University Kelley School of Business, Indiana University.

Johan Wiklund is Associate Professor at the Department of Entrepreneurship and Emerging Enterprises at Whitman School of Management, Syracuse University and Professor in Entrepreneurship at Jonkoping International Business School.

Please send correspondence to Volker Bruns tel.: +49-163-330 2 330, e-mail: volker.bruns@jibs.hj.se; Daniel V. Holland, tel.: 435-797-3132, e-mail: Daniel.Holland@usu.edu, Dean A. Shepherd, tel.: 812-856-5220, e-mail: shepherd@indiana.edu; Johan Wiklund, tel.: 315-443-3356, e-mail: jwiklund@syr.edu Table 1 Descriptive Statistics and Correlation Matrix for Level 2 Human Capital and Control Variables Variable Mean SD (1) (2) 1. Education (1 = college 50.9% --

or higher) 2. Banking experience 22.86 9.74 -.385 *** 3. Lending experience 12.97 7.39 -.129 -.697 *** 4. Recent small business 40.45 50.85 .004 -.043

loan experience 5. Gender (1 = male) 86.0% -- -.296 *** .218 * 6. Age 45.52 8.44 -.261 ** .897 *** Variable (3) (4) (5) 1. Education (1 = college

or higher) 2. Banking experience 3. Lending experience 4. Recent small business .102

loan experience 5. Gender (1 = male) .438 *** -.008 6. Age .644 *** -.028 .205 * ([dagger]) p < .10 * p < .05 ** p < .01 *** p < .001 n = 114 Table 2 Results of Hierarchical Linear Modeling of Loan Officers Decision Policies Toward the Likelihood of Granting a Small Business Loan

Main-effects model

Coefficient T-ratio Intercept 5.047 .072 *** Business risk .141 .044 ** Share of investment 1.122 .059 *** Current financial position 1.674 .062 *** Independent collateral 1.18 .066 *** Related experience 1.269 .066 *** CEO tenure .494 .048 *** Past performance 1.759 .061 *** Comprehensiveness of strategic plan .029 .045 Business risk x share of investment Business risk x financial position Business risk x independent collateral Business risk x related experience Model (@) [R.sup.2] .549 *** Change in [R.sup.2] .528 ***

Full-model

Coefficient T-ratio Intercept 5.047 59.539 *** Business risk .158 2.96 ** Share of investment 1.037 16.123 *** Current financial position 1.638 26.752 *** Independent collateral 1.229 15.754 *** Related experience 1.249 16.361 *** CEO tenure .542 9.84 *** Past performance 1.749 24.082 *** Comprehensiveness of strategic plan .056 1.049 Business risk x share of investment .069 .797 Business risk x financial position -.205 -2.429 * Business risk x independent collateral .356 3.861 *** Business risk x related experience .053 .586 Model (@) [R.sup.2] .550 *** Change in [R.sup.2] .001 *** ([dagger]) p < .10 * p < .05 ** p < .01 *** p < .001 (@) These model statistics were calculated using hierarchical regression analysis and significance levels relate to F statistic. n = 3,648 Table 3 Results of Hierarchical Linear Modeling of Loan Officers' Human Capital Variables on their Loan Approval Decision Policies

Business

risk x

share of

Intercept investment Education Coefficient (@) .107 -.277

T-ratio .559 -1.245 Banking experience Coefficient (@) .040 -.0003

T-ratio 1.829 -.011

([dagger]) Lending experience Coefficient (@) -.008 .011

T-ratio -.459 .531 Recent small business Coefficient (@) -.0004 .002

loan experience T-ratio -.247 1.173 Intercept Coefficient (@) 5.057 .064

T-ratio 67.474 *** .737 Control variables

Age Coefficient (@) -.041 -.007

T-ratio -1.99 * -.312

Gender Coefficient (@) -.220 -.130

T-ratio -.839 -.428

Business Business

risk x risk x

financial ind. of

position collateral Education Coefficient (@) .522 -.134

T-ratio 2.343 * -.601 Banking experience Coefficient (@) .002 -.023

T-ratio .076 -.924 Lending experience Coefficient (@) -.008 .019

T-ratio -.405 .0910 Recent small business Coefficient (@) .001 .003

loan experience T-ratio .742 1.927

([dagger]) Intercept Coefficient (@) -.232 .295

T-ratio -2.664 ** 3.393 *** Control variables

Age Coefficient (@) .003 .021

T-ratio .106 .882

Gender Coefficient (@) .465 -.269

T-ratio 1.524 -.883

Business

risk x

related

exp Education Coefficient (@) -.082

T-ratio -.367 Banking experience Coefficient (@) -.027

T-ratio -1.058 Lending experience Coefficient (@) .009

T-ratio .426 Recent small business Coefficient (@) -.0008

loan experience T-ratio -.431 Intercept Coefficient (@) .061

T-ratio 0.699 Control variables

Age Coefficient (@) .028

T-ratio 1.180

Gender Coefficient (@) .612

T-ratio 2.006 * ([dagger]) p < .10 * p < .05 ** p < .01 *** p < .001 (@) All variables were standardized and group centered. n = 3.648 Table 4 Results of Hierarchical Linear Modeling of Human Capital Variables on the Decision Attribute: Borrower's Related Business Experience