• No results found

Factors Leading to Small Business Bank Lending

N/A
N/A
Protected

Academic year: 2021

Share "Factors Leading to Small Business Bank Lending"

Copied!
29
0
0

Loading.... (view fulltext now)

Full text

(1)

Factors Leading to Small Business Bank Lending

Brian W. Richard, Norman Walzer, and Andy Blanke

Presented to

2013 Community Development Society Meetings

Charleston, SC

(2)

Obstacles to Small Business Expansions

Ability to assess market opportunities

Staff too busy with existing business demands

Lack of technical management assistance

Inadequate financing opportunities

Financial institutions—Banks

State supported programs

(3)

Small Business Bank Lending

Plagued by information problems that may result in inefficient

allocation of loans

Publicly supported programs attempt to correct small

business lending market imperfections

Technical Assistance

– Help with creating business plans and pro forma financial statements,

financial reporting, and expansion plans

– Small Business Development Center

Loan Subsidies

– Direct lending by local, state, or federal government

(4)

Small Business Loan Subsidies

Small Business Administration

SBA 7a Loan Guarantees--banks can make federally guaranteed loans to small businesses.

• Guarantee encourages lenders to make loans to businesses that might not quite meet their underwriting terms.

• Guarantees 85 percent of loans up to $150,000 and 75 percent of loans over $150,000 (Office of the Comptroller of Currency, 2013).

SBA 504 Loans.

• SBA loans funds to businesses through Certified Development Companies. Typically, bank provides 50 % of project funding (first mortgage)

• SBA 504 loan funds 40 % (second mortgage),

(5)

Small Business Loan Subsidies

Revolving Loan Funds

– Locally managed, self-replenishing pool of money, using interest and

principal repayments to issue new loans

– RLF management practices vary by fund (unregulated loan funds),

many operate similar to SBA 504 loan program, providing subordinate loans to additional bank financing

– Often have small balances and don’t provide management assistance

– May not have much expertise in lending or business management

practices

(6)

Small Business Technical Assistance

Business Incubators

offer a variety of services to small

businesses including advice on business plan development

and refinement, marketing assistance, business training,

high-speed internet access, and accounting assistance (Knopp,

2006).

Community Colleges

. Community colleges actively support

local economic development --promoting an entrepreneurial

culture and building the human capital required for a

(7)

Small Business Technical Assistance

Service Corps of Retired Executives (SCORE). SCORE provides technical assistance for small businesses through both in-person mentoring and through a variety of online resources designed to help small businesses owners find and successfully apply for credit (SCORE Association, 2011).

Small Business Development Centers (SBDCs). SBDCs provide an array of services for entrepreneurs including market research, business plan development, procurement aid, and preparing businesses for loan applications (SBA, 2013).

Chambers of Commerce. Some chambers of commerce offer loan

packaging, a service where financial consultants prepare loan proposals for greater success in loan applications to banks.

(8)

Small Business Relationship Lending

Credit scoring and relationship lending used to address the

issue of unclear financial information. Relationship lending

largely bases loan decisions on proprietary information about

the firm and its owner gathered through contacts over time

(Ongena and Smith, 2001; Giannetti, 2012).

– “Small businesses consistently appear more willing to ask for credit

when their bank is a regional or community bank (and they appear to be more successful in their requests)” (Dennis, 2012).

(9)

Hypotheses

• H1: Positive relationship between the frequency banks work with the SBA

and the bank’s small business lending growth.

• H2: Positive relationship between the frequency banks work with

Revolving Loan Funds and the bank’s small business lending growth.

• H3: Community banks have higher small business lending growth than

larger banks.

• H4: Banks that work with technical assistance providers have higher small

(10)

Survey Data

Survey of bankers

– Illinois, October 2011

– Wisconsin, March 2013

Dependent Variable: Indicate how your financial institution's

total number of approved small business loans has changed in

the past 12 months.

– Increased by more than 10% (coded as 7)

– Increased by 5% - 10% (6)

– Increased by 1% - 5% (5)

– Unchanged (4)

– Decreased by 1% - 5% (3)

– Decreased by 5% - 10% (2)

(11)

National Bank, Community Bank, or S & L

Bankers were asked about their charter--national bank,

regional bank, community bank, or savings & loan.

• A dichotomous variable was created, set at 1 for community bank or

savings & loan and 0 for other responses.

– Of the 110 responses, 89 indicated that their bank was a community

(12)

Combined Responses from Bank Survey

Illinois (2011) and Wisconsin (2013)

How often has your institution worked with SBA or a RLF

during the past two years to close small business loans?

(13)

SBA and ILRF Use Comparisons

Illinois and Wisconsin

0 10 20 30 40 50 60

ILSBA WISBA ILRLF WIRLF

Never Rarely Sometimes Often Always

(14)

Working with Other Organizations

Illinois and Wisconsin Bank Responses

For hypothesis 4, an index was created based on responses to

the question “How often does your institution work with the

following organizations to assist in business support and

development?”

– Small Business Development Center

– S.C.O.R.E.

– Chamber of Commerce

– Local Economic Development Agency

– EDA District Office

– Local University

– Local Community College

(15)

Survey Data

Control variables included to account for differences

in local economies and banks.

– Dummy variable used: responses in the Wisconsin survey are 1 (58

responses) and Illinois are 0 (52 responses).

– Respondents selected from statements that “best characterizes the

local economic conditions in your region?” Both positive and negative statements were included. If more positive than negative statements were selected, the local economy variable was set to 1; otherwise 0.

• Respondents from Wisconsin had more positive view (67 percent vs. 34 percent of Illinois respondents) perhaps partly because of the timing of the surveys.

(16)

Survey Data

Control variables included to account for differences

in local economies and banks.

– Respondents were asked “On average what percentage of personal

equity injection does your institution require for a business loan?” Respondents selected an answer from the following categories:

• More than 80% (coded as 5)

• 61% to 80% (4)

• 41% to 60% (3)

• 21% to 40% (2)

(17)

Definition of Variables

WSBA: How often worked with SBA on loans in past 12 months

WRLF: How often worked with RLFs in past 12 months

CommBank: Community Banks = 1; Others=0

Assistindex: How often work with one of 8 other agencies, SBDC etc. in past 12 months.

Wisc: Adjustment for time of survey 2011 = 0; 2013=1(Wisconsin)

ECPos: Economic conditions in area rating

PCTEquity: Percent of equity bank requires for loans

Dep. Variable: Change in total number of approved business loans in past 12 months (Index)

(18)

Ordinal Regression Results

Variable Estimate Std. Error Wald Sig.

WSBA .389 .183 4.54 .033 WRLF .228 .226 1.01 .314 CommBank -1.832 .499 13.50 .000 AssistIndex .676 .310 4.77 .029 Wisc .369 .408 .82 .366 ECPos 1.109 .384 8.34 .004 PctEquity -1.307 .352 13.75 .000

-2 Log Likelihood Chi-Square DF Sig.

343.552 48.999 7 .000

Nagelkerke R-Square

(19)

Findings

Interactions with SBA

H

1

: A positive relationship exists between the frequency

banks work with the SBA and the bank’s small business

lending growth.

– This hypothesis is supported by the data.

– However, some of the comments provided by bankers in open-ended

questions indicated that they are frequently frustrated with the amount of ‘red tape’ associated with SBA guarantees and loans.

(20)

Findings

RLFs and Lending Growth

H

2

: A positive relationship exists between the frequency the

banks work with RLFs and the bank’s small business lending

growth.

– Results not significant

– Revolving loan funds are often run by city/county employees or local

EDOs. The loan funds are managed as a part time job and they may not market them vigorously

(21)

Findings

Size of Bank

H

3

: Community banks have higher small business lending growth

than larger banks.

– The variable for community banks produced a result contrary to the hypothesis.

– This is surprising because there is considerable literature focused on the practices of community banks being more ‘small business friendly’.

– However, some studies are finding that this may no longer the case. In an international study, de la Torre et.al. (2010) found that large banks are perceived as the main player in the small-medium sized businesses financing market.

– Small banks may not have expertise to evaluate business opportunities.

– Large banks increasingly rely on more sophisticated screening mechanisms that lower the information costs of providing small business loans.

(22)

Findings

Collaboration with TA Providers

H

4

: Banks that work with technical assistance providers have

higher small business lending growth.

– This hypothesis was supported by the data.

– It is not clear from the data whether the relationship is driven by

financial TA or other TA making the businesses more viable (marketing, planning, exporting, etc.).

– It may be that technical assistance providers are screening the

(23)

Additional Research

Identify location of bank and business starts

Obtain more information about obstacles to lending

Explore management of RLFs and effects

Understand collaboration between banks and RLFs, in more

detail

Determine types of training needed by RLF managers

Identify best practices with RLFs

Survey entrepreneurs to determine access to banks and other

sources

(24)

For More Information, Contact

Brian W. Richard Norman Walzer Andy Blanke

Senior Research Associate Senior Research Scholar Research Associate brichard@niu.edu nwalzer@niu.edu ablanke@niu.edu

Center for Governmental Studies

148 N. Third Street DeKalb, IL 60115 www.NIUCGS.org

(25)

References

• Berger, Allen N. and Gregory F. Udell (1995). Relationship Lending and Lines of Credit in Small Firm Finance. The Journal of Business, Vol. 68.

• Berger, Allen N. and Gregory F. Udell (2002). Small Business Credit Availability and Relationship Lending: The Importance of Bank Organizational Structure. Journal of Finance. Vol. 112.

• Carol, J. (2004). Going after capital. A comprehensive guide to business incubation. 2nd ed. Athens, OH: National Business Incubator Association.

• Colbert, C., Adkins, D., Wolfe, C., & LaPan, Karl. (2010). Best practices in action: Guidelines for implementing first-class business incubation programs. 2nd ed. Athens, OH: National Business Incubator Association

• Council of Development Finance Agencies (N.D.). CDFA Spotlight: Revolving Loan Funds (RLFs).

• Craig, Ben R., William E. Jackson III, & James B. Thomson, (2007). SBA-Loan Guarantees and Local Economic Growth, Journal of Small Business Management, Vol. 45.

• Craig, Ben R., William E. Jackson III, & James B. Thomson, (2008a). Credit Market Failure Intervention: Do Government Sponsored Small Business Credit Programs Enrich Poorer Areas? Small Business Economics Small Business Economics. Vol. 30, No. 4.

• Craig, Ben R., William E. Jackson III & James B. Thomson, (2008b). On Government Intervention in the Small Firm Credit Market and Economic Performance. In Entrepreneurship in Emerging Domestic Markets: Barriers and Innovation. Glenn Yago, James R. Barth, Betsy Zeidman, eds.

• Craig, Ben R., William E. Jackson III & James B. Thomson, (2010). Does Small Business Administration Guaranteed Lending Improve Economic Performance in Low- Income Areas? Entrepreneurship in Low- and Moderate- Income Communities Economic Commentary 55.

• de la Torre, Augusto, Maria Soledad Martinez Peria & Sergio L. Schmukler (2010). Bank Involvement with SMEs: Beyond Relationship Lending. Journal of Banking & Finance. Vol. 34.

• Dennis, Jr., William J. (2012). Small Business Credit Access and the Lingering Recession. National Federation of Independent Businesses Research Foundation, www.NFIB.com/creditpoll.

• Diamond, D. W. (1989). Reputation acquisition in debt markets. Journal of Political Economy Vol. 97.

• Drabenstott, M., Novack, N., & Weiler, S. (2004). New governance for a new rural economy: Reinventing public and private institutions—A conference summary. Economic Review. Vol. 89, No, 4.

• Giannetti, C (2012). Relationship Lending and Firm Innovativeness. Journal of Empirical Finance Vol. 19.

• Greenbaum,S. I.; Kanatas, G.; and Venezia, I. (1989). Equilibrium loan pricing under the bank-client relationship. Journal of Banking and Finance, Vol. 13.

• Knopp, L. 2006. State of the Business Incubation Industry. Athens, OH: National Business Incubation Association.

(26)

References

• Lewis, D.A., Harper-Anderson, E., & Molnar, L.A. (2011). Incubating success: Incubation best practices that lead to successful new ventures. Ann Arbor, MI: University of Michigan.

• McFarland, C., & McConnell, J.K. (2012). Small business growth during a recession: Local policy implications. Economic Development Quarterly. published online October 8, 2012.

• Mihajlov, Thomas P. (2012). SBA 504 Loans Help Improve Balance Sheets: A Micro Analysis. Journal of Marketing Development and Competitiveness. Vol. 6, No. 1.

• Office of the Comptroller of the Currency (2013). Community Development Fact Sheet: SBA 7(a) Guaranteed Loan Program.

• O’Connell, Ann A. (2006). Logistic Regression Models for Ordinal Response Variables. Sage Publications, Thousand Oaks, CA.

• Ongena, Steven and David C Smith, (2001). The duration of bank relationships. Journal of Financial Economics. Vol. 61.

• Petersen, M. A., and Rajan, R. G. (1993). The effect of credit market competition on firm-creditor relationships. Working paper. Chicago: University of Chicago

• Reynolds, P., Storey, D.J., & Westhead, P. (1994). Cross-national comparisons of the variation in new firm formation rates. Regional Studies Vol. 28.

• SCORE Association. (2011). Media fact sheet. Retrieved May 20, 2013 from: http://www.score.org/Media_Resources

• SCORE Association. (2012). Our impact. Retrieved May 20, 2013 from: http://www.score.org/our-impact

• Sharpe, S. A. (1990). Asymmetric information, bank lending, and implicit contracts: A stylized model of customer relationships. Journal of Finance, Vol. 45.

• Stiglitz, Jospeh E. & Andrew Weiss (1981). Credit Rationing in Markets with Imperfect Information, The American Economic Review. Vol. 71, No. 393.

• Torres, V., Viterito, A., Heeter, A., Hernandez, E., Santiague, L., Johnson, S. (2013). Sustaining opportunity in rural community colleges. Community College Journal of Research and Practice. Vol. 37.

• United States Small Business Administration (N.D.). Credit Factors: Equity Investment.

• United States Small Business Administration (N.D.). Small Business Development Centers (SBDCs). Retrieved May 20, 2013 from: http://www.sba.gov/content/small-business-development-centers-sbdcs

• United States Small Business Administration. (2013). FY 2014 Congressional Budget Justification and FY 2012 Annual Performance Report. Retrieved May 16, 2013 from: http://www.sba.gov/about-sba-services/21731

• United States Business Administration. (2012). FY 2013 Congressional Budget Justification and FY 2011 Annual Performance Report. Retrieved May 16, 2013 from: http://www.sba.gov/about-sba-services/21731

• United States Small Business Administration. (2010). FY 2011 Congressional Budget Justification and FY 2009 Annual Performance Report. Retrieved May 16, 2013 from: http://www.sba.gov/about-sba-services/21731

(27)

Business Lending Trends

Year Commercial and Industrial loans Small Business loans Small Business Loans as % of Total Com'l Loans

2005 1,085,572 N/A 2006 1,214,728 N/A 2007 1,439,127 N/A 2008 1,493,934 N/A 2009 1,213,895 N/A 2010 1,183,962 334,214 28.23% 2011 1,345,034 315,457 23.45% 2012 1,508,400 302,224 20.04%

(28)

Changes in Business Loans

Dependent Variable:

How financial institution's number of

approved small business loans changed in past 12 months.

(29)

Methodology

The data were analyzed using ordinal logistic regression.

Ordinal logistic regression is an extension of the general

logistic regression model. It predicts cumulative logits:

ln(𝑌′𝑗)=ln 𝜋𝑗 𝑥

1 − 𝜋𝑗 𝑥 =∝𝑗 +(𝛽1𝑋1 + 𝛽2𝑋2 + ⋯ 𝛽𝑝𝑋𝑝)

– Where “𝜋 𝑌 ≤ 𝑗 𝑋1, 𝑋2, … 𝑋𝑝 = 𝜋𝑗 𝑥 represent the probability that

a response falls in a category less than or equal to the jth category”

References

Related documents

OVERVIEW: tipc - a TIP to llvm compiler USAGE: tipc [options] <tip source file> OPTIONS:.

Information systems in airports contain data that crosses functional areas; the data might be collected in various divisions, used by several different divisions, and only available

SB 353 Senator Hershey Electric Companies ‐ Installation of Solar Electric Generating Facility ‐ New Interconnection Agreement Finance; Economic Matters 2/17/2015 3/19/2015

Limited Liability : In the event that circumstances beyond the commercially reasonable control of Organizer interferes with, or prevents, Organizer from fulfilling, in part, or all

The Demand Capacity Ratios for all the columns removed were calculated and the values were less than 2 which suggests that all columns have the potential to resist

We in- vestigate convergence of inflation using unit labour cost (ULC) growth and applying PANIC (Bai and Ng, 2004) and cluster procedures (Hobijn and Franses, 2000, Busetti et

The North Carolina Board of Nursing, a contributing entity to the NCSBN taxonomy of error supports investigation of errors committed by licensed nurses working within the state

Furthermore, single-unit studies first in nonhuman primate models ( Raz et al., 2001; Goldberg et al., 2002 ) and then later in clinical recordings have resulted in a model of