This Selected Issues paper on United States 2012 Article IV Consultation discusses rebound of manufacturing production. The U.S. share in global manufacturing production declined through most of the past three decades, but it has stabilized since the Great Recession. It currently represents about 20 percent of global manufacturing value added. Interestingly, after a sharp increase during most of the previous decade, China’s share in global manufacturing has also stabilized since the Great Recession, at a level similar to that of the United States. The notion of a manufacturing renaissance has been fuelled partly by the rebound in production since the end of the Great Recession.

Abstract

This Selected Issues paper on United States 2012 Article IV Consultation discusses rebound of manufacturing production. The U.S. share in global manufacturing production declined through most of the past three decades, but it has stabilized since the Great Recession. It currently represents about 20 percent of global manufacturing value added. Interestingly, after a sharp increase during most of the previous decade, China’s share in global manufacturing has also stabilized since the Great Recession, at a level similar to that of the United States. The notion of a manufacturing renaissance has been fuelled partly by the rebound in production since the end of the Great Recession.

Are U.S. Small Businesses Credit Constrained?1

A. Introduction

1. The evolution of financial conditions in the United States over the past few years has differed greatly across institutional sectors:

  • Large corporates have enjoyed particularly easy financial conditions. Corporates are flush with cash, the corporate credit market has expanded rapidly, and terms and conditions of bank commercial and industrial loans to large firms have been easing since 2010 (Chart).

  • By contrast, households still face relatively tight access to mortgages. Notably, credit scores for new borrowers (for both prime and FHA mortgages) continue to be much higher than pre-crisis years (see Duke, 2013).

  • Credit conditions for small and medimum-sized enterprises (SMEs) are more difficult to assess.2 Small businesses face higher interest rates than larger firms and have benefited less from easier loan standards in 2012. The volume of credit to SMEs has declined sharply since 2008, although the National Federation of Independent Business survey on small businesses suggests that SMEs remain mostly concerned about the sale outlook, rather than access to credit. However, controlling for the stage of the cycle, the share of SMEs reporting unsatisfied borrowing needs remains higher than in the 2000–01 recession (Chart).

uA04fig01

Tightening Loan Standards: Large Firms

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A004

Source: Federal Reserve Board Senior Loan Officer Opinion Survey.Note: net percentage of firms on y-axis, quarters from NBER troughs on x-axis.
uA04fig02

Borrowing Needs Not Satisfied

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A004

Source: NFIB. Note:percentage of firms on y-axis, quarters from NBER troughs on x-axis.

2. The objective of this chapter is to assess whether SMEs face tighter credit conditions relative to pre-crisis levels. To separate demand versus supply factors and mitigate identification problems, it uses firm-level data. In particular, the chapter tries to control for changes in credit supply conditions using loan applications data, exploiting the difference in housing markets developments across states and their effect on housing collateral values—a key determinant of SMEs access to credit. By doing so, we are able to assess whether firms that operate in states where house prices experienced a sharper decline also face more difficulty in accessing credit—a sign that they are experiencing tighter credit conditions. To do this we use a database of nearly 5,000 new businesses or startups that are being tracked annually since 2004 from the Kaufmann Firm Survey (KFS). Data currently are available through the year 2011.

3. The chapter finds that access to credit for small businesses is still impaired, mainly as the value of housing as collateral has weakened. Over the 2007–2011 period firms in the KFS reduced their application rate for loans, suffered an increase in the rejection rate of their applications, and were increasingly discouraged from applying for a loan when they needed it.3 These trends manifested themselves more strongly for firms in states that were hardest hit by the decline in house prices and much more weakly in the five states that went relatively unscathed from the housing price collapse. A very large percentage of the firms whose loan application was rejected indicated as a reason tighter restrictions on lending, especially in hardest hit states.

4. The rest of the Chapter is structured as follows: Section B presents stylized facts on the U.S. SMEs. Section C presents stylized facts on the start-ups in the KFS and results from regression analyses seeking to establish a link between difficulties to secure funding and the use of real estate collateral. Section D concludes with a description of the main takeaways.

B. SMEs in the U.S. Economy

5. Small businesses have been hit particularly hard in the Great Recession. As of 2010, they employ almost half of private sector employees, and generate about 60 of net new private sector jobs. Over the last 35 years SMEs have displayed remarkable resilience as jobs generators, as they continued to generate jobs on a net basis since 1977. Interestingly, in contrast to large firms, SMEs have continued to create jobs during recessions over the past three decades (Chart). However, the Great Recession is an exception, as net job creation dropped dramatically for both large firms and SMEs.

uA04fig03

Net Job Creation by Firm Size

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A004

Source: U.S. Census Bureau and staff calculations. On the y-axis thousands of jobs, on the x-axis years from NBER troughs.

6. This reflects their concentration in the construction sector. Almost one third of SMEs and of their employment are concentrated in the construction, real estate and leasing sectors, which have felt the brunt of the crisis with the collapse of housing prices. Moreover, SMEs account for more than 80 percent of output and employment of the construction sector, and about three quarters of the output and half of the employment in the real estate and leasing sectors. Firms with less than 50 employees, in particular, account for more than half of the employed in the construction sector and almost one third in the real estate sector.

7. It also reflects the fact that SMEs typically rely only on bank credit, often secured with real estate collateral. Commercial banks institutions traditionally have been the most important providers of credit to small businesses.4 According to the most recent NFIB survey in 2011 almost 90 percent of small businesses had a commercial bank as primary financial institution. Additionally, small businesses have traditionally relied on personal residence as collateral.5 Loans to SMEs have declined strongly in this crisis, and have been contracting since the trough in 2009: as of 2012, loans below one hundred thousand dollars, normally extended to small firms, are 15 percent below their pre crisis peak in 2008 (Chart). Loans of less than 1 million dollars are down by 16 percent. While non-mortgage bank credit has rebounded mortgages are still contracting. Moreover, for smaller firms the share of loans that had to be secured by collateral—typically real estate of the family owning the business—has trended up after the crisis to above 90 percent, while that for larger firms has decreased significantly. For all the size of loans, the share of loans secured by collateral is higher in this crisis than in the previous one.

uA04fig04

Loans to Small Businesses

(Amounts in $ Million)

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A004

Source: FDIC.

C. Are SMEs Credit Constrained? Some Evidence from Start-ups

8. A large literature has tried to disentangle supply and demand drivers of credit conditions, but the identification of their relative role is complicated by a number of confounding micro and macro factors (Jimenez et al., 2011). Policy implications are very different according to which effect prevails, and policies to ease access to credit may be appropriate if supply effects are found to be significant. This is particularly relevant for SMEs as they depend on bank credit and are exposed to informational asymmetries that may make credit constraints difficult to overcome without adequate collateral or credit history (Petersen and Rajan, 1994; Berger and Udell, 2006).

9. To assess whether lower credit to SMEs reflect supply factors, we looked at financing conditions for small young businesses. We used the restricted-access data from the Kaufmann Firm Survey (KFS), a panel study of nearly 5,000 new businesses nationally representative of startups that are being tracked annually since 2004.6 The KFS dataset provides data on how businesses are financed; which products, services, and innovations they develop in their early years of existence; and what are the characteristics of those who own and operate them. Data currently are available through the year 2011.

10. Small young businesses experienced increasing difficulties in accessing bank credit during the crisis, especially in states where housing prices declined the most.

  • The percentage of firms that applied for a loan declined from 12.5 percent in 2007 to 10.8 percent in 2011. In the five states hit hardest by the house price collapse, the percentage of firms applying for a loan declined 4 percentage points to 9.1 in 2011, while in the five states that performed better in terms of housing prices the ratio increased 0.4 points to 12.9 percent in 2011 (Table 1).

  • The percentage of firms whose loan application was always accepted decreased from 72.4 percent in 2007 to 70.3 in 2011. The decline was much greater (about 5 percentage points) in the states which suffered the most from the housing bust, while the acceptance ratio actually increased (8 percentage points) in states with the most favorable house price dynamics. In these states the percentage of firms whose application was always rejected increased by 2.5 pp, compared to 8 pps in the states most hit by the crisis.

  • The share of firms who thought about applying for a loan but did not do so for fear of rejection increased to 16.5 in 2011. But again this result mask significant difference across states, as the share of “discouraged” firms increased about 5 pps in the states with the largest house price decline, while it actually decreased by 3.2 percentage points in the other states.

Table 1.

Financing Experiences of Start-Ups

(Percentage of firms)

article image
Source: Kauffman Firm Survey, Haver. Note: FHFA house price indexes, States house price changes since the peak of the federal FHFA house price index in Q12007 to the trough in 2011Q2. Arizona, California, Florida, Nevada and Rhode Island registered the strongest declines in house price; Iowa, North Dakota, Oklahoma, South Dakota and Texas registered the smallest declines, if any.

11. Credit supply constraints seem to be still at work. The percentage of firms that pointed to restrictions on lending as the reason why their application was denied was still 78.7 percent in 2011 (Table 2). Moreover, it has been increasingly difficult to post personal real estate as collateral for loans (Table 3). The percentage of young firms that posted personal real estate as collateral decreased to 30.8 percent in 2011 from 42.6 in 2009. The ratio declined significantly more (18 pps) in the five states hardest hit from the housing bust, while it remained constant in the other states. At a national level, however, constraints seem to be relaxing: about 30 percent of firms said lack of collateral was the reason for loan rejection in 2011, down from 43.3 percent in 2007.

Table 2.

Reasons for Denial of Loan Application or Renewal of Credit Line

(Percentages of firms)

article image
Source: Kauffman Firm Survey, Haver. Note: FHFA house price indexes, States house price changes ranked with respect to the decline since the peak of the federal FHFA house price index in Q12007 to the trough in 2011Q2. Arizona, California, Florida, Nevada and Rhode Island are the states that registered the strongest declines; Iowa, North Dakota, Oklahoma, South Dakota and Texas registered the smallest declines, if any.
Table 3.

Type of Collateral Posted for Loans

(Percentages of firms)

article image
Sources: Kauffman Firm Survey, Haver Analytics. Note: FHFA house price indexes, States house price changes ranked with respect to the decline since the peak of the federal FHFA house price index in Q12007 to the trough in 2011Q2. Arizona, California, Florida, Nevada and Rhode Island are the states that registered the strongest declines; Iowa, North Dakota, Oklahoma, South Dakota and Texas registered the smallest declines, if any.

12. Empirical exercises suggest the existence of constraints for small young businesses trying to access credit using real estate collateral. We estimated the probability that a loan application of a young business was submitted, discouraged and approved during the crisis over the 2009–2011 period. The models were estimated with a panel probit regression of the following form:

Li,t = αi + δXi,t + εi,t

where Li,t takes respectively the value of one if a loan application of firm i in year t is discouraged when a firm needs the loan, submitted or approved. Xi,t is a vector of variables that captures the following firm’s characteristics: sales, real estate collateral value, non-real estate collateral, bank debt, non-bank debt. The main results are:

  • The probability that a firm applies for a loan when using real estate as collateral is lower in states that were hardest hit by the housing bust (Table s4).

    Table 4.

    Panel Regression Estimates for Probability of a Firm Loan Application

    article image
    Note: The dependent variable is the probability that a firm does apply for a new loan. Panel probit model with random effects. Standard errors with white correction are in italics. *** 1 percent significance. ** 5 percent. * 10 percent.

  • The probability that a loan application is approved increases when the collateral assisting the application is represented by real estate than when it is represented by other assets. However, the coefficients are not statistically significant in either of the two sub-samples (Table 5).

Table 5.

Panel Regression Estimates for Probability that a Firm Loan Application is Approved

article image
Note: The dependent variable is the probability that a firm does apply for a new loan. Panel probit model with random effects. Standard errors with white correction are in italics. *** 1 percent significance. ** 5 percent. * 10 percent.

D. Conclusions

13. The chapter provides some evidence that access to credit for small businesses is still impaired, mainly as the value of housing as collateral has weakened. Using a dataset on startups suggests that small young businesses may face difficulties in accessing bank credit, especially when located in areas most affected by housing price shocks, in line with recent literature.7 Our results suggest that a credit channel may be at work, akin to the home equity to financing channel suggested by the literature.

14. The case for policies supporting small business finance seems stronger than before the crisis. The U.S. Small Business Administration provides a number of financial assistance programs for small businesses that have been specifically designed to meet key financing needs, including debt financing, surety bonds, and equity financing. Policies to overcome these difficulties could include a bolstering of the SBA financial assistance programs aimed at easing the access to debt financing. Such policies might have a beneficial effect on job creation, 60 percent of which is done by small businesses, and probably a higher effect if targeted to ease the constraints faced by new businesses, that have the potential to enhance the employment and growth prospects of the economy with new products and technologies.8

References

  • Berger A.N. and Udell G.F. (2006), “A More Complete Conceptual Framework for SME Finance”, Journal of Banking and Finance, 30 (11), 2945-66.

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  • Federal Reserve Board (2012), “Report to the Congress on the Availability of Credit to Small Businesses”.

  • Fort T., J. Haltiwanger, R. S. Jarmin and J. Miranda (2012) “How Firms Respond to Business Cycles: The Role of Firm Age and Firm Size”, Paper presented at the 13th Jacques Polak Annual Research Conference at the IMF.

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  • Jiménez G., S Ongena, J. Peydró and J. Saurina (2011) “Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications”, American Economic Review.

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  • Petersen M. A. and Rajan R.G. (1994), “The Benefit of Firm-Creditor Relationships: Evidence from Small Business Data”, Journal of Finance, (1), pp. 337.

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  • Robb Alicia, and Reedy E.J. (2012), “An Overview of the Kauffman Firm Survey”.

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  • U.S. Small Business Administration Office of Advocacy (2010), “Small Business lending in the United States, 2009–10.

1

Prepared by Francesco Columba with research assistance by Madelyn Estrada. We thank the Kauffman Foundation for granting access to the restricted-access data from the Kauffman Firm Survey, Roberto Cardarelli and Gian Maria Milesi-Ferretti for useful comments.

2

In the rest of the chapter SMEs are firms with less than 500 employees, in line with the United States Small Business Administration (USSBA) definition USSBA, 2010.

3

Data on loan applications are available from 2007.

5

In the first quarter of 2012 more than two thirds of total small business debt was represented by mortgages.

United States: Selected Issues
Author: International Monetary Fund. Western Hemisphere Dept.