1、 外文 翻译 Small Business Reliance on Bank Financing in Ghana Material Source： Emerging Markets Finance and Trade Author： Joshua Abor and Nicholas Biekpe There is growing recognition of the importance of small and medium-sized enterprises(SMEs) to economic development. In many countries, SMEs make up th
2、e majority of businesses and account for the highest proportion of employment. The economic and social contributions of SMEs suggest that it is in the public interest for SMEs to thrive (Fisher and Reuber 2000). However, SMEs often have difficulty financing their operations. Biekpe (2004) argues tha
3、t most small businesses,especially in sub-Saharan Africa, fail in their first year due to lack of support from government and traditional banks. Prior research has noted that banks are a major source of external capital forsmall firms (see Cole and Wolken 1995; Petersen and Rajan 1994; Scherr et al.
4、 1993). However, small firms find it more difficult to obtain bank loans than do large firms (Orser et al. 1994; Peterson and Schulman 1987). Binks et al. (1992) caution that small businesses restricted access to bank debt may not be directly attributable to their size, but rather to problems associ
5、ated with the availability ofinformation used to evaluate a project, or information asymmetry. Banks generally prefer borrowers with good track records of profitability, some degree of longevity,longer-term banking relationships, and assets that can be used as collateral (Berger and Udell 1995; Cole
6、 and Wolken 1995; Ennew and Binks 1995; Weinberg 1994),and they employ certain strategies to minimize the risks in dealing with potential loan borrowers. To reflect the greater uncertainty of repayment, banks may raise the interest rates on loans to riskier borrowers, such as small businesses (Berge
7、rand Udell 1995). Previous empirical studies have also identified a disparity between the demand for bank credit by SMEs and the supply of bank funds in Ghana. This has mainly been attributed to cumbersome banking procedures, the absence of viable and bankable projects, the lack of collateral, and h
8、igh interest rates on bank loans (see Aryeetey 1998; Bigsten et al. 2000; Buatsi 2002; Sowa et al. 1992). The main financial challenge for SMEs in Ghana is access to affordable credit over a reasonable period, which, according to Tagoe et al. (2005), is determined by the financing needs of SMEs and
9、the actions of investors. Tagoe et al. (2005) suggest that SME financing needs reflect their operational requirements, whereas investors actions depend on their risk perception and the attractiveness of alternative investments, which affects their willingness to invest. Previous studies, however, fo
10、cused mainly on the problems SMEs face in accessing bank loans generally. What determines SMEs access to bank finance in Ghana in particular remains unexplored. This paper examines the determinants of bank financing of SMEs in Ghana by employing a panel regression model. Methodology This study explo
11、res the determinants of bank financing of Ghanaian SMEs b y employing firm-level characteristics identified in previous empirical studies examining the financial structure of SMEs. The characteristics include the age and size of the firm, asset tangibility, profitability, and firm growth. This study
12、 also includes macroeconomic variables inflation and interest rates as determinants of bank finance. Sample and Variables Empirical analysis is based on a sample of 105 SMEs, drawn from databases of firms from the Association of Ghanaian Industries and the National Board for Small-Scale Industries.
13、The sample selection was based on the criteria set by the Regional Project on Enterprise Development for SMEs in Ghana, meaning that firms with less than 100 employees were included in the study sample. The data were derived from the firms during a six-year period, 1998 to 2003. This study focused o
14、n SMEs that had bank loans in their balance sheets during that period. The dependent variable used to measure bank financing is the bank-debt ratio, or the proportion of the total debt obtained from banks, and is defined as the ratio of bank debt total debt. This measures the role of bank financing
15、in the SME sector. Firm age is included in the model to proxy reputation. It is believed that as a firm stays in business, it establishes itself as a continuing business and therefore increases its capacity to take on more debt; hence, age is positively related to debt. Before granting a loan, banks
16、 tend to evaluate the creditworthiness of entrepreneurs, who are generally believed to pin high hopes on very risky projects that promise high profitability rates. To overcome problems in evaluating creditworthiness, Diamond(1989) suggests using firm reputation the good name a firm has built up over
17、the years that is understood by the market, which has observed the firms ability to meet its obligations in a timely manner. Rajan (1992) and Petersen and Rajan(1994), among others, argue that a long lending or banking relationship reduces the severity of informational asymmetries for banks by infor
18、ming them about the borrowers credit history and account movements, as well as the personal behavior of the firms manager. Timmons (1994) observes that capital requirements are different at different stages of firm growth. Young firms may be able to draw capital from internal sources, such as earnin
19、gs, and informal sources, such as family and friends. As a successful firm grows, however, more capital is required to finance growth, and at some point, the firm must turn to external sources, such as banks.Consequently, the expected sign is positive. Firm size, which the model measures as the loga
20、rithm of total assets, represents either the largeness or smallness of the firm. The larger the firm, the lower the probability of default, which in turn is related to greater diversification, availability of collateral, or commercial success. Its expected effect on the probability of obtaining cred
21、it is positive. Smaller firms, on the other hand, may find it relatively more costly to resolve information asymmetries with lenders, and thus may present lower debt ratios. Smaller enterprises have greater problems with bank credit than do larger firms because the success rate for large firms apply
22、ing for bank loans, for instance, is higher than that of smaller firms (Aryeetey et al. 1994). Firm size is predicted to be related positively to the bank-debt ratio of SMEs. Diamond (1991) and Ooi (2000), however, find in the case of large firms that the size of the firm is related negatively to th
23、e bank-debt ratio. Asset tangibility is operationalized as the tangible fixed assets of the firm divided by the firms total assets. The ratio of tangible fixed assets to total assets is seen by Cassar and Holmes (2003) as an appropriate measure of asset structure and collateral value. It is suggeste
24、d that SMEs access to bank financing, especially long-term loans, depends upon whether the lending can be secured by tangible assets (Ang et al. 1995; August et al. 1997; Berger and Udell 1995, 1998; Boot et al.1991; Storey 1994). SMEs that invest heavily in tangible fixed assets tend to have higher
25、 bank-debt ratios, as tangible fixed assets can be used as collateral, reducing the banks potential losses for a given interest rate and discouraging moral-hazard behavior. It is therefore hypothesized that there is a positive relation between asset tangibility and bank-debt ratio. Profitable firms
26、have low bankruptcy risk and therefore can attract more bank loans (Storey 1994). Profitability is measured as earnings before interest and taxes,divided by total assets. According to Ooi (1999), profitable firms that are more attractive to financial institutions as lending prospects are likely to a
27、ttract more external debt capital. The higher a firms profitability, the lower the probability of default,and the higher the probability of successfully obtaining a bank loan. This suggests that highly profitable SMEs can easily access more bank finance. We therefore expect a positive relation betwe
28、en profitability and the bank-debt ratio. Growth is measured by diversification through exports. SMEs involved in export are seen to be more diversified, and as such, can accommodate greater debt capital (Abor 2004). A firms export performance may convey valuable information to a bank: First, it rev
29、eals the degree of competitiveness in usually aggressive markets, and second, it indicates productive diversification against domestic shocks. The probability of default is likely to be lower for export-oriented firms, provided the bank trusts or confirms the firms expectations. It is measured throu
30、gh a dummy variable, taking the value 1 if the firm exports and 0 otherwise. A positive relation is expected. The macroeconomic variables the inflation and interest rates are expected to have negative relations with bank finance, as SMEs are discouraged from taking out loans from banks at higher int
31、erest rates. During inflationary periods, banks increase their lending rates to cover their costs. Also, banks prefer investing their resources in government securities rather than lending to risky SMEs. The Model This study adopts the model used by Ooi (2000), modifying it where necessary. The new
32、model considers the relation between the bank-debt ratio and age and size of the firm, asset tangibility, profitability, and growth. It includes the inflation and interest rates as macroeconomic variables, as used in standard financial-structure literature (see Demirgc-Kunt and Maksimovic 1999). The
33、 model for the empirical investigation takes the following form: yit = Xit + Mit + i + t + it, (1) where yit represents the bank-debt ratio that is, the ratio of bank debt to total debt for firm i in time t; Xit is a vector of firm-level characteristics, such as the age and size of the firm, asset t
34、angibility, profitability, and growth; Mit is a vector of macroeconomic variables that is, the inflation and interest rates; i is the individual specific effects; t is the time-specific effects; and it is the residual term. Empirical Results Descriptive Statistics Table 1 summarizes the dependent an
35、d independent variables, reporting the mean statistics for the attributes of the firms included in the sample. Firm age has a mean (median) age of 11.0949 (8.0), meaning that, on average, the SMEs in our sample have been in business for eleven years. Size in terms of the log of total assets has a me
36、an (median) of 21.2280 (21.3518). Asset tangibility has a mean (median) of 0.4638 (0.4386), indicating that, on average, tangible fixed assets account for 43.86 percent of total assets. Profitability shows a mean value of 0.0891, suggesting a return on assets of 8.9 percent. On average, 33.60 percen
37、t of the SMEs in our sample are in the export business. The average inflation and interest rates during the six-year period are 21.24 percent and 33.26 percent, respectively. Regarding our investigation of SMEs reliance on bank borrowings, the financial statements identify explicitly the aggregate a
38、mount of the total debt of the firms, as well as the amount made up of bank borrowing. The reported figures only reflect loans that are actually outstanding, and do not account for undrawn loan commitments. Although the amount of nonbank debt is not reported, it can be inferred by deducting the amou
39、nt of bank debt from the total outstanding debt. The mean bank-debt ratio is 0.2114, suggesting that, on average, less than a quarter of SMEs debt financing is obtained from banks. Regression Model Results:A panel regression model is used to estimate the effect of each explanatory variable on the ba
40、nk-debt ratio. The panel data set is useful because it allows us to separate out economic effects that cannot be distinguished using either cross-section or time-series data alone. The method of pooling cross-sectional and time-series data is, however, susceptible to heteroskedasticity, which we cor
41、rect using White heteroskedastic-consistent standard errors and covariance. The results were derived using Eviews 5 application software. The ordinary least square (OLS) panel regression was found to be the most robust after testing for various options of the panel-data regression, such as fixed and
42、 random effects. The results of the OLS panel regression are therefore presented in Table 2. The empirical results show that age has a positively significant relation to the bank-debt ratio. This could be because older SMEs, in terms of how long they have been in business or the length of the relati
43、onship they have with banks, tend to have good track records and therefore fewer problems acquiring bank loans. Relatively older and experienced SMEs also appear to have high credit ratings and therefore more easily access bank loans than do their newer counterparts. The findings support those of Ra
44、jan (1992) and Petersen and Rajan (1994), who argue that a long-term lending relationship reduces the severity of informational asymmetries Table 1 Description Summary Statistics Variable Mean Standard deviation Minimum Median Maximum Bank-debt ratio 0.2114 0.2985 0 0.036 0.9974 Age 11.0949 8.8286 1
45、 8 39 Size 21.2280 1.9390 15.7910 21.3518 25.2359 Tangibility 0.4683 0.2950 0.0006 0.4386 0.9999 Profitability 0.0891 0.1747 -0.7712 0.0718 1.6393 Growth 0.3360 0.4730 0 0 1 Inflation 21.2423 7.1515 12.4 17.8 32.9 Interest 33.2681 6.0562 26.62 34.18 47.53 for banks by informing them about the borrow
46、ers credit history and account movements, as well as and the personal behavior of the firms manager. The banks decision to lend or not to lend to new firms is assumed to depend on the expected value of the return. Storey (1994) is of the opinion that key elements in the decision will not only be the
47、 expected default rate, but also the growth rate of the firm, because new firms that grow quickly use bank firms that grow slowly. Table 2 Regression model results variable Coefficient Standard error t-value t-probability Constant -0.6709 0.0947 -7.0834 0 Age 0.0025 0.0007 3.4632 0.0006 Size 0.0356
48、0.0034 10.3913 0 tangibility 0.1860 0.0283 6.5808 0 profitability -0.1340 0.0420 -3.1887 0.0016 Growth 0.0112 0.0187 0.5997 0.5490 Inflation -0.0008 0.001 -0.7953 0.4270 Interest -0.0004 0.0011 -0.3913 0.6958 R 2 0.7841 Standard error of regression 0.2770 f-statistic 187.3460 Probability 0 (f-statis
49、tics) The significantly positive relationship between firm size and reliance on bank debt is consistent with the argument that the larger the firm, the lower is the probability of default, which in turn is related to higher diversification, availability of collateral, and commercial success. The results of this study indicate that SMEs with high asset value have easier access to bank financing. Relatively smaller firms denote higher risk, which could cause banks to shy away from lending to them. Larger firms may have well
