Empirical Strategy

The main aim of this research is to investigate the effect of the credit crisis on financial policies of private firms in the UK. To achieve the objective of the study, our identification strategy has three elements that help to overcome this problem. First, we identify the exogenous credit crisis. The recent credit crisis 2007-2009 provides us with such an event, and this has been argued in some recent papers (Kahle and Stulz, 2010; Duchin et al., 2010). Duchin et al., (2010) for instance, argue that ‗The crisis represents an unexplored negative shock to the supply of external finance for non-financial firms‘. Second, our empirical strategy relies on the firm fixed effect model. As this study employs panel data, there is a potential concern of unobserved heterogeneity. This is because the data contains multiple observations per firm. The fixed effect model will help to account for this concern. In addition, as this study identifies the supply channel, the fixed effect model can be regarded as the most appropriate for this investigation. The fixed effect regression model that we use in this study is highlighted below.

Yit = λ1i+Π1*Crisisit + δ2* ΣXit + δ3 *Crisis* Σ Xit + μit (1) The last element of our identification strategy is the inclusion of a set of control variables that

partial out the effect of demand factors on our variable of interest. We use variables (such as size, growth and profitability) highlighted in latest research findings to be consistently and closely related to firm financing decisions (Rajan and Zingales, 1995; Leary, 2009). Love et al., (2007) however, observe that ‗..causal factors that are either time-invariant (e.g., industry) or slow changing (e.g., size) should be captured by the fixed effects‘. We therefore include only return on assets, and growth and their interaction with crisis dummy in regression models as proxy for firm demand. These variables however change with the dependent variables. In light of all these points we construct the following models.

Long term debt = β 0+ β1 *ROA + β2* GT+ β3* CR + β4* GT *CR + β5* ROA *CR+ μit (2)

Short term debt = β 0+ β1 *ROA + β2* GT+ β3* CR + β4* GT *CR + β5* ROA *CR+ μit (3)

Trade Credit = β 0+ β1 *CF + β2* GT+ β3* CR + β4* GT *CR + β5* CF *CR+ μit (4)

Net Debt Issue = β 0+ β1 *ROA + β2* GT+ β3* CR + β4* GT *CR + β5* ROA *CR+ μit (5)

Net Equity Issue = β 0+ β1 *ROA + β2* GT+ β3* CR + β4* GT *CR + β5* ROA *CR+ μit (6)

Cash Reserve = β 0+ β1 *CF + β2* GT+ β3* CR + β4* GT *CR + β5* CF *CR+ μit (7)

3.2 Data

Data is extracted from Financial Analysis Made Easy (FAME) database for the years 2004- 2009. We exclude assurance companies, guarantees, limited liability partnerships, public investment trusts and unlimited companies (Michaely and Roberts, 2007; Brav, 2009). Our sample only includes firms, which have registered offices in the United Kingdom. We exclude firms that operate in financial sectors for standard reasons. In addition, we exclude firms in public sector and regulated industries (Duchin et al., 2010; Chava and Purnanandam, 2011). The issue of missing observations is a serious problem in any research study. To avoid this problem the sample firms included in this study must have no missing values for the key variables of the study such as short term debt, long term debt, trade credit, issued capital, cash and cash equivalent, EBIT, and total assets. This is in line with the existing literature (for example, Sufi, 2009; and Lemmon and Roberts, 2010). The final sample thus includes a total of 4973 firms. In addition, for addressing the outliers problem we winsorized the top and bottom 1% of all variables. This is in line with previous literature (see for example, Love et al., 2007).

4. Results

4.1 Financial Crisis and the Leverage Ratios

To examine the effect of the credit crisis on the leverage ratios of private firms, we first run the fixed effect regression on total debt ratio. Next, we divide the total debt ratio into its components such as short term debt, long term debt and trade credit, then we ran separate regressions on each of these variables. The coefficients in table 1 and subsequent tables should be interpreted as follows. CR represents crisis dummy for the crisis period. The impact on the dependent variable during the crisis period is given by the sum of the coefficient associated with the given variable and variable interacted with the crisis dummy. The crisis dummy is interacted with control variables to determine the change in response relative to the pre-crisis period. The coefficient referring to the pre-crisis period is given by the non-interacted variables. CF is the measure of cash flow, GT is the measure of sales growth, and ROA is the measure of firm performance. ***, **, * representing 1%, 5% and 10% levels of significance respectively.

Results from the estimation of model 1 are presented in Table 1. The dependent variable in model 1 is the total debt ratio. It shows that all independent variables have expected signs and are highly significant. As expected, the coefficient on return on assets (ROA) variable is negative and significant at the level of 1% or better in both time periods. This is consistent with the predictions of the pecking order theory. This implies that profitable firms use less debt (Gaud et al., 2007; Aggarwal and Kyaw, 2010; Voutsinas and Werner, 2011) during the crisis period. Similarly, the coefficient of the growth variable is positive in both the pre-crisis and the crisis periods and is significant at the level of 1% or better. This implies that growing firms need more external finance which is consistent with earlier published studies (Michael et al., 1999a; Sogorb-Mira, 2005). We focus on our main variable of interest in the subsequent models.

The main variable of interest is the crisis dummy. The results of Model 1 highlight that the coefficient on the crisis dummy is negative and significant at the level of 1% or better. This implies that the financial crisis has a negative impact on a firm‘s total debt ratio. In other words, the flow of credit to these firms was reduced during the crisis period. This suggests that supply of credit is an important determinant of firm financing decisions. Since total debt encompasses all forms of debt, which means that aggregate external financing activities of private firms contracted in response to the credit supply shocks. However, from the results of model 1 the impact on the components of the firm financial mix is not clear. To investigate this further, the model 2 is then run on long term debt.

Table 1: Effect of financial Crisis on Leverage Ratio

Variables Model 1

Total Debt

Model 2 Long term debt

Model 3 Short term debt

Model 4 Trade credit ROA -0.312 -0.080 -0.174 --- (-12.02)*** (-4.07)*** (-11.01)*** GT 0.026 0.011 -0.003 0.009 (4.19)*** (2.12)** (-0.82) (2.31)** CF 0.046

(4.08)*** CR*ROA -0.225 -0.112 -0.051 --- (-7.51)*** (-5.22)*** (-2.72)*** GT*CR 0.049 0.004 0.020 0.040 (5.04)*** (0.48) (2.91)*** (6.51)*** CF*CR -0.027 (-2.13)** CR -0.059 -0.006 -0.025 -0.043 (-5.66)*** (-0.79) (-3.47)*** (-6.59)*** C 0.526 0.193 0.172 0.172 (78.04)*** (33.78)*** (36.09)*** (39.73)*** R-squared 0.853 0.853 0.750 0.909 No of Obs 21559 21979 22039 10041 F-statistics 24.171 24.628 12.695 32.071 Prob(F-statistics) 0.000 0.000 0.000 0.000

Results from the analysis of model 2 are presented in table 1. These results highlight that the sign on the coefficient of the crisis dummy is negative, but statistically insignificant. This implies that the credit crisis had no significant impact on the long term debt ratio.

To investigate the impact on short term debt the fixed effect regression model 3 and associated results are reported in table 1. Results show that coefficient on the crisis dummy is negative and significant at the 1% level or better. This reveals that the flow of short term credit to private firms is squeezed as a result of the credit crisis. This suggests that the financial crisis has impaired the short term financing channel for private firms. As private firms are generally considered risky for the reason discussed above, lenders may have squeezed the availability of credit to these firms because it has been shown that banks only consider safer loan options during tight credit conditions (Lang and Nakamura, 1995).

Finally, the fixed effect regression model 4 is run on trade credit and reported the results in table 1. The dependent variable in model 4 is trade credit scaled by total assets. The use of this measure is motivated by the fact that research suggests that ‗...it is a better measure for studying the role of trade credit as a source of finance for firms‘ assets‘ (Atanasova and Wilson, 2003). Since we are interested in the financing motive of trade credit during the crisis period, this measure is the most appropriate in our study. The results highlight that all variables are statistically significant. The significance of the control variables in the equation suggest that model is the best fit. This is also evident from the high R-squared value of 91%. Interestingly, the coefficient on the crisis dummy variable is negative and significant at the 1% level or better. The negative coefficient reveals that supply of trade credit decreased during the crisis period. The general expectation is an increase in the supply of trade credit during the crisis period, but our result finds the opposite. The reduction of trade credit also shows the lack of substitution towards this short term source of finance during the crisis

period. The results further suggest that the supply of trade credit decreases when the financial crisis reduces the availability of credit, supporting the view that trade credit is a complement for bank credit rather than a substitute.

These results thus contribute to the existing literature by first, suggesting that both the demand and supply factors are crucial in understanding the firm financing decisions. Second, it suggests that the short term financing channel (i.e. short term credit and trade credit) is sensitive to variations in the supply of credit. Third, it suggests that trade credit does not compensate for a reduction in the supply of credit from financial institutions. In the next section, we examine the effect of credit supply shocks on the behaviour of alternative sources of finance.

4.2 The Use of Alternative Sources of Finance

To investigate whether private firms substitute alternative sources of finance to offset the reduction of debt in their capital structure, the fixed effect panel regression are run on net debt issued, net equity issued, and internal finance. When we run model 5, the fixed effect panel regression model is run on net debt issued. The results are presented in table 2, which highlights that all the variables are statistically significant. The coefficient of crisis dummy is - 0.26 and is significant at the 1% level. This is evidence that net debt issuance activities of private firms are adversely affected by the credit crisis. This result confirms our earlier findings which suggest that contractions in credit supply have negatively affected the leverage ratios of private firms. Overall, the fixed effect results suggest that net debt issue of private firms was reduced during the crisis period.

Model 6 is then run on net equity issued. The results are also reported in table 2. The coefficient on the crisis dummy is positive and significant at the 1% level or better. These results show that net equity issued by private firms increased following contractions in the supply of credit. This is consistent with the credit supply effect, that is, when there are exogenous shocks to the supply of credit, this reduces credit availability and firms therefore issue more equity to offset the adverse effect of credit contractions. It implies that private firms substitute equity finance to minimize the effect of credit supply contractions.

Next, we examine the cash reserve to see whether private firms increased the use of internal finance or hold cash during the crisis period. From the estimation of model 7 the regression is run on cash reserves and the results are reported in table 2. The results reveal that the coefficient on the crisis dummy variable is positive and significant. This indicates that private firms held more cash during the crisis period. This is consistent with the precautionary saving motive. Since the financial crisis increased uncertainty about the availability of credit, in response to that, private firms held more cash during the crisis period to hedge themselves from the unexpected reduction of credit in the near future. Our result is in line with the findings in Lin and Paravisini (2010). They report that public firms use more equity financing and hold cash in response to credit contractions, consistent with the precautionary saving motive. Our results, however, do not seem to be in line with some of the recent findings in this area (see for example, Leary, 2009; Lemmon and Roberts 2010). Our result adds to this strand of literature first, by providing evidence from the perspective of private firms. Second, the results suggest that private firms hold more cash in response to exogenous credit contractions.

Table 2: Financial Crisis and Alternative Sources of Finance

Variables Model 5

Net Debt Issue

Model 6 Net Equity Issue

Model 7 Cash Reserve ROA -1.201 -0.062 ---- (-9.94)*** (-2.27)** GT 0.253 0.033 5.049 (6.38)*** (3.44)*** (3.16)*** CF 22.587 (10.79)*** CF*CR ---- ---- 5.021 (1.46) CR*ROA 0.269 0.006 ---- (2.22)** (0.27) GT*CR 0.168 -0.027 -4.524 (2.85)*** (-1.83)* (-2.77)*** CR -0.256 0.040 4.390 (-4.16)*** (3.21)*** (2.27)** C -0.026 0.962 -4.256 (-0.61) (128.01)*** (-2.06)*** R-squared 0.220 0.321 0.351 No of Obs 20476 9990 6764 F-statistics 1.111 1.519 1.291 Prob(F-statistics) 0.000 0.000 0.000 5. Conclusion

This paper examines the effects of credit contractions on financial policies of private firms. The results suggest that credit supply shocks have adversely affected the total debt ratio of private firms. The results further highlight that credit contractions have impaired short term financing channels (such as short term debt and trade credit) while the credit crisis has no significant effect on the long term financing channel. As a consequence, private firms hold cash and issue equity to hedge themselves from the negative effect of credit contractions. We, however, do not find any evidence that private firms substitute to net debt issue and trade credit. Overall, our results suggest that financial policies of the private firms are vulnerable to variations in the supply of credit.

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