Debt Financing and Survival of Firms in Malaysia

Debt Financing and Survival of Firms in Malaysia Sui-Jade Ho & Jiaming Soh Bank Negara Malaysia September 21, 2017 We thank Rubin Sivabalan, Chuah Kue-Peng, and Mohd Nozlan Khadri for their comments and suggestions. The views expressed are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Central Bank of Malaysia or of anyone else associated with the Central Bank of Malaysia. Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 1 / 28

Introduction and Motivation Business dynamism and new firm formations is vital to productivity and sustained economic growth Net entry of firms accounts for 25% of U.S. productivity growth (Foster et al., Nov 1998) Net entry of firms accounts for 72% of Chinese productivity growth (Brandt et al., March 2012) The exit of inefficient firms is crucial to enable the reallocation of resources (labor and capital) towards more productive firms. Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 2 / 28

Introduction and Motivation (continued...) However, in the presence of capital market imperfections, even efficient firms may be forced to exit due to lack of funds (Lester, 1966; Patrick and Scharfstein, 1990) This could hurt aggregate productivity growth (Zingales, 1998; Khanna and Tice, 2005) In an ideal environment, debt should not affect the survival and the life expectancy of firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 3 / 28

Introduction and Motivation (continued...) Channels through which high leverage may negatively affect the survival of efficient firms in the presence of capital market imperfections : 1 Highly indebted efficient firms are unable to finance new profitable investments. This eventually force them out of the market (Myers, 1977) 2 Leverage and pricing strategy: Leverage weakens a firm s competitive position (Zingales, 1998) Low debt firms strategically lower prices during recessions to force exit of efficient, financially constrained rivals (Khanna and Tice, 2005) Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 4 / 28

Contribution of our paper Most studies on debt financing are based on observations in developed countries, including the mechanisms of debt Using a firm-level dataset in Malaysia, we explore whether debt has a negative effect on firms in an emerging market by testing the following research questions: Does debt affect the survival of firms? Does debt affect the life expectancy of firms? To our knowledge this is one of the few attempts that link debt with survival and life expectancy of firms in an emerging market In an ideal scenario, efficient firms should not 1) exit the industry or 2) have shorter life expectancy due to leverage Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 5 / 28

Contribution: Findings of this paper Does debt negatively affect the survival of firms? No significant evidence that higher leverage increases the probability of exit for firms in Malaysia Does debt affect the life expectancy of firms? High leverage reduces firms life expectancy, particularly for the efficient firms. Due to high indebtedness, the efficient firms have to forgone profitable investment opportunities Inefficient firms, on the other hand, have shorter life expectancy due mainly to their internal weakness Hence, the negative effect of debt on life expectancy is more pertinent among efficient firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 6 / 28

Data Extracted 184,000 firms located in Malaysia from 2007 to 2015 from the Bureau Van Dijk Orbis worldwide firm dataset Extensive coverage of unlisted firms A few steps to prepare the dataset for analysis A systematic alphanumeric industry codes and locations at the individual firm level is required. Orbis provides only the description of industries and locations The prevalence of outliers and poor quality financial statement information are addressed This leaves us with around 107000 number of firms for our analysis Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 7 / 28

Data (Main Variables) No information in the dataset to identify firms that exit the industry. Definition of exit in our analysis: A firm exit at year t if its sales data is missing at year t and the subsequent years onwards There are two key dependent variables : 1) a dichotomous variable to indicate exit of firms and 2) firms age of death Leverage is defined as the ratio of liabilities-to-total assets Use the following variables to represent firms characteristics that are known to affect firm s survival in the literature 1 Age of firms 2 Size of firms 3 Tangible assets-to-total assets 4 Whether the firms are locally-owned or foreign-owned All standard errors are clustered at city x industry x year level Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 8 / 28

Characteristics of Firms in Malaysia Overall, Malaysian firms are mostly non-listed, young, locally-owned and small-sized companies On average, 4% of the firms in our sample eventually died, and the average life expectancy of firms is 19 years old (a) Distribution of Firm Age (b) Distribution of Firm Size 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 41% 28% 20% 10% 1% 0-3 3-12 12-25 25-40 > 40 6 16 32 46 Micro Small Medium Large Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 9 / 28

Identification Strategy Employ panel regression linear probability approach to test whether leverage affects a firm s exit probability (Equation 1) P rexit i = β 0 + β 1 Lev i,t 1 + β j J (X j,i,t 1 ) + η t + γ + ɛ i,t (1) where Lev i,t 1 is firm s leverage ratio in the past periods. X i,t 1 is firm i s characteristics including 1 Return on assets 2 Age of firms : 0-3, 3-12, 12-25, 24-40, above 40 3 Size 4 Tangible asset to total asset 5 Ownership of firms All regressions are controlled with city x industry x year dummies. All standard errors are clustered at city x industry x year level. j=2 Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 10 / 28

Identification Strategy (continued...) Did a panel regression on firms that eventually exit the industry to test whether leverage affects the life expectancy of firms (Equation 2) AgeDeath i = θ 0 + θ 1 Lev i,t 1 + θ j J (X j,i,t 1 ) + η t + γ + ɛ i,t (2) where the dependent variable AgeDeath i is the age of death for firm i There are 4700 firms that died in the sample (around 4% of the total firms we use in the regression) j=2 Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 11 / 28

Baseline results : Debt and Survival Probability (1) (2) Dependent Variables: Probability of Exit Age of Death Liabilities-to-Assets (t-1) 0.000-0.769*** [0.000] [0.269] Firms' Characteristics Age (t-1. 0-3) -0.010*** - [0.003] Age (t-1, 3-12) 0.007** - [0.003] Age (t-1, 12-25) 0.016*** - [0.003] Age (t-1, 25-40) 0.030*** - [0.003] Size (t-1) -0.004*** 0.138 [0.001] [0.174] Tangible Assets (t-1) -0.005* 0.935 [0.003] [0.714] Foreign-Owned 0.007** 0.059 [0.003] [0.553] Return on Assets (t-1) -0.000-0.118 [0.000] [0.202] Observations 414,550 15,368 Absorb by City Industry Year City Industry Year Year 2007-2015 2007-2015 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 12 / 28

Baseline results : Debt and Survival Probability No significant evidence that higher leverage increases the probability of exit for firms in Malaysia Other firms characteristics play a bigger role in influencing the probability of exit However, leverage has a significant effect on the life expectancy of firms Firms with higher leverage died at a much younger age compared to firms with lower level of leverage Suggests that high debt level does reduce the life expectancy of firms Next to test if the negative effect of debt on the life expectancy of firms applies to both efficient and inefficient firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 13 / 28

Results : Efficient and Inefficient Firms Use a modified Altman-Z score (Altman, 2005) to proxy for firms level of efficiency The lower the Altman Z-score, the more likely the company is headed toward bankruptcy and financial distress. Define these firms as less efficient EMScore = 6.56(X 1 ) + 3.26(X 2 ) + 6.72(X 3 ) + 1.05(X 4 ) + 3.25 (3) where X 1 is working capital to total assets; X 2 is retained earnings to total assets; X 3 is operating income to total assets; and X 4 is equity to total liabilities. The coefficients are from Altman (2005) Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 14 / 28

Distribution of Altman Z-score Figure 3: Distribution of Altman Z-score for Exit and Survived Firms The Z-scores for the dead firms are indeed more on the lower end, can be used as a proxy for firms underlying characteristics Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 15 / 28

Definition of Efficiency Test a few ways to define firm s efficiency A firm is inefficient if its Z-score is below the median Z-score from the dead firms distribution (Method 1) The cutoff for Z-score is chosen such that the number of predicted inefficient firms corresponds to the number of actual exits in our sample (Method 2) Robustness check Interacting continuous Z-score with leverage without choosing a cut-off point Using return on assets as an alternative measure of efficiency Robustness results suggest the same finding Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 16 / 28

Identification Strategy: Efficient and Inefficient Firms Capture the differential effect of leverage on efficient and inefficient firms using the following equation (Equation 4) AgeDeath i = β 0 + β 1 D i + β 2 Lev i,t 1 + β j +β J+1 Lev i,t 1 D i + β j K j=j+2 J (X j,i,t 1 ) j=3 (X j,i,t 1 D i ) + η t + γ + ɛ i,t (4) where the variable D i is the dichotomous variable to indicate inefficient firms. Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 17 / 28

Figure 4: Debt and Life Expectancy: Efficient and Inefficient Firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 18 / 28 Method 1 : Efficient and Inefficient Firms Interestingly, the negative effect of debt on life expectancy is greater for efficient firms than inefficient firms Dependent Variable: Age of Death (1) (2) Efficient Firms Inefficient Firms Liabilities-to-Assets (t-1) -6.799*** -2.909*** [0.602] 0.492 Firms' Characteristics Size (t-1) 0.700*** 0.272 [0.204] 0.205 Tangible Assets (t-1) 3.156*** 1.742*** [0.785] 0.599 Foreign-Owned -0.723 0.195 [0.805] 1.700 Return on Assets (t-1) 0.034-0.664 [0.072] 0.897 Observations 13,850 13,850 Absorb by City Industry Year City Industry Year Year 2007-2015 2007-2015 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1

Discussion : Efficient and Inefficient Firms Conjecture : for inefficient firms, internal weakness is likely the more important factor than debt in influencing their life expectancy But for efficient firms, leverage have greater role in determining their life expectancy because due to high indebtedness, these firms are unable to finance new profitable investments (Myers, 1977), which eventually contributed to their short-life expectancy To test this hypothesis, we investigate if efficient firms in more competitive industries have shorter life expectancy due to leverage since competition for profitable investments will be more intense under this environment Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 19 / 28

Effect of Competition Capture the degree of competition in an industry using the Herfindahl Index constructed at three-digit level Malaysia Standard Industrial Classification code industries We define industry i to be relatively more competitive if the Herfindahl Index of industry i is below the median Herfindahl index from the distribution of all industries Examples of relatively more competitive industries: Construction sector, Wholesale and retail sector Examples of relatively less competitive industries : Agriculture sector, Information and communication sector Run Equation 4 separately on competitive and less competitive industries Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 20 / 28

Results: Competitive and Less Competitive Industries Dependent Variable: Competitive Industries Age of Death (1) (2) Efficient Firms Inefficient Firms Liabilities-to-Assets (t-1) -7.805*** -3.641*** [0.781] 0.607 Firms' Characteristics Size (t-1) 0.787*** -0.113 [0.226] 0.214 Tangible Assets (t-1) 3.715*** 0.818 [0.911] 0.637 Foreign-Owned 0.856 0.477 [0.970] 2.120 Return on Assets (t-1) 0.059-0.189 [0.037] 1.024 Observations Absorb by Year Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 7,733 City Industry Year 2007-2015 (a) Firms in Competitive Industries Dependent Variable: Less-Competitive Industries Age of Death (1) (2) Efficient Firms Inefficient Firms Liabilities-to-Assets (t-1) -5.864*** -1.314* [0.879] 0.793 Firms' Characteristics Size (t-1) 0.786* 1.164*** [0.432] 0.419 Tangible Assets (t-1) 1.823 3.543*** [1.436] 1.110 Foreign-Owned -2.614* -0.373 [1.405] 1.272 Return on Assets (t-1) -2.666** -2.158 [1.315] 1.693 Observations Absorb by Type Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 6,117 City Industry Year 2007-2015 (b) Firms in Less Competitive Industries Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 21 / 28

Discussion: Competitive and Less Competitive Industries The negative effect of debt on the life expectancy of firms is stronger in competitive industries than less-competitive industries. Competition amplifies the negative effect of debt In particular, efficient firms in a competitive market are more negatively affected by higher leverage than efficient firms in less competitive market This lends some supports to the investment channel where due to high indebtedness, more profitable investments are lost to the less-indebted counterparts especially in a competitive environment Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 22 / 28

Summary and Conclusion The findings suggest that high debt level does reduce the life expectancy of firms Particularly for efficient firms. Due to high indebtedness, these firms have to forgone profitable investment opportunities which contributed to their shorter life expectancy This channel is partly verified using the analysis on competitive and less-competitive industries Inefficient firms, on the other hand, have shorter life expectancy due mainly to their internal weakness Hence, the negative effect of debt on life expectancy is more pertinent among efficient firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 23 / 28

Limitations of study Endogeneity issue - to identify an instrument or natural experiment to establish a causal claim between leverage, survival and life expectancy Missing data for firms - to fill in the data gaps with data from other sources Exit could be due to acquisition or merger Testing with alternative measures of efficiency Not looking for a threshold - intuitively threshold could possibly exist, have to verify further Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 24 / 28

Robustness : Efficient and Inefficient Firms Dependent Variable: Age of Death (1) (2) Efficient Firms Inefficient Firms Liabilities-to-Assets (t-1) -4.625*** -2.320** [0.378] [1.245] Firms' Characteristics Size (t-1) 0.171 3.422*** [0.154] [0.795] Tangible Assets (t-1) 2.933*** -2.201 [0.482] [1.715] Foreign-Owned -0.548 7.470 [0.727] [5.894] Return on Assets (t-1) 0.041-2.774 [0.077] [2.458] Observations 13,850 13,850 Absorb by City Industry Year City Industry Year Year 2007-2015 2007-2015 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 Figure 6: Method 2: Efficient and Inefficient Firms Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 25 / 28

Robustness: Efficient and Inefficient Firms Both results show that higher leverage and more efficient firms have shorter life expectancy Dependent Variable: Age of Death Liabilities-to-Assets (t-1) -2.063*** [0.531] Liabilities-to-Assets (t-1) * Altman Z-score -0.183*** [0.034] Firms' Characteristics Altman Z-score (Higher = more efficient) 0.059** [0.026] Size (t-1) 0.495*** [0.159] Tangible Assets (t-1) 2.156*** [0.470] Foreign-Owned -0.608 [0.737] Return on Assets (t-1) 0.023 [0.096] Observations 13,850 Absorb by CITY INDUSTRY YEAR Year 2007-2015 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 (a) Continuous Altman Z-score Dependent Variable: Age of Death Liabilities-to-Assets (t-1) -0.717** [0.310] Liabilities-to-Assets (t-1) * Return on Assets -0.014** [0.006] Firms' Characteristics Return on Assets (Higher = more efficient) 0.125*** [0.042] Size (t-1) -0.058 [0.155] Tangible Assets (t-1) 0.601 [0.612] Foreign-Owned -0.068 [0.688] Observations 15,368 Absorb by CITY INDUSTRY YEAR Year 2007-2015 Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 (b) Alternative Efficiency Measure: ROA Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 26 / 28

Appendix: Characteristics of Firms in Malaysia Summary Statistics: All Firms N % Total Firms Exit 107206 4675 4% Age Age (0-3) 21589 20% Age (3-12) 43727 41% Age (12-25) 30147 28% Age (25-40) 10805 10% Age (40 above) 923 1% Ownership Foreign-Owned 1450 1% Year 2007-2015 Summary Statistics: All Firms N Mean Min Max Age of Death 4675 19.0 2.0 92.0 Liabilities to Total Assets 107206 0.7 0.0 3.2 Return on Assets 107206 0.0-0.7 0.3 Size 107206 1.3 0.0 3.0 Tangible Assets to Total Assets 107206 0.3 0.0 1.0 Year 2007-2015 Figure 8: Summary Statistics for Firms in the Sample Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 27 / 28

Appendix: Large and Small Firms Dependent Variable: Large Firms Age of Death (1) (2) Efficient Firms Inefficient Firms Dependent Variable: Small Firms Age of Death (1) (2) Efficient Firms Inefficient Firms Liabilities-to-Assets (t-1) -8.341* -10.810 [5.038] 11.320 Firms' Characteristics Size (t-1) 1.898 0.449 [2.143] 4.809 Tangible Assets (t-1) -2.146 0.370 [6.956] 7.683 Foreign-Owned -2.820 31.930*** [3.448] 9.544 Return on Assets (t-1) -10.873 22.650 [13.121] 22.510 Observations Absorb by Type Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 (a) Large Firms 851 City Industry Year 2007-2015 Liabilities-to-Assets (t-1) -6.663*** -0.753 [0.618] 0.905 Firms' Characteristics Size (t-1) 0.623*** 0.277 [0.237] 0.228 Tangible Assets (t-1) 3.173*** 1.742*** [0.799] 0.614 Foreign-Owned 0.107 0.538 [1.093] 1.689 Return on Assets (t-1) 0.038-0.753 [0.067] 0.905 Observations Absorb by Type Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 (b) Small Firms 12,998 City Industry Year 2007-2015 Sui-Jade Ho & Jiaming Soh (Bank Negara Malaysia) Debt Financing and Survival September 21, 2017 28 / 28

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