The firms’ debt reversibility trend: An application to a large sample of industrial SMEs

Figures & data

Table 1. Subsectors (Industry)

NACE Rev. 2	Small and medium-sized industrial enterprises (SMEs)		Percentage	N° Firms
(2 digits)
Codes	Sectors	Freq.
10	Manufacture of food products	3 866	10.84	551
11	Manufacture of beverages	947	2.65	134
13	Manufacture of textiles	2 277	6.38	310
14	Manufacture of wearing apparel	2 888	8.10	426
15	Manufacture of leather and related products	2 193	6.15	316
16	Manufacture of wood and products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials	1 801	5.05	247
17	Manufacture of paper and paper products	771	2.16	105
18	Printing and reproduction of recorded media	1 046	2.93	141
19	Manufacture of coke and refined petroleum products	29	0.08	5
20	Manufacture of chemicals and chemical products, except pharmaceuticals	969	2.72	134
21	Manufacture of basic pharmaceutical products and pharmaceutical preparations	190	0.53	31
22	Manufacture of rubber and plastic products	2 007	5.63	272
23	Manufacture of other non-metallic mineral products	2 648	7.42	370
24	Manufacture of basic metals	392	1.10	55
25	Manufacture of fabricated metal products, except machinery and equipment	6 703	18.79	894
26	Manufacture of computer, electronic and optical products	197	0.55	34
27	Manufacture of electrical equipment	678	1.9	103
28	Manufacture of machinery and equipment n.e.c	1 900	5.33	265
29	Manufacture of motor vehicles, trailers, and semi-trailers	628	1.76	86
30	Manufacture of other transport equipment	171	0.48	33
31	Manufacture of furniture	1 713	4.8	232
32	Other manufacturing	645	1.81	93
33	Repair and installation of machinery and equipment	1 010	2.83	153
Total		35 669	100.00	4 990

OBS: Codes according to NACE Rev. 2 Primary

Table 2. Definition of the variables

Variables	Terms	Measures
Dependent variable:
Change in the Total debt ratio	ΔTotDebt	The ratio of the annual change in the total debt to total assets *
Independent Variables:
Distance from observed debt to optimal debt	DistTO	The ratio of the difference between the optimal debt (forecast cross-sectional model) in the current period and the observed debt in the current period to total assets **
Distance from observed debt and the target debt	DistIN	The ratio of the difference between the objective debt in the current period and the observed debt in the current period to total assets ***
Distance from observed debt to objective debt	DistMA	The ratio of the difference between the sample period average debt and the observed debt in the current period to total assets ****
Assets tangibility	Tang	The ratio of Total fixed assets to Total assets
Firm size	SIZE	Natural logarithm of Total assets
Non-debt tax shield	NDTS	The ratio of the Depreciation of fixed assets over the period to Total assets
Return on assets	ROA	Earnings before tax divided by total assets
Effective Income Tax Rate	EfTax	Tax paid to income before taxes
Growth opportunities	Intang	The ratio between intangible assets and total assets
Assets tangibility (Industry average)	TangMI	The ratio of the Average Total Fixed Assets to Total Assets of the industry
Firm size (Industry average)	SIZEMI	Average of the Natural logarithm of Total assets of the industry
Non-debt tax shield (Industry average)	NDTSMI	The ratio of the average depreciation of fixed assets for the period to Total assets, of the industry
Return on assets (Industry average)	ROAMI	The ratio of industry average earnings before tax to Total assets of the industry
Effective Income Tax Rate (Industry average)	EfTaxMI	Effective Average Rate of Income Tax paid by the industry
Growth opportunities (Industry average)	IntangMI	The ratio of the average of industry Intangible Assets to Total Assets of the industry
COVID-19 impact on the Portuguese SMEs’ capital structure	Covid	This variable is dichotomous: it assumes the value of 1 for the year 2019, and 0 otherwise

OBS: * Total debt: We define the total debt ratio as total liabilities divided by total assets (determined by the total debt ratio, as total liabilities divided by total liabilities plus net worth (Net worth = “Total Assets subtracted by Total Liabilities”; e.g., Booth et al., 2001; Rajan & Zingales, 1995). The annual change is calculated by the difference between the ratio of total debt at time t subtracted by total debt at time t-1.

** The optimal leverage was determined for each firm and each year by a provisional regression model (cross-sectional) determined in an “endogenous” way, with the firm characteristics (variables that are the most important determinants of the capital structure of each firm): Tang; SIZE; NDTS; ROA; EfTax; Intang). Optimal leverage varies according to the state of the company (its capital structure) and each year (e.g., Ozkan, 2001, 194; Flannery & Rangan, 2006; Byoun, 2008; Faulkender et al., 2012; Devos et al., 2017; Aybar-Arias et al., 2012).

***The objective debt in the current period is the median of its industry debt.

****The firm’s debt average was determined by the firm’s debt average in the sample period

Table 3. Statistics of variables *

Variables	N° Observations	Average	Standard deviation	Minimum	Maximum
ΔTotDebt	35,669	−0.002	0.084	−0.612	0.610
DistTO	35,649	0.186	0.101	0.000	0.500
DistIN	35669	0.131	0.094	0.000	0.598
DistMA	35669	0.063	0.056	0.000	0.462
Tang	35,669	0.350	0.198	0.000	0.994
ROA	35669	0.047	0.074	−1.052	0.802
SIZE	35669	14.844	1.048	10.335	17.727
NDTS	35656	0.045	0.056	0.000	2.074
EfTax	35,669	0.269	3.692	−0.738	0.996
Intang	35,662	0.006	0.027	0.000	0.763

OBS: * Results obtained by the STATA software.

Table 4. Correlation matrix

Variables	ΔTotDebt	DistTO	DistIN	DistMA	Tang	ROA	SIZE	NDTS	EfTax	Intang
ΔTotDebt	1.0000
DistTO	0.1594*	1.0000
DistIN	0.1657*	0.3429*	1.0000
DistMA	0.0844*	0.0364*	0.1988*	1.0000
Tang	0.0311*	0.4187*	0.1221*	0.0617*	1.0000
ROA	−0.1460*	−0.3282*	−0.1045*	−0.0070	−0.1545*	1.0000
SIZE	−0.0169	0.4206*	0.0608*	−0.0882*	0.2508*	−0.0400*	1.0000
NDTS	−0.0135	0.0178	0.0024	0.0401*	0.1804*	0.0292*	−0.0721*	1.0000
EfTax	0.0007	−0.0122	−0.0016	0.0000	−0.0147	−0.0053	−0.0167	−0.0030	1.0000
Intang	0.0075	0.0463*	0.0187	0.0104	0.1342*	−0.0535*	0.0767*	−0.0327*	−0.0044	1.0000

OBS: * Significance at 5% level

Table 5. Pairs test of the differences among coefficients of the variables of the distances to target debt

Pairs (distances to target debt)	Difference test
(i) DistTO—DistIN	11.80***
(ii) DistTO—DistMA	17.90***
(iii) DistIN—DistMA	0.4612

OBS: *** Significant at the 1% level

Table 6. Estimates results

Dependent variable: ΔTotDebt Independent variables:	Model 1—TO^# Trade-off Perspective	Model 2—IN^# Herd behaviour Perspective	Model 3—MA^# Mechanical mean reversion Perspective
DistTO	0.1472163*** (0.004846)
DistIN		0.1305728***(0.0052399)
DistMA			0.1267113***(0.0119810)
Tang	0.0320282***(0.0070195)	0.0498074***(0.0070149)	0.0544368***(0.0070587)
SIZE	0.0172271***(0.0019059)	0.0217075***(0.0018810)	0.0261971***(0.0018984)
NDTS	−0.0436212***(0.0128333)	−0.0428525*** (0.0120963)	−0.0457396***(0.0123184)
ROA	−0.2020923***(0.0109391)	−0.2300582***(0.0109051)	−0.2427580***(0.0111035)
EfTax	−0.0000342 (0.0001095)	−0.0000569 (0.0001024)	−0.0000585 (0.0001009)
Intang	−0.0345834 (0.0343465)	−0.0553887 (0.0337550)	−0.0597415 (0.0337774)
TangMI	−0.0596814***(0.0075288)	−0.0626114***(0.0075363)	−0.0645956***(0.0075980)
SIZEMI	−0.0251978***(0.0019180)	−0.0252797***(0.0019085)	−0.0289001***(0.0019213)
NDTSMI	0.0713261***(0.0191116)	0.0757493***(0.0187278)	0.0749740***(0.0189189)
ROAMI	0.1803194***(0.0142887)	0.1536201***(0.0142231)	0.1454565***(0.0142593)
EfTaxMI	0.0003868 (0.0004387)	0.0005227 (0.0004515)	0.0005818 (0.0004547)
IntangMI	0.0806179 (0.0410396)	0.0840304***(0.0403843)	0.0847958***(0.0400754)
Covid	−0.0072167***(0.0013335)	−0.0079945***(0.0013355)	−0.0108345***(0.0013712)
Cons	0.0981873***(0.0071733)	0.0404949***(0.0068673)	0.0370042***(0.0070148)
Observations	35 649	35 649	35 649
F (14. 35,634)	135.79	109.35	72.83
Prob. > F	0.0000	0.0000	0.0000
R-squared	0.0641	0.0649	0.0512
Root MSE	0.08131	0.08127	0.08187

OBS: Estimates - OLS estimator - white’s test heteroskedasticity - robust standard errors; *** Significant at the 1% level; MI: referring to the average variables values of the industry to which firms belong; # indicates the perspective underlying each model, respectively: (TO - Trade-off theory), (IN - Herd behaviour theory), (MA - Mechanical mean reversion theory) - each perspective is according to the proxy used to determine the target debt in each model.

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