Capital Structure Adjustment Speed: Evidence from Borsa Istanbul Sub-Sectors

Korkmaz, Turhan; Erkol, Aslı Yıkılmaz

doi:10.1007/978-3-030-54108-8_18

Turhan Korkmaz² &
Aslı Yıkılmaz Erkol²

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Abstract

In this chapter, we have scrutinized the adjustment speed of Borsa Istanbul index sub-sectors during the pre-crisis, crisis, and post-crisis periods. The classical dynamic partial adjustment model developed by Flannery and Rangan (Journal of Financial Economics 79:469–506, 2006), which is frequently used in the literature, is used to estimate the target debt level. The adjustment speed could be determined except in one of the six sectors in the BIST100 index. For all periods, the adjustment speed of the sub-sectors is below 50%. Empirical evidence on the existence of the target debt level of these five sectors supported the trade-off theory. Another striking finding is the significant decrease in the adjustment speed of the BİST 100 index sub-sectors during the crisis period.

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Faculty of Economics and Administrative Sciences, Mersin University, Mersin, Turkey
Turhan Korkmaz & Aslı Yıkılmaz Erkol

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Correspondence to Turhan Korkmaz .

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Faculty of Transportation and Logistics, Istanbul University, Avcilar/Istanbul, Turkey
Burcu Adıgüzel Mercangöz

Appendix: Descriptive Statistics

		Growth	Size	D	Roa	Tang
Food, beverage, and tobacco
Pre-crisis (2005–2007)	Mean	0.1128	18.5057	0.4593	−0.0283	0.7055
	Median	0.0707	18.1735	0.4709	−0.0014	0.7200
	Maximum	1.3432	22.1737	0.9117	0.3824	0.9934
	Minimum	−0.7688	16.5566	0.0667	−0.8733	0.1597
	Std. dev.	0.3312	1.2234	0.2104	0.1705	0.2236
Crisis (2008–2012)	Mean	0.0906	18.8013	0.4294	−0.0290	0.7670
	Median	0.0829	18.5705	0.4186	0.0033	0.7798
	Maximum	2.9925	23.0675	0.9777	0.1602	0.9968
	Minimum	−0.8346	16.2374	0.0313	−1.1933	0.2801
	Std. dev.	0.3311	1.4714	0.2161	0.1714	0.1907
Post-crisis (2013–2018)	Mean	0.2189	19.3658	0.4509	0.0486	0.7398
	Median	0.1506	19.1499	0.4653	0.0066	0.7784
	Maximum	5.7992	24.4383	0.9252	5.7148	0.9930
	Minimum	−0.6510	16.3548	0.0283	−0.9495	0.2485
	Std. dev.	0.5398	1.6659	0.2404	0.5093	0.1754
All periods (2005–2018)	Mean	20.6336	19.1537	0.5235	0.1591	66.4286
	Median	13.5850	18.1467	0.4993	−1.8800	65.3750
	Maximum	299.2500	24.4383	0.9777	571.4800	99.5400
	Minimum	−83.460	16.8779	0.0392	−119.330	24.8500
	Std. dev.	49.9473	2.1723	0.2574	64.7783	20.4882
Textile, wearing apparel, and leather
Pre-crisis (2005–2007)	Mean	0.1000	18.7608	0.5071	0.0126	0.6875
	Median	0.0765	18.8381	0.5306	0.0193	0.7233
	Maximum	1.5920	21.0176	0.9210	0.1421	0.9844
	Minimum	−0.8084	16.2696	0.0189	−0.3061	0.0982
	Std. dev.	0.3185	0.9728	0.2010	0.0746	0.2159
Crisis (2008–2012)	Mean	0.0696	18.9541	0.5453	−0.0105	0.7583
	Median	0.0391	18.8988	0.5835	0.0030	0.8340
	Maximum	4.1277	21.2542	0.9199	0.1231	0.9930
	Minimum	−0.6783	16.6911	0.0080	−0.2593	0.2992
	Std. dev.	0.4749	0.9247	0.2129	0.0684	0.1950
Post-crisis (2013––2018)	Mean	0.1397	19.5024	0.6161	0.0123	0.6465
	Median	0.1441	19.4034	0.6527	0.0119	0.6918
	Maximum	3.9616	22.2951	0.9283	0.3275	0.9990
	Minimum	−0.9415	17.3960	0.0148	−0.1580	0.0629
	Std. dev.	0.3973	0.9301	0.2275	0.0761	0.2108
All periods (2005–2018)	Mean	20.6336	19.1537	0.5235	0.1591	66.4286
	Median	13.5850	18.1467	0.4993	−1.8800	65.3750
	Maximum	299.250	24.4383	0.9777	571.480	99.5400
	Minimum	−83.460	16.8779	0.0392	−119.330	24.8500
	Std. dev.	49.9473	2.1723	0.2574	64.7783	20.4882
Chemicals, petroleum, rubber, and plastic products
Pre-crisis (2005–2007)	Mean	0.0844	19.8024	0.4305	0.0419	0.7243
	Median	0.0834	19.5514	0.3978	0.0564	0.7532
	Maximum	0.6532	22.9275	0.8967	0.2800	0.9628
	Minimum	−0.3499	18.2531	0.0935	−0.2925	0.2284
	Std. dev.	0.1669	1.2083	0.1895	0.0905	0.1800
Crisis (2008–2012)	Mean	0.1461	20.2005	0.4521	0.0477	0.7665
	Median	0.1176	19.9391	0.4128	0.0598	0.7917
	Maximum	1.3129	23.5360	0.9228	0.3732	0.9787
	Minimum	−0.4647	18.2055	0.1147	−0.2295	0.3953
	Std. dev.	0.2392	1.2674	0.2058	0.0822	0.1395
Post-crisis (2013–2018)	Mean	0.1395	20.8499	0.4274	0.0786	0.7142
	Median	0.1243	20.7746	0.3915	0.0793	0.7289
	Maximum	0.9708	24.4180	0.8636	0.3036	0.9852
	Minimum	−0.3134	18.2855	0.1298	−0.1474	0.2593
	Std. dev.	0.1791	1.4123	0.1868	0.0701	0.1764
All periods (2005–2018)	Mean	0.1301	20.3935	0.4369	0.0597	0.7350
	Median	0.1092	20.2545	0.4015	0.0645	0.7580
	Maximum	1.3129	24.4180	0.9228	0.3732	0.9852
	Minimum	−0.4647	18.2055	0.0935	−0.2925	0.2284
	Std. dev.	0.2014	1.3828	0.1943	0.0807	0.1664
Fabricated metal products, machinery, and equipment
Pre-crisis (2005–2007)	Mean	0.1229	19.1426	0.3908	0.0360	0.7440
	Median	0.1038	18.9024	0.3796	0.0515	0.8165
	Maximum	0.8653	23.7131	0.9208	0.3638	1.0000
	Minimum	−0.3365	15.7999	0.0046	−1.2893	0.1006
	Std. dev.	0.2073	2.0108	0.2164	0.1647	0.1988
Crisis (2008–2012)	Mean	0.1486	19.4826	0.4551	0.0364	0.7752
	Median	0.1039	19.3855	0.4584	0.0330	0.7994
	Maximum	1.3142	24.1449	0.9553	0.6383	0.9989
	Minimum	−0.6177	16.6643	0.0055	−1.2225	0.4100
	Std. dev.	0.3216	1.7687	0.2117	0.1518	0.1450
Post-crisis (2013–2018)	Mean	0.1678	20.1468	0.4441	0.0702	0.7045
	Median	0.1527	19.8631	0.4429	0.0498	0.7039
	Maximum	1.8638	24.0714	0.9008	0.6517	0.9873
	Minimum	−0.6074	17.1253	0.0125	−0.3469	0.1579
	Std. dev.	0.2416	1.8103	0.2375	0.1480	0.1761
All periods (2005–2018)	Mean	0.1513	19.6944	0.4366	0.0508	0.7382
	Median	0.1260	19.4182	0.4402	0.0450	0.7543
	Maximum	1.8638	24.1449	0.9553	0.6517	1.0000
	Minimum	−0.6177	15.7999	0.0046	−1.2893	0.1006
	Std. dev.	0.2669	1.8829	0.2250	0.1537	0.1736
Non-metallic mineral products
Pre-crisis (2005–2007)	Mean	0.1866	19.2627	0.2307	0.1481	0.6263
	Median	0.1662	19.2484	0.1730	0.1294	0.6358
	Maximum	1.1573	21.2316	0.6865	0.7199	0.9513
	Minimum	−0.2947	16.3214	0.0170	−0.1039	0.1087
	Std. dev.	0.1925	1.1472	0.1656	0.1363	0.1779
Crisis (2008–2012)	Mean	0.0447	19.4730	0.2589	0.0688	0.6812
	Median	0.0484	19.4374	0.2248	0.0530	0.7030
	Maximum	0.5571	21.6888	0.9026	0.5010	0.9577
	Minimum	−0.4695	16.2952	0.0145	−0.2142	0.2595
	Std. dev.	0.1642	1.2185	0.1961	0.1047	0.1711
Post-crisis (2013–2018)	Mean	0.1532	20.0357	0.3340	0.0855	0.7013
	Median	0.1201	19.9019	0.3289	0.0839	0.7508
	Maximum	1.8643	23.0611	0.8597	0.7195	0.9840
	Minimum	−0.4586	16.7113	0.0344	−0.2137	0.1853
	Std. dev.	0.2306	1.2760	0.2085	0.0936	0.1844
All periods (2005–2018)	Mean	0.1216	19.6691	0.2850	0.0929	0.6780
	Median	0.1053	19.6218	0.2490	0.0792	0.7065
	Maximum	1.8643	23.0611	0.9026	0.7199	0.9840
	Minimum	−0.4695	16.2952	0.0145	−0.2142	0.1087
	Std. dev.	0.2090	1.2699	0.2001	0.1118	0.1804
Technology
Pre-crisis (2005–2007)	Mean	0.0688	18.4635	0.4091	0.0404	0.8355
	Median	0.1042	18.7998	0.5259	0.0559	0.8962
	Maximum	1.4215	21.0593	0.7191	0.2762	0.9972
	Minimum	−0.5770	15.7859	0.0334	−0.2267	0.3951
	Std. dev.	0.3325	1.4543	0.2442	0.0879	0.1873
Crisis (2008–2012)	Mean	0.6002	18.6789	0.3973	0.0419	0.7825
	Median	0.1295	18.9252	0.4168	0.0337	0.8692
	Maximum	32.7236	21.9259	0.8483	0.7244	0.9986
	Minimum	−0.6565	15.6319	0.0204	−0.1246	0.2116
	Std. dev.	3.5939	1.6291	0.2683	0.1234	0.2242
Post-crisis (2013–2018)	Mean	0.2146	19.5313	0.3630	0.0711	0.8225
	Median	0.1886	19.6789	0.3086	0.0546	0.9143
	Maximum	1.5902	23.6921	0.8112	0.2877	0.9953
	Minimum	−0.9957	16.2457	0.0213	−0.1237	0.3908
	Std. dev.	0.3664	1.7697	0.2644	0.0751	0.1933
All periods (2005–2018)	Mean	0.3183	18.9655	0.3735	0.0518	0.8095
	Median	0.1554	19.1083	0.3491	0.0467	0.9073
	Maximum	32.726	23.6921	0.8483	0.7244	0.9986
	Minimum	−0.9957	15.6319	0.0107	−0.2267	0.1912
	Std. dev.	2.1689	1.7250	0.2632	0.0972	0.2060

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Korkmaz, T., Erkol, A.Y. (2021). Capital Structure Adjustment Speed: Evidence from Borsa Istanbul Sub-Sectors. In: Adıgüzel Mercangöz, B. (eds) Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics. Springer, Cham. https://doi.org/10.1007/978-3-030-54108-8_18

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DOI: https://doi.org/10.1007/978-3-030-54108-8_18
Published: 18 February 2021
Publisher Name: Springer, Cham
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Online ISBN: 978-3-030-54108-8
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Capital Structure Adjustment Speed: Evidence from Borsa Istanbul Sub-Sectors

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