Balazs Vedres: The Dissolution of Ownership Networks

Balázs Vedres:
The Dissolution of Ownership Networks and the Formation of a Strict Corporate Governance System

Preliminary summary with figures

The research project covered the mapping of the ownership structures and networks of the top 500 Hungarian firms (according to 97 revenue) in spring/summer of 1999. These figures are from the paper accepted for publication in the Hungarian Review of Economics. The complete translation is to be finished in a month.

Hypotheses of a post socialist property system:

1. State property is still dominant
2. The property structure is fragmented
3. Besides state property the second most important is the cross ownership between domestic firms
4. Cross ownership is organized in dense knit networks
5. Cross ownership represents indirect state ownership
6. Belonging to the cross ownership network increases efficiency and growth
7. Most companies have diversified portfolios (more types of owners)
8. Having more types of owners increases efficiency and growth

Figure 1: The distribution of ownership shares in the Hungarian top 500, 1999.

Figure 2: Concentration of ownership

	Population	Average of the largest share	Median of the largest share
Austria	50 firms on stock exchange	54,1	52,0
Belgium	150 firms on stock exchange	55,8	55,5
France	40 firms on stock exchange	29,4	20,0
Germany	347 firms on stock exchange	n.a.	52,1
Italy	216 firms on stock exchange	51,9	54,5
Holland	137 firms on stock exchange	42,8	43,5
Spain	193 firms on stock exchange	40,1	34,2
UK	250 firms on stock exchange	15,2	10,9
USA	1309 firms (NYSE)	< 5	< 5
Czech Republic	706 privatized firms	68,4*	67,2*
Hungary	411 firms (top 500)	74,2	85,0
Hungary	27 firms on stock exchange	53,4	50,9

* The sum of the five largest owners

The source of western data: Crama, Y. – Leruth, L. – Renneboog, L. – Urbain, J. P. (2000): Corporate Governance Structures, Control and Performance in European Markets: A Tale of Two Systems. Manuscript

The source of Czech data: Claessens, Stijn – Djankov, Simeon (1999): Ownership concentration and Corporate Performance in the Czech Republic. Journal of comparative Economics, 1999/27.

Figure 3: Concentration in international comparison

	Number of appearance	Capital in hand (M Ft.) (%)	Revenues in hand (M Ft) (%)	Average share (standard dev)	Number of majority positions (%)
Local Government	318	288 939 (20,28)	283 788 (4,88)	3,93 (14,28)	9 (2% of 318)
State	74	134 200 (9,42)	780 788 (13,41)	45,71 (41,37)	34 (46% of 74)
Hungarian nonfinancial firm	578	372 627 (26,15)	1 088 673 (18,70)	18,53 (29,90)	73 (13% of 578)
Hungarian financial	120	29 207 (2,05)	139 501 (2,40)	11,35 (21,38)	6 (5% of 120)
Hungarian private person	971	30 648 (2,15)	295 242 (5,07)	5,46 (13,41)	22 (2% of 971)
Foreign nonfinancial firm	260	495 467 (34,77)	2 775 520 (47,68)	59,94 (39,24)	147 (57% of 260)
Foreign financial	90	71 841 (5,04)	440 846 (7,57)	14,09 (23,56)	6 (7% of 90)
Foreign private person	27	2 067 (0,14)	16 778 (0,29)	8,35 (14,45)	0 (0% of 27)
sum	2438	1 424 993 (=100%)	5 821 137 (=100%)	16,13 (29,56)	297 (12% of 2438)

	Number of 90%+ positions (%)	Number of 100% positions (%)	Average number of appearances at the same firm, if any	Number of firms with at least one such owner	Number of firms with such owner(s) in majority position
Local Government	4 (1%)	4 (1%)	4,18 (4,82)	70 (17%)	14 (3%)
State	19 (26%)	12 (16%)	1,17 (0,64)	61 (15%)	34 (8%)
Hungarian nonfinancial firm	45 (8%)	25 (4%)	2,98 (4,47)	185 (45%)	98 (24%)
Hungarian financial	4 (3%)	3 (2%)	2,20 (3,62)	51 (12%)	10 (2%)
Hungarian private person	5 (0,5%)	3 (0,3%)	5,77 (6,96)	158 (38%)	49 (12%)
Foreign nonfinancial firm	103 (40%)	78 (30%)	1,33 (0,78)	196 (48%)	156 (38%)
Foreign financial	3 (3%)	2 (2%)	1,98 (2,06)	44 (11%)	9 (2%)
Foreign private person	0 (0%)	0 (0%)	1,60 (0,58)	19 (5%)	1 (0,2%)
sum	183 (8%, 2438=100%)	127 (5%, 2438=100%)	5,92 (6,98)	411 (100%)	371 (90%, 411=100%)

Figure 4: The features of the ownership position of major types of owners

	Local Government	State	Hungarian nonfinancial firm	Hungarian financial	Hungarian private person	Foreign nonfinancial firm	Foreign financial	Foreign private person
Local Government	1,000	-,033	-,051	-,031	-,086	-,145**	-,028	-,025
State	-,033	1,000	-,182**	-,033	-,102*	-,263**	-,052	-,040
Hungarian nonfinancial firm	-,051	-,182**	1,000	-,080	-,195**	-,461**	-,084	,022
Hungarian financial	-,031	-,033	-,080	1,000	-,048	-,172**	,050	-,028
Hungarian private person	-,086	-,102*	-,195**	-,048	1,000	-,317**	-,076	,008
Foreign nonfinancial firm	-,145**	-,263**	-,461**	-,172**	-,317**	1,000	-,152**	-,065
Foreign financial	-,028	-,052	-,084	,050	-,076	-,152**	1,000	-,015
Foreign private person	-,025	-,040	,022	-,028	,008	-,065	-,015	1,000

** p< 0.01

* p< 0.05

Figure 5: Correlation between the ownership positions of the major types of owners at the same firm

	Cluster 1: Foreign dominance	Cluster 2: Domestic dominance	Cluster 3: Domestic private persons	Cluster 4: State and financials	Cluster 6:Local gov. and foreign financials
Local Government	0,22	0,53	0,38	1,59	43,64
State	0,47	1,72	0,72	66,59	1,26
Hungarian nonfinancial firm	7,05	87,42	8,13	1,90	12,34
Hungarian financial	0,53	2,35	1,26	20,76	0,42
Hungarian private person	0,65	2,29	78,78	2,90	1,17
Foreign nonfinancial firm	88,21	0,36	5,12	0,00	5,74
Foreign financial	0,57	1,59	0,00	2,83	30,38
Number of firms (%)	168 (44%)	90 (23%)	57 (15%)	45 (12%)	24 (6%)

Figure 6: Clusters of ownership structures according to type of owner

Group	Number of firms	%
No network connection	278	67,6
1. Bábolna-groupt	9	2,2
2. Financial group	19	4,6
3. Dunaferr-group	8	1,9
4. MOL-group	9	2,2
5. MFB-group	5	1,2
6. Wheat group	13	3,2
Groups total	63	15,3
In dyads or triads	70	17,0
Total	411	100,0

Figure 7: The importance of ownership networks: firms according to ownership network connections (owning or beeing owned by another top 500 firm)

	Only owner 68 cég	Both 10 cég	Only owned 74 cég
Only owner 68 cég	-	11 (14,6%)	108 (29,7%)
Both 10 cég	-	5 (33,4%)	14 (25,3%)
Only owned 74 cég	-	-	-

Figure 8: The network roles: the roles in the network are clear: a firm is eighter an owner or an affiliate, an owned unit. The level of ambiguity is low.


1. Bábolna-group of agrarian firms	2. Financial group of banks with joint projects as firms	3. Metal-group (the Heavy Metal group in Stark's recombinant property paper)

4. MOL-group around the giant oil company	5. MFB-group around the state development bank	6. Wheat group with mills and wheat trading houses

Figure 9: Groups beyond the triad in the ownership network: mostly out of the recombinet shape.

	Models of efficiency (revenue/employee)
model	1	2	3	4	5	6	7
R square	,120**	,146**	,149**	,169**	,316**	,372**	,383**
R square change		,026**	,003	,020**	,146**	,056**	,011**
Constant	2,233**	2,389**	2,312**	,781	,224	,633	1,128*
Cluster of foreign firm owner dominance	,853**	,816**	,803**	,777**	,830**	,775**	,719**
Cluster of domestic firm owner dominance	,286*	,294*	,292*	,313*	,337**	,289*	,257*
Cluster of domestic private person owner dom.	,721**	,715**	,723**	,815**	,724**	,643**	,566**
Member of a network group beyond triad		,196	,225	,193	,204	,258*	,212
Diversified owner portfolio (more than one type)		-,328**	-,326**	-,372**	-,293**	-,327**	-,275**
Few owners, quite equal shares			,159	,198	,211	,215*	,170
Few owners, concentrated			,079	,104	,014	-,079	-,126
Revenue+				,171**	,197**	,144**	,143**
Agrarian, food industry					,154	,217	,219
Wood, textile, light industry					-,069	-,167	-,158
Retail, wholesale trade					1,021**	,858**	,843**
Service, transport, telecom, finance (not bank)					,428**	,131	,068
Budapest (registered in)						,554**	,581**
1997 number of employees per 1994 number							-,442**

N=297
†Dependent: the natural logarithm of the 1997 net revenues per number of employees.
+Natural log.
*: p less than 0,10
**: p less than 0,05

Figure 10: Linear regression models of efficiency.

	Models of growth†
model	1	2	3	4	5	6	7
R square	,067**	,089**	,094**	,107**	,178**	,182**	,263**
R square change		,022*	,004	,013*	,072**	,004	,081**
Constant	1,036**	1,094**	1,096**	,633**	,818**	,767**	,681**
Cluster of foreign firm owner dominance	,148**	,135**	,129**	,122*	,166**	,176**	,069
Cluster of domestic firm owner dominance	-,067	-,060	-,064	-,060	,009	,015	-,012
Cluster of domestic private person owner dom.	,184**	,182**	,174**	,202**	,264**	,274**	,192**
Member of a network group beyond triad		,069	,070	,056	,070	,067	,054
Diversified owner portfolio (more than one type)		-,118**	-,137**	-,144**	-,165**	-,163**	-,122**
Few owners, quite equal shares			,059	,066	,032	,034	-,003
Few owners, concentrated			-,006	-,003	-,009	,000	,025
Revenue+				,051*	,035	,041	,018
Agrarian, food industry					-,064	-,070	-,108*
Wood, textile, light industry					-,124	-,114	-,094
Retail, wholesale trade					-,284**	-,261**	-,383**
Service, transport, telecom, finance (not bank)					,058	,089	,095
Budapest (registered in)						-,058	-,130**
Efficiency (revenue/employee)++							,144**

N=242
† Dependent: the 1997 net revenues per 1994 net revenues (both in 1990 prices): real growth.
+ Natural log.
++ The natural logarithm of the 1997 net revenues per number of employees.
*: p less than 0,10
**: p less than 0,05

Figure 11: Linear regression