Mandatory dividend and corporate investment: a multi-country analysis

Vancin, Daniel; Kirch, Guilherme

doi:10.1108/RAUSP-05-2019-0113

Daniel Vancin ^**Corresponding author Daniel Vancin can be contacted at: daniel_vancin@hotmail.com

PPG Ciências Contábeis, Unisinos – Campus de Porto Alegre, Porto Alegre, Brazil

https://orcid.org/0000-0001-6303-0555

Guilherme Kirch

UFRGS, Porto Alegre, Brazil

*Corresponding author Daniel Vancin can be contacted at: daniel_vancin@hotmail.com

Associate Editor: Wilson Toshiro Nakamura

The authors contributed to the paper in the following ways: Vancin, Daniel, Corresponding Author, Conceptualization (Equal), Data curation (Equal), Formal analysis (Equal), Funding acquisition (Equal), Investigation (Equal), Methodology (Equal), Project administration (Equal), Resources (Equal), Software (Equal), Validation (Equal), Visualization (Equal), Writing-original, draft (Equal), Writing-review and editing (Equal), Kirch, Guilherme.

Variables	Whole sample				Countries with mandatory dividend				Countries without mandatory dividend
Variables	n	Mean	Median	SD	n	Mean	Median	SD	n	Mean	Median	SD
I_i,t	212,595	0.051	0.015	0.185	7,690	0.03	0.011	0.164	204,905	0.047	0.015	0.185
CF_i,t	212,595	0.078	0.086	0.195	7,690	0.093	0.09	0.133	204,905	0.067	0.086	0.196
Q_i,t−1	212,595	2.516	1.094	4.881	7,690	4.833	1.204	8.985	204,905	2.427	1.094	4.629
P_c	212,595	10.785	11.1	2.319	7,690	9.45	9.366	1.557	204,905	10.836	11.1	2.328
GDP_c	212,595	4.263	4.531	0.535	7,690	4.064	4.086	0.279	204,905	4.271	4.531	0.542

Variables	(1)	(2)	(3)
Variables	I_i,t	I_i,t	I_i,t
CF _i,t	0.16^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (10.52)	1.50^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (7.46)	1.18^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (4.97)
q_i,t−1	0.006^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (10.37)	0.00^ Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (2.58)	0.00(0.11)
CF_i,t × DivM_c		0.23^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; p < 0.05; * p < 0.1 (10.75)	0.17^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; p < 0.05; * p < 0.1 (1.83)
q_i,t−1 × DivM_c		−0.00^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (−2.84)	−0.00(−0.07)
CF_i,t × P_c		−0.06^ Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (−2.37)	−0.06^ Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (−2.49)
q_i,t−1 × P_c		0.00^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (2.79)	0.00(0.02)
CF_i,t × GDP_c,t		−0.15^ Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (−2.13)	−0.05(−0.61)
q_i,t−1 × GDP_c,t		−0.00^ Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (−2.65)	−0.00(−0.07)
σ CF_i,t			0.31^* Notes: The “variables” column shows all variables included in the model. The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The acronym EF stands for fixed effect. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (12.2)
Constant	−0.04(−0.00)	−0.10(0.00)	−0.06(−0.01)
Observations	212,595	212,595	123,695
R ²	0.07	0.09	0.08
Firms FE	Yes	Yes	Yes
Year FE	Yes	Yes	Yes
Industry-year FE	Yes	Yes	Yes
County-year FE	Yes	Yes	Yes
Period	2000-2016	2000-2016	2000-2016

Treatment variable:	DivM_c
Dependent variable:	I_i,t
ATE	−0.013^* Notes: The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The treatment variable was the mandatory dividend (DivMc), a dummy that assumes a value of 1 if the country adopts this legal mechanism and 0 otherwise. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01; ** p < 0.05; * p < 0.1 (0.003)
Observations	15,380

Treatment variable:	DivM_c
Dependent variable:	I_i,t
ATE	−0.02^* Notes: The regression had the dependent variable Ii,t, that is, investment variable of the company i in period t – this measure consists of the combination of the annual growth in properties, plants and equipment, added to the growth in the inventory, plus expenses with research and development. The treatment variable was the mandatory dividend (DivMc), a dummy that assumes a value of 1 if the country adopts this legal mechanism and 0 otherwise. The data are for the period 2000-2016. We extracted these multi-country data from Compustat Global®. The t-statistic is in parentheses, in which * p < 0.01, p < 0.05, * p < 0.1 (0.064)
Observations	6,740
Source: Elaborated by authors.

I_{i, t} = α_{i} + α_{t} + α_{c, t} + α_{I, t} + β_{1} {C F}_{i, t} + β_{2} q_{i, t - 1} + β_{3} ({C F}_{i, t} X {D i v M}_{c}) + β_{4} (q_{i, t - 1} X {D i v M}_{c}) + β_{5} ({C F}_{i, t} X P_{c}) + β_{6} (q_{i, t - 1} X P_{c}) + β_{7} ({C F}_{i, t} X {G D P}_{c, t}) + β_{8} (q_{i, t - 1} X {G D P}_{c, t}) + ε_{i, t}

[1] *Corresponding author Daniel Vancin can be contacted at: daniel_vancin@hotmail.com

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Mandatory dividend and corporate investment: a multi-country analysis

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