Multinationals, research and development, and carbon emissions: international evidence

Figures & data

Table 1. Definitions of variables.

Variable name	Variable definition	Variable measurement
Dependent variables
Emissions Intensity	Carbon dioxide and its equivalents, such as methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCS), perfluorinated compound (PFCs), sulfur hexafluoride (SF6), and nitrogen trifluoride (NF3) emissions scaled by sales, following Alam et al. (2019).	Carbon emissions (Tons)/Sales
Independent and control variables
R&D Intensity	Research and development expenditures (R&D) scaled by sales.	R&D/Sales
Size	Size of the firm	Ln (total assets in USD)
MNC_Dummy	Whether a firm is a multinational (MNC) or domestic company, based on a 25% cut-off in the foreign sales ratio	1 if a firm is an MNC; otherwise, 0
FxSalRatio	Foreign sales ratio, the level of internationalization	International sales/total sales
Leverage	Firm leverage	Total debt/total assets
CapInt	Capital Intensity: The volume of investment required for the production process	Total assets/total sales
Tobin's Q	Firm market performance	(Asset – book value of equity + market value of equity)/total assets
ROA	Return on assets, firm accounting performance	Net income/total assets
DPS	Dividend per share, dividend payout	1 if dividends are paid; 0 otherwise
CapEx	Capital expenditures	Capital expenditures/total assets
GovOwn	Percentage of shares owned by the state	Government ownership
GDP	Gross domestic product	Ln GDP (current USD)
RegQual	Regulatory quality based on Worldwide Governance Indicators measured by the World Bank: the ability of the state to develop and introduce high-quality policies and regulations that facilitate private sector expansion	Average of following six components: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption
FDI	Foreign direct investment, inflows of investment to an economy from the rest of the world	FDI inflows/GDP

Notes: This table provides definitions of firm- and country-level variables. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019.

Table 2. Descriptive statistics.

Variable	N	Mean	Median	Min.	Max.	St.Dev.
Emissions Intensity	19929	0.184	0.025	0.000	3.181	0.468
R&D Intensity	19929	0.026	0.002	0.000	3.944	0.088
MNC_Dummy	19929	0.656	1.000	0.000	1.000	0.475
FxSalRatio	19929	0.451	0.459	0.000	1.000	0.338
Size	19929	15.696	15.676	10.099	18.332	1.360
Leverage	19929	0.249	0.239	0.000	0.938	0.162
CapInt	19929	1.893	1.242	0.279	94.865	4.048
Tobin's Q	19929	1.757	1.406	0.582	10.606	1.169
ROA	19929	0.051	0.049	−1.080	0.327	0.082
DPS	19929	0.854	1.000	0.000	1.000	0.353
CapEx	19929	0.053	0.041	0.000	0.348	0.045
GovOwn	19929	0.023	0.000	0.000	0.500	0.088
GDP	19929	7.806	7.903	4.800	9.973	1.316
RegQual	19929	1.332	1.461	−0.513	2.058	0.551
FDI	19929	0.354	0.176	−0.342	3.684	0.672

Notes: This table presents the summary statistics for the variables. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. All variables are defined in Table 1.

Figure 1. Time trend in carbon emissions and R&D expenditures a. The relationship between emissions intensity and R&D intensity in the full sample b. Comparison of the relationships between emissions intensity and R&D intensity for MNCs and domestic companies

Table 3. Sample countries and mean values of selected variables.

Country Name	N	Emissions Intensity	R&D Intensity	GDP	RegQual	FDI
Argentina	15	0.155	0.000	6.369	−0.380	0.191
Australia	883	0.394	0.013	7.120	1.809	0.356
Austria	75	0.207	0.008	6.020	1.488	0.052
Belgium	172	0.386	0.036	6.195	1.285	0.709
Brazil	254	0.146	0.002	7.627	−0.020	0.360
Canada	940	0.444	0.005	7.361	1.716	0.291
Chile	50	0.001	0.000	5.574	1.383	0.479
China	213	0.084	0.024	9.407	−0.209	0.152
Colombia	56	0.281	0.002	5.746	0.374	0.413
Denmark	218	0.030	0.056	5.777	1.764	0.037
Finland	274	0.220	0.023	5.521	1.794	0.242
France	900	0.198	0.027	7.866	1.174	0.169
Germany	698	0.237	0.032	8.156	1.642	0.218
Greece	67	0.867	0.000	5.503	0.517	0.119
Hong Kong	602	0.112	0.013	5.736	2.020	2.892
Hungary	23	0.001	0.000	4.926	0.884	0.717
India	315	0.025	0.009	7.622	−0.352	0.176
Indonesia	74	0.001	0.004	6.801	−0.206	0.202
Ireland	53	0.336	0.003	5.637	1.685	2.212
Israel	39	0.039	0.102	5.637	1.231	0.380
Italy	245	0.340	0.016	7.608	0.782	0.124
Japan	3075	0.002	0.036	8.532	1.190	0.032
Korea, Rep.	510	0.000	0.018	7.176	0.994	0.078
Luxembourg	32	0.490	0.004	4.800	1.723	3.307
Malaysia	155	0.240	0.001	5.721	0.673	0.327
Mexico	151	0.043	0.000	7.049	0.324	0.279
Netherlands	325	0.341	0.023	6.719	1.829	2.164
New Zealand	98	0.292	0.005	5.177	1.934	0.115
Norway	233	0.078	0.009	5.997	1.616	0.159
Peru	13	0.274	0.008	5.305	0.471	0.309
Philippines	56	0.006	0.000	5.668	−0.064	0.201
Poland	60	0.076	0.001	6.236	0.958	0.273
Portugal	72	0.305	0.000	5.412	0.925	0.408
Russian Federation	101	0.012	0.000	7.412	−0.418	0.174
Saudi Arabia	18	0.264	0.005	6.513	0.033	0.111
Singapore	139	0.187	0.029	5.711	1.982	2.328
South Africa	641	0.067	0.001	5.861	0.312	0.124
Spain	303	0.218	0.011	7.193	1.033	0.253
Sweden	507	0.017	0.020	6.235	1.766	0.252
Switzerland	440	0.176	0.053	6.391	1.704	0.551
Thailand	163	0.018	0.001	6.017	0.204	0.205
Turkey	105	0.125	0.008	6.746	0.243	0.157
United Kingdom	2669	0.280	0.023	7.914	1.748	0.381
United States	3897	0.221	0.044	9.707	1.447	0.182
Total/Mean	19929	0.184	0.026	7.806	1.332	0.354

Notes: The table presents the mean values of some variables by country. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. The variables are defined in Table 1.

Table 4. Pairwise correlations.

Variables		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)
(1)	Emissions Intensity	1
(2)	R&D Intensity	−0.082	1
(3)	MNC	0.044	−0.071	1
(4)	Size	0.030	−0.229	0.271	1
(5)	Leverage	0.054	−0.089	0.002	0.255	1
(6)	CapInt	0.141	0.429	−0.117	−0.205	−0.074	1
(7)	Tobin's Q	−0.079	0.212	−0.075	−0.341	−0.174	0.088	1
(8)	ROA	−0.081	−0.477	0.106	0.325	−0.095	−0.302	−0.082	1
(9)	DPS	−0.066	−0.191	−0.016	0.338	−0.003	−0.190	−0.115	0.308	1
(10)	CapEx	0.191	−0.093	−0.095	−0.061	0.051	0.068	0.023	0.018	−0.049	1
(11)	GovOwn	−0.021	−0.027	0.004	0.127	0.023	−0.014	−0.044	0.034	0.062	0.037	1
(12)	GDP	−0.003	0.128	−0.061	0.016	0.011	−0.038	0.095	−0.130	−0.182	−0.093	−0.192	1
(13)	RegQual	0.122	0.073	0.148	−0.069	−0.031	0.075	−0.006	−0.122	−0.105	−0.048	−0.111	0.093	1
(14)	FDI	0.031	−0.036	0.050	0.050	−0.001	0.025	−0.019	0.047	0.061	−0.004	0.054	−0.387	0.197	1

Notes: This table presents the pairwise correlations. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. The variables are defined in Table 1.

Table 5. The effect of R&D Intensity on Emissions Intensity.

	Model 1	Model 2	Model 3	Model 4	Model 5
R&D Intensity	−0.301***	−0.103***	−0.279***	−0.279***	−0.278***
	(0.089)	(0.039)	(0.087)	(0.087)	(0.087)
MNC_Dummy		0.030*	0.028*	0.028	0.026
		(0.017)	(0.017)	(0.017)	(0.017)
R&DxMNC_Dummy		−0.537***	−0.409**	−0.410**	−0.409**
		(0.205)	(0.195)	(0.195)	(0.194)
Size			0.013*	0.013*	0.014*
			(0.008)	(0.008)	(0.008)
Leverage			−0.01	−0.009	−0.006
			(0.047)	(0.047)	(0.047)
CapInt			0.012***	0.012***	0.012***
			(0.003)	(0.003)	(0.003)
Tobin's Q			−0.005	−0.005	−0.004
			(0.008)	(0.008)	(0.008)
ROA			−0.191**	−0.194***	−0.201***
			(0.075)	(0.075)	(0.074)
DPS			−0.009	−0.009	−0.007
			(0.018)	(0.018)	(0.018)
CapEx			0.931***	0.931***	0.947***
			(0.202)	(0.202)	(0.198)
GovOwn			−0.202**	−0.202**	−0.199**
			(0.079)	(0.079)	(0.079)
GDP				−0.041	−0.109***
				(0.040)	(0.032)
RegQual				0.009	0.017
				(0.031)	(0.028)
Constant	−0.025	−0.023	−0.226	0.018	0.377
	(0.115)	(0.114)	(0.147)	(0.276)	(0.237)
Adj. R-sq	0.28	0.283	0.3	0.3	0.3
N	19929	19929	19929	19929	19929
Country FE	Yes	Yes	Yes	Yes	Yes
Industry FE	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	No

Notes: This table reports the results from multivariate OLS linear regressions for the effect of R&D intensity on carbon emissions intensity based on Equation 1(1) $\mathrm{E}\mathrm{m}\mathrm{i}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{I}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{s}\mathrm{i}\mathrm{t}{\mathrm{y}}_{\mathrm{i},\mathrm{t}}={\alpha }_{\mathrm{i}}+\text{β}1\mathrm{R}\mathrm{\&}{\mathrm{D}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}2\mathrm{M}\mathrm{N}\mathrm{C}\mathrm{\_}\mathrm{D}\mathrm{u}\mathrm{m}\mathrm{m}{\mathrm{y}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}3(\mathrm{R}\mathrm{\&}\mathrm{D}\mathrm{x}\mathrm{M}\mathrm{N}\mathrm{C}\mathrm{\_}\mathrm{D}\mathrm{u}\mathrm{m}\mathrm{m}\mathrm{y}{)}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}4\mathrm{S}\mathrm{i}\mathrm{z}{\mathrm{e}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}5\mathrm{L}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}{\mathrm{e}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}6\mathrm{C}\mathrm{a}\mathrm{p}\mathrm{I}\mathrm{n}{\mathrm{t}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}7\mathrm{T}\mathrm{o}\mathrm{b}\mathrm{i}{\mathrm{n}}^{\mathrm{\prime }}\mathrm{s}{\mathrm{Q}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}8\mathrm{R}\mathrm{O}{\mathrm{A}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}9\mathrm{D}\mathrm{P}{\mathrm{S}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}10\mathrm{C}\mathrm{a}\mathrm{p}\mathrm{E}{\mathrm{x}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}11\mathrm{G}\mathrm{o}\mathrm{v}\mathrm{O}\mathrm{w}{\mathrm{n}}_{\mathrm{i},\mathrm{t}\text{-}1}+\text{β}12\mathrm{G}\mathrm{D}{\mathrm{P}}_{\mathrm{c},\mathrm{t}\text{-}1}+\text{β}13\mathrm{R}\mathrm{e}\mathrm{g}\mathrm{Q}\mathrm{u}\mathrm{a}{\mathrm{l}}_{\mathrm{c},\mathrm{t}\text{-}1}+\mathrm{C}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{y}\mathrm{F}\mathrm{E}+\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}\mathrm{F}\mathrm{E}+\mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}\mathrm{F}\mathrm{E}+{ϵ}_{\mathrm{i},\mathrm{t}}$(1) . The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. The variables are defined in Table 1. Financial and utility firms are excluded. Explanatory variables are lagged by one period to minimize the possibility of reverse causality. Robust standard errors in parentheses are clustered at the firm level. ***, **, and * significant at the 1%, 5%, and 10% levels, respectively.

Table 6. The role of FDI in explaining the effect of R&D Intensity on Emissions Intensity.

	Full Sample		Developed Countries		Developing Countries
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
R&D Intensity	−0.296***	−0.238***	−0.282***	−0.193***	−0.174	−0.315
	(0.099)	(0.071)	(0.105)	(0.054)	(0.214)	(0.207)
MNC_Dummy	0.027	0.025	0.027	0.02	0.021	0.016
	(0.017)	(0.018)	(0.021)	(0.022)	(0.022)	(0.019)
R&DxMNC_Dummy	−0.438***	−0.598***	−0.375**	−0.547***	−0.149	0.111
	(0.159)	(0.146)	(0.159)	(0.147)	(0.276)	(0.256)
FDI	−0.015	−0.024*	−0.017	−0.052**	0.01	0.007
	(0.013)	(0.014)	(0.015)	(0.025)	(0.023)	(0.020)
R&DxFDI	0.087	−0.218*	0.075	−0.511***	−0.239*	−0.141
	(0.165)	(0.128)	(0.212)	(0.103)	(0.129)	(0.107)
FDIxMNC_Dummy		0.007		0.039		0.006
		(0.016)		(0.033)		(0.018)
R&DxFDIxMNC_Dummy		0.482**		0.730***		−0.23
		(0.232)		(0.230)		(0.241)
Size	0.014*	0.015*	0.018**	0.018**	0.006	0.006
	(0.008)	(0.008)	(0.009)	(0.009)	(0.012)	(0.012)
Leverage	−0.007	−0.008	0.05	0.049	−0.121*	−0.119*
	(0.047)	(0.046)	(0.056)	(0.056)	(0.068)	(0.067)
CapInt	0.012***	0.012***	0.012***	0.013***	0.012*	0.012*
	(0.003)	(0.003)	(0.003)	(0.003)	(0.007)	(0.007)
Tobin's Q	−0.004	−0.004	−0.016***	−0.015**	0.019	0.019
	(0.008)	(0.008)	(0.006)	(0.006)	(0.026)	(0.026)
ROA	−0.201***	−0.201***	−0.163**	−0.161**	−0.084	−0.085
	(0.074)	(0.074)	(0.078)	(0.078)	(0.170)	(0.172)
DPS	−0.008	−0.008	0.002	0.001	−0.063**	−0.064**
	(0.018)	(0.018)	(0.020)	(0.020)	(0.031)	(0.031)
CapEx	0.946***	0.942***	1.072***	1.073***	0.172	0.175
	(0.198)	(0.197)	(0.259)	(0.258)	(0.167)	(0.167)
GovOwn	−0.198**	−0.202**	−0.235*	−0.233*	−0.144*	−0.143*
	(0.080)	(0.079)	(0.130)	(0.130)	(0.076)	(0.077)
GDP	−0.111***	−0.111***	−0.158***	−0.158***	−0.058*	−0.057*
	(0.032)	(0.032)	(0.039)	(0.039)	(0.033)	(0.033)
RegQual	0.017	0.017	0.017	0.019	0.024	0.023
	(0.028)	(0.028)	(0.031)	(0.031)	(0.054)	(0.054)
Constant	0.390*	0.392*	0.914***	0.919***	0.254	0.252
	(0.236)	(0.237)	(0.310)	(0.310)	(0.266)	(0.265)
Adj. R-sq	0.3	0.3	0.326	0.327	0.216	0.216
N	19929	19929	16259	16259	3670	3670
Country FE	Yes	Yes	Yes	Yes	Yes	Yes
Industry FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	No	No	No	No	No	No

Notes: This table reports the results from multivariate OLS linear regressions for the role of FDI in changing the effect of R&D intensity on carbon emissions intensity. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. The variables are defined in Table 1. Financial and utility firms are excluded. Explanatory variables are lagged by one period to minimize the possibility of reverse causality. Robust standard errors in parentheses are clustered at the firm level. ***, **, and * significant at the 1%, 5%, and 10% levels, respectively.

Table 7. Subperiod analysis for the role of FDI in explaining the effect of R&D Intensity on Emissions Intensity.

	2002–2014		2015–2019
	Model 1	Model 2	Model 3	Model 4
R&D Intensity	−0.629***	−0.698***	−0.244***	−0.201***
	(0.193)	(0.244)	(0.080)	(0.061)
MNC_Dummy	0.042*	0.03	0.008	0.009
	(0.022)	(0.024)	(0.019)	(0.021)
R&DxMNC_Dummy	−0.558***	−0.424*	−0.25	−0.473***
	(0.211)	(0.247)	(0.162)	(0.136)
FDI		−0.028		−0.008
		(0.022)		(0.013)
R&DxFDI		0.138		−0.243**
		(0.185)		(0.106)
FDIxMNC_Dummy		0.04		0.003
		(0.029)		(0.016)
R&DxFDIxMNC_Dummy		−0.371		0.501***
		(0.281)		(0.176)
Size	0.021**	0.021**	0.006	0.007
	(0.009)	(0.009)	(0.008)	(0.008)
Leverage	−0.051	−0.052	0.016	0.014
	(0.054)	(0.054)	(0.062)	(0.062)
CapInt	0.014***	0.014***	0.010***	0.010***
	(0.004)	(0.004)	(0.003)	(0.003)
Tobin's Q	−0.014	−0.013	−0.003	−0.002
	(0.009)	(0.009)	(0.010)	(0.010)
ROA	−0.068	−0.066	−0.289***	−0.293***
	(0.101)	(0.101)	(0.091)	(0.091)
DPS	0.006	0.005	−0.025	−0.027
	(0.021)	(0.021)	(0.024)	(0.024)
CapEx	0.842***	0.848***	1.048***	1.035***
	(0.245)	(0.245)	(0.246)	(0.246)
GovOwn	−0.186*	−0.182*	−0.229***	−0.234***
	(0.109)	(0.109)	(0.079)	(0.079)
GDP	−0.190***	−0.189***	0.01	0.005
	(0.040)	(0.040)	(0.036)	(0.036)
RegQual	−0.018	−0.016	0.002	0.005
	(0.040)	(0.041)	(0.032)	(0.032)
Constant	1.201***	1.201***	−0.291	−0.259
	(0.339)	(0.340)	(0.253)	(0.255)
Adj. R-sq	0.339	0.339	0.27	0.271
N	10757	10757	9172	9172
Country FE	Yes	Yes	Yes	Yes
Industry FE	Yes	Yes	Yes	Yes
Year FE	No	No	No	No

Notes: This table reports the results from multivariate OLS linear regressions for the role of FDI in changing the effect of R&D intensity on carbon emissions intensity in two subsample periods. The data for firm-level variables are collected from Thomson Reuters ESG/Eikon/DataStream databases, whereas the country-level data are from the World Bank and OECD databases for the period 2003-2019. The variables are defined in Table 1. Explanatory variables are lagged by one period to minimize the possibility of reverse causality. Robust standard errors in parentheses are clustered at the firm level. ***, **, and * significant at the 1%, 5%, and 10% levels, respectively.

Alam, M., Atif, M., Chu, C. C., & Soytas, U. (2019). Does corporate R&D investment affect firm environmental performance? Evidence from G-6 countries. Energy Economics, 78, 401–411. https://doi.org/10.1016/j.eneco.2018.11.031

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