What role economic growth and sustainability-oriented innovation play on the level of carbon emission: case of China

Figures & data

Figure 1. CO2 Emission in China (world development indictor).

Source: WDI.

Table 1. Variables with measurements.

S#	Variables	Measurement	Sources
01	Carbon Emission	Carbon dioxide damages (% of GNI)	(McGrath et al., 2022)
02	Gross Domestic Product	GDP growth (annual percentage)	(Ramzan et al., 2019)
03	National Income	Net national income (annual % growth)	(Pei et al., 2020)
04	Human Capital Index	Human capital index (HCI) (scale 0-1)	(Collin & Weil, 2020)
05	Employment Ratio	Employment to population ratio, 15+, total (%)	(Abraham & Kearney, 2020)
06	Inflation	Inflation, consumer price (% annual)	(Usman & Musa, 2018)
07	Exports	Exports of goods and services (% of GDP)	(Ali, et al., 2018)
08	Eco-innovation	High-technology exports (% of manufactured exports)	(Mavi & Mavi, 2021)

Source: Authors estimations.

Table 2. Descriptive statistics year-wise.

Years	CO2	GDP	NNI	HCI	ER	INF	EXP	EIN
1986	6.670	8.950	8.784	0.927	82.970	6.892	8.712	30.013
1987	8.228	11.657	8.922	0.918	82.437	7.234	12.482	30.042
1988	8.160	11.223	9.059	0.910	81.904	18.812	14.382	30.071
1989	7.909	4.206	9.196	0.901	81.371	18.246	11.844	30.100
1990	8.183	3.920	9.333	0.893	80.839	3.052	13.615	30.129
1991	8.554	9.263	9.470	0.884	80.306	3.557	14.488	30.157
1992	8.428	14.225	9.607	0.875	79.773	6.354	15.658	30.186
1993	9.097	13.884	9.744	0.867	79.240	14.610	16.702	30.215
1994	7.952	13.037	9.882	0.858	78.707	24.257	18.537	30.244
1995	7.024	10.954	10.019	0.850	78.174	16.791	17.951	30.273
1996	6.476	9.923	12.660	0.841	77.641	8.313	17.923	30.301
1997	6.044	9.237	9.520	0.833	77.109	2.786	19.493	30.330
1998	5.622	7.846	8.751	0.824	76.576	−0.773	18.342	30.359
1999	5.459	7.662	9.559	0.816	76.043	−1.401	18.163	30.388
2000	5.283	8.490	9.591	0.807	75.320	0.348	20.893	30.417
2001	5.125	8.336	11.651	0.798	75.340	0.719	20.312	30.445
2002	5.330	9.134	12.239	0.790	74.430	−0.732	22.645	30.474
2003	5.775	10.038	11.938	0.781	73.820	1.128	26.981	30.503
2004	5.914	10.114	11.376	0.773	73.230	3.825	31.061	30.532
2005	6.036	11.395	13.030	0.764	72.800	1.776	33.830	30.561
2006	5.818	12.721	14.456	0.756	72.440	1.649	36.035	30.589
2007	4.837	14.231	15.513	0.747	72.020	4.817	35.435	30.151
2008	4.377	9.651	7.195	0.738	71.430	5.925	32.603	29.364
2009	4.096	9.399	13.385	0.730	70.890	−0.728	24.750	31.938
2010	4.134	10.636	9.088	0.721	69.180	3.175	27.185	32.124
2011	3.877	9.551	4.631	0.713	68.890	5.554	26.568	30.484
2012	3.659	7.864	10.661	0.704	68.740	2.620	25.493	30.849
2013	3.492	7.766	6.788	0.696	68.610	2.621	24.599	31.574
2014	3.302	7.426	8.849	0.687	68.470	1.922	23.510	29.695
2015	3.201	7.041	7.958	0.679	68.360	1.437	21.354	30.422
2016	3.176	6.849	8.538	0.670	68.170	2.000	19.584	30.243
2017	3.107	6.947	7.927	0.673	67.930	1.593	19.692	30.907
2018	2.984	6.750	5.200	0.647	67.660	2.075	19.112	31.467
2019	3.086	5.950	5.082	0.621	67.350	2.899	18.410	30.783
2020	2.990	2.348	4.487	0.653	67.196	2.419	18.497	31.274

Source: Authors estimations.

Table 3. Descriptive statistics.

Variable	Obs	Mean	Std. Dev.	Min	Max
CO2	35	5.526	1.921	2.984	9.097
GDP	35	9.103	2.797	2.348	14.231
NNI	35	9.545	2.597	4.487	15.513
HCI	35	0.781	0.088	0.621	0.927
ER	35	74.153	5.107	67.196	82.970
INF	35	5.022	6.176	−1.401	24.257
EXP	35	21.338	6.753	8.712	36.035
EIN	35	30.503	0.578	29.364	32.124

Source: Authors estimations.

Figure 2. Correlation matrix.

Source: Authors estimations.

Table 4. Correlation matrix.

Variables	CO2	GDP	NNI	HCI	ER	INF	EXP	EIN
CO2	1.000
GDP	0.455	1.000
NNI	0.322	0.543	1.000
HCI	0.937	0.356	0.314	1.000
ER	0.938	0.317	0.273	0.992	1.000
EXP	0.429	0.317	0.400	−0.516	−0.575	−0.348	1.000
EIN	−0.621	0.142	0.645	−0.432	−0.373	0.252	0.337	1.000

Source: Authors estimations.

Table 5. Unit root test.

ADF	Level	t-stats	p-values
CO2	I(0)	−4.882	.012
GDP	I(1)	−5.990	.00
NNI	I(1)	−5.262	.00
HCI	I(0)	−2.101	.035
ER	I(0)	3.189	.015
INF	I(0)	−3.302	.027
EXP	I(1)	−5.108	.00
EIN	I(1)	−5.127	.00

Source: Authors estimations.

Figure 3. CUSUM and CUSUM square.

Source: Authors estimations.

Table 6. QARDL model.

	GDP	NNI	HCI	ER	INF	EXP	EIN
Panel A: Short-run Coeff
Q0.1	.54*	.32*	.51**	.43**	.43**	.37*	−.34*
Q0.2	.38**	.29**	.60**	.56*	.39*	.54**	−.43*
Q0.3	.72*	.20*	.31*	.49*	.51*	.53**	−.76**
Q0.4	.10*	.61***	.75**	.55**	.47*	.52*	−.57*
Q0.5	.62***	.72*	.15	.67***	.26	.55**	−.34*
Q0.6	.81*	.04	.07	.17	.52**	.17	−.54*
Q0.7	.70*	.12	.91**	.08	.17	.12	−.12*
Q0.8	.62*	.82*	.52*	.18	.28*	.10	−.03
Q0.9	.01	.72**	.19	.65**	.10	.73**	−.10
Panel B: Long-run Coeff
Q0.1	.38*	.54*	.34**	.29**	.43*	.54**	−.45*
Q0.2	.48**	.29**	.61**	.35*	.56**	.37*	−.64*
Q0.3	.39*	.72***	.44*	.91***	.84**	.40*	−.76**
Q0.4	.65*	.43**	.30*	.33*	.92**	.32*	−.87**
Q0.5	.68**	.28*	.23*	.23*	.62**	.20*	−.36*
Q0.6	.32*	.19*	.83***	.19*	.22*	.01	−.46*
Q0.7	.10	.12	.04	.12	.30*	.10	−.42*
Q0.8	.19	.10	.02	.23*	.03	.39*	−.31*
Q0.9	.13	.19	.18	.02	.06	.53*	−.11
Panel C: Diagnostics
Ad. R square	.65
Reset	1.47*
LM	.98
CUSUM	S
CUSUMQ	S

Source: Authors estimations.

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