Regional artificial intelligence and the geography of environmental technologies: does local AI knowledge help regional green-tech specialization?

Figures & data

Figure 1. Number of green-tech specializations (EIs) by region, 2014–17.

Figure 2. Artificial intelligence (AI) knowledge stock by region, 2014–17.

Table 1. Descriptive statistics (n = 654,810).

Variable	Mean	SD	Minimum	Maximum
GreenTech	0.05	0.21	0	1
AI stock	14.31	169.00	0	8003.57
Relatedness	0.12	0.05	0	0.50
Patent stock	1883.00	12,771.93	0	406,044.70
GVA per employee	45.11	14.71	3.06	316.39

Note: Number of regions: 1267 NUTS-3 regions; number of green technologies: 69; period of coverage: 1982–2017.

Table 2. GreenTech (dependent variable) and AI at the NUTS-3 level: linear probability model (LPM).

	(a)	(b)	(c)	(d)	(e)
GreenTech (t – 1)	0.227***	0.181***	0.227***	0.223***	0.162***
	[0.005]	[0.018]	[0.005]	[0.005]	[0.017]
AI stock (t – 1)	−0.379**	−0.384**	−2.391***	−0.521***	−2.285***
	[0.149]	[0.152]	[0.443]	[0.167]	[0.443]
Relatedness	0.091***	0.088***	0.092***	0.090***	0.088***
	[0.008]	[0.008]	[0.008]	[0.008]	[0.008]
Patent stock (t – 1)	0.404***	0.410***	0.445***	0.382***	0.426***
	[0.117]	[0.119]	[0.106]	[0.113]	[0.109]
GVA per employee (t – 1)	0.016	0.017	0.014	0.015	0.013
	[0.025]	[0.025]	[0.025]	[0.026]	[0.026]
GreenTech(t – 1)*Relat.		0.166***			0.213***
		[0.058]			[0.054]
AI(t – 1)*Relat.			9.837***		8.594***
			[2.054]		[1.934]
GreenTech(t – 1)*AI(t – 1)				0.995***	1.003***
				[0.220]	[0.221]
NUTS-3 FEs	Yes	Yes	Yes	Yes	Yes
CPC FEs	Yes	Yes	Yes	Yes	Yes
Period FEs	Yes	Yes	Yes	Yes	Yes
N	654,810	654,810	654,810	654,810	654,810
R^2	0.171	0.171	0.172	0.172	0.172

Note: The analysis covers 69 green CPC classes in 1267 NUTS-3 regions over nine four-year periods covering 1982–2017. The dependent variable takes the value of 1 if a region specializes in a green technology in a given period, and 0 otherwise. Robust standard errors clustered at the NUTS-3 level are shown in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01.