Modelling intangibles at the regional level in Europe: what lessons from a multidimensional approach?

Figures & data

Figure 1. Research model.

Table 1. Regional intangible capital measures and data sources.

Variable	Description	Source
Human capital (a) Higher education (b) Health	Tertiary education attainment (25–64 y.o.), % Participation rate in education and training (25–64 y.o.), (last 4 weeks),% Labour force (15–64 y.o.) with tertiary education (levels 5–8), % Life expectancy, years Health personnel, Per hundred thousand inhabitants State of health services in a country (0–10 scale) Subjective general health (1–5 scale)	Eurostat, 2017 ESS Round 8, 2016
Renewal capital (a) Employment in knowledge-intensive activities (b) R&D spending	Total R&D personnel and researchers, % of total employment Employment in high-technology sectors, % of total employment Persons employed in science and technology, % of active population Scientists and engineers, % of active population R&D expenditure in the public sector, % of GDP R&D expenditure in the business sector, % of GDP	Eurostat, 2017 RIS, 2017
Institutional capital Governmental quality Institutional trust Freedom of speech	The European Quality of Government Index (corruption, impartiality, and quality dimensions) Trust in country’s parliament, legal system, police, politicians, political parties (0–10 scale) Political system allows people to have a say in what government does (1–5 scale)	EQGI, 2017 ESS Round 8, 2016
Social capital (a) Cognitive social capital (b) Structural social capital	Most people can be trusted or you can’t be too careful (0–10 scale) Most people try to take advantage of you, or try to be fair (0–10 scale) Most of the time people helpful or mostly looking out for themselves (0–10 scale) Member of trade union or similar organisation, % of respondents Worked in another organisation or association last 12 months, % of respondents Take part in social activities compared to others of same age (1–5 scale)	ESS Round 8, 2016
ICT infrastructure capital	Households with access to the internet at home, % of households Households with broadband access, % of households	Eurostat, 2017
Entrepreneurship capital	Number of enterprise births divided by the number of enterprises active, % 3 year old enterprises’ share of the business population, %	Eurostat, 2017

Figure 2. Regional intangible capital index across European NUTS 2 regions.

Figure 3. GDP per capita across European NUTS 2 regions.

Table 2. Descriptive statistics.

	Mean	Std.Dev.	Min	Max
GDP per capita, log	10.02	0.506	9.000	11.10
Capital	8.790	1.064	5.321	11.95
Labour force	71.90	5.552	52	85.30
Human capital	0.456	0.104	0.218	0.697
Renewal capital	0.387	0.124	0.185	0.794
Institutional capital	0.433	0.155	0.143	0.889
ICT infrastructure capital	0.598	0.128	0.229	0.954
Social capital	0.486	0.141	0.0796	0.871
Entrepreneurship capital	0.329	0.160	0.0103	0.797
RIC index	0.448	0.0906	0.284	0.766

Table 3. Correlation matrix.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
(1) GDP per capita, log	1.00
(2) Capital	0.50*	1.00
(3) Labour force	0.44*	0.11	1.00
(4) Human capital	0.80*	0.41*	0.60*	1.00
(5) Renewal capital	0.64*	0.47*	0.54*	0.67*	1.00
(6) Institutional capital	0.50*	0.17	0.68*	0.60*	0.64*	1.00
(7) ICT infrastructure capital	0.56*	0.24*	0.55*	0.54*	0.68*	0.68*	1.00
(8) Social capital	0.68*	0.29*	0.57*	0.67*	0.59*	0.81*	0.60*	1.00
(9) Entrepreneurship capital	−0.54*	−0.16	0.01	−0.29*	−0.11	−0.01	−0.23*	−0.31*	1.00
(10) RIC index	0.59*	0.32*	0.71*	0.73*	0.82*	0.91*	0.78*	0.80*	0.07	1.00

* p < 0.05

Table 4. Spatial regression results for regional intangibles: Direct and moderated effects of human capital.

	(1)	(2)	(3)	(4)	(5)	(6)
	est1	est2	est3	est4	est5	est6
GDP per capita, log Controls Capital	0.155***	0.050*	0.056*	0.053*	0.043^†	0.042*
	(0.029)	(0.025)	(0.023)	(0.024)	(0.024)	(0.021)
Labour force	0.041***	0.002	0.010	0.002	−0.004	0.006
	(0.006)	(0.006)	(0.006)	(0.006)	(0.006)	(0.005)
Direct effects Human capital		3.069***	3.661***	3.066***	2.451***	2.774***
		(0.412)	(0.445)	(0.418)	(0.457)	(0.367)
Renewal capital		0.612*	0.209	0.246	0.628*	0.664**
		(0.296)	(0.308)	(0.313)	(0.294)	(0.250)
Interactions Institutional capital			0.006 (0.230)
Human capital x Institutional capital			5.421*** (1.558)
ICT infrastructure capital				0.647** (0.241)
Human capital x ICT infrastructure capital				2.328 (1.772)
Social capital					0.809*** (0.229)
Human capital x Social capital					−1.279 (1.748)
Entrepreneurship capital						−0.832*** (0.142)
Human capital x Entrepreneurship capital						5.758*** (1.444)
Constant	5.943***	7.692***	8.503***	9.258***	9.665***	9.046***
	(0.863)	(0.652)	(0.769)	(0.731)	(0.668)	(0.432)
Lambda	0.957***	0.958***	0.961***	0.961***	0.954***	0.898***
	(0.043)	(0.042)	(0.039)	(0.039)	(0.046)	(0.103)
AIC	87.626	10.768	3.129	6.049	2.831	−31.145

n = 121, Standard errors in parentheses

^†p < 0.10, * p < 0.05, ** p < 0.01, ***p < p < 0.001

Table 5. Spatial regression results for regional intangibles: Direct and moderated effects of renewal capital.

	(1)	(2)	(3)	(4)	(5)	(6)
	est1	est2	est3	est4	est5	est6
GDP per capita, log Controls Capital	0.155***	0.050**	0.067**	0.057*	0.050*	0.049*
	(0.029)	(0.025)	(0.024)	(0.024)	(0.024)	(0.021)
Labour force	0.041***	0.002	0.005	0.001	−0.002	0.007
	(0.006)	(0.006)	(0.006)	(0.006)	(0.006)	(0.005)
Direct effects Human capital		3.069***	2.976***	2.859***	2.586***	2.399***
		(0.412)	(0.408)	(0.399)	(0.417)	(0.367)
Renewal capital		0.612*	0.533^†	0.292	0.567*	0.817*
		(0.296)	(0.295)	(0.300)	(0.283)	(0.255)
Interactions Institutional capital			0.096 (0.230)
Renewal capital x Institutional capital			2.994** (1.071)
ICT infrastructure capital				0.753** (0.243)
Renewal capital x ICT infrastructure capital				2.550* (1.230)
Social capital					0.765*** (0.224)
Renewal capital x Social capital					0.635 (1.110)
Entrepreneurship capital						−0.825*** (0.147)
Renewal capital x Entrepreneurship capital						2.859** (0.999)
Constant	5.943***	7.692***	7.501***	8.012***	8.422***	8.063***
	(0.863)	(0.652)	(0.748)	(0.734)	(0.726)	(0.460)
Lambda	0.957***	0.958***	0.960***	0.963***	0.957***	0.921***
	(0.043)	(0.042)	(0.041)	(0.038)	(0.043)	(0.079)
AIC	87.626	10.768	6.677	3.544	3.039	−24.094

n = 121, Standard errors in parentheses

^†p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

Table

	Top 10 regions
Code	Name	RIC
NO01	Oslo og Akershus	0.80
SE11	Stockholm	0.78
CH04	Zürich	0.77
DK01	Hovedstaden	0.77
NO06	Trøndelag	0.76
NL31	Utrecht	0.76
CH03	Nordwestschweiz	0.75
SE23	Västsverige	0.74
CH06	Zentralschweiz	0.74
NO07	Nord-Norge	0.73

Table

	Bottom 10 regions
Code	Name	RIC
FRY5	Mayotte	0.26
EL61	Thessaly	0.26
EL51	Eastern Macedonia & Thrace	0.25
EL65	Peloponnese	0.24
EL64	Central Greece	0.24
EL42	South Aegean	0.24
EL53	Western Macedonia	0.24
EL62	Ionian Islands	0.22
BG34	Southeastern	0.21
BG31	Northwestern	0.17