Energy security as a source of international competitiveness in new EU member states

Honorata Nyga-Łukaszewska; Tomasz M. Napiórkowski

doi:10.2478/ijme-2023-0015

Energy security as a source of international competitiveness in new EU member states

International Journal of Management and Economics

Volume 59 (2023): Issue 3 (September 2023)

By: Honorata Nyga-Łukaszewska and Tomasz M. Napiórkowski

Open Access

|Sep 2023

Figures & Tables

Poland’s and EU’s GDP annual growth rate (%) 2005–2019. *Source:* Own work based on data from the World Bank [2020].

Poland’s and EU’s exports of goods and services (% of GDP) 2005–2019. *Source:* Own work based on data from the World Bank [2020].

Poland’s and EU’s total primary energy supply (tons of oil equivalent, millions) 2005–2018. *Source:* Own work based on data from the OECD [2020].

Relative share of renewable energy in gross final energy consumption 2005–2018. BG, Bulgaria; CZ, Czechia; ES, Estonia; HU, Hungary; LT, Lithuania; LV, Latvia; MT, Malta; RO, Romania; SK, Slovakia; SL, Slovenia. *Source:* Own work based on data from the Eurostat [2020c].

Table 1.

Variables description

Group	Description (source)	Formula
Dependent variable	Relative RCA*	$\ln (R C A_{i}^{}) - \ln (R C A_{P L}^{})$
Heckscher–Ohlin theory	Relative physical capital per worker endowment	$[\ln (\frac{K_{i}}{L_{i}}) - \ln (\frac{K_{P L}}{L_{P L}})] \frac{K_{i}}{G V A_{i}}$
	Relative human capital endowment	$[\ln (H_{i}) - \ln (H_{P L})] \frac{w_{i}}{\bar{w}}$
Ricardian theory	Relative labor productivity	$\ln (\frac{G V A_{i}}{L_{i}}) - \ln (\frac{G V A_{P L}}{L_{P L}})$
Energy variables	Total primary energy supply [OECD, 2020]	ln (TPES_i) – ln (TPES_PL)
	Energy import dependency [Eurostat, 2020b]	ln (EID_i)–ln(EID_PL)
	Share of renewable energy in gross final energy consumption [Eurostat, 2020c]	ln (RES_i)–ln(RES_PL)
	Energy intensity [Eurostat, 2020d]	ln(EI_i)–ln(Ei_PL)
	Greenhouse gas emissions [Eurostat, 2020e]	ln (GHG_i)–ln (GHG_PL)

1 Note: The time subscript t has been omitted to ensure clarity.

Source: Authors’ own input.

Table 2.

Values of VIFs

Variable	ln(TPES_i) – ln(TPES_PL)	$\ln (\frac{G V A_{i}}{L_{i}}) - \ln (\frac{G V A_{P L}}{L_{P L}})$	$[\ln (\frac{K_{i}}{L_{i}}) - \ln (\frac{K_{P L}}{L_{P L}})] \frac{K_{i}}{G V A_{i}}$	ln(RES_i) – ln(RES_PL)	ln(GHG_i) – ln(GHG_PL)	ln(EI_i) – ln(Ei_PL)	$[\ln (H_{i}) - \ln (H_{P L})] \frac{w_{i}}{\bar{w}}$	ln(EID_i) – ln(EID_PL)	Mean VIF
VIF	10.480	5.540	3.930	3.370	2.980	2.760	2.590	2.490	4.270

1 Source: Own calculations with STATA 15 based on data from the World Bank [2020], OECD [2020], University of Groningen [2019a], and Eurostat [2020a-e].

Poland’s RCA* 2004–2017.
*Source:* Own work based on data from the World Bank [2020].

Relative RCA* for the analyzed economies. BG, Bulgaria; CZ, Czechia; ES, Estonia; HU, Hungary; LT, Lithuania; LV, Latvia; MT, Malta; RO, Romania; SK, Slovakia; SL, Slovenia.
*Source:* Own work based on data from the World Bank [2020].

Table 3.

Results of econometric modeling

	Model 1 (Eq. [3])		Model 2 (Eq. [4])		Model 3 (Eq. [5])
$\ln (R C A_{i}^{⋆}) - \ln (R C A_{P L}^{*})$	Coef.	P > t	Coef.	P > t	Coef.	P > t
ln(TPES_i) – ln(TPES_PL)	–0.220*	0.058	–0.213**	0.023	–0.170*	0.078
ln(EID_i) – ln(EID_PL)	–0.013	0.743	-	-	-	-
ln(RES) – ln(RES_PL)	–0.018**	0.047	–0.020**	0.018	-	-
ln(EI_i) – ln(EI_PL)	–0.031	0.671	-	-	-	-
ln(GHG_i) – ln(GHG_PL)	0.021	0.684	-	-	-	-
$[\ln (\frac{K_{i}}{L_{i}}) - \ln (\frac{K_{P L}}{L_{P L}})] \frac{K_{i}}{G V A_{i}}$	195.925*	0.094	191.537	0.105	212.377*	0.068
$[\ln (H_{i}) - \ln (H_{P L})] \frac{w_{i}}{\bar{w}}$	1.482**	0.015	1.519**	0.015	1.533**	0.016
$\ln (\frac{G V A_{i}}{L_{i}}) - \ln (\frac{G V A_{P L}}{L_{P L}})$	–0.058	0.680	–0.045	0.760	–0.057	0.700
β₀	–0.600	0.021	–0.595	0.006	–0.515	0.026
Lagram–Multiplier	0.001		0.001		0.001
Modified Wald	0.000		0.000		0.000
Jarque–Bera P-value	0.016		0.021		0.126
Shapiro–Wilk P-value	0.000		0.000		0.017
Levin–Lin–Chu P-value	0.000		0.000		0.000
Harris–Tzavalis P-value	0.000		0.000		0.000
R² within	0.263		0.259		0.235
R² between	0.235		0.239		0.277
R² overall	0.193		0.196		0.228
Prob. > F	0.000		0.001		0.001

1 Note: ** and * denote significance at the 5% and 10% levels, respectively.

Source: Own calculations with STATA 15 based on data from the World Bank [2020], OECD [2020], University of Groningen [2019a], and Eurostat [2020a-e].

References

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Articles in this issue

DOI: https://doi.org/10.2478/ijme-2023-0015 | Journal eISSN: 2543-5361 (formerly 2299-9701) | Journal ISSN: 2299-9701

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Language: English

Page range: 209 - 224

Submitted on: Jul 15, 2022

Accepted on: Jun 6, 2023

Published on: Sep 30, 2023

Published by: SGH Warsaw School of Economics

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

energy security,

factor endowment theory,

Heckscher–Ohlin trade model,

international competitiveness,

Ricardian trade model

JEL:

Q43,

F14,

N74

Related subjects:

Business and economics,

Business management,

Management accounting, financial controlling, cost calculation, investment

© 2023 Honorata Nyga-Łukaszewska, Tomasz M. Napiórkowski, published by SGH Warsaw School of Economics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 59 (2023): Issue 3 (September 2023)

Energy security as a source of international competitiveness in new EU member states

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Table 1.

Table 2.

Figure 5.

Figure 6.

Table 3.

Paradigm

My account