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Natural Resources, Urbanisation, Economic Growth and the Ecological Footprint in South Africa: The Moderating Role of Human Capital Cover

Natural Resources, Urbanisation, Economic Growth and the Ecological Footprint in South Africa: The Moderating Role of Human Capital

Quaestiones Geographicae
Volume 40 (2021): Issue 2 (June 2021)
By:   
Open Access
|Jun 2021
Figures & tables

Figures & Tables

Table 1

Studies on NR, human capital, energy consumption, and the EF.

Author(s)Time periodMethodologyVariables consideredCountry(ies)Key finding(s)
Nathaniel (2021)1990–2016AMGNRR, GDP, HC, EFASEAN blocNRR does not hurt environment in Thailand and Laos PDR. Bidirectional causality exists between HC and GDP, and between NRR and GDP.
Ulucak et al. (2020)1995–2016DOLS, FMOLS.EF, GDP, NRR, URB, RENBRICSREN, URB, and NRR decrease EF. GDP enhances environmental degradation.
Ahmed et al. (2020a)1970–2016ARDLNRR, HC, GDP, URB, EFChinaURB, NRR, and GDP drive EF in China.
Ahmed et al. (2020b)1971–2014CUP-FM, CUP-BC.FDI, GDP, NRE, URB, HC, EFG7 countries.GDP, NRE, and URB increase EF, while HC and FDI reduce it.
Nathaniel (2020)1971–2014ARDLGDP, NRE, URB, TRD, EFIndonesiaNRE, GDP, and URB increase EF in Indonesia.
Baloch et al. (2019a)1990–2016Driscoll-Kraay panel regressionFDI, GDP, FDV, NRE, URB, EF59 Belt and Road countries.FDV, FDI, NRE and URB have negative influence on environment.
Hassan et al. (2019a)1971–2014ARDLNRR, GDP, BIO, GDP2 EFPakistanLong-run causality exists between BIO and EF. NRR has positive impact on EF.
Hassan et al. (2019b)1971–2014ARDLHC, GDP, BIO, EFPakistanBIO increases EF. GDP declines EF by 0.60%. HC exerts negative effect on EF. GDP Granger causes EF.
Dogan et al. (2019)1971–2013ARDLFossil fuel energy, URB, Export, FDV, REN, EFMexico, Indonesia, Nigeria, and Turkey.URB is chief cause of environmental degradation.
Nathaniel et al. (2020c)1990–2016AMGREN, NRE, URB, EF, FDV, GDPMENAFDV, GDP, NRE, and URB increase EF in MENA. One-way causality flows from NRE and URB to EF.
Nathaniel et al. (2020d)1980–2016Panel Quantile RegressionFDI, EF, NRE, URB, GDP, carbon footprint, CO2 emissionsCoastal Mediterranean countriesNRE degrades environment. Effects of GDP and URB on environment were mixed for different indicators.
Ulucak et al. (2020)1992–2016FMOLS, DOLS.NRR, URB, REN, GDP, GDP2, EFBRICSEKC is validated in individual BRICS countries. NRR, URB, and REN reduce EF.
Destek, Sinha (2020)1980–2014MG. FMOLS-MG, DOLS-MG.GDP, GDP2, EF, REN, TRD, NRE24 OECD countries.EKC hypothesis does not hold. REN reduces EF.
Wang, Dong (2019)1990–2014AMGREN, URB, GDP, GDP2, EF, NRE14 SSA countries.Feedback causality runs among NRE, URB, GDP, and EF. NRE, GDP, and URB exert positive effects on EF.
Sharma et al. (2020)1990–2015Panel ARDLREN, URB, POP, FOR, NRE, GDP, EFAsiaURB, GDP, NRE, FOR, and POP drive EF. REN restores environmental quality.
Ansari et al. (2020)1991–2017PMGEF, URB, Material footprint, GDP, GLO, NRE37 Asian countriesURB and GLO increase EF. GDP and NRE also increase EF.
Sharif et al. (2020)1965Q1–2017Q4Quantile ARDLNRE, EF, REN, GDPTurkeyFeedback causality exists among listed variables; RE, GDP, NRE, and EF.
Altıntaş, Kassouri (2020)1990–2014CCEMG, IFE.CO2 emissions, EF, RE, GDP, NREEuropeRE is environmentally friendly. NRE exerts positive impact on EF.
Baz et al. (2020)1971–2014NARDLGDP, NRE Capital, EFPakistanEF Granger causes NRE. GDP does not cause EF.
Aziz et al. (2020)1990–2018QARDLGDP, EF, FOR, REPakistanFOR and REN minimise EF. GDP increases EF thereby encouraging environmental degradation.

[i] Note: ARDL – autoregressive distributed lag model; QARDL: BRICS – Brazil, Russia, India, China and South Africa; BIO – biocapacity; CUP-FM – continuously updated fully modified; CUP-BC – continuously updated bias-corrected; DOLS – dynamic ordinary least squares; EF – ecological footprint; EKC – Environmental Kuznets Curve; FDI – Foreign Direct Investment; FOR – forest; FMOLS – fully modified ordinary least squares; FDV – Financial Development; GLO – globalisation; HC – human capital; IFE – interactive fixed effects; MG – mean group; MENA – Middle East and North Africa; NR – natural resources; NRE – non-renewable energy; NARDL – non-linear ARDL; POP – population; REN – renewable energy; SSA – Sub-Saharan Africa; TRD – trade openness; TRD – trade; Quantile ARDL; URB – urbanisation.

[ii] Source: own compilation.

Table 2

Measurement and source of data.

S/NIndicator nameMeasurementSource
1UrbanisationUrban population (% of total population)WDI (2019)
2Natural resourcesTotal natural resource rent (% of GDP)✓
3GDP per capitaIn constant 2010 USD✓
4Interaction term(Human capital × Urbanisation)✓
5GDP per capita2In constant 2010 USD✓
6Ecological footprintGlobal hectares per capitaGFN (2019)
7Human capitalHuman capital indexPenn World Table

[i] GFN – global footprint network; WDI – World Development Indicator.

[ii] Source: own compilation.

Fig. 1

Plots of the series. EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

Source: own compilation.

Table 3

Descriptive statistics.

EFGRGRNRHCUBIN
Mean1.0708.77214.511.6570.7273.9910.549
Max.3.9308.93315.052.6781.0164.1790.801
Min.1.1008.61514.000.6500.5843.8670.426
Std. D0.2450.0930.3090.4600.1310.1040.114
Skewness−0.1170.2650.2810.0620.8620.3110.836
Kurtosis2.1982.1262.1282.7072.3841.6692.350
Prob.0.5050.3590.3480.9050.0370.1200.042

[i] EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation; GR – economic growth; IN – interaction between HC and UB.

[ii] Source: author's computation.

Table 4

Results of the DF-GLS and NG-Perron unit root tests.

VariablesDF-GLSNG-Perron
At levelDifferenceAt levelDifference
t-statistict-statistict-statisticMSB 5%t-statisticMSB 5%
EF0.091−6.811***0.8290.2330.148**0.233
GR−0.846−4.228***0.3460.2330.162**0.233
HC−0.318***−0.2080.244**0.2330.5590.233
NR−2.426−8.647***0.2340.2330.154***0.233
UB−1.702***−0.7970.143**0.2330.5190.233
IN−0.528***−0.4740.228**0.2330.5510.233
GR2−0.920−4.152***0.3380.2330.164***0.233

[i] Note: *** and ** represent 1% and 5% significance level respectively. −1.61 (10%), −1.94 (5%) and −2.61 (1%) are the DF-GLS critical values.

[ii] EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Table 5

ZA unit root results.

VariablesZA unit root test
LevelDifference
t-valueBreak yeart-valueBreak year
EF−4.1912003−8.473***2008
GR−3.1162004−5.155**1994
NR−3.6591987−9.614**1981
HC−1.7262001−5.336***2001
UB−4.9911986−7.031***1985
IN−3.5812001−3.989***2001
GR2−3.0241985−5.206**1994

[i] Note: *** represents 0.01% significance level.

[ii] EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Table 6

Bounds test results.

ModelsLower boundUpper boundSignificance level
Model 1
Fc (lngr, lnnr, lnhc, lnub). F = 8.34252.25
2.86
3.69		3.59
3.76
4.46		10%
5%
1%
Model 2
Fc (lngr, lnnr, lnhc, lnub, lnin). F = 7.60691.81
2.14
2.82		2.93
3.34
4.21		10%
5%
1%
Model 3
Fc (lngr, lnnr, lnhc, lnub, lngr2). F = 8.56472.29
2.71
3.46		3.38
4.56
4.76		10%
5%
1%

[i] Source: author's computation.

Table 7

BH test results.

Estimated modelsEG − JOHEG − JOH − BO − BDMCointegration
lnEF = f(lnGR,lnNR,lnHC,lnUB)14.65138.854Yes
lnEF = f(lnGR,lnNR,lnHC,lnUB,lnIN)21.36144.537Yes
lnEF = f(lnGR,lnNR,lnHC,lnUB,lnGR2)15.10136.342Yes
5% critical value (for Model 1)10.57620.143
5% critical value (for Models 2 and 3)10.41919.888

[i] Note: ** represents 0.05% significance level.

[ii] EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Table 8

ARDL results.

Long-run results
VariablesModel 1Model 2Model 3
Constant4.162**4.432**2.465
(2.478)(3.441)(1.047)
GR (log)0.032**0.546***0.129***
(2.675)(4.567)(3.657)
HC (log)−0.044**−0.146**−0.198***
(−2.987)(−2.286)(−3.892)
NR (log)0.275***0.297***0.140***
(2.979)(3.486)(3.287)
UB (log)0.450***0.228***0.052***
(7.657)(6.836)(6.679)
IN (log)–−0.231***–
–(−4.675)–
GR2 (log)––−0.056***
––(−7.546)
Short-run results
VariablesModel 1Model 2Model 3
EF(−1) (log)−0.298***−0.672***−0.098***
(−4.564)(−6.978)(−7.619)
Dlog(HC)−1.324−0.174**−1.534
(−0.246)(−2.167)(−0.678)
Dlog(HC(−1))1.349−0.4371.872
(0.392)(−1.443)(0.954)
Dlog(NR)0.032***0.060***0.007*
(5.923)(5.823)(1.878)
Dlog(NR(−2)0.062–0.567
(1.409)–(1.765)
Dlog(UB)0.629***0.672***0.050***
(6.867)(7.562)(6.985)
Dlog(GR)0.045***0.045***1.546
(4.670)(3.967)(0.845)
CointEq(−1)*−0.986***−0.876***−0.156***
(−8.719)(−7.491)(−6.821)
Diagnostic tests
R-squared0.7670.6270.843
χ2 Jarque-Bera0.8670.9650.825
χ2 LM test0.6290.5640.725
χ2 Ramsey0.1850.4870.627
χ2 Breusch-Pagan-Godfrey0.4890.6460.342

[i] Note: ***, ** and * represent statistical significance at the 1%, 5% and 10% levels of significance respectively; t-statistics are in parentheses.

[ii] ARDL – autoregressive distributed lag; EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Table 9

Robustness check.

VariablesFMOLSDOLSCCR
GR (log)0.056**0.202**0.326***
(2.276)(2.581)(4.768)
HC (log)−0.064***−1.667***−0.621***
(−5.835)(−9.673)(−8.289)
NR (log)0.024***0.241***1.046***
(3.768)(4.573)(9.231)
UB (log)0.348***0.271***0.2286***
(3.987)(9.482)(7.271)

[i] Note: *** and ** represent statistical significance at the 1% and 5% levels respectively; t-statistics are in parentheses.

[ii] CCR – canonical regression; DOLS – dynamic ordinary least squares; FMOLS – fully modified ordinary least squares; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Table 10

Toda-Yamamoto test results.

Null HypothesesMWALD Stat.ProbabilityCausality
GR→EF6.0150.021Yes
HC→EF5.8920.044Yes
NR→EF4.0420.120No
UB→EF8.7630.007Yes
EF→GR7.3820.035Yes
HC→GR9.7020.031Yes
NR→GR5.8190.042Yes
UB→GR8.2810.018Yes
EF→HC1.7450.650No
GR→HC0.6190.723No
NR→HC1.8910.634No
UB→HC2.8170.380No
EF→NR0.4830.066Yes
GR→NR0.5810.001Yes
HC→NR1.2910.035Yes
UB→NR9.3820.491No
EF→UB0.1730.849No
GR→UB0.4810.341No
HC→UB1.4610.635No
NR→UB9.9030.045Yes

[i] Note: All the variables are logged.

[ii] EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

[iii] Source: author's computation.

Fig. 2

Causality relationship schema.

EF – ecological footprint; HC – human capital; NR – natural resources; UB – urbanisation.

Fig. 3

Cusum and Cusumsq plots for Model 1.

Source: own compilation.

Fig. 4

Cusum and Cusumsq plots for Model 2.

Source: own compilation.

Fig. 5

Cusum and Cusumsq plots for Model 3.

Source: own compilation.

DOI: https://doi.org/10.2478/quageo-2021-0012 | Journal eISSN: 2081-6383 | Journal ISSN: 2082-2103 (formerly 0137-477X)
Journal RSS Feed
Language: English
Page range: 63 - 76
Submitted on: Oct 22, 2020
Published on: Jun 30, 2021
Published by: Adam Mickiewicz University
In partnership with: Paradigm Publishing Services
Keywords:
urbanisation,
natural resources,
ecological footprint,
human capital,
South Africa
Related subjects:
Geosciences,
Geography

© 2021 Solomon Prince Nathaniel, published by Adam Mickiewicz University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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