Skip to main content

Advertisement

SpringerLink
Log in

The role of human capital in energy-growth nexus: an international evidence

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

This study examines the role of human capital and the Granger causal relationship between energy and economic growth using data from 56 countries over a period of 1970–2014 on the basis of three perspectives—energy trade status, stages of economic development, and geophysical locations. Through continuously updated fully modified estimates that allow for cross-sectional dependence, we find that energy is an important factor input to economic growth, and the output elasticity with respect to energy ranges between 0.1 and 0.5 in various subsamples. Energy is a complement to human capital, and the growth-driving effect of energy is evidenced to be enhanced by human capital development. Furthermore, the bootstrapped panel Granger causality test results suggest that energy Granger causes economic growth in energy-exporting, high-income, and American countries, and therefore, energy conservation policies are more appropriate in energy-importing, middle-income and non-American countries. Based on the results, policy synergies between energy and human capital and multilateral cooperation in promoting energy efficiency should be emphasized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. It would be interesting to see whether the results differ when the energy importers/exporters are further split into different income groups or geographic regions. However, due to the small-sample size issue in further breakdown, the tests and estimations cannot be meaningfully carried out.

  2. For more details on the human capital index, refer to Feenstra et al. (2015) and Fang (2016).

  3. The human capital index is constructed based on the assumptions that earlier years’ education has a higher rate of return than later years’ education (Fang 2016). The findings of this study would be more convincing if different measures of human capital index are applied. Thank the referee for pointing this out.

  4. The group of countries is based on the 2013 World Development Indicators, World Bank. Due to the small N issue, some geographic regions are combined so that we group the countries into four regions: Europe, Asia Pacific, America, and Middle East and Africa.

  5. Following Shahbaz et al. (2013) and Chen and Fang (2018), we assume constant returns to scale and use the per capita terms in the analysis. The analysis based on the per capita variables is also seen in many other studies (Yoo and Lee 2010; Payne 2010).

  6. It is noted that lower-order coefficients in the regression are not of direct interest (Braumoeller 2004).

  7. One exception is the Pesaran’s CD test result for the Asia Pacific countries, which may be caused by the small N problem. The other two tests still support the interdependence.

  8. One exception is the LnK for the Asia Pacific sample which are not stationary at the significance level of 10% even after the first difference. Since the null hypothesis of unit roots can be rejected at a larger significance level, we continue the analysis for Asia Pacific countries as that for other subsamples.

  9. While FMOLS and DOLS are popular in estimating the dynamic panel regressions, Cup-FM approach is selected due to the cross-sectional dependence in the data.

  10. In the sample of Middle East and African countries, the results are not reliable because the cointegration test does not support the presence of a cointegrating relationship.

  11. Note that this increasing/decreasing returns to scale are on per capita terms.

  12. This is, however, in contrast with findings in Pablo-Romero and Sánchez-Braza (2015) who used the GMM to estimate coefficients for a panel sample of 38 countries over 13 years and found a weak substitution relationship between the two.

  13. Other panel causality tests allowing for heterogeneous panels include Dumitrescu and Hurlin (2012) and Kónya (2006).

References

  • Al-Iriani MA (2006) Energy–GDP relationship revisited: an example from GCC countries using panel causality. Energy Policy 34(17):3342–3350

    Article  Google Scholar 

  • Apergis N, Payne JE (2009a) Energy consumption and economic growth: evidence from the Commonwealth of Independent States. Energy Econ 31(5):641–647

    Article  Google Scholar 

  • Apergis N, Payne JE (2009b) Energy consumption and economic growth in Central America: evidence from a panel cointegration and error correction model. Energy Econ 31(2):211–216

    Article  Google Scholar 

  • Apergis N, Payne JE (2010) Energy consumption and growth in South America: evidence from a panel error correction model. Energy Econ 32(6):1421–1426

    Article  Google Scholar 

  • Apergis N, Payne JE (2012) Renewable and non-renewable energy consumption-growth nexus: evidence from a panel error correction model. Energy Econ 34(3):733–738

    Article  Google Scholar 

  • Apergis N, Tang CF (2013) Is the energy-led growth hypothesis valid? New evidence from a sample of 85 countries. Energy Econ 38:24–31

    Article  Google Scholar 

  • Bai J, Kao C (2006) On the estimation and inference of a panel cointegration model with cross-sectional dependence. In: Baltagi BH (ed) Panel data econometrics: theoretical contributions and empirical applications. Elsevier Science, Amsterdam, pp 3–30

    Chapter  Google Scholar 

  • Bai J, Kao C, Ng S (2009) Panel cointegration with global stochastic trends. J Econom 149(1):82–99

    Article  Google Scholar 

  • Barro RJ (1991) Economic growth in a cross section of countries. Q J Econ 106(2):407–443

    Article  Google Scholar 

  • Braumoeller BF (2004) Hypothesis testing and multiplicative interaction terms. Int Org 58(4):807–820

    Article  Google Scholar 

  • Chang T, Gatwabuyege F, Gupta R, Inglesi-Lotz R, Manjezi NC, Simo-Kengne BD (2014) Causal relationship between nuclear energy consumption and economic growth in G6 countries: evidence from panel Granger causality tests. Prog Nucl Energy 77:187–193

    Article  Google Scholar 

  • Chang T, Gupta R, Inglesi-Lotz R, Simo-Kengne B, Smithers D, Trembling A (2015) Renewable energy and growth: evidence from heterogeneous panel of G7 countries using Granger causality. Renew Sustain Energy Rev 52:1405–1412

    Article  Google Scholar 

  • Chen Y, Fang Z (2018) Industrial electricity consumption, human capital investment and economic growth in Chinese cities. Econ Model 69:205–219

    Article  Google Scholar 

  • Chen ST, Kuo HI, Chen CC (2007) The relationship between GDP and electricity consumption in 10 Asian countries. Energy Policy 35:2611–2621

    Article  Google Scholar 

  • Chontanawat J, Hunt LC, Pierse R (2008) Does energy consumption cause economic growth? Evidence from a systematic study of over 100 countries. J Policy Model 30(2):209–220

    Article  Google Scholar 

  • Costantini M, Destefanis S (2009) Cointegration analysis for cross-sectionally dependent panels: the case of regional production functions. Econ Model 26(2):320–327

    Article  Google Scholar 

  • Cowan WN, Chang T, Inglesi-Lotz R, Gupta R (2014) The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries. Energy Policy 66:359–368

    Article  Google Scholar 

  • Damette O, Seghir M (2013) Energy as a driver of growth in oil exporting countries? Energy Econ 37:193–199

    Article  Google Scholar 

  • Dieck-Assad FA, Peralta E (2013) Energy and capital inputs: cornerstones of productivity growth in Mexico: 1965–2004. Empir Econ 44(2):563–590

    Article  Google Scholar 

  • Diks C, Panchenko V (2006) A new statistic and practical guidelines for nonparametric Granger causality testing. J Econ Dyn Control 30(9):1647–1669

    Article  Google Scholar 

  • Diks C, Wolski M (2016) Nonlinear granger causality: guidelines for multivariate analysis. Journal of Applied Econometrics 31:1333–1351

    Article  Google Scholar 

  • Dumitrescu E, Hurlin C (2012) Testing for Granger non-causality in heterogeneous panels. Econ Model 29:1450–1460

    Article  Google Scholar 

  • Emirmahmutoglu F, Kose N (2011) Testing for Granger causality in heterogeneous mixed panels. Econ Model 28:870–876

    Article  Google Scholar 

  • Emirmahmutoglu F, Bacilar M, Apergis N, Simo-Kengne BD, Chang T, Gupta R (2016) Causal relationship between asset prices and output in the United States: evidence from the state-level panel Granger causality test. Reg Stud 50:1728–1741

    Article  Google Scholar 

  • Engle RF, Granger CW (1987) Co-integration and error correction: representation, estimation, and testing. Econometrica 55:251–276

    Article  Google Scholar 

  • Fang Z (2016) Data on examining the role of human capital in the energy-growth nexus across countries. Data Brief 9:540–542

    Article  Google Scholar 

  • Fang Z, Chang Y (2016) Energy, human capital and economic growth in Asia Pacific countries—evidence from a panel cointegration and causality analysis. Energy Econ 56:177–184

    Article  Google Scholar 

  • Fang Z, Chen Y (2017) Human capital and energy in economic growth–evidence from Chinese provincial data. Energy Econ 68:340–358

    Article  Google Scholar 

  • Fang Z, Wolski M (2016) Human capital, energy and economic growth in China–Evidence from multivariate nonlinear Granger causality, working paper (unpublished)

  • Fang Z, Chang Y, Hamori S (2017) Human capital and energy: a driver or drag for economic growth. Singap Econ Rev 1750016

  • Feenstra RC, Inklaar R, Timmer MP (2015) The next generation of the Penn World Table. Am Econ Rev 105(10):3150–3182

    Article  Google Scholar 

  • Frees EW (1995) Assessing cross-sectional correlation in panel data. J Econom 69:393–414

    Article  Google Scholar 

  • Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J Am Stat Assoc 32:675–701

    Article  Google Scholar 

  • Ghali KH, El-Sakka MIT (2004) Energy use and output growth in Canada: a multivariate cointegration analysis. Energy Econ 26:225–238

    Article  Google Scholar 

  • Glasure YU (2002) Energy and national income in Korea: further evidence on the role of omitted variables. Energy Econ 24:355–365

    Article  Google Scholar 

  • Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 36:424–438

    Article  Google Scholar 

  • Hansen BE, Seo B (2002) Testing for two-regime threshold cointegration in vector error correction models. J Econom 110:293–318

    Article  Google Scholar 

  • Hiemstra C, Jones JD (1994) Testing for linear and nonlinear Granger causality in the stock price-volume relation. J Finance 49(5):1639–1664

    Google Scholar 

  • Hossain MS (2011) Panel estimation for CO2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. Energy Policy 39(11):6991–6999

    Article  Google Scholar 

  • Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econom 115(1):53–74

    Article  Google Scholar 

  • Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxf Bull Econ Stat 52(2):169–210

    Article  Google Scholar 

  • Kónya L (2006) Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Econ Model 23(6):978–992

    Article  Google Scholar 

  • Kraft J, Kraft A (1978) On the relationship between energy and GNP. J Energy Dev 3:401–403

    Google Scholar 

  • Levin A, Lin CF, Chu CSJ (2002) Unit root test in panel data: asymptotic and finite sample properties. J Econom 108:1–24

    Article  Google Scholar 

  • Mahadevan R, Asafu-Adjaye J (2007) Energy consumption, economic growth and prices: a reassessment using panel VECM for developed and developing countries. Energy Policy 35(4):2481–2490

    Article  Google Scholar 

  • Mehrara M (2007) Energy consumption and economic growth: the case of oil exporting countries. Energy Policy 35(5):2939–2945

    Article  Google Scholar 

  • Nasreen S, Anwar S (2014) Causal relationship between trade openness, economic growth and energy consumption: a panel data analysis of Asian countries. Energy Policy 69(C):82–91

    Article  Google Scholar 

  • Noor S, Siddiqi MW (2010) Energy consumption and economic growth in South Asian countries: a co-integrated panel analysis. Int Sch Sci Res Innov 4(7):196–201

    Google Scholar 

  • Ozturk I (2010) A literature survey on energy-growth nexus. Energy Policy 38:340–349

    Article  Google Scholar 

  • Ozturk I, Al-Mulali U (2015) Natural gas consumption and economic growth nexus: panel data analysis for GCC countries. Renew Sustain Energy Rev 51:998–1003

    Article  Google Scholar 

  • Pablo-Romero MDP, Sánchez-Braza A (2015) Productive energy use and economic growth: energy, physical and human capital relationships. Energy Econ 49:420–429

    Article  Google Scholar 

  • Payne JE (2010) Survey of the international evidence on the causal relationship between energy consumption and growth. J Econ Stud 37:53–95

    Article  Google Scholar 

  • Pedroni P (1999) Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxf Bull Econ Stat 61:653

    Article  Google Scholar 

  • Pedroni P (2004) Panel cointegration: asymptotic and finite samples properties of pooled time series tests with an application to the PPP hypothesis. Econom Theory 20:597–625

    Article  Google Scholar 

  • Perron P (1997) Further evidence on breaking trend functions in macroeconomic variables. J Econom 80:355–385

    Article  Google Scholar 

  • Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. Cambridge working papers in economics No. 0435

  • Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econom 22:265–312

    Article  Google Scholar 

  • Pesaran MH, Yamagata T (2008) Testing slope homogeneity in large panels. J Econom 142(1):50–93

    Article  Google Scholar 

  • Pesaran MH, Shin Y, Smith R (2001) Bounds testing approaches to the analysis of level relationships. J Appl Econom 16:289–326

    Article  Google Scholar 

  • Rezitis AN, Ahammad SM (2015) The relationship between energy consumption and economic growth in South and Southeast Asian countries: a panel vector autoregression approach and causality analysis. Int J Energy Econ Policy 5(3):704–715

    Google Scholar 

  • Romer PM (1990) Human capital and growth: theory and evidence. Carnegie-Rochester conference series on public policy 32:251–286

    Article  Google Scholar 

  • Sadorsky P (2012) Energy consumption, output and trade in South America. Energy Econ 34:476–488

    Article  Google Scholar 

  • Shahbaz M, Khanb S, Tahir MI (2013) The dynamic links between energy consumption, economic growth, financial development and trade in China: fresh evidence from multivariate framework analysis. Energy Econ 40:8–21

    Article  Google Scholar 

  • Sims CA (1972) Money, income, and causality. Am Econ Rev 62:540–552

    Google Scholar 

  • Smith LV, Leybourne S, Kim TH, Newbold P (2004) More powerful panel data unit root tests with an application to mean reversion in real exchange rates. J Appl Econom 19(2):147–170

    Article  Google Scholar 

  • Stern D (2000) A multivariate cointegration analysis of the role of energy in the US economy. Energy Econ 22:267–283

    Article  Google Scholar 

  • Swamy PA (1970) Efficient inference in a random coefficient regression model. Econometrica 38:311–323

    Article  Google Scholar 

  • Toda HY, Yamamoto T (1995) Statistical inferences in vector autoregressions with possibly integrated processes. J Econom 66:225–250

    Article  Google Scholar 

  • Westerlund J (2006) Testing for panel cointegration with multiple structural breaks. Oxf Bull Econ Stat 68(1):101–132

    Article  Google Scholar 

  • Westerlund J (2007) Testing for error correction in panel data. Oxf Bull Econ Stat 69(6):709–748

    Article  Google Scholar 

  • Yildirim E, Aslan A, Ozturk I (2014) Energy consumption and GDP in ASEAN countries: bootstrap-corrected panel and time series causality tests. Singap Econ Rev 59(02):1450010

    Article  Google Scholar 

  • Yoo SH, Lee JS (2010) Electricity consumption and economic growth: a cross-country analysis. Energy Policy 38(1):622–625

    Article  Google Scholar 

  • Zivot E, Andrews D (1992) Further evidence of the great crash, the oil price shock, and the unit root hypothesis. J Bus Econ Stat 10:251–270

    Google Scholar 

Download references

Acknowledgements

We are grateful for the helpful comments provided by the editor professor Robert Kunst and the anonymous referee. Jiang Yu gratefully acknowledges financial support from the MOE Project of Key Research Institute of Humanities and Social Sciences (Grant No. 16JJD790044), and National Social Sciences Foundation Project (Grant No. 17BJY219).

Author information

Authors and Affiliations

  1. School of Business, Singapore University of Social Sciences, #05-04, 463 Clementi Road, Singapore, 599494, Singapore

    Zheng Fang

  2. The Center for Economic Development Research, Wuhan University, Wuhan, China

    Jiang Yu

Authors
  1. Zheng Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zheng Fang.

Appendix

Appendix

See Table 9.

Table 9 List of countries
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, Z., Yu, J. The role of human capital in energy-growth nexus: an international evidence. Empir Econ 58, 1225–1247 (2020). https://doi.org/10.1007/s00181-018-1559-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00181-018-1559-8

Keywords

JEL Classification

Search

Navigation