Skip to main content

Advertisement

SpringerLink
Log in

Does energy aid improve energy efficiency in developing countries?

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

The study examines the effect of energy aid on the energy efficiency of 70 developing countries in the period 1990–2016. We consider two-stage least squares identification strategy to examine the energy aid-energy efficiency nexus empirically. Energy aid is instrumented by similar voting preferences between donors and recipient countries in the United Nations General Assembly. Our finding suggests that energy aid has a significant positive effect on the energy efficiency of aid recipient countries. The result is robust with different sensitivity checks, such as using alternative measures of energy efficiency, alternative measures of energy aid, alternative estimation methods, and dropping outliers.

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

Similar content being viewed by others

Notes

  1. Other noteworthy studies that look at specific channels of foreign aid are McPherson and Rakovski (2001) and Gomanee et al. (2002). They apply a multi-equation system model to find that aid influences economic growth through the investment channel.

  2. Source AidData database. Link: http://aiddata.org/.

  3. It is common to use this scaling procedure in the aid effectiveness literature (e.g. see Wilson 2011; d’Aiglepierre and Wagner 2013). Further, following Arndt et al. (2010), we treat zero-valued aid observations as zeroes, rather than missing.

  4. This paper uses only bilaterally committed energy aid which is coded as 230 on the AidData database. The reason we use only bilaterally committed energy aid is that the affinity index (an instrument used for energy aid) has a direct effect on bilateral energy aid but not on multilateral energy aid. However, in other unreported results, we regress overall energy aid (i.e. bilaterally plus multilaterally committed energy aid) on energy efficiency using OLS and GMM empirical strategies. The results are qualitatively similar to the baseline results. The results are available upon request.

  5. We have followed Belke et al. (2011) and Beckmann et al. (2014) to empirically test the presence of reverse causality between energy efficiency and energy aid using a panel cointegration approach. The causality tests show the presence of a bi-directional causal relationship between energy efficiency and energy aid. We do not report the panel cointegration results due to paucity of space. However, the results are available upon request.

  6. We also run the model using fixed effect and random effect estimations, and the results are qualitatively similar to the OLS findings (results are available upon request).

  7. In other unreported results, we have conducted various linearity and nonlinearity tests (e.g. logistic and exponential transition functions) following Beckmann et al. (2014) before we consider a linear relationship between energy efficiency and energy aid as our preferred specification. The results show that the hypothesis of linearity is not rejected.

  8. Using the lag values of foreign aid is well accepted in the literature (e.g. Mishra and Newhouse 2009). We regress energy efficiency on different lagged values of energy aid and find qualitatively similar results with the baseline findings (see robustness check in Sect. 5).

  9. It is important to mention that the time fixed effect term captures, among other things, the effect of structural breaks that can potentially arise when the number of periods is relatively large. Similarly, Westerlund (2006) suggests that the probability of a structural break in the cointegration relation increases with the length of the time-series dimension of the panel. Hence, we have performed a unit root test by considering endogenous structural breaks Zivot–Andrews and Clemente–Montañés–Reyes tests for energy efficiency and energy aid, and the results show that most of the countries reject the null hypothesis of the unit root for both variables. The results for these tests are available upon request.

  10. It is important to note that Dalgaard et al. (2004) and Djankov et al. (2008) examine the impact of overall aid on growth.

  11. The presence of aid elements in the error term of Eq. (1) may violate one of the Gauss–Markov assumptions, such as the expected value of the aid variable and the error term may not be zero, and thereby create an endogeneity issue (see Cragg and Donald 1993).

  12. We also run regressions using the affinity index of other bilateral donors including Australia, France, Germany, Italy, Japan, Korea, Netherlands, Norway, Spain and Sweden as instrumental variables of energy aid, and the results are qualitatively similar to the results reported in column 3 of Table 2 (results available upon request). However, it is worth noting that these donors have much missing data on the affinity index, as compared to USA, Canada, UK and China, which may potentially lead to ambiguous conclusions. Therefore, our analysis mainly focuses on the findings obtained from the use of the affinity indices of USA, Canada, UK and China as instruments of the aid variable.

  13. “Appendix” shows the amount of energy aid provided by the largest bilateral donors.

  14. The outliers are treated using Hadi (1992) procedures.

  15. It is important to mention that aid targeted to power generation may not exert a potential effect on energy efficiency as its main purpose is related to energy generation rather than energy consumption. However, descriptions of project activities provide some evidence that power generation aid is also allocated for promoting energy efficiency. For example, Uganda has received $US 28.402 million aid capital targeted to assisting technical managers for energy-efficient stoves concentrates on implementing and securing standards and quality regarding the production process, to increase efficient and environmentally sustainable energy supply and to promote renewable energies and energy efficiency. This evidence can be taken as one of the reasons for obtaining a positive and significant effect of power generation aid on energy efficiency in the recipient countries.

  16. In other unreported results, we also examine the effect of both energy research and development and power generation aid on fossil fuel energy consumption (% of total). The results are qualitatively similar to the findings reported in Table 3 and available upon request.

  17. In other unreported results, we have used alternative measures of the disaggregated forms of energy aid (energy research and development and power generation aid) and then examined their effects on energy efficiency. The findings are qualitatively similar to those reported in Table 3 and available upon request.

  18. In other unreported results, we checked this relationship by taking a 5-year lag of energy aid and the results are qualitatively similar.

References

  • Alesina A, Dollar D (2000) Who gives foreign aid to whom and why? J Econ Growth 5(1):33–63

    Article  Google Scholar 

  • Arellano M, Bond S (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev Econ Stud 58(2):277–297

    Article  Google Scholar 

  • Arndt C, Jones S, Tarp F (2010) Aid, growth, and development: have we come full circle? J Glob Dev 1(2):1–29

    Google Scholar 

  • Beckmann J, Belke A, Czudaj R (2014) Regime-dependent adjustment in energy spot and futures markets. Econ Model 40:400–409

    Article  Google Scholar 

  • Belke A, Dobnik F, Dreger C (2011) Energy consumption and economic growth: new insights into the cointegration relationship. Energy Econ 33(5):782–789

    Article  Google Scholar 

  • Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econom 87(1):115–143

    Article  Google Scholar 

  • Brenton P, von Uexkull E (2015) Product specific technical assistance for exports–has it been effective?. In: International trade, distribution and development: empirical studies of trade policies, pp 373–392

  • Burnside C, Dollar D (2000) Aid, policies, and growth. Am Econ Rev 90(4):847–868

    Article  Google Scholar 

  • Clemens MA, Radelet S, Bhavnani RR, Bazzi S (2012) Counting chickens when they hatch: timing and the effects of aid on growth. Econ J 122(561):590–617

    Article  Google Scholar 

  • Collier P, Dollar D (2003) Aid allocation and poverty reduction. Eur Econ Rev 46(8):1475–1500

    Article  Google Scholar 

  • Cragg JG, Donald SG (1993) Testing identifiability and specification in instrumental variable models. Econom Theory 9(2):222–240

    Article  Google Scholar 

  • d’Aiglepierre R, Wagner L (2013) Aid and universal primary education. Econ Educ Rev 37:95–112

    Article  Google Scholar 

  • Dalgaard CJ, Hansen H, Tarp F (2004) On the empirics of foreign aid and growth. Econ J 114(496):F191–F216

    Article  Google Scholar 

  • Djankov S, Montalvo JG, Reynal-Querol M (2008) The curse of aid. J Econ Growth 13:169–194

    Article  Google Scholar 

  • Dreher A, Nunnenkamp P, Thiele R (2008) Does aid for education educate children? Evidence from panel data. World Bank Econ Rev 22(2):291–314

    Article  Google Scholar 

  • Gartzke E (2009). The affinity of nations index, 1946–2002, version 4.0 and related documents. http://dss.ucsd.edu/~egartzke/htmlpages/data.html. Accessed 30 Oct 2018

  • Gillingham K, Newell RG, Palmer K (2009) Energy efficiency economics and policy. Annu Rev Resour Econ 1(1):597–620

    Article  Google Scholar 

  • Gomanee K, Girma S, Morrissey O (2002) Aid, investment and growth in sub-Saharan Africa. In: Paper prepared for the 10th general conference of EADI, Ljubljana

  • Guillaumont P, Chauvet L (2001) Aid and performance: a reassessment. J Dev Stud 37(6):66–92

    Article  Google Scholar 

  • Hadi AS (1992) Identifying multiple outliers in multivariate data. J Roy Stat Soc Ser B (Methodol) 54(3):761–771

    Google Scholar 

  • Hansen H, Tarp F (2001) Aid and growth regressions. J Dev Econ 64(2):547–570

    Article  Google Scholar 

  • Harvey D (2010) Social justice and the city, vol 1. University of Georgia Press, Athens

    Google Scholar 

  • Janulis P (2004) Reduction of energy consumption in biodiesel fuel life cycle. Renew Energy 29(6):861–871

    Article  Google Scholar 

  • Kees M, Feldmann L (2011) The role of donor organisations in promoting energy efficient cook stoves. Energy Policy 39(12):7595–7599

    Article  Google Scholar 

  • Kiernan B (2003) The demography of genocide in Southeast Asia: the death tolls in Cambodia, 1975–79, and East Timor, 1975–80. Crit Asian Stud 35(4):585–597

    Article  Google Scholar 

  • Knack S, Keefer P (1995) Institutions and economic performance: cross-country tests using alternative institutional measures. Econ Politics 7(3):207–227

    Article  Google Scholar 

  • Lee LF (2007) GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. J Econom 137(2):489–514

    Article  Google Scholar 

  • McPherson MF, Rakovski T (2001). Understanding the growth process in sub-Saharan Africa: some empirical estimates. In: African economic policy discussion paper. Harvard University, Cambridge, MA

  • Middleton N, O’keefe P (2006) Politics, history and problems of humanitarian assistance in Sudan. Rev Afr Political Econ 33(109):543–559

    Article  Google Scholar 

  • Mishra P, Newhouse D (2009) Does health aid matter? J Health Econ 28(4):855–872

    Article  Google Scholar 

  • Pacheco R, Ordóñez J, Martínez G (2012) Energy efficient design of building: a review. Renew Sustain Energy Rev 16(6):3559–3573

    Article  Google Scholar 

  • Rajan RG, Subramanian A (2008) Aid and growth: what does the cross-country evidence really show? Rev Econ Stat 90(4):643–665

    Article  Google Scholar 

  • Roodman D (2004) The anarchy of numbers: aid, development, and cross-country empirics. Center for Global Development working paper no. 32

  • Roodman D (2009) A note on the theme of too many instruments. Oxf Bull Econ Stat 71(1):135–158

    Article  Google Scholar 

  • Shahbaz M, Zakaria M, Shahzad SJH, Mahalik MK (2018) The energy consumption and economic growth nexus in top ten energy-consuming countries: fresh evidence from using the quantile-on-quantile approach. Energy Econ 71:282–301

    Article  Google Scholar 

  • Strange A, Park B, Tierney MJ, Fuchs A, Dreher A, Ramachandran V (2013) China’s development finance to Africa: a media-based approach to data collection. Center for Global Development working paper no. 323

  • Tierney MJ, Nielson DL, Hawkins DG, Roberts JT, Findley MG, Powers RM, Parks B, Wilson SE, Hicks RL (2011) More dollars than sense: refining our knowledge of development finance using AidData. World Dev 39(11):1891–1906

    Article  Google Scholar 

  • Toman MA, Jemelkova B (2003) Energy and economic development: an assessment of the state of knowledge. Energy J 24(4):93–112

    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 

  • Wilkinson P, Smith KR, Beevers S, Tonne C, Oreszczyn T (2007) Energy, energy efficiency, and the built environment. Lancet 370(9593):1175–1187

    Article  Google Scholar 

  • Wilson SE (2011) Chasing success: health sector aid and mortality. World Dev 39(11):2032–2043

    Article  Google Scholar 

  • Winkler H, Simões AF, La Rovere EL, Alam M, Rahman A, Mwakasonda S (2011) Access and affordability of electricity in developing countries. World Dev 39(6):1037–1050

    Article  Google Scholar 

Download references

Acknowledgements

We are thankful to the associate editor and two anonymous referees for providing insightful comments in earlier drafts of the paper.

Author information

Authors and Affiliations

  1. Centre for Applied Finance and Economics, Business School, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia

    Admasu Asfaw Maruta & Rajabrata Banerjee

Authors
  1. Admasu Asfaw Maruta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rajabrata Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Admasu Asfaw Maruta.

Ethics declarations

Conflict of interest

We have no conflict of interest to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Total committed energy aid from largest donors: 1990–2016

Appendix: Total committed energy aid from largest donors: 1990–2016

Donor

Total committed energy aid (constant $US 2010)

Australia

2,045,000

Canada

29,100,088

France

19,000,000

Germany

18,200,000

Italy

7,902,100

Japan

10,220,000

Korea

1,233,145

Netherlands

8,580,200

Norway

5,875,500

Spain

6,874,000

Sweden

7,810,000

UK

40,635,000

USA

35,021,000

China

943,180,160

  1. Source: AidData database

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maruta, A.A., Banerjee, R. Does energy aid improve energy efficiency in developing countries?. Empir Econ 61, 355–388 (2021). https://doi.org/10.1007/s00181-020-01854-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00181-020-01854-y

Keywords

JEL Classification

Search

Navigation