The influence of energy consumption and democratic institutions on output and CO2 emissions in Bangladesh: a time–frequency approach


This paper reports the results of a study that investigates the causal interactions among the entities energy consumption, democracy, income, and CO2 emissions in Bangladesh. Bootstrapping causality and time–frequency domain causality methods were adopted to examine the causal co-movements between the variables, using data series for a period of more than four decades. Results show that time-scale behavior plays an important role. Democracy is an important factor for emissions and national income. The nexus of democracy and CO2 emission is bidirectional. The impact of democracy on CO2 is stronger than vice versa. This study provides new insights for policymakers: democratic practices play an important role in implementing climate change policies, at least in the case of Bangladesh.

This is a preview of subscription content, access via your institution.

Fig. 1

Source: All time series are collected from WDI on-line database (World Bank), except Democracy data collected from Freedom House. Sample period: 1972–2010

Fig. 2
Fig. 3

Source: Data for GDP: log of Real GDP (Gross Domestic Product) per capita, CO2: Log of Carbon dioxide emission per capita, Energy: log of energy use (KWh) per capita, are collected from WDI on-line database (World Bank), except Democracy data collected from Freedom House. Sample period: 1972–2010


  1. 1.

    Government of the People’s Republic of Bangladesh: National Adaptation Programme of Action [19].

  2. 2.

    World Development Indicator, World Bank. Summary statistics is available on request.

  3. 3.

    Bangladesh Development Initiative [2].

  4. 4.

    The application of this approach provides accurate inference in the presence of the ARCH effects, and the goal of the VAR model is to conduct ex ante inference.

  5. 5.

    The optimal lag order k is determined by minimizing an information criterion suggested by Hatemi-J [26].

  6. 6.

    Where \( \beta = vec(D) \) and vec is the column-stacking operator; the notation ⊗ represents the Kronecker product and C is a (p×n)(1 + p×n) indicator matrix with elements consisting of ones and zeros. The unrestricted VAR model, denoted by SU, is defined as \( {\mathbf{S}}_{U} = \frac{{\hat{\varepsilon }_{U}^{{\prime }} \hat{\varepsilon }_{U} }}{T - b} \), where b is the number of estimated parameters and the Wald statistic follows a χ2 distribution asymptotically with p degrees of freedom.

  7. 7.

    See Bekiros and Marcellino [3] for details.

  8. 8.

    For I(1) variables see Breitung and Candelon [5].


  1. 1.

    Arrow, K., Bolin, B., Costanza, R., Dasgupta, P., Folke, C., Holling, C.S., Jansson, B., Levin, S., Mäler, K., Perings, C., Pimentel, D.: Economic growth, carrying capacity, and the environment. Ecol. Econ. 15, 91–95 (1995)

    Article  Google Scholar 

  2. 2.

    Bangladesh Development Initiative, six-point policy—priorities for Bangladesh: 2009–2013, (2009). Accessed 30 Apr 2015

  3. 3.

    Bekiros, S., Marcellino, M.: The multiscale causal dynamics of foreign exchange markets. J. Int. Money Finance 33, 282–305 (2013)

    Article  Google Scholar 

  4. 4.

    Bernauer, T., Koubi, V.: Effects of political institutions on air quality. Ecol. Econ. 68(5), 1355–1365 (2009)

    Article  Google Scholar 

  5. 5.

    Breitung, J., Candelon, B.: Testing for short and long-run causality: a frequency domain approach. J. Econom. 132, 363–378 (2006)

    MathSciNet  Article  Google Scholar 

  6. 6.

    Chadwick, B.P.: Fisheries, sovereignties and red herrings. J. Int. Αffairs 48(2), 559–584 (1995)

    Google Scholar 

  7. 7.

    Dasgupta, P., Mäler, K.-G.: Poverty, institutions and the environmental resource-base. In: Behrman, J., Srinivaan, T.N. (eds.) Handbook of development economics, vol. 3A. Elsevier Science, Amsterdam (1995)

    Google Scholar 

  8. 8.

    Deacon, R.: The political economy of environment-development relationships: a preliminary framework. FEEM Working Paper No. 3.00. (2000)

  9. 9.

    Desai, U.: Environment, economic growth, and government. In: Desai, U. (ed.) Ecological policy and politics in developing countries. State University of New York Press, Albany (1998)

    Google Scholar 

  10. 10.

    Dickey, D.A., Fuller, W.A.: Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 1057–1072 (1981)

    MathSciNet  Article  Google Scholar 

  11. 11.

    Farzin, Y.H., Bond, C.A.: Democracy and environmental quality. J. Dev. Εcon. 81(1), 213–235 (2006)

    Article  Google Scholar 

  12. 12.

    Finance Division. Bangladesh economic review. Annual Review. Ministry of Finance, Bangladesh Government. (2016). Accessed 29 Jul 2017

  13. 13.

    Fredriksson, P.G., Neumayer, E.: Democracy and climate change policies: is history important? Ecol. Econ. 95, 11–19 (2013)

    Article  Google Scholar 

  14. 14.

    Fredriksson, P.G., Neumayer, E., Damania, R., Gates, S.: Environmentalism, democracy, and pollution control. J. Environ. Econ. Manag. 49(2), 343–365 (2005)

    Article  Google Scholar 

  15. 15.

    Freedom House: Freedom in the world. (2011)

  16. 16.

    Geweke, J.: Measurement of linear dependence and feedback between multiple time series. J. Am. Stat. Assoc. 77, 304–324 (1982)

    MathSciNet  Article  Google Scholar 

  17. 17.

    Goel, K., Herrala, R., Mazhar, U.: Institutional quality and environmental pollution: MENA countries versus the rest of the world. Econ. Syst. 37(4), 508–521 (2013)

    Article  Google Scholar 

  18. 18.

    Government of the People’s Republic of Bangladesh: National Adaptation Programme of Action (NAPA). (2005). Accessed 10 Aug 2017

  19. 19.

    Granger, C.W.J.: Investigation causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438 (1969)

    Article  Google Scholar 

  20. 20.

    Green Alliance: Paris (2015)—getting a global agreement on climate change (2014)

  21. 21.

    Gronwald, M.: Reconsidering the macroeconomics of the oil price in Germany: a testing for causality in the frequency domain. Empir. Econ. 36, 441–453 (2009)

    Article  Google Scholar 

  22. 22.

    Grossman, M., Krueger, A.: Economic growth and the environment. Q J Econ 110(2), 353–377 (1995)

    Article  Google Scholar 

  23. 23.

    Hacker, R.S., Hatemi-J, A.: Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application. Appl. Econ. 38, 1489–1500 (2006)

    Article  Google Scholar 

  24. 24.

    Hatemi, J.A., Uddin, G.S.: Is the causal nexus of energy utilization and economic growth asymmetric in the US? Econ. Syst. 36(3), 461–469 (2012)

    Article  Google Scholar 

  25. 25.

    Hatemi-J, A.: A new method to choose optimal lag order in stable and unstable VAR models. Appl. Econ. Lett. 10, 135–137 (2003)

    Article  Google Scholar 

  26. 26.

    Heerink, N., Mulatu, A., Bulte, E.: Income inequality and the environment: aggregation bias in environmental Kuznets curves. Ecol. Econ. 38(2), 359–367 (2001)

    Article  Google Scholar 

  27. 27.

    Houghton, J.T., Callander, B.A., Varney, S.K.: Climate change 1992. Cambridge University Press, Cambridge (1992)

    Google Scholar 

  28. 28.

    Intergovernmental Panel on Climate Change: Working Group III Report: Mitigation of Climate Change. (2007)

  29. 29.

    IPCC: Climate Change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. In: Field, C.B., Barros, V.R. (eds.) Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change, pp. 1–32. Cambridge University Press, New York (2014)

    Google Scholar 

  30. 30.

    Johansen, S.: Likelihood-Based Inference in Cointegrated Vector Auto-regressive Models. Oxford University Press Inc., New York (1995)

    Google Scholar 

  31. 31.

    Kuznets, S.: Economic growth and income inequality. Am. Econ. Rev. 45, 1–28 (1955)

    Google Scholar 

  32. 32.

    Lau, L.-S., Choong, C.-K., Eng, Y.-K.: Carbon dioxide emission, institutional quality, and economic growth: empirical evidence in Malaysia. Renew. Energy 68, 276–281 (2014)

    Article  Google Scholar 

  33. 33.

    MacKinnon, J.G., Haug, A.A., Michelis, L: Numerical distribution functions of likelihood ratio tests for cointegration. J. Appl. Econometrics. 14, 563–577 (1999)

    Article  Google Scholar 

  34. 34.

    Midlarsky, M.I.: Democracy and the environment: an empirical assessment. J. Peace Res. 35(3), 341–361 (1998)

    Article  Google Scholar 

  35. 35.

    Neumayer, E.: Do democracies exhibit stronger international environmental commitment? A cross-country analysis. J. Peace Res. 39(2), 139–164 (2002)

    Article  Google Scholar 

  36. 36.

    Olson, M.: Dictatorship, democracy and development. Am. Polit. Sci. Rev. 87(3), 567–576 (1993)

    Article  Google Scholar 

  37. 37.

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

    Article  Google Scholar 

  38. 38.

    Pachauri, R.K., Allen, M.R., Barros, V.R., Broome, J., Cramer, W., Christ, R., Dubash, N.K.: Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change, IPCC, p. 151 (2014)

  39. 39.

    Panayotou, T.: Demystifying the environmental Kuznets curve: turning a black box into a policy tool. Environ. Dev. Econ. 2, 465–484 (1997)

    Article  Google Scholar 

  40. 40.

    Payne, R.A.: Freedom and the environment. J. Democr. 6(3), 41–55 (1995)

    Article  Google Scholar 

  41. 41.

    Phillips, P.C., Perron, P.: Testing for a unit root in time series regression. Biometrika 75, 335–346 (1988)

    MathSciNet  Article  Google Scholar 

  42. 42.

    Roberts, J.T., Parks, B.C.: A climate of injustice: global inequality, north-south politics, and climate policy. MIT Press, Cambridge (2007)

    Google Scholar 

  43. 43.

    Romuald, K.S.: Democratic institutions and environmental quality: effects and transmission channels. In 2011 International congress, August 30–September 2 2011, Zurich, Switzerland (No. 120396), European Association of Agricultural economists (2011)

  44. 44.

    Scruggs, L.A.: Political and economic inequality and the environment. Ecol. Econ. 26(3), 259–275 (1998)

    Article  Google Scholar 

  45. 45.

    The World Bank: Bangladesh: bolstering economic growth to reduce poverty.,,contentMDK:22888421~menuPK:141311~pagePK:34370~piPK:34424~theSitePK:4607,00.html (2015). Accessed 24 Apr 2015

  46. 46.

    Tiwari, A.K.: The asymmetric Granger-causality analysis between energy consumption and income in the United States. Renew. Sustain. Energy Rev. 36, 362–369 (2014)

    Article  Google Scholar 

  47. 47.

    Tiwari, A.K.: The frequency domain causality analysis between energy consumption and income in the United States. Economia Aplicada 18(1), 51–67 (2014)

    Article  Google Scholar 

  48. 48.

    Torras, M., Boyce, J.K.: Income, inequality, and pollution: a reassessment of the environmental Kuznets curve. Ecol. Econ. 25(2), 147–160 (1998)

    Article  Google Scholar 

  49. 49.

    United Nations Development Programme, About Bangladesh, (2015). Accessed 29 Apr 2015

  50. 50.

    Winslow, M.: Is Democracy Good for the Environment? J. Environ. Planning Manage. 48(5), 771–783 (2005)

    Article  Google Scholar 

  51. 51.

    World Bank: Bangladesh—country snapshot. Country Report, World Bank, Washington, D.C. 2016. Accessed 29 Jul 2017

  52. 52.

    World Bank: Bangladesh: ensuring a reliable and quality energy supply. Media report. 2017. Accessed 29 Jul 2017

  53. 53.

    You, W.-H., Zhu, H.-M., Yu, K., Peng, C.: Democracy, financial openness, and global carbon dioxide emissions: heterogeneity across existing emission levels. World Dev. 66, 189–207 (2015)

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Stelios Bekiros.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ahmed, A., Bekiros, S., Rosklint-Lindvall, E. et al. The influence of energy consumption and democratic institutions on output and CO2 emissions in Bangladesh: a time–frequency approach. Energy Syst 11, 195–212 (2020).

Download citation


  • CO2 emissions
  • Climate policy
  • Democracy
  • Time–frequency causality

JEL codes

  • G1
  • G15