Economic growth, climate change, and agriculture sector: ARDL bounds testing approach for Bangladesh (1971-2020)

Main Article Content

Ebrima K Ceesay Momodou Mustapha Fanneh


Agriculture, Food security, Climate change, and food import are vital components of an economy. This article empirically explored the long-run and short-run impact of these variables on the economic development of Bangladesh by employing the ARDL model over the period from 1971 to 2020. The outcome of the F-bounds test confirmed the existence of a no long-run relationship among the variables examined, and hence, the appropriate model is ARDL. The study then analysed the short-run impact of agriculture, food security, food import and climate change on economic growth. The short-run and long-run coefficients revealed a positive and significant impact of the agriculture sectors on economic growth in Bangladesh in the short-run and long-run. Findings further showed that climate change and food security have a positive and insignificant impact on economic development. Food import has a negative and insignificant impact on economic growth in the short-run and an insignificant positive impact in the long-run+. Therefore, the study concludes that Bangladesh should invest in the agriculture sector as an engine of economic growth. Climate change, food security and food imports are essential for Bangladesh's economy.

Article Details

How to Cite
CEESAY, Ebrima K; FANNEH, Momodou Mustapha. Economic growth, climate change, and agriculture sector: ARDL bounds testing approach for Bangladesh (1971-2020). Economics, Management and Sustainability, [S.l.], v. 7, n. 1, p. 95-106, may 2022. ISSN 2520-6303. Available at: <>. Date accessed: 29 june 2022. doi:


Alam, K. J., & Sumon, K. K. (2020). Causal relationship between trade openness and economic growth: A panel data analysis of Asian countries. International Journal of Economics and Financial Issues, 10(1), 118.
Alimi, R. S. (2014). ARDL bounds testing approach to cointegration: A re-examination of augmented fisher hypothesis in an open economy. Asian Journal of Economic Modelling, 2(2), 103-114.
Belford, C., Huang, D., Ceesay, E., Ahmed, Y.N., & Jonga, R.H. (2020). Environmental change effects on economic growth: mixed empirical evidence. Int. J. Hum. Cap. Urban Manag. 5, 99–110.
Deitchler, M., Ballard, T., Swindale, A., & Coates, J. (2010). Validation of a measure of household hunger for cross-cultural use. Washington, DC: Food and Nurtrition Technical Assistance II Project (FANTA-2), Acedemy for Educational Development.
de Janvry, A., & Sadoulet, E. (2006). Making conditional cash transfer programs more efficient: Designing for maximum effect of the conditionality. World Bank Economic Review, 20(1), 1–29.
Ceesay, E. K., Francis, P. C., Jawneh, S., Njie, M., Belford, C., & Fanneh, M. M. (2021). Climate change, growth in agriculture value-added, food availability and economic growth nexus in the Gambia: a Granger causality and ARDL modeling approach. SN Business & Economics, 1(7), 1-31.
Ceesay, E. K. (2020). Does Flood Disaster Lessen GDP Growth. Evidence from the Gambia’s Manufacturing and Agricultural Sectors, 11, 404. Monetary Fund. Independent Evaluation Office. (2020). Progress Report to The IMFC On the Activities Of The Independent Evaluation Office Of The IMF. Policy Pap.
Harris, R., & Sollis, R. (2003). Applied time series modelling and forecasting. Wiley.
International Monetary Fund. (2020). Progress report to the IMFC on the activities of the independent evaluation office of the IMF. Policy Papers, 2020(021).
Islam, M. S., Hasif, M. A. M., Ema, N. S., & Jahan, H. (2020). Role of Agriculture and Manufacturing Sectors in the Economic Growth of Bangladesh and India: An ARDL Approach. The Romanian Economic Journal, 78, 89-92.
Mougou, R., Mansour, M., Iglesias, A., Chebbi, R. Z., & Battaglini, A. (2011). Climate change and agricultural vulnerability: a case study of rain-fed wheat in Kairouan, Central Tunisia. Regional Environmental Change, 11(1), 137-142.
Nasrullah, M., Rizwanullah, M., Yu, X., Jo, H., Sohail, M. T., & Liang, L. (2021). Autoregressive distributed lag (ARDL) approach to study the impact of climate change and other factors on rice production in South Korea. Journal of Water and Climate Change, 12(6), 2256-2270.
Ozturk, I., & Acaravci, A. (2010). CO2 emissions, energy consumption and economic growth in Turkey. Renewable and Sustainable Energy Reviews, 14(9), 3220-3225.
Pesaran, M. H., & Shin, Y. (1995). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis (No. 9514). Faculty of Economics, University of Cambridge.
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
Riaz, A., & Rahman, M. S. (Eds.). (2016). Routledge handbook of contemporary Bangladesh. Routledge.
Sarker, M. A. R., Alam, K., & Gow, J. (2019). Performance of rain-fed Aman rice yield in Bangladesh in the presence of climate change. Renewable agriculture and food systems, 34(4), 304-312.
Sarkodie, S. A., Adams, S., Owusu, P. A., Leirvik, T., & Ozturk, I. (2020). Mitigating degradation and emissions in China: the role of environmental sustainability, human capital and renewable energy. Science of the Total Environment, 719, 137530.
Subramaniam, V., & Reed, M. R. (2009). Agricultural inter-sectoral linkages and its contribution to economic growth in the transition countries (No. 1005-2016-79162).
The World Bank Group. (2014). World Development Indicators 2014. Retrieved from