Climate change, macroeconomic sensitivity and the response of remittances to the North African countries: a panel VAR analyse

ABSTRACT

This article aims to empirically analyse the role of remittances in alleviating the real GDP oscillations induced by the meteorological variability detected by the average annual changes in precipitation and temperature in the North African countries between 1980 and 2016. We use a vector autoregressive model on panel data (PVAR) in order to allow endogenous interactions between the model variables and to circumvent the problem of a small series size by combining the spatial and temporal dimensions. Our results aim to show on the one hand the negative impact of interannual meteorological variability on real GDP per capita. A slight decrease in the latter but it remains statistically significant by 0.2% and 0.13% during the shocks of precipitation and temperature respectively. This is mainly due to the stability of the climate in the region during the last decades. On the other hand, remittances make a contribution of around 3.7% to fluctuations in GDP. These remittances can be used as a cushion on the macroeconomic stability of countries adversely affected by weather conditions. They are characterized by contracyclical patterns which increase adaptability and resistance to hazards. Therefore, the future policies need to be more rigorously focused on adaptation policies and investing in green technologies that mitigate the negative consequences of annual weather and long-term climate change. These measures will contribute to the achievement of Sustainable Development Goals (SDGs).

KEYWORDS:

• Remittances
• GDP
• Climate Change
• Adaptation
• North Africa
• PVAR model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Using the package of a Stata program provided by Love I. (2001) to estimate a panel VAR. This specification is redeveloped by Love and Zicchino (2006) which uses the Stata code (PVAR), available at https://github.com/gaulinmp/accounting-predictability/blob/master/STATA/pvar.ado

2. These tables contain data from the Penn World Table (PWT), version 10.0 (2021)), available at www.ggdc.net/pwt.

3. For the latest data on migration and remittances, please visit https://www.knomad.org/, World Bank (2020).

4. Climate data are available at https://lr1.uea.ac.uk/cru/data.

Additional information

Funding

This research received no external funding.