Abstract
This study estimates the potential effects of climate change on GDP in the agriculture sector in the ASEAN region based on historic data from 1995-2018. An econometric panel model is applied to examine the impact of the changing climatic and non-climate variables AGDP. The empirical estimation results show that some significant and insignificant. Based on estimation results, if the policymaker is concerned about climate change actions, it helps more comprehensive risk decision-making, and policy exertions should be concentrated toward climate change to the total gross domestic product in the ASEAN region. Under projections of the future climate change, the simulation results reveal that the substantial change in GDP in agriculture in the ASEAN region arises due to the fluctuation of temperature and precipitation. For instance, GDP in the agriculture sector would be decreased by 0.27% to 0.90% in response to different scenarios over the century. Therefore, it is necessary to take immediate adaptive actions appropriately to mitigate the decrease in GDP in the agriculture sector in the ASEAN region.
Highlights
The cumulative effects of global climate change depend on how the world responds to increasing emissions (Bhuyar et al, 2019; Saengsawang et al, 2020)
Metadata: future climate information is derived from 35 available global circulation models (GCMs) used by the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report
We investigate the effects of climate change on GDP in the agriculture sector in the ASEAN region includes: Cambodia, Lao PDR, Myanmar, Vietnam, Thailand, Malaysia and, the Philippines, providing helpful information for effect to sustain GDP in the agriculture sector in the future
Summary
The cumulative effects of global climate change depend on how the world responds to increasing emissions (Bhuyar et al, 2019; Saengsawang et al, 2020). Given its computational complexity, computable general equilibrium (CGE) modelling has primarily concentrated on individual country effects or dynamic models with limited numbers of countries or regions and an absence of forward-looking behaviour, that is, so-called recursive dynamic models with static or adaptive price-level forecasts. These recursive dynamic models have value, but the assumption that future price-level expectations are based only on current and past values is broadly incongruent with known future projections of various climate change outcomes and resulting trade effects (Kompas and Van Ha, 2019). The effects of climate change and environmental variation are mainly estimated by the number of stress spells, their impact on daily life, and damage to agriculture crops (UNICEF and Organization, 2017)
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