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<p>Rice cultivation is an important source of agricultural methane emissions, and country-level monitoring is needed to evaluate how emission pressure evolves together with rice-sector production and market conditions. This study provides an exploratory dynamic monitoring assessment of methane emissions in Indonesia, the Philippines, and Viet Nam over the period 2000–2023. Annual data from FAOSTAT were used to examine methane emissions, methane emission intensity, rice production indicators, producer prices, and Food CPI. Long-term trends were evaluated using the Mann–Kendall test and Sen’s slope estimator. Dynamic associations were assessed using a parsimonious panel vector autoregression, with unit-root and residual-based cointegration diagnostics, first-difference robustness analysis, alternative Cholesky orderings, generalized impulse responses, and residual-bootstrap confidence intervals. The trend results reveal heterogeneous methane-emission trajectories across the three countries. Methane emissions declined significantly in Indonesia, increased significantly in the Philippines, and showed no statistically significant trend in Viet Nam. In contrast, methane emission intensity declined in all three countries, indicating that total emissions and intensity-based performance may move in different directions. The revised PVAR(1) results suggest that methane-emission responses are statistically associated with selected agricultural and price-related innovations, particularly producer-price innovations under the baseline recursive ordering. However, first-difference results show that many responses are concentrated in the short run, and FEVD results are sensitive to identification assumptions. Generalized impulse response-based decomposition indicates that methane-emission variability is primarily own-driven under ordering-invariant assumptions. Overall, the findings support a cautious monitoring interpretation. Rice-sector methane assessment should track both total emissions and emission intensity while considering production scale, harvested area, and dynamic adjustment patterns. The study provides exploratory evidence for three rice-producing countries and highlights the importance of transparent data construction, parsimonious modelling, and robustness checks when using aggregate country-level data to assess methane-emission dynamics.</p>

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Dynamic assessment of methane emission trends and rice-sector adjustment in three Southeast Asian countries

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • Yi-Chia Lin,
  • Sheng-Yao Huang

摘要

Rice cultivation is an important source of agricultural methane emissions, and country-level monitoring is needed to evaluate how emission pressure evolves together with rice-sector production and market conditions. This study provides an exploratory dynamic monitoring assessment of methane emissions in Indonesia, the Philippines, and Viet Nam over the period 2000–2023. Annual data from FAOSTAT were used to examine methane emissions, methane emission intensity, rice production indicators, producer prices, and Food CPI. Long-term trends were evaluated using the Mann–Kendall test and Sen’s slope estimator. Dynamic associations were assessed using a parsimonious panel vector autoregression, with unit-root and residual-based cointegration diagnostics, first-difference robustness analysis, alternative Cholesky orderings, generalized impulse responses, and residual-bootstrap confidence intervals. The trend results reveal heterogeneous methane-emission trajectories across the three countries. Methane emissions declined significantly in Indonesia, increased significantly in the Philippines, and showed no statistically significant trend in Viet Nam. In contrast, methane emission intensity declined in all three countries, indicating that total emissions and intensity-based performance may move in different directions. The revised PVAR(1) results suggest that methane-emission responses are statistically associated with selected agricultural and price-related innovations, particularly producer-price innovations under the baseline recursive ordering. However, first-difference results show that many responses are concentrated in the short run, and FEVD results are sensitive to identification assumptions. Generalized impulse response-based decomposition indicates that methane-emission variability is primarily own-driven under ordering-invariant assumptions. Overall, the findings support a cautious monitoring interpretation. Rice-sector methane assessment should track both total emissions and emission intensity while considering production scale, harvested area, and dynamic adjustment patterns. The study provides exploratory evidence for three rice-producing countries and highlights the importance of transparent data construction, parsimonious modelling, and robustness checks when using aggregate country-level data to assess methane-emission dynamics.