Abstract
This research investigated the empirical relationship between meat consumption and greenhouse gas (GHG) emissions in Argentina. The Autoregressive Distributed Lag (ARDL) and Dynamic Ordinary Least Squares (DOLS) techniques were employed to analyze time-series data from 1990 to 2020. The ARDL bound test demonstrates the long-term cointegration of all variables. According to the DOLS model, a 1 % increase in meat consumption increases GHG emissions by 0.91 % over the long term. Moreover, a 1 % increase in economic growth and energy consumption will increase Argentina's GHG emissions by 1.15 % and 1.32 %, respectively. The fully modified least squares (FMOLS) method was used to assess the reliability of the DOLS results. Additionally, the pairwise Granger causality test was employed to assess the causal relationship between the variables. The empirical findings indicate that the Argentine livestock industry can become more environmentally friendly with proper policy formulation and implementation.
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