Impact of Climate Change, Agricultural Credit and Inflation on Cereal Crop Productivity in Ethiopia: Novel Dynamic Simulated <scp>ARDL</scp> Approach

Abstract

This study examines the impact of climate change, agricultural credit, and inflation on cereal crop productivity (CCP) in Ethiopia, using time series data from 1992 to 2022. Novel Dynamic Simulated Autoregressive Distributed Lag (NDS-ARDL) model was applied for the empirical analysis. To address the dynamic effects, impulse response functions were simulated, indicating the impact of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:mrow><mml:mo>±</mml:mo> <mml:mn>10</mml:mn></mml:mrow> </mml:mrow> </mml:math> % shocks for each independent variable on CCP. The bound test results show that the variable illustrates long-term relationships. The coefficient of error correction term is -0.67, suggesting about 67% annual adjustment towards long run equilibrium. In the long-run, fertilizer application, cropland, and agricultural subsidy showed positive and significant contributions, while CO₂ and inflation showed a negative and significant impact on CCP. Furthermore, in the short-run, agricultural credit has a positive and significant, while inflation showed a significant negative impact on CCP. To boost long-term agricultural productivity, government should promote use of location-specific quality fertilizers, improved land use policy, and sustain agricultural subsidies. Additionally, financial institution and agricultural cooperatives should provide affordable credit services for farmers to support short-term productivity gains. Furthermore, to combat the adverse impact of CO₂ emissions and inflation, government should promote climate-smart agricultural practices and implement a price control policy on essential agricultural inputs.