Abstract
This study attempts to investigate the short-run and long-run impact of formal credit (CR) and climate change (CC, via CO2 emissions) on agricultural production (AP) in Pakistan. In addition, other imperative control variables included in this study comprise technology factors (tractors (TRs) and tube wells (TWs), energy consumption (EC), and labor force (LF). This study used annual data covering the period 1983–2016. The autoregressive distributed lag (ARDL) approach is applied to explore the cointegration between the underlying variables and used the granger causality test under the vector error correction model (VECM) context to determine the direction of causality among the variables. The findings of the ARDL bounds-testing approach suggest that there is a long-term relationship among formal credit, climate change (CO2 emissions), technology factors (tractors and tube wells), energy consumption, labor force, and agricultural production. The empirical results reveal that formal credit, technology use (tractors), and labor force have a positive and significant impact on agricultural production in both the short-run and long-run. CO2 emissions have a positive impact on agricultural production but are not significant in either case. Finally, a unidirectional relationship is established from formal credit to agricultural production; labor force to agricultural production; and electricity consumption and technology factors (tractors and tube wells) to CO2 emissions. The recent study claims that formal institutions should guarantee the redeployment of their services/amenities to those who call for them acutely, with the purpose of boosting their approach to monetary credit facilities and empower farmers to further the resilience that will capitalize on post-fruitage enrichments. Finally, considering that climatic change is a widespread fact with regional community trajectories, perhaps the global community may provide reassurance for loaning to smallholder agriculturalists through central and commercial banks by protecting the moneys that banks lend to the agriculturalists towards supporting climatic change espousal strategies.
Highlights
The agriculture sector of Pakistan possess a dominant role in its economy, with a contribution to economic growth between 1949 and 1950 of about 60%, a decline of around 30% between 1978 and 1979, and ratio of about 18.5% during 2018–2019
The empirical study carries out the several estimation tests, Equation (1) can be articulated as follows: LNAPt = α0 + α1LNCRt + α2LNTRt + α3LNTWt + α4LNECt + α5LNLFt + α6LNCO2t +εt where LNAPt represents the logarithm function of the agricultural output; LNCRt represents the logarithm function of formal credit; LNTRt represents the logarithm function of the tractors; LNTWt represents the logarithm function of the tube wells; LNECt represents the logarithm function of the consumption of electricity in agricultural sector; LNLFt represents the logarithm function of the laborr force; and LNCO2t represents the logarithm function of the CO2 emissions, respectively
The results of the Autoregressive Distributed Lag (ARDL) bounds-testing approach confirm the presence of long-term cointegration relationships among formal credit, technology factors such as tractors and tube wells, energy consumption, labor force, CO2 emissions and agricultural production over the study period
Summary
The agriculture sector of Pakistan possess a dominant role in its economy, with a contribution to economic growth between 1949 and 1950 of about 60%, a decline of around 30% between 1978 and 1979, and ratio of about 18.5% during 2018–2019. Poverty rates are still high in many developing countries, and climate change might result in poor crop yields and quality, losses of crops and revenue, intensifications in pest attacks, and interruptions in planting periods [16,26]. All these factors add fuel to the fire, causing severe financial and food security issues in the developing world.
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