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Article

Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach

1
College of Economics, Sichuan Agricultural University, Chengdu 611130, China
2
School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
3
School of Economics, Lanzhou University, Lanzhou 730000, China
4
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
5
School of Economics and Management, Southeast University, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(13), 5241; https://doi.org/10.3390/su12135241
Submission received: 30 April 2020 / Revised: 15 June 2020 / Accepted: 15 June 2020 / Published: 28 June 2020

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.
Keywords: agricultural production; formal credit; CO2 emissions; ARDL approach; Pakistan agricultural production; formal credit; CO2 emissions; ARDL approach; Pakistan

Share and Cite

MDPI and ACS Style

Chandio, A.A.; Jiang, Y.; Rauf, A.; Ahmad, F.; Amin, W.; Shehzad, K. Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach. Sustainability 2020, 12, 5241. https://doi.org/10.3390/su12135241

AMA Style

Chandio AA, Jiang Y, Rauf A, Ahmad F, Amin W, Shehzad K. Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach. Sustainability. 2020; 12(13):5241. https://doi.org/10.3390/su12135241

Chicago/Turabian Style

Chandio, Abbas Ali, Yuansheng Jiang, Abdul Rauf, Fayyaz Ahmad, Waqas Amin, and Khurram Shehzad. 2020. "Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach" Sustainability 12, no. 13: 5241. https://doi.org/10.3390/su12135241

APA Style

Chandio, A. A., Jiang, Y., Rauf, A., Ahmad, F., Amin, W., & Shehzad, K. (2020). Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach. Sustainability, 12(13), 5241. https://doi.org/10.3390/su12135241

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