Causal Linkage among Agricultural Insurance, Air Pollution, and Agricultural Green Total Factor Productivity in United States: Pairwise Granger Causality Approach

Nihal Ahmed; Zeeshan Hamid; Farhan Mahboob; Khalil Ur Rehman; Muhammad Sibt E Ali; Piotr Senkus; Aneta Wysokińska-Senkus; Paweł Siemiński; Adam Skrzypek

doi:10.3390/agriculture12091320

Akademii Sztuki Wojennej

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Tytuł

Causal Linkage among Agricultural Insurance, Air Pollution, and Agricultural Green Total Factor Productivity in United States: Pairwise Granger Causality Approach

Autorzy

Nihal Ahmed ^{[ 1 ]}
Zeeshan Hamid ^{[ 2 ]}
Farhan Mahboob ^{[ 3 ]}
Khalil Ur Rehman ^{[ 4 ]}
Muhammad Sibt E Ali ^{[ 5 ]}
Piotr Senkus ^{[ 6 ]}
Aneta Wysokińska-Senkus (WZiD) ^{[ 7 ][ 6.6 ][ P ]}
Paweł Siemiński ^{[ 8 ]}
Adam Skrzypek ^{[ 9 ]}

^{[ 1 ]} College of Economics & Management, Northwest Agricultural & Forestry University, Xianyang 712100, China | ^{[ 2 ]} Department of Management Sciences, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST), Pakistan | ^{[ 3 ]} Department of Finance and Economics, Mohammad Ali Jinnah University, Pakistan | ^{[ 4 ]} Department of Humanities and Social Sciences, Khwaja Fareed University of Engineering and Information Technology, Pakistan | ^{[ 5 ]} School of Business, Zhengzhou University, China | ^{[ 6 ]} Faculty of Social Sciences, Siedlce University of Natural Sciences and Humanities, Poland | ^{[ 7 ]} Instytut Zarządzania, Wydział Zarządzania i Dowodzenia, Akademia Sztuki Wojennej | ^{[ 8 ]} Department of Economics and Economic Polity in Agribusiness, Poznań University of Life Sciences, Poland | ^{[ 9 ]} Institute of Journalism and Management, Faculty of Social Sciences, The John Paul II Catholic University of Lublin, Poland | ^{[ P ]} pracownik

Dyscyplina naukowa (Ustawa 2.0)

[6.6] Nauki o zarządzaniu i jakości

Rok publikacji

2022

Opublikowano w

Agriculture

Rocznik: 2022 | Tom: volume 12 | Numer: issue 9

Typ artykułu

artykuł naukowy

Język publikacji

angielski

Słowa kluczowe

EN

Agricultural green total factor productivity
Agricultural insurance
AGTFP
Air pollution
Panel auto-regressive distributed lags method
United States

PL

Polityka rolna
Rolnictwo ekologiczne
Ubezpieczenia rolnicze
Zanieczyszczenie powietrza
Stany Zjednoczone (USA)

Streszczenie

EN Agricultural insurance and green agriculture are strongly related. Agricultural insurance not only motivates farmers to adopt environmentally friendly production technology and enhances the effectiveness of production, but it also accomplishes the goal of lowering the number of chemicals that are put into the environment. This article investigates the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. To complete the aim, the authors used the panel auto-regressive distributed lags method (PMG method) and panel data from 50 states of the United States between 2005 and 2019. The empirical findings demonstrate a considerable co-integration and a cross-sectional reliance between agricultural insurance, air pollution, and agricultural green total factor production. Expanding agricultural insurance may boost agricultural green whole factor output but also exacerbate air pollution. However, significant air pollution does not increase agricultural production’s green total factor productivity. The panel Granger causality test shows a one-way causal relationship between agricultural insurance, green total factor productivity, and air pollution. A one-way causal relationship exists between air pollution and agricultural green total factor productivity. The author concluded that improving agricultural insurance coverage or cutting down on air pollution will boost agricultural green total factor output. These findings have long-term policy and management repercussions, particularly for those involved in agriculture policy and environmental management.

Data udostępnienia online

26.08.2022

Strony (od-do)

1 - 17

DOI

10.3390/agriculture12091320

URL

https://www.mdpi.com/2077-0472/12/9/1320

Typ licencji

CC BY (uznanie autorstwa)

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