How energy consumption is related to agricultural growth and export: An econometric analysis on Iranian data

Koondhar

et al. 2021

Environ Sci Pollut Res

This study aims to contribute to the literature and examine the causal relationship between Pakistan’s agricultural products export, industrialization, urbanization, transportation, energy consumption, and carbon emissions. For the last four decades, time-series data were used to employ short-run and long-run nexus between the selected variables by analyzing the autoregressive distributed lag model (ARDL). The Granger causality test was analyzed to estimate the causality directions. The unit root test results indicate that all the selected variables are stationary at the level and first difference. The bound test confirmed that all variables are cointegrated at a 1% significance level. Long-run estimates suggest that an increase in energy consumption will increase the export of agricultural products. An increase in urbanization, transportation, and carbon emission resulted in a decrease in agricultural products export in Pakistan. In the short run, an increase in industrialization, transportation, and energy consumption leads to an increase in agricultural products export. Increasing urbanization and carbon emission decrease the agricultural products export of Pakistan. Based on our findings, we recommend sustainable agricultural production, renewable energy consumption, low carbon emission technologies, and a green portfolio for sustainable agricultural products export.

Section: Resultssupporting

confidence: 88%

Dynamic linkage between industrialization, energy consumption, carbon emission, and agricultural products export of Pakistan: an ARDL approach

Koondhar

et al. 2021

Environ Sci Pollut Res

“…Many studies have quantified the energy use and GHG emissions in agriculture and specifically, in wheat production, e.g., energy use and efficiency evaluation in wheat production in China [20], energy auditing in different cropping systems in India [3,15,[29][30][31][32][33][34][35][36], energy analyses and GHG emissions from different crops in Iran [37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53], assessment of on-farm energy use and GHG emissions from wheat in New Zealand [1,18,54,55], analyses of agricultural energy in Bangladesh [56], energy input-output analysis in Turkey for production of cotton, vegetables, grapes, sugar beet and dry apricot [17,[57][58][59][60][61][62][63], effect of fertilizer management on GHG emissions in agriculture [64], energy and economic analyses for different vegetables in Indonesia [65] and estimation of energy use and CO 2 emissions in Thailand [66...…”

Section: Introductionmentioning

confidence: 99%

Investigation of Input and Output Energy for Wheat Production: A Comprehensive Study for Tehsil Mailsi (Pakistan)

et al. 2020

The global increasing food demand can be met by efficient energy utilization in mechanized agricultural productions. In this study, input–output energy flow along with CO2 emissions for different wheat production cases (C-I to C-V) were investigated to identify the one that is most energy-efficient and environment-friendly case. Data and information about input and output sources were collected from farmers through questionnaires and face-to-face interviews. Input and output sources were converted into energy units by energy equivalents while CO2 emissions were calculated by emission equivalents. Data envelopment analysis (DEA) was conducted to compare technical efficiencies of the developed cases for optimization of inputs in inefficient cases. Results revealed that case C-Ⅴ (higher inputs, larger fields, the tendency of higher fertilizer application and tillage operations) has the highest energy inputs and outputs than the rest of the cases. Moreover, it possesses the lowest energy use efficiency and energy productivity. The highest CO2 emissions (1548 kg-CO2/ha) referred to C-Ⅴ while lowest emissions per ton of grain yield were determined in C-Ⅳ (higher electricity water pumping, moderate energy input). The grain yield increases directly with input energy in most of the cases, but it does not guarantee the highest values for energy indices. C-Ⅲ (moderate irrigations, educated farmers, various fertilizer applications) was found as an optimum case because of higher energy indices like energy use efficiency of 4.4 and energy productivity of 153.94 kg/GJ. Optimum input and better management practices may enhance energy proficiency and limit the traditionally uncontrolled CO2 emissions from wheat production. Therefore, the agricultural practices performed in C-Ⅲ are recommended for efficient cultivation of wheat in the studied area.

“…In the case of existence of longrun association, the short-run dynamics can be related to long-run stable relationship via vectorerror-correction model (VECM). This model has a very important policy making implication as it reveals how the impact of a shock would be corrected as time passes [13,6,7,8,11,12,15].…”

Section: Econometric Techniquesmentioning

confidence: 99%

“…Energy is categorized among the essential drivers of global development in general and developing nations' economic growth in particular [19,13,30,31,32]. Some ecological economists believe that in the biophysical growth model, energy acts as the most influential factor [27,23,24,26,27,29].…”

Section: Introductionmentioning

confidence: 99%

How Globalization Is Related to Energy Productivity? (A Mathematical Analysis on Iran’s Agricultural Data)

Ghasemi

Moghaddasi

Zeraatkish

2020

ijaa

Agriculture is recognized as a key economic sector for almost all developing nations including Iran. Nowadays, world economy has been highly integrated as economic performance of a given country is more susceptible to policies taken by other countries than four decades ago. So, investigating the possible impacts of this new worldwide phenomenon (globalization) would be a vital issue. This paper is an empirical examination of the association between globalization and energy productivity in the Iran's agriculture context by using time series econometrics techniques including causality and cointegration tests for the period 1967-2018. Main results confirm existence of a unidirectional causality from globalization to agricultural energy productivity. Other findings revealed that every one percent increase in globalization index is expected to lead in 0.75 percent rise in agricultural energy productivity in the long-run. The error correction coefficient is estimated at-0.25 implying that the effect of every shock imposed on the long-run equation would be vanished in just four years.