Abstract
The current empirical study explores the linkage between carbon dioxide (CO2) emissions, average temperature, cultivated area, consumption of fertilizer, and rice production in Pakistan. For this research, the annual time series data from 1968 to 2014 were used to enhance the validity of the empirical outcomes. The cointegration analysis with the auto-regressive distributed lag (ARDL) bounds testing approach is applied to explore the effects of climate change on rice production. Additionally, the estimated long-run outcomes are verified by employing fully modified ordinary least squared (FMOLS) and canonical cointegrating regression (CCR) approaches. The empirical outcomes revealed that the selected important study variables are cointegrated demonstrating the existence of long-run linkages among them. The main fruitful outcomes of this study are that rice production in Pakistan is positively affected by the carbon dioxide (CO2) emissions in both long-run and short-run.
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Abbreviations
- ARDL-bounds test:
-
Autoregressive distributed-lag (ARDL) bounds test
- UCB:
-
Upper critical bound
- LCB:
-
Lower critical bound
- AIC:
-
Akaike information criteria
- SBC:
-
Schwarz Bayesian criteria
- HQC:
-
Hannan-Quinn information criterion
- ECM:
-
Error correction model
- OLS:
-
Ordinary least square
- ADF:
-
Augmented Dickey-Fuller
- PP:
-
Phillips Perron
- KPSS:
-
Kwiatkowski, Phillips, Schmidt and Shin
- CUSUM:
-
Cumulative sum of recursive residuals
- CUSUMSQ:
-
Cumulative sum of squares of recursive residuals
- FMOLS:
-
Fully modified ordinary least square
- DOLS:
-
Dynamic ordinary least square
- GOP:
-
Government of Pakistan
- WDI:
-
World development indicator.
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CHANDIO, A.A., MAGSI, H. & OZTURK, I. Examining the effects of climate change on rice production: case study of Pakistan. Environ Sci Pollut Res 27, 7812–7822 (2020). https://doi.org/10.1007/s11356-019-07486-9
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DOI: https://doi.org/10.1007/s11356-019-07486-9