Modelling the impacts of climate change and air pollutants on the agricultural production yields in Malaysia using Random-Effects Error Components Regression model

Authors

  • Z.L. Chuan Centre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • S.F. Fam Technopreneurship Department, Faculty of Technology Management and Technopreneurship, Universiti Teknikal Melaka Malaysia, Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • Q.H. Lee Faculty of Industrial Sciences and Technology, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • J.S. Kok Faculty of Industrial Sciences and Technology, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • M.N.B.M. Azam Centre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.

DOI:

https://doi.org/10.15282/daam.v3i2.7755

Keywords:

Agricultural yields, Climate change, Climate variable, Air pollutants, Food security

Abstract

The occurrence of climate change is attributable to anthropogenic emissions of greenhouse gases (GHG) which have affected the C3 plants’ agricultural production yields in past decades. Therefore, this article aims to model the linear association among these C3 plants’ agricultural production yields with several climatic and non-climatic explanatory variables using one-way random-effects error components regression model. To be congruent with the main objective of this study, the balanced longitudinal dataset period 1980 to 2018 under big data was acquired. The analysis results revealed that merely maximum temperature.

ARTICLE HISTORY
Received: 29/05/2022
Revised: 19/09/2022
Accepted: 30/09/2022
Published: 30/09/2022

References

Ministry of Plantation Industries and Commodities, Q4/2020 pocketstats agricommodity. Putrajaya, Malaysia: Ministry of Plantation Industries and Commodities, 2020.

Statista, “Gross domestic product (GDP) from paddy in Malaysia from 2016 to 2020,” Available:https://www.statista.com/statistics/952735/malaysia-gdp-from-rice-industry/, 2021. [Accessed Jan. 25, 2022].

Trading Economics, “Malaysia exports of cocoa and cocoa preparations,” Available:https://tradingeconomics.com/malaysia/exports/cocoa-cocoa-preparations, 2022. [Accessed Jan. 28, 2022].

Department of Statistics Malaysia, “Supply and utilization accounts selected agricultural commodities, Malaysia 2015-2019,” Available:https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=164&bulid=OTM1TDMzS1IvYm5mU1JiU1

Fwekt3UT09&menu_id=Z0VTZGU1UHBUT1VJMFlpaXRRR0xpdz09, 2020. [Accessed Jan. 28, 2022].

Department of Statistics Malaysia, “Supply and utilization accounts selected agricultural commodities, Malaysia 2016-2020,” Available:

https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=164&bul_id=cHgwanhNdU4vWXRvc3pnZU9xSjZTUT09&menu_id=Z0VTZGU1UHBUT1VJMFl paXRRR0xpdz09, 2021. [Accessed Jan. 28, 2022]

Z.L. Chuan, S.M. Deni, S-.F. Fam and N. Ismail, “The effectiveness of a probabilistic principal component analysis model and expectation maximisation algorithm in treating missing daily rainfall data,” Asia-Pacific Journal of Atmospheric Sciences., vol. 56, pp. 119-129, 2020.

A. Chizari, Z. Mohamed, M.N. Shamsudin and K.W.K. Seng, “The effects of climate change phenomena on cocoa production in Malaysia,” International Journal of Environment, Agriculture and Biotechnology., vol. 2, no. 5, pp. 2599-2604, 2017.

B.T. Tan, P.S. Fam, R.B.R. Firdaus, M.L. Tan and M.S. Gunaratne, “Impact of climate change on rice yield in Malaysia: a panel data analysis,” Agriculture., vol. 11, no. 6, pp. 569, 2021.

M.H.M. Hazir, R.A. Kadir and Y.A. Karim, “Projections on future impact and vulnerability of climate change towards rubber areas in Peninsular Malaysia,” in IOP Conference Series: Earth and Environmental Science., vol. 169, no. 012053,2018.

M.W. Murad, R.I. Molla, M.B. Mokhtar and M.A. Raquib, “Climate change and agricultural growth: an examination of the link in Malaysia,” International Journal of Climate Change Strategies and Management., vol. 2, no. 4, pp. 403-417, 2010.

A.A. Houma, M.R. Kamal, M.A. Mojid, A.F.B. Abdullah and A. Wayayok, “Climate change impacts on rice yield of alarge-scale irrigation scheme in Malaysia,” Agricultural Water Management., vol. 252, no. 106908, 2021.

N.M. Roslan, W.L. Shinyie and S.S. Ling, “Modelling high dimensional paddy production data using copulas,” Pertanika Journal of Science & Technology., vol. 29, no. 1, pp. 263-284, 2021.

A. Abubakar, M.Y. Ishak and A.A. Makmo, “Impacts of and adaption to climate change on the oil palm in Malaysia: asystematic review,” Environmental Science and Pollution Research., vol. 28, pp. 54339-54361, 2021.

M.S. Fahmy, “The value of big data to the world economy,” Arab Journal of Administration, vol. 40, no. 4, pp. 307-322,2020.

Y. Ge and H. Wu, “Prediction of corn price fluctuation based on multiple linear regression analysis model under big data,”Neural Computing and Applications, vol. 32, no. 1, pp.16843-16855, 2020.

M.L. Tan, L. Juneng, F.T. Tangang, J.X. Chung and R.B.R. Firdaus, “Changes in temperature extremes and the irrelationship with ENSO in Malaysia from 1985 to 2018,” International Journal of Climatology, vol. 41, no. S1, pp. E2564-E2580, 2021.

V.S. Shevade and T.V. Loboda, “Oil palm plantations in Peninsular Malaysia: determinants and constraints on expansion,”PLoS ONE, vol. 14, no. 2, pp. e0210628, 2019.

A. Simon, V.K. Subbiah, C.F. Tyng and N.H.M. Yusuf, “Genetic diversity of Sabah rice cultivars using random amplified polymorphic DNA (RAPD) markers,” Borneo International Journal of Biotechnology (BIJB), vol. 1, pp. 35-43, 2020.

N. Vaghefi, M.N. Shamsudin, A. Radam and K.A. Rahim, “Impact of climate change on food security in Malaysia: economic and policy adjustments for rice industry,” Journal of Integrative Environmental Sciences, vol. 13, no. 1, pp. 19-35, 2015.

J. Lu, G.J. Carbone, X. Huang, K. Lackstrom and P. Gao, “Mapping the sensitivity of agriculture to drought and estimating the effect of irrigation in the United States, 1950-2016,” Agricultural and Forest Meteorology, vol. 292-293, no. 1, pp.108124, 2020.

W. Mahrous, “Climate change and food security in EAC region: a panel data analysis,” Review of Economics and PoliticalScience, vol. 4, no. 4, pp. 270-284, 2019.

S.H. Mosavi, S. Soltani and S. Khalilian, “Coping with climate change in agriculture: evidence from Hamadan-Bahar plainin Iran,” Agricultural Water Management, vol. 241, no. 1, pp. 106332, 2020.

M.A.R. Sarker, K. Alam and J. Gow, “Assessing the effects of climate change on rice yields: an econometric investigation using Bangladeshi panel data,” Economic Analysis and Policy, vol. 44, no. 4, pp. 405-416, 2014.

J.A. Hausman, “Specification tests in econometrics,” Econometrica, vol. 46, no. 6, pp. 1251-1271, 1978.

B.H. Baltagi and Q. Li, “Testing AR(1) against MA(1) disturbances in an error component model,” Journal of Econometrics, vol. 68, no. 1, pp. 133-151, 1995.

G.S. Maddala and S. Wu (1999), “A comparative study of unit root tests with panel data and a new simple test,” Oxford Bulletin of Economics and Statistics, vol. 61, no. S1, pp. 631-652, 1999.

S.S. Arora, “Error components regression models and their applications,” Annals of Economic and Social Measurement,vol. 2, no. 4, pp. 451-461, 1973.

P.A.V.B. Swamy and S.S. Arora, “The exact finite sample properties of the estimators of coefficients in the error components regression models,” Econometrica, vol. 40, no. 2, pp. 261-275, 1972.

P.M. Aliha, A.P.D.T. Sarmidi and D.F.F. Said, “Applying panel data model for comparing static and dynamic forecasts ofan autoregressive money demand incorporating financial innovation in Asean countries,” International Journal of Accounting, Finance and Business, vol. 5, no. 28, pp. 22-36, 2020.

R. Cellmer, A.B. Cichulska and M. Belej, “The regional spatial diversity of housing prices and market activity-evidence from Poland,” Acta Scientiarum Polonorum Administratio Locorum, vol. 20, no. 1, pp. 5-18, 2021.

R. Stefko, B. Gavurova, M. Kelemen, M. Rigelsky and V. Ivankova, “Relationships between renewable energy and the prevalence of morbidity in the countries of the European Union: a panel regression approach,” International Journal of Environmental Research and Public Health, vol. 18, no. 12, pp. 6548, 2021.

B.H. Baltagi, Econometric Analysis of Panel Data, 6th Edition, Cham, Switzerland AG: Springer Nature, 2021.

N.P. Joshi, K.L. Maharjan and L. Piya, “Effect of climate variables on yield of major food-crops in Nepal: a time-series analysis,” Journal of Contemporary India Studies: Space, Society, vol. 1, pp. 19-26, 2011.

Y. Xu, L. Yu, W. Li, P. Ciais, Y. Cheng and P. Gong, “Annual oil palm plantation maps in Malaysia and Indonesia from2001 to 2016,” Earth System Science Data, vol. 12, no. 2, pp. 847-867, 2020.

R.B.R. Firdaus, M.L. Tan, S.R. Rahmat and M.S. Gunaratne, “Paddy, rice and food security in Malaysia: a review of climate change impacts,” Cogent Social Sciences, vol. 6, no. 1, pp. 1818373.

J.L Hatfield and J.H. Prueger, “Temperature extremes: effect on plant growth and development,” Weather and Climate Extremes, vol. 10, no. Part A, pp. 4-10, 2015.

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Published

2022-09-30

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Section

Research Articles

How to Cite

[1]
Z. L. Chuan, S.F. Fam, Q.H. Lee, J.S. Kok, and M.N.B.M. Azam, “Modelling the impacts of climate change and air pollutants on the agricultural production yields in Malaysia using Random-Effects Error Components Regression model ”, Data Anal. Appl. Math., vol. 3, no. 2, pp. 1–12, Sep. 2022, doi: 10.15282/daam.v3i2.7755.

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