Change in cereal production caused by climate change in Malaysia
Introduction
Human intervention in nature has improved our living standards, while leading to many dangerous conditions in the air, land and water. This has resulted in climate change that has affected all sectors of the economy, particularly those related to agriculture. Climate change has had a negative impact on food security due to decreasing production of agricultural commodities (Kogo et al., 2021). Agriculture is the main source of food production and food security and contribute significantly to the economic growth of developing countries. In 2020, it accounts for 5.5% of the world's GDP (The World Bank, 2020). Food production depends not only on climate change factors (CO2 emissions, precipitation and temperature), but also on farmers' incomes, prices of agricultural products and primary inputs. Therefore, estimating the impact of key climate variables on food production is necessary for all countries, which this study aims to achieve for Malaysia.
There are some regional and international regulations that oblige countries to reduce their GHG emissions over time through implementation of certain policies for each country. These policies cover a wide range of quantitative and qualitative methods, such as the use of more energy-efficient equipment and machinery, low carbon engines, the emissions trading scheme, carbon and energy taxes and so on. The use of bio-energies has also motivated energy policymakers, as an agriculture base method, to reduce environmental degradation. Therefore, the agriculture sector contributes significantly to the production of bioenergy, and climate change will affect this production.
More than half of the world's population is living in Asia. Southeast Asia also accounts for about 15% of the total Asia's population. This large number of people shows the high demand for food products that must pay more attention to achieve food security in the region. The issue of food security, which is related to the lack of supply of staple food, can be enhanced through the performance of the agricultural sector. This may occur due to climatic and non-climatic factors such as weather temperature, rainfall, increases in agricultural prices and so on. For example, some Southeast countries like Vietnam and Thailand have experienced significant changes in their food supply due to climate change (Lin et al., 2022). Evidence also showed that temperature and CO2 emissions decline crop production in South Asia (Chandio et al., 2022a, Chandio et al., 2022b). Other studies also have found that climate change negatively impacts paddy production, which increases food insecurity in Malaysia (Firdaus et al., 2020). Climate change and changes in ecosystem productivity are issues that affect supply chain costs and retail prices (FAO, 2015).
Malaysia has a population of around 32.5 million, with about 4.5% living in rural areas. In 2020, the agriculture, forestry and fishing sector accounted for about 10.5% of Malaysia's total employment and 7.4% of its gross domestic product. This share has decreased over time due to fast economic growth and the industrialization process. The major contributors to agricultural value-added are oil palm (37.1%), other agricultural products (27.9%), livestock (16.1%), fishing (11.2%), forestry and logging (5.2%) and rubber (2.5%). Cereal production in Malaysia increased from 2383 kg per hectare in 1970 to 4128 kg per hectare in 2018. According to Fig. 1, Malaysia is one of the top cereal producers among the ASEAN countries. Since cereal production is the main source of food security for a country, its production by increasing the population needs to be increased. But Fig. 1 shows the slow increase in cereal production in Malaysia and other ASEAN countries, whereas their population is growing at a more rapid rate. Therefore, with high population growth, high food demand and fast changes in climate variables, food security in Malaysia and globally is a major concern for policymakers, agriculturists and researchers.
Fig. 2 represents the top CO2 emitters in the ASEAN countries. It shows that Malaysia is among the top 3 CO2 emitters in the ASEAN region and its CO2 emissions are increasing. Evidence showed that the rise in CO2 emissions because of the adverse impact on climate will decrease the production of agricultural commodities (Ahmad et al., 2020; Murad et al., 2010), particularly cereal yield. In Malaysia, climate change factors have an adverse impact on food availability as well as on access to food because of the fall in the supply of agricultural commodities (Solaymani, 2018). This eventually leads to higher prices for agricultural commodities and, therefore, to poverty (Solaymani, 2017). On the other hand, the agriculture sector has a negative effect on CO2 emissions (Mahmood et al., 2019; Rehman et al., 2019). This will happen through the use of bio-energies obtained from agricultural products (Jebli and Youssef, 2017). In China, temperature and CO2 emissions are the main variables in crop yield variations (Zhang et al., 2021). On the other hand, an increase in precipitation reduces the adverse impact of temperature on crop production (Srivastava et al., 2021). In some regions, climate change affects crop production in different ways. For example, in the North China Plain, it had an adverse impact on maize production and a positive impact on wheat production (Xiao et al., 2020). In sub-Saharan Africa, using a crop model, some studies found that cereal yield is more vulnerable than maize to climate change variables (Stuch et al., 2021). Similarly, using multiple regression analysis, other studies demonstrated that the impact of temperature on land productivity is negative for most of the crops in India (Praveen and Sharma, 2020). According to the Food and Agriculture Organization (FAO) report, continuing the current climate change condition by the year 2100 will result in a 20% to 50% reduction in the production of major crops (FAO, 2015).
In tropical and developing regions like Malaysia, a few studies have investigated the link between climate change factors and the production of agricultural commodities using the dynamic ARDL simulations method. Moreover, they have not predicted the effect of climatic factors on the production of agricultural commodities. Many of these studies have used non-econometric approaches concentrate mainly on African countries. Therefore, besides using a general autoregressive distributed lag model, the current study applies an innovative and new methodology, known as the dynamic ARDL simulations, to estimate and predict the impacts of climatic and non-climatic factors on cereal production in Malaysia. The later technique is a novel methodology that allows the user to predict the effect of actual change in certain independent variables on the dependent variable over a time horizon. This study uses time-series data on cereal production, cultivated land, labor force, fossil fuel consumption, CO2 emissions, temperature, and rainfall during 1969–2018. Second, besides estimating the pairwise Granger causality between the dependent variable and all independent variables, it estimates the short- and long-run impacts of climatic and non-climatic factors on cereal production.
The remainder of the present study is organized in the following way. A review of the literature that investigates the impact of climate change variables on the agricultural sector is presented in the following section. Section 3 provides an overview of the data source and the methodology. Section 4 evaluates the outcomes of the study. Section 5 provides a discussion on the findings of the study and the final section concludes the results.
Section snippets
Literature review
The effect of climate change factors on the production of agricultural commodities differs by commodity and region (FAO, 2016) and all climate-related disturbances have dramatic impacts not only on the way food is distributed, but also on food access and quality (Arora, 2019). For example, in West Africa, climate change between 2000 and 2009 reduced the average regional yield of millet and sorghum by 10–20% and 5–15%, respectively (Sultan et al., 2019). Using the multiple regression analysis,
Data and methodology
The general form of a production function is that the production of a crop is a function of the primary inputs (i.e., labor, capital (in our case cultivated land per hectare) and energy), which can be controlled by framers. However, a crop production function is a function of other factors such as climatic change factors (carbon dioxide (CO2), temperature and rainfall) that cannot be controlled by farmers. Therefore, the primary cereal production function of this study can be formulated as
Primary tests on variables
To validate the results of the study, it is necessary to perform preliminary tests. The first test is the stationary test and the second test is the co-integration relationship between the research variables. The existence of nonstationary variables leads to invalid t and F tests and the regression becomes a spurious regression. Therefore, it is first necessary to perform a test to determine the stationary before any other action. There are several tests to determine the stationary of
Discussion
The results of the study show the existence of a long-run relationship between cereal production and the climatic and non-climatic variables in the study model. These findings support the results of previous studies such as Ahmad et al. (2020) and Ahsan et al. (2020).
Cultivated cereal land per hectare positively affects cereal yield in the short- and long-run. It shows that if cultivated land rises by 1%, cereal yield increases by 1.11% and 0.83% in the long- and short-run, respectively. But
Conclusions and recommendations
This study investigated the impacts of climatic and non-climatic factors on cereal yield in Malaysia from 1969 to 2018. For this purpose, it used several econometric methods. After checking the primary and essential tests, we used the ARDL bounds testing approach to identify the presence of a long-run link between the model's variables. We also used Johansen and Juselius' co-integration (J-J) test to reexamine the robustness of co-integration results. After finding the long-run relationships,
Author contributions
Saeed Solaymani: Conceptualization; Data curation; Formal Anaysis; Investigation; Methodology; Project administration; Software; Supervision; Validation; Writing - original draft. Xinyue Xiang: Funding acquisition; Visualization; Writing - review & editing.
Funding
Key Project of National Social Science Fund (ProjectNo.: 20AZD116).This funding is recieved by Dr. Xinyue Xiang.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Availability of data and materials
The source of all data used in this study is reported in the reference list of this paper. They will be available upon request.
Declaration of Competing Interest
The authors have no relevant financial or non-financial interests to disclose.
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