Impact of climate change on production of selected agricultural commodities in Malaysia
Climate change is arguably one of the most important factors influencing agricultural production in developing countries such as Malaysia. Malaysian population rely mostly on agriculture and other climate-dependent resources. However, inadequate attention has limited the country’s capacity towards a...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2017
|
Online Access: | http://psasir.upm.edu.my/id/eprint/70353/1/FP%202017%2026%20IR.pdf http://psasir.upm.edu.my/id/eprint/70353/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Putra Malaysia |
Language: | English |
Summary: | Climate change is arguably one of the most important factors influencing agricultural production in developing countries such as Malaysia. Malaysian population rely mostly on agriculture and other climate-dependent resources. However, inadequate attention has limited the country’s capacity towards adapting to climate change, while population increase continues to pose a serious challenge to food security. Therefore, it becomes important to explore the impacts of climate change on agricultural yield and production.
In this study, efforts were made to figure out the impacts of climate change (rainfall and temperature) on 12 strategic agricultural commodities production. Efforts were also intensified towards developing market model for each of the commodities. These commodities were selected based on their contribution to the GDP and their role in food security issues.
This study applied the autoregressive distributed lag (ARDL) co-integration approach over the periods (1980 – 2014). The model provides a convenient framework for analyzing the effects of climate change on agricultural commodities production.
The data analysis was based on the bound testing approach for co-integration. Essentially, the Bounds testing approach employs a Wald or F-test of significance for the lagged levels of the variables which are reformulated in a conditional error correction version of the ARDL model. In the present study, the Bounds procedure followed three steps: the optimal lag length p for the equation was selected to correct simultaneously for endogeneity and serial correlation. Once the lag length is confirmed, the long-run relationship in the equations was tested by estimating the equation over the baseline period of 1980-2014 and finally, the values of the F-statistic corresponding to the null hypotheses were computed.
To commence the forecasting and simulation of all the commodities models, the year 2014 was chosen as the base year. There are two main methods including the Regional Climate Model (RCM) which can reasonably produce appropriate projections that can be used for climate scenario generation in a country-scale. Based on this information, this study considered three scenarios: 1) First Scenario, Temperature changes: Based on the anticipated temperature changes in Malaysia by 2020 which is expected to increase by +1.15°C more than the normal trend. 2) Second Scenario, Rainfall changes: Based on the projected rainfall changes in Malaysia by 2020 which is expected to increase by +6% more than the normal trend. 3) Third Scenario, Scenario 1 and 2 simultaneously.
Preliminary results from the Autoregressive Distributed Lag (ARDL) model applied indicated that despite the projected changes in the climate variables (temperature and rainfall), beef production will increase from 53,840.97 Metric Tonne (MT) in 2014 to 137,169.1 MT in 2020. Besides, the average trend compared to the baseline is positive and expected to increase by +6.06% annually. Finally, the results showed that the overall trend is positive and climate change will also have positive impacts on the industry.
Broiler production will also increase from 1,481,684 MT in 2014 to 2,004,610 MT in 2020. However, the aggregate trend compared to the baseline is negative and expected to drop by -1.068% annually. Finally, the results showed that the overall trend is positive but climate change will have negative impacts on the industry. Similarly, cocoa yield will also increase from 0.154 t/ha to 0.189 t/ha by 2020. The average trend compared to the baseline is positive and expected to increase by +6.06% annually. Finally, the results showed that the overall trend is positive and climate change will also positive impacts on the industry. Furthermore, eggs production will also increase from 10,739.33 mu to 11,369.81 mu by 2020. However, the aggregate trend compared to the baseline is negative and expected to drop by -2.64% annually. Finally, the results showed that the overall trend is positive but after considering climate impacts, it has negative influence on the industry. Based on the projected changes in temperature and rainfall, palm oil yield will increase from 17.51 in 2014 t/ha to 17.81 t/ha in 2020. However, the aggregate trend compared to the baseline is negative and expected to drop by -0.82% annually. Finally, the results showed that the overall trend is positive but after considering climate impact, it has negative effect on this industry. In paddy industry even though the yield will increase from 3,811.32 t/ha to 4,037.40 t/ha by 2020, the total trend compared to the baseline is negative and expected to drop by -0.36% annually. Finally, the results showed that the overall trend is positive but after considering climate impacts, it has negative influence on paddy production. In pepper, the yield will increase from 1.78 t/ha in 2014 to 1.67 t/ha in 2020. The aggregate trend compared to the baseline is positive and expected to develop by 0.68% annually. Finally, the results revealed that the overall trend is negative. However, climate change will have no negative influence on the industry. The pineapple yield will fall from 21.59 t/ha to 16.23 t/ha by 2020. Also, the overall trend compared to the baseline is negative and expected to drop by -5.57% annually. Finally, the results revealed that the overall trend is negative and climate change will also have negative impacts on the industry. In Pork, production will drop from 156,830.4 MT in 2014 to 76,341.35 MT in 2020. Also, the aggregate trend compared to the baseline is negative and expected to drop by -9.40% annually. Finally, the results showed that not only the overall trend is negative but climate change will also have negative impacts on the industry. Furthermore, the rubber yield will increase from 1.57 t/ha to 1.64 t/ha by 2020. However, the aggregate trend compared to the baseline is negative and projected to drop by -0.53% annually. Finally, the results revealed that the overall trend is positive although climate change will have negative impacts on the industry. In tobacco, the yield will increase from 990.26 kg/h in 2014 to 1,054.94 kg/h in 2020. However, the aggregate trend compared to the baseline is negative and projected to drop by -0.42% annually. Finally, the results showed that the overall trend is positive but after considering climate impacts, it has negative influence on the industry.
The general conclusion based on scenario 3 (simultaneous changes in rainfall and temperature) showed that the changing climatic conditions have no negative impacts on beef and cocoa, and more efforts need to be directed towards enhancing the yield in these industries. Also, the negative impacts of climate change on paddy, palm oil, pepper, tobacco and rubber is very minimal. Thus, Production in these sub-sectors can be enhanced by developing models that include other variables such as transportation, the timing of flowering, improved farming practices, and technology. Lastly, changing climatic conditions has a considerable negative impact on broiler, mutton, pork, egg and pineapple as it threatens the production and yield in these industries. Therefore, these sub-sectors require more comprehensive investigations regarding climate change and its effects on yield and productivity. As it has been confirmed, the effects on the livestock sub-sector are much more pronounced than crop sub-sector. Therefore, introducing supporting policies and programs such as improved technology, new resistant-breed, adjustment of the market and the control of diseases can go a long way in enhancing the performance of the livestock sector. |
---|