1.3 Sampling Frame and Design

Project Semai engaged with private and public stakeholders in its survey design stage. The Ministry of Agriculture and Food Security of Malaysia provided invaluable guidance and insights into the smallholders' landscape in Malaysia. The Department of Agriculture (DOA), Department of Veterinary Services (DVS), and Department of Fisheries (DOF) provided the Team with the population size of smallholders within each subsector.

Khazanah Research Institute (KRI), industry players and relevant stakeholders provided advisory, guidance and input through meetings and a roundtable discussion (held on 10 May 2022).

A non-random method was used in sample selection because there was no complete list of smallholders across the different agricultural sectors in Malaysia. Additionally, geographical challenges in reaching out to smallholders across different regions might have made random sampling logistically challenging, and time constraints further influenced the decision.

The sample of smallholders was structured using a quota-based method¹ on the approximate share representation of the three agriculture subsectors. Convenience sampling² was used to reach the targeted respondents.

Despite the limitations of non-random sampling techniques, the survey implementation teams were extensively trained, and local experts were engaged to target respondents based on specific criteria and guidelines. Additionally, multiple sources were employed to identify potential respondents to increase representativeness (across sectors, locations, etc.).

It is important to note that our sample was non-randomly selected. As a result, Project Semai's findings cannot be generalized to the entire smallholder population in Malaysia.

While we acknowledge the limitations of non-random sampling techniques, particularly in terms of representativeness and potential bias, the steps taken in sample selection were aimed at ensuring that we could derive meaningful insights in our sectoral analyses while mitigating these challenges.

Note 1: The quota-based sampling method is a non-random sampling technique that involves selecting a sample from various subgroups of a population based on predetermined quota sizes. However, it does not entail random sample selection within these subgroups.

Note 2: Convenience sampling method is a non-random sampling technique that involves selecting a sample from the target population based on practical considerations such as easy accessibility, geographic proximity, availability, and willingness to participate in the study at a specific time. Similar to the quota-based sampling method, it does not entail random sample selection

1.4 Targeted Sample Size

The targeted sample sizes for Project Semai were 2,356 for crops, 1,436 for livestock, and 870 for aquaculture. These sample sizes were estimated based on the information gathered during the pilot survey.

During the pilot survey, the overall response rate was 50%. However, the response rate for the livestock sector was significantly lower at 25% due to various challenges encountered throughout the livestock-specific survey, including accessibility, logistics, and communication issues. The challenges faced during the pilot survey were factored into the sample size design for the actual survey.

Regarding actual responses received, Project Semai obtained 2,100 responses for crops, 816 for livestock, and 702 for aquaculture. The final response rate was 89% for crops, 57% for livestock, and 81% for aquaculture. The final response rate is higher than initially expected as the Team proactively reached out to more stakeholders and continually improved the survey approach.

Table 2: Sample size of smallholders surveyed

Note 1: The population size of smallholders is sourced from the Ministry of Agriculture and Food Security of Malaysia, DOA, DVS, and DOF.

Note 2: Some smallholders are involved in multisector farming. The analysis considered each smallholder involved in multisector farming for every subsector separately. Therefore, the same smallholder may be double counted in crops, livestock, and aquaculture sample size. As a result, the sum of the Crops, Livestock, and Aquaculture sample sizes (N=3,618), representing the dataset's observations, is more than the total number of unique actual farmers surveyed (N=3,300).

Note 3: Considering the response rates, the margin of error for the crops and aquaculture sectors was set at 2.5%, while a higher margin of error of 5.0% was set for the livestock sector.

1.5 Survey Fieldwork

The survey was conducted over five months, between October 2022 and March 2023, in the order of Crops, Livestock, and Aquaculture. The questionnaire was prepared in Malay language, with translated versions in English, Mandarin, and Tamil made available to assist enumerators in overcoming language barriers. During the face-to-face interviews, local enumerators were also employed to help overcome language barriers, such as regional dialects, to ensure that respondents understood the questions as accurately as possible.

1.5.1 Survey implementation teams

Six regional coordinators were involved in the fieldwork. They were responsible for hiring field staff, organizing training sessions for enumerators, and entering data.

• • AgriData Portal
• • Owl & Badger Research
• • Penang Institute
• • Universiti Malaysia Sarawak (UNIMAS)
• • Universiti Putra Malaysia (UPM)
• • Universiti Sultan Zainal Abidin (UniSZA)

1.5.2 Data entry and processing

The data coordination process was led by Think City. This entailed checking and cleaning the data and basic data tabulation.

The datasets were further processed and analyzed by Khazanah's internal Team. The analysis involved exploratory data analysis to understand the main characteristics of the dataset, followed by descriptive study to identify patterns, trends, and relationships within the data.

1.6 Survey limitations

The objective of Project Semai is to validate some of the challenges faced by smallholder farmers involved in the agriculture sector in Malaysia, including crops, livestock, and aquaculture. Paddy and oil palm are excluded from this survey.

Project Semai is only able to cover some challenges faced by smallholder farmers in Malaysia due to the complexity and nuances of the sector. For example, the survey does not extensively cover issues related to supply chain management and research and development, even though they may be relevant to challenges faced by smallholder farmers.

It should be noted that the results obtained from Project Semai are not representative of the broader smallholders' population in Malaysia, as the sampling design has inherent limitations. Project Semai survey design and execution are limited to the availability of smallholder data and networks within different regions.

Additionally, the responses obtained are based on self-reported data, which may be subject to reporting bias or errors. Smallholder farmers' operations vary extensively due to different factors such as the size and type of farms, farming experience, and farmers' age.

Moreover, Project Semai does not make any causal claims among variables.

While the survey aims to provide Khazanah with an understanding of potential opportunities for strategic investments within the agriculture sector, one should interpret the findings from Project Semai with caution and not rely upon them as the sole basis for making any policy or investment decisions.

Findings from Project Semai are limited to better understanding the challenges faced by smallholders in different agriculture subsectors. The information furnished in this website is for informational purposes only. The information should not be relied upon by any person to make an investment decision or for any other purposes.