Department Of Statistics Malaysia Research Articles

Predicting air quality trends in Malaysia’s largest cities: the role of urban population dynamics and COVID-19 effects

This paper aims to explore the relationship between the Air Quality Index (AQI), COVID-19 incidence rates, and population density within Malaysia’s ten most populous cities from January 2018 to December 2021. Data were sourced from the Department of Statistics Malaysia, the World Air Quality Index Project, and Our World in Statistics. The methodology integrated population-based city classification and AQI assessment, cluster analysis through SPSS, and Generalized Additive Mixed Model (GAMM) analysis using R Studio despite encountering a data gap in AQI for five months in 2019. Cities were organized into three clusters based on their AQI: Cluster One included Ipoh, Penang, Kuala Lumpur, and Melaka, Cluster Two comprised Kuantan, Seremban, Johor Bahru, and Kota Bharu, Cluster Three featured Kota Kinabalu and Kuching. GAMM analysis revealed prediction accuracies for AQI variations of 58%, 60%, and 41% for the respective clusters, indicating a notable impact of population density on air quality. AQI variations remained unaffected by COVID-19, with a forecasted improvement in air quality across all clusters. The paper presents novel insights into the negligible impact of COVID-19 on AQI variations and underscores the predictive power of population dynamics on urban air quality, offering valuable perspectives for environmental and urban planning.

Predictions of Malaysia Age-Specific Fertility Rates using the Lee-Carter and the Functional Data Approaches

Global fertility has been experiencing a significant decline, reaching towards the replacement ratio. This trend, coupled with increasing life expectancies, has led to the emergence of an ageing population. In this study, we delve into an analysis of fertility patterns among Malaysian women, considering both their childbearing age and ethnic groups. A comprehensive 63-year fertility dataset, from 1958 to 2020, were obtained from the Department of Statistics Malaysia. These data were fitted into the Lee-Carter model and its modified version, which is the functional data model. The models were evaluated using the out-sample forecast error measures. Results indicate that the third-order functional data model able to capture most of variation present in the actual data, consequently outperforming the Lee-Carter model in forecasting fertility rates among Chinese and Indian populations. The 20-year forecasts reveal a noteworthy shift in maternal ages of the highest births to older ages suggesting a trend towards delayed pregnancies among women. It is predicted that the Malay total fertility rates will likely fall to below the replacement level reaching 1.71 in 2040 whereas Chinese and Indian total fertility rates will substantially decrease to the lowest level in history below 1.0 which are 0.54 and 0.70 respectively. The evolution in Malaysian fertility rates is an alarming fact as, together with low mortality rates, it may impact the Malaysian population structure in future. Proactive policy measures are urgently needed to address these demographic shifts.

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

This study measured the level of technical efficiency (TE) that exerted a significant impact on the Malaysian electric and electronic manufacturing industry, which consists of 13 sub-industries, from 2010 to 2015. Unbalanced panel data from 1880 firms was obtained from the Department of Statistics Malaysia. We used stochastic frontier (SFA) analysis with the transcendental logarithmic approach to estimate the empirical analysis parametric. The maximum likelihood estimated regression of the SFA parameters revealed a high total average TE of 0.944%. Both the manufacturing sub-industries for communications equipment (MSIC 263) and irradiation, electromedical, and electrotherapeutic equipment (MSIC 266) demonstrated the highest average TE value and consistency (0.989%). The consumer electronics manufacturing sub-industry (MSIC 264) yielded a notably lower TE level (0.846%). Changes in TE for all industries were monitored via standard deviation analysis. The low standard deviation (SD) for MSIC 263, 271, and 275 indicated continuous progress and demands for these industries, while the higher SD for MSIC 264, 266, 272, and 273 pointed out major changes that happened within the period. The findings demonstrated that studies on the TE levels indicate that the E&E manufacturing industry has highly expended and continuous efforts to update technologies and human capital innovations. Therefore, the practical implication is to achieve Sustainable Development Goal 9 for sustainable industrialization and fostering innovation by 2030.

Population Outside the Labour Force, Its Causes and Potential: A Review from An Islamic Perspective

The population outside the labour force refers to individuals who are not classified as employed or unemployed. The Department of Statistics Malaysia have classified individuals who are not interested in jobs into six main reasons: (1) attending school or training programmes, (2) homeworking or family responsibilities, (3) pursuing further studies, (4) disability, (5) disinterest, and (6) retirement. Based on the data, there is no specific trend to the population outside the labour force in Malaysia. However, there are concerns about the lack of information on the population outside the labour force in Malaysia which may result in them being discounted from the labour force. On the flip side, technological advancement, working arrangement, and new “non-standard” employment are part of the factors that may have influenced this population to remain outside of the labour force. This paper highlights the importance of revisiting the meaning of employment, especially in the new way of working arrangements so that policymakers are able to assemble accurate labour market information in making strategic moves in accordance with the needs and demands of every sector. In addition, this paper also explores the Islamic view of the trend in the wider context, going beyond the terms of wage and profit.

Investigation of the impacts of climate change and rising temperature on food poisoning cases in Malaysia.

This study is an attempt to investigate climate-induced increases in morbidity rates of food poisoning cases. Monthly food poisoning cases, average monthly meteorological data, and population data from 2004 to 2014 were obtained from the Malaysian Ministry of Health, Malaysian Meteorological Department, and Department of Statistics Malaysia, respectively. Poisson generalised linear models were developed to assess the association between climatic parameters and the number of reported food poisoning cases. The findings revealed that the food poisoning incidence in Malaysia during the 11 years study period was 561 cases per 100 000 population for the whole country. Among the cases, females and the ethnic Malays most frequently experienced food poisoning with incidence rates of 313 cases per 100,000 and 438 cases per 100,000 population over the period of 11 years, respectively. Most of the cases occurred within the active age of 13 to 35 years old. Temperature gave a significant impact on the incidence of food poisoning cases in Selangor (95% CI: 1.033-1.479; p = 0.020), Melaka (95% CI: 1.046-2.080; p = 0.027), Kelantan (95% CI: 1.129-1.958; p = 0.005), and Sabah (95% CI: 1.127-2.690; p = 0.012) while rainfall was a protective factor in Terengganu (95% CI: 0.996-0.999; p = 0.034) at lag 0 month. For a 1.0°C increase in temperature, the excess risk of food poisoning in each state can increase up to 74.1%, whereas for every 50 mm increase in rainfall, the risk of getting food poisoning decreased by almost 10%. The study concludes that climate does affect the distribution of food poisoning cases in Selangor, Melaka, Kelantan, Sabah, and Terengganu. Food poisoning cases in other states are not directly associated with temperature but related to monthly trends and seasonality.

The Determinants of Household Debt in Malaysia

This study aims to observe the determinants of the factors affecting household debt in Malaysia. This study has listed six independent variables that would affect Malaysia’s household debt: real interest rate, inflation rate, unemployment rate, household consumption expenditure, gross domestic product (GDP), and housing price index (HPI). This research was conducted by using annual data for 30 years (1991-2021); this study also used a quantitative approach to the collection of data using secondary data such as the website of the World Bank, Department of Statistics Malaysia, Eikon Thomson Reuters, and Bank Negara Malaysia. A theoretical model with the hypothesized relationships was tested with the help of the structural equation modelling procedures. Findings showed that the unemployment rate and gross domestic product have a positive and significant relationship with household debt. These determinants are directly affecting household debt in Malaysia, especially in microeconomic factors. This study will contribute to a better understanding that household debt can be influenced by other factors. Further study on the other determinants of household debt may result in varying results.

COMPETITIVENESS INDEX OF PENINSULAR MALAYSIA'S NORTHERN BORDER DISTRICTS

Competitive cities are known for their substantial economic growth, high incomes, and the ability to attract foreign investments. While a strong economy is crucial, other factors such as effective governance, efficient transportation, adequate housing, social inclusivity, and environmental sustainability also contribute to a city's competitiveness. This paper aims to assess the economic competitiveness of border districts in northern Peninsular Malaysia. Border cities hold significant importance following their proximity to neighbouring countries, subsequently offering advantages in terms of trade opportunities, cultural exchange, diplomatic relations, security, and socio-cultural integration. This research employed the quantitative method to measure the competitiveness level of 10 districts using economic and socioeconomic statistical data from the Department of Statistics Malaysia. The results indicated a distinct disparity among the districts along the Malaysia-Thailand border. In particular, the western districts of Perlis and Kubang Pasu displayed a higher level of economic development compared to the rural eastern districts due to their economic diversity and close proximity to industrial hubs such as Penang, Sungai Petani, and Songkhla in Southern Thailand. Furthermore, the strategic locations of the busiest international entry points, Bukit Kayu Hitam and Padang Besar, contribute significantly to the importance of logistics in these areas. In contrast, the middle and eastern districts heavily rely on agricultural activities, resulting in lower average incomes and higher poverty rates.

Financial Risk and International Inbound Tourism: A Malaysian Illustration

The impact of financial risk on inbound tourism is explored in this study by examining the effect of shocks in foreign debt level and debt service stability on the tourist arrival rate in Malaysia, based on the Theory of Planned Behavior (TPB). Quarterly data from 2010 to 2020 were obtained from multiple sources, which include the Malaysia Tourism corporate website, the official portal of the Ministry of Economy Malaysia, the Department of Statistics Malaysia, and the Federal Reserve (FRED) Economic statistical website. A VAR model was estimated, together with the Granger causality test, to identify the relationship between financial risk, control variables, and the tourist arrival rate in Malaysia. We specifically consider the effects of financial risk on estimated impulse responses and variance decompositions for the studied variables. Empirical results indicate that there is a unidirectional causality running from foreign debt level stability, debt service stability, and industrial production to tourist arrivals. In addition, there is also bidirectional causality from the effective exchange rate to tourist arrivals and from tourist arrivals to the effective exchange rate. This study is the first of its kind to explore the effect of financial risks in the context of foreign debt levels and debt service stability in Malaysia. The study emphasizes the importance of monitoring the country’s debt financing threshold to maintain financial stability, which if violated would be detrimental to tourism.

FACTORS INFLUENCING HOUSE BUYER’S DECISION IN MALAYSIA. CASE STUDY: SEPANG, SELANGOR

Housing is a basic human need as explained in the Maslow hierarchy needs. Having a house is a very important entity in ensuring a sense of security for each individual and family. Deciding on buying a house is a crucial decision since housing expenses involved a large amount of cost in individual monthly expenses. Furthermore, the homeownership rate in Malaysia as reported by the Department of Statistics Malaysia (DOSM) in 2019 didn’t increase significantly. Thus, the government and house developers need to identify the important factors that influence the house buying decision-making to increase the homeownership rate in Malaysia. This study investigates the factors influencing housing buying decisions and the difference in factors influencing different income groups in Sepang, Selangor. This study measures the internal factors and external factors influencing house-buying decisions. The internal factors measure the income, stage of life cycle, employment and education subfactors. The external factors measure the financial and economic condition, house price, location, neighbourhood, house type and design and also government housing incentives. A mixed method was applied in this study by interviewing real estate experts and also a survey of 184 respondents in the case study area. Using transcribe method and analysing of the survey data with descriptive and inferential analyses to study the influencing factors. The real estate expert and respondents agreed all the factors were influencing house buying decisions except for education. The importance of the factors is also different among the income groups. For internal factors, all income groups agree that income is the most influential factor followed by employment, stage of life cycle and education. The importance of external factors is different among the groups.

Multivariable Projections of Caries-Free Prevalence and the Associated Factors from 2019 to 2030 among Schoolchildren Aged 6, 12 and 16-Year-Old in Malaysia.

This study identified caries-free associated factors and conducted multivariable projections of the caries-free prevalence until 2030 among six-, 12-, and 16-year-old schoolchildren in Malaysia. It was a secondary data analysis of caries-free prevalence and potential associated factors obtained from the Health Information Management System (HIMS), Department of Statistics Malaysia (DOSM), and Food Balance Sheets (FBS). Multiple linear regression and regression with ARMA errors were employed to determine the associated factors and predict the caries-free prevalence from 2019 or 2020 until 2030 for the six-, 12-, and 16-year-old groups, respectively. Gross Domestic Product (GDP) and household income, sugar consumption, and water fluoridation were significantly associated with caries-free status, with the most impactful in all age groups being water fluoridation. With the projected values of the associated factors, the caries-free prevalence in schoolchildren of all age groups in Malaysia is predicted to increase in the next decade. Similar to the past decade, the prevalence trend will remain the highest among the 12-year-olds and the lowest among six-year-olds. Caries-free prevalence was predicted to increase by 9.10%, 15.52%, and 15.10% in the six-, 12-, and 16-year-old groups, respectively. The prevalence multiplied the highest at four times greater than in the past ten years among 16-year-olds, compared with less than 2% in the six- and 12-year-old groups. In conclusion, by factoring in economic factors, sugar consumption, water fluoridation, and age groups, the caries-free prevalence of schoolchildren in Malaysia is projected to increase at different rates in the next decade until 2030. Thus, strategic oral health plans to recognise effective promotion programmes and strengthen others for each age group are crucial.

K-means clustering analysis and multiple linear regression model on household income in Malaysia

Household income plays a significant role in determining a country's socioeconomic standing. This measure is often used by the government to formulate the federal budget and policies that are most appropriate for national development. In spite of this, Malaysia's current economic circumstances continue to be characterized by income disparity. Therefore, this shortcoming can be addressed by analyzing the household income survey (HIS) conducted by Department of Statistics Malaysia (DoSM). In this study, the hybrid model is proposed where K-means and multiple linear regression (MLR) for clustering and predicting household income in Malaysia. Based on the experimental results, the K-means clustering analysis in conjunction with the MLR model outperformed the MLR model without clustering with a smaller mean square error. As a result, clustering analysis results in a more accurate estimate of household income because it reduces the variation between households. It is important that household income information reflect the concern of policymakers about the impact of universal and targeted interventions on different socioeconomic groups.

Repas lama dam water quality and heavy metal contamination using Qual2k

Repas Lama Dam in Bentong Pahang has been experiencing pollution by Non-Point Sources (NPS) that can be found upstream of the Sungai Repas, the pollution being so evident that discoloration of the water is observable at the location. The area is littered with mines active and inactive, with many of the inactive mines being improperly shut down. When there are mining activities, some major waste or tailings are produced as the by-products of the process which drastically increases the amount of pollution that a water body that runs through these areas will contain. The Water Quality Parameters at a location, whether biological, chemical, or physical, can give a lot of insight into the level of pollution found in a water body. Through collecting these parameters and running them through a water quality model, it can give a lot of information on the present state of a river and help in attaining predictions of the health of a river. QUAL2K is the water quality model that was used to analyse the water at Old Repas Dam and further make predictions on the state of the river after 10 years. After the modelling process, the water quality parameters and the heavy metals present were analyzed using the Malaysian National Water Quality Standard (NWQS), which also assisted in classifying the water at Old Repas Dam based off individual parameters and its overall Water Quality Index score. The major water quality parameters that were used for this study are Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), Ammonia Nitrogen, pH and Total Suspended Solids (TSS). In terms of heavy metal analysis, the heavy metals that were looked at are Arsenic (As), Lead (Pb), Zinc (Zn), Copper (Cu), Tin (Sn) and Aluminium (Al). The data for these parameters being collected from studies that were conducted on the site in 2021 and information given by the Department of Statistics Malaysia.

The Immediate Impacts of COVID-19 on Low-Income Households: Evidence from Malaysia

This study unravelled the economic impacts of the coronavirus disease 2019 (COVID-19) on low-income households. The asymmetric economic impacts of the pandemic that are biased towards the poor, young, and women have been well established. However, micro evidence on the poor is limited, thus demanding detailed understanding to design an effective targeted assistance. In this study, data were gathered from face-to-face interviews using a sampling frame provided by the Department of Statistics Malaysia (DOSM). Online data collection was dismissed to ensure all low-income households had the same chance to participate, as some might have no online access. Logistic regressions were estimated to identify the characteristics of households that suffered job loss and income reduction. The findings revealed that one in ten households experienced job loss during the pandemic, while one third survived with lower income. The extent of income reduction was rather severe, as the pandemic had reduced income generation by more than half among the affected households. The regression outcomes showed that the higher-income households among the low-income households had higher chances of experiencing income reduction. A similar scenario was noted for less-educated households. Notably, the adverse impacts were not biased toward female-headed households, as is widely perceived. There was no evidence that economic sectors explained job losses, but households involved in the agriculture, domestic, and transportation sectors had higher chances of suffering from income reduction. These results suggest that monetary government assistance should not rely on general indicators, such as female-headed households and below-poverty-line income (PLI). Instead, a more effective measure is to look at other characteristics, such as employment type, education level, and job sectors.

From Farms to Factories and Firms—Structural Transformation and Labor Productivity Growth in Malaysia

AbstractUsing data from the Department of Statistics Malaysia from 1987 to 2018 and decompositions that take account of both the static and dynamic efficiency gains from labor reallocation, this study documents that Malaysia has undergone structural transformation from an agriculture-driven to a services-driven economy. In contrast to common perceptions, however, the country's impressive growth in output per capita over the last three decades can largely be attributed not to its structural transformation but instead to sustained growth in within-sector labor productivity. At 3 percent, the contribution of between-sector reallocation of labor to output per capita growth has been relatively low.

Effect of Innovation, Market Knowledge, and Social Capital on Dayak Women Entrepreneurship in Kuching, Samarahan and Serian Divisions of Sarawak

Women entrepreneurship is considered an effective instrument for the economic development and empowerment of women. The importance of entrepreneurship growth in Malaysia is supported by the vast amount of supporting mechanisms and business policies created by the policy maker to support the industry growth. As the focus on Sarawak itself, many entrepreneurship activities seem to become more and more important in supporting the people and state economy. Considering the importance of the issue, this study seeks to investigate the effect of innovation, social capital and market knowledge on Dayak women entrepreneurs in Kuching, Samarahan and Serian divisions of Sarawak. Since the Dayak community is the largest in Sarawak which is 33.4% of the population of Sarawak (Department of Statistics Malaysia, 2020), more research is needed to understand the Dayak women because they represent an important aspect of the state's cultural and economic diversity. The efforts to support their development and empowerment are essential for promoting inclusive and sustainable growth in the region. The sample population included 300 Dayak women entrepreneurs in Kuching, Samarahan and Serian divisions of Sarawak. Using questionnaire as the main means of data collection, the correlation among variables of entrepreneurship, innovation, social capital and market knowledge will be evaluated. Data analysis will be conducted using structural equation modelling (SEM). Overall, the findings will highlight and explain further on the concept of social capital, innovation and market knowledge that will be both beneficial to Dayak women entrepreneurs and government as well as contributing to the knowledge of studies related to entrepreneurship. Further studies are recommended to explore more on the market opportunities available to Dayak women entrepreneurs, including both local and global markets. This could help identify potential areas for growth and development of women entrepreneurs in Sarawak.

Can Inclusive Entrepreneurialism Be a Solution for Unemployed Female Graduates? A Study on Inclusive Entrepreneurial Intention

Recent reports highlighted a worrying trend in Malaysia where the number of female graduates has increased but at the same time there is a lower number of female workers. Particularly, in 2022, most unemployed graduates are women, accounting for 54.2% of the total, according to the Department of Statistics Malaysia (DoSM). This increases the gender gap in the workforce and subsequently decreases female participation towards nation-building and economic growth. Meanwhile, studies have shown that inclusivity can significantly affect the reduction of unemployment rates and increase re-employment. Thus, this study suggests that “Inclusive Entrepreneurship” can be a viable solution to the problem observed, as entrepreneurship might be a more attractive option than employment for female graduates. This paper aims to explore the factors influencing inclusive entrepreneurial intention among female graduates in Malaysia. Specifically, this study employed the theory of planned behaviour (TPB) and opted for a quantitative exploratory study using the conductive method. The collected survey sample of 227 female students in Malaysia was analysed using PLS-SEM. The framework structure is based on a combination of formatively and reflectively measured variables. The results indicated that attitude, perceived behavioural control and inclusive innovativeness have significant relationships to the inclusive entrepreneurial intention of female graduates in Malaysia. These insights can lead to the formulation of effective policies and programs to encourage as well as enable female graduates to contribute towards the nation’s development via inclusive entrepreneurialism.

An Analysis of Factors Affecting Malaysia’s Youth Unemployment Rate

This study aims to identify if macroeconomics-related indicators consisting of gross domestic product (GDP), inflation, population and economic shocks are related in the Malaysia’s youth unemployment. The youth unemployment rate and its determinants’ data from an extended period of 1982 to 2020 were obtained from the Department of Statistics Malaysia (DOSM). By employing the autoregressive distributed lag (ARDL) analysis, findings show that Gross Domestic Product and Population significantly affect Youth Unemployment in the long-run. These findings indicate that the Malaysian government should develop youth-specific strategies to combat youth unemployment, with Technical and Vocational Education Training (TVET) quality and availability being one of the key initiatives. Emergency income support for youth starting in the job market ought to be provided as well, to assist them during economic shocks. Future research that includes foreign direct investment and gender variables together with youth unemployment data utilised in the current study is recommended.

Neural Network Model in Forecasting Malaysia’s Unemployment Rates

Neural networks (NN) have been widely applied in time series forecasting. This study aims to develop basic NN models for forecasting the unemployment rate in Malaysia by gender. The yearly unemployment rate of thirty-eight years from the year 1982 to 2019 was obtained from the Department of Statistics Malaysia. In addition, datasets of gross domestic product, inflation and population rates extracted from the World Bank Data website were used as input variables in developing the NN models. Several NN models with different number of hidden nodes were developed and evaluated. Results showed that the best model for the male population was the NN model with four hidden nodes in one hidden layer whereas the NN model with two hidden nodes in one hidden layer was the best for the female population. Additionally, it can be concluded that the trend for the future unemployment rate in Malaysia for male and female population in the next ten years will be gradually constant throughout the year starting from 2020 to 2030.

The Impacts of Employment-to-Population, Interest Rate Spread and Inflation on Malaysian Economic Growth: Evidence from 1991 to 2019

The International Monetary Fund (IMF), in its latest Global Financial Stability Report issued in October 2022, foresees that the world economy is going to be in deep recession in 2023. The main issues highlighted in the report that contribute to the global recession are the multi-decades higher-than-anticipated inflation and the hike in the interest rates. The report further highlights that the large-sized firms are facing a declining profitability due to skyrocketing cost and the increasing number of bankruptcy cases among the small and medium-sized firms because of rising borrowing cost. In the wake of this, the firms need to close down the businesses or to scale down by cutting down the number of employees. This, consequently, will affect the employment rate relative to increasing number of world population. Therefore, based on these current issues, we aim to examine the relationship and the impacts of the macroeconomic determinants on the economic growth focusing on Malaysia. Four macroeconomic determinants were selected namely employment-to-total population ratio (EPR), MYR-to-USD exchange rate (EXC), lending-borrowing interest rate spread (IRS) and consumer price index (CPI). Gross domestic product growth rate (GDPGR) was used as a proxy for the economic growth. Annual secondary data from 1991 to 2019 were gathered from the World Bank Open Data and the Department of Statistics Malaysia (DOSM) Official Portal. We based our analyses on the descriptive statistics to look at the mean, maximum-minimum and standard deviation of the data of respective variables, then we use the Pearson’s correlation test to show the negative or positive correlation between the dependent variable (DV) and independent variables (IVs) and finally we employ the multiple regressions test to reveal the significant or insignificant relationships together with the positive or negative impacts of each IV on the DV. The main findings from the correlation test indicate EPR, EXC and IRS have negative correlations, where EXC has moderate correlation whilst the other two have very weak correlations with GDPGR. Meanwhile, CPI shows positive but very weak correlation with GDPGR. Meanwhile, the regressions test reveals EPR and IRS positively influence GDPGR whilst EXC and CPI have negative impacts on the Malaysian economic growth. However, only EXC is found to be significant out of the four determinants. The results imply the higher employment creates larger productivity to the economy and the more stable monetary policy (IRS) the better contribution to economic growth. On contrary, depreciation of MYR against USD and fluctuation in price level of goods and services lead to economic instability. The findings have significant implications for policy makers, businesses and investors in their decision making. For future research, we suggest to test on other economic variables such as industrial production index, foreign direct investment and money supply together with non-economic variables such as human development index, corruption perception index and global peace index of the country. We also suggest future studies to apply other methodologies for robustness. Comparison with other countries will also make the findings more meaningful.

Estimating excess mortalities due to the COVID-19 pandemic in Malaysia between January 2020 and September 2021

Excess mortalities are a more accurate indicator of true COVID-19 disease burden. This study aims to investigate levels of excess all-cause mortality and their geographic, age and sex distributions between January 2020-September 2021. National mortality data between January 2016 and September 2021 from the Department of Statistics Malaysia was utilised. Baseline mortality was estimated using the Farrington algorithm and data between 1 January 2016 and 31 December 2019. The occurrence of excess all-cause mortality by geographic-, age- and sex-stratum was examined from 1 January 2020 to 30 September 2021. A sub-analysis was also conducted for road-traffic accidents, ethnicity and nationality. Malaysia had a 5.5–23.7% reduction in all-cause mortality across 2020. A reversal is observed in 2021, with an excess of 13.0–24.0%. Excess mortality density is highest between July and September 2021. All states and sexes reported excess trends consistent with the national trends. There were reductions in all all-cause mortalities in individuals under the age of 15 (0.4–8.1%) and road traffic accident-related mortalities (36.6–80.5%). These reductions were higher during the first Movement Control Order in 2020. Overall, there appears to be a reduction in all-cause mortality for Malaysia in 2020. This trend is reversed in 2021, with excess mortalities being observed. Surveillance of excess mortalities can allow expedient detection of aberrant events allowing timely health system and public health responses.