Loss of Employment, Lockdown Measures and Government Responses in Malaysia during the Covid-19 Pandemic: A Note

In this paper, we use daily administrative data from January 25, 2020 to December 31, 2020 to examine the relationship between job losses and the Malaysian lockdown measures. The Auto Regressive Distributed Lag (ARDL) approach is used to estimate both the long-run and short-run models. The results of the Bounds F-test for cointegration reveal that there is a long-run link between job losses and the Malaysian government lockdown measures (both linear and non-linear). The positive association between job loss and lockdown measures shows that as the lockdown gets tighter, more people will lose their jobs. However, as time passes, especially in conjunction with the government stimulus package programmes, job losses decrease.

COVID-19 PANDEMIC: THE MALAYSIAN GOVERNMENT'S APPROACH IN MANAGING NATIONAL SECURITY

Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) coronavirus or better known as Covid-19 was first detected on 17 November 2019 in Hubei province, China, and was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. Until 1 November 2020, the Covid-19 pandemic has spread to 215 countries worldwide where the total number of cases recorded is 45,942,902 cases and 1,192,644 deaths. In Malaysia, a total of 31,548 cases and 249 deaths were recorded. The Covid-19 pandemic has caused economic paralysis and affected the lives of communities around the world. The main objective that will be discussed in this article is the Malaysian government's approach in dealing with the Covid-19 pandemic to ensure that the country's socio-economy is not affected where it could affect national security. In this article, the method of collecting information is through references in websites, e-journals, e-newspapers, and related reports. The results show that the Malaysian government has taken two main approaches in managing national security, namely through the health and economy of the people. The health approach is through efforts to curb the Covid-19 epidemic from spreading further in the country which can have a negative impact on the economy and society of Malaysians. Next, the people's economic approach implemented is through the People's Economic Stimulus Package announced by the government to help the people affected by the Covid-19 epidemic and ensure that the country's economy can be restored. This approach has succeeded in maintaining national peace as well as preventing the occurrence of things that could affect national security such as riots or demonstrations by the people due to dissatisfaction with the government.

Dinamika Pembangunan Ekonomi Di Madura Pada Era Kebiasaan Baru Covid-19; Tantangan dan Peluangnya

This study examines the challenges and opportunities for development in Madura amid the adoption of a new habit era due to the global pandemic, Covid-19. There are three main problems examined in this study; Econimi development in Madura, the era of new habits, and Covid-19. By using qualitative research and analysis based on the sociological theory of development, this study finds a number of findings; first, the dynamics of development in Madura in the midst of the adoption of a new habit era in general experienced quite serious upheavals or shocks, especially in the economic development sector. Second, the opportunities for strengthening Madura development in the midst of the new custom era are relatively open. This is influenced by the geographical condition of Madura as an archipelago which has abundant natural-social wealth, especially those originating from the maritime sector. Empowerment and utilization of natural resources, especially those based on local wisdom, can become a strategy in the midst of turbulent national-global economic chains; Third, to maximize these efforts, it is necessary to have collaboration and synergy with related parties, especially the government. In addition to ensuring the implementation of health protocols, it is equally important to ensure the financial power of the community. Providing stimulus packages, both fiscal and non-fiscal, so that later it can push the wheels of the regional economy. This is at the same time the biggest challenge, how to ensure that the distribution of the stimulus package is carried out in a measured, fast, and on target, as well as touching on fundamental sectors. (Studi ini mengkaji tantangan dan peluang pembangunan ekonomi di Madura di tengah diterapkannya era kebiasaan baru akibat pandemi global, Covid-19. Terdapat tiga permasalahan pokok yang dikaji dalam penelitian ini; pembangunan Madura, era kebiasaan baru, dan Covid-19. Dengan mempergunakan jenis penelitian kualitatif dan analisa berdasarkan teori sosiologi pembangunan, kajian ini mendapati sejumlah temuan; pertama, dinamika pembangunan di Madura di tengah penerapan era kebiasaan baru secara umum mengalami gejolak atau guncangan cukup serius, khususnya di sektor pembangunan ekonomi. Kedua, peluang penguatan pembangunan di Madura di tengah diberlakukannya era kebiasaan baru relatif terbuka. Demikian dipengaruhi oleh kondisi geografis Madura sebagai daerah kepulauan yang mempunyai kekayaan alam-sosial cukup melimpah, terutama yang bersumber dari sektor kemaritiman. Pemberdaayaan dan pemanfaatan kekayaan alam khususnya yang berbasis kearifan lokal dapat menjadi strategi di tengah gejolak rantai ekonomi nasional-global yang tidak menentu; Ketiga, untuk memaksimalkan upaya tersebut, perlu adanya kolaborasi dan sinergitas antara pemerintah dan elemen masyarakat. Selain memastikan jalannya protokol kesehatan, pun tak kalah pentingnya adalah memastikan daya finansial masyarakat. Memberi paket stimulus baik fiskal maupun nonfiskal, sehingga nantinya dapat mendorong roda perekonomian daerah. Ini sekaligus menjadi tantangan terbesar, bagaimana memastikan distribusi paket stimulus tersebut dilakukan secara terukur, cepat, dan tepat sasaran, serta menyentuh sektor-sektor fundamental.)

COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques

Background: The Malaysian government reacted to the pandemic’s economic effect with the Prihatin Rakyat Economic Stimulus Package (ESP) to cushion the novel coronavirus 2019 (COVID-19) impact on households. The ESP consists of cash assistance, utility discount, moratorium, Employee Provident Fund (EPF) cash withdrawals, credit guarantee scheme and wage subsidies. A survey carried out by the Department of Statistics Malaysia (DOSM) shows that households prefer different types of financial assistance. These preferences forge the need to effectively customise ESPs to manage the economic burden among low-income households. In this study, a recommender system for such ESPs was designed by leveraging data analytics and machine learning techniques. Methods: This study used a dataset from DOSM titled “Effects of COVID-19 on the Economy and Individual - Round 2,” collected from April 10 to April 24, 2020. Cross-Industry Standard Process for Data Mining was followed to develop machine learning models to classify ESP receivers according to their preferred subsidies types. Four machine learning techniques—Decision Tree, Gradient Boosted Tree, Random Forest and Naïve Bayes—were used to build the predictive models for each moratorium, utility discount and EPF and Private Remuneration Scheme (PRS) cash withdrawals subsidies. The best predictive model was selected based on F-score metrics. Results: Among the four machine learning techniques, Gradient Boosted Tree outperformed the rest. This technique predicted the following: moratorium preferences with 93.8% sensitivity, 82.1% precision and 87.6% F-score; utilities discount with 86% sensitivity, 82.1% precision and 84% F-score; and EPF and PRS with 83.6% sensitivity, 81.2% precision and 82.4% F-score. Households that prefer moratorium subsidies did not favour other financial aids except for cash assistance. Conclusion: Findings present machine learning models that can predict individual household preferences from ESP. These models can be used to design customised ESPs that can effectively manage the financial burden of low-income households.

COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques

Background: The Malaysian government reacted to the pandemic’s economic effect with the Prihatin Rakyat Economic Stimulus Package (ESP) to cushion the novel coronavirus 2019 (COVID-19) impact on households. The ESP consists of cash assistance, utility discount, moratorium, Employee Provident Fund (EPF) cash withdrawals, credit guarantee scheme and wage subsidies. A survey carried out by the Department of Statistics Malaysia (DOSM) shows that households prefer different types of financial assistance. These preferences forge the need to effectively customise ESPs to manage the economic burden among low-income households. In this study, a recommender system for such ESPs was designed by leveraging data analytics and machine learning techniques. Methods: This study used a dataset from DOSM titled “Effects of COVID-19 on the Economy and Individual - Round 2,” collected from April 10 to April 24, 2020. Cross-Industry Standard Process for Data Mining was followed to develop machine learning models to classify ESP receivers according to their preferred subsidies types. Four machine learning techniques—Decision Tree, Gradient Boosted Tree, Random Forest and Naïve Bayes—were used to build the predictive models for each moratorium, utility discount and EPF and Private Remuneration Scheme (PRS) cash withdrawals subsidies. The best predictive model was selected based on F-score metrics. Results: Among the four machine learning techniques, Gradient Boosted Tree outperformed the rest. This technique predicted the following: moratorium preferences with 93.8% sensitivity, 82.1% precision and 87.6% F-score; utilities discount with 86% sensitivity, 82.1% precision and 84% F-score; and EPF and PRS with 83.6% sensitivity, 81.2% precision and 82.4% F-score. Households that prefer moratorium subsidies did not favour other financial aids except for cash assistance. Conclusion: Findings present machine learning models that can predict individual household preferences from ESP. These models can be used to design customised ESPs that can effectively manage the financial burden of low-income households.

The SOE Channel of Monetary Policy Transmission: Evidence from China's Economic Stimulus Package

We examine the state-owned enterprises (SOEs) channel in monetary policy transmission in the context of China's 2008 stimulus package. Using a difference-in-difference approach, we show that the higher SOE share in the cities after the stimulus package, the more bank loans issued in the cities. Furthermore, we find that the role of SOEs in monetary policy transmission is more significant in underdeveloped cities and cities with a high level of government intervention. We adopt propensity score matching difference-in-difference to deal with potential endogeneity problem. The baseline results also survive a series of robustness tests.

Inclusive housing programmes to stimulate the economy and improve health outcomes after COVID-19

Countries around the globe have experienced the health and economic consequences of the COVID-19 pandemic. In many countries in the Global South, interventions in the housing sector can support public and private investments and have large economic stimulus effects. This article develops a series of principles that would ensure investments in housing not only serve as economic stimuli but deliver the basis for long-term improvement in housing conditions and overall community wellbeing and health by being inclusive and sustainable. This article proposes five principles and illustrates how to apply them in core areas that would typically be included in a housing stimulus package: 1) focus on supporting housing for the underserved middle- and lower-income households; 2) inclusion of both ownership and rental markets; 3) inclusion of both formal and informal housing markets; 4) incorporating communities; and 5) avoiding long-term negative effects on housing and housing finance market development.

The Impact of the Lockdown on the Greek Economy and the Role of the Recovery Fund

We develop a microfounded macroeconomic model that embeds the key features of the Greek economy. After calibrating the model to Greek data over 1995–2019, we assume that the economy is initially in the year 2019 and then quantify the adverse economic impact of the lockdown measures taken to control the spread of the pandemic, as well as the implications of the various policy measures (at national and EU level) taken to cushion the impact of the economic hit. We give quantitative answers to questions like: What will be the size and duration of the economic downturn? What are the implications of the national fiscal stimulus? What will be the role of the fiscal transfers coming from the European Recovery Fund? Our results imply that the national fiscal stimulus package adopted so far is helpful but, for the Greek economy to enter an era of sustainable growth, a mix of policies is also needed that combines: (i) a growth-enhancing fiscal mix (ii) product market deregulation (iii) a socially productive use of the resources coming from the Recovery Fund.

Impact of COVID-19 on Agriculture and Allied Sectors

Impact of Corona virus outbreak on mankind is serious. Apart from health issues and social life stand still, global economy has been affected drastically. Many sectors have been hit by this pandemic and agriculture and allied sectors are no exception. Issues such as shortage of labour, restricted access to markets have been tremendously affected this sector. Many of its frailties were exposed during the course but the resilient cultivation sector surfaced with some promising results after a good monsoon and aggressive response demonstrated by the government to support the sector. Government excluded several farming activities such as farm operations, agribusiness, dairy, poultry and fishery from lockdown limitations after the lockdown extended in May, 2020. Pandemic also presented a great opportunity to think over and evaluate the hidden potential of respective sectors. Solemn efforts are required for innovation and technical up gradation of agricultural operations to alleviate the impacts of the COVID-19 pandemic. As India struggles to uplift the distressed economy, government announced economic stimulus package worth INR 20, 00,000 crore under Atma Nirbhar Bharat Campaign. Long term impacts of this campaign are estimated to develop agriculture and allied sectors with major emphasis on quality products and increased exports of agriculture commodities.