Ageing Population's Impact on Economic Growth in Malaysia From 1981 to 2019: Evidence From an Autoregressive Distributed Lag Approach

This study investigates the impact of the ageing population on the economic growth for short- and long-run estimations in Malaysia, by using time series data from 1981 to 2019. This study adopts the autoregressive distributed lag (ARDL) method with the Bound test approach for the long-run estimation and the vector error correction model for the short-run estimation. Several econometric diagnostic tests were applied for validation and the appropriate model specification basis. The estimated result of this work indicates that the age dependency ratio proxy for the ageing population variable has a significant negative impact on economic growth in Malaysia. A 1% increase in old age dependency will decline gross domestic product's (GDP's) growth by an average of 6.6043% at the 5% level of significance. Hence, an increase in the ageing population will impede economic growth. Although controlled variables (e.g., physical capital, labour participation, and human capital) have a significant positive impact on economic growth in Malaysia, there is evidence of a long- and short-run relationship between economic growth and the ageing population variable, and also the control variable.

Study of fiscal decentralization, macroeconomic stability and regional growth in Indonesia

Indonesia has been implementing fiscal decentralization since 2001. In theory, fiscal decentralization affected macroeconomic stability and economic growth—this study using data panels at the provincial level from 2010 to 2013. In the relationship between fiscal decentralization and macroeconomic stability with control variable income, significant variables are income to GRDP, GRDP per capita, and population. If control variable expenditure, significant variables are expenditure to GRDP, GRDP per capita, and population. In the model that analyzes fiscal decentralization and economic growth with control variable income, significant variables are income to GRDP, consumption to GRDP, and population. Meanwhile, if control variable expenditure, significant variables are expenditure to GRDP, consumption to GRDP, and population. By using sensitivity analysis, the population variable is a high priority. Therefore stakeholders should treat population variables carefully.

Analsis determinan yang mempengaruhi perdagangan luar negeri Indonesa terhadap dua negara yang terlibat perang dagang Amerika Serikat VS China

The purpose of this study is to analyze how Indonesia's exports and imports compared to the United States and China and to investigate how the exchange rate, labor force, and population influence Indonesia's imports from China and the United States. The results show that Indonesia's exports to the United States and Indonesia's exports to China are 2.02, while the average comparison of Indonesian imports from the United States and Indonesia's imports from China is 1.31. the average is more significant when compared to Indonesia's exports and imports with China. Based on the regression results, the exchange rate variable has a significant negative effect on Indonesia's exports and imports with the United States and China. The labor variable has a significant positive impact on Indonesia's exports and imports to the United States and China. In contrast, the population variable significantly affects Indonesia's exports to the United States. It does not substantially affect Indonesian imports from the United States and does not dramatically affect Indonesia's exports and imports with China.

Spatial Approach to Contribution of Public Policies to the Dynamization of the Rural Population

In this article we will analyze the results, in terms of population, of the Common Agricultural Policy of the European Union, in a small European region, of one million inhabitants, with geographical characteristics typical of mountain agriculture. We will use spatial econometric techniques to verify whether the hypothesis that public spending destined for direct subsidization contributes positively to the territorial dynamics of certain relevant economic variables is fulfilled, specifically we will study in our case the population variable. From a methodological point of view, we will use several complementary approaches that give solidity to the results, always from the focus of spatial econometrics, essential when working with territorial data at a low level of disaggregation. On the one hand, we will carry out an exploratory spatial data analysis, which will allow us to detect possible patterns of spatial dependence, and then move on to a confirmatory analysis that will consider both, autocorrelation (models of lag and spatial error) and spatial heterogeneity (switching regressions). In addition to this cross-sectional data approach, which is based on a method of estimating the particular to the general, we will also use the estimation of spatial models of panel data, to include a temporal approach, with a method of estimating the general to the particular. The best results are obtained with a Spatial Durbin Model.

Analisa Pengaruh Jumlah Penduduk terhadap Jumlah Angkatan Kerja pada Kota Bekasi Menggunakan Metode Regresi Linear

Abstrak: Bertambahnya jumlah populasi penduduk maka dibutuhkan juga penambahan lapangan pekerjaan, agar jumlah angkatan kerja yang bekerja semakin meningkat. Penelitian ini bertujuan menunjukkan pengaruh populasi penduduk pada jumlah Angkatan kerja yang bekerja di kota Bekasi dari tahun 2011 sampai tahun 2020. Analisa tersebut dilakukan dengan menggunakan metode regresi linier sederhana, tingkat populasi penduduk (X) dan Angkatan kerja yang bekerja (Y) di kota Bekasi tahun 2011-2020. Dari data dapat disimpulkan bahwa variabel jumlah populasi (X) telah memiliki pengaruh positif pada variabel jumlah Angkatan kerja yang bekerja di kota Bekasi. Pada penelitian ini juga diperoleh nilai korelasi antara Jumlah penduduk dengan Jumlah Angkatan kerja yang bekerja, yaitu sebesar 0.942. Dari hasil pengolahan dapat disimpulkan bahwa terdapat hubungan korelasi yang positif dan sangat kuat antara jumlah penduduk kota Bekasi dengan jumlah Angkatan kerja di Kota Bekasi yang bekerja. Jika Jumlah penduduk meningkat maka jumlah Angkatan kerja di Kota Bekasi yang bekerja juga mengalami peningkatan. Kata kunci: angkatan kerja, jumlah penduduk, regresi Abstract: As the population increases, additional employment opportunities are also needed, so that the number of the working force will increase. This study aims to show the effect of population on the number of the workforce working in the city of Bekasi from 2011 to 2020. The analysis was carried out using a simple linear regression method, the population level (X) and the working force (Y) in the city of Bekasi. year 2011-2020. From the data it can be concluded that the population variable (X) has a positive influence on the variable number of the workforce working in the city of Bekasi. In this study also obtained the correlation value between the number of residents with the number of working force, which is equal to 0.942. From the results of the processing, it can be concluded that there is a positive and very strong correlation between the population of the city of Bekasi and the number of the workforce in the city of Bekasi who work. If the population increases, the number of the workforce in Bekasi City who work also increases. Keywords: workforce, total population, regression

The Reliability of Metagenome-Assembled Genomes (MAGs) in Representing Natural Populations: Insights from Comparing MAGs against Isolate Genomes Derived from the Same Fecal Sample

ABSTRACT The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock data sets of known composition. However, these mock data sets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population-variable genes (those shared by >10% but <90% of the members of the population) as efficiently as core genes (those shared by >90% of the members). To address these issues, we compared the gene variabilities of pathogenic Escherichia coli isolates from eight diarrheal samples, for which the isolate was the causative agent, against their corresponding MAGs recovered from the companion metagenomic data set. Our analysis revealed that MAGs with completeness estimates near 95% captured only 77% of the population core genes and 50% of the variable genes, on average. Further, about 5% of the genes of these MAGs were conservatively identified as missing in the isolate and were of different (non-Enterobacteriaceae) taxonomic origin, suggesting errors at the genome-binning step, even though contamination estimates based on commonly used pipelines were only 1.5%. Therefore, the quality of MAGs may often be worse than estimated, and we offer examples of how to recognize and improve such MAGs to sufficient quality by (for instance) employing only contigs longer than 1,000 bp for binning. IMPORTANCE Metagenome assembly and the recovery of metagenome-assembled genomes (MAGs) have recently become common tasks for microbiome studies across environmental and clinical settings. However, the extent to which MAGs can capture the genes of the population they represent remains speculative. Current approaches to evaluating MAG quality are limited to the recovery and copy number of universal housekeeping genes, which represent a small fraction of the total genome, leaving the majority of the genome essentially inaccessible. If MAG quality in reality is lower than these approaches would estimate, this could have dramatic consequences for all downstream analyses and interpretations. In this study, we evaluated this issue using an approach that employed comparisons of the gene contents of MAGs to the gene contents of isolate genomes derived from the same sample. Further, our samples originated from a diarrhea case-control study, and thus, our results are relevant for recovering the virulence factors of pathogens from metagenomic data sets.

Weighted proportional mean inactivity time model

<abstract><p>In this paper, a mean inactivity time frailty model is considered. Examples are given to calculate the mean inactivity time for several reputable survival models. The dependence structure between the population variable and the frailty variable is characterized. The classical weighted proportional mean inactivity time model is considered as a special case. We prove that several well-known stochastic orderings between two frailties are preserved for the response variables under the weighted proportional mean inactivity time model. We apply this model on a real data set and also perform a simulation study to examine the accuracy of the model.</p></abstract>

Pengaruh Urbanisasi Terhadap Penurunan Kemiskinan di Indonesia

Urbanization and poverty are two important aspects closely linked to sustainable development goals. Urbanization in Indonesia is still far from improving migrant welfare as well as their destination regions. Every 1% growth of urbanization in Indonesia can only increase 4% of GDP per capita. Low economic benefits resulted from urbanization in Indonesia merely shift rural poor to become urban poor. The purpose of this study was to analyze the effect of urbanization on poverty reduction in Indonesia, both in the regional aggregate and at the rural and urban levels as the origin and destination regions of urbanization. This study used secondary data of population and poverty from Population Census (SP), the Inter-Census Population Survey (SUPAS), and the National Socio-Economic Survey (SUSENAS). Data analysis was performed using regionalization techniques, Primacy Index, Lorenz Curve, Geographic Information System (GIS), and simple linear regression. The results showed that the rate of urbanization had a positive relationship with per capita income and the population of urban poor, but had a negative relationship with the population of rural poor. A unit increase in urban population variable percentage would increase the average GDP/capita variable by 0,466. This would be followed by an increase in the average urban poor population variable by 0,447 and a reduction in the average rural poor population variable by 0,705.

The socio-economic catalysers of COVID-19 pandemic

The COVID-19 pandemic was triggered on December 2019 in the city of Wuhan, China, spreading across the world causing global economic crisis and public health emergency. One could ask: what are the socio-economic factors that catalyse the spread of the disease and why are some countries more affected by the COVID-19 pandemic. Therefore, the goal of this paper is to investigate these socio-economic catalysers of the COVID-19 spread. For that purpose, a cross-country regression analysis was conducted at three time points (April 1st, 2020, April 15th 2020 and April 29th, 2020) using OLS, Tobit and PPML estimators. The results of the analysis have shown that countries with higher gross domestic product per capita, population, HDI and HFI indices have been hardely hit with the global COVID-19 pandemic. When some variables were transformed with by dividing it with the population variable, POPDEN and TOUR variables appeared to be significant. The AGE variable was important in the model taking into account total deaths due to the COVID-19 infection. The limitations of the paper are related to data unavailability for some variables in the most recent year. The results obtained from this analysis should be repeated, taking into account other time points and additional COVID-19 socioeconomic catalysers.

PENGARUH JUMLAH PENDUDUK TERHADAP PERTUMBUHAN EKONOMI DI KOTA LHOKSEUMAWE

This research was conducted in Lhokseumawe City and the aim is to see the effect of population on economic growth in the city of Lhokseumawe. The data used in this research is secondary data sourced from the Central Statistics Agency (BPS) for 18 years from 2001-2018. The data analysis method used in this research is simple linear regression. The results of this study indicate that the population variable does not have a negative effect on population growth and the magnitude of the influence of the population variable on economic growth is 0.0938 (9.38%).