scholarly journals The Impact of Mobility Restriction Strategies in the Control of the COVID-19 Pandemic: Modelling the Relation between COVID-19 Health and Community Mobility Data

2021 ◽  
Vol 18 (19) ◽  
pp. 10560
Author(s):  
Adil Al Wahaibi ◽  
Amal Al Maani ◽  
Fatma Alyaquobi ◽  
Abdullah Al Manji ◽  
Khalid Al Harthy ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Movement Restriction ◽  
Mobility Data ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Community Mobility ◽  
Lag Model ◽  
Level 3 ◽  
Evaluation And Monitoring ◽  
The Impact

Background: Non-pharmaceutical interventions (NPIs), particularly mobility restrictions, are mainstay measures for the COVID-19 pandemic worldwide. We evaluated the effects of Oman’s mobility restriction strategies to highlight their efficacy in controlling the pandemic. Methods: Accessible national data of daily admissions and deaths were collected from 1 April 2020 to 22 May 2021. Google Community Mobility Report (CMR) data were downloaded for the same period. Among six CMR categories, three were used and reduced to one index—the community mobility index (CMI). We used a generalised linear model with a negative binomial distribution combined with a non-linear distributed lag model to investigate the short-term effects of CMI on the number of admitted PCR-confirmed COVID-19 cases and deaths, controlling for public holidays, day of the week, and Eid/Ramadan days. Results: We demonstrated the feasibility of using CMRs in the evaluation and monitoring of different NPIs, particularly those related to movement restriction. The best movement restriction strategy was a curfew from 7 p.m. to 5 a.m. (level 3 of CMI = 8), which had a total reduction of 35% (95% confidence interval (CI); 25–44%) in new COVID-19 admissions in the following two weeks, and a fatality reduction in the following four weeks by 52% (95% CI; 11–75%). Conclusion: Evening lockdown significantly affected the course of the pandemic in Oman which lines up with similar studies throughout the world.

scholarly journals The impact of education tax and investment in human capital on economic growth in Nigeria

2020 ◽  
Vol 3 (2) ◽  
pp. 77-86
Author(s):  
Abubakar Aminu ◽  
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Tertiary Education ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Long Run ◽  
Lag Model ◽  
The Government ◽  
Capital Development ◽  
The Impact

This paper investigated the impact of education tax and investment in human capital on economic growth in Nigeria utilizing the Non-Linear Autoregressive Distributed Lag Model of cointegration covering the period of 25 years from 1995 to 2019. The findings reveal that education tax and investment in human capital have positive and significant effect on the growth of the Nigerian economy over the sampled period. The paper recommends that in order to boost the economy, Nigeria would need to, among other policy frameworks, provide a suitable environment for ensuring macro-economic stability through effective utilization of income from education tax that will encourage increased investment in human capital in the public sector. In addition to income from education tax, for effective and speedy economic growth and development in Nigeria, the government, beneficiaries (students/parents), employers of labor and other stakeholders in the society should share the responsibility for financing primary, secondary and tertiary education, so as to provide a solid foundation for human capital development. However, as revealed in this paper, the contribution of education tax and investment in human capital is most likely to be realized over a long-run period than in the short term. Keywords: Education Tax; Investment; Human capital; Economic growth

scholarly journals Community movement and COVID-19: a global study using Google's Community Mobility Reports

2020 ◽  
Vol 148 ◽  
Author(s):  
M. Sulyok ◽  
M. Walker
Keyword(s):  
Western Europe ◽  
Disease Incidence ◽  
Information Criteria ◽  
Model Quality ◽  
Distributed Lag ◽  
The North ◽  
Distributed Lag Model ◽  
Community Mobility ◽  
Lag Model ◽  
Industrialised Countries

Abstract Google's ‘Community Mobility Reports’ (CMR) detail changes in activity and mobility occurring in response to COVID-19. They thus offer the unique opportunity to examine the relationship between mobility and disease incidence. The objective was to examine whether an association between COVID-19-confirmed case numbers and levels of mobility was apparent, and if so then to examine whether such data enhance disease modelling and prediction. CMR data for countries worldwide were cross-correlated with corresponding COVID-19-confirmed case numbers. Models were fitted to explain case numbers of each country's epidemic. Models using numerical date, contemporaneous and distributed lag CMR data were contrasted using Bayesian Information Criteria. Noticeable were negative correlations between CMR data and case incidence for prominent industrialised countries of Western Europe and the North Americas. Continent-wide examination found a negative correlation for all continents with the exception of South America. When modelling, CMR-expanded models proved superior to the model without CMR. The predictions made with the distributed lag model significantly outperformed all other models. The observed relationship between CMR data and case incidence, and its ability to enhance model quality and prediction suggests data related to community mobility could prove of use in future COVID-19 modelling.

scholarly journals PENDUGAAN PARAMETER MODEl DISTRIBUTED LAG POLA POLINOMIAL MENGGUNAKAN METODE ALMON

2021 ◽  
Vol 15 (4) ◽  
pp. 761-772
Author(s):  
Fitria Virgantari ◽  
Wilda Rahayu
Keyword(s):  
Regression Model ◽  
Time Series Data ◽  
Operating Cost ◽  
Series Data ◽  
Operating Income ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Lag Model ◽  
Forecast Time ◽  
The Impact

The distributed lag model is a regression  model that describes the relationship between the dependent variable of a given period and the independent variables of a certain or previous periods. The model can be used to determine the impact of the independent variable to dependent variables over time and forecast time series data for the next periods. There are two forms of distributed lag model that have been widely proposed in the estimation of distributed lag regression model. The first form  is proposed by Koyck and the second form by Almon. This paper aims to apply the Almon model to examine the effect of  the ratio of BOPO (Operating Cost and Operating Income) to the ROA (Return on Asset) of a government bank based on quarterly data, to estimate its parameters, to examine the feasibility of the model, and to predict the next quarter.  Results shows that distributed lag model is  = 10.110 - 0.078  + 0.015  + 0.026  – 0.045  with Yt is ROA, and Xt is the ratio BOPO  on the 1st quarter until the previous 3 quarters. The model is quite good according to the determination coefficient that is 0.75, no autocorrelation in the model, t test and F test are also significant. Based on the model, the value of ROA ratio next quarter predicted 4.63%. The decrease in profitability ROA ratio is due to an increase in interest expense while interest income can not compensate

scholarly journals Does Inflation have Effect on Economic Growth? Empirical Evidence from Pakistan

2020 ◽  
Vol 1 (1) ◽  
pp. 41-52
Author(s):  
Raima Nazar ◽  
Aisha Ambreen ◽  
Sumbal Sabtain
Keyword(s):  
Economic Growth ◽  
Inflation Rate ◽  
Negative Impact ◽  
Annual Data ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Lag Model ◽  
Auto Regressive ◽  
The Impact ◽  
Model Technique

Pakistan is one of the developing countries instead of possessing large amount of natural resources like mines, reserves of coal, adequate amount of minerals and oil, But, Pakistan is still deprived of basic necessities of life and suffering from extreme inflation in the country. Therefore, this study is an attempt to synopsis the impact of inflation on GDP of Pakistan. This study mainly focus on the inflation rate from the period 1980 to 2016, time series annual data has been employed in the study. The Auto Regressive Distributed Lag Model technique is applied in the study in order to estimate and analyze the data. The study concludes that inflation indicates negative impact on the GDP of Pakistan and it can only be minimized if all resources of the country are properly allocated and fully utilized.

scholarly journals Research on the Impact of Green Finance and Fintech in Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Zheng He ◽  
Zhengkai Liu ◽  
Hui Wu ◽  
Xiaomin Gu ◽  
Yuanjun Zhao ◽  
...  
Keyword(s):  
Smart Cities ◽  
Economic Transformation ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Green Finance ◽  
Green Development ◽  
Lag Model ◽  
The Cost ◽  
The Impact ◽  
Financial Technology

The green development level reflected in the green finance index and the evaluation of the degree of green development in smart cities have important practical effects on economic transformation. For promoting the transformation and upgrading of finance, we select 2013–2019 data and construct a distributed lag model to analyse the important role played by green finance and financial technology in the construction of smart cities. In the paper, we find green finance promotes the construction of smart cities, and only it will not appear until nine months late. Financial technology has an opposite impact on the construction of smart cities, this is mainly because the research and marketization of financial technology are higher, and the cost is also higher. This influence will appear in the next 14 months.

scholarly journals Impact of Environmental Investments and Air Protection Costs on the Sustainable Development of Coal Mining Regions

2019 ◽  
Vol 105 ◽  
pp. 02003 ◽  
Author(s):  
Elena Morozova ◽  
Anatoly Akulov ◽  
Timur Logunov
Keyword(s):  
Sustainable Development ◽  
Regression Equations ◽  
Coupling Equation ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Lag Model ◽  
Low Efficiency ◽  
The Impact ◽  
Mining Regions ◽  
Stationary Sources

The transition to sustainable development of mining regions depends on the size and effectiveness of environmental investments. This study examines the impact of investments and current costs of air protection on the amount of air emissions from stationary sources. We used data on investments in atmospheric air protection, current costs of air protection, and amounts of air emission in 12 mining regions of Russia. The impact of investment and emission costs was simulated using standard pairwise regression equations and the Almon distributed lag model. The statistical insignificance of the models has been established, both in terms of the form of coupling equation and the significance of most coefficients with explanatory variables. The distributed lag model using data on investments in air protection over five years is also statistically insignificant. The paper also discusses the impact of investments and current costs on the specific emission amount per 1 ruble of the gross regional product. The model of pairwise linear regression and other possible forms of the coupling equation in this case are statistically insignificant. The study found that investments and current costs do not affect emissions from stationary sources. This suggests a lack of investments in the air protection and a low efficiency of their use.

scholarly journals Validation of J-Curve Hypothesis in the Nigerian Non Oil Sector

2015 ◽  
Vol 8 (1) ◽  
pp. 15
Author(s):  
Jude O. Obasanmi ◽  
Fidelis O. Nedozi
Keyword(s):  
Exchange Rate ◽  
Unit Root Test ◽  
Policy Makers ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
J Curve ◽  
Oil Export ◽  
Lag Model ◽  
Oil Sector ◽  
The Impact

J-Curve is a term used to describe the impact of currency devaluation on a country’s balance of trade. In carrying out the study, two objectives stated which are; the validation of the j-curve hypothesis in the short (SR) and long runs (LR). Also, the researcher used the OLS in addition to distributed lag model because exchange rate devaluation does not take effect immediately giving room for lag model effect. The study span from 1985-2014. The study adopted its model from Rose and Yellen (1989) and Rose (1990). The unit root test was used to determine the stationarity of the data. From the results, the OLS result showed delayed J-curve hypothesis. Under the distributed lag (DL), the result shows obedience to the J-curve hypothesis. It is concluded that, policy makers should implement the theory only when the aggregate exchange rate differential between export (non oil) and import (all) is continuously greater than one or equal to one in favour of export (non oil export). One of the recommendations of the study is that policy makers should know that in the current competitive globe, no importing economy will relax to see its economy be a dumping ground (import bias), so superior trade policies should be advocated and implemented. The sustenance of development is one of Nigeria’s challenges. The major policy implication of the study is that Nigeria should diversify the economy, deepen its non oil export and improve its infrastructural base.

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