scholarly journals COVID-19 Transmission: Bangladesh Perspective

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1793
Author(s):  
Masud M A ◽  
Md Hamidul Islam ◽  
Khondaker A. Mamun ◽  
Byul Nim Kim ◽  
Sangil Kim
Keyword(s):  
Time Series Data ◽  
Profile Likelihood ◽  
Least Square ◽  
Series Data ◽  
Time Intervals ◽  
Identification Rate ◽  
The Public ◽  
Estimated Parameters ◽  
Likelihood Approach ◽  
Developed Nations

The sudden emergence of the COVID-19 pandemic has tested the strength of the public health system of the most developed nations and created a “new normal”. Many nations are struggling to curb the epidemic in spite of expanding testing facilities. In this study, we consider the case of Bangladesh, and fit a simple compartmental model holding a feature to distinguish between identified infected and infectious with time series data using least square fitting as well as the likelihood approach; prior to which, dynamics of the model were analyzed mathematically and the identifiability of the parameters has also been confirmed. The performance of the likelihood approach was found to be more promising and was used for further analysis. We performed fitting for different lengths of time intervals starting from the beginning of the outbreak, and examined the evolution of the key parameters from Bangladesh’s perspective. In addition, we deduced profile likelihood and 95% confidence interval for each of the estimated parameters. Our study demonstrates that the parameters defining the infectious and quarantine rates change with time as a consequence of the change in lock-down strategies and expansion of testing facilities. As a result, the value of the basic reproduction number R0 was shown to be between 1.5 and 12. The analysis reveals that the projected time and amplitude of the peak vary following the change in infectious and quarantine rates obtained through different lock-down strategies and expansion of testing facilities. The identification rate determines whether the observed peak shows the true prevalence. We find that by restricting the spread through quick identification and quarantine, or by implementing lock-down to reduce overall contact rate, the peak could be delayed, and the amplitude of the peak could be reduced. Another novelty of this study is that the model presented here can infer the unidentified COVID cases besides estimating the officially confirmed COVID cases.

scholarly journals Estimating the function of oscillatory components in SSA-based forecasting model

2019 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Winita Sulandari ◽  
Subanar Subanar ◽  
Suhartono Suhartono ◽  
Herni Utami ◽  
Muhammad Hisyam Lee
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Real Data ◽  
Least Square ◽  
Series Data ◽  
Forecasting Model ◽  
Data Series ◽  
Ordinary Least Square ◽  
Seasonal Time Series ◽  
Estimated Parameters

The study of SSA-based forecasting model is always interesting due to its capability in modeling trend and multiple seasonal time series. The aim of this study is to propose an iterative ordinary least square (OLS) for estimating the oscillatory with time-varying amplitude model that usually found in SSA decomposition. We compare the results with those obtained by nonlinear least square based on Levenberg Marquardt (NLM) method. A simulation study based on the time series data which has a linear amplitude modulated sinusoid component is conducted to investigate the error of estimated parameters of the model obtained by the proposed method. A real data series was also considered for the application example. The results show that in terms of forecasting accuracy, the SSA-based model where the oscillatory components are obtained by iterative OLS is nearly the same with that is obtained by the NLM method.

Revisiting the growth effects of government bonds in the emerging capital market.

2019 ◽  
Vol 3 (1) ◽  
pp. 32-38
Author(s):  
Temitayo O. Olaniyan ◽  
Samuel O. Ekundayo
Keyword(s):  
Method Of Moments ◽  
Capital Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Annual Reports ◽  
Series Data ◽  
Government Bonds ◽  
Market Growth ◽  
The Public ◽  
Generalised Method Of Moments

We revisited the effects of government bonds for the growth on the Nigerian capital market. Utilising time-series data obtained from the Nigeria Stock Exchange (NSE) annual reports for the period from 2010 to 2017, this study through the Generalised Method of Moments (GMM) regression estimator found that the value and the number of listed government bonds’ positively and significantly affect capital market growth in Nigeria. Furthermore, low capitalisation of government bonds negatively affects the growth of the market. The null hypothesis of the Hansen J-statistics is accepted; hence this implies that the IVs used in the GMM model is valid. We concluded that government bonds have positive and significant effects on the growth of the Nigerian capital market, thus government bonds have made the NSE All-Share Index grow over the period under investigation. Following the findings from the study, it was recommended, inter alia, that there should be more issuance of government bonds to the public and further to enhance the efficiency of the capital markets, both primary and secondary, while the funds raised from the capital market through government issuance should be channelled towards Nigeria’s productive sectors to promote an all-inclusive growth in the Nigerian economy.

scholarly journals Import Flows of Bangladesh: Gravity Model Approach under Panel Data Methodology

2012 ◽  
Vol 60 (2) ◽  
pp. 153-157 ◽  
Author(s):  
Mili Roy ◽  
Md. Israt Rayhan
Keyword(s):  
Panel Data ◽  
Gravity Model ◽  
Cross Section ◽  
Time Series Data ◽  
Random Effect ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square ◽  
Extended Gravity ◽  
Trading Partners

In counterpoint to export growth, Bangladesh import growth has remained much less strong, despite impressive progress in import liberalization. This study gives an overview of different methodologies related to gravity model analysis in Bangladesh’s import flow. A pooled cross section and time series data were analyzed to incorporate the country specific heterogeneity in country pair trading partners. The import flows are justified by the basic gravity model since Bangladesh’s imports are positively significant by the economy size and inversely related to trade barrier. Accordingly, we have analyzed pooled ordinary least square, fixed effect, random effect. This study also explores extended gravity model using several variables in the light of gravity model panel data approach. Bangladesh’s import is determined by the home and foreign country’s gross domestic product and exchange rate. In addition, Cross section results show that regional trade arrangement which is South Asian Association for Regional Co-operation and border are significant for Bangladesh’s importimplies that Bangladesh should import more from intra regional country and also should import from India.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11485 Dhaka Univ. J. Sci. 60(2): 153-157, 2012 (July)  

scholarly journals Uncertainty quantification of the effects of biotic interactions on community dynamics from nonlinear time-series data

2018 ◽  
Vol 15 (147) ◽  
pp. 20180695 ◽  
Author(s):  
Simone Cenci ◽  
Serguei Saavedra
Keyword(s):  
Time Series ◽  
Community Dynamics ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Model Averaging ◽  
Biotic Interactions ◽  
Series Data ◽  
Time Intervals ◽  
Novel Approach ◽  
Data Generating Process

Biotic interactions are expected to play a major role in shaping the dynamics of ecological systems. Yet, quantifying the effects of biotic interactions has been challenging due to a lack of appropriate methods to extract accurate measurements of interaction parameters from experimental data. One of the main limitations of existing methods is that the parameters inferred from noisy, sparsely sampled, nonlinear data are seldom uniquely identifiable. That is, many different parameters can be compatible with the same dataset and can generalize to independent data equally well. Hence, it is difficult to justify conclusive assertions about the effect of biotic interactions without information about their associated uncertainty. Here, we develop an ensemble method based on model averaging to quantify the uncertainty associated with the effect of biotic interactions on community dynamics from non-equilibrium ecological time-series data. Our method is able to detect the most informative time intervals for each biotic interaction within a multivariate time series and can be easily adapted to different regression schemes. Overall, this novel approach can be used to associate a time-dependent uncertainty with the effect of biotic interactions. Moreover, because we quantify uncertainty with minimal assumptions about the data-generating process, our approach can be applied to any data for which interactions among variables strongly affect the overall dynamics of the system.

scholarly journals Analysis of Budget Imbalance Dynamics in Kenya

2018 ◽  
Vol 4 (4) ◽  
pp. 352
Author(s):  
Alex Oguso ◽  
Francis M. Mwega ◽  
Nelson H. Wawire ◽  
Purna Samanta
Keyword(s):  
Public Sector ◽  
Time Series Data ◽  
Supply And Demand ◽  
Series Data ◽  
Fiscal Consolidation ◽  
The Public ◽  
Distributed Lag ◽  
Seeking Behavior ◽  
Development Goals ◽  
The Government

<p><em>Kenya needs substantial and sustained fiscal consolidation to create fiscal space for financing the government’s election pledges, the Vision 2030 development projects, and sustainable development goals. However, the government has found it hard to sustain its fiscal consolidation attempts. This study investigates the fiscal consolidation constraints that act through the budget imbalance dynamics in Kenya using the </em><em>Olivera-Tanzi effect approach.</em><em> The study covers the period 2000-2015</em><em> using time series data and employs three </em><em>Auto-regressive Distributed Lag (ARDL) error correction models</em><em> in the analysis. The study showed that a </em><em>rise in the general price levels in the economy, adjustment of minimum wages, rise</em><em> in perceived levels of corruption in the public sector and the political budget cycles (occurrence of a general election) worsen the budget imbalances (deficits) thus </em><em>constrain fiscal consolidation efforts in Kenya. The study also demonstrated that </em><em>budget imbalance dynamics in Kenya could partly be explained by the Olivera-Tanzi proposition. </em><em>The study rec</em><em>ommends measures to reduce the fiscal imbalance gap in Kenya, which include controlling both supply and demand side inflationary pressure and dealing with rent seeking behavior in the public sector.</em></p>

scholarly journals Factors affecting beta in manufacturing companies in Indonesia Stock Exchange

2020 ◽  
Vol 1 (4) ◽  
pp. 259-268
Author(s):  
Retnoning Ambarwati
Keyword(s):  
Time Series Data ◽  
Stock Exchange ◽  
Least Square ◽  
Series Data ◽  
Manufacturing Companies ◽  
Financial Leverage ◽  
Online Data ◽  
Dividend Payout ◽  
Asset Growth ◽  
Asset Size

This research has want to know and prove the effect of dividend payout, asset growth, asset size, liquidity, financial leverage, earning variability and accounting beta to beta of stock simultaneously and partially in manufacturing companies at Jakarta Stock Exchange.  This research use secondary data which is collected based on time series data and cross section include 12 manufacturing company stocks as the sample. The data is collected from the online data of Jakarta Stock Exchange in YPKP, Indonesia Capital Market Directory, JSX Statistic, and Business News. The model of this research is estimated by Generalized Least Square (GLS) with Fixed Effect Model and Dummy Variable to estimate the effect of some financial variables specifically towards Beta of Stock. The result show that all of the variables in this research consistent with the theory as expected. The coefficient direction of asset growth, financial leverage, earning variability and accounting beta shows positive, while the coefficient direction of dividend payout, asset size, liquidity shows oppositely. Simultaneously all variables influence beta of stock, in the other side partially shows that asset growth, earning variability, asset size, and liquidity, have significant effect to beta, whereas dividend payout ratio, financial leverage and accounting beta do not have significant effect. One of the implications of this research is that the study of beta of stock should be more comprehensively, not only contains micro variables but also the macro variables as well include dimension of social economy and politic

scholarly journals Islamic Finance and Economic Growth Nexus: An Econometric Analysis

2019 ◽  
Vol 2 (1) ◽  
pp. 11-22
Author(s):  
Kashif Raza ◽  
Rashid Ahmad ◽  
Muhammad Abdul Rehman Shah ◽  
Muhammad Umar
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Trade Openness ◽  
Unit Root Test ◽  
Least Square ◽  
Series Data ◽  
Islamic Finance ◽  
Causality Test ◽  
Economic Agents ◽  
Fixed Capital Formation

Researchers have written chain of research papers about the dynamics of financial development and economic growth. The financial capital plays a productive role when it delivers to economic agents who are facing shortage or excess of funds.  This study explores the linkages among Islamic financing and economic growth for Pakistan, by using annual time series data from 2005-2018. Islamic banks’ financing funds used as a proxy of Islamic financing, Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF), labor force (LF),Broad money(M) and Trade openness (TO) to presents real sector of an economy. For the exploration, the unit root test, Ordinary least square technique and Granger causality test are applied. The results validate a substantial causal relationship of Islamic financing and GDP, which supports the Schumpeter’s supply-leading view. The results indicate that Islamic finance contributed towards economic growth.  

scholarly journals Pengaruh Variabel Internal Perbankan Terhadap Kinerja Bank Konvensional di Indonesia

2019 ◽  
Vol 4 (1) ◽  
pp. 90
Author(s):  
Ali Akbar
Keyword(s):  
Commercial Banks ◽  
Time Series Data ◽  
Partial Least Square ◽  
Least Square ◽  
Series Data ◽  
Internal Variables ◽  
Operating Income ◽  
Performance Factors ◽  
Conventional Banks ◽  
Dominant Influence

This research is to know the influence of internal variables of banking (amount of credit and operational expense than operating income (BOPO)) on the performance of conventional banks. The population in this research is the whole of conventional commercial banks in Indonesia year of 2010-2017. The sampel  is the conventional commercial banks by as much as 14 banks, with time series data. The method used is the analysis of partial least square (PLS). The results showed that internal variables of banking (amount of credit, BOPO) negative and no significant effect on performance of conventional banks (CAR, NPL, ROA, LDR) and amount of credit credit is an indicator of a dominant influence variation/change from a conventional banks performance factors (CAR, NPL, ROA and LDR).

scholarly journals The Role of Technical Innovation and Development of Industrial Sector in Korean International Business

2021 ◽  
Vol 22 (1) ◽  
pp. 55-73
Author(s):  
Ali Mohammed Khalel Al-Shawaf ◽  
Tahira Yasmin
Keyword(s):  
Time Series Data ◽  
Positive Impact ◽  
Generalized Method Of Moments ◽  
Value Added ◽  
Industrial Sector ◽  
Least Square ◽  
Policy Implications ◽  
Series Data ◽  
Significance Level

With the pace of development and competitiveness, innovation plays an important role to capture the market share. Various countries have effective strategies to enhance Research and Development (R&D) and exchange value added products in international market. So, based on this the aim of this research is to examine the role of R&D, industrial design and charges for intellectual property in innovative exports in South Korean economy. Time series data for the period 1998 to 2017, Ordinary Least Square (OLS) and Generalized Method of Moments (GMM) models are used to determine the dynamic interrelationship among the study variables. In summary, the overall results show that there is co-integration rank of in both trace test and value test at 1% significance level. Moreover, OLS and GMM findings depict that there is significant and positive coefficient for ID & RD which represent that they have positive impact on HT. Whereas, the IP displays a negative and significant relationship with high technology exports accordingly. Lastly, the diagnostic tests show that model is stable for the study time period and result is reliable. The current study also suggests some policy implications which can enhance innovative export products of South Korea while enhancing R&D.

scholarly journals ANALISIS DETERMINASI PERTUMBUHAN EKONOMI PROVINSI JAMBI

2018 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Ali Fahmi
Keyword(s):  
Economic Growth ◽  
Government Spending ◽  
Capital Investment ◽  
Time Series Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square ◽  
Investment Capital

This research aims to analyze the effect of government spending, investment of foreign capital investment, capital investment In Land and labor against growth of Jambi province during the 2004-2015. This research using Time Series data with regression analysis "Ordinary Least Square (OLS) wear EViews 8.  The findings from this research indicate that Labor become the most variable gives a positive impact against the next economic growth, government spending and investment, while investing PMDN PMA gives negative impact on The Economic Growth Of The Province Of Jambi. PMA investment posit no impact and no signikan against economic growth this is not prevalent, but it is possible the investment PMA in Jambi province is relatively small and still no impact in the absorption of the local Workforce. Menyikapai is an effort to boost the Economic growth of the Province of Jambi then needed a special business development policies should be directed at the activities that are labor-intensive to absorb labor as much as possible. Keywords: economic growth, government spending, PMA, the PMDN, and labor.

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