scholarly journals Mathematical Models and Data Analysis of Residential Land Leasing Behavior of District Governments of Beijing in China

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2314
Author(s):  
Jing Cheng
Keyword(s):  
Mathematical Models ◽  
Least Squares Method ◽  
Large City ◽  
Ordinary Least Squares ◽  
Numerical Results ◽  
Policy Implications ◽  
Residential Land ◽  
District Government ◽  
Beijing China ◽  
Land Leasing

To analyze the leasing behavior of residential land in Beijing, the mathematical models of the price and the total area of the leased residential land are presented. The variables of the mathematical models are proposed by analyzing the factors influencing the district government’s leasing behavior for residential land based on the leasing right for residential land in Beijing, China. The regression formulae of the mathematical models are obtained with the ordinary least squares method. By introducing the data of the districts in Beijing from 2004 to 2015 into the mathematical models, the numerical results of the coefficients in the mathematical models are obtained by solving the equations of the regression formulae. After discussing the numerical results of the influencing factors, the district government behavior for leasing residential land in Beijing, China, is investigated. The numerical results show the factors concerning the government and how these factors influence the leased price and the total leased area of residential land for this large city in China. Finally, policy implications for the district government regarding residential land leasing in Beijing are proposed.

scholarly journals Data Analysis of the Factors Influencing the Industrial Land Leasing in Shanghai Based on Mathematical Models

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Jing Cheng
Keyword(s):  
Data Analysis ◽  
Mathematical Models ◽  
Subway Station ◽  
Land Area ◽  
Government Behavior ◽  
Industrial Land ◽  
Factors Influencing ◽  
District Government ◽  
The Government ◽  
Land Leasing

By analyzing the background of land leasing in Shanghai, the hypotheses of the mathematical models of industrial land leasing in Shanghai are proposed, and then, the mathematical models of the land price and land area are presented for analyzing the factors of industrial land leasing. Based on the mathematical models and the district data of Shanghai from 2007 to 2015, the factors influencing industrial land leasing by the district government are studied. It is shown that the influencing factors, such as the land area, GDP, tenure of district mayor, and the distance between the land and the nearest subway station, affect the government behavior on industrial land leasing.

Determinants of Net Interest Margin of Commercial Banks in Vietnam

2015 ◽  
pp. 69-82 ◽  
Author(s):  
Khanh Hoang Trung ◽  
Tra Vu Thi Dan
Keyword(s):  
Commercial Banks ◽  
Global Financial Crisis ◽  
Least Squares Method ◽  
Secondary Data ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
Financial Reports ◽  
Net Interest Margin ◽  
The Global Financial Crisis ◽  
Interest Margin

This study provides an insight into the determinants of net interest margin (NIM) of commercial banks in Vietnam during the recession period. We employ secondary data collected from published audited consolidated financial reports of Vietnamese commercial banks from 2008, the year marking the outbreak of the global financial crisis, to the end of 2012. Altogether, the data constitute 175 panel-data observations. The regression using the ordinary least squares method yields the result that operating expense, management quality, risk aversion, and inflation rate have a positive effect on NIM, while the banking sector’s market concentration affects NIM negatively. Afterwards, some policy implications are derived from those findings to mitigate and put NIM under control, so that the efficiency of the financial intermediary system can be developed.

scholarly journals The impact of diseases on economic growth: the case of Viet Nam

2020 ◽  
Vol 3 (4) ◽  
pp. 428-437
Author(s):  
Pham Thanh Thai ◽  
Nguyen Thanh Le
Keyword(s):  
Public Health ◽  
Economic Growth ◽  
Infectious Diseases ◽  
Least Squares Method ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
World Health ◽  
New Knowledge ◽  
The Impact ◽  
Hiv Aids

The spread of diseases is a global challenge which affects life expectancy, productivity and economic growth. A healthy workforce has a faster acquisition of new knowledge to apply it to production and maintains high productivity, thereby promoting economic growth. On the contrary, a disease-infected workforce may have a low level of productivity, high expenses for disease treatment, insufficient health and finance to acquire new knowledge and as such, slowing down the economic growth. This study examines the implications of major infectious diseases, including HIV/AIDS, dengue, malaria and tuberculosis on the economic growth of Vietnam. The cointegration regression model with the ordinary least squares method is applied in the estimation procedure on a time series dataset obtained from World Bank, World Health Organization, UN and the Ministry of Health of Vietnam from 1986 to 2016. The results indicate that the number of new patients of any major infectious disease is negatively related to per-capita income. In particular, a 1% increase in the number of new patients with HIV/AIDS, tuberculosis, dengue and malaria leads to a decrease of 0.022%, 0.095%, 0.015% and 0.057% in yearly income, respectively. These findings have significant policy implications in terms of improving the effectiveness of the prevention of infectious diseases, protection of public health so as to boost the economic growth of the country. In addition, the results also provide add to the current literature evidence of the relationship between public health and economic growth in Vietnam.

Analysis of Twisting Stiffness for a Multifiber Composite Layer

1974 ◽  
Vol 41 (3) ◽  
pp. 658-662 ◽  
Author(s):  
C. W. Bert ◽  
S. Chang
Keyword(s):  
Cross Section ◽  
Least Squares Method ◽  
Rectangular Cross Section ◽  
Torsional Rigidity ◽  
Composite Layer ◽  
Circular Cross Section ◽  
Relaxation Method ◽  
Fiber Composites ◽  
Numerical Results ◽  
Torsion Problem

The twisting stiffness of a rectangular cross section consisting of a single row of solid circular cross-section fibers embedded in a matrix is analyzed. The problem is formulated as a Dirichlet torsion problem of a multielement region and solved by the boundary-point least-squares method. Numerical results for a single-fiber square cross section compare favorably with previous relaxation-method results. New numerical results for three and five-fiber composites suggest that the torsional rigidity of a multifiber composite can be approximated from the torsional rigidities of single and three-fiber models.

scholarly journals Influence of Fiscal Policies and Labor Market Characteristics on Sustainable Social Insurance Budgets—Empirical Evidence from Central and Eastern European Countries

2021 ◽  
Vol 13 (11) ◽  
pp. 6197
Author(s):  
Adriana Florina Popa ◽  
Stefania Amalia Jimon ◽  
Delia David ◽  
Daniela Nicoleta Sahlian
Keyword(s):  
Labor Market ◽  
Social Insurance ◽  
Social Protection ◽  
Least Squares Method ◽  
Panel Study ◽  
Ordinary Least Squares ◽  
Political Agenda ◽  
Fiscal Policies ◽  
Protection Systems ◽  
Social Protection Systems

Social protection systems are a key factor for ensuring the long-term sustainability and stability of economies in the European Union, their reform being nowadays present in the political agenda of member states. Aging and the dependence on mandatory levies applied to the employed population on the labor market represent a threat for the sustainability of public social protection systems. In terms of sustainability, our purpose was to highlight the factors influencing social insurance budgets, considering the fiscal policies implemented in six countries of Central and Eastern Europe and their particular labor market characteristics. Therefore, a panel study based on a regression model using the Ordinary Least Squares method (OLS) with cross section random effects was used to determine the correlations between funding sources and labor market specific indicators. The data analyzed led to relevant results that emphasize the dependence of social insurance budgets on positive factors such as the average level of salaries, the share of compulsory social contributions, the unemployment rate, and the human development index, suggesting the continuing need for professional and personal development of the workforce.

Cops and COVID: an examination of California officers' perceptions and experiences while policing during a pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
John Shjarback ◽  
Obed Magny
Keyword(s):  
Police Officers ◽  
Online Survey ◽  
Ordinary Least Squares ◽  
Point Of View ◽  
Policy Implications ◽  
Organizational Level ◽  
Sensitive Information ◽  
Content Type ◽  
Police Agencies ◽  
Police Executives

PurposeUsing online survey data from a sample of 440 police officers in California throughout May 2020, the current study collected time-sensitive information on officers' perceptions and departmental experiences in the wake of the pandemic. It examined officers' perceptions of agency responsivity as well as their perceptions of morale, stress and risk following agency responses and changes in policy patterns, service delivery innovations and other administrative challenges.Design/methodology/approachCOVID-19 had a tremendous impact on the law enforcement community, who continued to work and adapt in order to provide public safety. During the first few months of the pandemic, a number of national data collection efforts set out to understand what police agencies, at the organizational-level, were doing to address the crisis. Largely missing from these initial discussions were the perspectives of individual officers, particularly how they felt about their respective departments ensuring safety and balancing risk.FindingsResults from ordinary least squares (OLS) regressions found that the number of departmental changes made in the wake of COVID-19 that reduced police–public contact was associated with (1) increased levels of perceived agency responsivity to officer needs (i.e. balancing officer safety, taking active steps to maintain officers' mental health) and (2) reduced levels of perceived negative outlook (e.g. stress, low morale, danger/risk). Policy implications and the importance of police executives' decisions during crisis are discussed.Originality/valueThis study is one of the first, to the authors’ knowledge, to examine perceptions of policing during the pandemic from an individual officer point of view rather than an organizational standpoint.

Fiscal Deficit and Economic Growth in Bangladesh

2016 ◽  
Vol 62 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Ebney Ayaj Rana ◽  
Abu N. M. Wahid
Keyword(s):  
Economic Growth ◽  
Budget Deficit ◽  
Negative Impact ◽  
Political Stability ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
Government Budget ◽  
The Government ◽  
The Impact ◽  
Government Budget Deficit

The economy of Bangladesh is currently going through a period of continuous budget deficit. The present data suggest that the government budget deficit, on average, is nearly 5% of the country’s GDP. This has been true since the early 2000s. To finance this deficit, governments have been borrowing largely from domestic and foreign sources resulting in inflationary pressure on one hand, and crowding out of private investments on the other. During the same period, although the economy has grown steadily at a rate of more than 6%, this growth is less than the potential. This article presents an econometric study of the impact of government budget deficits on the economic growth of Bangladesh. We conduct a time-series analysis using ordinary least squares estimation, vector error correction model, and granger causality test. The findings suggest that the government budget deficit has statistically significant negative impact on economic growth in Bangladesh. Policy implications of our findings include reestablishing the rule of law, political stability in the country, restructuring tax structure, closing tax loopholes, and harmonizing fiscal policy with monetary policy to attract additional domestic and foreign investment.

scholarly journals Determination of parameters for Cauchy’s problem for systems of ODEs with application to biological modelling

BIOMATH ◽  
2016 ◽  
Vol 5 (1) ◽  
pp. 1604231
Author(s):  
A.N. Pete ◽  
Peter Mathye ◽  
Igor Fedotov ◽  
Michael Shatalov
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Least Squares ◽  
Numerical Method ◽  
Least Squares Method ◽  
Algebraic Equations ◽  
Systems Of Odes ◽  
Determination Of Parameters ◽  
Biological Modelling

An inverse numerical method that estimate parameters of dynamic mathematical models given some information about unknown trajectories at some time is applied to examples taken from Biology and Ecology. The method consisting of determining an over-determined system of algebraic equations using experimental data. The solution of the over-determined system is then obtained using, for example the least-squares method. To illustrate the effectiveness of the method an analysis of examples and corresponding numerical example are presented.

scholarly journals Towards the attainment of sustainable development goal 7: what determines clean energy accessibility in sub-Saharan Africa?

Green Finance ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 268-286
Author(s):  
Paul Adjei Kwakwa ◽  
◽  
Frank Adusah-Poku ◽  
Kwame Adjei-Mantey ◽  
◽  
...  
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Poverty Reduction ◽  
Random Effect ◽  
Clean Energy ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
Sub Saharan Africa ◽  
Political Regime ◽  
Sub Saharan

<abstract> <p>Access to clean energy is necessary for environmental cleanliness and poverty reduction. That notwithstanding, many in developing countries especially those in sub-Saharan Africa region lack clean energy for their routine domestic activities. This study sought to unravel the factors that influence clean energy accessibility in sub-Saharan Africa region. Clean energy accessibility, specifically access to electricity, and access to clean cooking fuels and technologies, were modeled as a function of income, foreign direct investment, inflation, employment and political regime for a panel of 31 sub-Saharan countries for the period 2000–2015. Regression analysis from fixed effect, random effect and Fully Modified Ordinary Least Squares show that access to clean energy is influenced positively by income, foreign direct investment, political regime and employment while inflation has some negative effect on its accessibility. The policy implications from the findings among other things include that expansion in GDP per capita in the sub-region shall be helpful in increasing accessibility to clean energy. Moreover, strengthening the democratic institutions of countries in the region shall enhance the citizens' accessibility to clean energy. Ensuring sustainable jobs for the citizens is necessary for access clean energy.</p> </abstract>

scholarly journals Least Squares Estimations for the General Linear Model Parameters with Epsilon Skew Normal Error Term

2020 ◽  
pp. 636-645
Author(s):  
Hussain Karim Nashoor ◽  
Ebtisam Karim Abdulah
Keyword(s):  
Least Squares ◽  
Linear Model ◽  
Least Squares Method ◽  
General Linear Model ◽  
Ordinary Least Squares ◽  
Skewed Distribution ◽  
General Linear ◽  
Average Error ◽  
Model Parameters ◽  
Skew Normal

Examination of skewness makes academics more aware of the importance of accurate statistical analysis. Undoubtedly, most phenomena contain a certain percentage of skewness which resulted to the appearance of what is -called "asymmetry" and, consequently, the importance of the skew normal family . The epsilon skew normal distribution ESN (μ, σ, ε) is one of the probability distributions which provide a more flexible model because the skewness parameter provides the possibility to fluctuate from normal to skewed distribution. Theoretically, the estimation of linear regression model parameters, with an average error value that is not zero, is considered a major challenge due to having difficulties, as no explicit formula to calculate these estimates can be obtained. Practically, values for these estimates can be obtained only by referring to numerical methods. This research paper is dedicated to estimate parameters of the Epsilon Skew Normal General Linear Model (ESNGLM) using an adaptive least squares method, as along with the employment of the ordinary least squares method for estimating parameters of the General Linear Model (GLM). In addition, the coefficient of determination was used as a criterion to compare the models’ preference. These methods were applied to real data represented by dollar exchange rates. The Matlab software was applied in this work and the results showed that the ESNGLM represents a satisfactory model. 

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