scholarly journals Effect of air pollution on household insurance purchases. Evidence from China household finance survey data

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242282
Author(s):  
Wenxia Zhao
Keyword(s):  
Air Pollution ◽  
Health Insurance ◽  
Life Insurance ◽  
Poisson Regression ◽  
Regression Models ◽  
Household Finance ◽  
Economic Effects ◽  
Using Data ◽  
The Impact ◽  
Degree Of Heterogeneity

In recent years, the health and economic effects of air pollution have attracted considerable attention, and health and insurance services have been closely related to residents’ welfare. However, there are few studies on the influence of pollution on household purchases of insurance. Using data from the 2013 and 2015 China Household Finance Surveys, this study investigates the effect of air pollution on insurance purchases using Logit and Poisson regression models. It is found that air pollution significantly increases the probability of household insurance purchases and the level of premium expenditure, although the impact of air pollution on insurance purchases shows a degree of heterogeneity. Health insurance is more sensitive to air pollution than life insurance and other types of insurance. In areas where NO2 and O3 are the main types of pollutants, air pollution has a greater impact on household insurance purchases.

Impact of Health Plan Deductibles and Health Insurance Marketplace Enrollment on Health Care Experiences

2018 ◽  
Vol 77 (5) ◽  
pp. 483-497
Author(s):  
Weiwei Chen ◽  
Timothy F. Page
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
The United States ◽  
Health Plans ◽  
Medical Needs ◽  
Care Access ◽  
Health Care Experiences ◽  
Monitoring Survey ◽  
Using Data ◽  
The Impact

High-deductible health plans (HDHPs) have become increasingly prevalent among employer-sponsored health plans and plans offered through the Health Insurance Marketplace in the United States. This study examined the impact of deductible levels on health care experiences in terms of care access, affordability, routine checkup, out-of-pocket cost, and satisfaction using data from the Health Reform Monitoring Survey. The study also tested whether the experiences of Marketplace enrollees differed from off-Marketplace individuals, controlling for deductible levels. Results from multivariable and propensity score weighted regression models showed that many of the outcomes were adversely affected by deductible levels and Marketplace enrollment. These results highlight the importance of efforts to help individuals choose the plan that fits both their medical needs and their budgets. The study also calls for more attention to improving provider acceptance of HDHPs and Marketplace plans as these plans become increasingly common over time.

scholarly journals Modeling a Bridge When Survey Questions Change: Evidence from the Current Population Survey Health Insurance Redesign

2019 ◽  
Vol 35 (1) ◽  
pp. 189-202
Author(s):  
Brett O’Hara ◽  
Carla Medalia ◽  
Jerry J. Maples
Keyword(s):  
Health Insurance ◽  
Current Population Survey ◽  
Time Trend ◽  
Population Survey ◽  
The United States ◽  
Community Survey ◽  
Historical Time ◽  
Current Population ◽  
Using Data ◽  
The Impact

Abstract Most research on health insurance in the United States uses the Current Population Survey Annual Social and Economic Supplement. However, a recent redesign of the health insurance questions disrupted the historical time trend in 2013. Using data from the American Community Survey, which has a parallel trend in the uninsured rate, we model a bridge estimate of the uninsured rate using the traditional questions. Also, we estimate the effect of changing the questionnaire. We show that the impact of redesigning the survey varies substantially by subgroup. This approach can be used to produce bridge estimates when other questionnaires are redesigned.

scholarly journals FERTILITY LEVELS IN RELATION TO EDUCATION IN PAKISTAN

2014 ◽  
Vol 21 (06) ◽  
pp. 1103-1112
Author(s):  
Abid Ghafoor Chaudhry ◽  
Asha Gul ◽  
Shaheer Ellahi Khan ◽  
Nida Khan ◽  
Maha Khan
Keyword(s):  
Higher Education ◽  
Poisson Regression ◽  
Living Standards ◽  
Level Of Education ◽  
Aggregate Analysis ◽  
Interesting Conclusion ◽  
Using Data ◽  
The Impact ◽  
Disaggregate Analysis

The objective of this study was to examine the effect of education on fertility levels in Pakistan using data for 4125 females aged 15-49 years from the Pakistan Social and Living Standards Measurement Survey (PSLM) 2007-08 both at the aggregate and disaggregate level. The methodology of this study uses Poisson regression, the estimated results of which verify that education (measured by the highest class passed) has a negative and statistically significant impact on fertility levels, but this relation does not hold true for all levels of education. While higher secondary and higher education are significant across all specifications in the aggregate analysis, the impact of matriculation on fertility levels is mixed. Although, similar results are obtained from the disaggregate analysis, an interesting conclusion is that no level of education comes out to

scholarly journals Banking Development and Economy in Greece: Evidence from Regional Data

2020 ◽  
Vol 13 (10) ◽  
pp. 243
Author(s):  
Christos Floros
Keyword(s):  
Regression Models ◽  
Local Economy ◽  
Data Envelopment ◽  
Banking Efficiency ◽  
Banking Services ◽  
Atm Network ◽  
Using Data ◽  
The Impact ◽  
Banking Development ◽  
Number Of Branches

This article examines the development of Greek systemic banks for the period 2003–2018, using data such as the ATM network and branches at a regional level. We test the impact of the ATM network and branches on the deposits of Greek commercial banks as well as the impact of local GDP on the regional banking efficiency. The analysis is carried out in two steps, (1) we use the Data Envelopment Analysis (DEA) for efficiency analysis, and (2) we use panel regression models for regression analysis. The results show that branches that operate at small regions are less efficient than those of the larger regions. Furthermore, both the ATMs and the number of branches have a positive relationship with deposits. This means that banks must continue to operate branches and ATMs in Greece. Finally, we show that local GDP helps significantly in increasing regional banking efficiency. The above findings are important given the need to support the local economy with modern banking services in Greece.

scholarly journals Messaging and the Mandate: The Impact of Consumer Experience on Health Insurance Enrollment Through Exchanges

2015 ◽  
Vol 105 (5) ◽  
pp. 105-109 ◽  
Author(s):  
Natalie Cox ◽  
Benjamin Handel ◽  
Jonathan Kolstad ◽  
Neale Mahoney
Keyword(s):  
Health Insurance ◽  
Large Scale ◽  
Consumer Experience ◽  
Important Distinction ◽  
Web Based ◽  
Demographic Heterogeneity ◽  
Average Impact ◽  
Scale Experiment ◽  
Using Data ◽  
The Impact

The ability of web-based retailers to learn about and provide targeted consumer experiences is touted as an important distinction from traditional retailers. In principal, web-based insurance exchanges could benefit from these advantages. Using data from a large-scale experiment by a private sector health insurance exchange we estimate the returns to experimentation and targeted messaging. We find significant improvements in conversions in one treatment tested. Underlying the average impact were both intertemporal and demographic heterogeneity. We estimate that learning and targeted messaging could increase insurance applications by approximately 13 percent of the baseline conversion rate.

Releases From a Local Jail: The Impact of Visitation on Recidivism

2020 ◽  
pp. 088740342091948 ◽  
Author(s):  
William M. Casey ◽  
Jennifer E. Copp ◽  
William D. Bales
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Large Body ◽  
Current Investigation ◽  
Research Attention ◽  
Logistic Regression Models ◽  
Local Jail ◽  
Number Of Visits ◽  
Using Data ◽  
The Impact

There is a large body of research that examines the impact of visitation on the likelihood of recidivism among released state prisoners. That research reveals that receiving any visits, and a greater number of visits, reduces the likelihood of recidivism. However, whether the recidivism-reducing effect of visitation operates within the jail setting remains unclear. Using data from a Florida jail, the current investigation examines the association between visitation and recidivism among a cohort of releases ( N = 6,565). Analyses also consider the extent to which the frequency of visits impacts the likelihood of recidivism. Findings from a series of logistic regression models reveal that inmates who received visits were no less likely to recidivate than their counterparts. Yet, among inmates who were visited, those receiving more frequent visits were less likely to recidivate. This departs from existing visitation research and underscores the importance of directing research attention to local jails.

scholarly journals Prediction of atmospheric pollution using neural networks model of fine particles in the town of Kennedy in Bogota

2020 ◽  
Vol 10 (6) ◽  
pp. 6574
Author(s):  
Juan Camilo Pedraza ◽  
Oswaldo Alberto Romero ◽  
Helbert Eduardo Espitia
Keyword(s):  
Neural Networks ◽  
Air Pollution ◽  
Atmospheric Pollution ◽  
Fine Particles ◽  
Particulate Material ◽  
High Impact ◽  
Geographical Environment ◽  
Using Data ◽  
The Impact ◽  
The Town

This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.

scholarly journals The Causal Effect of Air Pollution on COVID-19 Transmission: Evidence from China

2020 ◽  
Author(s):  
Guojun He ◽  
Yuhang Pan ◽  
Takanao Tanaka
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Causal Effect ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Percentage Point Increase ◽  
Distributed Lag ◽  
Using Data ◽  
Epidemiological Characteristics ◽  
The Impact

There is increasing concern that ambient air pollution could exacerbate COVID-19 transmission. However, estimating the relationship is challenging because it requires one to account for epidemiological characteristics, to isolate the impact of air pollution from potential confounders, and to capture the dynamic impact. We propose a new econometric framework to address these challenges: we rely on the epidemiological Susceptible-Infectious-Recovered-Deceased (SIRD) model to construct the outcome of interest, the Instrument Variable (IV) model to estimate the causal relationship, and the Flexible-Distributed-Lag (FDL) model to understand the dynamics. Using data covering all prefectural Chinese cities, we find that a 10-point (14.3%) increase in the Air Quality Index would lead to a 2.80 percentage point increase in the daily COVID-19 growth rate with 2 to 13 days of delay (0.14 ∼ 0.22 increase in the reproduction number: R0). These results imply that improving air quality can be a powerful tool to contain the spread of COVID-19.

scholarly journals Air Pollution, Residents’ Happiness, and Environmental Regulation: Evidence from China

2021 ◽  
Author(s):  
Fang Xu ◽  
Xiao-Ling Luo ◽  
Di Zhou
Keyword(s):  
Air Pollution ◽  
Environmental Regulation ◽  
Environmental Regulations ◽  
Critical Path ◽  
Leisure Activities ◽  
General Social Survey ◽  
Probit Model ◽  
Critical Paths ◽  
Using Data ◽  
The Impact

Abstract Using data from the China General Social Survey and data on air pollution, this study explores the impact and the critical path of air pollution on residents’ happiness in China and evaluates whether environmental regulations can alleviate these effects. A probit model is used to analyze the impact of air pollution on residents’ happiness, and wind speed is taken as the instrumental variable of air pollution to overcome endogeneity. A stepwise regression is used to test the critical path of air pollution on residents’ happiness. Finally, the effects of environmental regulations are considered by adding an interaction term between environmental regulation and air pollution. The following conclusions are drawn. First, air pollution can significantly impair residents’ happiness, especially those who have children, are younger, are in poor health, have a lower education level, have lower income, and live in a rural area. Second, there are two critical paths through which air pollution impairs residents’ happiness: mental health level and the frequency of leisure activities. Finally, command-and-control, market-based, and voluntary environmental regulations can all effectively alleviate the impact of air pollution on residents’ happiness.

scholarly journals Physical distancing reduced the incidence of influenza and supports a favorable impact on SARS-CoV-2 spread in Mexico

2020 ◽  
Vol 14 (09) ◽  
pp. 953-956
Author(s):  
Efrén Murillo-Zamora ◽  
José Guzmán-Esquivel ◽  
Ramón Alberto Sánchez-Piña ◽  
Guillermo Cedeño-Laurent ◽  
Iván Delgado-Enciso ◽  
...  
Keyword(s):  
Poisson Regression ◽  
Surveillance System ◽  
Regression Models ◽  
Preventive Measures ◽  
Age Groups ◽  
Physical Distance ◽  
Incidence Rates ◽  
School Closures ◽  
Transmission Mechanisms ◽  
The Impact

Introduction: Physical distancing preventive measures were implemented in Mexico as a response to the coronavirus disease 2019 (CoViD-19) pandemic. School closures occurred on March 16, 2020, in 10 out of 32 Mexican states, and one week later in the remaining states. Because the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the influenza virus have similar transmission mechanisms, we aimed to evaluate the impact of physical distancing on the incidence of influenza as a proxy of the impact on SARS-CoV-2 contagion. Methodology: A national flu surveillance system was cross-sectionally analyzed and daily average percent changes (APCs) of incidence rates were calculated throught Poisson regression models. Results: Greater decreasing trends (APCs -8.8, 95% CI: -12.5, -4.5; vs. -6.0, 95% CI: -9.9, -2.0; p = 0.026) were documented in the states with earlier school closures and across age groups, suggesting that earlier implementation of physical distance results in reduced SARS-CoV-2 spread. Conclusions: Physical distancing policies decrease the incidence of influenza infections in Mexico; its favorable impact on the spread of SARS-CoV-2 is commendable.

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