scholarly journals FACTORS AFFECTING THE WILLING TO JOIN IN COFFEE CROP INSURANCE IN DAK LAK PROVINCE, VIETNAM: A NOVEL APPLICATION OF BAYESIAN MODEL AVERAGING APPROACH

2020 ◽  
Vol 8 (5) ◽  
pp. 68-80
Author(s):  
Le Dinh Thang ◽  
Nguyen Van Si
Keyword(s):  
Rural Areas ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Crop Insurance ◽  
Insurance Companies ◽  
Coffee Tree ◽  
Significance Level ◽  
Factors Affecting ◽  
Independent Variables ◽  
Model Average

Purpose of the study: this paper aims to determine factors affecting the willingness to join crop insurance. Besides, this paper is the purpose of developing a coffee tree insurance program. Methodology: The authors used a systematic random sampling technique. The authors used the Bayesian Model Average (BMA) that calculated the probability of all independent variables affecting the dependent variable with significance level 0.05. Besides, the data based on 480 coffee farmers in Dak Lak province, Vietnam. Main Findings: Authors calculated the probability of all independent variables affecting the dependent variable with significance level 0.05. Independent variables, including loans, drought risks, educational level, experiences, and productivity. Applications of this study: This result is a vital science document for insurance companies and managers to apply and suggest recommendations for developing coffee tree insurance in the future. Novelty/Originality of this study: Vietnam is an agricultural country, 60-70% of the population lives in rural areas, and agricultural insurance should have a considerable market. Farmers’ agrarian insurance cultivated the coffee trees that are currently underdeveloped and challenging.  

scholarly journals Contribution Factors on Congenital Malformations in Neonates in Iran

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Sevda Riyahifar ◽  
Reza Ali Akbari Khoei ◽  
Kayvan Mirnia
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Congenital Malformations ◽  
Family Relationship ◽  
Chi Square ◽  
Significance Level ◽  
Factors Affecting ◽  
Education Of Patients ◽  
And Gender ◽  
Hands And Feet

Background: Congenital malformations are one of the most important and common types of anomalies in infants, and they are considered as the leading causes of disability and mortality in children. These malformations impose enormous costs on families and organizations involved in the treatment, maintenance, and education of patients. Objectives: This study aimed to investigate the risk factors affecting the incidence of congenital anomalies in infants born in Iran. Methods: In this retrospective descriptive-analytical study, we registered various information of all newborns examined and their mothers, including gender, family relationship of parents, type of delivery, types of congenital malformations, anomalies of the hands and feet, and anomalies of the nervous and reproductive systems in the maternity wards of hospitals in Iran. Data were gathered using a checklist. The relationships between different factors were assessed by chi-square test, and the factors influencing congenital malformations were investigated by logistic regression using SPSS-26 software. The significance level of all tests was 0.05. Results: According to the results, 7.5% of newborns had congenital malformations. Eclampsia and diabetes mellitus increased the risk of congenital malformations by 15 and 11%, respectively. The risk of congenital malformations in rural areas was 12% higher than in urban areas. Factors such as consanguineous marriages, history of abortion, and gender also affected the risk of congenital malformations. Conclusions: Necessary measures and plans in the field of premarital counseling, regular pre-pregnancy and post-pregnancy tests and controls, especially in rural and deprived areas, are essential and effective in reducing the incidence of congenital malformations.

scholarly journals Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States

2020 ◽  
Vol 21 (10) ◽  
pp. 2401-2418 ◽  
Author(s):  
E. C. Massoud ◽  
H. Lee ◽  
P. B. Gibson ◽  
P. Loikith ◽  
D. E. Waliser
Keyword(s):  
United States ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Climate Model ◽  
Model Averaging ◽  
Daily Rainfall ◽  
Climate Projections ◽  
Total Uncertainty ◽  
Model Average ◽  
Ensemble Mean

AbstractThis study utilizes Bayesian model averaging (BMA) as a framework to constrain the spread of uncertainty in climate projections of precipitation over the contiguous United States (CONUS). We use a subset of historical model simulations and future model projections (RCP8.5) from the Coupled Model Intercomparison Project phase 5 (CMIP5). We evaluate the representation of five precipitation summary metrics in the historical simulations using observations from the NASA Tropical Rainfall Measuring Mission (TRMM) satellites. The summary metrics include mean, annual and interannual variability, and maximum and minimum extremes of precipitation. The estimated model average produced with BMA is shown to have higher accuracy in simulating mean rainfall than the ensemble mean (RMSE of 0.49 for BMA versus 0.65 for ensemble mean), and a more constrained spread of uncertainty with roughly a third of the total uncertainty than is produced with the multimodel ensemble. The results show that, by the end of the century, the mean daily rainfall is projected to increase for most of the East Coast and the Northwest, may decrease in the southern United States, and with little change expected for the Southwest. For extremes, the wettest year on record is projected to become wetter for the majority of CONUS and the driest year to become drier. We show that BMA offers a framework to more accurately estimate and to constrain the spread of uncertainties of future climate, such as precipitation changes over CONUS.

Willingness to pay for agricultural crop insurance in the northern EU

2014 ◽  
Vol 74 (4) ◽  
pp. 539-554 ◽  
Author(s):  
Petri Liesivaara ◽  
Sami Myyrä
Keyword(s):  
Willingness To Pay ◽  
Crop Insurance ◽  
Arable Land ◽  
Mixed Logit ◽  
Insurance Companies ◽  
Agricultural Crop ◽  
Content Type ◽  
Factors Affecting ◽  
Anchoring Effect ◽  
Split Sample

Purpose – The purpose of this paper is to investigate the demand for crop insurance. Moreover, farmer willingness to pay (WTP) for crop insurance was derived. Factors affecting the demand were also examined in a country where crop insurance products are not currently available. Sensitivity analysis was conducted by studying the price-anchoring effect. Design/methodology/approach – Data from a choice experiment (CE) were analyzed with mixed logit models and the distribution of farmer WTP for crop insurance was derived. A split sample approach with varying premium vectors was used to analyze the price-anchoring effect. Findings – Demand was revealed for crop insurance products in Finland. The demand was higher among younger farmers and farms with more arable land. WTP for crop insurance products was very sensitive to the premium interval presented in the CE design. Research limitations/implications – The price-anchoring effect may disrupt the market development of crop insurance products, because insurance companies may take advantage of the lack of awareness among farmers of crop insurance pricing. Practical implications – The insurance product expected indemnity was a more important factor than the deductible in determining farmer WTP for crop insurance. Therefore, the 30 percent deductible level set for subsidized crop insurance products is not an obstacle for the development of such products in the EU. Originality/value – The study applied a well-known method (CE) to crop insurance in a country where these products are non-existent. The split sample approach was used to examine the price-anchoring effect on crop insurance.

scholarly journals Statistical Analysis of the Development Indicators’ Impacts on E-Commerce of Individuals in Selected European Countries

2018 ◽  
Vol 64 (2) ◽  
pp. 15-24
Author(s):  
Ksenija Dumičić ◽  
Ivana Skoko Bonić ◽  
Berislav Žmuk
Keyword(s):  
Principal Component ◽  
European Countries ◽  
It Infrastructure ◽  
Significance Level ◽  
Factors Affecting ◽  
Development Indicators ◽  
Independent Variables ◽  
Online Purchase ◽  
Main Variable ◽  
It Skills

AbstractThe aim of this paper is to analyse the influence of the development level indicators on the e-commerce, i.e. on the online purchase by individuals, in selected European countries in 2013. In the analysis, the main variable under study and all the independent variables are included as standardised. Based on nine variables, the principal component analysis with varimax rotation was performed and the two extracted factors were used as the regressors in the multiple regression analysis. In the regression model both components, Factor 1, which includes seven variables, called Prosperity, Investing in Education and IT Infrastructure, and Awareness, and Factor 2, comprised of two variables, called IT Skills, are statistically significant at the significance level of 1%. Both factors show a positive correlation with the online purchase of individuals. Inclusion and analysis of distributions and impacts of even nine independent variables, which make up two distinct factors affecting the e-commerce, make a new contribution of this work.

scholarly journals The Panel Data Analysis to Identify the Factors Affecting Turkish Currency Assets of Foreign Deposit Banks

2021 ◽  
pp. 121-128
Author(s):  
Ersan Özgür
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Banking Sector ◽  
Free Market ◽  
Panel Data Analysis ◽  
Foreign Banks ◽  
Significance Level ◽  
Factors Affecting ◽  
Independent Variables ◽  
Study Results

With the implementation of free market economy in Turkey starting from 1980, restrictions on foreign capital flows began to be abolished. Within the scope of international expansion in financial aspects, steps for integration with global financial markets were taken, and regulations were made. Accordingly, the number of foreign banks in Turkish banking system have increased since 1980, and reached an important scale in the sector. The share of foreign deposit banks’ total assets in the entire banking sector is at 22,8% level as of 2019. In this study, panel data analysis was performed to identify the factors affecting the Turkish currency assets of foreign deposit banks. The 11-year data for the 2009-2019 period were utilized in the study. Turkish Currency Assets / Total Assets was determined as the dependent variable in the analysis. The factors affecting the Turkish currency assets of foreign deposit banks were identified as Turkish Currency Liability / Total Liability [TPYUK], Turkish Currency Deposits / Total Deposits [TPMEV], and Turkish Currency Loans / Total Loans [TPKREDI]. Based on the study results the model formed was significant, and the ratio of independent variables for explaining the dependent variable in the model was approximately 48%. The independent variables TPYUK and TPKREDI were revealed to have a statistically significant positive effect on the dependent variable at 5% significance level. A 1-unit raise in TPYUK increased the dependent variable by 0,436 unit, and a 1-unit raise in TPKREDI by 0,033 unit. No statistically significant effect of TPMEV as the other independent variable was identified on the dependent variable.

Gaussian process modeling of nonstationary crop yield distributions with applications to crop insurance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wenbin Wu ◽  
Ximing Wu ◽  
Yu Yvette Zhang ◽  
David Leatham
Keyword(s):  
Gaussian Process ◽  
Crop Yield ◽  
Bayesian Model Averaging ◽  
Crop Yields ◽  
Crop Insurance ◽  
Model Averaging ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Content Type ◽  
Stage Estimation

PurposeThe purpose of this paper is to bring out the development of a flexible model for nonstationary crop yield distributions and its applications to decision-making in crop insurance.Design/methodology/approachThe authors design a nonparametric Bayesian approach based on Gaussian process regressions to model crop yields over time. Further flexibility is obtained via Bayesian model averaging that results in mixed Gaussian processes.FindingsSimulation results on crop insurance premium rates show that the proposed method compares favorably with conventional estimators, especially when the underlying distributions are nonstationary.Originality/valueUnlike conventional two-stage estimation, the proposed method models nonstationary crop yields in a single stage. The authors further adopt a decision theoretic framework in its empirical application and demonstrate that insurance companies can use the proposed method to effectively identify profitable policies under symmetric or asymmetric loss functions.

scholarly journals Bayesian Model Averaging Using Power-Expected-Posterior Priors

Econometrics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 17
Author(s):  
Dimitris Fouskakis ◽  
Ioannis Ntzoufras
Keyword(s):  
Bayesian Model ◽  
Prediction Accuracy ◽  
Bayesian Model Averaging ◽  
Linear Models ◽  
Model Averaging ◽  
Real Data ◽  
Bayesian Variable Selection ◽  
Point Estimate ◽  
Model Average ◽  
Evaluation Strategies

This paper focuses on the Bayesian model average (BMA) using the power–expected– posterior prior in objective Bayesian variable selection under normal linear models. We derive a BMA point estimate of a predicted value, and present computation and evaluation strategies of the prediction accuracy. We compare the performance of our method with that of similar approaches in a simulated and a real data example from economics.

scholarly journals WHAT DRIVES PEOPLE'S INTEREST IN SHARIA INSURANCE? EVIDENCE FROM PALANGKA RAYA

2021 ◽  
Vol 2 (1) ◽  
pp. 39-59
Author(s):  
Umi Purwaningsih ◽  
Putri Nurmala ◽  
Muhammad Riza Hafizi
Keyword(s):  
Economic Conditions ◽  
Insurance Companies ◽  
Research Approach ◽  
Product Price ◽  
F Test ◽  
Significance Level ◽  
Factors Affecting ◽  
The People ◽  
Study Product ◽  
Islamic Insurance

This studi aims to analyze factors affecting people become member of sharia insurance in Palangka Raya, Central Borneo, Indonesia. This research approach uses a quantitative approach. The variables used in this study, product, price, promotion, lifestyle and economic conditions. The method used in data collection using purposive sampling method, by distributing online questionnaires. The number of samples in this study were 42 respondents. The analytical tool used to determine the public's interest in participating in Prudential sharia insurance in Palangka Raya City is to use SPSS 23. The results of this study indicate that there is a significant positive effect on promotion and lifestyle variables on interest in Prudential sharia insurance, this is evidenced by the F test, which shows a significance level of 0.000. This is because the magnitude of the significance level of the F test from the F count value of 16,215 with the F table value of 2.5, this indicates that the F count value is greater than the F table value (16, 215 > 2.5). In this study, the magnitude of the influence of the Adjusted R Square of the promotion and lifestyle variables is 0,650 or 65% which affecting become sharia insurance participant in Palangka Raya. Meanwhile, based on the results of the T test, it shows that the variables of product, price and economic conditions are not significant. This is because the Palangka Raya is not as big as the cities in the capital, so people who use the services of Sharia Insurance are still not priority for the people of Palangka Raya. This study contributes empirically to the describe sharia insurance in Palangka Raya. In addition, the existing sharia insurance in the Palangka Raya should be re-socialized so that people are more familiar and using sharia insurance services compared to using conventional insurance. Islamic insurance uses the concept of protecting each other. This concept is different from conventional insurance, where participants pay premiums to insurance companies.

scholarly journals Factors Affecting Life Expectancy in East Java: Predictions with A Bayesian Model Averaging Approach

2021 ◽  
Vol 5 (2) ◽  
pp. 283-295
Author(s):  
Harun Al Azies ◽  
Vivi Mentari Dewi
Keyword(s):  
Life Expectancy ◽  
Regression Model ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
Infant Mortality Rate ◽  
Model Parameters ◽  
Data Set ◽  
Expectancy Value ◽  
Factors Affecting

This study predicts the factors that influence life expectancy in East Java, Indonesia. In particular, this study compares the prediction results between the linear regression model and the Bayesian Model Averaging (BMA). The study used a 2015 data set from the Central Bureau of Statistics (BPS) of the province of East Java.The results of data exploration show that the life expectancy in East Java is 70.68 years, the Bondowoso regency is the region with the lowest life expectancy at 65.73 years and the city of Surabaya is the area with the highest life expectancy value in East Java, which is 73.85 years.The results of the inference study indicate that the factors that are expected to affect life expectancy in East Java are the infant mortality rate and the illiteracy rate of the population aged 10 and over.The results of the comparison between the BMA and the regression show that the BMA is a better model for predicting the factors that affect life expectancy in East Java than the regression model because the BMA model can estimate the parameters more efficiently by estimating the model parameters based on the standard error value.

scholarly journals Factors Affecting Profitability of Insurance Companies. Evidence from Kosovo

2022 ◽  
Vol 25 ◽  
pp. 122-142
Author(s):  
Yllka Ahmeti ◽  
Etem Iseni
Keyword(s):  
Firm Growth ◽  
Profit Margin ◽  
Insurance Companies ◽  
Company Size ◽  
Return On Assets ◽  
Factors Affecting ◽  
Independent Variables ◽  
Net Profit ◽  
Tangible Asset ◽  
Available Resources

Profitability expresses the ability to make a profit from all the business activities of the company. It shows how efficiently management generates profit by utilizing all available resources. This paper examined the effects of specific company factors, namely independent variables such as: liquidity, company size, company age, tangible asset, leverage, company capital and growth of com-pany, on profitability represented by return on assets (ROA) and net profit margin (NPM) as a dependent variable. The sample in this study includes eleven insurance companies for the period 2015 - 2020. The regression results indicate that size, leverage and age of company, have significant effects on the ROA. Meanwhile in NPM of insurance companies in Kosovo size of company and firm growth have significant effects.

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