Role of Socio-Economic Variables on Adoption of Crop Insurance Schemes

2017 ◽  
Author(s):  
Mrinali Kumari ◽  
Krishna M. Singh ◽  
Rewati Raman Mishra ◽  
D. K. Sinha ◽  
Nasim Ahmad
Keyword(s):  
Crop Insurance ◽  
Economic Variables ◽  
Socio Economic Variables

scholarly journals Role of Socio-economic Variables in Adoption of Crop Insurance: A Discriminant Function Approach

2017 ◽  
Vol 62 (3) ◽  
pp. 361
Author(s):  
Mrinali Kumari ◽  
K.M. Singh ◽  
R.R. Mishra ◽  
D.K. Sinha ◽  
Nasim Ahmad
Keyword(s):  
Discriminant Function ◽  
Crop Insurance ◽  
Function Approach ◽  
Economic Variables ◽  
Socio Economic Variables

scholarly journals Role of Accessibility and Socio-Economic Variables in Modelling Population Change at Varying Scale

2014 ◽  
Vol 06 (04) ◽  
pp. 386-403 ◽  
Author(s):  
Ossi Kotavaara ◽  
Mari Pukkinen ◽  
Harri Antikainen ◽  
Jarmo Rusanen
Keyword(s):  
Population Change ◽  
Economic Variables ◽  
Socio Economic Variables

scholarly journals Mapping chronic disease prevalence based on medication use and socio-demographic variables: an application of LASSO on administrative data sources in healthcare in the Netherlands

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Koen Füssenich ◽  
Hendriek C. Boshuizen ◽  
Markus M. J. Nielen ◽  
Erik Buskens ◽  
Talitha L. Feenstra
Keyword(s):  
Chronic Disease ◽  
Hospital Admission ◽  
Medication Use ◽  
Disease Prevalence ◽  
Percentage Error ◽  
Economic Variables ◽  
Regional Patterns ◽  
Prevalence Estimates ◽  
Socio Economic Variables ◽  
Chronic Disease Prevalence

Abstract Background Policymakers generally lack sufficiently detailed health information to develop localized health policy plans. Chronic disease prevalence mapping is difficult as accurate direct sources are often lacking. Improvement is possible by adding extra information such as medication use and demographic information to identify disease. The aim of the current study was to obtain small geographic area prevalence estimates for four common chronic diseases by modelling based on medication use and socio-economic variables and next to investigate regional patterns of disease. Methods Administrative hospital records and general practitioner registry data were linked to medication use and socio-economic characteristics. The training set (n = 707,021) contained GP diagnosis and/or hospital admission diagnosis as the standard for disease prevalence. For the entire Dutch population (n = 16,777,888), all information except GP diagnosis and hospital admission was available. LASSO regression models for binary outcomes were used to select variables strongly associated with disease. Dutch municipality (non-)standardized prevalence estimates for stroke, CHD, COPD and diabetes were then based on averages of predicted probabilities for each individual inhabitant. Results Adding medication use data as a predictor substantially improved model performance. Estimates at the municipality level performed best for diabetes with a weighted percentage error (WPE) of 6.8%, and worst for COPD (WPE 14.5%)Disease prevalence showed clear regional patterns, also after standardization for age. Conclusion Adding medication use as an indicator of disease prevalence next to socio-economic variables substantially improved estimates at the municipality level. The resulting individual disease probabilities could be aggregated into any desired regional level and provide a useful tool to identify regional patterns and inform local policy.

scholarly journals Time versus State in Insurance: Experimental Evidence from Contract Farming in Kenya

2018 ◽  
Vol 108 (12) ◽  
pp. 3778-3813 ◽  
Author(s):  
Lorenzo Casaburi ◽  
Jack Willis
Keyword(s):  
Crop Insurance ◽  
Counterparty Risk ◽  
Harvest Time ◽  
Contract Farming ◽  
Present Bias ◽  
The Poor ◽  
Percentage Points ◽  
Randomized Control ◽  
The Difference

The gains from insurance arise from the transfer of income across states. Yet, by requiring that the premium be paid up front, standard insurance products also transfer income across time. We show that this intertemporal transfer can help explain low insurance demand, especially among the poor, and in a randomized control trial in Kenya we test a crop insurance product which removes it. The product is interlinked with a contract farming scheme: as with other inputs, the buyer of the crop offers the insurance and deducts the premium from farmer revenues at harvest time. The take-up rate for pay-at-harvest insurance is 72 percent, compared to 5 percent for the standard pay-up-front contract, and the difference is largest among poorer farmers. Additional experiments and outcomes provide evidence on the role of liquidity constraints, present bias, and counterparty risk, and find that enabling farmers to commit to pay the premium just 1 month later increases demand by 21 percentage points. (JEL G22, I32, O13, O16, Q12, Q14)

scholarly journals Maternal nutritional status (as measured by height, weight and BMI) in Bangladesh: trends and socio-economic association over the period 1996 to 2007

2015 ◽  
Vol 19 (8) ◽  
pp. 1438-1445 ◽  
Author(s):  
Masuda Mohsena ◽  
Rie Goto ◽  
CG Nicholas Mascie-Taylor
Keyword(s):  
Nutritional Status ◽  
Considerable Increase ◽  
Substantial Reduction ◽  
Overweight And Obesity ◽  
Demographic And Health Surveys ◽  
Economic Variables ◽  
Maternal Nutritional Status ◽  
Economic Association ◽  
Education Of Women ◽  
Socio Economic Variables

AbstractObjectiveTo analyse trends in maternal nutritional status in Bangladesh over a 12-year period and to examine the associations between nutritional status and socio-economic variables.DesignMaternal nutritional status indicators were height, weight and BMI. Socio-economic variables used were region, residency, education and occupation of the mothers and their husbands, house type, and possession score in the household.SettingBangladesh Demographic and Health Surveys (1996, 2000, 2004 and 2007) were the source of data.SubjectsA total of 16 278 mothers were included.ResultsAll of the socio-economic variables showed significant associations with maternal nutritional status indicators. Regional variation was found to be present; all three indicators were found to be lowest in the Sylhet division. Upward trends in maternal height, weight and BMI were evident from no possessions to four possessions in households, and for no education to higher education of women and their husbands. Bangladeshi mothers measured in 2007 were found to be on average 0·34 cm taller and 3·36 kg heavier than mothers measured in 1996. Between 1996 and 2007 maternal underweight fell from nearly 50 % to just over 30 % while overweight and obesity increased from about 3 % to over 9 % (WHO cut-offs) or from 7 % to nearly 18 % (Asian cut-offs).ConclusionsThe study reveals that over the 12-year period in Bangladesh there has been a substantial reduction in maternal underweight accompanied by a considerable increase in obesity. It is also evident that malnutrition in Bangladesh is a multidimensional problem that warrants a proper policy mix and programme intervention.

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