scholarly journals I Learn, You Learn, We Gain. Experience in Crop Insurance Markets

2018 ◽  
Author(s):  
Fabio Gaetano Santeramo
Keyword(s):  
Crop Insurance ◽  
Insurance Markets

Evidence of Adverse Selection in Crop Insurance Markets

2001 ◽  
Vol 68 (4) ◽  
pp. 685 ◽  
Author(s):  
Shiva S. Makki ◽  
Agapi Somwaru
Keyword(s):  
Adverse Selection ◽  
Crop Insurance ◽  
Insurance Markets

scholarly journals Rationality of Choices in Subsidized Crop Insurance Markets

2016 ◽  
Vol 99 (3) ◽  
pp. 732-756 ◽  
Author(s):  
Xiaodong Du ◽  
Hongli Feng ◽  
David A. Hennessy
Keyword(s):  
Crop Insurance ◽  
Insurance Markets

Systemic Risk, Reinsurance, and the Failure of Crop Insurance Markets

1997 ◽  
Vol 79 (1) ◽  
pp. 206-215 ◽  
Author(s):  
Mario J. Miranda ◽  
Joseph W. Glauber
Keyword(s):  
Systemic Risk ◽  
Crop Insurance ◽  
Insurance Markets

Studying the factors of regional insurance market development using the correlation and regression analysis

2020 ◽  
Vol 26 (7) ◽  
pp. 1610-1630
Author(s):  
E.L. Prokop'eva
Keyword(s):  
Regression Analysis ◽  
Federal District ◽  
Insurance Market ◽  
Market Development ◽  
Insurance Markets ◽  
Regression Equations ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Country Level ◽  
Inverse Effect

Subject. The article investigates and quantifies factors of insurance markets functioning in Russian regions, and reveals possibilities to manage them. Objectives. The purpose of the study is to substantiate regional factors that determine the specifics of regional insurance market development; to quantify them to increase the efficiency of regional insurance. Methods. The study draws on statistical methods, functional analysis, algorithm development, correlation and regression analysis. Results. I calculated coefficients of pair and multiple correlation with the indicators of insurance markets in the context of the subjects of the Russian Federation, and composed regression equations. Based on the analysis, I determined the algorithm for inverse effect of the insurance market on the economic, social, fiscal and environmental performance of the region, offered appropriate measures aimed at developing the economic potential of the region and its social sphere. Conclusions. The paper considers the case of the Republic of Khakassia, one of depressed subjects in the Siberian Federal District. The developed models can be used for other regions of Russia, given the geographical and economic features of development. The findings may help generate regional strategies for socio-economic development at the country level. The scientific contribution and the novelty of the work consist of systematizing and quantifying the factors affecting the insurance mechanisms of regional markets, and assessing the inverse effect of insurance mechanisms on integrated development of the region.

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