scholarly journals Predicting Italian Wine Quality from Weather Data and Expert Ratings

2019 ◽  
Vol 14 (3) ◽  
pp. 234-251 ◽  
Author(s):  
Alessandro Corsi ◽  
Orley Ashenfelter
Keyword(s):  
Probit Model ◽  
Weather Conditions ◽  
Ordered Probit ◽  
Weather Data ◽  
Ordered Probit Model ◽  
Wine Quality ◽  
Italian Wine ◽  
Quality Ratings ◽  
Expert Ratings ◽  
Jel Classifications

AbstractIn this paper we estimate how a variety of subjective measures of quality taken from the published opinions of several experts on Italian wines (Barolo and Barbaresco) are determined by the weather conditions during the relevant season, in order to assess their reliability. Since these measures of quality are only ordinal, we estimate their determinants using an ordered probit model. The method provides measures of the determinants of vintage quality ratings and suggestions on the reliability of each expert. (JEL Classifications: D12, Q11, Q13)

Do the heterogeneous determinants of life satisfaction affect differently across borrowers of diverse credit sources? A propensity score approach

2018 ◽  
Vol 45 (8) ◽  
pp. 1142-1158 ◽  
Author(s):  
Tiken Das ◽  
Manesh Choubey
Keyword(s):  
Life Satisfaction ◽  
Propensity Score ◽  
Probit Model ◽  
Ordered Probit ◽  
Primary Data ◽  
Ordered Probit Model ◽  
Future Research ◽  
Content Type ◽  
Credit Access ◽  
Physical Assets

Purpose The purpose of this paper is to evaluate the non-monetary effect of credit access by providing an econometric framework which controls the problem of selection bias. Design/methodology/approach The study is conducted in Assam, India and uses a quasi-experiment design to gather primary data. The ordered probit model is used to evaluate the non-monetary impact of credit access. The paper uses a propensity score approach to check the robustness of the ordered probit model. Findings The study confirms the positive association of credit access to life satisfaction of borrowers. It is found that, in general, rural borrower’s life satisfaction is influenced by the ability and capacity to work, the value of physical assets of the borrowers as well as some other lenders’ and borrowers’ specific factors. But, the direction of causality of the factors influencing borrowers’ life satisfaction is remarkably different across credit sources. Research limitations/implications The study argues to provide productive investment opportunities to semiformal and informal borrowers while improving their life satisfaction score. Although the results are adjusted for selection and survivorship biases, it is impossible with the available data to assess which non-income factors explain the findings, and therefore this limitation is left to future research. Originality/value The study contributes to the literature of rural credit by assessing the probable differences among formal, semiformal and informal credit sources with respect to non-monetary impacts.

scholarly journals The Organization of Political Violence by Insurgencies

2012 ◽  
Vol 18 (3) ◽  
Author(s):  
Roos Haer
Keyword(s):  
Political Violence ◽  
Probit Model ◽  
Ordered Probit ◽  
Process Theory ◽  
Ordered Probit Model ◽  
Armed Groups ◽  
Human Right ◽  
Armed Group ◽  
The World ◽  
The Relationship

AbstractA range of theories have attempted to explain the variation in civilian abuse of warring parties. Most of these theories have been focused on the strategic environment in which these acts take place. Less attention is devoted to the perpetrators of these human right abuses themselves: the armed groups. This study tries to fill this niche by using the organizational process theory in which it is assumed that armed groups, like every organization, struggles for survival. The leader tries to ensure the maintenance of her armed group by increasing her control over her troops. The relationship between the level of control and the perpetrated civilian abuse is examined with a new dataset on the internal structure of more than 70 different armed groups around the world. With the help of a Bayesian Ordered Probit model, this new dataset on civilian abuse is analyzed. The results show that especially particular incentives play an important role.

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