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on Discrete Choice Models |
| By: | Andrén, Daniela (Department of Business, Economics, Statistics and Informatics) |
| Abstract: | Using a discrete choice one-factor model, we estimate mean treatment parameters and distributional treatment parameters to analyze the effects of degree of sick leave on the probability of full recovery of lost work capacity for employed and unemployed individuals, respectively. Our results indicate that one year after the sick leave spell started, the average potential impact of part-time sick listing on an individual randomly chosen from the population on sick leave was positive for both groups, but the average effect on those who actually were on part-time sick leave was positive only for the employed, and negative for the unemployed. |
| Keywords: | unemployed; part-time sick leave; selection; unobserved heterogeneity; treatment effects |
| JEL: | I12 J21 J28 |
| Date: | 2011–03–31 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:oruesi:2011_005&r=dcm |
| By: | Lo Duca, Marco (BOFIT); Peltonen, Tuomas (BOFIT) |
| Abstract: | This paper develops a framework for assessing systemic risks and for predicting (out-of-sample) systemic events, i.e. periods of extreme financial instability with potential real costs. We test the ability of a wide range of “stand alone” and composite indicators in predicting systemic events and evaluate them by taking into account policy makers’ preferences between false alarms and missing signals. Our results highlight the importance of considering jointly various indicators in a multivariate framework. We find that taking into account jointly domestic and global macro-financial vulnerabilities greatly improves the performance of discrete choice models in forecasting systemic events. Our framework shows a good out-of-sample performance in predicting the last financial crisis. Finally, our model would have issued an early warning signal for the United States in 2006Q2, 5 quarters before the emergence of money markets tensions in August 2007. |
| Keywords: | early warning indicators; asset price booms and busts; financial stress; macro-prudential policies |
| JEL: | E44 E58 F01 F37 |
| Date: | 2011–04–05 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofitp:2011_002&r=dcm |
| By: | Kim, GwanSeon; Petrolia, Daniel R.; Interis, Matthew G. |
| Abstract: | Replaced with revised version of paper 02/02/11. |
| Keywords: | Contingent Valuation, Double-Bounded Dichotomous Choice, Willingness to Pay, Environmental Economics and Policy, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:saea11:98899&r=dcm |
| By: | Reynolds-Allie, Kenesha; Fields, Deacue |
| Abstract: | Direct marketing to restaurants has become increasingly popular as chefs desire high quality, fresh foods to meet the demand of their customers who are becoming more health conscious. Restaurants accounted for approximately 70 percent of the 2009 total food expenditures, and as a result represent a tremendous potential for developing a sustainable network with local growers. This study seeks to determine restaurant/chefsâ preferences for local food in Alabama using choice based conjoint analysis, as well as, determine challenges faced by restaurants interested in purchasing locally. Availability and lack of knowledge are found to be the major barriers to purchasing locally. Results also suggest there is great potential for direct marketing to restaurants in Alabama that producers are not currently utilizing. |
| Keywords: | Restaurants, Conjoint, Local, Chefs, Preferences, Marketing, Agribusiness, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:saea11:98822&r=dcm |
| By: | Sewando,, Ponsian T.; Mdoe, N. Y. S.; Mutabazi, K.D.S |
| Abstract: | Abstract: The study was conducted to determine farmers’ preferential choice decision of alternative cassava value chain strands and as well as factors behind such decisions in Morogoro rural District, Tanzania. Factor analysis was first used to reduce and identify the factors (variables for further analysis whereby the factors with highest eigen-value were applied to develop factor scores to measure the attitudinal variables. Results indicate that farmers have positive risk attitude towards participation in the alternative cassava value chain strands for commercialization. A count data model known as Poisson model was applied to determine the factors which influenced this attitude. Results indicated that farm size, experience, female-headed households and land-holding had influenced the farmers’ preferential choice decision. Recommendations for enhancing farmers’ participation in profitable cassava value chain strands are strengthening coordination, provision of improved cassava varieties and introduction of cassava processing technologies. |
| Keywords: | Preferential choice decisions; factor analysis; cassava farmers; risk attitude; Poisson model |
| JEL: | D8 |
| Date: | 2011–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:29797&r=dcm |