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on Discrete Choice Models |
| By: | Zhang, Xiao-Bing (Department of Economics, School of Business, Economics and Law, Göteborg University); Hassen, Sied (Department of Economics, School of Business, Economics and Law, Göteborg University) |
| Abstract: | Using seven rounds of household survey data that span more than a decade, this paper analyzes the determinants of household fuel choice in urban China. Unlike the existing studies, we use an empirical strategy that takes into account the potential heterogeneous effects of socio-economic factors in households’ preference ordering. Robustness of this empirical strategy is checked against alternative methods. The results show that household fuel choice in urban China is related to fuel prices, household’s economic status and size, and household head’s gender, education and occupation. Our results suggest that policies and interventions that raise household income, reduce prices of clean fuel sources, and empower women in the household are of great significance in encouraging the adoption of clean energy sources. |
| Keywords: | Household fuel choice; Panel data; Random effect generalized probit model; Urban China |
| JEL: | C25 Q23 Q40 Q42 |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:gunwpe:0595&r=dcm |
| By: | Sami BEN JABEUR; Youssef FAHMI |
| Abstract: | The aim of this paper is to compare between three statistical methods in predicting corporate financial distress. We will use the Discriminant Analysis, Logit model and Random Forest. These approaches are based on a sample of 800 companies during the period from 2006 to 2008, as well as on the use of 33 financial ratios. The results show a superiority of the random forest approach. |
| Date: | 2014–06–02 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-319&r=dcm |
| By: | Sami BEN JABEUR |
| Abstract: | The objective of this article is to apply the technique of the PLS logistic regression to the forecast of the financial distress of the French firm. This research is motivated by the shortcomings of traditional models. The sample consisted of 800 French SMEs for which accounting and financial ratios were calculated over the period 2008-2006. The purpose of our work is within the context of analysis and explanation of financial distress. It aims to show how the forecast provides a clear explanation of distress through indicators that reflect the empirical situation. |
| Keywords: | financial distress, Logit model, PLS regression. |
| Date: | 2014–06–02 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-321&r=dcm |