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on Discrete Choice Models |
| By: | Xiaoming Li (University of Connecticut) |
| Abstract: | Estimations of nonlinear panel models that include individual specific fixed effects are complicated by the incidental parameters problem, that is, the asymptotic bias in the estimation of typical fixed effects panel models generally results in inconsistent estimates. In this paper, I characterize the leading term of a large-T expansion of the biases in the nonlinear least square estimator (NLSE) and estimators of the average partial effects in panel fractional response models. The resulting estimator after analytical bias correction is robust to the incidental parameters bias and reduces the bias order from O(T−1) to O(T−2). I also examine the finite sample performance of the proposed estimator using a new data generating process in which panel fractional response variables are collapsed from repeated, clustered cross-sectional binary probit choices. A proof showing the generated data satisfies the identification assumption at the cluster level has been given. Simulation results suggest that, in the static case, the bias corrected estimator performs comparably to the quasi-maximum likelihood estimator (QMLE), which is the standard approach in the literature, for 8 or more periods, while in the dynamic case, the bias corrected estimators are substantially superior to those QMLE’s. |
| Keywords: | Fractional responses, Panel Data, Unobserved effects, Probit, Partial effects, Bias, Incidental parameters problem, Fixed effects, Bias Correction |
| JEL: | C23 C25 I22 |
| Date: | 2011–06 |
| URL: | http://d.repec.org/n?u=RePEc:uct:uconnp:2011-11&r=dcm |
| By: | Adi Schnytzer (Department of Economics, Bar Ilan University) |
| Abstract: | The purpose of this paper is to make a novel contribution to the literature on the prediction market for the Australian Football League, the major sports league in which Australian Rules Football is played. Taking advantage of a novel micro-level data set which includes detailed per-game player statistics, predictions are presented and tested out-of-sample for the simplest kind of bet: fixed odds win betting. It is shown that player-level statistics may be used to yield very modest profits net of transaction costs over a number of seasons, provided some more global variables are added to the model. A comparison of different specifications of the linear probability model (LPM) versus conditional logit (CLOGIT) regressions reveals that the LPM usually outperforms CLOGIT in terms of profitability. It is further shown that adding significant variables to a regression specification which is clearly superior in econometric terms may reduce the efficacy of the prediction and thus profits. |
| Date: | 2011–03 |
| URL: | http://d.repec.org/n?u=RePEc:biu:wpaper:2011-15&r=dcm |
| By: | Mateusz Mysliwski (Warsaw School of Economics) |
| Abstract: | The aim of this paper is twofold. Firstly, we attempt to investigate the challenges for the constantly changing music industry on the ex- ample of Poland, positing a conclusion that both artists and lables could prot from a precisely determined set of factors in uencing the ultimate sales success. On the other hand, the article intends to ll the gap between record industry analyses an econometric literature, as in the course of research, we found that the use of quantitative methods is rarely encountered in such analyses. The study uses a self-compiled dataset, containing information on 619 albums, which appeared on the Ocial Sales Chart (OLiS) between 2008 and 2009. We propose three models for dierent quantitative variables and summarize the obtained results, stating that the use of microeconometric methods in this area of research seems promising. |
| Keywords: | music industry, discrete choice models, partial proportional odds model |
| JEL: | C25 C51 C52 L82 |
| Date: | 2011–05–30 |
| URL: | http://d.repec.org/n?u=RePEc:wse:wpaper:54&r=dcm |
| By: | MORITA Tamaki; MANAGI Shunsuke |
| Abstract: | Eco-labeling systems for fish and fishery products provide the fishery industry with incentives to conserve marine resources and protect the environment. Under these systems, unlike command-and-control fishery management mechanisms, the fishery industry voluntarily controls their catch. By choosing products labeled as ecologically friendly, consumers can also help promote sustainable fisheries. <br /><br />Despite Japan being a major fishing and fish-consuming country, the system is still in its infancy. One reason may be that Japanese consumers are not aware of the fisheries' harmful ecological impacts and the relationship of these impacts with their seafood consumption. Would Japanese consumers change their consumption patterns if they knew which of the fish available in the supermarkets, were being overfished?<br /><br />We devised a web survey that included discrete choice conjoint analysis. We investigated what kind of information influences consumers' awareness of overfishing, and also what affects consumers' preferences regarding eco-labeled seafood. Our study revealed that Japanese consumers are willing to choose seafood based on eco-labeling when they: understand the role of eco-labeling, encounter reliable information about the item's relationship with marine resources, and know that a reliable organization is responsible for the labels. This result supports the idea of designing a feasible eco-labeling mechanism in Japan. |
| Date: | 2010–07 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rdpsjp:10037&r=dcm |