G2TT
来源类型Discussion paper
规范类型论文
来源IDDP7447
DP7447 Frequentist Inference in Weakly Identified DSGE Models
Lutz Kilian; Atsushi Inoue; Pablo A. Guerron-Quintana
发表日期2009-09-23
出版年2009
语种英语
摘要I present two flexible models of multivariate, count data regression that make use of the Sarmanov family of distributions. This approach overcomes several existing difficulties to extend Poisson regressions to the multivariate case, namely: i) it is able to account for both over and underdispersion, ii) it allows for correlations of any sign among the counts, iii) correlation and dispersion depend on different parameters, and iv) constrained maximum likelihood estimation is computationally feasible. Models can be extended beyond the bivariate case. I estimate the bivariate versions of two of these models to address whether the pricing strategies of competing duopolists in the early U.S. cellular telephone industry can be considered strategic complements or substitutes. I show that a Sarmanov model with double Poisson marginals outperforms the alternative count data model based on a multivariate renewal process with gamma distributed arrival times because the latter imposes very restrictive constraints on the valid range of the correlation coefficients.
主题Industrial Organization
关键词Sarmanov distributions Double poisson Gamma Multivariate count data models Tariff options
URLhttps://cepr.org/publications/dp7447
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/536298
推荐引用方式
GB/T 7714
Lutz Kilian,Atsushi Inoue,Pablo A. Guerron-Quintana. DP7447 Frequentist Inference in Weakly Identified DSGE Models. 2009.
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