【24h】

Estimating Models with Dispersed Information

机译:带有分散信息的估计模型

获取原文
获取原文并翻译 | 示例
           

摘要

We conduct likelihood evaluation of a DSGE model in which firms have imperfect common knowledge. Imperfect common knowledge is found to be more successful than price stickiness a la Calvo to account for the highly persistent effects of nominal shocks on out-put and inflation. Our likelihood analysis suggests that firms pay little attention to aggregate nominal conditions. This paper shows that such allocation of attention is plausible because it is optimal for firms with a reasonably small size of information frictions and a size of idiosyncratic uncertainty that is in line with the micro evidence on price changes.
机译:我们对企业知识不完善的DSGE模型进行可能性评估。人们发现,不完善的常识比按价格计算的粘性更成功,这可以说明名义冲击对产出和通货膨胀的高度持续影响。我们的可能性分析表明,企业很少关注总体名义条件。本文表明,这种注意力分配是合理的,因为它对于信息摩擦量较小且特质不确定性大小与价格变化的微观证据一致的公司而言是最佳选择。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号