Beveridge curve under endogenous separation model: The role of wage rigidity and match-specific productivity

IF 4.2 2区 经济学 Q1 ECONOMICS Economic Modelling Pub Date : 2024-08-12 DOI:10.1016/j.econmod.2024.106845
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Abstract

A standard endogenous separation model developed by Mortensen and Pissarides (1994) has a drawback in replicating the negative correlation between unemployment and vacancy rates. To address this issue, I extended the model by incorporating wage rigidity and modifying the assumption about idiosyncratic match-specific productivity. Results indicate that introducing wage rigidity can produce the Beveridge curve, while the degree of negative correlation is slightly lower than that presented in the data. Modifying the model to randomly draw match-specific productivity for new matches also increases the degree of negative correlation between unemployment and vacancy rates. These results suggest that an endogenous separation model can explain the observed variation by adding frictions.

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内生分离模型下的贝弗里奇曲线:工资刚性和特定匹配生产力的作用
Mortensen 和 Pissarides(1994 年)建立的标准内生离职模型在复制失业率和空缺率之间的负相关性方面存在缺陷。为了解决这个问题,我对模型进行了扩展,加入了工资刚性并修改了关于特异匹配生产率的假设。结果表明,引入工资刚性可以产生贝弗里奇曲线,而负相关程度略低于数据。修改模型以随机抽取新匹配的特定生产率,也会增加失业率和空缺率之间的负相关程度。这些结果表明,内生分离模型可以通过增加摩擦来解释观察到的变化。
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来源期刊
Economic Modelling
Economic Modelling ECONOMICS-
CiteScore
8.00
自引率
10.60%
发文量
295
期刊介绍: Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling. The journal prime objective is to provide an international review of the state-of-the-art in economic modelling. Economic Modelling publishes the complete versions of many large-scale models of industrially advanced economies which have been developed for policy analysis. Examples are the Bank of England Model and the US Federal Reserve Board Model which had hitherto been unpublished. As individual models are revised and updated, the journal publishes subsequent papers dealing with these revisions, so keeping its readers as up to date as possible.
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