Nonlinear Phillips curves, mixing feedback rules and the distribution of inflation and output

IF 2.3 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2003-12-01 DOI:10.1016/S0165-1889(02)00184-7
Luisa Corrado , Sean Holly
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Abstract

Optimal nominal interest rate rules are usually set assuming that the underlying world is linear. In this paper, we consider the performance of ‘optimal’ rules when the underlying relationship between inflation and the output gap may be nonlinear. In particular if the inflation–output trade-off exhibits nonlinearities this will impart a bias to inflation when a linear rule is used. By deriving some analytical results for the higher moments and in particular the skewness of the distribution of output and inflation, we show that the sign of the skewness of the distribution of inflation and output depends upon the nature of the nonlinearity. For the convex modified hyperbolic function used by Chadha et al. (IMF Staff Papers 39(2) (1992) 395) and Schaling (Bank of England Working Paper Series, 1999) inflation is positively and output negatively skewed. Whereas, if a concave–convex form is used the skewness of inflation and output is reversed. To correct this bias we propose a piecewise linear rule, which can be thought of as an approximation to the nonlinear rule of Schaling (1999). In order to evaluate the relevance of these results, we turn to some illustrative empirical results for the US and the UK. We show that this reduces the bias, but at the expense of an increase in the volatility of the nominal interest rate.
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非线性菲利普斯曲线,混合反馈规则和通货膨胀和产出的分布
最优名义利率规则通常假定基础世界是线性的。在本文中,我们考虑了当通货膨胀和产出缺口之间的潜在关系可能是非线性时“最优”规则的性能。特别是如果通货膨胀-产出权衡表现出非线性,当使用线性规则时,这将对通货膨胀产生偏差。通过对高矩,特别是输出和膨胀分布偏度的一些分析结果,我们证明了膨胀和输出分布偏度的符号取决于非线性的性质。对于Chadha等人(IMF工作人员论文39(2)(1992)395)和Schaling(英国央行工作论文系列,1999)使用的凸修正双曲函数,通胀为正,产出为负偏。然而,如果使用凹凸形式,则通货膨胀和产出的偏度是相反的。为了纠正这种偏差,我们提出了分段线性规则,它可以被认为是Schaling(1999)的非线性规则的近似。为了评估这些结果的相关性,我们转向美国和英国的一些说明性实证结果。我们表明,这减少了偏差,但代价是名义利率的波动性增加。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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