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Credit Spreads and Monetary Policy

机译:信贷利差和货币政策

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We consider the desirability of modifying a standard Taylor rule for a central bank's interest-rate policy to incorporate cither an adjustment for changes in interest-rate spreads (as proposed by Taylor [2008] and by McCulley and Toloui [2008]) or a response to variations in the aggregate volume of credit (as proposed by Christiano et al. [2007]). We consider the consequences of such adjustments for the way in which policy would respond to a variety of types of possible economic disturbances, including (but not limited to) disturbances originating in the financial sector that increase equilibrium spreads and contract the supply of credit. We conduct our analysis using the simple DSGE model with credit frictions developed in Curdia and Woodford (2009), and compare the equilibrium responses to a variety of disturbances under the modified Taylor rales to those under a policy that would maximize average expected utility. According to our model, a spread adjustment can improve upon the standard Taylor rule, but the optimal size is unlikely to be as large as the one proposed, and the same type of adjustment is not desirable regardless of the source of the variation in credit spreads. A response to credit is less likely to be helpful, and the desirable size (and even the right sign) of the response to credit is less robust to alternative assumptions about the nature and persistence of disturbances.
机译:我们认为有必要修改中央银行利率政策的标准泰勒规则,以纳入对利率利差变化的调整(由泰勒[2008]以及麦库利和托洛伊[2008]提出)。信贷总量的变化(如克里斯蒂安诺等人[2007]提出的)。我们考虑到这种调整对政策应对各种可能的经济干扰的方式的后果,这些经济干扰包括(但不限于)源自金融部门的干扰,这些干扰会增加均衡利差并收缩信贷供应。我们使用在Curdia和Woodford(2009)中开发的带有信用摩擦的简单DSGE模型进行分析,并将修正的泰勒规则下的各种干扰的均衡响应与最大化平均预期效用的策略下的均衡响应进行比较。根据我们的模型,利差调整可以根据标准泰勒规则进行改进,但最佳规模不太可能像建议的那样大,并且无论信贷利差变化的来源如何,均不希望使用相同类型的调整。对信用的回应不太可能有帮助,并且对信用的回应的期望规模(甚至正确的迹象)对于有关干扰的性质和持续性的替代性假设而言,不够可靠。

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  • 来源
    《Working Paper Series》 |2009年第15289期|A1-A21-60|共62页
  • 作者

    Vasco Curdia; Michael Woodford;

  • 作者单位

    Federal Reserve Bank of New York 33 Liberty Street, 3rd Floor New York, NY 10045;

    Department of Economics Columbia University 420 W. 118th Street New York, NY 10027 and NBER;

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