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Inferences about structural instability in macroeconomics.

机译：关于宏观经济学中结构不稳定的推论。

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摘要

I investigate the problem of making inferences about nonlinearity and volatility change in macroeconomic time series from both the theoretical and econometric perspectives.;In the first essay, I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatility), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about prevailing and future regimes based on Bayes' rule. I develop an estimation method that takes these probabilistic inferences into account when relating state variables to observed data. In an application to postwar U.S. data, I find stronger support for regime switching in monetary policy than in technology or nominal rigidities. In addition, a model with regime switching policy that conforms to the long-run Taylor principle given in Davig and Leeper (2007) is preferred to a determinacy- indeterminacy model motivated by Lubik and Schorfheide (2004). These empirical results indicate that, even though a passive policy regime produced more volatility in the economy from the early 1970s to the mid-1980s, the economy can be explained by determinacy over the entire postwar period, implying no role for sunspot shocks in explaining the changes in volatility.;The second essay proposes a new approach to constructing confidence sets for the timing of structural breaks. This approach involves using Markov-chain Monte Carlo methods to simulate the marginal "fiducial" distributions of break dates from the likelihood function. We compare our proposed approach to asymptotic and bootstrap confidence sets and find that it has the best overall finite-sample performance in terms of producing short confidence sets with accurate coverage rates.;In the third essay, I study how to make inference about complicated patterns of structural breaks in time series. For example, multiple groups of parameters (e.g., intercept, persistence, and conditional variance) have structural breaks independently at different dates. In this essay, I extend Chib's (1998) algorithm in which a Markov-chain transition matrix governs the change-point structure to allow for breaks at different dates in an efficient and tractable way. In particular, I do this by adding as many transition matrices as necessary for the parameter groups. I apply this approach to postwar U.S. inflation and find support for an autoregressive model with multiple structural breaks in intercept (higher around 1965), persistence (lower around the mid-1980s), and conditional variance (higher around 1968 and lower again around the mid-1980s).
机译：我从理论和计量经济学的角度研究了对宏观经济时间序列的非线性和波动性变化进行推断的问题。在第一篇文章中，我估计了在货币政策（通货膨胀目标和反应系数），技术不断变化的情况下的DSGE模型。 （增长率和波动性）和/或名义价格刚性。在模型中，假定代理知道深的参数值，但根据贝叶斯规则对当前和将来的状态进行概率推断。我开发了一种估计方法，该方法将状态变量与观察到的数据相关联时考虑了这些概率推断。在对战后美国数据的应用中，我发现货币政策的政权转换比技术或名义刚性更受支持。另外，具有政权转换政策的模型应符合Davig and Leeper（2007）的长期泰勒原理，而不是由Lubik和Schorfheide（2004）提出的确定性-不确定性模型。这些经验结果表明，即使从1970年代初到1980年代中期，被动的政策体制在经济中造成了更大的动荡，但可以通过整个战后时期的确定性来解释经济，这并不意味着黑子冲击在解释经济波动方面没有作用。第二篇文章提出了一种新的方法来构造结构性突破时间的置信度集。该方法涉及使用马尔可夫链蒙特卡罗方法从似然函数模拟中断日期的边际“基准”分布。我们比较了我们提出的渐近和自举置信度集的方法，发现在生成具有准确覆盖率的短置信度集方面，它具有最佳的整体有限样本性能。在第三篇文章中，我研究了如何对复杂模式进行推断时间序列中的结构性中断。例如，多组参数（例如，截距，持久性和条件方差）在不同日期具有独立的结构中断。在本文中，我扩展了Chib（1998）的算法，在该算法中，马尔可夫链跃迁矩阵控制变化点结构，以便以有效且易于处理的方式允许在不同日期中断。特别是，我通过为参数组添加所需数量的转换矩阵来实现此目的。我将这种方法应用于战后美国的通货膨胀，并为自回归模型提供了支持，该模型具有多个拦截结构中断（在1965年左右较高），持续性（在1980年代中期较低）和条件方差（在1968年左右较高并且在中期左右又降低-1980年代）。

著录项

  • 作者

    Eo, Yunjong.;

  • 作者单位

    Washington University in St. Louis.;

  • 授予单位 Washington University in St. Louis.;
  • 学科 Economics General.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 110 p.
  • 总页数 110
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 经济学;
  • 关键词

  • 入库时间 2022-08-17 11:38:29

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