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美国财政政策冲击：通过 GMM 实现代理变量 SVAR 过度识别AI 解读

Summary Using external instruments, one can recover the effects of individual shocks without fully identifying a vector autoregression (VAR). We show that fully or almost fully instrumenting a VAR—that is, using an instrument for each shock—allows one to overidentify the model by incorporating the condition that the structural shocks are uncorrelated, via the generalized method of moments (GMM). We apply our approach to a fiscal VAR for the United States over 1948–2019,…

经验似然区块自助法AI 解读

Monte Carlo evidence has made it clear that asymptotic tests based on generalized method of moments (GMM) estimation have disappointing size. The problem is exacerbated when the moment conditions are serially correlated. Several block bootstrap techniques have been proposed to correct the problem, including Hall and Horowitz (1996) and Inoue and Shintani (2006). We propose an empirical likelihood block bootstrap procedure to improve inference where models are characterized…

协整检验之间的混合信号AI 解读

Abstract This paper illustrates that, under the null hypothesis of no cointegration, the correlation of p ‐values from a single‐equation residual‐based test (i.e., ADF or $\widehat{Z}_{\alpha}$ ) with a system‐based test (trace or maximum eigenvalue) is very low even as the sample size gets large. With data‐generating processes under the null or ‘near’ it, the two types of tests can yield virtually any combination of p ‐values regardless of sample size. As a practical…

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存在机制转换的协整模型中基于残差的检验AI 解读

In this paper we examine tests for cointegration which allow for the possibility of regime shifts. We propose ADF-, Zα-, and Zt-type tests designed to test the null of no cointegration against the alternative of cointegration in the presence of a possible regime shift. In particular we consider cases where the intercept and/or slope coefficients have a single break of unknown timing. A formal proof is provided for the limiting distributions of the various tests for the…

线性二次模型中的协整检验AI 解读

This article evaluates the finite-sample performance of various tests for cointegration by Monte Carlo methods. The evaluation takes place within the linear quadratic model. The results indicate sharp differences in the ability of the tests to detect cointegrating relations, especially when the cost-of-adjustment term and the number of regressors are large. Although no single test dominates for all the parameter settings considered, overall the augmented Dickey-Fuller,…

A stochastic macroeconomic model with no free parameters can be tested by comparing its features, such as moments, with those of data. Repeated simulation allows exact tests and gives the distribution of the sample moment under the null hypothesis that the model is true. The authors calculate the size of tests of the model studied by R. Mehra and E. C. Prescott. The approximate size of their test (which seeks to match model-generated, mean, risk-free interest rates and…

平稳时间序列长期性质的检验AI 解读

In this article, a Wald test is developed for testing long-run properties of stationary time series. The authors specialize the test and consider testing the long-run independence of two time series. They examine two applications of the test for long-run independence.

自回归条件异方差的非参数检验：马尔可夫链方法AI 解读

In this article we propose a nonparametric test for autoregressive conditional heteroscedasticity based on finite-state Markov chains. A simple Monte Carlo experiment suggests that in finite samples it performs comparably to the Lagrange multiplier test under conditional normality and is superior for the t, lognormal, and exponential distributions. As an illustration, we apply both tests to Canadian/U.S. forward foreign exchange data.

理性预期假说约束的 Wald 检验构造AI 解读

Abstract In this paper, we examine the small sample properties of alternative formulations of Wald tests of non‐linear restrictions implied by the rational expectations hypothesis. A Monte Carlo analysis is presented as well as an example using Canadian aggregate time series data. The evidence indicates that Wald test results are extremely sensitive in small samples to the way in which the non‐linear restrictions in such models are parameterized, with a multiplicative form…