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A New Approach to Robust Inference in Cointegration

Jin, Sainan; Phillips, Peter C.B.; Sun, Yixiao - Cowles Foundation for Research in Economics, Yale University - 2005

A new approach to robust testing in cointegrated systems is proposed using nonparametric HAC estimators without truncation. While such HAC estimates are inconsistent, they still produce asymptotically pivotal tests and, as in conventional regression settings, can improve testing and inference....

Persistent link: https://www.econbiz.de/10005593449

Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects

Zhang, Yonghui; Su, Liangjun; Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 2011

This paper proposes a nonparametric test for common trends in semiparametric panel data models with fixed effects based on a measure of nonparametric goodness-of-fit (R^2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain...

Persistent link: https://www.econbiz.de/10009358886

Functional Coefficient Nonstationary Regression

Gao, Jiti; Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 2013

. An empirical illustration examines nonlinear dependencies in aggregate consumption function behavior in the US over the …

Persistent link: https://www.econbiz.de/10010895669

The Tail Behavior of Maximum Likelihood Estimates of Cointegrating Coefficients in Error Correction Models

Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 1991

number of variables in the system and r is the dimension of the cointegration space. These results help to explain simulation …

Persistent link: https://www.econbiz.de/10005634731

The Long-Run Australian Consumption Function Reexamined: An Empirical Exercise in Bayesian Influence

Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 1991

This paper reports an empirical application of new Baynesian methodology to Australian data on consumption, income … nonstationarity and cointegration in the data and various long-run model specifications are studied in detail. Bayesian empirical … the classical test results are mixed. Our empirical results show that real private consumption expenditure and household …

Persistent link: https://www.econbiz.de/10005634716

Higher-order Improvements of the Parametric Bootstrap for Long-memory Gaussian Processes

Andrews, Donald W.K.; Lieberman, Offer - Cowles Foundation for Research in Economics, Yale University - 2002

This paper determines coverage probability errors of both delta method and parametric bootstrap confidence intervals (CIs) for the covariance parameters of stationary long-memory Gaussian time series. CIs for the long-memory parameter d_0 are included. The results establish that the bootstrap...

Persistent link: https://www.econbiz.de/10005464054

On the Number of Bootstrap Repetitions for Bootstrap Standard Errors, Confidence Intervals, and Tests

Andrews, Donald W.K.; Buchinsky, Moshe - Cowles Foundation for Research in Economics, Yale University - 1997

This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors, confidence intervals, and tests. For each of these problems, the paper provides a three-step method for choosing B to achieve a desired level of accuracy. Accuracy is measured by the...

Persistent link: https://www.econbiz.de/10004990816

Higher-order Improvements of the Parametric Bootstrap for Markov Processes

Andrews, Donald W.K. - Cowles Foundation for Research in Economics, Yale University - 2001

This paper provides bounds on the errors in coverage probabilities of maximum likelihood-based, percentile-t, parametric bootstrap confidence intervals for Markov time series processes. These bounds show that the parametric bootstrap for Markov time series provides higher-order improvements...

Persistent link: https://www.econbiz.de/10005093948

Smoothed Empirical Likelihood Methods for Quantile Regression Models

Whang, Yoon-Jae - Cowles Foundation for Research in Economics, Yale University - 2004

This paper considers an empirical likelihood method to estimate the parameters of the quantile regression (QR) models and to construct confidence regions that are accurate in finite samples. To achieve the higher-order refinements, we smooth the estimating equations for the empirical likelihood....

Persistent link: https://www.econbiz.de/10005593469

Higher-Order Improvements of a Computationally Attractive-Step Bootstrap for Extremum Estimators

Andrews, Donald W.K. - Cowles Foundation for Research in Economics, Yale University - 1999

This paper establishes the higher-order equivalence of the k-step bootstrap, introduced recently by Davidson and MacKinnon (1999a), and the standard bootstrap. The k-step bootstrap is a very attractive alternative computationally to the standard bootstrap for statistics based on nonlinear...

Persistent link: https://www.econbiz.de/10005593591