Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity

Hong, Seung Hyun; Phillips, Peter C.B.

doi:10.1198/jbes.2009.07182

Cited by 47 publications

(48 citation statements)

References 41 publications

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“…Additionally also specification and cointegration tests are developed. With respect to specification testing amongst other things this paper extends the work of Hong and Phillips (2010), who consider LM-type specification testing based on residuals of cointegrating linear relationships, in several aspects (see Section 2.3). With respect to asymptotic theory our work relies upon important contributions of Chang, Park, and Phillips (2001), Phillips (1999, 2001) and Ibragimov and Phillips (2008).…”

Section: Introductionmentioning

confidence: 86%

“…Our assumptions are most closely related to those of Chang, Park, and Phillips (2001), Phillips (1999, 2001) and Hong and Phillips (2010). processes to the concept of near epoch dependent sequences and some moment conditions.…”

Section: Setup and Assumptionsmentioning

confidence: 99%

“…Thus, the assumptions with respect to kernel (A3) and bandwidth choice (A4) formulated in Jansson have to be taken into account. For more explicit calculations with respect to long-run variance estimation in a context related to this paper see also Hong and Phillips (2010). For the remainder of the paper we assume from now on that long-run variance estimation is performed consistently.…”

Section: Fully Modified Ols Estimationmentioning

confidence: 99%

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Cointegrating Polynomial Regressions: Fully Modified Ols Estimation and Inference

2015

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This paper develops a fully modified OLS estimator for cointegrating polynomial regressions, i.e. for regressions including deterministic variables, integrated processes and powers of integrated processes as explanatory variables and stationary errors. The errors are allowed to be serially correlated and the regressors are allowed to be endogenous. The paper thus extends the fully modified approach developed in Phillips and Hansen (1990). The FM-OLS estimator has a zero mean Gaussian mixture limiting distribution, which is the basis for standard asymptotic inference. In addition Wald and LM tests for specification as well as a KPSS-type test for cointegration are derived. The theoretical analysis is complemented by a simulation study which shows that the developed FM-OLS estimator and tests based upon it perform well in the sense that the performance advantages over OLS are by and large similar to the performance advantages of FM-OLS over OLS in cointegrating regressions.

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Section: Introductionmentioning

confidence: 86%

Section: Setup and Assumptionsmentioning

confidence: 99%

Section: Fully Modified Ols Estimationmentioning

confidence: 99%

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Cointegrating Polynomial Regressions: Fully Modified Ols Estimation and Inference

2015

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“…In order to maintain a good balance between the goodness of fit and the model variability, a large number of basis func-1 Other contributions to the literature on the stability tests in cointegrating regression includes Hansen (1992), Hao (1996), Quintos (1997), Kuo (1998), Hansen and Johansen (1999), Johansen, Mosconi and Nielsen (2000), Harris, McCabe and Leybourne (2002), and among others. Furthermore, Hong and Phillips (2010) propose a modified RESET test for testing linearity in the cointegration model. Gao, King, Lu and Tjøstheim (2009) consider a nonparametric specification test for a nonparametric time series model with nonstationary variables.…”

Section: Introductionmentioning

confidence: 99%

Estimation and Inference for Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines

Chen¹,

Fang²,

Li³

2014

Econom. Theory

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This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing the mixed model representation of penalized splines, we develop a likelihood ratio test statistic for checking the stability of the regression coefficients. We derive both the exact and the asymptotic null distributions of this test statistic. We also demonstrate its optimality by examining its local power performance. These theoretical findings are well supported by simulation studies.JEL Classification: C12, C14, C22

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“…Hong and Phillips (2005), and Kasparis (2008) considered model specification testing in cointegration models. Juhl and Xiao (2005b) focused on testing for cointegration using a partially linear model.…”

Section: Introductionmentioning

confidence: 99%

Nonparametric Estimation and Specification Testing in Nonstationary Time Series Models

Gao

Chen

et al. 2010

SSRN Journal

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In this paper, we consider both estimation and testing problems in a nonlinear time series model with nonstationarity. A nonparametric estimation method is proposed to estimate a sequence of nonparametric departure functions. We also propose a test statistic to test whether the regression function is of a known parametric nonlinear form. The power function of the proposed nonparametric test is studied and an asymptotic distribution of the test statistic is shown to depend on the asymptotic behavior of the "distance function" ∆ n (·) under a sequence of general semiparametric local alternatives. The asymptotic theory developed in this paper differs from existing work on nonparametric estimation and specification testing in the stationary time series case. In order to implement the proposed test in practice, a computerintensive bootstrap simulation procedure is proposed and asymptotic approximations for both the size and power functions are established. Furthermore, the bandwidth involved in the test statistic is selected by maximizing the power function while the size function is controlled by a significance level. Meanwhile, both simulated and real data examples are provided to illustrate the proposed approach.

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Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity

Cited by 47 publications

References 41 publications

Cointegrating Polynomial Regressions: Fully Modified Ols Estimation and Inference

Cointegrating Polynomial Regressions: Fully Modified Ols Estimation and Inference

Estimation and Inference for Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines

Nonparametric Estimation and Specification Testing in Nonstationary Time Series Models

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