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Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to ppp hypothesis: new results

P Pedroni
- Vol. 20, Iss: 3, pp 597-627
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The article was published on 2004-01-01 and is currently open access. It has received 3609 citations till now. The article focuses on the topics: Cointegration & Sample (statistics).

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Book

Econometric Analysis of Panel Data

TL;DR: In this article, the authors proposed a two-way error component regression model for estimating the likelihood of a particular item in a set of data points in a single-dimensional graph.
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Testing for error correction in panel data

TL;DR: This article proposed new error correction-based cointegration tests for panel data, which have good small-sample properties with small size distortions and high power relative to other popular residual-based panel coIntegration tests.
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Introductory Econometrics for Finance

TL;DR: The third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time as discussed by the authors.
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A PANIC Attack on Unit Roots and Cointegration

TL;DR: In this paper, a new methodology called PANIC (Pan Analysis of Nonstationarity in Idiosyncratic and Common components) is proposed to detect whether the nonstationarity of a series is pervasive or variable-specific.
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Renewable energy consumption and economic growth: Evidence from a panel of OECD countries

TL;DR: In this paper, the relationship between renewable energy consumption and economic growth for a panel of twenty OECD countries over the period 1985-2005 within a multivariate framework was examined, where a panel cointegration and error correction model was employed to infer the causal relationship.
References
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Journal ArticleDOI

Testing for a Unit Root in Time Series Regression

TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
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Statistical analysis of cointegration vectors

TL;DR: In this paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
Journal ArticleDOI

Testing for unit roots in heterogeneous panels

TL;DR: In this article, a unit root test for dynamic heterogeneous panels based on the mean of individual unit root statistics is proposed, which converges in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension)→∞.
Journal ArticleDOI

Unit root tests in panel data: asymptotic and finite-sample properties

TL;DR: In this article, the authors consider pooling cross-section time series data for testing the unit root hypothesis, and they show that the power of the panel-based unit root test is dramatically higher, compared to performing a separate unit-root test for each individual time series.

Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models / Søren Johansen

S Johansen
TL;DR: In this paper, the authors present the likelihood methods for the analysis of cointegration in VAR models with Gaussian errors, seasonal dummies, and constant terms, and show that the asymptotic distribution of the maximum likelihood estimator is mixed Gausssian.
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