### Abstract

This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section (n) and time series (T) observations. The limit theory allows for both sequential limits, wherein T → x followed by n → x, and joint limits where T,n → x simultaneously; and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors when there is no individual time series cointegration and when there is heterogeneous cointegration. These relations are parameterized in terms of the matrix regression coefficient of the long-run average covariance matrix. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied. The limit theory enables us to test hypotheses about the long run average parameters both within and between subgroups of the full population.

Original language | English |
---|---|

Pages (from-to) | 1057-1111 |

Number of pages | 55 |

Journal | Econometrica |

Volume | 67 |

Issue number | 5 |

DOIs | |

Publication status | Published - 1999 Jan 1 |

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### All Science Journal Classification (ASJC) codes

- Economics and Econometrics

### Cite this

*Econometrica*,

*67*(5), 1057-1111. https://doi.org/10.1111/1468-0262.00070

}

*Econometrica*, vol. 67, no. 5, pp. 1057-1111. https://doi.org/10.1111/1468-0262.00070

**Linear regression limit theory for nonstationary panel data.** / Phillips, Peter C.B.; Moon, Hyungsik Roger.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Linear regression limit theory for nonstationary panel data

AU - Phillips, Peter C.B.

AU - Moon, Hyungsik Roger

PY - 1999/1/1

Y1 - 1999/1/1

N2 - This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section (n) and time series (T) observations. The limit theory allows for both sequential limits, wherein T → x followed by n → x, and joint limits where T,n → x simultaneously; and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors when there is no individual time series cointegration and when there is heterogeneous cointegration. These relations are parameterized in terms of the matrix regression coefficient of the long-run average covariance matrix. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied. The limit theory enables us to test hypotheses about the long run average parameters both within and between subgroups of the full population.

AB - This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section (n) and time series (T) observations. The limit theory allows for both sequential limits, wherein T → x followed by n → x, and joint limits where T,n → x simultaneously; and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors when there is no individual time series cointegration and when there is heterogeneous cointegration. These relations are parameterized in terms of the matrix regression coefficient of the long-run average covariance matrix. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied. The limit theory enables us to test hypotheses about the long run average parameters both within and between subgroups of the full population.

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U2 - 10.1111/1468-0262.00070

DO - 10.1111/1468-0262.00070

M3 - Article

VL - 67

SP - 1057

EP - 1111

JO - Econometrica

JF - Econometrica

SN - 0012-9682

IS - 5

ER -