Panels with non-stationary multifactor error structures

Abstract

a b s t r a c tThe presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently, work by Pesaran (2006) has suggested a method which makes use of crosssectional averages to provide valid inference in the case of stationary panel regressions with a multifactor error structure. This paper extends this work and examines the important case where the unobservable common factors follow unit root processes. The extension to I(1) processes is remarkable on two counts. First, it is of great interest to note that while intermediate results needed for deriving the asymptotic distribution of the panel estimators differ between the I(1) and I(0) cases, the final results are surprisingly similar. This is in direct contrast to the standard distributional results for I(1) processes that radically differ from those for I(0) processes. Second, it is worth noting the significant extra technical demands required to prove the new results. The theoretical findings are further supported for small samples via an extensive Monte Carlo study. In particular, the results of the Monte Carlo study suggest that the crosssectional-average-based method is robust to a wide variety of data generation processes and has lower biases than the alternative estimation methods considered in the paper.

Fiscal policy and TFP in the OECD: measuring direct and indirect effects

“…Kapetanios et al (2011) show that these asymptotic results continu to hold in non-stationary panels provided that the idiosyncratic error term ε it is stationary. We outline our approach for testing whether this assumption (of cointegration) is satisfied in Section 4.3 below.…”

“…More specifically, we use the Common Correlated Effects Pooled (CCEP) estimator of Pesaran (2006), which controls for unobserved common factors by adding cross-sectional averages of the data. As shown by Kapetanios et al (2011) this approach is also valid in a non-stationary panel context. A second contribution of this paper is that we allow and model time-variation in the access of countries to worldwide technology.…”

“…In line with Pesaran (2006) and Kapetanios et al (2011), we identify the unobserved common factors Ft from the cross-section dimension of the data. Taking cross-sectional averages of the model in equation (6) yields…”

The long-run determinants of fertility: one century of demographic change 1900–1999

“…(A.8) in the Appendix). Kapetanios et al (2011) have recently shown that the CCE estimator is consistent regardless of whether the common factors are stationary or nonstationary.…”

Remittance and domestic labor productivity: Evidence from remittance recipient countries

“…can be either stationary or nonstationary, which does not influence the validity of the estimation (Kapetanios, 2011). In addition, the cross-sectional specific errors are permissible to be serially correlated over time and weakly dependent across the countries (Cavalcanti et al 2011).…”