On the robustness of the pooled CCE estimator

Juodis, Artūras; Karabiyik, Hande; Westerlund, Joakim

doi:10.1016/j.jeconom.2020.06.002

Cited by 39 publications

(27 citation statements)

References 31 publications

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“…and y i is defined in Equation (2). As it is shown in Everaert and De Groote (2016) and Juodis, Karabıyık, and Westerlund (2020), the CCE-style factor proxies, F e = (y, y −1 ), which arise in our context by setting V i = (y i , y i,−1 ) and w i = 1, satisfy Assumption 3.1 provided that E F [λ i ] = 0. In this setup, none of the two factor proxies in F e alone is able to estimate f consistently; instead only a linear combination of both columns can be estimated consistently.…”

Section: Methods Ii: Multiple Variables Single Weightmentioning

confidence: 87%

A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors

Juodis

Sarafidis

2020

Journal of Business & Economic Statistics

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A novel method-of-moments approach is proposed for the estimation of factor-augmented panel data models with endogenous regressors when T is fixed. The underlying methodology involves approximating the unobserved common factors using observed factor proxies. The resulting moment conditions are linear in the parameters. The proposed approach addresses several issues which arise with existing nonlinear estimators that are available in fixed T panels, such as local minima-related problems, a sensitivity to particular normalization schemes, and a potential lack of global identification. We apply our approach to a large panel of households and estimate the price elasticity of urban water demand. A simulation study confirms that our approach performs well in finite samples.

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Section: Methods Ii: Multiple Variables Single Weightmentioning

confidence: 87%

A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors

Juodis

Sarafidis

2020

Journal of Business & Economic Statistics

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“…Moreover, any dependence between ε i,t and e i,t is assumed away in order to allow for a tractable proof of the main theoretical result in this article. Lastly, the fact that we assume rk [μ λ , μ Λ ] = r = m+1 to hold suggests that we consider an ideal setup where none of the rank condition-related problems documented in Karabıyık, Reese, and Westerlund (2017), or Juodis, Karabıyık, and Westerlund (2021) apply.…”

Section: Multifactor Error Structurementioning

confidence: 99%

“…In analogy with the previous sections, we assume that β is known. Thus, we disregard the estimation error β CCE −β, which is generally of order O P ((NT) −1/2 )+O P (N −1 ), see, for example, Pesaran (2006) and Juodis, Karabıyık, and Westerlund (2021). We begin our asymptotic analysis, by noting that in the model with assumed (known) homogeneous σ the result follows directly as in the model with time effects only.…”

Section: Multifactor Error Structurementioning

confidence: 99%

“…However, this result is of limited empirical importance as in most cases researchers include all available cross-section averages. While this practice ensures that the estimator is invariant to β, inclusion of too many cross-section averages can potentially have detrimental effects on the asymptotic properties of the estimator, see the corresponding discussion in Juodis, Karabıyık, and Westerlund (2021) and Juodis (2020).…”

Section: Multifactor Error Structurementioning

confidence: 99%

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The Incidental Parameters Problem in Testing for Remaining Cross-Section Correlation

Juodis

Reese

2021

Journal of Business & Economic Statistics

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115

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In this article, we consider the properties of the Pesaran CD test for cross-section correlation when applied to residuals obtained from panel data models with many estimated parameters. We show that the presence of period-specific parameters leads the CD test statistic to diverge as the time dimension of the sample grows. This result holds even if cross-section dependence is correctly accounted for and hence constitutes an example of the incidental parameters problem. The relevance of this problem is investigated for both the classical two-way fixed-effects estimator and the Common Correlated Effects estimator of Pesaran. We suggest a weighted CD test statistic which re-establishes standard normal inference under the null hypothesis. Given the widespread use of the CD test statistic to test for remaining cross-section correlation, our results have far reaching implications for empirical researchers.

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“…Note that the number of effective factors argument holds here. If f y t = f x t , then the rank condition changes to rank (f Juodis et al 2018). Pesaran (2006) shows that, under certain conditions, β CCE,i , β CCEP and β CCEMG are consistent and asymptotically normally distributed as N , T → ∞.…”

Section: Large Heterogeneous Static Stationary Panels With a Multifacmentioning

confidence: 99%

Econometric Analysis of Panel Data Models with Multifactor Error Structures

2019

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Economic panel data often exhibit cross-sectional dependence, even after conditioning on appropriate explanatory variables. Two approaches to modeling cross-sectional dependence in economic panel data are often used: the spatial dependence approach, which explains cross-sectional dependence in terms of distance among units, and the residual multifactor approach, which explains cross-sectional dependence by common factors that affect individuals to a different extent. This article reviews the theory on estimation and statistical inference for stationary and nonstationary panel data with cross-sectional dependence, particularly for models with a multifactor error structure. Tests and diagnostics for testing for unit roots, slope homogeneity, cointegration, and the number of factors are provided. We discuss issues such as estimating common factors, dealing with parameter plethora in practice, testing for structural stability and nonlinearity, and dealing with model and parameter uncertainty. Finally, we address issues related to the use of these economic panel models.

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On the robustness of the pooled CCE estimator

Cited by 39 publications

References 31 publications

A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors

A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors

The Incidental Parameters Problem in Testing for Remaining Cross-Section Correlation

Econometric Analysis of Panel Data Models with Multifactor Error Structures

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