Bootstrap-based bias correction for dynamic panels

Everaert, Gerdie; Pozzi, Lorenzo

doi:10.1016/j.jedc.2006.04.006

Cited by 188 publications

(166 citation statements)

References 22 publications

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“…Our preferred methodology is BCFE estimation of equation (11). The standard errors used to calculate the t-statistics are simulated using the bootstrap algorithm as outlined in Everaert and Pozzi (2007). They are robust to both cross-sectional heteroscedasticity and cross-sectional error correlation.…”

Section: Estimation Resultsmentioning

confidence: 99%

“…Standard errors for the long-run effects are also simulated using the bootstrap algorithm. In line with Everaert and Pozzi (2007), we report the median and the 5 th and 95 th percentiles of the simulated distribution of the long-run effects rather than the mean and the t-statistic. The reason 7 The matlab code for the BCFE estimator is available upon request.…”

Section: Estimation Resultsmentioning

confidence: 99%

“…As an alternative, Everaert and Pozzi (2007) propose a bias-correction for the FE estimator using an iterative bootstrap algorithm. Like analytical corrections, this bootstrap correction reduces the bias of the FE estimator while maintaining its higher efficiency compared to GMM estimators.…”

Section: Choice Of Dynamic Panel Data Estimatormentioning

confidence: 99%

“…Without going in too much technical details (for this we refer to Everaert and Pozzi, 2007), the basic BCFE estimator searches over the parameter space and takes as bias-corrected estimates the set of parametersθ for which holds that when repeatedly generating artificial data from equation (11) setting θ =θ and next estimating this equation from these artificial data using FE yields on average (over repeated samples) the original biased FE estimatesθ. In practice, this search over the parameter space is computationally implemented through an iterative bootstrap algorithm, initiated by setting as a first guessθ 0 =θ, which is used to generate 1000 bootstrap data samples from equation (11) setting θ =θ 0 .…”

Section: Implementation Of the Bcfe Estimatormentioning

confidence: 99%

“…In contrast to the literature and in line with Hatton (1995) we include both lagged migration and migration stock which allows us to separately identify network effects and dynamics stemming from partial adjustment. Second, we estimate this dynamic panel data model using an extended version of the bias-corrected fixed effects (BCFE) estimator suggested by Everaert and Pozzi (2007). This estimator corrects for the dynamic panel data bias of the FE estimator using an iterative bootstrap algorithm.…”

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confidence: 99%

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Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework

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This paper investigates the determinants of bilateral immigrant flows to 19 OECD countries between 1998 and 2007 from both advanced and developing origin countries. We pay particular attention to dynamics by including both the lagged migrant flow and the migrant stock to capture partial adjustment and network effects. To correct for the dynamic panel data bias of the fixed effects estimator we use a bootstrap algorithm. Our results indicate that immigrants are primarily attracted by better income opportunities and higher growth rates abroad. Also short-run increases in the host country's employment rate positively affect migration from both advanced and developing countries.High public services, on the other hand, discourage migration from advanced countries but exert a pull on migration from developing sources, in line with the welfare state hypothesis. Finally, we find evidence for both partial adjustment and the presence of strong network effects. This confirms that both should be considered crucial elements of the migration model and that a correction for their joint inclusion is required.JEL Classification: F22, J61, C33

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Section: Estimation Resultsmentioning

confidence: 99%

Section: Estimation Resultsmentioning

confidence: 99%

Section: Choice Of Dynamic Panel Data Estimatormentioning

confidence: 99%

Section: Implementation Of the Bcfe Estimatormentioning

confidence: 99%

mentioning

confidence: 99%

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Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework

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Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect

2018

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Procedural failures of physicians or teams in interventional healthcare may positively or negatively predict subsequent patient outcomes. We identify this effect by applying (non)linear dynamic panel methods to data from the Belgian transcatheter aorta valve implantation registry containing information on the first 860 transcatheter aorta valve implantation procedures in Belgium. We find that a previous death of a patient positively and significantly predicts subsequent survival of the succeeding patient. We find that these learning from failure effects are not long-lived and that learning from failure is transmitted across adverse events.

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Central bank's money market operations and daily stock returns

Chundakkadan

Sasidharan

2019

Int. J Fin Econ

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The objective of this paper is to examine the relationship between the central bank's daily money market operations in the form of Term Repo and Term Reverse Repo operations on stock returns using daily data. Unlike earlier studies, we use two new monetary measures, namely, Repo Spread and Reverse Repo Spread. Controlling for firm‐specific factors and time dummies and addressing endogeneity issue, we show that the central bank's money market operations have a significant effect on daily returns. Further, we also observe that the inclusion of these monetary variables improves the prediction of the stock returns.

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Bootstrap-based bias correction for dynamic panels

Cited by 188 publications

References 22 publications

Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework

Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework

Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect

Central bank's money market operations and daily stock returns

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