Cross-Sectional Dependence in Panel Data Analysis

Sarafidis, Vasileios; Wansbeek, Tom

doi:10.1080/07474938.2011.611458

Cited by 352 publications

(208 citation statements)

References 87 publications

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“…important characteristic in the analysis of macro and panel data models and can reflect global common shocks with heterogeneous impact across countries, such as the oil crises in the 1970s or the recent financial crisis and local spillover effects as a result of spatial or other forms of local dependencies (Pesaran and Tosetti, 2011;Sarafidis and Wansbeek, 2012). Allowing for cross-sectional correlation in the error terms we avoid severe size distortions in panel unit root testing and thus obtain more powerful results.…”

Section: Introductionmentioning

confidence: 99%

Unemployment by Gender: Evidence from EU Countries

Bakas

Papapetrou

2013

Int Adv Econ Res

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This paper applies panel unit-root tests that allow for structural breaks and cross-sectional dependence to examine the validity of hysteresis in gender unemployment rates and gender unemployment gap for a panel of 15 European countries. Addressing breaks, there is evidence to reject the null hypothesis of hysteresis for the unemployment rates and unemployment gap series. Allowing for both cross-sectional dependence and heterogeneous structural breaks this result is reverted and we fail to reject the null hypothesis of unit root.

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Section: Introductionmentioning

confidence: 99%

Unemployment by Gender: Evidence from EU Countries

Bakas

Papapetrou

2013

Int Adv Econ Res

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“…unemployment when both heterogeneity and interdependence among EU states are taken into account (albeit lower to the homogenous case). Furthermore, we observe that these heterogeneous estimates (Table 4) 12 Following the theoretical argument of Sarafidis and Wansbeek (2012) and analogously to the findings in Bakas et al (2016), we observe that neglecting to account for cross sectional dependence in the estimation will lead to an upward bias in the estimates. 13 Similarly, the elasticity of unemployment with respect to sigma (based on the CCEMG estimator) will be equal to 6.16% at the sample maximum value of the reallocation index ( = 0.07) (see Table 2).…”

Section: Resultsmentioning

confidence: 77%

On the significance of labour reallocation for European unemployment: Evidence from a panel of 15 countries

Bakas

Panagiotidis

Pelloni

2016

Journal of Empirical Finance

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We explore the macroeconomic effects of sectoral shifts for 15 European countries. An extensive panel is constructed that allows us the assessment of the impact of labor reallocation on unemployment in the European context. Indexes of labor market turbulence based on alternative sectoral disaggregation are constructed. The effect of labor reallocation on unemployment is found to be positive and significant in all different specifications. This remains robust when we take into account volatility measures in the model. JEL classification: E24, E32, J21, R23, C23Keywords: labor reallocation, sectoral shifts hypothesis, unemployment, EU * Acknowledgements: We would like to thank Richard Bailey and two anonymous referees for their constructive comments and helpful suggestions. We would also like to thank Karim Abadir and Paolo Giordani for their useful comments and suggestions on earlier versions of this work. All remaining errors are our own.Bakas:

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“…It is therefore inappropriate for settings with error cross-sectional dependence, as this can lead to biased coefficient estimates. Moreover, as Sarafidis and Wansbeek (2012) notes, error cross-sectional dependence can inflate test statistics for the over identifying restrictions tests and lead to erroneous rejections of the null. Therefore, although system-GMM is not entirely reliable in this setting, it should be viewed as an additional check on the benchmark specification.…”

Section: Benchmark Bank Profits Regressionsmentioning

confidence: 99%

Have Large Scale Asset Purchases Increased Bank Profits?

Montecino

Epstein

2014

SSRN Journal

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This paper empirically examines the effects of the Federal Reserve's Large Scale Asset Purchases (LSAP) on bank profits. We use a new dataset on individual LSAP transactions and bank holding company data from the Fed's FRY-9C regulatory reports to construct a large panel of banks for 2008Q1 to 2009Q4. Our results suggest that banks that sold Mortgage-backed Securities to the Fed ("treatment banks") experienced economically and statistically significant increases in profitability after controlling for common determinants of bank performance. Banks heavily "exposed" to MBS purchases should also experience increases in profitability through asset appreciation. Our results also provide evidence for this type of spillover effect and suggest that large banks may have been more affected. Although our results suggest that MBS purchases increased bank profits, we find only mixed evidence that these were associated with increased lending. Our findings are thus consistent with the hypothesis that the Federal Reserve undertook these policies, at least in part, to increase the profitability of their main constituency: the large banks.JEL classification: G21, G28, G32

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Cross-Sectional Dependence in Panel Data Analysis

Cited by 352 publications

References 87 publications

Unemployment by Gender: Evidence from EU Countries

Unemployment by Gender: Evidence from EU Countries

On the significance of labour reallocation for European unemployment: Evidence from a panel of 15 countries

Have Large Scale Asset Purchases Increased Bank Profits?

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