Applied Economics · 2019 · 11 citations · 25 references
Social SciencesEconomicsFinanceEconometricsFinancial EconomicsMacroeconomicsCross-sectional EconometricsMicroeconometricsPanel Data AnalysisPanel Data MethodsSpatial EconometricsVolatility ModelingDynamic Spatial Panel ModelsGmm EstimationGrowth RatesPanel Data EstimationPanel Regression ModelsPanel Time Series AnalysisSpatial Panel Data ModelsVolatility
The existing literature documents positive but potentially non-linear relationship between financial depth measured as private credit to GDP ratio and volatility of GDP. In this paper, we extend the analysis by considering also the role of financial depth dynamics. We use dynamic spatial panel models to address the issue of cross-sectional dependence of errors obtained from the standard dynamic panel models. We confirm the non-linear impact of the financial depth level but also find that higher growth rates of financial depth are significantly associated with higher volatility of output. The role of the latter factor is considerably more important in terms of explained variance compared to the impact of the private credit level. These results are robust to changes in the sample range, specification of the model, and measurement of the key variables. We also document considerable differences between the estimates obtained from the standard GMM and the spatial models.
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American Economic Review · 2013 · 15.2K citations
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Testing Weak Cross-Sectional Dependence in Large Panels
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