Quantile regression for dynamic panel data with fixed effects

Galvao, Antônio F.

doi:10.1016/j.jeconom.2011.02.016

Cited by 327 publications

(247 citation statements)

References 61 publications

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“…Adding those banks would require a wider range of models, perhaps by estimating different models for different bank types, which is beyond the scope of the paper. Second, the small time-series dimension of the recent BHCs likely requires an instrumental variable estimation approach to obtain consistent estimators for dynamic panel data models (Galvão Jr. 2011). For these reasons and to simplify the analysis we estimate both the FE-OLS and FE-QAR model specifications using a balanced panel with 15…”

Section: Data Sources and Estimation Resultsmentioning

confidence: 99%

Stress-Testing U.S. Bank Holding Companies: A Dynamic Panel Quantile Regression Approach

2013

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We estimate a fixed effects quantile autoregressive model with exogenous macroeconomic variables that is well-suited for capturing the nonlinear dynamics of bank losses and profitability during periods of macroeconomic stress. We use the density forecasts generated by the dynamic panel quantile regression model to simulate capital shortfalls during the last financial crisis for some of the largest U.S. bank holding companies. First, we report that several banks had a relatively high likelihood of violating the minimum capital requirements during the last financial crisis, suggesting that the quantile model would be able to pick up some fragility in the U.S. banking system at the onset of the last financial crisis. Second, the density forecasts of regulatory capital ratios generated using the quantile model have fat tails. This implies that the capital shortfalls estimated using the dynamic panel quantile regression model are higher than the capital shortfalls obtained using a linear dynamic panel data model.

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Section: Data Sources and Estimation Resultsmentioning

confidence: 99%

Stress-Testing U.S. Bank Holding Companies: A Dynamic Panel Quantile Regression Approach

2013

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“…In addition, most quantile panel data estimators include additive fixed effects which separate the disturbance term and assumes the parameters vary based only on the time-varying components of the disturbance term (Canay, 2011;Galvao, 2011;Harding and Lamarche, 2009;Koenker, 2004;Lamarche, 2010;Ponomareva, 2011;Rosen, 2012). With additive fixed effects, the model is ,…”

Section: Methodsmentioning

confidence: 99%

Quantile Parameter Heterogeneity in the Finance-Growth Relation: The Case of OECD Countries

Uyar¹,

Uyar²

2018

Prague Economic Papers

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This paper seeks to investigate the effect of financial development on growth in OECD countries during 1999-2014. The aim of the analysis is to study the dependence of growth on given financial development indicators along quantiles of the conditional growth distribution, taking into account the effect played by each country over time. For the purpose of the empirical analysis, it performed the instrumental variable quantile regression panel data (IV-QRPD) model suggested by Powell (2016). The findings of IV-QRPD model indicated that the effect of finance on growth is changing along quantiles of the conditional growth distribution. That is to say, we provide some evidence that high-growth OECD countries react to the changes in financial development less than low-growth countries.

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“…Quantile regression models allow the researcher to account for unobserved heterogeneity and heterogeneous covariates effects, while the availability of panel data potentially allows the researcher to include fixed effects to control for some unobserved covariates (Canay, 2011). Recently, some researchers associated these two methodologies and named it Panel Quantile Regression (Koenker, 2004;Geraci and Bottai, 2007;Abrevaya and Dahl, 2008;Galvao, 2008;Rosen, 2009;Lamarche, 2010;Guloglu, et al 2016). Koenker (2011) explains the panel quantile regression with fixed effect like these: suppose that the conditional quantile functions of the response of the j th observation on the i th individual y ij takes the form:…”

Section: Methodsmentioning

confidence: 99%

The Relationship Between Energy Consumption and Growth in Emerging Markets by Panel Quantile Regression: Evidence from VISTA Countries

Uyar¹,

Gökçe²

2017

PAU J Soc Sci Ins

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Energy consumption and economic growth relationship is an important topic for global economy. Most of researchers investigated this relationship with different methods on different macro-economic data. These methods are including not only time-series econometrics but also panel data analysis. Moreover, they analyzed different countries or country groups classified by OECD, World Bank or any other economic organizations. The aim of study is the relationship between energy consumption and economic growth with panel quantile regression method on VISTA countries (Vietnam, Indonesia, South Africa, Turkey and Argentina). Estimations are made annually for 1985 -2013 period. Dependent variable is GDP per capita growth and independent variables are logarithmic energy consumption indicators which are Oil Consumption, Coal Consumption, Hydroelectricity Consumption and Primary Energy Consumption. Results show that the effects of logarithmic energy consumption variables are changing on economic growth for different quantiles (τ = 0.25; 0.50; 0.75; 0.90). In conclusion, effect of oil consumption on economic growth is falling at high quantiles of GDP growth. In contrast, effect of hydroelectricity consumption and primary energy consumption on economic growth is rising at high quantiles. But, there is not a statistical significant effect of coal consumption on economic growth at any quantile.

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Quantile regression for dynamic panel data with fixed effects

Cited by 327 publications

References 61 publications

Stress-Testing U.S. Bank Holding Companies: A Dynamic Panel Quantile Regression Approach

Stress-Testing U.S. Bank Holding Companies: A Dynamic Panel Quantile Regression Approach

Quantile Parameter Heterogeneity in the Finance-Growth Relation: The Case of OECD Countries

The Relationship Between Energy Consumption and Growth in Emerging Markets by Panel Quantile Regression: Evidence from VISTA Countries

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