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Vávra Marián

Senior researcher
RePEc profile
Fields of interest: time series econometrics, bootstrap methods, nonlinear models.
years of publ. | NBS Publications |
---|---|
2019 | Marián Vávra, 2019. “On statistical measures of underlying inflation,” NBS Discussion Note, No. 65. |
2018 | Marián Vávra, 2018. “Putting new fan-charts into use,” NBS Discussion Note, No. 57. |
2015 | Marián Vávra, 2015. “On a bootstrap-based Diebold-Mariano test,” NBS Working Paper, No. 5. |
2015 | Juraj Huček, Alexandr Karsay, and Marián Vávra, 2015. “Short-term forecasting of Slovak GDP using monthly data,” NBS Occasional Paper, No. 1. |
years of publ. | Selected External Publications |
---|---|
2021 | Zacharias Psaradakis and Marián Vávra, 2021. “Using Triples to Assess Symmetry Under Weak Dependence,” Journal of Business and Economic Statistics. |
2020 | Marián Vávra, 2020. “Assessing distributional properties of forecast errors for fan-chart modelling,” Empirical Economics, 2020, Vol. 59. |
2020 | Zacharias Psaradakis and Marián Vávra, 2020. “Normality tests for dependent data,” Communications in Statistics – Simulation and Computation, Vol. 49. |
2019 | Zacharias Psaradakis and Marián Vávra, 2019. “Bootstrap-assisted tests of symmetry for dependent data,” Journal of Statistical Computation and Simulation, Vol. 89. |
2019 | Zacharias Psaradakis and Marián Vávra, 2019. “Generalized portmanteau tests for linearity of stationary time series,” Econometric Reviews, Vol. 38. |
2017 | Zacharias Psaradakis and Marián Vávra, 2017. “A distance test of normality for a wide class of stationary processes,” Econometrics and Statistics, Vol. 2. |
2015 | Zacharias Psaradakis and Marián Vávra, 2015. “A quantile-based test for symmetry of weakly dependent processes,” Journal of Time Series Analysis, Vol. 36. |
2014 | Zacharias Psaradakis and Marián Vávra, 2014. “On testing for nonlinearity in multivariate time series,” Economics Letters, Vol. 125. |
2014 | Marián Vávra, 2014. “Empirical evidence of joint nonlinearity in EA and US economic variables using two modified multivariate nonlinearity tests,” Applied Economics Letters, Vol. 14. |