sk sk

Vávra Marián

Space for a photography of the author

Senior Researcher

Fields of interest:
  • econometrics
  • bootstrap methods
  • nonlinear models

2019

VÁVRA, Marián. 2024. A Growth-at-Risk Model in Slovakia. Working Paper NBS 7/2024. 22 pages.

2019

VÁVRA, Marián. 2019. On statistical measures of underlying inflation. Discussion Note NBS 65.

2018

VÁVRA, Marián. 2018. Putting new fan-charts into use. Discussion Note NBS 57.

2015

VÁVRA, Marián. 2015. On a Bootstrap: Test for Forecast Evaluations. Working Paper NBS 5/2015. 23 pages.

2015

HUČEK, Juraj – KARSAY, Alexandr – VÁVRA, Marián. 2015. Short-term forecasting of Slovak GDP using monthly data. Occasional Paper NBS 1/2015. 25 pages.

2021

PSARADAKIS, Zacharias – VÁVRA, Marián. 2021. Using Triples to Assess Symmetry Under Weak Dependence. In Journal of Business and Economic Statistics.

2020

VÁVRA, Marián. 2020. Assessing distributional properties of forecast errors for fan-chart modelling. In Empirical Economics, 2020, vol. 59.

2020

PSARADAKIS, Zacharias – VÁVRA, Marián. 2020. Normality tests for dependent data. In Communications in Statistics – Simulation and Computation, 2020, vol. 49.

2019

PSARADAKIS, Zacharias – VÁVRA, Marián. 2019. Bootstrap-assisted tests of symmetry for dependent data. In Journal of Statistical Computation and Simulation, 2019, vol. 89.

2019

PSARADAKIS, Zacharias – VÁVRA, Marián. 2019. Generalized portmanteau tests for linearity of stationary time series. In Econometric Reviews, 2019, vol. 38.

2017

PSARADAKIS, Zacharias – VÁVRA, Marián. 2017. A distance test of normality for a wide class of stationary processes. In Econometrics and Statistics, 2017, vol. 2.

2015

PSARADAKIS, Zacharias – VÁVRA, Marián. 2015. A quantile-based test for symmetry of weakly dependent processes. In Journal of Time Series Analysis, 2015, vol. 36.

2014

PSARADAKIS, Zacharias – VÁVRA, Marián. 2014. On testing for nonlinearity in multivariate time series. In Economics Letters, 2014, vol. 125.

2014

VÁVRA, Marián. 2014. Empirical evidence of joint nonlinearity in EA and US economic variables using two modified multivariate nonlinearity tests. In Applied Economics Letters, 2014, vol. 14.

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