Macroeconomic volatility effect on labour market performance has been detected for OECD countries during the years of 1985-2011. Current research adds a number of improvements to the subject field. Labour market performance incorporates a large number of associative indicators rather than simple unemployment rate. Variety of performance indicators has been used in attempt to underpin the system mechanism. Advanced techniques are used for volatility estimation. Distinct volatility measures are used for exchange rate, inflation and interest rate series according to their stochastic properties. For long memory inflation series ARFIMA-GARCH models have been used, for interest rates that bare asymmetry due to Central Bank and market interventions QARCH, GJR-GARCH and PARCH models have been fitted. Exchange rate series have been modelled using ARIMA-GARCH and EGARCH. In estimation of volatility effect on labour market performance either random or fixed effects models have been used. Standard errors of the models have been tested and corrected for serial correlation, heteroskedasticity and cross-sectional dependence. For the robustness of the results panel time series methods have been used where possible due to its advantages for macroeconomics models (Eberhardt (2012)). Where use of these methods has been restricted by the nature of the models, Arellano-Bond (1991) and Bruno (2005) models have been fit. Hybrid (Allison (2009)) and Correlated Random effects models (Mundalak (1978)) have been used where categorical variables have been included in the regression.