The pricing mechanism in the gasoline market has often been the subject of public debate in Greece during the crisis years. Inefficient pricing could imply oligopolistic practices and losses to consumers’ welfare. A way to test for inefficient pricing, is by testing for asymmetries in the adjustment of domestic gasoline prices to world oil price changes. The present paper tests for asymmetric adjustment of gasoline prices to oil price variations in the Greek market and examines whether the structural reforms that took place in the post-2010 period had any impact on the functioning of the market. The analysis applies a consistent threshold cointegration technique and makes use of the most recent observations at the lowest frequency available. The results provide evidence in favour of symmetric behaviour, just for the recent period. This may reflect competitive behaviour by suppliers who had to interact in a new institutional framework following the reforms.

Using a multisectoral model and the latest data from the OECD Input-Output Tables (IOTs-2021 ed.), this article estimates labour and capital productivities of the 38 OECD member countries. As measures of the productivity of labour, we consider the inverse of the vertically integrated labour coefficients, while Perron–Frobenius theorems are employed so as to measure capital productivity. In this respect, the productive technologies and the intersectoral relationships of each economy are taken into account. We further investigate the relationship between productivity, economic efficiency and living standards. Findings indicate that the impact of capital productivity on higher living standards depends on the evolutionary and institutional background of the economy at hand.

Building on a proper selection of macroeconomic variables for constructing a Gross Domestic Product (GDP) forecasting multivariate model (Kazanas, 2017), this paper evaluates whether alternative Bayesian model specifications can provide greater forecasting accuracy compared to a standard Vector Error Correction model (VECM). To that end, two Bayesian Vector Autoregression models (BVARs) are estimated, a BVAR using Litterman’s prior (1979) and a BVAR with time-varying parameters (TVP-VAR). The BVAR is found to have statistically significant forecasting gains against the benchmark and the TVP-VAR. Furthermore, the BVAR requires only minimal modifications to account for the effect of pandemic observations on its coefficients, only for longer-term forecasts. JEL classification: C11, C51, C52, C53. Keywords: Bayesian VARs, Forecasting, GDP, VECM.