Central European Journal of Economic Modelling and Econometrics

The monetary policy decision process is fundamental to achieving price stability and sustainable economic growth over the medium term. In recent years, given the multitude of unprecedented shocks that hit the global economy, many complex models still need to estimate accurately the magnitude of these shocks and their impact on economic activity. This paper proposes a small quarterly projection model to assess the economic outlook for a selected group of Central Eastern European countries with similar economic characteristics. Therefore, we present a comparable analysis between Hungary, Poland and Romania for 2005Q4-2023Q4. Our results suggest a relatively good performance regarding the assessment of the economic downturn from 2020 and a similar recovery pattern in Hungary and Poland, while the recovery in Romania was only partial. A real-time forecasting exercise ensures that the trajectory of macroeconomic indicators is close to the actual data, especially during regular times.

The measurement of the labor share is subject to a bias due to the income of self-employed (the mixed income). The aim of this study is to address this bias using a number of assumptions. We present our results for Poland, where both the self-employed and mixed income have high shares in employment and value added, respectively. In our calculations we account for the differences in socio-demographic characteristics of populations of both employees and self-employees and the differences in tax rates. The latter is our original contribution to the issue of measurement of the labor share. We show that in Poland, the correction of raw labor share with a fraction of mixed income increases labor share by an average of 8-13%, with the most reliable estimates being in a lower part of the range. Moreover, the treatment of the self-employed in agriculture is important. We also show that the corrections applied amplify the upward tendency in the labor share, observed since 2012. There are differences in sectoral labor shares - downward tendencies of labor shares dominate in manufacturing and other industries, whereas upward tendencies dominate in services. The shift-share decomposition revealed that the changing structure of the economy was roughly neutralized by the reallocation effect and the economy-wide movements are generated mostly by the within sector changes of labor shares.

In modern statistics and its applications, in particular in econometrics, random parameters or latent variables are widely used, and their estimation or prediction is of interest. Under some prior assumptions, Bayes formula can be used to obtain their posterior distribution. However, on the sampling-theory grounds, the unknown constants appearing in the prior distribution are estimated using the data being actually modelled. We call such approaches quasi-Bayesian; empirical Bayes procedures give important examples. In this paper we propose theoretical framework that enables Bayesian validation (or interpretation) of quasi-Bayesian inference techniques. Our framework amounts to establishing a formal Bayesian model that justifies the quasi-Bayesian "posterior" as a valid posterior distribution. From the Bayesian model validating the quasi-posterior, i.e. from the joint distribution of observations and other quantities, one can deduce the true sampling model, that is the conditional distribution of observations, and the true prior (or marginal) distribution of the remaining quantities. We illustrate our approach not only by simple examples, but also by the complicated Bayesian model validating one of the basic empirical Bayes estimators of the multivariate normal mean. This model is in fact a non-standard joint measure that separates two subsets of the Cartesian product of the observation space and the parameter space.