We propose a method of constructing multisector-multiregion input-output tables, based on the standard multisector tables and the tools of spatial econometrics. Voivodship-level (NUTS-2) and subregion-level data (NUTS-3) on sectoral value added is used to fit a spatial model, based on a modification of the Durbin model. The structural coefficients are calibrated, based on I-O multipliers, while the spatial weight matrices are estimated as parsimoniously parametrised functions of physical distance and limited supply in certain regions. We incorporate additional restrictions to derive proportions in which every cross-sectoral flow should be interpolated into cross-regional flow matrix. All calculations are based on publicly available data. The method is illustrated with an example of regional economic impact assessment for a generic construction company located in Eastern Poland.
The model considered in the paper is defined as VAR with the prior distribution for parameters generated by the dynamic stochastic general equilibrium (DSGE) model. The degree of economic restrictions in the DSGE-VAR model is controlled by the weighting parameter. In the paper there is investigated the impact of the weighting parameter prior specifications for the posterior shape of impulse response functions (IRFs). In case of conditional models the paths of IRFs highly depend on the value of the weighting parameter that is set arbitrary. When considering full estimation with different prior types, means and gradual change in the dispersion the posterior time paths of IRFs are similar in models with high values of the marginal data density.
The aim of this paper was to estimate the gender wage gap in Poland and in the 16 NUTS2 Polish regions in 2010, and to verify the predictions of the spatial monopsony model for Poland with a newly created, harmonized database for wages of individuals in Poland. According to the model, the unexplained part of the gender wage gap, identified with wage discrimination, tend to be lower in regions with more competition between employers.
The results of the analyses performed in this paper show that in more urbanized regions the average wages are higher than in the rural ones. In each of the 16 NUTS2 Polish regions, women earn less than men. Raw differences in wages between men and women are largest in the most urbanized regions but a significant part of the differences in those regions can be explained by differences in workers’ characteristics, especially by different sectoral structure of employment. The part of the gender wage gap which remains unexplained, and in the literature is commonly attached to discrimination, is the highest in rural regions of Eastern Poland in line with the predictions of the spatial monopsony model.
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