Ułomności statystyki motoryzacji w Polsce i ich konsekwencje dla badań geograficznych = Shortcomings of Poland’s motorisation statistics, and their implications for geographical research

Abstract

Reports from the European Commission (e.g. European Commission, 2018) show a relatively high level of motorisation in Poland (leaving the country ranked 6th among EU Member States). The number of cars per 1000 inhabitants is higher here than in any other of the formerly-communist countries acceding to the EU in or after 2004. Unfortunately, however, this situation inter alia reflects twisted statistics on motorisation that do not therefore offer a full or proper reflection of the real situation on the Polish car market. This article has devoted itself to the analysis of shortcomings characterising three groups of motorisation statistics relating to: 1. the cars known as “dead souls” (end-of-life vehicles) – whose numbers are overstated (by perhaps 6 million cars – or 26% of the entire total), given the retention on the register of those that have not been on the road for a long time, 2. “cars with a grille” – part of a Poland-specific phenomenon that results in understatement of numbers of cars and overstatement of numbers of goods vehicles (to the tune of perhaps 750,000), given people’s efforts to ensure that personal cars are approved for registration as commercial vehicles, 3. company cars, given overstatement (equal to perhaps 1.5 million) of numbers of vehicles in cities due to the presence of leasing companies and large enterprises operating company cars. The spatial distribution across the country of cars in the above–mentioned groups is very uneven and does much to influence spatial patterns relating to Poland’s motorisation rate (s). Overall, motorisation is much overestimated in large cities (e.g. Warsaw, Poznań, Katowice and Wrocław), while being underestimated in rural areas (especially in SE Poland). A crucial achievement of our analysis involves correction of official European statistics in this regard. The discrepancies characterising the statistics have the clear spatial distribution presented in Fig. 6. In its last section, this article then attempts to determine the consequences of such twisting of the motorisation statistics where both geographical research and decision-making are concerned.

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