Case Study on the Relationship between Road Safety and Economy in Hungary

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Comparing the time series of the Hungarian GDP per capita to those of other EU Member States, it can be stated that the economic growth of Hungary has recently slowed down even in view of the neighbouring economies. This also supports the presumption that the crisis has had a more severe effect on Hungary than on the neighbouring countries.

These less favourable economic trends as compared to the neighbouring Member States lead us to believe that recession has exerted an influence above the average both on the Hungarian rate of motorization and on the road transport performance; thus also on accident risk (Hungarian Central Statistical Office, 2013).

Nevertheless, the relationship between GDP and the number of accidents is not determined by only one factor. For instance, it can be supposed that in countries with more developed economies higher resources can be allocated to police enforcement, with an obvious positive effect on reducing the number of accidents. Apart from this, countries with economies on a higher level of development may be supposed to possess safer road networks and, newer, more modern car fleets. These influence the number of accidents in a positive direction by way of decreasing the probability and severity of accidents. Contrary to the effect of GDP on road transport performance, these factors rather have a mid- and long term positive influence on the number of accidents.

Figure 2. Time series of total number of accidents and transport performance in Hungary. Source: Hungarian Roads Management Company, Hungarian Central Statistical Office

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The study aiming to compare the most significant transport safety factors dependent on economic development (Beenstock & Gafni, 2000), distinguished national and international trends. It analyses how international transport safety trends, like the improvement of vehicle safety, and local efforts, like increasing the presence of the police force, improving road traffic behaviour or road network safety influence the long term accident trends.

In Hungary, just as in other developing countries, while the vehicle fleet, of which average age can be regarded as even a presently growing one, will turn to be more modern, the effects coupled to these incoming vehicle technologies might bring about significant transport safety improvement.

Figure 3 also indicates that the average age of Hungarian vehicle fleet is growing. It means that individuals change their cars later, so cars are used further in time. Since vehicle fleet is still changing permanently, the inflow of developed vehicle safety technology is continuous however the ratio of new cars is decreasing compared to old cars. Therefore, by the withdrawal of older vehicles, the safety level of vehicle equipment will probably show an improving tendency. This in itself will mitigate the severity of accidents.

Due to the increase in the average age of the vehicle fleet, that is, the slowing pace of vehicle fleet modernisation, it may be presumed that the development of vehicle safety technology has only contributed in a small extent to the improvement of the accident severity in Hungary. Thus it may be assumed, that in Hungary it has not primarily been the development of vehicle technology which has brought about the decrease in accident risk and accident severity.

Figure 3. Time series of GDP and of the average age of the vehicle fleet in Hungary. Source: Hungarian Central Statistical Office

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Beenstock and Gafni suggested that vehicle safety parameters are directly determined by the earnings level of the vehicle owner, considering that the individuals disposing of higher earnings may presumably afford safer vehicles (Beenstock & Gafni, 2000). In connection with this, it needs to be emphasized that, anticipating an economic growth, the modernisation of the vehicle fleet may be expected, thus, the effects related to the rollout of up-to-date vehicle safety technologies incorporate a significant transport safety potential in Hungary (Beke et al., 2014).

Investigating long term traffic safety effects of GDP, Kopits and Cropperb analysed data from 88 countries. The aim of research was to describe the relationship between the increase in the per capita income and the decline of the road death rate experienced during economic growth. The authors explain the relationship between the per capita income growth and the decrease of fatality rate among others with the development of vehicle and infrastructure safety. In the research the authors have shown that traffic fatality risk (fatalities/population) has started to show a steadily decreasing tendency in the 88 countries investigated, when, in the course of economic growth, the per capita income has reached $8,600. (Kopits & Cropperb, 2005)

The per capita income has not reached $8,600 in Hungary yet. The average gross income was 1,234,646 HUF per capita in 2012, which is $5,487 at the average 2012 exchange rate. Taking into account that the authors have determined the $8,600 value at the 1985 price level, it is reasonable to consider the income level of 2012 at the value discounted to 1985. This correction may be executed using the real wage value index available from the website of the Hungarian Central Statistical Office. Thus, the average gross income per capita in Hungary becomes $6,250 at the price level of 1985.

Although the number of fatalities have started to decrease significantly after 2006, the discussion above indicate that the decline of the accident rate is in a larger extent due to the consequences of short term economic effects, and only in a smaller extent to the technological development resulting from continuous technological development.

Examining the Hungarian tendencies from an international perspective, it can be stated that the traffic mortality rate (fatalities/population) has slightly been above the EU (Papadimitriou et al., 2013.)

The number of fatalities per vehicle shows a much more unfavourable picture of Hungary, as this value takes into account the rate of motorization as well. This number in Hungary is more than double than that of the countries in the region with a higher rate of motorization (e.g. IT, AT, SI) (Papadimitriou et al., 2013.)

Are we to assess the traffic safety position of a certain country as based on the two indicators described above, we might reach ambiguous conclusions, as, for instance, Hungary is not badly ranked considering the fatalities per population rate. However, regarding traffic fatalities per vehicles, a much gloomier picture emerges.

This contradiction may be resolved by the methodology introduced by Trinca et al., adapted for Hungary by Dr Péter Holló (Holló et al., 2010) and presented in Figures 4 and 5. Using this method, and employing both indicators simultaneously, road transport safety may be characterized in a more sophisticated way, clustering the countries as based on their traffic safety morale and safety considerations.

Further on this complex approach has been validated and applied in many researches to compare and rank countries from a road safety point of view (Gitelman, 2012).

Assessing the road safety position of Hungary as based on the Trinca model indicates that the country is already at the stage of continuous development. This result shows Hungary in a better light than the estimates based on real wage per capita values, according to which Hungarian transport safety has not entered the phase of continuous development yet. On the other hand some important aspects are still not possible to be analysed in this model, since traffic performance is also an important explanatory factor of accidents, especially considering that the frequency and distance of vehicle usage is an important contributor to the increasing road safety risk.

However there are other approaches, like DEA - data envelopment analysis, which can make the road safety ranking process to be more nuanced.

Applying DEA model, it is possible to consider both efficiency change and technical change together as the total factor productivity change. Accordingly, the overall road safety progress in the 26 EU countries during the last decade are deduced, which is illustrated in the Figure 4 (Shen et al., 2013).

Figure 4. Time series of GDP and of the average age of the vehicle fleet in Hungary. Source: Hungarian Central Statistical Office

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