This paper gives an over view of the economic and social issues associated with reducing the congestion in Brisbane city. It describes the effects of road congestion on the economic efficient of the market equilibrium. It also explains both the negative and positive externalities involved in this congestion. The research paper also explains the policies to be used in overcoming this problem. It is basically discuses which policies are effective in reducing the congestion. That is to say, whether to charge a congestion tax, provide public transport or by investing in construction of more roads. And finally, it ends with a conclusion.
The BSB 113 consulting Agent should aim at analyzing the costs and economic benefits of the construction of flyovers and overpasses so that traffic jam is reduced in the city of Brisbane (Martin and Thornton, 2016). However, the Brisbane city council major problem is the congestion of traffic jam in the city. Traffic jam is one of the major issues responsible for delaying employees who travel to their work place which has affected the economy negatively. The road transport in Brisbane city has grown rapidly in the last years with an increase of 20.0% car usage in Urban centres (Martin and Thornton, 2016). For example, the total number of miles travelled by cars and motorcycles has increasingly been rising. The data by the Brisbane city council, 2010 shows a 56.0 % increase in the kilometres travelled in the last few years (Portland, 2016). Cases of air pollution and the related emissions from traffic have been reported to have increased from 10% in 2000 to 35% in 2010. Congestion of traffic conditions has reportedly been a problem in the city since 2000 and this is due to the road traffic growth. According to Portland (2016) there is projected increase for transport demand and congestion by the year of 2015. It is believed that traffic congestion contributes about 10.05% of the environmental impacts mostly in busy and big cities. These impacts are as a result of noise pollution created by cars and motorcycles (Martin and Thornton, 2016). Many scholars have explicitly argued that, there is an adverse direct effect by the congestion on the air quality or emissions from traffic in these cities (Martin and Thornton, 2016).
From the economic perspective, research indicates that most people are willing to pay a high tax fair and use trains instead of their cars. For example, most drivers are willing to pay at least $1.30 in order to save time during the jam. Economically, time wasted is never gained and similarly time is considered to be a scarce resource (Paramita etal.,2018). (Martin and Thornton, 2016) argues that, production reduces as these workers spend more time in congestion. He continues to explain the effect of time wasted during traffic jam in relation to economics. Increase in hours for work increases the production rate in the same direction. It means here time is a variable factor and production is a dependent factor which depends on time.
For example, from the equation that; Yt = Xt + P…………………….1, where Yt– production at time t, Xt- time variable and P is a constant. The above equation demonstrates the impact of time in production. It implies for any worker to increase production, time at spent at work should also be increased. Therefore, there is need to reduce traffic jam and increase which later increases production in the economy. With increase in production, demand for goods and services also increases. This implies that the economy is doing well in terms of production and growth. Eliasson (2012) study conducted in Australia, argues that due to an increase of traffic congestion, households’ average incomes have reduced from 30.0% to 26.77% of the GDP per capita (Martin and Thornton, 2016).
However, road congestion is associated with both social and economic issues that have greatly affected the people of Australia (Coglan and Compiler, 2016). From the economic point of view, road congestion imposes a lot of costs that are significant in nature onto the people in the society. It is contributed by the long travel times of the flow of traffic interruptions. Similarly, the economic and social costs involved in this perspective may be high for the individuals. For example, individuals adding in the extra time travels and use a vehicle in areas with little congestion (Portland 2016). It implies that people are paying much in transport than what they actually earn. While from the social perspective, road congestion costs individuals their money, time and Health wise not doing well. The research shows that, during the peak time, most drivers use almost 40 hours in the road congestion.
Eliasson (2012) argues that drivers from California city spend at most 105 hours in congestion. He stated that it more important to walk than being in jam for almost those hours burning fuel. It is reported that the rate at which cars in congestion burn fuel is high compared to the ones not in traffic jam. And it is estimated that fuel burns at a rate of 80% more than any car in free areas of no congestion (Brisbane City council, 2018). With this, there are high emissions of carbon dioxide released and air pollution in the environment. This has a disadvantage to human life as heart attack incidences increase, Asthma and strokes. All these incidences contribute to the poor health of the infants and even city dwellers (Productivity Commission, 2017).
Road congestion has got effects on the economic efficient of the market. For example, it creates shadow costs of extrapolation which are to be recovered hence inefficiencies in the market. These shadow costs are always volatile meaning they hard to be calculated. It implies that reducing road congestion is constrained by these costs which extrapolates the growth hence risks are much involved. Additionally, shadow cost brings about unconstrained demand growth that determines the growth in traffic volume needed to be reduced. Hence from the equation;Sct = sct-1 * VoTt/VoTt-1 *[1 + d], where Sct – shadow costs at time ‘’t’’, VoTt – value of time in time ‘’t’’, d- unconstrained demand forecast. The equation implies that, shadow cost grows for all the costs of reducing congestion during extrapolation periods.
More so, the relation of traffic congestion to the nation’s economy in difficult and complicated to the extent that many scholars have entirely not explained it well. Nevertheless, according to (Eliasson, 2012), argues that peoples are always late at work due to road congestion. He explains that employees are always stressed and tired before their work places. Similarly, most of the deliveries will not happen as expected which leaves individuals in a hating life style.
The analysis of road congestion effect on the economic efficient equilibrium of markets shows that there has a significant relation between road network and traffic congestion.
Manners (2014) argue that the analysis is through considering the road networks since it is a common resource property. Assuming drivers and other users of the road are same meaning face the same demand curve. Any additional of the driver has an average travel time and increases travel time for the other drivers. From the economics point of view, the additional driver imposes a negative externality onto other road users (Martin and Thornton, 2016). Which causes inefficiencies in the price market mechanism? The market output level is determined by the point where price equals the marginal cost (Portland, 2016).
The market inefficiencies caused by the road congestion is demonstrated in the figure 1.0 below which assumes the identical drivers whose use the same road network on the same day. In this case, the marginal cost is defined as (MPC) marginal private cost which represents costs paid per car-hour in using the road(Leslie et al., 2017). All the other users have same average social cost that is equal to the (MPC). Drivers travel freely at low-flows where MPC is kept constant.
Figure 1.0 shows market inefficiency of traffic congestion.
From the graph above, the introduction of the demand curve raises the price of the road usage from what was initially at P* to P0. It implies that the demand for extra road usage that is free from congestion is high as its price increases. Similarly, the traffic flows increase from Ft to F*. With this effect, the dead weight loss created will the area above the demand curve and between MSC and MPC curves ( Eliasson, 2012).
Different policies have been taken to reduce this congestion although many of them have not effectively worked as expected. For example, imposing the congestion charge onto drivers could reduce congestion. With policy, electronic detectors which are placed on the bridges as drivers pay for use of the road space can effectively reduce this congestion (Elizabeth Street, 2016). That is to say, payment for the access of the free road network. The figure 2.0 below demonstrates this effect on road user.
The figure above implies that the demand for road space increases as congestion increases which rotates the demand curve to the right.
Brisbane City council (2018) states that the construction of roads through building many subways can also reduce the congestion. It creates many options for road users to choose what to use in case they suspect congestion. The figure 2.1 below explain the scenario of public road.
The graph shows the relationship of public roads with congestion. However, this encourages more drivers which in turn increases the demand for road space. With this cause, the demand curve rotates outwards and there is congestion still. Additionally, building costs increase which creates the opportunity cost (Department of Infrastructure and Regional Development, 2015).
Finally, the use of public road reduces the demand for other private roads which in turn reduces the usage of cars. T
The figure 2.2 below shows the relationship.
In summary, use of a congestion charge has a direct effect onto the users of road. Individuals are required to pay an extra charge for the use of free roads which might be a problem to low income earners(Cramtom, P. Geddes, R.R., and Ockenfel, 2018). Which implies that economically it will affect the individual’s income. While on the other hand, the government is able to collect more revenues which can redirected to other uses. Similarly, use of public roads seem to be a perfect policy in reducing congestion since there are no costs involved (Cramtom, P. Geddes, R.R., and Ockenfel, 2018). Road users are free to use these roads which in turn reduces traffic jam and productivity increases as workers reach at their work on time. Finally, building more roads would cost the council more extra money which may not be enough. However, congestion will be reduced at the same time economy is boosted (Coglan and Compiler, 2016).
Conclusion
This paper explained different scenarios of traffic congestion in cities, however, many scholars used a different approach in explaining this phenomenon. According to the research, congestion can be a good indicator or bad factor depending on the way it happens and in different countries Therefore, it should be noted that congestion is not totally a bad indicator. This is because in some countries it signifies growth of individuals incomes On the other hand, traffic congestion may not necessary indicate growth mostly in developing countries therefore, if identified it should be handled with immediate effect.
References
Brisbane City council. (2018). Reducing congestion. Retrieved from:https://www.brisbane.qld.gov.au/traffic-transport/reducing-congestion
Coglan, L., and Compiler, (2016). Essentials of Economics, (4th ed.). Australia: Pearson Australia, Chapter 11.
Cramtom, P. Geddes, R.R., and Ockenfel, A., (2018). Set road charges in real time ease traffic. Nature, 60, 23-25. Retrieved from:https://www.nature.com/articles/d41586-018-05836-0
Department of Infrastructure and Regional Development. (2015). Traffic and congestion cost trends for Australia capital cities. Retrieved from: https://bitre.gov.au/publications/2015/is_074.aspx
Elizabeth Street. (2016). Congestion and Reliability Review Full Report: Queens department of transport and main roads. Australian Government Department of Infrastructure. Tohmatsu LimitedPublisher.Retrievedfrom:https://www.transport.tas.gov.au/__data/assets/pdf_file/0013/152320/AP-R534-16_Congestion_and_Reliability_Review_Full_Report.pdf
Jonas, Eliasson. (2012). How to solve traffic jams. TEDx event organized by Volunteers: speakers are selectedindependentlyofTED.Retrievedfrom:https://www.ted.com/talks/jonas_eliasson_how_to_solve_traffic_jams
Leslie,A., Martin., and Sam. Thornton. (2017). The conversation: City wide trial shows how road use charges can reduce traffic jams. Academic rigor, journalistic flair. University of Melbourne. Retrieved from: https://theconversation.com/city-wide-trial-shows-how-road-use-charges-can-reduce-traffic-jams-86324
Manners, P.(2014). Congestion Pricing: Why and How. Retrieved from: https://www.thecie.com.au/wpcontent/uploads/2014/06/Congestion-pricing.pdf
Martin, L. A. and Thornton, S. (2016). City-wide trial shows how road use charges can reduce trafficjams. The Conversation. Retrieved from:https://theconversation.com/city-wide-trial-shows-howroad-use-charges-can-reduce-traffic-jams-86324
Paramita, P, Zheng Z, Haque MM, Washington S. and Hyland P. (2018). User satisfaction with train fares: A comparative analysis in five Australian cities. PLoS ONE 13(6): e0199449. Retrieved from: https://doi.org/10.1371/journal.pone.0199449
Productivity Commission. (2017). Transport. Shifting the Dial:5-year productivity review, (Ch 4, Section 4.5). Retrieved from:https://www.pc.gov.au/inquiries/completed/productivity-review/report/4-townscities
Portland. (2016). Economic Impacts of Congestion: On the Portland metro and Oregon economy. Business Alliance. Portland Business Alliance, Portland. Retrieved from: https://2014-cost=of=congestion-final_pdf
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