Time Series Theory and Methods

Question: Discuss about the Time Series for Theory and Methods. Answer: Introduction: Trade off is the concept, which depicts that loses of an aspect of something in return for gaining another aspect. As all the factors cannot be attained at a same time, one has to give a product or service in order to gain another product. Traffic congestion is a major problem in Australia. Therefore, working people suffers from increasing vehicle queue. It can be assumed that there may be short and long rout to reach a destination. Probability of traffic congestion is greater at the shorter route. Hence, in order to avoid the traffic congestion, people can take alternative routes, which takes longer time. Therefore, people needs to trade off between routes with and without congestion (Anderson 2014, p. 2764). Opportunity cost: Opportunity cost is the concepts used in economic analysis, which says that a person has to give one opportunity to avail another one. Development of proper infrastructure can reduce the road congestion. However, construction of road incurs huge cost. Road congestion has also costs in terms of reduction in working hour, lengthy travel time, efficiency loss in production (Tsekeris and Geroliminis 2013, p. 5). Therefore, government has either to build infrastructure or to deal with traffic congestion. Marginal decision making: As discussed by Mahmud, Gope and Chowdhury (2012, p. 112), marginal decision making is the process through which a person chooses the best alternative that gives maximum benefits. Marginal benefit is greater when opportunity cost is low. People choose different options such as alternative roads, trade off between private and public transport based on their cost benefit analysis. Explanation of the cartoon The cartoon shows that a person is sitting under the sun and reading newspaper. Moreover, he is an aged person. As per invisible hand theory of Adam Smith, price and quantity is determined in the market through bargain between seller and buyer. The objective of the person was to get rid off from the temperature. Everyone chooses their buying and selling decision based on marginal utility. Utility of the seller maximises by increasing revenues (Tirachini, Hensher and Rose 2014, p. 41). As seen from the picture that the person buys the umbrella from the seller instead of cold drinks. Both of them maximises their utility. The seller is willing to give umbrella as this decision has less opportunity cost as he has hat to be protected from sun. On the other hand, the person sitting on the bench is benefitted by receiving the umbrella. Therefore, both can maximise their utility from this transaction as demand and supply meet each other. Explicit and implicit opportunity costs to motorists of road usage As mentioned by Fosgerau and De Palma (2013, p. 110), implicit opportunity cost is the lost of opportunity in the use of own resources of a firm or individual. This cost is important while making decision about the alternative opportunity. Implicit costs are intangibles. On the other hand explicit cost is the accounting cost of losing an opportunity. Costs that can be computed in terms of cost of resources are explicit cost (Pierce and Shoup 2013, p. 77). There is an economic cost or opportunity cost of traveling on the road. People can devote that hours in any productive usage that generates income. People can trade off that time with consumption of leisure as leisure has also utility. Safety is another implicit cost associated with the road usage by motorists. Motorists take risk of property damage, injuries and risk of death due to crashes. People trade off these risks with the income earned. Explicit cost of motorists is user cost. Toll taxes and other legal costs, license fees are explicit cost. Traffic congestion on road reduces the speed of motor vehicle and causing air pollution. Moreover, fuel cost increases with the congestion. Cost of travelling delays are the un-priced monetary externalities caused by congestion. Road pricing in Melbourne according to the time based charge or the distance of travel is the explicit cost for the motorists. In the view of Miller (2016), every one in five cars in Melbourne causes unnecessary congestion on road as their travels are not related to work or study. Therefore, road pricing at peak hour can reduce traffic jam effectively. Three approaches to improve road congestion Three approaches are described here for the reduction of traffic congestion in cities. Transportation network has been suffered from traffic congestion due to absence of capacity, supply side constraint and lack of investment in infrastructure development (Bigazzi and Figliozzi 2013, p.19). Three approaches have been adopted in Chicago to reduce congestion on road. The first one is building additional capacities in the important areas of the city. he second one is better management of existing network through intelligence transport technologies, improved signal coordination, traffic control and congestion pricing. Increasing transit into the regional roadway network planning and programming is another approach of reducing traffic congestion in roads (Staley 2012). Trends of the time series From an analysis of Figure 1 we find that there is a steady increase in the total distance travelled (billion km) by a metropolitan vehicle from 1990 to 2030. We also find that there is a constant increase in the avoidable congestion cost ($b) during the same period. In addition, we also find that the air pollution by metropolitan vehicles due to the road travel initially increases from 1990 to 1999, post 1999 the air pollution steadily decreases. The time series takes into account the forecast for the years 2017 to 2030. Relationship between the time-series over the period The analysis of the time series shows that there is a positive relationship between the distance travelled by a metropolitan vehicle and avoidable congestion cost during the period 1990 to 2030 (including the forecasted period). From the analysis, we find that from the period 1990 to 1999 as the distance travelled by metropolitan vehicles increase the air pollution also positively increases. This can be attributed to older vehicles and their technology. From 1999 to the present 2017 and again for a forecast period of 2017 to 2030, the air pollution decreases as the distance (in billion km) travelled by metropolitan vehicles increases. This decrease in air pollution can be attributed to newer vehicles and may be due to better technology of the vehicles (Brockwell and Davis 2013, p. 304). Inefficiency of public road use during peak travel times In the absence of any road pricing, travel on highways are free. There flow of traffic increases in the cities even in the peak hours. People use private cars for personal recreation, which has negative externalities in term of pollution, congestion, loss of production. Bigazzi and Figliozzi (2013, p. 23) stated that roads are scare factor in the economy as land is naturally fixed. Sellers often increases price in order to meet the demand with the supply so that some consumers are excluded from the market. During peak hour, road congestion increases marginal social cost over the marginal social benefits. Opportunity of road congestion is higher. If government imposes equal tariff during high and low demand times, inefficiency is created in the market. Traffic volume will inefficiently low during low demand periods. People travelling during off peak period will be worse off and marginal social benefits will be reduced creating market failure (Pierce and Shoup 2013, p. 70). Moreover, congestion during peak period is less likely to reduce as there as people are equally worse off during both periods. They may continue to travel during peak periods. As figure 2 shows that the effect of road pricing is higher while it is implemented in an aggregate way. There is a negative relationship between the traffic volume and traffic pricing. With the increase in road price, traffic volume on road reduces. Pricing is effective when there is huge demand in the market as well as shortage. Demand for road is greater from the office goer and the students during the peak hours. Therefore, willingness to pay price is greater during this period. On the other hand, as the flow of traffic is less during off peak hours, charging pricing creates inefficiency. The marginal social cost is flat till a certain level as prices are relatively constant during the level of demand. During peak hours, free flow of traffic increases. As there is shortage of road supply or poor signalling system, congestion is created (Anderson 2014, p. 2788). Therefore, equal tariff for all the periods fails to reduce traffic volume during peak hours. Efficiency can be increased by equating marginal social benefits with marginal social costs. Price discrimination for peak period and off-peak period is effective decision. Higher price during congestion period efficiently reduces the magnitude of congestion (Fosgerau and De Palma 2013, p. 111). Toll price t* per unit increases user cost, equating to the marginal social cost. Therefore, traffic volume decreases by bringing efficiency in the economy. Producer surplus is the region below the price line and above the supply curve. Here marginal social cost curve is the supply curve of traffic. Consumer surplus is the region below the demand curve and the above the price line. The shaded region in figure 3 is the consumer surplus. P*CB is the producer surplus in the market. With the tariff t per unit, no deadweight loss is created in the market. Imposition of road pricing hikes the user cost up to the MSC and market demand meets the market supply. At the equilibrium level, where, P= MSC= user cost, no deadweight loss is created as utility is maximised at this point for the given infrastructure (Brockwell and Davis 2013, p. 250). Hence, inefficiency is removed that has been shown in the earlier diagram. References Anderson, M.L., 2014. Subways, strikes, and slowdowns: The impacts of public transit on traffic congestion.The American Economic Review,104(9), pp.2763-2796. Bigazzi, A.Y. and Figliozzi, M.A., 2013. Marginal costs of freeway traffic congestion with on-road pollution exposure externality.Transportation Research Part A: Policy and Practice,57, pp.12-24. Brockwell, P.J. and Davis, R.A., 2013.Time series: theory and methods. Springer Science Business Media. Fosgerau, M. and De Palma, A., 2013. The dynamics of urban traffic congestion and the price of parking.Journal of Public Economics,105, pp.106-115. Mahmud, K., Gope, K. and Chowdhury, S.M.R., 2012. Possible causes solutions of traffic jam and their impact on the economy of Dhaka City.Journal of Management and Sustainability,2(2), p.112. Miller, J., 2016. Melbourne needs a user-pays scheme to beat traffic congestion. Available from: https://www.theage.com.au/comment/melbourne-needs-a-userpays-scheme-to-beat-traffic-congestion-20161125-gsxkdf.html Pierce, G. and Shoup, D., 2013. Getting the prices right: an evaluation of pricing parking by demand in San Francisco.Journal of the American Planning Association,79(1), pp.67-81. Staley, R. S., 2012. Practical Strategies for Reducing Congestion and Increasing Mobility for Chicago. Available at: https://nacto.org/docs/usdg/practical_strategies_for_reducing_congestion_and_increasing_mobility_chicago_staley.pdf Tirachini, A., Hensher, D.A. and Rose, J.M., 2014. Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding.Transportation Research Part B: Methodological,61, pp.33-54. Tsekeris, T. and Geroliminis, N., 2013. City size, network structure and traffic congestion.Journal of Urban Economics,76, pp.1-14.