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on Transport Economics |
| By: | Philip Ulrich; Ulrike Lehr |
| Abstract: | The number of passenger cars with electric drives in Germany has nearly quadrupled in the last three years. Even though electric vehicles (EV) still hold less than 1% of the registrations, expectations are high for the future. E-mobility is expected to change the way cars are produced as well as households’ expenditures, as EV could hold 10 to 20% of new cars in 2030. The possible impacts on the economy are manifold; but thus far most studies use microeconomic methods to describe parts of the system changes or they analyze effects of investment in infrastructure. This ignores that manufacturing of cars with electric drives need different – and fewer - inputs than a car with a combustion engine. Therefore, long-term changes in the value chain are going to occur with impacts on the whole economy. In Germany E-mobility is pushed not only to gain or maintain the automotive industry’s shares in the global market but also to use potentials for a greener mobility. The aim is to stronger diversify the energy base in the transport sector and to develop potentials for the use of renewable energies. The objective of this contribution is to show the economic effects of both changing input-output relations and energy use by comparing two scenarios with different shares of electric or other alternative drives in passenger cars. Both indicators of resource use and employment are analyzed on an aggregate and a sector specific level. The analysis is based upon simulation results obtained with the macroeconometric model PANTA RHEI. PANTA RHEI has a macroeconometric simulation and forecasting model at its core, which consistently describes the annual inter-industry flows between the 59 sectors, their contributions to personal consumption, government, equipment investment, construction, inventory investment, exports as well as prices, wages, output, imports, employment, labor compensation, profits, taxes, etc. for each sector as well as for the total economy. The transportation module within the model describes traffic performances of all transport sectors and includes vehicle stocks with fuel or technology categories. Traffic and its modal split are extensively linked with private consumption, intermediate inputs and energy use. To analyze specific implications of drive technologies in cars the transportation module was extended and specific links to the energy use were established. Intermediate inputs between manufacturing industries were changed aligned to the technological transition. To examine the economic effects of a stronger market penetration of EV in Germany our analysis applies PANTA RHEI to two scenarios: a business as usual scenario and a scenario with an increased share of EV among new cars. Both scenarios are implemented in the macro-econometric model PANTA RHEI. The respective differences in economic indicators, such as employment, GDP etc. can then be attributed to more e-mobility in the scenario, since all other factors are held equal. Changes in volumes and prices are fully accounted for. The simulation model runs until 2030. In the scenario with an increased share of EV among new cars the government target of 6 Mio EV in 2030 is met, which is 14% of all vehicles. The long useful life period of cars leads to a rather long term transition. In the business as usual scenario 3.2 Mio personal vehicles with electric drives are operated at the end of the time horizon. The results show that the upcoming shifts in structures of manufacturing and consumption described in the model are not leading to strong macroeconomic effects. In the long term they are found to be negative, as increasing demand in electrical industry is overcompensated by decreasing demand in the automobile industry and related suppliers as well as (traditional) gas stations. Energy consumption in the EV-scenario is lower than in the reference, and so is the import of fuels. The way the well-established automotive value chain is adapting to the upcoming new technologies is very critical for the economic effects in Germany. The strong interlinkages within the automotive industries potentially imply self-energizing effects. Given the past structures these effects are rather negative as capacities for manufacturing electrical drives and batteries are not part of the – often metal-related – sectors. In the scenario analysis employment is higher in the electrical industry and in the energy sector. From 2020 on especially the lower employment in the automobile industry and gas stations lead to a slightly negative or rather balanced net employment effect. |
| Keywords: | Germany, Macroeconometric modeling, Sectoral issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9219&r=tre |
| By: | Zhu, Jiayi (Jason) |
| Abstract: | The New Zealand (NZ) Transport sector represents over 40% of the country’s greenhouse gas emissions from the energy sector. Electric Vehicles (EV) are fast emerging globally as a viable alternative to traditional fossil fuel burning cars. In hope of addressing the low EV adoption in NZ, the Ministry of Transport published a series of EV policies in May 2016. The literature review found a broad spectrum of EV adoption barriers from a global perspective covering technology, economic, social, environmental, and political factors. However, the analysis of barriers from a NZ perspective is overly simplistic and largely based on international findings with little empirical evidence specific to NZ. The most influential barriers specific to NZ are deemed as 1) range; 2) charging time; 3) purchase price; 4) charging facilities and 5) NZ car market. While there is literature which evaluates global policies and suggests effective policies for NZ, there is no current research that evaluates whether the latest NZ government policy is going to be effective in improving EV uptake in NZ. These papers tend to prescribe a solution of government policies without truly knowing whether their assumptions about EV adoption barriers apply to NZ. Using a mixed methodology, a questionnaire containing both quantitative and qualitative research questions was carried out. The findings of this paper show there are four major NZ specific barriers, namely 1) high purchase price; 2) unknown cost of ownership (i.e. service, maintenance and repair); 3) lack of charging facilities and 4) lack of EV knowledge. Other barriers highlighted by literature such as range and charging time are found to be less influential barriers. Overall, the sentiment for EV adoption is positive and the government policy is deemed to be reasonably effective as it either directly or indirectly addresses the above four barriers; however, certain policies such as ones addressing the cost of ownership can be improved. |
| Keywords: | Electric vehicles, Government policy, Adoption barriers, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:vuw:vuwmba:6190&r=tre |
| By: | Francisco Gallego; Juan-Pablo Montero; Hernán Barahona |
| Abstract: | Driving restrictions —limits on car use based on the last digit of a car’s license plate— are increasingly popular forms of pollution and congestion control, notwithstanding the literature has shown they typically result in more pollution by moving the fleet composition toward higher-emitting vehicles. We study a design feature present in some restriction programs but much overlooked in the literature: that cleaner cars be exempted from the restriction. Based on evidence from Santiago- Chile’s 1992 program, we find this exemption feature to have a large impact on fleet composition toward cleaner vehicles. We also develop and calibrate for Santiago a vertical-differentiation model of the car market to show that driving restrictions that make optimal use of these exemptions can be way more effective in the fight against local air pollution than alternative instruments such as scrappage subsidies and gasoline taxes. |
| JEL: | J14 O12 L26 M53 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ioe:doctra:469&r=tre |
| By: | Moisés Obaco (AQR Research Group-IREA. University of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain.); Vicente Royuela (AQR Research Group-IREA. University of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain); Xavier Vítores (Independent Statistical Researcher.) |
| Abstract: | Identifying integrated urban areas is an important issue for urban analysis and policy evaluation. In this paper, we extend the OECD’s methodology to identify Functional Urban Areas to countries where there is not commuting data. We do so substituting such socioeconomic flows by available information on road structure, which allow us to work with accessibility based on travel time. The main advantage of our procedure is its applicability to most countries in the world, as it only uses GIS data. In this paper we apply the procedure two border countries: Colombia, which has a recent census with commuting data, to calibrate our approach, and Ecuador, where there is not commuting census. We perform several sensitivity analysis and robustness checks to Ecuador with alternative sources of socioeconomic flows. |
| Keywords: | Functional Urban Areas. GIS data. Ecuador. Colombia. Travel time. JEL classification: R12, R14, R52. |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:201705&r=tre |
| By: | Christine Fauvelle-Aymar; Abel François |
| Abstract: | Few studies have tried to assess the empirical impact of transport cost on electoral turnout. Unfortunately, these researches suffer from different limits, especially limites related to the endogeneity of the voting station localization. Our study, based on French data, overcomes the main usual empirical difficulties. In particular, the French case provides a very valuable opportunity for testing the impact of transport cost on individual decision of turnout, because voters can be registered in another municipality than their residential municipality. As such, some of them have to travel important distance in order to cast their ballot. And this distance is totally exogenous to the electoral manipulation of places of voting location potentially made by local administration. So, we show that distance, and in fine cost of voting, have a highly significant impact on electoral turnout: at average distance (122 km) a 1% increase of distance induces a 0.05% decrease at the first round of 2012 presidential election and 0.04% at the second round. This result is robust to many tests: if we change the empirical method carried out or the election studied or if we control for the weight of the largest distance, the results remain the same. |
| Keywords: | Electoral turnout; cost of voting; transport cost; transport cost; electoral registration; voting paradox |
| JEL: | D72 |
| Date: | 2017–03–30 |
| URL: | http://d.repec.org/n?u=RePEc:sol:wpaper:2013/249250&r=tre |
| By: | Johanes Agbahey; Khalid Siddig; Harald Grethe |
| Abstract: | The Palestinian-Israeli conflict witnessed a new development in the mid-90s with the introduction of the closure policy. This policy consisting in roadblocks, and fixed and mobile checkpoints restricts the movement of goods and labor between the Palestinian territories and Israel, between the West Bank and the Gaza Strip, and inside the West Bank. As a result of this policy the economic space of the West Bank is divided into small pieces and trade with the rest of the world is distorted. The impact of the closure policy on the West Bank's economy is largely understudied. Taking advantage of this unique context, this study addresses the economy-wide effects of removing the closures. The study uses a SAM developed for the West Bank for the year 2011 with explicit representation of trade and transport margins. A variant of the STAGE suite of CGE models is used and extended to conform the unique feature of the West Bank economy. In this paper the removal of the closures is simulated through the reduction of the trade and transport margins by 30%, and the increase in efficiency in the transportation sector by 30%. The results suggest that removing the closure policy will induce a substantial growth of the West Bank's economy by 2 to 7% and will have distributional effects among the household groups Model and data The model used in this study belongs to the STAGE suite of CGE models. STAGE-2 uses a combination of linear and non-linear relationships governing the behavior of the model’s agents (Mc-Donald and Thierfelder, 2013). The model explicitly accounts for transport and trade margins and allows to capture the transactions costs associated with the closure regime that is investigated in this study. The model is calibrated to a West Bank SAM for 2011 (Agbahey et al., forthcoming). The full SAM comprises 325 accounts, of which 83 are commodities and 49 are activities. This detailed disaggregation allows assessing the impact of the closure regime on trade for specific commodity groups and the multiplier effects on the production sectors. The SAM also includes three margin accounts, namely wholesale trade, retail trade and transport margins. The depiction of the margins in the SAM is essential to study the effects of the closure regime as the restrictions basically increase the transaction costs. The SAM encompasses 59 production factor accounts and 111 household groups, allowing the assessment of the multiplier effects on factor markets and households’ welfare. Finally, the SAM singles out Israel from the rest of the world allowing to capture explicitly the transactions between Israel and the West Bank. Simulations The closure regime has two major effects on trade in the West Bank. First, it raises transaction costs. Passage at checkpoints and uncertainty of closures generate delays and add to the costs of doing business. The second major impact is on productivity in the transportation sector. The back-to-back system in place requires trucks upon arrival at a checkpoint to be unloaded and then reloaded on to another truck. This system causes additional labour and fuel costs and a decline in the factor productivity in the transportation sector. Three simulations are run in this study. The first simulates a reduction in the transaction costs associated with the closures. Akkaya et al. (2008) estimated the closure-induced increase in transaction costs at about 33%. In this first simulation, a pre-closure situation is reproduced by removing 33% of the transport and trade margins. In the second simulation factor productivity in the transportation sector is increased. In the absence of a documented estimation of the decline in productivity in the transportation sector, a 33% increase is assumed. Finally, the third simulation combines the first two. Sensitivity analysis is conducted to assess the extent to which the results are robust to differences in the magnitude of the imposed shock. Reduced transaction costs and increased productivity in the transportation sector would potentially have strong effects on the West Bank economy. Total domestic production is expected to increase, as the economy benefits from better access to import markets for intermediate inputs and higher export revenues. The effects between sectors, however, may differ strongly and some sectors may suffer from stronger import competition and changes in factor prices. Higher production would on average have positive multiplier effects on labour income and ultimately on household income. Effects on different household groups will differ according to their composition of income as well as consumption expenditure. However, for the economy as a whole, welfare gains are expected to largely offset losses. |
| Keywords: | West Bank (Palestine), General equilibrium modeling, Impact and scenario analysis |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9197&r=tre |
| By: | Laha, A. K.; Putatunda, Sayan |
| Abstract: | The analysis of data streams offers a great opportunity for development of new methodologies and applications in the area of Intelligent Transportation Systems. In this paper, we propose a new incremental learning approach for the travel time prediction problem for taxi GPS data streams in different scenarios and compare the same with four other existing methods. An extensive performance evaluation using four real life datasets indicate that when the drop-off location is known and the training data sizes are small to moderate the Support Vector Regression method is the best choice considering both prediction accuracy and total computation time. However when the training data size becomes large the Randomized K-Nearest Neighbor Regression with Spherical Distance becomes the method of choice. Even when the drop-off location is unknown then the Support Vector Regression method is the best choice when the training data size is small to moderate while for large training data size the Linear Regression method is a good choice. Finally, when continuous prediction of remaining travel time and continuous updating of total travel time along the trajectory of a trip are considered we find that the Support Vector Regression method has the best predictive accuracy. We also propose a new hybrid method which improves the prediction accuracy of the SVR method in the later part of a trip. |
| URL: | http://d.repec.org/n?u=RePEc:iim:iimawp:14564&r=tre |
| By: | Ann Hartell |
| Abstract: | Transportation planning in the United States is moving to widespread use of performance-based planning methods as new federal requirements for Metropolitan Planning Organizations (MPOs) are implemented. In addition to requirements for measures of safety and infrastructure, many MPOs are adopting performance measures for other issues. This study explores current planning practice in using a performance-based approach to tackle a complex planning issue: location affordability, defined as the combined household cost burdens of housing and transportation. A review of long-range transportation plans at 20 large MPOs provides information on how location affordability is represented in regional transportation plans, how it is defined and measured, and how it is integrated into the planning process. Using Christensen’s (1985) matrix of planning and policy problems as a theoretical framework, appropriate application of performance measures in connection with location affordability is identified. For challenging planning issues where solutions are uncertain or infeasible, performance measures are more appropriate if used in project or program evaluation, supporting a search for more effective solutions rather than holding MPOs accountable for outcomes. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwsre:sre-disc-2017_03&r=tre |
| By: | Pereira, Alfredo; Pereira, Rui |
| Abstract: | Using a newly-developed data set, we analyze the effects of infrastructure investment on economic performance in Portugal. A vector-autoregressive approach estimates the elasticity and marginal products of twelve types of infrastructure investment on private investment, employment and output. We find that the largest long-term accumulated effects come from investments in railroads, ports, airports, health, education, and telecommunications. For these infrastructures, the output multipliers suggest that these investments pay for themselves through additional tax revenues. For investments in ports, airports and education infrastructures, the bulk of the effects are short-term demand-side effects, while for railroads, health, and telecommunications, the impact is mostly of a long term and supply side nature. Finally, investments in health and airports exhibit decreasing marginal returns, with railroads, ports, and telecommunications being relatively stable. In terms of the other infrastructure assets, the economic effects of investments in municipal roads, electricity and gas, and refineries are insignificant, while investments in national roads, highways, and waste and waste water have positive economic effects, but too small to improve the public budget. Clearly, from a policy perspective, not all infrastructure investments in Portugal are created equal. |
| Keywords: | Infrastructure Investment, Multipliers, Budgetary Effects, VAR, Portugal. |
| JEL: | C32 E22 E62 H54 H60 O47 |
| Date: | 2017–03–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:77369&r=tre |
| By: | Xieshu WANG (Centre d'Economie de l'Université de Paris Nord (CEPN)); Joel RUET (Centre d'Economie de l'Université de Paris Nord (CEPN)); Xavier Richer (University Sorbonne Nouvelle) |
| Abstract: | The context of EU-China relations has dramatically changed over the past five years. China’s interest in Europe has expanded geographically and substantially. At the broader diplomatic and strategic level, the OBOR initiative has come to symbolize China’s growing significance in international affairs, reshaping regional dynamics. The European Commission and the Chinese government have agreed to enhance synergies in connectivity platforms. However, new investment trends and trade relations with China are highly differentiated across Europe and across sectors. The lack of a clearly defined OBOR plan in most European countries is weakening their bargaining power. In the meantime, China is following its flexible foreign policy approach when dealing with the EU. So far, the OBOR projects in Europe are mainly focusing on transport and infrastructure in Central, Eastern and Southern Europe. We are witnessing the reconfiguration of international institutions and the emergence of a more multi-polar global order. |
| Keywords: | One Belt One Road, connectivity, infrastructure, investment, governance |
| JEL: | F02 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:upn:wpaper:2017-04&r=tre |
| By: | Fujita, Yasuo |
| Abstract: | The concept of “Inclusive growth,” which has increasingly been used in the international arena, is concerned with both the pace and pattern of growth (i.e., the income growth of both poor and non-poor, non-income poverty and inequality). Developing countries and donors have often considered rural roads to have a positive impact on the growth of the rural economy and poverty reduction, through the promotion of better connectivity. This paper analyzes the impact of a rural road improvement project on inclusive growth in Bangladesh using a difference-in-difference method based on panel data from a large household survey. The results show that the project did contribute to the growth of the average income in the project area, and therefore to the inclusive growth at the national level. However this was mainly because of the income growth of households other than the poorest. In particular, the poor households with inferior initial resource endowments in landholding and househol d occupation did not benefit from the project. Thus, rural road projects are not necessarily inclusive at household level, though project specific factors should carefully be considered. A policy implication is that a rural road project in a poor rural area does not always benefit the poorest; hence complimentary interventions for these poorest households are needed. |
| Keywords: | inclusive growth,impact analysis,rural infrastructure,Bangladesh |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:jic:wpaper:138&r=tre |
| By: | Laha, A. K.; Putatunda, Sayan |
| Abstract: | The prediction of the destination location at the time of pickup is an important problem with potential for substantial impact on the efficiency of a GPS enabled taxi service. While this problem has been explored earlier in the batch data set-up, we propose in this paper new solutions in the streaming data set-up. We examine four incremental learning methods using a Damped window model namely, Multivariate multiple regression, spherical-spherical regression, Randomized spherical K-NN regression and an Ensemble of these methods for their effectiveness in solving the destination prediction problem. The performance of these methods on several large datasets are evaluated using suitably chosen metrics and they were also compared with some other existing methods. The Multivariate multiple regression method and the Ensemble of the three methods are found to be the two best performers. The next pickup location problem is also considered and the aforementioned methods are examined for their suitability using real world datasets. As in the case of destination prediction problem, here also we find that the Multivariate multiple regression method and the Ensemble of the three methods gives better performance than the rest. |
| URL: | http://d.repec.org/n?u=RePEc:iim:iimawp:14563&r=tre |