|
on Transport Economics |
| By: | Gustav Fredriksson; Alexander Roth; Simone Tagliapietra; Reinhilde Veugelers |
| Abstract: | The automotive sector is currently at the centre of a global transformation, driven by four key trends - electrification, autonomous driving, sharing and connected cars. While each of these interconnected trends is already visible in daily life, their full deployment is not yet guaranteed, nor is the speed of take-up. This Policy Contribution investigates the position of the European automotive industry in a scenario in which electrification substantially progresses. The results are encouraging for Europe - EU companies entered the global electric vehicle race late, but on the basis of our analysis it is not yet too late for them to catch up and make the best of this change. European car manufacturers can rely on a large internal market, long experience in automotive manufacturing and a portfolio of research and development projects and patents that is diversified across various power-train technologies. But if Europe wants to succeed in the global electric vehicle race, its automotive industry will have to move into higher gear to meet the global – notably Chinese – competition. Nevertheless, industry needs the proper framework conditions as the basis for more ambitious investments in electrification – as examples such as Norway or China demonstrate. This Policy Contribution formulates a broad policy framework for deployment and production of electric vehicles in Europe, combining demand and supply-side instruments. Europe cannot follow China in the adoption of centrally-planned industrial policy measures. But it certainly can and should do more to stimulate the transformation of its automotive industry through more ambitious policies. On February 12, Bruegel is hosting an event on electric vehicles in European automotive industry, which will feature among others a presentation from the authors of this Policy Contribution. Click here to register. |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:bre:polcon:28892&r=all |
| By: | Asplund, Disa (CTS - Centre for Transport Studies Stockholm (KTH and VTI)) |
| Abstract: | The main aim of the study is to advice the Swedish national guidelines on cost-benefit analysis (CBA) of transport infrastructure investments, ASEK about the appropriate set of discount-rates (currently 3.5% for all investments). To this end, first a literature review with a theoretical focus along with some new perspectives are provided. Second the conclusions are applied to Swedish infrastructure transport CBA, using the current proposition of a new HSR line as a case. Based on empirical research concerning parameter values new discount rates are estimated, and sensitivity analysis performed. The best estimate of the social discount rate in the present study, for land transport infrastructure investment in Sweden, is about 5.1%. |
| Keywords: | Discount rate; Cost-benefit analysis; Social time preference; Social opportunity cost; Risk |
| JEL: | D61 G11 H43 H54 |
| Date: | 2018–12–14 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:ctswps:2018_023&r=all |
| By: | Tho V. Le; Junyi Zhang; Makoto Chikaraishi; Akimasa Fujiwara |
| Abstract: | To analyze the influence of introducing the High-Speed Railway (HSR) system on business and non-business travel behavior, this study develops an integrated inter-city travel demand model to represent trip generations, destination choice, and travel mode choice behavior. The accessibility calculated from the RP/SP (Revealed Preference/Stated Preference) combined nested logit model of destination and mode choices is used as an explanatory variable in the trip frequency models. One of the important findings is that additional travel would be induced by introducing HSR. Our simulation analyses also reveal that HSR and conventional airlines will be the main modes for middle distances and long distances, respectively. The development of zones may highly influence the destination choices for business purposes, while prices of HSR and Low-Cost Carriers affect choices for non-business purposes. Finally, the research reveals that people on non-business trips are more sensitive to changes in travel time, travel cost and regional attributes than people on business trips. |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1812.04184&r=all |
| By: | Carl Gaigné (UMR-1302, SMART-LERECO INRA, AGROCAMPUS OUEST, F-35000 Rennes, France); Vincent Hovelaque (Univ Rennes, CNRS, CREM UMR 6211, F-35000 Rennes, France); Youcef Méchouar (Univ Rennes, CNRS, CREM UMR 6211, F-35000 Rennes, France) |
| Abstract: | Recent studies on facility location under the carbon pricing scheme highlight that increas-ing the carbon price can ensure meaningful reductions in transport-related greenhouse gas emissions (GHGs). Indeed, when we assume the bill of materials (BOM) as a production technology (i.e. complementary of inputs), a higher carbon price does not change the supply planning because the input proportions are fixed, but it does increase the total transport cost, which pushes the firm to make its location choice more sustainable (lower level of emissions). However, when we account for possible substitution between input quantities, this may cease to hold. In this paper, we propose to revisit the Production-Location Problem (PLP) considering transport-related carbon emission mitigation due to carbon taxation and production technologies that allow complementarity or substitution among input quantities. We first show that cost-minimizing location may differ from carbon emission minimizing location, regardless of the production technology type. We also find that an increased car-bon tax may increase carbon emissions when we enable substitution across input quantities. Gradual changes in carbon tax affect the relative delivered prices of inputs (the per-unit procurement and transportation costs of an input compared to the costs of another) such that the firm has an incentive to relocate its facility and substitute among input quantities, leading to new shipping patterns that can generate a higher level of pollution under certain parameters. |
| Keywords: | Location, transport-related carbon emissions, carbon tax, production technology, sustainability |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:tut:cremwp:2018-12&r=all |
| By: | Zou, Wei (Asian Development Bank Institute); Chen, Liangheng (Asian Development Bank Institute); Xiong, Junke (Asian Development Bank Institute) |
| Abstract: | We establish a general equilibrium trade model and adopt the “market access” approach to measure the impact of the high-speed railway (HSR) network on the economic growth of 110 of the main prefecture-level cities of the People’s Republic of China, for which we manually collect the pairwise travel distances and railway speeds to calculate market access. The empirical results show that the launch of the HSR exerts significant positive effects on growth. Specifically, a 1% increase in market access leads to an increase in real income of 0.123% (controlling the region fixed effect) or 0.121% (controlling the province fixed effect). Counterfactual econometric analysis indicates that, if all the HSR were removed in 2015, the market access would fall by an average of 76.2% and the aggregate real income would decline by up to 9.4%. The growth effect of the HSR varies across cities, and the HSR has a more prominent impact on services than on manufacturing. The conclusion remains valid after a series of robustness tests. |
| Keywords: | high-speed railway; transport infrastructure; market access; economic growth; PRC |
| JEL: | F14 R11 R42 |
| Date: | 2018–07–20 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbiwp:0852&r=all |
| By: | Shenhao Wang; Jinhua Zhao |
| Abstract: | It is an enduring question how to combine revealed preference (RP) and stated preference (SP) data to analyze travel behavior. This study presents a new approach of using multitask learning deep neural network (MTLDNN) to combine RP and SP data and incorporate the traditional nest logit approach as a special case. Based on a combined RP and SP survey in Singapore to examine the demand for autonomous vehicles (AV), we designed, estimated and compared one hundred MTLDNN architectures with three major findings. First, the traditional nested logit approach of combining RP and SP can be regarded as a special case of MTLDNN and is only one of a large number of possible MTLDNN architectures, and the nested logit approach imposes the proportional parameter constraint under the MTLDNN framework. Second, out of the 100 MTLDNN models tested, the best one has one shared layer and five domain-specific layers with weak regularization, but the nested logit approach with proportional parameter constraint rivals the best model. Third, the proportional parameter constraint works well in the nested logit model, but is too restrictive for deeper architectures. Overall, this study introduces the MTLDNN model to combine RP and SP data, relates the nested logit approach to the hyperparameter space of MTLDNN, and explores hyperparameter training and architecture design for the joint demand analysis. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1901.00227&r=all |
| By: | Shenhao Wang; Jinhua Zhao |
| Abstract: | Deep neural network (DNN) has been increasingly applied to microscopic demand analysis. While DNN often outperforms traditional multinomial logit (MNL) model, it is unclear whether we can obtain interpretable economic information from DNN-based choice model beyond prediction accuracy. This paper provides an empirical method of numerically extracting valuable economic information such as choice probability, probability derivatives (or elasticities), and marginal rates of substitution. Using a survey collected in Singapore, we find that when the economic information is aggregated over population or models, DNN models can reveal roughly S-shaped choice probability curves, inverse bell-shaped driving probability derivatives regarding costs and time, and reasonable median value of time (VOT). However at the disaggregate level, choice probability curves of DNN models can be non-monotonically decreasing with costs and highly sensitive to the particular estimation; derivatives of choice probabilities regarding costs and time can be positive at some region; VOT can be infinite, undefined, zero, or arbitrarily large. Some of these patterns can be seen as counter-intuitive, while others can potentially be regarded as advantages of DNN for its flexibility to reflect certain behavior peculiarities. These patterns broadly relate to two theoretical challenges of DNN, irregularity of its probability space and large estimation errors. Overall, this study provides a practical guidance of using DNN for demand analysis with two suggestions: First, researchers can use numerical methods to obtain behaviorally intuitive choice probabilities, probability derivatives, and reasonable VOT. Second, given the large estimation errors and irregularity of the probability space of DNN, researchers should always ensemble either over population or individual models to obtain stable economic information. |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1812.04528&r=all |
| By: | Dominik Boddin; Frank Stähler |
| Abstract: | This paper discusses how international trade is organized from export to trans-boundary transport to import. All evidence suggests that the transport sector is independent, may exercise market power and features strong economies of scale. We develop a model of a transport industry that operates under imperfect competition and economies of scale and two generic trade models in which export and import activities are either organized at arm’s length or in a vertical partnership. Using a large dataset of maritime transport costs, tariffs and export prices, we test the model predictions and find that economies of scale beat market power: a decline in the tariff implies a decline in freight rates. Furthermore, our results are consistent only with international trade being organized in vertical partnerships because a tariff increase does not lead to a decrease in export prices. |
| Keywords: | trade costs, transport costs, export prices, vertical integration |
| JEL: | F12 F14 R40 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7378&r=all |
| By: | Julien Milanesi (CERTOP - Centre d'Etude et de Recherche Travail Organisation Pouvoir - CNRS - Centre National de la Recherche Scientifique - UPS - Université Toulouse III - Paul Sabatier - Université Fédérale Toulouse Midi-Pyrénées - UT2J - Université Toulouse - Jean Jaurès - INU Champollion - Institut national universitaire Champollion - Albi) |
| Date: | 2018–11–29 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-01939312&r=all |
| By: | Bergantino, Angela Stefania; Capozza, Claudia; Intini, Mario |
| Abstract: | This paper explores the nature of price variation in the retail gasoline sector with a novel approach. An empirical model is proposed that jointly analyses: i) the spatial interaction between stations in price setting; ii) the direct and the indirect effect of local competition on prices; iii) the role of territorial factors, generally neglected in the studies on gasoline prices. For all these purposes, variables at sub-municipal level are constructed. The results of the empirical model, tested on the city of Rome, confirm the spatial price interaction across stations. Moreover, evidence of direct and indirect effects of local competition on prices is found: the competitive forces acting in the gasoline sector are not bounded within a local market but they spill over across local markets. Micro-territorial variables turn out to have a sizeable influence on prices, particularly the real estate value. When these variables are added to the model, the strength of spatial interaction weakens. This suggests that including micro-territorial variables in the empirical specification strongly contributes to explain the variation of gasoline prices and to accurately detect the spatial dependence. |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:sit:wpaper:18_5&r=all |
| By: | Wang, Wei; Liu, Xiujuan; Ding, Lili; Li, Chen; Zhang, Wensi |
| Abstract: | The authors examine a mixed duopoly market with Cournot or Bertrand competition between a purely private port (port 1) and a partial public port (port 2). Considering both horizontal and vertical differentiation between the two ports, they analytically derive the welfare effect of privatization of port 2 and determine the optimal degree of privatization. Under Cournot or Bertrand competition, it is demonstrated that the social desirable private level of port 2 varies among full privatization, partial privatization and full nationalization, which hinges mainly upon the market size, both horizontal and vertical differentiation between the two ports and the marginal operation cost of each port. As a result, there is not necessarily a one-size-fits-all strategy for port privatization, and it is important for policymakers to consider the effects of market demand, port competition factors in port privatization. |
| Keywords: | port,competition,privatization,horizontal and vertical differentiation |
| JEL: | D43 L33 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:201884&r=all |