SPEAKERS
Prottoy AKBAR (Aalto University)
Biography:
Prottoy A. Akbar is an Assistant Professor at the Department of Economics at Aalto University and the Helsinki Graduate School of Economics. He is an applied microeconomist with a focus on urban and transportation economics. His recent research explores questions such as: What explains slow urban travel in rich versus poor countries? How do the gains from faster transportation networks compare for high- and low-income travelers? What are its implications for residential segregation and the distribution of economic activity within cities?
Presentation Title:
"Who benefits from faster public transit?"
Abstract:
Fast public transit networks are widely believed to (i) attract more riders and reduce negative externalities of driving, and (ii) reduce inequality by improving mobility for the urban poor. But are the transit improvements that are most effective at increasing transit ridership also more equitable? Combining survey data with web-scraped counterfactual travel times for millions of trips across 49 large US cities, I estimate a model of travel mode and residential location choice. I characterize the heterogeneity across income groups and cities in commuters' marginal willingness to pay for access to faster transit and to increase their transit ridership. I find that higher-income transit riders sort more aggressively into the fastest transit routes and are, on average, willing to pay more for faster commutes. Improvements in transit speed are most effective at generating transit ridership and welfare gains where transit is already fast (relative to driving), in cities with a greater share of rail-based transit and where the gains are larger for higher-income commuters. Transit improvements benefit lower-income commuters more where transit is relatively slow, in cities with more bus transit, and where the overall marginal gains are small.
Nicholas W. BUCHHOLZ (Princeton University)
Biography:
Nicholas Buchholz is an Assistant Professor of Economics at Princeton University. His work studies the design and regulation of transportation markets and urban infrastructure. Recent work examines welfare and efficiency of pricing and price discrimination in taxi and ride-hail markets, as well as the use of these markets as settings to conduct novel measurements of labor supply elasticity and consumers’ value of time. Buchholz holds a Ph.D. in Economics from the University of Texas at Austin and a B.S. in Economics and Mathematics from the University of Chicago.
Presentation Title:
"Rethinking Reference Dependence: Wage Dynamics and Optimal Taxi Labor Supply"
Abstract:
Workers with variable earnings and flexible hours offer unique opportunities to evaluate intertemporal labor supply elasticities. Existing static analyses, however, have generated well-known puzzles, suggesting evidence of downward sloping labor supply curves. Using a large sample of shifts of New York City taxicab drivers, we estimate a dynamic optimal stopping model of drivers’ work times and quitting decisions. We model the equilibrium interactions of supply and demand through dynamic state transition densities, allowing us to estimate driver opportunity costs via a single agent problem. Our results demonstrate that several apparent behavioral biases documented in the literature can be reproduced using entirely standard preferences. We use our model to provide new estimates of individual earnings elasticities and show that taxi drivers have similar elasticities to workers in markets where experimental evidence has been obtained. Finally, we use data spanning a 2012 fare change to estimate labor supply elasticities with respect to market prices, accounting for the equilibrium impact of prices on supply and demand. We find market elasticities to be approximately a third of the size of individual elasticities, suggesting that existing estimates of the benefits to recent earnings legislation in the taxi and ride-hail industries are overstated.
Alejandro ROBINSON-CORTES (University of Exeter)
Biography:
Alejandro Robinson-Cortés is a Lecturer in Economics at the University of Exeter Business School in the UK. His research interests lie at the intersection of Empirical Industrial Organization and Market Design. His work uses a mix of theoretical and empirical methods to study questions related to the matching aspect of markets. For example, he has studied how children are assigned to foster homes in the child welfare system, as well as the functioning of decentralized matching markets in the lab. More recently, he has studied how to manage congestion in online two-sided platforms through algorithm design. He received a PhD from Caltech in 2020.
Presentation Title:
"Managing Congestion in Two-Sided Platforms: The Case of Online Rentals"
Abstract:
Thick two-sided matching platforms, such as the room-rental market, face the challenge of showing relevant objects to reduce search frictions. Many platforms use simple ranking algorithms to determine the search results that users are shown, often breaking ties with a random number. The main problem is that rough criteria to determine exposure is the same for all users. Using rich data on a room rental platform we show that such simple ranking algorithms create an inefficient source of congestion, inducing individuals to view, click, and request the same rooms. This greatly limits the number of matches created by the platform. We estimate preferences semiparametrically and simulate counterfactuals under different search algorithms. The counterfactual number of views, requests and matches that can be generated if rooms are shown differently is larger.
Juan CAMILLO CASTILLO (University of Pennsylvania)
Biography:
Juan Camilo Castillo is an Assistant Professor in the Economics Department at the University of Pennsylvania. His research is in Industrial Organization, Microeconomic Theory, and Market Design, with a focus on online platforms, the digital economy, and transportation. He has also done work on how to accelerate widespread access to Covid-19 vaccines, and some of his earlier research analyzes the economics of violence and illegal drug markets.
Presentation Title:
“Optimal Urban Transportation Policy: Evidence from Chicago.”
Abstract:
Urban transportation policies have become a focal point in cities’ efforts to curb congestion and address environmental and distributional concerns. This paper characterizes the optimal mix of policies and evaluates their welfare and distributional effects. To that end, we present a framework of a municipal government aiming to maximize welfare. The government chooses the prices and frequencies of different modes of transportation, subject to a budget constraint that introduces monopoly-like distortions. We move on to an empirical application of this framework to the city of Chicago. We first construct a novel dataset of all relevant transportation modes. On the demand side, our empirical model captures the rich heterogeneity in travel choices. On the supply side we account for differential congestion and costs of different road- based modes. Our counterfactual results suggest that if the city only intervenes on public transit, it should lower transit prices even further but also lower frequency to meet its budget constraint. On the other hand, introducing a per-kilometer tax on drivers leads to higher welfare gains.
Peter CHRISTENSEN (University of Illinois)
Biography:
Peter Christensen is an applied microeconomist who studies how public policy and technological interventions can be used to improve social and environmental outcomes in cities around the world. He directs BDEEP, a research team that combines data science and economic methods at the National Center for Supercomputing Applications. He is a Research Associate at the National Bureau of Economic Research and a faculty affiliate with the Poverty Action Laboratory (J-PAL) and Evidence for Action on Energy Efficiency (E2e). He has ongoing research partnerships with teams at Zillow, Uber Technologies, and Google. His work has been supported by the US EPA, National Science Foundation, Sloan Foundation, and the Russell Sage Foundation. He holds a PhD and a MESc from Yale University and a BA from UC Davis.
Presentation Title:
Abstract:
Isis DURRMEYER (Toulouse School of Economics)
Biography:
Isis Durrmeyer is a professor at TSE and affiliated with CEPR. She joined the University of Toulouse in 2016, after obtaining a PhD in economics from the University of Paris 1 Panthéon-Sorbonne and a post-doctorate at the University of Mannheim. Her research is at the intersection of empirical industrial economics and public policy evaluation. She has developed structural models to evaluate environmental policies in the automobile market and urban transportation policies. In 2019, she was awarded a prestigious ERC fellowship to study price dispersion, understand the reasons for it, and evaluate the consequences for consumers.
Presentation Title:
"Price Discrimination and Online Sales in the Automobile Industry"
Abstract:
We investigate the welfare consequences of the introduction of an online distribution channel in the retail sector. Online transactions imply buyer's anonymity, which prevents online sellers to price discriminate and buyers to obtain discounts over the posted prices. Moreover, online transactions save transportation costs to buyers. We analyze these trade-offs in the context of the car dealing industry. We model demand for cars and estimate how the distance to local dealers influences car purchases. We estimate a supply model with in-person transactions and unobserved discounts over the posted prices. We use the estimated parameters and a model with both online and in-person distribution channels to predict the consequences of introducing the online channel for sellers and buyers. Our preliminary results indicate that an online distribution channel would be beneficial for sellers and internet-savvy buyers, while it would hurt other buyers.
Gabrielle GAMBULI (Université Gustave Eiffel (GRETTIA) and INSEE (SSPLab) )
Biography:
Gabrielle Gambuli is a Postdoctoral Research Fellow at Université Gustave Eiffel (GRETTIA) and INSEE (SSP Lab), working on MobiTIC ANR project with Etienne Côme and Marie-Pierre Joubert - de Bellefon. Her research is at the intersection of Economic Geography, Transportation, and Innovation. She obtained her PhD in Economics from ESSEC Business School and CY Cergy-Paris Université in 2023.
Presentation Title:
"High-Speed Railways and the Geography of Inventors' Collaboration: Evidence from France (1980-2010)".
Abstract:
This study explores the impact of high-speed railways (HSR) on inventor collaboration over long distances, which plays as a catalyst of face-to-face interactions and knowledge exchange. We use a novel region-to-region travel time dataset using HSR implementation in France. Employing a gravity model with three-way fixed effects, we assess the causal relationship between travel time reduction and cross-regional co-patenting trends between NUTS3 region-pairs, addressing endogeneity concerns. Results show a robust positive effect of reduced travel time on collaboration, most of all as comparison of intra-regional and long-distance collaborations. Core regions significantly benefit, but advantages extend beyond directly-HSR-connected regions. Moreover, reduced travel time is related to collaborative patents exhibiting higher novelty and wider scope within the realm of technology fields. Finally, we find that the reduction in travel time has fostered connections among inventor leaders and inventors with superior productivity compared to their collaborators’ pool.
Cristina GUALDANI (Queen Mary University)
Biography:
Cristina Gualdani is an Associate Professor at Queen Mary University of London (QMUL). She earned her PhD in Economics from University College London in 2017. Before joining QMUL, she served as an Assistant Professor at the Toulouse School of Economics. In her research, Cristina combines game theory and econometric models to analyze the strategic choices of firms and individuals, providing valuable insights for policymaking. She has a particular interest in questions related to market entry, transportation settings, networks, and matching. Cristina's research papers have been published or are forthcoming in prestigious journals, including the Journal of Political Economy and the Journal of Econometrics.
Presentation Title:
"Price Competition and Endogenous Product Choice in Networks: Evidence from the US Airline Industry"
Abstract:
We develop a two-stage game in which competing airlines first choose the networks of markets to serve in the first stage before competing in price in the second stage. Spillovers in entry decisions across markets are allowed, which accrue on the demand, marginal cost, and fixed cost sides. We show that the second-stage parameters are point identified, and we design a tractable procedure to set identify the first-stage parameters and to conduct inference. Further, we estimate the model using data from the domestic US airline market and find significant spillovers in entry. In a counterfactual exercise, we evaluate the 2013 merger between American Airlines and US Airways. Our results highlight that spillovers in entry and post-merger network readjustments play an important role in shaping post-merger outcomes.
Nicolas KOCH (Mercator Research Institute on Global Commons and Climate Change, MCC)
Biography:
Nicolas Koch is head of the Policy Evaluation Lab at the Mercator Research Institute on Global Commons and Climate Change (MCC) and a Research Fellow at the IZA Institute of Labor Economics. He is an environmental economist drawing from the fields of urban and transportation economics, health economics, and applied microeconomics in general. His research combines methodologies for causal impact and welfare analysis and has been published articles in, amongst others, AEJ: Economic Policy, PNAS, Nature Climate Change, JAERE, JEEM, and JUE.
Presentation Title:
"Machine Learning from Big GPS Data about the Welfare Costs of Imperfect Congestion Pricing"
Abstract:
We exploit GPS-coded vehicle movement data that records millions of road users every second of their way over a full year in Berlin to suggest a novel approach to estimate the external costs of traffic congestion from revealed choices in a big data setting. To measure travel choices, we use unsupervised machine learning to assign anonymous commuting and non-commuting trips to individual drivers and track their repeated trip and route choices. We move beyond considering particular roads in isolation and quantify externalities created by actual trips on routes that combine the diverse road technologies of main roads and side streets. Causal identification for the route-level congestion elasticity relies on exogenous increases in traffic density from rerouting induced by traffic incidences that occur on adjacent roads off a given trip’s route. Our findings highlight significant heterogeneity in the marginal external costs of congestion dependent on a granular set of temporal and spatial dimensions. Sufficient statistics suggest that simple and commonly used pricing schemes do not improve efficiency by much. Only more sophisticated pricing schemes that vary by hour and route are efficient.
Xavier Lambin (ESSEC Business School)
Biography:
I am an Assistant Professor at ESSEC Business School. I am an applied theory and empirical economist. My research interests cover Industrial Organization, Machine Learning, Market Design and Regulation, with applications to the Digital and Energy sectors. I am the scientific coordinator of the BlaBlaModes project for ESSEC.
Presentation Title:
"Riding together: Eliciting Travelers' Preferences for Long-Distance Darpooling"
Abstract:
Most seats in private cars are empty when drivers hit the road. Carpooling thus represents a low-cost strategy to reduce carbon emissions in the transportation sector. Using revealed preference data from actual long-distance carpooling trips in France, we estimate passengers' preferences for the different characteristics of a ride. We find that passengers are highly price-elastic and value significantly the convenience of pick-up and drop-off locations. In contrast, their value of time once in the car is significantly lower than typical reference values. Finally, we discuss the effectiveness of several policy tools aimed at promoting carpooling and we assess the extent to which drivers and passengers could be better matched.
Mathias REYNAERT (Toulouse School of Economics)
Biography:
Mathias Reynaert is a Professor of Economics at the Toulouse School of Economics and a research affiliate at the Center for Economic Policy Research (CEPR). His fields of interest are empirical industrial organization and environmental economics.
Presentation Title:
"When will electric vehicles connect to the grid? with Pascal Heid and Kevin Remmy"
Abstract:
The transition to electricity-powered personal vehicles poses major challenges to policymakers. A crucial aspect is the timing of intraday charging of electric vehicles (EV). The electricity market equilibrium depends on the intraday distribution of the additional load from EVs. This affects the amount of pollution from the energy supply: renewables are the marginal generation source at some but not all points of the day. We build and estimate an equilibrium model for Germany where we model EV owners' optimal charging decision, car demand, charging station entry, and the electricity market. We rely on rich individual-level data on daily driving patterns and data from charging station demand to investigate when EVs are charged intraday within the current policy framework. Our empirical model allows us to study how policy options such as demand subsidies, charging station subsidies, and electricity rates affect the interplay between EV demand, the electricity market, and resulting pollution levels.
Nikhil VELLODI (Paris School of Economics)
Biography:
Presentation Title:
"Insider Imitation"
Abstract:
We study how regulating data usage impacts innovation in digital markets. Platforms commonly use proprietary data about third-party sellers to inform their own competing offerings, dampening incentives for innovation. We model this interaction and characterize how data usage restrictions reshape these incentives. An outright ban on data usage may boost or curtail innovation, depending upon the thickness of the right tail of demand for new products. More flexible rules controlling when and what data is made available can always improve the effectiveness of regulation. Our results contribute to an ongoing policy discussion regarding competition in digital markets.
Kenan ZHANG (École Polytechnique Fédérale de Lausanne)
Biography:
Dr. Kenan Zhang is a tenure-track Assistant Professor at the École polytechnique fédérale de Lausanne (EPFL) and leads the Laboratory for Human-Oriented Mobility Eco-system (HOMES). Her research focuses on the mathematical modeling, optimization and operations management of urban transportation systems, with special interests in emerging mobility services and technologies.
Kenan obtained her BSc. in Civil Engineering from Tsinghua University and MSc. in Architecture-Engineering-Construction Management (AECM) from Carnegie Mellon University. She completed her Ph.D. in Civil Engineering (with a focus on Transportation System Analysis and Planning) and a second MSc. in Statistics at Northwestern University. Prior to joining EPFL, Kenan worked as a postdoctoral researcher at ETH Zurich.
Presentation Title:
"How does mobility-as-a-service (MaaS) platform survive as an intermediary?"
Abstract:
The primary goal of mobility-as-a-service (MaaS) is to provide seamless door-to-door trips by integrating different transport modes. Although many MaaS platforms have emerged in recent years, most of them remain at a limited integration level. In this talk, I will present our recent work on the MaaS platform design. Specifically, we consider the MaaS platform as an intermediary in a multi-model transport system that purchases capacity from different service operators and sells multi-modal trips to travelers only based on their origin-destination pairs, regardless of the transport mode. We adopt the analysis framework of many-to-many stable matching to decompose the assignment and pricing problems and solve them in sequence. I will discuss several analytical results regarding the conditions of stable outcomes and show some numerical results on a hypothetical multi-modal transport system based on the Sioux Falls network.
Dianzhuo ZHU (University of Paris-Dauphine, PSL)
Biography:
Dianzhuo Zhu is a post-doctoral researcher at Paris-Dauphine University, PSL. Her main research interests are transportation economics and digital economics. She is particularly interested in carpooling and other shared mobility modes, from user behavior to operators’ roles in digital and ecological transition, to the regulatory challenges. She currently leads the Dauphine team of the BlaBlaModes project, of which PSE, ESSEC, and Dauphine are academic partners. Besides research, she also enjoys teaching. She is the co-responsible for the “ecological transition” track of the IREN master at Dauphine, where she creates and teaches the fundamental course on ecological transition and a specialization course on mobility.
LinkedIn: https://www.linkedin.com/in/dianzhuo-zhu/
Personal website: https://sites.google.com/view/dianzhuozhu
Presentation Title:
"How Does Price Recommendation Shape Drivers’ Behavior in the Carpooling Market"
Abstract:
The emergence of digital sharing economy platforms has enabled individuals to share access to their assets with strangers without being professional service providers, showing great potential for better exploiting idle resources. However, the lack of market knowledge among suppliers may hamper their pricing ability. A non-binding price recommendation mechanism may provide imperfect but effective information to shape the market. We benefit from empirical data of an exogenous recommended price increase of BlaBlaCar, Europe’s largest inter-city carpooling company. Results indicate that drivers do follow recommendations in general, but experienced drivers deviate more often. However, the deviation tendency gap shrank after the reform. Moreover, an increased overall supplied price after the reform led to more supplied rides, both at the extensive and the intensive margin. Total transactions also increased, suggesting a right shift of the demand curve. We discuss potential welfare implications and outline future steps.