Speed

We investigate the determinants of driving speed in large us cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed and to rank cities by driving speed. Our data suggest that a congestion tax of, on average, about 1.5 cents per kilometer yields welfare gains of about 30 billion dollars per year, that centralized cities are slower, that cities with ring roads are faster, and that the provision of automobile travel in cities is subject to decreasing returns to scale

Speed

We investigate the determinants of driving speed in large us cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed and to rank cities by driving speed. Our data suggest that a congestion tax of, on average, about 1.5 cents per kilometer yields welfare gains of about 30 billion dollars per year, that centralized cities are slower, that cities with ring roads are faster, and that the provision of automobile travel in cities is subject to decreasing returns to scale

A framework for ensemble modelling of climate change impacts on lakes worldwide : the ISIMIP Lake Sector

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5 degrees x 0.5 degrees global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.Peer reviewe

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Three Essays in Urban Economics

This thesis studies the benefits and costs of urban living. Chapter 1 is a theoretical and empirical analysis of the benefits of urban density for consumers, while Chapter 2 proposes a model of how cities enhance the incentives for knowledge diffusion. Chapter 3 investigates the costs of congestion and the determinants of car travel speed across US cities. In Chapter 1, I study the consumption value of urban density by combining Google’s local business data with microgeographic travel data. I show that increased density enables consumers to both realize welfare gains from variety and save time through shorter trips. I estimate the gains from density in the restaurant industry, identifying willingness to pay for access to a slightly preferred location from the extra travel costs incurred to reach it. The results reveal large but very localized gains from density. Increasing the density of destinations generates little reduction in trip times, so most of these gains from density are gains from variety, not savings on travel time. In Chapter 2, I propose a new micro-foundation for knowledge spillovers. I model a city in which uncompensated knowledge transfers to entrepreneurs are bids by experts in auctions for jobs. The model derives from the key ideas about how knowledge differs from other inputs of production, namely that knowledge must be possessed for its value to be assessed, and that knowledge is freely reproducible. Agglomeration economies result from growth in the number of meetings between experts and entrepreneurs, and from heightened competition for jobs among experts. In Chapter 3, written jointly with Gilles Duranton and Matt Turner, we investigate the determinants of driving speed in large US cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed. Our investigation of the determinants of speed provides the foundations for a welfare analysis. This analysis suggests large gains in speed if slow cities can emulate fast cities, and sizable deadweight losses from congestion.Ph

Replication data for: "Speed"

Replication data for: "Speed

Mobility and Congestion in Urban India

We develop a methodology to estimate robust city-level vehicular speed indices, exactly decomposable into uncongested speed and congestion. We apply it to 180 Indian cities using 57 million simulated trips measured by a web mapping service. We verify the reliability of our simulated trips using a number of alternative data sources, including data on actual trips. We find wide variation in speed across cities that is driven more by differences in uncongested speed than congestion. Denser and more populated cities are slower, only in part because of congestion. Urban economic development is correlated with faster speed despite worse congestion.Peer reviewe