Does traffic congestion reduce employment growth?

This paper examines the impact of traffic congestion on employment growth in large U.S. metropolitan areas. An historic highway plan and political variables serve as instruments for endogenous congestion. The results show that high initial levels of congestion dampen subsequent employment growth. This finding suggests that increasing the efficiency of public infrastructure can spur local economies. Counterfactual estimates show that the employment-growth returns from modest capacity expansion or congestion pricing are substantial.Urban growth Congestion Transportation

Induced demand and rebound effects in road transport

This paper analyzes aggregate personal motor-vehicle travel within a simultaneous model of aggregate vehicle travel, fleet size, fuel efficiency, and congestion formation. We measure the impacts of driving costs on congestion, and two other well-known feedback effects affecting motor-vehicle travel: its responses to aggregate road capacity ("induced demand") and to driving costs including those caused by fuel-economy improvements ("rebound effect"). We measure these effects using cross-sectional time series data at the level of US states for 1966 through 2004. Results show that congestion affects the demand for driving negatively, as expected, and more strongly when incomes are higher. We decompose induced demand into effects from increasing overall accessibility of destinations and those from increasing urban capacity, finding the two elasticities close in magnitude and totaling about 0.16, somewhat smaller than most previous estimates. We confirm previous findings that the magnitude of the rebound effect decreases with income and increases with fuel cost, and find also that it increases with the level of congestion.Vehicle-miles traveled Congestion Rebound effect Induced demand

Estimating the price elasticity of fuel demand with stated preferences derived from a situational approach

An evidence-based policy debate about future fuel demand requires reliable estimates for fuel price elasticities. Such predictions are often based on revealed preference (RP) data. However, this procedure will only yield reliable results in the absence of severe structural discontinuities. In order to overcome this potential limitation we used a situational stated preference (SP) survey to estimate the response to hypothetical fuel price changes beyond the scope of previous observations. We elicit fuel price elasticities for price increases up to four Euros per liter and find that the situational approach predicts the actual responses to previously observed fuel price changes very well. We conclude that applying a situational approach is particularly useful, if behavioral predictions for unprecedented (non-monetary) policy interventions or supply side shocks are of interest that go beyond the reach of standard RP approaches. (Author's abstract

Validation of a Clinical Decision Rule to predict abuse in young children based on bruising characteristics

Importance: Bruising caused by physical abuse is the most common antecedent injury to be overlooked or misdiagnosed as nonabusive before an abuse-related fatality or near-fatality in a young child. Bruising occurs from both nonabuse and abuse, but differences identified by a clinical decision rule may allow improved and earlier recognition of the abused child. Objective: To refine and validate a previously derived bruising clinical decision rule (BCDR), the TEN-4 (bruising to torso, ear, or neck or any bruising on an infant Design, Setting, and Participants: This prospective cross-sectional study was conducted from December 1, 2011, to March 31, 2016, at emergency departments of 5 urban children\u27s hospitals. Children younger than 4 years with bruising were identified through deliberate examination. Statistical analysis was completed in June 2020. Exposures: Bruising characteristics in 34 discrete body regions, patterned bruising, cumulative bruise counts, and patient\u27s age. The BCDR was refined and validated based on these variables using binary recursive partitioning analysis. Main Outcomes and Measures: Injury from abusive vs nonabusive trauma was determined by the consensus judgment of a multidisciplinary expert panel. Results: A total of 21 123 children were consecutively screened for bruising, and 2161 patients (mean [SD] age, 2.1 [1.1] years; 1296 [60%] male; 1785 [83%] White; 1484 [69%] non-Hispanic/Latino) were enrolled. The expert panel achieved consensus on 2123 patients (98%), classifying 410 (19%) as abuse and 1713 (79%) as nonabuse. A classification tree was fit to refine the rule and validated via bootstrap resampling. The resulting BCDR was 95.6% (95% CI, 93.0%-97.3%) sensitive and 87.1% (95% CI, 85.4%-88.6%) specific for distinguishing abuse from nonabusive trauma based on body region bruised (torso, ear, neck, frenulum, angle of jaw, cheeks [fleshy], eyelids, and subconjunctivae), bruising anywhere on an infant 4.99 months and younger, or patterned bruising (TEN-4-FACESp). Conclusions and Relevance: In this study, an affirmative finding for any of the 3 BCDR TEN-4-FACESp components in children younger than 4 years indicated a potential risk for abuse; these results warrant further evaluation. Clinical application of this tool has the potential to improve recognition of abuse in young children with bruising

Validation of a Clinical Decision Rule to Predict Abuse in Young Children Based on Bruising Characteristics

Importance: Bruising caused by physical abuse is the most common antecedent injury to be overlooked or misdiagnosed as nonabusive before an abuse-related fatality or near-fatality in a young child. Bruising occurs from both nonabuse and abuse, but differences identified by a clinical decision rule may allow improved and earlier recognition of the abused child. Objective: To refine and validate a previously derived bruising clinical decision rule (BCDR), the TEN-4 (bruising to torso, ear, or neck or any bruising on an infant Design, Setting, and Participants: This prospective cross-sectional study was conducted from December 1, 2011, to March 31, 2016, at emergency departments of 5 urban children's hospitals. Children younger than 4 years with bruising were identified through deliberate examination. Statistical analysis was completed in June 2020. Exposures: Bruising characteristics in 34 discrete body regions, patterned bruising, cumulative bruise counts, and patient's age. The BCDR was refined and validated based on these variables using binary recursive partitioning analysis.Main Outcomes and Measures: Injury from abusive vs nonabusive trauma was determined by the consensus judgment of a multidisciplinary expert panel.Results: A total of 21123 children were consecutively screened for bruising, and 2161 patients (mean [SD] age, 2.1 [1.1] years; 1296 [60%] male; 1785 [83%] White; 1484 [69%] non-Hispanic/Latino) were enrolled. The expert panel achieved consensus on 2123 patients (98%), classifying 410 (19%) as abuse and 1713 (79%) as nonabuse. A classification tree was fit to refine the rule and validated via bootstrap resampling. The resulting BCDR was 95.6% (95% CI, 93.0%-97.3%) sensitive and 87.1% (95% CI, 85.4%-88.6%) specific for distinguishing abuse from nonabusive trauma based on body region bruised (torso, ear, neck, frenulum, angle of jaw, cheeks [fleshy], eyelids, and subconjunctivae), bruising anywhere on an infant 4.99 months and younger, or patterned bruising (TEN-4-FACESp).Conclusions and Relevance: In this study, an affirmative finding for any of the 3 BCDR TEN-4-FACESp components in children younger than 4 years indicated a potential risk for abuse; these results warrant further evaluation. Clinical application of this tool has the potential to improve recognition of abuse in young children with bruising.</p