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Purpose: This paper describes a benchmarking framework applied to medium-sized urban public bus agencies in the United States, which has overcome the challenges of data quality, comparability, and understanding. Design/methodology/approach: The benchmarking methodology described in this paper is based on lessons learned through seven years of development of a fixed-route key performance indicator (KPI) system for the American Bus Benchmarking Group (ABBG). Founded in 2011, the ABBG is a group of public medium-sized urban bus agencies that compare performance and share best practices with peers throughout the United States. The methodology is adapted from the process used within international benchmarking groups facilitated by Imperial College and consists of four main elements: peer selection, KPI system development, processes to achieve high-quality data, and processes to understand relative performance and change. Findings: The four main elements of the ABBG benchmarking methodology consist of 18 subelements, which when applied overcome three main benchmarking challenges: comparability, data quality, and understanding. While serving as examples for the methodology elements, the paper provides specific insights into service characteristics and performance among ABBG agencies. Research limitations/implications: The benchmarking approach described in this paper requires time and commitment and thus is most suitably applied to a concise group of agencies. Practical implications: This methodology provides transit agencies, authorities, and benchmarking practitioners a framework for effective benchmarking. It will lead to high-quality comparable data and a strong understanding of the performance context to serve as a basis for organizational changes, whether for policy, planning, operations, stakeholder communication, or program development. Originality/value: The methodology, while consistent with recommendations from literature, is unique in its scale, in-depth validation and analysis, and holistic and multidimensional approach. [ABSTRACT FROM AUTHOR]

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This paper estimates the productivity gains from agglomeration economies for a sample of the largest metropolitan areas in the United States using measures of urban agglomeration based on employment density and employment accessibility. The latter is a more accurate measure of economic proximity and allows testing for the spatial decay of agglomeration effects with increasing travel time. We find that the productivity gains from urban agglomeration are consistent between measures, with elasticity values between 0.07 and 0.10. The large majority of the productivity gains occur within the first 20 minutes, and do not appear to exhibit significant nonlinearities. [ABSTRACT FROM AUTHOR]

Much of the previous empirical literature that evaluates the relationship between public capital and productivity using a production function approach has not allowed for lagged responses of productivity to public capital. Using panel data for 48 contiguous US states over the period 1984-1997, this article demonstrates the importance of using correctly specified dynamics to examine the contribution of highway capital to state productivity. We find that the imposition of static production function models tends to overestimate the short-run effect of highways while underestimating the long-run effect. More plausible results are found when accounting for dynamic adjustments of state output and these show that both the short-run and long-run effects of highway capital are positive but fairly small, even after including positive productivity spillovers from highways located in other states. [ABSTRACT FROM AUTHOR]

Fuel demand elasticities to determine consumer responses to tax increases or price shocks are typically based on aggregate data. The literature generally provides one elasticity estimate for each country, assuming similar response for all households. However, it is possible that different households can have different responses to the same stimuli depending on the household characteristics. Assuming a single elasticity for all households may fail to capture the detailed distributional effect on different socio-economic groups, which is often needed to fully understand the impact of fuel tax measures. This paper presents results from a household level gasoline demand model which accommodates variation in price and income elasticity with increasing income as well as for different socio-economic characteristics in the USA. We find substantial heterogeneity in price and income elasticities based on demographic groupings and income groups. Results of a distributional analysis for a gasoline tax are also presented using the heterogeneous responses. [ABSTRACT FROM AUTHOR]

Time-series estimation of gasoline demand elasticities often does not take into account the possibility of nonstationarity in the underlying data, which may render the parameter estimates spurious. Studies have shown that the time trending variables used to explain gasoline demand could be difference stationary and therefore, may require cointegration analysis to assess the relationship among the trending variables. In this work we use the cointegration technique to derive long-run and short-run demand elasticities of noncommercial gasoline consumption using time-series data for the USA from 1949 to 2004. We also attempt to incorporate the presence of a structural break in the data generation process of the time trending variables. Our results show that the consumption of gasoline and lifetime income have a long-term stable relationship after the second oil shock of 1978. Prior to the first oil shock of 1973, no such long-run relationship could be established through cointegration. [ABSTRACT FROM AUTHOR]

This paper analyses the causal relationship between highway infrastructure and employment within the U.S. We estimate dynamic panel models in a vector autoregressive framework using time-series cross-sectional data on lane miles of roadway capacity and private sector employment for the 48 contiguous states over the period 1984–1997. The issue of spatial dependence is explicitly taken into account by means of a spatial filtering technique. Our analysis reveals evidence of employment growth temporally influenced by annual growth in the provision of major highways within the same state and all other states, as well as the other way around. However, the results show that the existence and direction of these temporal and spatial effects depend on the type of highways and time lags considered. [ABSTRACT FROM AUTHOR]

Background: U.S. adults are at unprecedented risk of becoming overweight or obese, and most scientists believe the primary cause is an obesogenic environment. Worksites provide an opportunity to shape the environments of adults to reduce obesity risk. The goal of this group-randomized trial was to implement a four-component environmental intervention at the worksite level to positively influence weight gain among employees over a two-year period. Environmental components focused on food availability and price, physical activity promotion, scale access, and media enhancements., Methods: Six worksites in a U.S. metropolitan area were recruited and randomized in pairs at the worksite level to either a two-year intervention or a no-contact control. Evaluations at baseline and two years included: 1) measured height and weight; 2) online surveys of individual dietary intake and physical activity behaviors; and 3) detailed worksite environment assessment., Results: Mean participant age was 42.9 years (range 18-75), 62.6% were women, 68.5% were married or cohabiting, 88.6% were white, 2.1% Hispanic. Mean baseline BMI was 28.5 kg/m(2) (range 16.9-61.2 kg/m(2)). A majority of intervention components were successfully implemented. However, there were no differences between sites in the key outcome of weight change over the two-year study period (p = .36)., Conclusions: Body mass was not significantly affected by environmental changes implemented for the trial. Results raise questions about whether environmental change at worksites is sufficient for population weight gain prevention., Trial Registration: ClinicalTrials.gov: NCT00708461.