The Experts below are selected from a list of 25968 Experts worldwide ranked by ideXlab platform
Chandra R Bhat - One of the best experts on this subject based on the ideXlab platform.
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incorporating a multiple discrete continuous outcome in the generalized heterogeneous data model application to Residential self selection effects analysis in an activity time use behavior model
Transportation Research Part B-methodological, 2016Co-Authors: Chandra R Bhat, Sebastian Astroza, Aarti C Bhat, Kai NagelAbstract:This paper makes both a methodological contribution as well as an empirical contribution. From a methodological perspective, we propose a new econometric approach for the estimation of joint mixed models that include a multiple discrete choice outcome and a nominal discrete outcome, in addition to the count, binary/ordinal outcomes, and continuous outcomes considered in traditional structural equation models. These outcomes are modeled together by specifying latent underlying unobserved individual lifestyle, personality, and attitudinal factors that impact the many outcomes, and generate the jointness among the outcomes. From an empirical perspective, we analyze Residential location choice, household vehicle ownership choice, as well as time-use choices, and investigate the extent of association versus causality in the effects of Residential Density on activity participation and mobility choices. The sample for the empirical application is drawn from a travel survey conducted in the Puget Sound Region in 2014. The results show that Residential Density effects on activity participation and motorized auto ownership are both associative as well as causal, emphasizing that accounting for Residential self-selection effects are not simply esoteric econometric pursuits, but can have important implications for land-use policy measures that focus on neo-urbanist design.
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a joint count continuous model of travel behavior with selection based on a multinomial probit Residential Density choice model
Transportation Research Part B-methodological, 2014Co-Authors: Chandra R Bhat, Sebastian Astroza, Raghuprasad Sidharthan, Mohammad Jobair Bin Alam, Waleed H KhushefatiAbstract:This paper formulates a multidimensional choice model system that is capable of handling multiple nominal variables, multiple count dependent variables, and multiple continuous dependent variables. The system takes the form of a treatment-outcome selection system with multiple treatments and multiple outcome variables. The Maximum Approximate Composite Marginal Likelihood (MACML) approach is proposed in estimation, and a simulation experiment is undertaken to evaluate the ability of the MACML method to recover the model parameters in such integrated systems. These experiments show that our estimation approach recovers the underlying parameters very well and is efficient from an econometric perspective. The parametric model system proposed in the paper is applied to an analysis of household-level decisions on Residential location, motorized vehicle ownership, the number of daily motorized tours, the number of daily non-motorized tours, and the average distance for the motorized tours. The empirical analysis uses the NHTS 2009 data from the San Francisco Bay area. Model estimation results show that the choice dimensions considered in this paper are inter-related, both through direct observed structural relationships and through correlations across unobserved factors (error terms) affecting multiple choice dimensions. The significant presence of self-selection effects (endogeneity) suggests that modeling the various choice processes in an independent sequence of models is not reflective of the true relationships that exist across these choice dimensions, as also reinforced through the computation of treatment effects in the paper.
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a joint count continuous model of travel behavior with selection based on a multinomial probit Residential Density choice model
Transportation Research Board 93rd Annual MeetingTransportation Research Board, 2014Co-Authors: Chandra R Bhat, Sebastian Astroza, Raghuprasad Sidharthan, Mohammad Jobair Bin Alam, Waleed H KhushefatiAbstract:This paper formulates a multidimensional choice model system that is capable of handling multiple nominal variables, multiple count dependent variables, and multiple continuous dependent variables. The parametric model system proposed in the paper is applied to an analysis of household-level decisions on Residential location, motorized vehicle ownership, the number of daily motorized tours, the number of daily non-motorized tours, and the average distance for the motorized tours.
David Brownstone - One of the best experts on this subject based on the ideXlab platform.
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a vehicle ownership and utilization choice model with endogenous Residential Density
Journal of Transport and Land Use, 2014Co-Authors: David Brownstone, Hao Audrey FangAbstract:This paper explores the impact of Residential Density on households’ vehicle type and usage choices using the 2001 National Household Travel Survey (NHTS). Attempts to quantify the effect of urban form on households’ vehicle choice and utilization often encounter the problem of sample selectivity. Household characteristics that are unobservable to the researchers might determine simultaneously where to live, what vehicles to choose, and how much to drive them. Unless this simultaneity is modeled, any relationship between Residential Density and vehicle choice may be biased. This paper extends the Bayesian multivariate ordered probit and tobit model developed in Fang (2008) to treat local Residential Density as endogenous. The model includes equations for vehicle ownership and usage in terms of number of cars, number of trucks (vans, sports utility vehicles, and pickup trucks), miles traveled by cars, and miles traveled by trucks. We carry out policy simulations which show that an increase in Residential Density has a negligible effect on car choice and utilization, but slightly reduces truck choice and utilization. We also perform an out-of-sample forecast using a holdout sample to test the robustness of the model.
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the impact of Residential Density on vehicle usage and fuel consumption evidence from national samples
Energy Economics, 2013Co-Authors: Jinwon Kim, David BrownstoneAbstract:This paper investigates the impact of Residential Density on household vehicle usage and fuel consumption. We estimate a simultaneous equations system to account for the potential Residential self-selection problem. While most previous studies focus on a specific region, this paper uses national samples from the 2001 National Household Travel Survey. The estimation results indicate that Residential Density has a statistically significant but economically modest influence on vehicle usage, which is similar to that in previous studies. However, the joint effect of the contextual Density measure (Density in the context of its surrounding area) and Residential Density on vehicle usage is quantitatively larger than the sole effect of Residential Density. Moving a household from a suburban to an urban area reduces household annual mileage by 18%. We also find that a lower neighborhood Residential Density induces consumer choices toward less fuel-efficient vehicles, which confirms the finding in Brownstone and Golob (2009).
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the impact of Residential Density on vehicle usage and fuel consumption
Research Papers in Economics, 2010Co-Authors: Jinwon Kim, David BrownstoneAbstract:This paper investigates the impact of Residential Density on vehicle usage and fuel consumption. The empirical model accounts for both Residential self-selection effects and non-random missing data problems. While most previous studies focus on a specific region, this paper analyzes national level data from the 2001 National Household Travel Survey. Comparing two households that are equal in all respects except Residential Density, the household residing in an area that is 1000 housing units per square mile denser (roughly 50% of the sample average) will drive 1500 (7.8%) less miles per year and will consume 70 (7.5%) fewer gallons of fuel than the household in the less dense area. The effect of the contextual Density measure (Density in the context of its surrounding area) is quantitatively larger than the sole effect of Residential Density. A simulation moving a household from suburban to urban area reduces household annual mileage by 15%.
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the impact of Residential Density on vehicle usage and energy consumption
Journal of Urban Economics, 2009Co-Authors: David Brownstone, Thomas F GolobAbstract:Abstract We specify and estimate a joint model of Residential Density, vehicle use, and fuel consumption that accounts for both self selection effects and missing data that are related to the endogenous variables. Our model is estimated on the California subsample of the 2001 U.S. National Household Travel Survey (NHTS). Comparing two California households that are similar in all respects except Residential Density, a lower Density of 1000 housing units per square mile (roughly 40% of the weighted sample average) implies an increase of 1200 miles driven per year (4.8%) and 65 more gallons of fuel used per household (5.5%). This total effect of Residential Density on fuel usage is decomposed into two paths of influence. Increased mileage leads to a difference of 45 gallons, but there is an additional direct effect of Density through lower fleet fuel economy of 20 gallons per year, a result of vehicle type choice.
Kristina Mjornell - One of the best experts on this subject based on the ideXlab platform.
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a matter of metrics how analysing per capita energy use changes the face of energy efficient housing in sweden and reveals injustices in the energy transition
Energy research and social science, 2020Co-Authors: Jenny Von Platten, Kristina Mjornell, Mikael MangoldAbstract:Improving energy performance of the housing stock continues to be an important undertaking in the energy transition of many EU member states. However, tendencies of low-income households generally living in buildings with low energy performance pose a challenge for this transition, and cases of ‘renoviction’ and ‘green gentrification’ are becoming more and more noticed in the scientific community. More so, questions regarding the distributive justice of costs and burdens in the energy transition of the housing stock have been raised. In this paper, we approach this problem from a perspective of energy performance metrics. Although energy performance (kWh/m2, year) is generally lower in buildings inhabited by low-income households, Residential Density—and thus building utilisation—tends to be higher. By measuring per capita energy use instead of area-normalised energy use, we investigate if a high Residential Density can offset a low energy performance and change the perception of which buildings are considered energy inefficient and which are not. Results showed that by measuring per capita energy use instead of area-normalised energy use, energy inefficient buildings were found in high-income city centres instead of in low-income suburbs of Swedish cities. Moreover, there has been an unjust distribution of the imposition of the energy transition over the past decade where the residents with the initially lowest per capita energy use have carried a disproportionately high share of the energy savings. This suggests that a change of energy performance metrics could offer an approach for a more socially just and sustainable energy transition of the housing stock. (Less)
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impact of high Residential Density on the building technology hvac systems and indoor environment in swedish apartments
12th Nordic Symposium on Building Physics NSB 2020 6 September 2020 through 9 September 2020, 2020Co-Authors: Akram Abdul Hamid, Jenny Von Platten, Kristina Mjornell, Dennis Johansson, Hans BaggeAbstract:During the last few years, there has been an increased number of overcrowded apartments, due to increased migration but also housing shortage in general, particularly in the suburbs to major cities. The question is how the indoor environment in these apartments is affected by the high number of persons and how the problems related to high Residential Density can be overcome. This paper aims to specify the problem by investigating and analysing the technical parameters influenced by Residential Density in Swedish apartments built between 1965-1974. To map the situation, 11 interviews with employees at housing companies were conducted. Based on extreme conditions described in the interviews, simulations of the indoor climate and moisture risks at some vulnerable parts of constructions were made. Simulations were focused on moisture loads and CO2 concentrations as functions of Residential Density and ventilation rate. Finally, measures to combat problems associated to overcrowding are suggested. The aim is that the results should be used by authorities to formulate incentives and/or recommendations for housing companies to take actions to ensure a good indoor environment for all, irrespective of Residential Density conditions. (Less)
Hao Audrey Fang - One of the best experts on this subject based on the ideXlab platform.
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a vehicle ownership and utilization choice model with endogenous Residential Density
Journal of Transport and Land Use, 2014Co-Authors: David Brownstone, Hao Audrey FangAbstract:This paper explores the impact of Residential Density on households’ vehicle type and usage choices using the 2001 National Household Travel Survey (NHTS). Attempts to quantify the effect of urban form on households’ vehicle choice and utilization often encounter the problem of sample selectivity. Household characteristics that are unobservable to the researchers might determine simultaneously where to live, what vehicles to choose, and how much to drive them. Unless this simultaneity is modeled, any relationship between Residential Density and vehicle choice may be biased. This paper extends the Bayesian multivariate ordered probit and tobit model developed in Fang (2008) to treat local Residential Density as endogenous. The model includes equations for vehicle ownership and usage in terms of number of cars, number of trucks (vans, sports utility vehicles, and pickup trucks), miles traveled by cars, and miles traveled by trucks. We carry out policy simulations which show that an increase in Residential Density has a negligible effect on car choice and utilization, but slightly reduces truck choice and utilization. We also perform an out-of-sample forecast using a holdout sample to test the robustness of the model.
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a discrete continuous model of households vehicle choice and usage with an application to the effects of Residential Density
Transportation Research Part B-methodological, 2008Co-Authors: Hao Audrey FangAbstract:This paper develops a new method to solve multivariate discrete-continuous problems and applies the model to measure the influence of Residential Density on households' vehicle fuel efficiency and usage choices. Traditional discrete-continuous modelling of vehicle holding choice and vehicle usage becomes unwieldy with large numbers of vehicles and vehicle categories. I propose a more flexible method of modelling vehicle holdings in terms of number of vehicles in each category, using a Bayesian multivariate ordinal response system. I also combine the multivariate ordered equations with Tobit equations to jointly estimate vehicle type/usage demand in a reduced form, offering a simpler alternative to the traditional discrete/continuous analysis. Using the 2001 National Household Travel Survey data, I find that increasing Residential Density reduces households' truck holdings and utilization in a statistically significant but economically insignificant way. The results are broadly consistent with those from a model derived from random utility maximization. The method developed above can be applied to other discrete-continuous problems.
Kristina Sundquist - One of the best experts on this subject based on the ideXlab platform.
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neighborhood environment and muscle mass and function among rural older adults a 3 year longitudinal study
International Journal of Health Geographics, 2020Co-Authors: Kristina Sundquist, Kenta Okuyama, Takafumi Abe, Shozo Yano, Toru NabikaAbstract:Sarcopenia, resulting from loss of muscle mass and function, is highly prevalent in the ageing societies and is associated with risk of falls, frailty, loss of independence, and mortality. It is important to identify environmental risk factors, so that evidence-based interventions to prevent sarcopenia can be implemented at the population level. This study aimed to examine the potential effect of several objectively measured neighborhood environmental factors on longitudinal change of muscle mass and function among older adults living in rural Japanese towns where the population is ageing. This study was based on data from the Shimane CoHRE Study conducted by the Center for Community-based Healthcare Research and Education (CoHRE) at Shimane University in 3 rural towns in the Shimane Prefecture, Japan. Subjects older than 60 years, who participated in an annual health examination in 2016 and any follow-up years until 2019, i.e., 4 possible time points in total, were included (n = 2526). The skeletal muscle mass index (SMI) and grip strength were assessed objectively for each year as a measure of muscle mass and function, respectively. Neighborhood environmental factors, i.e., hilliness, bus stop Density, intersection Density, Residential Density, and distance to a community center were measured by geographic information systems (GIS). Linear mixed models were applied to examine the potential effect of each neighborhood environmental factor on the change of SMI and grip strength over time. Males living far from community centers had a less pronounced decline in SMI compared to those living close to community centers. Females living in areas with higher Residential Density had a less pronounced decline in grip strength compared to those living in areas with lower Residential Density. Neighborhood environmental factors had limited effects on change of SMI and grip strength among rural older adults within the 3 years follow up. Further long-term follow up studies are necessary by also taking into account other modifiable neighborhood environmental factors.
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walkability parameters active transportation and objective physical activity moderating and mediating effects of motor vehicle ownership in a cross sectional study
International Journal of Behavioral Nutrition and Physical Activity, 2012Co-Authors: Ulf Eriksson, Daniel Arvidsson, Klaus Gebel, Henrik Ohlsson, Kristina SundquistAbstract:Background: Neighborhood walkability has been associated with physical activity in several studies. However, as environmental correlates of physical activity may be context specific, walkability parameters need to be investigated separately in various countries and contexts. Furthermore, the mechanisms by which walkability affects physical activity have been less investigated. Based on previous research, we hypothesized that vehicle ownership is a potential mediator. We investigated the associations between walkability parameters and physical activity, and the mediating and moderating effects of vehicle ownership on these associations in a large sample of Swedish adults. Methods: Residential Density, street connectivity and land use mix were assessed within polygon-based network buffers (using Geographic Information Systems) for 2,178 men and women. Time spent in moderate to vigorous physical activity was assessed by accelerometers, and walking and cycling for transportation were assessed by the International Physical Activity Questionnaire. Associations were examined by linear regression and adjusted for socio-demographic characteristics. The product of coefficients approach was used to investigate the mediating effect of vehicle ownership. Results: Residential Density and land use mix, but not street connectivity, were significantly associated with time spent in moderate to vigorous physical activity and walking for transportation. Cycling for transportation was not associated with any of the walkability parameters. Vehicle ownership mediated a significant proportion of the association between the walkability parameters and physical activity outcomes. For Residential Density, vehicle ownership mediated 25% of the association with moderate to vigorous physical activity and 20% of the association with the amount of walking for transportation. For land use mix, the corresponding proportions were 34% and 14%. Vehicle ownership did not moderate any of the associations between the walkability parameters and physical activity outcomes. Conclusions: Residential Density and land use mix were associated with time spent in moderate to vigorous physical activity and walking for transportation. Vehicle ownership was a mediator but not a moderator of these associations. The present findings may be useful for policy makers and city planners when designing neighborhoods that promote physical activity.
