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TransportationEcoefficiency     Social and Political Drivers in U.S.     Metropolitan Areas                        Dr. Ann...
Measuring Transportation Building         smarter cities requires good research on transportation   Many  micro-level st...
Transportation Ecoefficiency Environmental       impact of      transportation, per unit of travel Measured             ...
Measuring TE: Pop. Density Proxy for travel distance1 Associated with other built  environment features that affect trav...
Measuring TE: Commuting Commuting:       A   major share of personal travel        The most basic and fixed form of dai...
Measuring TE: Data & Sample Sample:   225 U.S. Metropolitan  Statistical Areas (MSAs), from 1980 to  2008 Source: Census...
TE in US Metro Areas                   For 225 U.S. MSAs:                                    1980 2008             Variabl...
TE Trends: Commuting 100%                                            16.26% 90%               22.48%                      ...
TE Trends: the index            Change in average TE score:      0.6      0.5      0.4      0.3      0.2      0.1        0...
Analyzing TE: data & methods Sample:       225 U.S. Metropolitan      Statistical Areas (MSAs)1 Dependent   variable: TE...
Results: New Political Culture New      Political Culture theory: beneficial      effects of educated professionals with ...
Results: Planning State-mandated    comprehensive    planning is expected to increase TE 1       State policies requirin...
Results: Planning Variable                                                         Coef. Beta State-mandated urban growth ...
Results: Race Race   should impact local policy,  housing, etc., and therefore also TE White Flight could reduce TE But...
Results: Race
Results: Census Region Westernregion showed significantly higher TE: coef. = 0.42***, beta = 0.22 Includingcensus region...
Results: InteractionsVariable                    Coef.   BetaReal income per capita * %  5.20*** 7.74change in real income...
Results: Predictive Power         1      0.98      0.96      0.94      0.92       0.9      0.88      0.86      0.84      0...
Limitations Qualitative  differences between bus and rail  transit (in service quality and perceptions) Interpretation o...
Main Contributions The  TE concept and metric is a useful  empirical tool1 Macro-level social forces impact urban  trans...
Recommendations for Practice Comprehensive    planning can achieve real  results, especially with enforceable plans Mult...
Acknowledgements                Funding & ResourcesOhio State University Dept. of SociologyOhio State University Environme...
References   Boschken H.L. 2003. “Global Cities, Systemic Power, and Upper-Middle-Class Influence.” Urban    Affairs Revi...
Mapping TE Scores (2000 data)
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Transportation Ecoefficiency: Social and Political Drivers in U.S. Metropolitan Areas

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Presentation at the Association of American Geographers' annual meeting, April 9-13, Los Angeles, CA. Session: Cities, Transportation and Sustainability.
Abstract:
As environmental impacts from automobiles have grown, more research is needed to determine what social and policy forces can influence transportation ecoefficiency (TE). TE is the environmental impact per unit of travel, including accessibility and mobility, and it is measured by proxy as the index of four z-scores: percent drive-alone commuting (sign reversed); percent commuting by public transit; percent of commuters walking or riding a bicycle; and population density. A higher TE index indicates more ecoefficient transportation, compared to the average. This study presents a macro-level analysis of institutional and structural predictors of TE in a sample of 225 United States Metropolitan Statistical Areas. Specifically, Ordinary Least Squares regression with robust standard errors points to several conclusions. A New Political Culture, measured by education and income (real per capita income and % change in real per capita income) increases TE, although professional status could reverse this effect. High and rising incomes interact to increase TE, with an effect size over 10 times larger than other effects. State-mandated urban growth management increases TE, demonstrating the beneficial effects of comprehensive planning. This is enhanced by higher incomes, and the combination of high incomes and state-mandated planning also has an effect size over 10 times larger than other effects. Percent African American has a quadratic influence, presumably due to the effects of tolerance and racial threat. Overall, this analysis demonstrates that macro-level social processes, including race, comprehensive planning, and the presence of a new political culture, have a significant impact on TE.

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Transportation Ecoefficiency: Social and Political Drivers in U.S. Metropolitan Areas

  1. 1. TransportationEcoefficiency Social and Political Drivers in U.S. Metropolitan Areas Dr. Anna C. McCreery
  2. 2. Measuring Transportation Building smarter cities requires good research on transportation  Many micro-level studies in the literature  Macro-level research less well established Thismacro-level study investigates broad social forces that impact local transportation
  3. 3. Transportation Ecoefficiency Environmental impact of transportation, per unit of travel Measured by proxy as the index of:  Population density1  % of commuters driving to work alone (sign reversed)  % of commuters taking public transit  % of commuters walking or bicycling1 Cervero 2007, Ewing and Cervero 2010, Naess 2006
  4. 4. Measuring TE: Pop. Density Proxy for travel distance1 Associated with other built environment features that affect travel 21 Ewing and Cervero 20102 Cervero 2007, Ewing and Cervero 2010, Naess 2006
  5. 5. Measuring TE: Commuting Commuting: A major share of personal travel  The most basic and fixed form of daily travel  Likely to co-vary with other trips 1 Different commute modes have vastly different environmental impacts:  Driving alone is very eco-inefficient  Public transit, walking, and cycling are generally more ecoefficient modes1 Lee et al. 2009; Naess 2006
  6. 6. Measuring TE: Data & Sample Sample: 225 U.S. Metropolitan Statistical Areas (MSAs), from 1980 to 2008 Source: Census data and American Community Survey
  7. 7. TE in US Metro Areas For 225 U.S. MSAs: 1980 2008 Variable mean meanPopulation Density* 320.3 360.0Commuters driving 67.9% 78.2%Commuters taking transit 3.21% 2.16%Commuters walking/bicycling 6.40% 3.35%TE Index 0.280 -0.204* People per square mile
  8. 8. TE Trends: Commuting 100% 16.26% 90% 22.48% other 3.35% other 2.16% walk 80% 6.40% transit bike walk 3.21 70% bike transit% 78.23% 60% 67.91% drive drive 50% 1980 2008 Other Modes % of commuters walking/bicycling % of commuters taking public transit % of commuters driving alone
  9. 9. TE Trends: the index Change in average TE score: 0.6 0.5 0.4 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 1980 1990 2000 2008 Mean 0.504 -0.068 -0.227 -0.211 TE index
  10. 10. Analyzing TE: data & methods Sample: 225 U.S. Metropolitan Statistical Areas (MSAs)1 Dependent variable: TE score, 2008 Analysis: Ordinary Least Squares regression with robust standard errors, predicting 2008 TE from various independent variables (measured around 1980). Controls for 1980 TE.1 Data sources: U.S. Census, American Community Survey, National Historical GIS, and others
  11. 11. Results: New Political Culture New Political Culture theory: beneficial effects of educated professionals with high and rising incomes1 Variable Coef. Beta% prof / tech workers -0.04*** -0.31% college grads 0.58*** 0.24real income per capita 1.64*** 0.30% change in real income percapita 0.75** 0.09 * p<0.05 ** p<0.01 *** p<0.0011 Boschken 2003; Clark & Harvey 2010; DeLeon & Naff 2004
  12. 12. Results: Planning State-mandated comprehensive planning is expected to increase TE 1  State policies requiring coordinated urban growth management2 should increase TE  State mandated planning is more likely to be enforceable1 Cervero 2002, Ewing and Cervero 2010, Filion and McSpurren 2007, Handy 2005, Quinn 20062 Yin and Sun 2007
  13. 13. Results: Planning Variable Coef. Beta State-mandated urban growth 0.10** 0.10 management * p<0.05 ** p<0.01 *** p<0.001Photo Credits: http://www.memphistn.gov/media/images/gov2.jpghttp://soetalk.com/wp-content/uploads/2011/01/06senate2-600.jpg
  14. 14. Results: Race Race should impact local policy, housing, etc., and therefore also TE White Flight could reduce TE But….theory does not predict direction of influence. Interpretation is tentative.Variable Coef. Beta% African American 0.100** 0.12% African American, squared -0.001** -0.22 * p<0.05 ** p<0.01 *** p<0.001
  15. 15. Results: Race
  16. 16. Results: Census Region Westernregion showed significantly higher TE: coef. = 0.42***, beta = 0.22 Includingcensus region altered the significance of other variables  Indicating that other regional differences affect what factors influence TE Culture? Climate?
  17. 17. Results: InteractionsVariable Coef. BetaReal income per capita * % 5.20*** 7.74change in real income percapitaReal income per capita * 0.60* 6.04State-mandated urban growthmanagement * p<0.05 ** p<0.01 *** p<0.001
  18. 18. Results: Predictive Power 1 0.98 0.96 0.94 0.92 0.9 0.88 0.86 0.84 0.82 0.8 High * Rising Income * Base Model Incomes Planning R-squared 0.872 0.882 0.879
  19. 19. Limitations Qualitative differences between bus and rail transit (in service quality and perceptions) Interpretation of the effect of race is very tentative Data limitations and imperfect measurement of:  Planning (preferably regional planning)  Non-significant variables
  20. 20. Main Contributions The TE concept and metric is a useful empirical tool1 Macro-level social forces impact urban transportation in significant and under- studied ways Grand sociological theories can lead to testable hypotheses and new insights about transportation1 McCreery forthcoming in Environment and Planning A
  21. 21. Recommendations for Practice Comprehensive planning can achieve real results, especially with enforceable plans Multi-pronged sustainability efforts are worth pursuing:  well-chosen investments in a strong, green economy might have indirect transportation benefits Influenceof planning plus higher incomes is dramatically larger than the effects of demographic and other factors that are beyond the influence of planners
  22. 22. Acknowledgements Funding & ResourcesOhio State University Dept. of SociologyOhio State University Environmental ScienceGraduate ProgramThe Fay Graduate Fellowship Fund in EnvironmentalSciences Colleagues Dr. J. Craig Jenkins Dr. Ed Malecki Dr. Maria Conroy Department of SOCIOLOG
  23. 23. References Boschken H.L. 2003. “Global Cities, Systemic Power, and Upper-Middle-Class Influence.” Urban Affairs Review 38(6): 808-830. Cervero, R. 2002. “Built environments and mode choice: toward a normative framework.” Transportation Research Part D- Transport and Environment 7(4): 265-284. Cervero, R. 2007. “Transit-Oriented Development’s Ridership Bonus: A Product of Self-Selection and Public Policies” Environment and Planning A 39: 2068-2085. Clark, T.N. and R. Harvey. 2010. “Urban Politics” pp. 423-440 in: Kevin T. Leicht and J. Craig Jenkins, eds. Handbook of Politics: State and Society in Global Perspective New York: Springer. DeLeon, R.E. and K.C. Naff. 2004. “Identity Politics and Local Political Culture: Some Comparative Results from the Social Capital Benchmark Survey” Urban Affairs Review 39(6): 689-719. Ewing, R, and R. Cervero. 2010. “Travel and the Built Environment: A Meta-Analysis” Journal of the American Planning Association 76(3): 265-294. Filion, P. and K. McSpurren. 2007. “Smart Growth and Development Reality: The Difficult Co- ordination of Land Use and Transport Objectives” Urban Studies 44(3): 501-523. Handy, S., L. Weston, and P. Mokhtarian. 2005. “Driving by choice or necessity?” Transportation Research Part A- Policy and Practice 39(2-3): 185-203. Lee, B., P. Gordon, H.W. Richardson, and J.E. Moore II. 2009. “Commuting Trends in U.S. Cities in the 1990s” Journal of Planning Education and Research 29(1): 78-89. McCreery, A.C. Forthcoming. “Transportation Ecoefficiency: Quantitative Measurement of Urban Transportation Systems with Readily Available Data.” Environment and Planning A. Naess P. 2006. “Accessibility, activity participation and location of activities: Exploring the links between residential location and travel behaviour” Urban Studies 43(3): 627-652. Quinn, B. 2006. “Transit-Oriented Development: Lessons from California” Built Environment 32(3): 311-322. Yin, M., and J. Sun. 2007. "The Impacts of State Growth Management Programs on Urban Sprawl in the 1990s" Journal of Urban Affairs 29(2): 149-179.
  24. 24. Mapping TE Scores (2000 data)

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