Transportation Ecoefficiency and Economic Structure: Six case studies of occupational patterns and public transit

Transportation Ecoefficiency and

Economic Structure

Six case studies of occupational patterns and

public transit

Anna C. McCreery

Ohio State University

Rich Quodomine

NY Department of Transportation

Association of American Geographers’ annual meeting, Tampa, FL, 8 April 2014

Transportation Ecoefficiency

� Environmental impact of transportation, per unit of travel

� Measured by proxy as the index of:� Population density

� % of commuters driving to work alone (sign reversed)

� % of commuters taking public transit

� % of commuters walking or bicycling

McCreery, A.C. 2013. “Transportation Ecoefficiency: Quantitative Measurement of Urban Transportation Systems with Readily Available Data” Environment and Planning A 45(8): 1995-2011.

Measuring TE: Pop. Density

� Proxy for travel distance

� Associated with other built environment features that affect travel

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

� Different commute modes have vastly different environmental impacts:� Driving alone is very eco-inefficient

� Public transit, walking, and cycling are generally more ecoefficient modes

Economic Structure and TE

� Industrial shift - is the transition from “rustbelt” to stronger post-industrial associated with changes in TE?


� Does the creative class create transit-friendly neighborhoods?


� Do “Eds and Meds” encourage healthier transportation?

Predicting TE: ColumbusVariable Beta

% of workers in the Construction industry -0.130***

% in the Manufacturing industry -0.126***

% in Finance, insurance, real estate, rental industries -0.093**

% in Education, health care, social assistance industries 0.091*

% in Management, business, science, arts occupations -0.156*

% of population under 18 years old -0.165***

% of adults below the poverty level 0.711***

% of population over age 25 with a bachelor's degree 0.251***

% female -0.071*

a p<0.1, * p<0.05, ** p<0.01, *** p<0.001

N=431 R2 = 0.767

Predicting TE: ClevelandVariable Beta

% of workers in the Construction industry -0.088**

% in Finance, insurance, real estate, rental industries 0.090*

% in Education, health care, social assistance industries 0.167***

% in Arts, entertainment, recreation, accommodation and food service industries

0.141***

% in Other services industries 0.154**

% of the population under 18 years old -0.109**

Per capita income, in 2012 inflation-adjusted $ -0.115*


% of population over age 25 with a bachelor's degree 0.173***

% unemployed 0.123*

a p<0.1, * p<0.05, ** p<0.01, *** p<0.001

N=632 R2 = 0.665

Predicting TE: Pittsburgh

a p<0.1, * p<0.05, ** p<0.01, *** p<0.001 N=702 R2 = 0.739

Variable Beta

% of workers in the Manufacturing industry -0.074*

% in the Information industry 0.099***

% in Finance, insurance, real estate, rental industries 0.204***

% in Professional, scientific, management, administrative, waste management industries

0.125***

% in Education, health care, social assistance industries 0.321***

% in Arts, entertainment, recreation, accommodation and food service industries

0.197***

% in Other services industries 0.060*

% in Management, business, science, arts occupations 0.145**

% of the population under 18 years old -0.100***

Per capita income, in 2012 inflation-adjusted $ -0.142**


% Private wage and salary workers 0.040a

Columbus, OH TE Scores

Columbus, OHEds and Meds

Cleveland, OHTE Scores

Cleveland, OHEds and Meds

Pittsburgh, PATE Scores

Pittsburgh, PAEds and Meds

Eds and Meds

A look at Buffalo Occupations as a TE Explainer

� Buffalo = “Classic Rust Belt City”

� Marked by:� Significant population decline:

� 560,000 [1950 pop] to 265,000 [2010 pop]

� Significant suburbanization

� Industrial patterns change: not only do they leave the city, the occupations change from industrial type to medical

� Eds and Meds take over core wealth generation

Buffalo Occupational Shift and Transit Modal Choice

•Poverty in Blue Areas•Wealthier areas in pale yellow / brown•Medical management represented as red dots, yellow with medical service occupations•Correlated with wealthier districts and less available transit

Baltimore

� Previously declining industrial city, recently re-strengthened through downtown core development

� Emphasis on Eds and Meds sector: Johns Hopkins, UMBC and Towson St

� Maryland Institute College of Arts

� Innovation from 1990s: Buy a house for extremely little, but one must improve it and own for a minimum of 5 years

Baltimore by Creative Class

� http://bit.ly/1kEmW0o

� Still classic ring city issues

� However, core concentrated downtown redevelopment with Eds and Meds, plus adding high-end entertainment (Football, Baseball, a first-rate aquarium) anchor the high-income producer

Cautionary tale: Boston

� Boston is a city that� Is traditionally centered around Eds, Meds and

finance

� Has extensive, well-known transit system

� Has an established national and international tourism base that did not need to be re-developed

� Has a very diverse economy and as Eds and Meds has driven growth since 1975, the basis for growth has stayed intact

� Transit System has generally expanded to meet demands of local populace, including current westward development

� End Result: Boston isn’t a very good study

Conclusions

� Transportation Ecoefficiency and resultant Analytics with Occupations, particularly in shifting economies, can show where demand for “greener transport” is increasing… and perhaps even more importantly, what occupations it may favor

� It is important to establish these “deeper analytics” so that planners and policymakers can develop transportation policy in line with economic growth

Contact Information

Anna McCreery, [email protected]

Richard D. Quodomine, MA, AAGTwitter: @[email protected]

Science

Transportation Ecoefficiency and Economic Structure: Six case studies of occupational patterns and public transit