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Chptr6.Pdf (813.5Kb) Chapter 6 Results of the Analysis of Household Travel Time In this section the results of the models that estimated household travel time are set out and discussed. The consistency of the results with expectations are discussed for each variable. The dependent variable in each model that estimated household travel time was the log of household travel time. Since the log specification complicates interpretation of the results, for each significant regressor a linear approximation of the change in household travel time attributable to a change in the regressor is calculated based on the estimated parameters holding all other regressors constant at their respective means. In the case of the two variables, access to the central business district and access to the nearest subcenter, the change is based upon adding fifteen minutes to the time to access the center. For all other continuous variables the change is based on an increase of one standard deviation from the mean. For discrete variables, it is based on an increase of one unit from the mean. For dummy variables the change is based on the difference between a zero and a one for the dummy condition. Models without Neighborhood Characteristics Complete results for the models that exclude any neighborhood variables, including calculations of changes in travel times, appear in Table 6.1. The discussion will begin with the variables that measure accessibility of centers as these are the focus of this research. The results for all three models and their relationships to each other will be discussed prior to considering the results for the other variables. The discussion will then proceed to the household characteristics variables, following the same process. The results for each variable will be discussed for all three models, as well as their differences and their similarities, prior to considering the next variable. Chapter 6-1 Table 6.1 Models without neighborhood effects Model City Suburbs Outlying Area Variable Parameter Time change Parameter Time change Parameter Time change Estimate (hours) Estimate (hours) Estimate (hours) Intercept -0.372* -0.965* 0.565* (.184) (.289) (.239) Time/distance variables (time change from a move that increases travel time to the central business district or nearest subcenter by 15 minutes) Travel time to 0.792* 0.243 1.581* -0.094 -0.739* -0.393 the CBD (.421) (.806) (.149) Travel time to -1.144* the CBD (.558) squared Travel time to -0.391 -0.360 0.356* 0.193 -0.039 -0.023 the nearest (.402) (.089) (.116) subcenter Dummy Variables (time change from change in the dummy condition) Household 0.033 0.064 -0.261* -0.495 -0.448* -0.908 income less (.354) (.108) (.128) than $10,000 Household -0.098 -0.177 -0.219* -0.424 -0.308* -0.667 income of (.094) (.075) (.113) $10,000- 20,000 Household -0.050 -0.093 -0.100* -0.205 -0.219* -0.495 income of (.088) (.056) (.078) $20,000- 30,000 Household -0.096** -0.174 -0.103* -0.212 -0.090** -0.216 income of (070) (.038) (.055) $30,000- 50,000 Household -0.124** -0.221 0.012 0.026 0.094* 0.247 income of .089) (.035) (.056) $75,000- 100,000 Household 0.049 0.095 0.029 0.064 -0.014 -0.035 income of (.095) (.049) (.093) $100,000- 125,000 Household -0.160* -0.281 0.073** 0.164 -0.196 -0.448 income of (.088) (.053) (.179) more than $125,000 Townhouse -0.010 -0.019 0.020 0.041 -0.092** -0.210 Chapter 6-2 (.064) (.035) (.064) Apartment -0.082 -0.147 -0.012 -0.025 -0.095 -0.216 (.074) (.047) (.102) Owner 0.034 0.060 0.104* 0.209 0.199** 0.434 (.062) (.039) (.070) Moved to 0.061 0.108 0.037 0.076 0.161* 0.357 present (.059) (.035) (.062) residence between 1980 and 1990 Moved to 0.085** 0.151 0.057** 0.118 0.178* 0.397 present (.060) (.039) (.066) residence after 1990 Discrete Variables (time change from an increase of one from the mean) Number of -0.020 -0.001 0.053* 0.111 0.056* 0.135 children (.050) (.019) (.021) Number of 0.411* 0.766 0.451* 1.176 0.351* 0.981 working adults (.055) (.042) (.072) Number of 0.266* 0.284 0.220* 0.507 0.094** 0.229 nonworking (.045) (.039) (.067) adults Number of 0.043 0.079 0.075* 0.161 0.179* 0.458 licensed drivers (.049) (.042) (.073) Number of 0.062** 0.114 0.056* 0.118 0.043* 0.103 vehicles (.040) (.020) (.026) Continuous Variables (time change from an increase of one standard deviation from the mean) Percent of 0.403* 0.254 0.484* 0.202 1.417* 0.188 household trips (.082) (.064) (.219) by transit Observations 7111937957 Mean Square .365 .336 .416 Error Durbin Watson 1.976 2.07 1.99 F-Statistic 11.860 54.42 29.06 Significance .000 .000 .000 R2 .256 .374 .383 Asymptotic standard deviations in parentheses * significant at =.05 ** significant at =.10 Chapter 6-3 Center Accessibility The City Model In the city model, which includes only observations from the City of Washington, the parameter estimate on access to the central business district is significant and positive. The simple linear calculation suggests that the choice of a housing location that adds one- quarter hour to the central business district access over the mean will increase total household travel time by slightly less than one-quarter hour, holding all other variables constant at their means. This simple calculation, however, is not very revealing since it is a linear estimation of only a short segment of the curve suggested by the parameter estimate. While the linear approximation is helpful for understanding the influence of access to the central business district on household travel time the nonlinear relationship between household travel time and access to the central business district clouds any interpretation of the result. A more complete representation of the relationship is a graph of household travel time as a function of access to the central business district holding all other variables constant at their means. Such a graph appears as Figure 6A below. Chapter 6-4 Household Travel Time (in hours) (in Time Travel Household Time to access to the central business district (in hours) Figure 6A. Household travel time as a function of access to the central business district for the city model without neighborhood characteristics Close examination reveals an almost one to one relationship between access to the central business district and total household travel. If an extreme, literal interpretation of the monocentric model is taken, one would expect a substantially larger coefficient. The model assumes that jobs, goods and services are densely concentrated at the center. At a minimum, each household could be expected to have one person that accesses the center every day. Doing so would entail adding twice the increase in the time to access the center to household travel time. More liberal (and realistic) interpretations of the central place theory assume economic activity is spread in and around the center with the greatest density at the center. Adopting this interpretation, the model’s predicted household travel times appear more reasonable, as households with less access to the center may be predicted to obtain the goods and services that they desire at locations that are outside the center. Chapter 6-5 The parameter estimate for access to the nearest subcenter in the city model was not significant. This result is not surprising since city residents have relatively easy access to the central business district. The central business district is the largest, most diverse concentration of economic activity. One would expect subcenters to have little or no influence on city residents as they have all of the commercial and cultural benefits of the central business district closer at hand. Therefore, the insignificant estimate on access to the nearest subcenter found in the city model is not surprising. This finding also does not imply that the metropolitan area as a whole is not polycentric. Polycentricity is a phenomenon that has occurred, in part, for the benefit of suburban residents. The only benefit that city residents should be expected to realize from polycentricity is an indirect side effect, the reduction of congestion in and around the city center. Consequently, the city model’s finding with respect to access to the nearest subcenter is inconsequential. Before turning to the suburban model two aspects of the metropolitan model are worth pointing out. First, the mean daily travel time for households in the city sample is the lowest of the three models, approximately one quarter hour less than that of households in the suburban sample and over one half hour less than that of households in the outlying areas model. Second, locating in or close to the central business district minimizes household travel times. These two factors alone suggest a household travel times are increasing as access to the central business district declines as purported by the monocentric and limited polycentric models. The results of this model alone are an incomplete representation of the influence of access to centers on household travel time, as the model only covers a small portion of the metropolitan area. The results, however, are important to understanding the area as a whole.1 The Suburban Model Unlike the city model, misspecification testing of the suburban model suggested the need to include the square of access to the central business district. In this model both linear and squared measures of access to the central business district, as well as the measure of 1 Recall that the variation in the influence of center access across the metropolitan area, shown by the tests of parameter stability, prevented using an econometric model that included the metropolitan area in its entirety.
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