Results

The correlations of the monthly rent with objective land use characteristics at the TAZ level were examined. As shown in Table 3, most of these characteristics are significantly associated with the rent, except the three measurements of employment density. These associations reveal that apartments located in highly-accessible, dense areas tend to have lower rents than those in the areas with a low level of accessibility and density; the rent of apartments tends to increase as vehicular travel time to CBD increases. Generally, these associations seem to be counterintuitive due to the commonly-believed premium for high accessibility. On the other hand, these associations may represent spurious relationships. For example, accessibility may act as a proxy for such attributes as space: the farther an apartment is from the CBD, the more spacious it is, and the more expensive. Apartments within specific distances (1/8, 1/4, 1/2 mile, respectively) of bus routes tend to have lower rents than those away from transit facilities; and the closer apartments are to bus routes, the stronger the association is. Therefore, it seems that proximity to bus routes has a negative impact on apartment rent.

In addition, the lease rate is significantly correlated with various perceived measures of the apartment and neighborhood (Table 3). In general, the findings are consistent with the research expectations. Note the age of the apartment (relatively new living unit) has the largest correlation with the rent. Easy access to an interstate highway has a positive association with the rent, but easy access to public transit is negatively associated with the rent. Thus, the influence of both objective and perceived measures of public transit point to a negative impact of bus transit on the lease rate of apartments.

The ordinary least squares (OLS) technique was used to determine hedonic value of transit accessibility, controlling for other factors. Potential explanatory variables were entered into the model in groups, starting with apartment attributes reported by respondents, followed by objective land use characteristics measured at the TAZ level, then characteristics of the current apartment and neighborhood perceived by respondents. At each step, insignificant variables were dropped, and the model was re-estimated before the next set of variables was entered. Variation inflation factor was used to test multicollinearity among explanatory variables. This statistic is smaller than 2 for all variables significant in the final model. Therefore, the multicollinearity is not a concern.

Table 4 presents the hedonic price model for the apartment. The adjusted R-square for the model is 0.740, indicating a reasonable goodness-of-fit compared to other hedonic models. A comparison of standardized coefficients shows that location and neighborhood attributes of an apartment tend to have a smaller impact on apartment rent than does its structure attributes.

Not surprisingly, the numbers of bedrooms and bathrooms are positively associated with the lease rate, with bedrooms having a larger impact. A patio, balcony, deck, or porch adds about $46 to apartment rent, all else equal. Additional appliances provided in an apartment tend to increase the value of the apartment. These appliances not only have the value themselves, but also indicate the luxury nature of the apartment. Amenities offered by the apartment complex also have positive impacts on the lease rate. If the dwellers are responsible for heat (heat is expensive in the winter), the rent is reduced by $63 on average. A newer apartment also tends to have a higher lease rate.

After controlling for these factors, the study finds that some measures of accessibility are associated with apartment rent. Interestingly, the model shows that vehicular travel time to CBD has a negative association with the rent. That is, the rent tends to be higher in areas with higher auto accessibility, all else equal. This result is different from their positive association observed in the correlation analysis, and confirms speculation that auto accessibility may act as a surrogate for other factors. Living on cul-de-sacs has a negative impact on apartment rent. This relationship is reasonable due to the lower accessibility of dead-end streets. It is worth noting that easy access to interstate highways is insignificant in the model, suggesting little location advantage of highway coverage in a small urban area. Apartments located in a TAZ with a higher retail employment density tend to have a lower value than other apartments. This association may result from the noise, traffic, and parking associated with retail businesses. Therefore, although mixed-use neighborhoods can improve the accessibility of residents, an excessive mix may have a negative impact on residential properties.

The model also shows that, on average, apartments located within 1/8 mile of bus routes are $18.41 less expensive than other apartments. This suggests that access to bus transit does not increase the value of apartments adjacent to bus routes. Note that if living within 1/8 mile of bus routes is manually removed from the model, neither living within 1/4 mile of bus routes nor living within 1/2 mile of bus routes is significant in the model. This finding suggests that after controlling for other factors, only properties very close to bus routes tend to have low rents.