Instrumental Regressions

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Note: Here, we briefly summarize results of the first-stage regressions focusing on the effects of our instrumental variables. The results show that the coefficient of distance to major roadways is positively associated with changes in overall job accessibility, but the coefficient of distance to subcenter is negatively associated with the variable. The latter makes sense because as mentioned above, jobs are generally clustered into subcenters for agglomeration economies. However, the former is more complicated to interpret because transportation facilities affect spatial distribution of jobs and households in a various way. One plausible explanation is that suburban areas have different development characteristics as compared to central areas. …show more content…
In general, firms are likely to locate near major roadways, which leads to the positive relationship between major roadways and changes in job accessibility. However, changes in job accessibility are also affected by other factors such as housing supply or household location choice as described in Section 3.1. For example, close to major roadways provides great benefits to firms, thus leads to an increase in job opportunities. And growing jobs attract more households. However, major roadways also can cause negative externalities (i.e. traffic congestion, noise, and pollution) and raise housing prices. In this case, households regard them as a disamenity or struggle to find affordable housings. If the major roadways attract jobs more than households, job accessibility would increase, whereas if the major roadways attract households more than jobs, accessibility would decrease. However, residential preferences are different by income and race as well as dependent on available affordable housings. Accordingly, the effect of major roadways on changes in job accessibility by income and race can be positive, negative, or neutral, and thus it is more related to an empirical

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