Browsing by Subject "Regression model"

Now showing 1 - 3 of 3
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    Modeling the land-use correlates of vehicle-trip lengths for assessing the transportation impacts of land developments
    (Journal of Transport and Land Use, 2013) Srinivasan, Sivaramakrishnan; Provost, Russell; Steiner, Ruth
    This study developed models that relate trip lengths to the land-use characteristics at the trip ends (both production and attraction ends). Separate models were developed by trip purpose. The results indicate several statistically significant and intuitively reasonable effects of land-use patterns. High residential densities and a good mix of complementary land uses are associated with shorter trips. Larger establishments attract longer trips, and the lengths of home-based other trips decrease with an increase in the number of convenient commercial land- use parcels in the neighborhood. The connectivity provided by the roadway network and the urban form of the area (measured in terms of number of intersections and cul-de-sacs) affect trip lengths. In addition to the local land-use characteristics, trip lengths also vary significantly by the location of the neighborhood within the region. All these results hold even after controlling for several trip and traveler characteristics. The models have been implemented in a spreadsheet program for use in assessing the transportation impacts of new land developments.
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    The Relationship Between Income Growth and Uninsured Rate
    (2017) Lu, Sirui
    Using data collected from the United States Census Bureau from 50 states spanning the years 2008 to 2015, I examine the relationship between uninsured rate and income growth. I use fixed effect model to do regression model to find that the lower uninsured rate, the higher income growth rate.
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    Semiparametric Two Stage Estimation of Sample Selection Models Subject to Tobit-Type Selection Rules
    (Center for Economic Research, Department of Economics, University of Minnesota, 1990-07) Lee, Lung-Fei
    A semiparametric two stage estimation method is proposed for the estimation of sample selection models which are subject to Tobit-type selection rules. With randomization restrictions on the disturbances of the model, all the regression coefficients in the model are in general identifiable without exclusion restrictions. The proposed estimator is shown to be Vn-consistent and asymptotically normal. Some Monte Carlo results to demonstrate its finite sample performance are also provided.