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Estimating demand for automobile ind...
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Qin, Xiaonan.
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Estimating demand for automobile industry in the U.S. market: 2010 - 2013.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Estimating demand for automobile industry in the U.S. market: 2010 - 2013./
作者:
Qin, Xiaonan.
面頁冊數:
37 p.
附註:
Source: Masters Abstracts International, Volume: 54-02.
Contained By:
Masters Abstracts International54-02(E).
標題:
Economics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1571464
ISBN:
9781321424362
Estimating demand for automobile industry in the U.S. market: 2010 - 2013.
Qin, Xiaonan.
Estimating demand for automobile industry in the U.S. market: 2010 - 2013.
- 37 p.
Source: Masters Abstracts International, Volume: 54-02.
Thesis (M.A.)--Northeastern University, 2015.
By applying market-level data on quantities, prices and vehicle characteristics in the year of 2010 and 2013, I conduct an estimation of automobile demand in the U.S. market using the conditional logit and nested logit model. By testing and applying the instruments variables, I address the exogeneity problem of prices and within-group market share. The demand for cars and light trucks are both elastic. The nested logit regression indicates that models within the same group/nest are better substitutes than models across the group. The results imply that consumers prefer the efficient vehicles. However, the electric vehicles and low displacement vehicles are not preferred over high displacement fuel vehicles by consumers.
ISBN: 9781321424362Subjects--Topical Terms:
517137
Economics.
Estimating demand for automobile industry in the U.S. market: 2010 - 2013.
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By applying market-level data on quantities, prices and vehicle characteristics in the year of 2010 and 2013, I conduct an estimation of automobile demand in the U.S. market using the conditional logit and nested logit model. By testing and applying the instruments variables, I address the exogeneity problem of prices and within-group market share. The demand for cars and light trucks are both elastic. The nested logit regression indicates that models within the same group/nest are better substitutes than models across the group. The results imply that consumers prefer the efficient vehicles. However, the electric vehicles and low displacement vehicles are not preferred over high displacement fuel vehicles by consumers.
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