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A platform for research: civil engineering, architecture and urbanism
Spatial unconditional quantile regression: application to Japanese parking price data
https://orcid.org/0000-0002-5392-7745
Abstract The present study develops a spatial unconditional quantile regression by extending Firpo et al.’s (Econometrica 77:953–973, 2009) unconditional quantile regression and empirically investigates the determinants of parking prices at different quantiles of prices in Japan. The empirical results suggest that spatial competition in terms of unit price and the unit time play important roles in determining parking prices. On the contrary, price is unaffected by demand, approximated by adopting several employment density variables and aggregated people flow data obtained from cell phones. Besides, significant differences exist among the factors that affect parking prices during the day and at night as well as among the unconditional quantiles.
Spatial unconditional quantile regression: application to Japanese parking price data
https://orcid.org/0000-0002-5392-7745
Abstract The present study develops a spatial unconditional quantile regression by extending Firpo et al.’s (Econometrica 77:953–973, 2009) unconditional quantile regression and empirically investigates the determinants of parking prices at different quantiles of prices in Japan. The empirical results suggest that spatial competition in terms of unit price and the unit time play important roles in determining parking prices. On the contrary, price is unaffected by demand, approximated by adopting several employment density variables and aggregated people flow data obtained from cell phones. Besides, significant differences exist among the factors that affect parking prices during the day and at night as well as among the unconditional quantiles.
Spatial unconditional quantile regression: application to Japanese parking price data
https://orcid.org/0000-0002-5392-7745
Abstract The present study develops a spatial unconditional quantile regression by extending Firpo et al.’s (Econometrica 77:953–973, 2009) unconditional quantile regression and empirically investigates the determinants of parking prices at different quantiles of prices in Japan. The empirical results suggest that spatial competition in terms of unit price and the unit time play important roles in determining parking prices. On the contrary, price is unaffected by demand, approximated by adopting several employment density variables and aggregated people flow data obtained from cell phones. Besides, significant differences exist among the factors that affect parking prices during the day and at night as well as among the unconditional quantiles.
Spatial unconditional quantile regression: application to Japanese parking price data
Seya, Hajime (author) / Axhausen, Kay W. (author) / Chikaraishi, Makoto (author)
2020
Article (Journal)
Electronic Resource
English
BKL:
83.64$jRegionalwirtschaft
/
74.12
Stadtgeographie, Siedlungsgeographie
/
38.00$jGeowissenschaften: Allgemeines
/
38.00
Geowissenschaften: Allgemeines
/
83.64
Regionalwirtschaft
/
74.12$jStadtgeographie$jSiedlungsgeographie
RVK:
ELIB39
/
ELIB18
/
ELIB45
Local classification FBW:
oek 4450
Spatial unconditional quantile regression: application to Japanese parking price data
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