The Impact of Local Taxes and Public Services on Property Values
(2019) In Sveriges Riksbank Working Paper Series- Abstract
- Attempts to measure the capitalization of local taxes into property prices, starting with Oates (1969), have suffered from a lack of local public service controls. We revisit this vast literature with a novel dataset of 947 time-varying local characteristic and public service controls for all municipalities in Sweden over the 2010-2016 period. To make use of the high dimensional vector of controls, as well as time and geographic fixed effects, we employ a novel empirical approach that modifies the recently-introduced debiased machine learning estimator by coupling it with a deep-wide neural network. We find that existing estimates of tax capitalization in the literature, including quasi-experimental work, may understate the impact of... (More)
- Attempts to measure the capitalization of local taxes into property prices, starting with Oates (1969), have suffered from a lack of local public service controls. We revisit this vast literature with a novel dataset of 947 time-varying local characteristic and public service controls for all municipalities in Sweden over the 2010-2016 period. To make use of the high dimensional vector of controls, as well as time and geographic fixed effects, we employ a novel empirical approach that modifies the recently-introduced debiased machine learning estimator by coupling it with a deep-wide neural network. We find that existing estimates of tax capitalization in the literature, including quasi-experimental work, may understate the impact of taxes on house prices by as much as 50%. We also exploit the unique features of our dataset to test core assumptions of the Tiebout hypothesis and to estimate the impact of public services, education, and crime on house prices.
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Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/f4aaabc7-953d-4bfe-bcbf-7f2b52d2aa50
- author
- Grodecka, Anna LU and Hull, Isaiah
- organization
- publishing date
- 2019-05-02
- type
- Working paper/Preprint
- publication status
- published
- subject
- keywords
- Local Public Goods, Tax Capitalization, Tiebout Hypothesis, Machine Learning, Property Prices
- in
- Sveriges Riksbank Working Paper Series
- issue
- 374
- pages
- 40 pages
- publisher
- Sveriges Riksbank
- language
- English
- LU publication?
- yes
- id
- f4aaabc7-953d-4bfe-bcbf-7f2b52d2aa50
- alternative location
- https://www.riksbank.se/globalassets/media/rapporter/working-papers/2019/wp374.pdf
- date added to LUP
- 2019-05-02 11:50:24
- date last changed
- 2019-05-02 13:03:34
@misc{f4aaabc7-953d-4bfe-bcbf-7f2b52d2aa50, abstract = {{Attempts to measure the capitalization of local taxes into property prices, starting with Oates (1969), have suffered from a lack of local public service controls. We revisit this vast literature with a novel dataset of 947 time-varying local characteristic and public service controls for all municipalities in Sweden over the 2010-2016 period. To make use of the high dimensional vector of controls, as well as time and geographic fixed effects, we employ a novel empirical approach that modifies the recently-introduced debiased machine learning estimator by coupling it with a deep-wide neural network. We find that existing estimates of tax capitalization in the literature, including quasi-experimental work, may understate the impact of taxes on house prices by as much as 50%. We also exploit the unique features of our dataset to test core assumptions of the Tiebout hypothesis and to estimate the impact of public services, education, and crime on house prices.<br/>}}, author = {{Grodecka, Anna and Hull, Isaiah}}, keywords = {{Local Public Goods; Tax Capitalization; Tiebout Hypothesis; Machine Learning; Property Prices}}, language = {{eng}}, month = {{05}}, note = {{Working Paper}}, number = {{374}}, publisher = {{Sveriges Riksbank}}, series = {{Sveriges Riksbank Working Paper Series}}, title = {{The Impact of Local Taxes and Public Services on Property Values}}, url = {{https://www.riksbank.se/globalassets/media/rapporter/working-papers/2019/wp374.pdf}}, year = {{2019}}, }