The program codes to produce the result in SSQ artcle, "Estimating the Willingness to Pay for Voting when Absentee Voting is not Allowed."
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Python: 3.6 python packages:
- numpy: 1.14.3
- pandas: 0.23.0
- matplotlib: 2.2.2
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Stata: SE 13
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counterfactual_total_price_change.py: calculate the counterfactual market share when the prices of all transportation modes change.
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counterfactual_absentee_voting.py: calculate the counterfactual market share when absentee voting is allowed.
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counterfactual_no_HSR.py: calculates the counterfactual market share when High Speed Rail (HSR) does not exist.
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BLP_market_share.py: a script to calculate predicted market share.
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progress.py: a script to show progress bar by Vladimir Ignatev.
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adj_census_pop_T.csv: the population data based on the 2010 Population Census conducted by the Ministry of the Interior.
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RawData20180515.csv: the data required for BLP model.