SSQ_Election

The program codes to produce the result in SSQ artcle, "Estimating the Willingness to Pay for Voting when Absentee Voting is not Allowed."

A. Program Version

1. Python: 3.6 python packages:

   • numpy: 1.14.3
   • pandas: 0.23.0
   • matplotlib: 2.2.2

2. Stata: SE 13

B. The program files:

1. counterfactual_total_price_change.py: calculate the counterfactual market share when the prices of all transportation modes change.

2. counterfactual_absentee_voting.py: calculate the counterfactual market share when absentee voting is allowed.

3. counterfactual_no_HSR.py: calculates the counterfactual market share when High Speed Rail (HSR) does not exist.

4. BLP_market_share.py: a script to calculate predicted market share.

5. progress.py: a script to show progress bar by Vladimir Ignatev.

C. Data files:

1. adj_census_pop_T.csv: the population data based on the 2010 Population Census conducted by the Ministry of the Interior.

2. RawData20180515.csv: the data required for BLP model.