The all_data_reduced file is a tab-delimited data file containing a subset of the subject decisions and responses from Study 1 of the paper ÒSequential Search and Learning from Rank Feedback: Theory and Experimental EvidenceÓ by Asa B. Palley and Mirko Kremer to appear in Management Science (2014). Specifically, this reduced data file contains exactly one row for each of the 50 (+2 practice for a total of 52) trials (a ÒtrialÓ is a set of 20 apartments that the subject could consider within one search) for every subject who participated in Study 1 (121 subjects x 52 trials per subject = 6292 total rows).

The variables in the file are as follows (note we use the words ÔoptionÕ and ÔapartmentÕ interchangeably here as they denote the same thing):

treatment: Indicates the treatment the subject was assigned to within Study 1 of the paper. Treatment 1 is the search condition with no discounting and full information, treatment 2 is the search condition with no discounting and partial information, treatment 3 is the search condition with a discount rate of 10% and full information, and treatment 4 is the search condition with a discount rate of 10% and partial information.
gsid: A unique subject identifier.
trial: Indicates which of the 50 trials the subject was playing. Trials were indexed as t=1...T (T=50 for Study 1), with trials -1 and 0 indicating the 2 initial Òpractice rounds.Ó Note that for four subjects (22-25) in our sample, the data from the last round (i.e., trial 50) is missing, due to a software issue.
stop_observed: The index (a number from 1 to 20) of the apartment that the subject selected in that trial (where they stopped and ended their search). 
stop_optimal: The index (a number from 1 to 20) of the apartment that a decision maker following the optimal policy throughout that trial would have selected in that trial (where they would have stopped and ended their search). 
payoff_observed: The value of the apartment (between 0 and 20) that the subject selected in that trial (where they stopped and ended their search). 
payoff_optimal: The value of the apartment (between 0 and 20) that a decision maker following the optimal policy throughout that trial would have selected in that trial (where they would have stopped and ended their search). 

