From b32f1fc684f42bb48a7e079a95bd526482ca67ae Mon Sep 17 00:00:00 2001
From: OI-nthor <52836091+OI-nthor@users.noreply.github.com>
Date: Wed, 11 Sep 2019 15:34:48 -0400
Subject: [PATCH] Update README.md

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 # Differential-Privacy
 Replication Package for "A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples"
+
+Figures Replication
+
+This folder contains the Stata code to reproduce figures 1 to 3 in “A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples” by Chetty and Friedman (2019).
+
+To run the code, please set the file paths in in the do-file all_figures_paper.do to the files contained in this replication package (tract_covariates.dta and tract_outcomes_early_dta_dp.dta). 
+
+
+Implementation of Noise-Infusion Algorithm: Example Code
+
+The sub-folder example_code_implementation_guide contains two examples of how to implement the noise-infusion algorithm outlined in the Appendix A of “A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples” by Chetty and Friedman (2019). The three files in the sub-folder contain the following:
+
+Example 1 – Simple regression coefficient as statistic of interest
+
+Implementation_guide_simple_reg.do
+
+Stata do-file showing a step-by-step example of how to apply the noise-infusion algorithm to publicly release the estimated coefficients of a simple regression estimate of child income rank on parent income rank in each of the cells of a simulated dataset.
+
+Example 2 – Predicted value of Y at a certain value of X as statistic of interest
+
+Implementation_guide_p_25_prediction.do
+
+Stata do-file showing a step-by-step example of how to apply the noise-infusion algorithm to publicly release the predicted value of child income rank at the 25th percentile of the parental income distribution in each of the cells of a simulated dataset.
+
+Dataset
+
+private_data_by_cells.dta
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+Simulated dataset in Stata format containing information on child income rank and parent income rank of 10,000 fictitious individuals grouped in 111 cells.Variable names: parent_rank, kid_rank, cell.