{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "# Python: Potential Quantiles and Quantile Treatment Effects\n", "In this example, we illustrate how the [DoubleML](https://docs.doubleml.org/stable/index.html) package can be used to estimate (local) potential quantiles and (local) quantile treatment effects. The estimation is based on [Kallus et al. (2019)](https://arxiv.org/abs/1912.12945)." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Potential Quantiles (PQs)\n", "\n", "At first, we will start with the estimation of the quantiles of the potential outcomes." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "### Data\n", "We define a data generating process to create synthetic data to compare the estimates to the true effect." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import doubleml as dml\n", "import multiprocessing\n", "\n", "from lightgbm import LGBMClassifier" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "The data is generated as a location-scale model with\n", "\n", "$$Y_i = \\text{loc}(D_i,X_i) + \\text{scale}(D_i,X_i)\\cdot\\varepsilon_i,$$\n", "\n", "where $X_i\\sim\\mathcal{U}[-1,1]^{p}$ and $\\varepsilon_i \\sim \\mathcal{N}(0,1)$.\n", "Further, the location and scale are determined according to the following functions\n", "\n", "\\begin{aligned}\n", "\\text{loc}(d,x) &:= 0.5d + 2dx_5 + 2\\cdot 1\\{x_2 > 0.1\\} - 1.7\\cdot 1\\{x_1x_3 > 0\\} - 3x_4 \\\\\n", "\\text{scale}(d,x) &:= \\sqrt{0.5d + 0.3dx_1 + 2},\n", "\\end{aligned}\n", "\n", "and the treatment takes the following form\n", "\n", "$$D_i = 1_{\\{(X_2 - X_4 + 1.5\\cdot 1\\{x_1 > 0\\} + \\epsilon_i > 0)\\}}$$\n", "\n", "with $\\epsilon_i \\sim \\mathcal{N}(0,1)$.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def f_loc(D, X):\n", " loc = 0.5*D + 2*D*X[:,4] + 2.0*(X[:,1] > 0.1) - 1.7*(X[:,0] * X[:,2] > 0) - 3*X[:,3]\n", " return loc\n", "\n", "def f_scale(D, X):\n", " scale = np.sqrt(0.5*D + 0.3*D*X[:,1] + 2)\n", " return scale\n", "\n", "def dgp(n=200, p=5):\n", " X = np.random.uniform(-1,1,size=[n,p])\n", " D = ((X[:,1 ] - X[:,3] + 1.5*(X[:,0] > 0) + np.random.normal(size=n)) > 0)*1.0\n", " epsilon = np.random.normal(size=n)\n", "\n", " Y = f_loc(D, X) + f_scale(D, X)*epsilon\n", "\n", " return Y, X, D, epsilon" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "We can calculate the true potential quantile analytically or through simulations. Here, we will just approximate the true potential quantile for a range of quantiles." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Potential Quantile Y(0): [-3.33014346 -2.71465114 -2.21155656 -1.77348822 -1.37436439 -1.00000591\n", " -0.64197957 -0.29548121 0.04653976 0.38866808 0.73608412 1.09347419\n", " 1.46811985 1.8685788 2.30982972 2.81568484 3.43597565]\n", "Potential Quantile Y(1): [-3.23789633 -2.53947541 -1.97276281 -1.48208358 -1.03698487 -0.62131806\n", " -0.22522221 0.15891559 0.53724023 0.91724807 1.30361321 1.7018663\n", " 2.12046836 2.56965663 3.06724028 3.64154727 4.35341202]\n" ] } ], "source": [ "tau_vec = np.arange(0.1,0.95,0.05)\n", "n_true = int(10e+6)\n", "\n", "_, X_true, _, epsilon_true = dgp(n=n_true)\n", "D1 = np.ones(n_true)\n", "D0 = np.zeros(n_true)\n", "\n", "Y1 = f_loc(D1, X_true) + f_scale(D1, X_true)*epsilon_true\n", "Y0 = f_loc(D0, X_true) + f_scale(D0, X_true)*epsilon_true\n", "\n", "Y1_quant = np.quantile(Y1, q=tau_vec)\n", "Y0_quant = np.quantile(Y0, q=tau_vec)\n", "\n", "print(f'Potential Quantile Y(0): {Y0_quant}')\n", "print(f'Potential Quantile Y(1): {Y1_quant}')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "Let us generate $n=5000$ observations and convert them to a [DoubleMLData](https://docs.doubleml.org/stable/api/generated/doubleml.DoubleMLData.html) object." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "n = 5000\n", "np.random.seed(42)\n", "Y, X, D, _ = dgp(n=n)\n", "obj_dml_data = dml.DoubleMLData.from_arrays(X, Y, D)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "### Potential Quantile Estimation\n", "Next, we can initialize our two machine learning algorithms to train the different nuisance elements. Then we can initialize the DoubleMLPQ objects and call fit() to estimate the relevant parameters. To obtain confidence intervals, we can use the confint() method." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Quantile: 0.1\n", "Quantile: 0.15000000000000002\n", "Quantile: 0.20000000000000004\n", "Quantile: 0.25000000000000006\n", "Quantile: 0.30000000000000004\n", "Quantile: 0.3500000000000001\n", "Quantile: 0.40000000000000013\n", "Quantile: 0.45000000000000007\n", "Quantile: 0.5000000000000001\n", "Quantile: 0.5500000000000002\n", "Quantile: 0.6000000000000002\n", "Quantile: 0.6500000000000001\n", "Quantile: 0.7000000000000002\n", "Quantile: 0.7500000000000002\n", "Quantile: 0.8000000000000002\n", "Quantile: 0.8500000000000002\n", "Quantile: 0.9000000000000002\n" ] } ], "source": [ "ml_m = LGBMClassifier(n_estimators=300, learning_rate=0.05, num_leaves=10)\n", "ml_g = LGBMClassifier(n_estimators=300, learning_rate=0.05, num_leaves=10)\n", "\n", "PQ_0 = np.full((len(tau_vec)), np.nan)\n", "PQ_1 = np.full((len(tau_vec)), np.nan)\n", "\n", "ci_PQ_0 = np.full((len(tau_vec),2), np.nan)\n", "ci_PQ_1 = np.full((len(tau_vec),2), np.nan)\n", "\n", "for idx_tau, tau in enumerate(tau_vec):\n", " print(f'Quantile: {tau}')\n", " dml_PQ_0 = dml.DoubleMLPQ(obj_dml_data,\n", " ml_g, ml_m,\n", " quantile=tau,\n", " treatment=0,\n", " n_folds=5)\n", " dml_PQ_1 = dml.DoubleMLPQ(obj_dml_data,\n", " ml_g, ml_m,\n", " quantile=tau,\n", " treatment=1,\n", " n_folds=5)\n", "\n", " dml_PQ_0.fit()\n", " dml_PQ_1.fit()\n", "\n", " ci_PQ_0[idx_tau, :] = dml_PQ_0.confint(level=0.95).to_numpy()\n", " ci_PQ_1[idx_tau, :] = dml_PQ_1.confint(level=0.95).to_numpy()\n", "\n", " PQ_0[idx_tau] = dml_PQ_0.coef.squeeze()\n", " PQ_1[idx_tau] = dml_PQ_1.coef.squeeze()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "Finally, let us take a look at the estimated quantiles." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Quantile Y(0) Y(1) DML Y(0) DML Y(1) DML Y(0) lower \\\n", "0 0.10 -3.330143 -3.237896 -3.408565 -3.128312 -3.813293 \n", "1 0.15 -2.714651 -2.539475 -2.855780 -2.495752 -3.245512 \n", "2 0.20 -2.211557 -1.972763 -2.345903 -1.978977 -2.638264 \n", "3 0.25 -1.773488 -1.482084 -1.924002 -1.533900 -2.189737 \n", "4 0.30 -1.374364 -1.036985 -1.482483 -1.148161 -1.683942 \n", "5 0.35 -1.000006 -0.621318 -1.246879 -0.700102 -1.509196 \n", "6 0.40 -0.641980 -0.225222 -0.932973 -0.291406 -1.244455 \n", "7 0.45 -0.295481 0.158916 -0.665264 0.145245 -0.949456 \n", "8 0.50 0.046540 0.537240 -0.077319 0.496551 -0.411582 \n", "9 0.55 0.388668 0.917248 0.378834 0.760104 0.070020 \n", "10 0.60 0.736084 1.303613 0.479928 1.216344 0.168614 \n", "11 0.65 1.093474 1.701866 1.059384 1.655284 0.677614 \n", "12 0.70 1.468120 2.120468 1.544097 2.036147 1.215342 \n", "13 0.75 1.868579 2.569657 1.700015 2.493219 1.400823 \n", "14 0.80 2.309830 3.067240 2.187690 2.988463 1.872768 \n", "15 0.85 2.815685 3.641547 2.631333 3.542647 2.226524 \n", "16 0.90 3.435976 4.353412 3.113207 4.243246 2.753523 \n", "\n", " DML Y(0) upper DML Y(1) lower DML Y(1) upper \n", "0 -3.003836 -3.448745 -2.807879 \n", "1 -2.466047 -2.687345 -2.304159 \n", "2 -2.053541 -2.177496 -1.780458 \n", "3 -1.658267 -1.684502 -1.383297 \n", "4 -1.281024 -1.319759 -0.976562 \n", "5 -0.984562 -0.844707 -0.555498 \n", "6 -0.621490 -0.428255 -0.154557 \n", "7 -0.381072 0.015698 0.274793 \n", "8 0.256944 0.367625 0.625477 \n", "9 0.687647 0.627560 0.892648 \n", "10 0.791241 1.088048 1.344640 \n", "11 1.441153 1.524657 1.785911 \n", "12 1.872852 1.907115 2.165178 \n", "13 1.999207 2.360004 2.626433 \n", "14 2.502612 2.857161 3.119766 \n", "15 3.036143 3.408539 3.676756 \n", "16 3.472891 4.098712 4.387780 \n" ] } ], "source": [ "data = {\"Quantile\": tau_vec, \"Y(0)\": Y0_quant, \"Y(1)\": Y1_quant,\n", " \"DML Y(0)\": PQ_0, \"DML Y(1)\": PQ_1,\n", " \"DML Y(0) lower\": ci_PQ_0[:, 0], \"DML Y(0) upper\": ci_PQ_0[:, 1],\n", " \"DML Y(1) lower\": ci_PQ_1[:, 0], \"DML Y(1) upper\": ci_PQ_1[:, 1]}\n", "df = pd.DataFrame(data)\n", "print(df)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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", 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