From 09dab71c04dbea085a3ce1ebbdb3a8765c056641 Mon Sep 17 00:00:00 2001 From: Alan Lujan Date: Wed, 13 Nov 2024 09:26:25 -0500 Subject: [PATCH] update ch11 --- ...sues in Using OLS with Time Series Data.md | 230 ++++++++ ...s in Using OLS with Time Series Data.ipynb | 494 ++++++++++++++++++ .../Ch2. The Simple Regression Model.ipynb | 1 + ...sues in Using OLS with Time Series Data.py | 218 ++++++++ 4 files changed, 943 insertions(+) create mode 100644 markdown/Ch11. Further Issues in Using OLS with Time Series Data.md create mode 100644 notebooks/Ch11. Further Issues in Using OLS with Time Series Data.ipynb create mode 100644 scripts/Ch11. Further Issues in Using OLS with Time Series Data.py diff --git a/markdown/Ch11. Further Issues in Using OLS with Time Series Data.md b/markdown/Ch11. Further Issues in Using OLS with Time Series Data.md new file mode 100644 index 0000000..644949f --- /dev/null +++ b/markdown/Ch11. Further Issues in Using OLS with Time Series Data.md @@ -0,0 +1,230 @@ +--- +jupyter: + jupytext: + formats: notebooks//ipynb,markdown//md,scripts//py + text_representation: + extension: .md + format_name: markdown + format_version: '1.3' + jupytext_version: 1.16.4 + kernelspec: + display_name: merino + language: python + name: python3 +--- + +# 11. Further Issues in Using OLS with Time Series Data + +```python +%pip install matplotlib numpy pandas statsmodels wooldridge scipy -q +``` + +```python +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import statsmodels.formula.api as smf +import wooldridge as wool +from scipy import stats +``` + +## 11.1 Asymptotics with Time Seires + +### Example 11.4: Efficient Markets Hypothesis + +```python +nyse = wool.data("nyse") +nyse["ret"] = nyse["return"] + +# add all lags up to order 3: +nyse["ret_lag1"] = nyse["ret"].shift(1) +nyse["ret_lag2"] = nyse["ret"].shift(2) +nyse["ret_lag3"] = nyse["ret"].shift(3) + +# linear regression of model with lags: +reg1 = smf.ols(formula="ret ~ ret_lag1", data=nyse) +reg2 = smf.ols(formula="ret ~ ret_lag1 + ret_lag2", data=nyse) +reg3 = smf.ols(formula="ret ~ ret_lag1 + ret_lag2 + ret_lag3", data=nyse) +results1 = reg1.fit() +results2 = reg2.fit() +results3 = reg3.fit() + +# print regression tables: +table1 = pd.DataFrame( + { + "b": round(results1.params, 4), + "se": round(results1.bse, 4), + "t": round(results1.tvalues, 4), + "pval": round(results1.pvalues, 4), + }, +) +print(f"table1: \n{table1}\n") +``` + +```python +table2 = pd.DataFrame( + { + "b": round(results2.params, 4), + "se": round(results2.bse, 4), + "t": round(results2.tvalues, 4), + "pval": round(results2.pvalues, 4), + }, +) +print(f"table2: \n{table2}\n") +``` + +```python +table3 = pd.DataFrame( + { + "b": round(results3.params, 4), + "se": round(results3.bse, 4), + "t": round(results3.tvalues, 4), + "pval": round(results3.pvalues, 4), + }, +) +print(f"table3: \n{table3}\n") +``` + +## 11.2 The Nature of Highly Persistent Time Series + +```python +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(0, 50, num=51) +plt.ylim([-18, 18]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock: + e = stats.norm.rvs(0, 1, size=51) + + # set first entry to 0 (gives y_0 = 0): + e[0] = 0 + + # random walk as cumulative sum of shocks: + y = np.cumsum(e) + + # add line to graph: + plt.plot(x_range, y, color="lightgrey", linestyle="-") + +plt.axhline(linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") +``` + +```python +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(0, 50, num=51) +plt.ylim([0, 100]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock: + e = stats.norm.rvs(0, 1, size=51) + + # set first entry to 0 (gives y_0 = 0): + e[0] = 0 + + # random walk as cumulative sum of shocks plus drift: + y = np.cumsum(e) + 2 * x_range + + # add line to graph: + plt.plot(x_range, y, color="lightgrey", linestyle="-") + +plt.plot(x_range, 2 * x_range, linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") +``` + +## 11.3 Differences of Highly Persistent Time Series + +```python +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(1, 50, num=50) +plt.ylim([-1, 5]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock and cumulative sum of shocks: + e = stats.norm.rvs(0, 1, size=51) + e[0] = 0 + y = np.cumsum(2 + e) + + # first difference: + Dy = y[1:51] - y[0:50] + + # add line to graph: + plt.plot(x_range, Dy, color="lightgrey", linestyle="-") + +plt.axhline(y=2, linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") +``` + +## 11.4 Regression with First Differences + +### Example 11.6: Fertility Equation + +```python +fertil3 = wool.data("fertil3") +T = len(fertil3) + +# define time series (years only) beginning in 1913: +fertil3.index = pd.date_range(start="1913", periods=T, freq="YE").year + +# compute first differences: +fertil3["gfr_diff1"] = fertil3["gfr"].diff() +fertil3["pe_diff1"] = fertil3["pe"].diff() +print(f"fertil3.head(): \n{fertil3.head()}\n") +``` + +```python +# linear regression of model with first differences: +reg1 = smf.ols(formula="gfr_diff1 ~ pe_diff1", data=fertil3) +results1 = reg1.fit() + +# print regression table: +table1 = pd.DataFrame( + { + "b": round(results1.params, 4), + "se": round(results1.bse, 4), + "t": round(results1.tvalues, 4), + "pval": round(results1.pvalues, 4), + }, +) +print(f"table1: \n{table1}\n") +``` + +```python +# linear regression of model with lagged differences: +fertil3["pe_diff1_lag1"] = fertil3["pe_diff1"].shift(1) +fertil3["pe_diff1_lag2"] = fertil3["pe_diff1"].shift(2) + +reg2 = smf.ols( + formula="gfr_diff1 ~ pe_diff1 + pe_diff1_lag1 + pe_diff1_lag2", + data=fertil3, +) +results2 = reg2.fit() + +# print regression table: +table2 = pd.DataFrame( + { + "b": round(results2.params, 4), + "se": round(results2.bse, 4), + "t": round(results2.tvalues, 4), + "pval": round(results2.pvalues, 4), + }, +) +print(f"table2: \n{table2}\n") +``` diff --git a/notebooks/Ch11. Further Issues in Using OLS with Time Series Data.ipynb b/notebooks/Ch11. Further Issues in Using OLS with Time Series Data.ipynb new file mode 100644 index 0000000..9e08204 --- /dev/null +++ b/notebooks/Ch11. Further Issues in Using OLS with Time Series Data.ipynb @@ -0,0 +1,494 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "325abb7b", + "metadata": {}, + "source": [ + "# 11. Further Issues in Using OLS with Time Series Data" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "adf113d4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install matplotlib numpy pandas statsmodels wooldridge scipy -q" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d5189009", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "import statsmodels.formula.api as smf\n", + "import wooldridge as wool\n", + "from scipy import stats" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 11.1 Asymptotics with Time Seires\n", + "\n", + "### Example 11.4: Efficient Markets Hypothesis" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "table1: \n", + " b se t pval\n", + "Intercept 0.1796 0.0807 2.2248 0.0264\n", + "ret_lag1 0.0589 0.0380 1.5490 0.1218\n", + "\n" + ] + } + ], + "source": [ + "nyse = wool.data(\"nyse\")\n", + "nyse[\"ret\"] = nyse[\"return\"]\n", + "\n", + "# add all lags up to order 3:\n", + "nyse[\"ret_lag1\"] = nyse[\"ret\"].shift(1)\n", + "nyse[\"ret_lag2\"] = nyse[\"ret\"].shift(2)\n", + "nyse[\"ret_lag3\"] = nyse[\"ret\"].shift(3)\n", + "\n", + "# linear regression of model with lags:\n", + "reg1 = smf.ols(formula=\"ret ~ ret_lag1\", data=nyse)\n", + "reg2 = smf.ols(formula=\"ret ~ ret_lag1 + ret_lag2\", data=nyse)\n", + "reg3 = smf.ols(formula=\"ret ~ ret_lag1 + ret_lag2 + ret_lag3\", data=nyse)\n", + "results1 = reg1.fit()\n", + "results2 = reg2.fit()\n", + "results3 = reg3.fit()\n", + "\n", + "# print regression tables:\n", + "table1 = pd.DataFrame(\n", + " {\n", + " \"b\": round(results1.params, 4),\n", + " \"se\": round(results1.bse, 4),\n", + " \"t\": round(results1.tvalues, 4),\n", + " \"pval\": round(results1.pvalues, 4),\n", + " },\n", + ")\n", + "print(f\"table1: \\n{table1}\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "table2: \n", + " b se t pval\n", + "Intercept 0.1857 0.0812 2.2889 0.0224\n", + "ret_lag1 0.0603 0.0382 1.5799 0.1146\n", + "ret_lag2 -0.0381 0.0381 -0.9982 0.3185\n", + "\n" + ] + } + ], + "source": [ + "table2 = pd.DataFrame(\n", + " {\n", + " \"b\": round(results2.params, 4),\n", + " \"se\": round(results2.bse, 4),\n", + " \"t\": round(results2.tvalues, 4),\n", + " \"pval\": round(results2.pvalues, 4),\n", + " },\n", + ")\n", + "print(f\"table2: \\n{table2}\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "table3: \n", + " b se t pval\n", + "Intercept 0.1794 0.0816 2.1990 0.0282\n", + "ret_lag1 0.0614 0.0382 1.6056 0.1088\n", + "ret_lag2 -0.0403 0.0383 -1.0519 0.2932\n", + "ret_lag3 0.0307 0.0382 0.8038 0.4218\n", + "\n" + ] + } + ], + "source": [ + "table3 = pd.DataFrame(\n", + " {\n", + " \"b\": round(results3.params, 4),\n", + " \"se\": round(results3.bse, 4),\n", + " \"t\": round(results3.tvalues, 4),\n", + " \"pval\": round(results3.pvalues, 4),\n", + " },\n", + ")\n", + "print(f\"table3: \\n{table3}\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 11.2 The Nature of Highly Persistent Time Series" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 0, 'time')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# set the random seed:\n", + "np.random.seed(1234567)\n", + "\n", + "# initialize plot:\n", + "x_range = np.linspace(0, 50, num=51)\n", + "plt.ylim([-18, 18])\n", + "plt.xlim([0, 50])\n", + "\n", + "# loop over draws:\n", + "for r in range(30):\n", + " # i.i.d. standard normal shock:\n", + " e = stats.norm.rvs(0, 1, size=51)\n", + "\n", + " # set first entry to 0 (gives y_0 = 0):\n", + " e[0] = 0\n", + "\n", + " # random walk as cumulative sum of shocks:\n", + " y = np.cumsum(e)\n", + "\n", + " # add line to graph:\n", + " plt.plot(x_range, y, color=\"lightgrey\", linestyle=\"-\")\n", + "\n", + "plt.axhline(linewidth=2, linestyle=\"--\", color=\"black\")\n", + "plt.ylabel(\"y\")\n", + "plt.xlabel(\"time\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 0, 'time')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# set the random seed:\n", + "np.random.seed(1234567)\n", + "\n", + "# initialize plot:\n", + "x_range = np.linspace(0, 50, num=51)\n", + "plt.ylim([0, 100])\n", + "plt.xlim([0, 50])\n", + "\n", + "# loop over draws:\n", + "for r in range(30):\n", + " # i.i.d. standard normal shock:\n", + " e = stats.norm.rvs(0, 1, size=51)\n", + "\n", + " # set first entry to 0 (gives y_0 = 0):\n", + " e[0] = 0\n", + "\n", + " # random walk as cumulative sum of shocks plus drift:\n", + " y = np.cumsum(e) + 2 * x_range\n", + "\n", + " # add line to graph:\n", + " plt.plot(x_range, y, color=\"lightgrey\", linestyle=\"-\")\n", + "\n", + "plt.plot(x_range, 2 * x_range, linewidth=2, linestyle=\"--\", color=\"black\")\n", + "plt.ylabel(\"y\")\n", + "plt.xlabel(\"time\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 11.3 Differences of Highly Persistent Time Series" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 0, 'time')" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# set the random seed:\n", + "np.random.seed(1234567)\n", + "\n", + "# initialize plot:\n", + "x_range = np.linspace(1, 50, num=50)\n", + "plt.ylim([-1, 5])\n", + "plt.xlim([0, 50])\n", + "\n", + "# loop over draws:\n", + "for r in range(30):\n", + " # i.i.d. standard normal shock and cumulative sum of shocks:\n", + " e = stats.norm.rvs(0, 1, size=51)\n", + " e[0] = 0\n", + " y = np.cumsum(2 + e)\n", + "\n", + " # first difference:\n", + " Dy = y[1:51] - y[0:50]\n", + "\n", + " # add line to graph:\n", + " plt.plot(x_range, Dy, color=\"lightgrey\", linestyle=\"-\")\n", + "\n", + "plt.axhline(y=2, linewidth=2, linestyle=\"--\", color=\"black\")\n", + "plt.ylabel(\"y\")\n", + "plt.xlabel(\"time\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 11.4 Regression with First Differences\n", + "\n", + "### Example 11.6: Fertility Equation" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fertil3.head(): \n", + " gfr pe year t tsq pe_1 pe_2 pe_3 pe_4 pill ... \\\n", + "1913 124.699997 0.00 1913 1 1 NaN NaN NaN NaN 0 ... \n", + "1914 126.599998 0.00 1914 2 4 0.0 NaN NaN NaN 0 ... \n", + "1915 125.000000 0.00 1915 3 9 0.0 0.0 NaN NaN 0 ... \n", + "1916 123.400002 0.00 1916 4 16 0.0 0.0 0.0 NaN 0 ... \n", + "1917 121.000000 19.27 1917 5 25 0.0 0.0 0.0 0.0 0 ... \n", + "\n", + " cpe_3 cpe_4 gfr_1 cgfr_1 cgfr_2 cgfr_3 cgfr_4 \\\n", + "1913 NaN NaN NaN NaN NaN NaN NaN \n", + "1914 NaN NaN 124.699997 NaN NaN NaN NaN \n", + "1915 NaN NaN 126.599998 1.900002 NaN NaN NaN \n", + "1916 NaN NaN 125.000000 -1.599998 1.900002 NaN NaN \n", + "1917 0.0 NaN 123.400002 -1.599998 -1.599998 1.900002 NaN \n", + "\n", + " gfr_2 gfr_diff1 pe_diff1 \n", + "1913 NaN NaN NaN \n", + "1914 NaN 1.900002 0.00 \n", + "1915 124.699997 -1.599998 0.00 \n", + "1916 126.599998 -1.599998 0.00 \n", + "1917 125.000000 -2.400002 19.27 \n", + "\n", + "[5 rows x 26 columns]\n", + "\n" + ] + } + ], + "source": [ + "fertil3 = wool.data(\"fertil3\")\n", + "T = len(fertil3)\n", + "\n", + "# define time series (years only) beginning in 1913:\n", + "fertil3.index = pd.date_range(start=\"1913\", periods=T, freq=\"YE\").year\n", + "\n", + "# compute first differences:\n", + "fertil3[\"gfr_diff1\"] = fertil3[\"gfr\"].diff()\n", + "fertil3[\"pe_diff1\"] = fertil3[\"pe\"].diff()\n", + "print(f\"fertil3.head(): \\n{fertil3.head()}\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "table1: \n", + " b se t pval\n", + "Intercept -0.7848 0.5020 -1.5632 0.1226\n", + "pe_diff1 -0.0427 0.0284 -1.5045 0.1370\n", + "\n" + ] + } + ], + "source": [ + "# linear regression of model with first differences:\n", + "reg1 = smf.ols(formula=\"gfr_diff1 ~ pe_diff1\", data=fertil3)\n", + "results1 = reg1.fit()\n", + "\n", + "# print regression table:\n", + "table1 = pd.DataFrame(\n", + " {\n", + " \"b\": round(results1.params, 4),\n", + " \"se\": round(results1.bse, 4),\n", + " \"t\": round(results1.tvalues, 4),\n", + " \"pval\": round(results1.pvalues, 4),\n", + " },\n", + ")\n", + "print(f\"table1: \\n{table1}\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "table2: \n", + " b se t pval\n", + "Intercept -0.9637 0.4678 -2.0602 0.0434\n", + "pe_diff1 -0.0362 0.0268 -1.3522 0.1810\n", + "pe_diff1_lag1 -0.0140 0.0276 -0.5070 0.6139\n", + "pe_diff1_lag2 0.1100 0.0269 4.0919 0.0001\n", + "\n" + ] + } + ], + "source": [ + "# linear regression of model with lagged differences:\n", + "fertil3[\"pe_diff1_lag1\"] = fertil3[\"pe_diff1\"].shift(1)\n", + "fertil3[\"pe_diff1_lag2\"] = fertil3[\"pe_diff1\"].shift(2)\n", + "\n", + "reg2 = smf.ols(\n", + " formula=\"gfr_diff1 ~ pe_diff1 + pe_diff1_lag1 + pe_diff1_lag2\",\n", + " data=fertil3,\n", + ")\n", + "results2 = reg2.fit()\n", + "\n", + "# print regression table:\n", + "table2 = pd.DataFrame(\n", + " {\n", + " \"b\": round(results2.params, 4),\n", + " \"se\": round(results2.bse, 4),\n", + " \"t\": round(results2.tvalues, 4),\n", + " \"pval\": round(results2.pvalues, 4),\n", + " },\n", + ")\n", + "print(f\"table2: \\n{table2}\\n\")" + ] + } + ], + "metadata": { + "jupytext": { + "formats": "notebooks//ipynb,markdown//md,scripts//py" + }, + "kernelspec": { + "display_name": "merino", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/Ch2. The Simple Regression Model.ipynb b/notebooks/Ch2. The Simple Regression Model.ipynb index 535e54a..3703be9 100644 --- a/notebooks/Ch2. The Simple Regression Model.ipynb +++ b/notebooks/Ch2. The Simple Regression Model.ipynb @@ -104,6 +104,7 @@ "cell_type": "code", "execution_count": 4, "metadata": { + "lines_to_end_of_cell_marker": 2, "lines_to_next_cell": 2 }, "outputs": [ diff --git a/scripts/Ch11. Further Issues in Using OLS with Time Series Data.py b/scripts/Ch11. Further Issues in Using OLS with Time Series Data.py new file mode 100644 index 0000000..b9727ac --- /dev/null +++ b/scripts/Ch11. Further Issues in Using OLS with Time Series Data.py @@ -0,0 +1,218 @@ +# --- +# jupyter: +# jupytext: +# formats: notebooks//ipynb,markdown//md,scripts//py +# text_representation: +# extension: .py +# format_name: light +# format_version: '1.5' +# jupytext_version: 1.16.4 +# kernelspec: +# display_name: merino +# language: python +# name: python3 +# --- + +# # 11. Further Issues in Using OLS with Time Series Data + +# %pip install matplotlib numpy pandas statsmodels wooldridge scipy -q + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import statsmodels.formula.api as smf +import wooldridge as wool +from scipy import stats + +# ## 11.1 Asymptotics with Time Seires +# +# ### Example 11.4: Efficient Markets Hypothesis + +# + +nyse = wool.data("nyse") +nyse["ret"] = nyse["return"] + +# add all lags up to order 3: +nyse["ret_lag1"] = nyse["ret"].shift(1) +nyse["ret_lag2"] = nyse["ret"].shift(2) +nyse["ret_lag3"] = nyse["ret"].shift(3) + +# linear regression of model with lags: +reg1 = smf.ols(formula="ret ~ ret_lag1", data=nyse) +reg2 = smf.ols(formula="ret ~ ret_lag1 + ret_lag2", data=nyse) +reg3 = smf.ols(formula="ret ~ ret_lag1 + ret_lag2 + ret_lag3", data=nyse) +results1 = reg1.fit() +results2 = reg2.fit() +results3 = reg3.fit() + +# print regression tables: +table1 = pd.DataFrame( + { + "b": round(results1.params, 4), + "se": round(results1.bse, 4), + "t": round(results1.tvalues, 4), + "pval": round(results1.pvalues, 4), + }, +) +print(f"table1: \n{table1}\n") +# - + +table2 = pd.DataFrame( + { + "b": round(results2.params, 4), + "se": round(results2.bse, 4), + "t": round(results2.tvalues, 4), + "pval": round(results2.pvalues, 4), + }, +) +print(f"table2: \n{table2}\n") + +table3 = pd.DataFrame( + { + "b": round(results3.params, 4), + "se": round(results3.bse, 4), + "t": round(results3.tvalues, 4), + "pval": round(results3.pvalues, 4), + }, +) +print(f"table3: \n{table3}\n") + +# ## 11.2 The Nature of Highly Persistent Time Series + +# + +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(0, 50, num=51) +plt.ylim([-18, 18]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock: + e = stats.norm.rvs(0, 1, size=51) + + # set first entry to 0 (gives y_0 = 0): + e[0] = 0 + + # random walk as cumulative sum of shocks: + y = np.cumsum(e) + + # add line to graph: + plt.plot(x_range, y, color="lightgrey", linestyle="-") + +plt.axhline(linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") + +# + +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(0, 50, num=51) +plt.ylim([0, 100]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock: + e = stats.norm.rvs(0, 1, size=51) + + # set first entry to 0 (gives y_0 = 0): + e[0] = 0 + + # random walk as cumulative sum of shocks plus drift: + y = np.cumsum(e) + 2 * x_range + + # add line to graph: + plt.plot(x_range, y, color="lightgrey", linestyle="-") + +plt.plot(x_range, 2 * x_range, linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") +# - + +# ## 11.3 Differences of Highly Persistent Time Series + +# + +# set the random seed: +np.random.seed(1234567) + +# initialize plot: +x_range = np.linspace(1, 50, num=50) +plt.ylim([-1, 5]) +plt.xlim([0, 50]) + +# loop over draws: +for r in range(30): + # i.i.d. standard normal shock and cumulative sum of shocks: + e = stats.norm.rvs(0, 1, size=51) + e[0] = 0 + y = np.cumsum(2 + e) + + # first difference: + Dy = y[1:51] - y[0:50] + + # add line to graph: + plt.plot(x_range, Dy, color="lightgrey", linestyle="-") + +plt.axhline(y=2, linewidth=2, linestyle="--", color="black") +plt.ylabel("y") +plt.xlabel("time") +# - + +# ## 11.4 Regression with First Differences +# +# ### Example 11.6: Fertility Equation + +# + +fertil3 = wool.data("fertil3") +T = len(fertil3) + +# define time series (years only) beginning in 1913: +fertil3.index = pd.date_range(start="1913", periods=T, freq="YE").year + +# compute first differences: +fertil3["gfr_diff1"] = fertil3["gfr"].diff() +fertil3["pe_diff1"] = fertil3["pe"].diff() +print(f"fertil3.head(): \n{fertil3.head()}\n") + +# + +# linear regression of model with first differences: +reg1 = smf.ols(formula="gfr_diff1 ~ pe_diff1", data=fertil3) +results1 = reg1.fit() + +# print regression table: +table1 = pd.DataFrame( + { + "b": round(results1.params, 4), + "se": round(results1.bse, 4), + "t": round(results1.tvalues, 4), + "pval": round(results1.pvalues, 4), + }, +) +print(f"table1: \n{table1}\n") + +# + +# linear regression of model with lagged differences: +fertil3["pe_diff1_lag1"] = fertil3["pe_diff1"].shift(1) +fertil3["pe_diff1_lag2"] = fertil3["pe_diff1"].shift(2) + +reg2 = smf.ols( + formula="gfr_diff1 ~ pe_diff1 + pe_diff1_lag1 + pe_diff1_lag2", + data=fertil3, +) +results2 = reg2.fit() + +# print regression table: +table2 = pd.DataFrame( + { + "b": round(results2.params, 4), + "se": round(results2.bse, 4), + "t": round(results2.tvalues, 4), + "pval": round(results2.pvalues, 4), + }, +) +print(f"table2: \n{table2}\n")