{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Trends and cycles in unemployment\n", "\n", "Here we consider three methods for separating a trend and cycle in economic data. Supposing we have a time series $y_t$, the basic idea is to decompose it into these two components:\n", "\n", "$$\n", "y_t = \\mu_t + \\eta_t\n", "$$\n", "\n", "where $\\mu_t$ represents the trend or level and $\\eta_t$ represents the cyclical component. In this case, we consider a *stochastic* trend, so that $\\mu_t$ is a random variable and not a deterministic function of time. Two of methods fall under the heading of \"unobserved components\" models, and the third is the popular Hodrick-Prescott (HP) filter. Consistent with e.g. Harvey and Jaeger (1993), we find that these models all produce similar decompositions.\n", "\n", "This notebook demonstrates applying these models to separate trend from cycle in the U.S. unemployment rate." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:24.794991Z", "iopub.status.busy": "2020-12-20T00:07:24.791162Z", "iopub.status.idle": "2020-12-20T00:07:25.938454Z", "shell.execute_reply": "2020-12-20T00:07:25.939196Z" } }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:25.945060Z", "iopub.status.busy": "2020-12-20T00:07:25.944262Z", "iopub.status.idle": "2020-12-20T00:07:29.121973Z", "shell.execute_reply": "2020-12-20T00:07:29.123335Z" } }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import statsmodels.api as sm\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:29.129178Z", "iopub.status.busy": "2020-12-20T00:07:29.127549Z", "iopub.status.idle": "2020-12-20T00:07:29.541939Z", "shell.execute_reply": "2020-12-20T00:07:29.543372Z" } }, "outputs": [], "source": [ "from pandas_datareader.data import DataReader\n", "endog = DataReader('UNRATE', 'fred', start='1954-01-01')\n", "endog.index.freq = endog.index.inferred_freq" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Hodrick-Prescott (HP) filter\n", "\n", "The first method is the Hodrick-Prescott filter, which can be applied to a data series in a very straightforward method. Here we specify the parameter $\\lambda=129600$ because the unemployment rate is observed monthly." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:29.549152Z", "iopub.status.busy": "2020-12-20T00:07:29.547495Z", "iopub.status.idle": "2020-12-20T00:07:29.576665Z", "shell.execute_reply": "2020-12-20T00:07:29.575229Z" } }, "outputs": [], "source": [ "hp_cycle, hp_trend = sm.tsa.filters.hpfilter(endog, lamb=129600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Unobserved components and ARIMA model (UC-ARIMA)\n", "\n", "The next method is an unobserved components model, where the trend is modeled as a random walk and the cycle is modeled with an ARIMA model - in particular, here we use an AR(4) model. The process for the time series can be written as:\n", "\n", "$$\n", "\\begin{align}\n", "y_t & = \\mu_t + \\eta_t \\\\\n", "\\mu_{t+1} & = \\mu_t + \\epsilon_{t+1} \\\\\n", "\\phi(L) \\eta_t & = \\nu_t\n", "\\end{align}\n", "$$\n", "\n", "where $\\phi(L)$ is the AR(4) lag polynomial and $\\epsilon_t$ and $\\nu_t$ are white noise." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:29.589271Z", "iopub.status.busy": "2020-12-20T00:07:29.588414Z", "iopub.status.idle": "2020-12-20T00:07:32.990913Z", "shell.execute_reply": "2020-12-20T00:07:32.991571Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Unobserved Components Results \n", "==============================================================================\n", "Dep. Variable: UNRATE No. Observations: 803\n", "Model: random walk Log Likelihood -452.634\n", " + AR(4) AIC 917.269\n", "Date: Sun, 20 Dec 2020 BIC 945.391\n", "Time: 00:07:32 HQIC 928.071\n", "Sample: 01-01-1954 \n", " - 11-01-2020 \n", "Covariance Type: opg \n", "================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "--------------------------------------------------------------------------------\n", "sigma2.level 0.0855 0.149 0.574 0.566 -0.207 0.378\n", "sigma2.ar 0.0916 0.153 0.599 0.549 -0.208 0.391\n", "ar.L1 1.0822 0.142 7.635 0.000 0.804 1.360\n", "ar.L2 -0.2236 0.392 -0.571 0.568 -0.991 0.544\n", "ar.L3 0.1185 0.248 0.478 0.632 -0.367 0.604\n", "ar.L4 -0.0262 0.102 -0.256 0.798 -0.227 0.174\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 0.00 Jarque-Bera (JB): 5804626.97\n", "Prob(Q): 0.95 Prob(JB): 0.00\n", "Heteroskedasticity (H): 9.38 Skew: 17.12\n", "Prob(H) (two-sided): 0.00 Kurtosis: 418.37\n", "===================================================================================\n", "\n", "Warnings:\n", "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n" ] } ], "source": [ "mod_ucarima = sm.tsa.UnobservedComponents(endog, 'rwalk', autoregressive=4)\n", "# Here the powell method is used, since it achieves a\n", "# higher loglikelihood than the default L-BFGS method\n", "res_ucarima = mod_ucarima.fit(method='powell', disp=False)\n", "print(res_ucarima.summary())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Unobserved components with stochastic cycle (UC)\n", "\n", "The final method is also an unobserved components model, but where the cycle is modeled explicitly.\n", "\n", "$$\n", "\\begin{align}\n", "y_t & = \\mu_t + \\eta_t \\\\\n", "\\mu_{t+1} & = \\mu_t + \\epsilon_{t+1} \\\\\n", "\\eta_{t+1} & = \\eta_t \\cos \\lambda_\\eta + \\eta_t^* \\sin \\lambda_\\eta + \\tilde \\omega_t \\qquad & \\tilde \\omega_t \\sim N(0, \\sigma_{\\tilde \\omega}^2) \\\\\n", "\\eta_{t+1}^* & = -\\eta_t \\sin \\lambda_\\eta + \\eta_t^* \\cos \\lambda_\\eta + \\tilde \\omega_t^* & \\tilde \\omega_t^* \\sim N(0, \\sigma_{\\tilde \\omega}^2)\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:33.000491Z", "iopub.status.busy": "2020-12-20T00:07:32.999587Z", "iopub.status.idle": "2020-12-20T00:07:35.891496Z", "shell.execute_reply": "2020-12-20T00:07:35.890288Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Unobserved Components Results \n", "=====================================================================================\n", "Dep. Variable: UNRATE No. Observations: 803\n", "Model: random walk Log Likelihood -455.171\n", " + damped stochastic cycle AIC 918.343\n", "Date: Sun, 20 Dec 2020 BIC 937.081\n", "Time: 00:07:35 HQIC 925.541\n", "Sample: 01-01-1954 \n", " - 11-01-2020 \n", "Covariance Type: opg \n", "===================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "-----------------------------------------------------------------------------------\n", "sigma2.level 0.1259 0.026 4.861 0.000 0.075 0.177\n", "sigma2.cycle 0.0416 0.024 1.711 0.087 -0.006 0.089\n", "frequency.cycle 0.3491 0.149 2.347 0.019 0.058 0.641\n", "damping.cycle 0.7932 0.045 17.649 0.000 0.705 0.881\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 1.55 Jarque-Bera (JB): 5968939.68\n", "Prob(Q): 0.21 Prob(JB): 0.00\n", "Heteroskedasticity (H): 9.10 Skew: 17.39\n", "Prob(H) (two-sided): 0.00 Kurtosis: 424.73\n", "===================================================================================\n", "\n", "Warnings:\n", "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n" ] } ], "source": [ "mod_uc = sm.tsa.UnobservedComponents(\n", " endog, 'rwalk',\n", " cycle=True, stochastic_cycle=True, damped_cycle=True,\n", ")\n", "# Here the powell method gets close to the optimum\n", "res_uc = mod_uc.fit(method='powell', disp=False)\n", "# but to get to the highest loglikelihood we do a\n", "# second round using the L-BFGS method.\n", "res_uc = mod_uc.fit(res_uc.params, disp=False)\n", "print(res_uc.summary())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Graphical comparison\n", "\n", "The output of each of these models is an estimate of the trend component $\\mu_t$ and an estimate of the cyclical component $\\eta_t$. Qualitatively the estimates of trend and cycle are very similar, although the trend component from the HP filter is somewhat more variable than those from the unobserved components models. This means that relatively mode of the movement in the unemployment rate is attributed to changes in the underlying trend rather than to temporary cyclical movements." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2020-12-20T00:07:35.901242Z", "iopub.status.busy": "2020-12-20T00:07:35.900393Z", "iopub.status.idle": "2020-12-20T00:07:37.212973Z", "shell.execute_reply": "2020-12-20T00:07:37.213736Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(2, figsize=(13,5));\n", "axes[0].set(title='Level/trend component')\n", "axes[0].plot(endog.index, res_uc.level.smoothed, label='UC')\n", "axes[0].plot(endog.index, res_ucarima.level.smoothed, label='UC-ARIMA(2,0)')\n", "axes[0].plot(hp_trend, label='HP Filter')\n", "axes[0].legend(loc='upper left')\n", "axes[0].grid()\n", "\n", "axes[1].set(title='Cycle component')\n", "axes[1].plot(endog.index, res_uc.cycle.smoothed, label='UC')\n", "axes[1].plot(endog.index, res_ucarima.autoregressive.smoothed, label='UC-ARIMA(2,0)')\n", "axes[1].plot(hp_cycle, label='HP Filter')\n", "axes[1].legend(loc='upper left')\n", "axes[1].grid()\n", "\n", "fig.tight_layout();" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 1 }