{ "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": "2022-06-22T04:40:00.609019Z", "iopub.status.busy": "2022-06-22T04:40:00.608754Z", "iopub.status.idle": "2022-06-22T04:40:01.850968Z", "shell.execute_reply": "2022-06-22T04:40:01.850296Z" } }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2022-06-22T04:40:01.857499Z", "iopub.status.busy": "2022-06-22T04:40:01.855700Z", "iopub.status.idle": "2022-06-22T04:40:03.013640Z", "shell.execute_reply": "2022-06-22T04:40:03.012915Z" } }, "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": "2022-06-22T04:40:03.017414Z", "iopub.status.busy": "2022-06-22T04:40:03.017006Z", "iopub.status.idle": "2022-06-22T04:40:03.255784Z", "shell.execute_reply": "2022-06-22T04:40:03.255137Z" } }, "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": "2022-06-22T04:40:03.261909Z", "iopub.status.busy": "2022-06-22T04:40:03.260121Z", "iopub.status.idle": "2022-06-22T04:40:03.273203Z", "shell.execute_reply": "2022-06-22T04:40:03.272642Z" } }, "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": "2022-06-22T04:40:03.278616Z", "iopub.status.busy": "2022-06-22T04:40:03.276990Z", "iopub.status.idle": "2022-06-22T04:40:04.332673Z", "shell.execute_reply": "2022-06-22T04:40:04.331964Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Unobserved Components Results \n", "==============================================================================\n", "Dep. Variable: UNRATE No. Observations: 821\n", "Model: random walk Log Likelihood -457.661\n", " + AR(4) AIC 927.321\n", "Date: Wed, 22 Jun 2022 BIC 955.577\n", "Time: 04:40:04 HQIC 938.163\n", "Sample: 01-01-1954 \n", " - 05-01-2022 \n", "Covariance Type: opg \n", "================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "--------------------------------------------------------------------------------\n", "sigma2.level 0.0756 0.165 0.458 0.647 -0.248 0.399\n", "sigma2.ar 0.1014 0.167 0.606 0.545 -0.227 0.429\n", "ar.L1 1.0619 0.106 10.006 0.000 0.854 1.270\n", "ar.L2 -0.1759 0.303 -0.581 0.561 -0.769 0.417\n", "ar.L3 0.0897 0.185 0.486 0.627 -0.272 0.451\n", "ar.L4 -0.0216 0.078 -0.278 0.781 -0.174 0.131\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 0.00 Jarque-Bera (JB): 6028026.69\n", "Prob(Q): 0.95 Prob(JB): 0.00\n", "Heteroskedasticity (H): 9.36 Skew: 17.11\n", "Prob(H) (two-sided): 0.00 Kurtosis: 421.64\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": "2022-06-22T04:40:04.336026Z", "iopub.status.busy": "2022-06-22T04:40:04.335620Z", "iopub.status.idle": "2022-06-22T04:40:05.270751Z", "shell.execute_reply": "2022-06-22T04:40:05.269698Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Unobserved Components Results \n", "=====================================================================================\n", "Dep. Variable: UNRATE No. Observations: 821\n", "Model: random walk Log Likelihood -460.750\n", " + damped stochastic cycle AIC 929.499\n", "Date: Wed, 22 Jun 2022 BIC 948.327\n", "Time: 04:40:05 HQIC 936.724\n", "Sample: 01-01-1954 \n", " - 05-01-2022 \n", "Covariance Type: opg \n", "===================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "-----------------------------------------------------------------------------------\n", "sigma2.level 0.1806 0.004 42.655 0.000 0.172 0.189\n", "sigma2.cycle 1.599e-11 0.002 6.4e-09 1.000 -0.005 0.005\n", "frequency.cycle 0.3490 571.184 0.001 1.000 -1119.151 1119.849\n", "damping.cycle 0.1097 35.924 0.003 0.998 -70.299 70.519\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 1.52 Jarque-Bera (JB): 6080363.13\n", "Prob(Q): 0.22 Prob(JB): 0.00\n", "Heteroskedasticity (H): 9.94 Skew: 17.13\n", "Prob(H) (two-sided): 0.00 Kurtosis: 423.98\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": "2022-06-22T04:40:05.274464Z", "iopub.status.busy": "2022-06-22T04:40:05.274167Z", "iopub.status.idle": "2022-06-22T04:40:05.835862Z", "shell.execute_reply": "2022-06-22T04:40:05.835241Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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