FRBUS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# An interactive notebook with the FRB/US model\n",
    "This notebook is based on the the FRB/US model packages located here https://www.federalreserve.gov/econres/us-models-package.htm. The packages provides an Eviews https://www.eviews.com/ implementation. The Eviews modelspecification has been transformed to ModelFlow BusinessLogic specification. \n",
    "\n",
    "You can experiment with the model using a simple interactive interface. \n",
    "\n",
    "FRB/US comes in two flawors: **VAR** in which expectaions are generated by backward looking equations, and **MCE** in which expectation are based on leaded values. \n",
    "This notebook implement the **VAR** flavour. \n",
    "\n",
    "The tool used is highly experimental and the results are purely for illustration. \n",
    "\n",
    "You can run each cell by pressing the run tool or shift+enter\n",
    "To run all cells use select cell/run all in the menu bar. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Import Python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ModelFlow info: CVXopt not installed. Only matters if you are incorporating optimization\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "from numba import jit\n",
    "# point to the modelflow library \n",
    "import sys\n",
    "sys.path.append(r'modelflow/')\n",
    " \n",
    "from modelsandbox import newmodel  \n",
    "from modelnet     import draw_adjacency_matrix\n",
    "from modeljupyter import inputwidget"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Prepare some stuff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "turbo = 0  # Determines if the the model is compiled or not \n",
    "\n",
    "# define af function which is in Eviews but not in Python\n",
    "@jit(\"f8(b1,f8,f8)\")\n",
    "def recode(condition,yes,no):\n",
    "    '''Function which recratetes the functionality of @recode from eviews ''' \n",
    "    return yes if condition else no"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "\"rise\":{\"scroll\":true , \"enable_chalkboard\": true}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Load the model and the data \n",
    "The model and the data has been prepared from the public packagde in a previous step. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "basedf  = pd.read_pickle('frbus/data/baseline.pc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "ffrbus  = open('frbus/model/ffrbusvar.txt','rt').read() \n",
    "# print(ffrbus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Create a model class instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This model has simultaneous elements or cyclical elements.\n"
     ]
    }
   ],
   "source": [
    "mfrbus = newmodel(ffrbus,funks=[recode])\n",
    "mfrbus.use_preorder = True  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Run Baseline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "res = mfrbus(basedf,'2020q1','2025q4',antal= 500,relconv=0.000000001,\n",
    "             conv='XGDPN',ljit=turbo,silent=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Provide descriptions for the model  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "trans = {'XGDPN':'GDP real terms (XGDPN)','RFF':'Federal Funds Rate (RFF)','GFSRPN':'Federal Budget surplus',\n",
    "        'RFFMIN':'Minimum Fed Funds'}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Define an interactive input widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": [],
    "scrolled": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "slidedef = {'Initial taylor':                {'var':'RFFINTAY_AERR','value':0.0,'min':-3, 'max':3,'op':'+'},\n",
    "            'Initial taylor inital impulse': {'var':'RFFINTAY_AERR','value':0.0,'min':-3, 'max':3,'op':'+impulse'},\n",
    "            'Minimum federal funds':         {'var':'RFFMIN',       'value':0.0,'min':-20,'max':5,'op':'='       ,'step':1.0}\n",
    "            }\n",
    "radiodef = {'Monetary policy reaction':\n",
    "            [['Inertial Taylor rule','DMPINTAY'],\n",
    "             ['Taylor rule','DMPTAY'],\n",
    "             ['Taylor rule with unemployment gap','DMPTLR'],\n",
    "             ['Estimated rule','DMPALT'],\n",
    "             ['Generalized rule','DMPGEN'],\n",
    "             ['Exogenous nominal funds rate', 'DMPEX'],\n",
    "             ['Exogenous real funds rate', 'DMPRR']\n",
    "            ]\n",
    "           }\n",
    "           \n",
    "checkdef = [('Timing of zero lower bound', 'DMPTRSH' ,True) ]\n",
    "\n",
    "input = inputwidget(mfrbus,basedf,slidedef=slidedef,checkdef=checkdef,radiodef=radiodef\n",
    "                   ,showout=True,varpat='RFF XGDPN RFFMIN GFSRPN DMPTRSH',modelopt={'silent':True},trans=trans)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Run the widget  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "code_folding": [],
    "scrolled": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "21b043962e454d4388381368374a1620",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Label(value='Input new parameter ', layout=Layout(width='41%')), Label(value='Al…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(input)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Some interfaces \n",
    ". (dot) makes it easy to look at single variable. \n",
    "\n",
    "\\[ \\] (Slice) alows inspection of many variables selected with wildcars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    " # we only want a few quarters \n",
    "_ = mfrbus.smpl('2020q1','2021q1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Endogeneous: RFF \n",
      "Formular: FRML  <> RFF=(1-DMPTRSH)*(RECODE((RFFRULE)>(RFFMIN),RFFRULE,RFFMIN))+DMPTRSH*(RECODE(((DMPTR(-1)*RFFRULE+(1-DMPTR(-1))*RFFMIN))>(RFFMIN),(DMPTR(-1)*RFFRULE+(1-DMPTR(-1))*RFFMIN),RFFMIN))+RFF_AERR  $\n",
      "Values : \n",
      "        2020Q1    2020Q2    2020Q3    2020Q4    2021Q1\n",
      "Base  3.153624  3.250023  3.324873  3.378474  3.411382\n",
      "Last  3.153624  3.250023  3.324873  3.378474  3.411382\n",
      "Diff  0.000000  0.000000  0.000000  0.000000  0.000000\n",
      "\n",
      "Input last run: \n",
      "                  2020Q1        2020Q2        2020Q3        2020Q4  \\\n",
      "DMPTR(-1)  1.000000e+00  1.000000e+00  1.000000e+00  1.000000e+00   \n",
      "DMPTRSH    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
      "RFFMIN    -9.999000e+03 -9.999000e+03 -9.999000e+03 -9.999000e+03   \n",
      "RFFRULE    3.153624e+00  3.250023e+00  3.324873e+00  3.378474e+00   \n",
      "RFF_AERR  -6.833184e-17 -6.833184e-17 -6.833184e-17 -6.833184e-17   \n",
      "\n",
      "                 2021Q1  \n",
      "DMPTR(-1)  1.000000e+00  \n",
      "DMPTRSH    0.000000e+00  \n",
      "RFFMIN    -9.999000e+03  \n",
      "RFFRULE    3.411382e+00  \n",
      "RFF_AERR  -6.833184e-17  \n",
      "\n",
      "Input base run: \n",
      "                  2020Q1        2020Q2        2020Q3        2020Q4  \\\n",
      "DMPTR(-1)  1.000000e+00  1.000000e+00  1.000000e+00  1.000000e+00   \n",
      "DMPTRSH    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
      "RFFMIN    -9.999000e+03 -9.999000e+03 -9.999000e+03 -9.999000e+03   \n",
      "RFFRULE    3.153624e+00  3.250023e+00  3.324873e+00  3.378474e+00   \n",
      "RFF_AERR  -6.833184e-17 -6.833184e-17 -6.833184e-17 -6.833184e-17   \n",
      "\n",
      "                 2021Q1  \n",
      "DMPTR(-1)  1.000000e+00  \n",
      "DMPTRSH    0.000000e+00  \n",
      "RFFMIN    -9.999000e+03  \n",
      "RFFRULE    3.411382e+00  \n",
      "RFF_AERR  -6.833184e-17  \n",
      "\n",
      "Difference: \n",
      "            2020Q1  2020Q2  2020Q3  2020Q4  2021Q1\n",
      "DMPTR(-1)     0.0     0.0     0.0     0.0     0.0\n",
      "DMPTRSH       0.0     0.0     0.0     0.0     0.0\n",
      "RFFMIN        0.0     0.0     0.0     0.0     0.0\n",
      "RFFRULE       0.0     0.0     0.0     0.0     0.0\n",
      "RFF_AERR      0.0     0.0     0.0     0.0     0.0\n"
     ]
    }
   ],
   "source": [
    "mfrbus.rff.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "          RFFTAY  RFFTAY_AERR   RFFRULE  RFFRULE_AERR\n",
       "2020Q1  3.096495    -1.960046  3.153624  2.400000e-10\n",
       "2020Q2  3.085904    -1.960046  3.250023  3.550000e-09\n",
       "2020Q3  3.056294    -1.960046  3.324873 -5.000007e-11\n",
       "2020Q4  3.008033    -1.960046  3.378474 -1.900001e-10\n",
       "2021Q1  2.949347    -1.960046  3.411382 -5.300001e-10"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mfrbus['rffta* rffrule*']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Formula        : FRML  <> RFFINTAY=.85*RFF(-1)+(1-.85)*(RSTAR+(PICXFE+PICXFE(-1)+PICXFE(-2)+PICXFE(-3))/4+0.5*((PICXFE+PICXFE(-1)+PICXFE(-2)+PICXFE(-3))/4-PITARG)+1.0*XGAP2)+RFFINTAY_AERR  $ \n",
      "\n",
      "                    2020Q1     2020Q2     2020Q3     2020Q4     2021Q1\n",
      "Variable    lag                                                       \n",
      "Base        0     3.153624   3.250023   3.324873   3.378474   3.411382\n",
      "Alternative 0     3.153624   3.250023   3.324873   3.378474   3.411382\n",
      "Difference  0     0.000000   0.000000   0.000000   0.000000   0.000000\n",
      "Percent     0    -0.000003  -0.000003  -0.000003  -0.000003  -0.000003\n",
      "\n",
      " Contributions to differende for  RFFINTAY\n",
      "                      2020Q1     2020Q2     2020Q3     2020Q4     2021Q1\n",
      "Variable      lag                                                       \n",
      "RFF           -1   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "RSTAR          0   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "PICXFE         0   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "              -1   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "              -2   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "              -3   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "PITARG         0   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "XGAP2          0   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "RFFINTAY_AERR  0   -0.000000  -0.000000  -0.000000  -0.000000  -0.000000\n",
      "\n",
      " Share of contributions to differende for  RFFINTAY\n",
      "                       2020Q1      2020Q2      2020Q3      2020Q4      2021Q1\n",
      "Variable      lag                                                            \n",
      "RFF           -1          -0%         -0%         -0%         -0%         -0%\n",
      "RSTAR          0          -0%         -0%         -0%         -0%         -0%\n",
      "PICXFE         0          -0%         -0%         -0%         -0%         -0%\n",
      "              -1          -0%         -0%         -0%         -0%         -0%\n",
      "              -2          -0%         -0%         -0%         -0%         -0%\n",
      "              -3          -0%         -0%         -0%         -0%         -0%\n",
      "PITARG         0          -0%         -0%         -0%         -0%         -0%\n",
      "XGAP2          0          -0%         -0%         -0%         -0%         -0%\n",
      "RFFINTAY_AERR  0          -0%         -0%         -0%         -0%         -0%\n",
      "Total          0          -0%         -0%         -0%         -0%         -1%\n",
      "Residual       0        -100%       -100%       -100%       -100%       -101%\n"
     ]
    }
   ],
   "source": [
    "_= mfrbus.rffintay.dekomp(start='2020q1',end='2021q1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
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   ],
   "source": [
    "_ = mfrbus.rfftay.explain(up=1,svg=1,pdf=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = mfrbus['rffta* rffrule*'].dif.plot(colrow=1,sharey=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "#mfrbus.drawendo(lag=0,title='FRB/US endogeneous interpendencies',pdf=0)\n",
    "# you will find the output files in different format in the /graph folder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# How is the interest rate determined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg height=\"432pt\" viewBox=\"0.00 0.00 139.40 432.00\" width=\"139pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g class=\"graph\" id=\"graph0\" transform=\"scale(0.492588 0.492588) rotate(0) translate(4 873)\">\n",
       "<title>TD</title>\n",
       "<polygon fill=\"white\" points=\"-4,4 -4,-873 279,-873 279,4 -4,4\" stroke=\"none\"/>\n",
       "<text font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"middle\" x=\"137.5\" y=\"-7.8\">RFF</text>\n",
       "<!-- ZRFF10 -->\n",
       "<g class=\"node\" id=\"node1\"><title>ZRFF10</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"273,-869 212,-869 212,-833 273,-833 273,-869\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"218.5\" y=\"-846.8\">ZRFF10</text>\n",
       "</g>\n",
       "<!-- DMPTR(&#45;1) -->\n",
       "<g class=\"node\" id=\"node2\"><title>DMPTR(-1)</title>\n",
       "<polygon fill=\"springgreen\" points=\"83,-572 1,-572 1,-536 83,-536 83,-572\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"7\" y=\"-549.8\">DMPTR(-1)</text>\n",
       "</g>\n",
       "<!-- RFF -->\n",
       "<g class=\"node\" id=\"node6\"><title>RFF</title>\n",
       "<polygon fill=\"Turquoise\" points=\"174,-464 120,-464 120,-428 174,-428 174,-464\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"134\" y=\"-441.8\">RFF</text>\n",
       "</g>\n",
       "<!-- DMPTR(&#45;1)&#45;&gt;RFF -->\n",
       "<g class=\"edge\" id=\"edge6\"><title>DMPTR(-1)-&gt;RFF</title>\n",
       "<path d=\"M73.0063,-535.956C76.861,-533.152 80.6323,-530.137 84,-527 101.275,-510.909 117.372,-489.611 128.832,-472.893\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"132.04,-474.393 134.7,-464.138 126.225,-470.496 132.04,-474.393\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZYHT -->\n",
       "<g class=\"node\" id=\"node3\"><title>ZYHT</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-815 215.5,-815 215.5,-779 269.5,-779 269.5,-815\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"224.5\" y=\"-792.8\">ZYHT</text>\n",
       "</g>\n",
       "<!-- DELRFF -->\n",
       "<g class=\"node\" id=\"node4\"><title>DELRFF</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"275,-761 210,-761 210,-725 275,-725 275,-761\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"216.5\" y=\"-738.8\">DELRFF</text>\n",
       "</g>\n",
       "<!-- ZRFF5 -->\n",
       "<g class=\"node\" id=\"node5\"><title>ZRFF5</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-707 215.5,-707 215.5,-671 269.5,-671 269.5,-707\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"221.5\" y=\"-684.8\">ZRFF5</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZRFF10 -->\n",
       "<g class=\"edge\" id=\"edge15\"><title>RFF-&gt;ZRFF10</title>\n",
       "<path d=\"M149.344,-464.337C154.49,-531.134 174.464,-760.821 210,-824 210.11,-824.196 210.223,-824.392 210.337,-824.586\" fill=\"none\" stroke=\"black\"/>\n",
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       "<!-- RFF&#45;&gt;ZYHT -->\n",
       "<g class=\"edge\" id=\"edge21\"><title>RFF-&gt;ZYHT</title>\n",
       "<path d=\"M147.429,-464.283C146.624,-516.03 149.943,-666.462 210,-770 210.113,-770.195 210.228,-770.389 210.345,-770.582\" fill=\"none\" stroke=\"black\"/>\n",
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       "</g>\n",
       "<!-- RFF&#45;&gt;DELRFF -->\n",
       "<g class=\"edge\" id=\"edge12\"><title>RFF-&gt;DELRFF</title>\n",
       "<path d=\"M148.338,-464.167C149.957,-509.845 159.1,-631.841 210,-716 210.242,-716.401 210.493,-716.798 210.75,-717.193\" fill=\"none\" stroke=\"black\"/>\n",
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       "</g>\n",
       "<!-- RFF&#45;&gt;ZRFF5 -->\n",
       "<g class=\"edge\" id=\"edge2\"><title>RFF-&gt;ZRFF5</title>\n",
       "<path d=\"M149.678,-464.229C153.998,-503.334 168.259,-597 210,-662 210.253,-662.394 210.513,-662.785 210.781,-663.174\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"208.13,-665.461 217.227,-670.893 213.504,-660.974 208.13,-665.461\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZYHP -->\n",
       "<g class=\"node\" id=\"node8\"><title>ZYHP</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-653 215.5,-653 215.5,-617 269.5,-617 269.5,-653\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"224.5\" y=\"-630.8\">ZYHP</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZYHP -->\n",
       "<g class=\"edge\" id=\"edge19\"><title>RFF-&gt;ZYHP</title>\n",
       "<path d=\"M151.897,-464.422C159.238,-496.046 177.389,-561.721 210,-608 210.27,-608.383 210.546,-608.763 210.828,-609.142\" fill=\"none\" stroke=\"black\"/>\n",
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       "</g>\n",
       "<!-- ZPIC58 -->\n",
       "<g class=\"node\" id=\"node9\"><title>ZPIC58</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"271,-599 214,-599 214,-563 271,-563 271,-599\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"220.5\" y=\"-576.8\">ZPIC58</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZPIC58 -->\n",
       "<g class=\"edge\" id=\"edge11\"><title>RFF-&gt;ZPIC58</title>\n",
       "<path d=\"M155.984,-464.002C166.447,-486.452 186.282,-525.359 210,-554 210.482,-554.582 210.978,-555.163 211.485,-555.74\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"209.083,-558.289 218.573,-562.999 214.092,-553.399 209.083,-558.289\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZYH -->\n",
       "<g class=\"node\" id=\"node10\"><title>ZYH</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-545 215.5,-545 215.5,-509 269.5,-509 269.5,-545\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"228.5\" y=\"-522.8\">ZYH</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZYH -->\n",
       "<g class=\"edge\" id=\"edge8\"><title>RFF-&gt;ZYH</title>\n",
       "<path d=\"M168.631,-464.041C180.675,-474.555 196.175,-488.055 210,-500 210.818,-500.706 211.647,-501.423 212.485,-502.145\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"210.267,-504.854 220.131,-508.723 214.833,-499.548 210.267,-504.854\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZDIVGR -->\n",
       "<g class=\"node\" id=\"node12\"><title>ZDIVGR</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"275,-491 210,-491 210,-455 275,-455 275,-491\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"216.5\" y=\"-468.8\">ZDIVGR</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZDIVGR -->\n",
       "<g class=\"edge\" id=\"edge20\"><title>RFF-&gt;ZDIVGR</title>\n",
       "<path d=\"M174.045,-453.521C182.132,-455.856 191.256,-458.491 200.119,-461.05\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"199.366,-464.476 209.945,-463.888 201.309,-457.751 199.366,-464.476\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RTB -->\n",
       "<g class=\"node\" id=\"node13\"><title>RTB</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-437 215.5,-437 215.5,-401 269.5,-401 269.5,-437\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"228.5\" y=\"-414.8\">RTB</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;RTB -->\n",
       "<g class=\"edge\" id=\"edge16\"><title>RFF-&gt;RTB</title>\n",
       "<path d=\"M174.045,-438.479C183.791,-435.665 195.041,-432.416 205.526,-429.388\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"206.634,-432.711 215.27,-426.574 204.692,-425.986 206.634,-432.711\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RFF(&#45;1) -->\n",
       "<g class=\"node\" id=\"node14\"><title>RFF(-1)</title>\n",
       "<polygon fill=\"springgreen\" points=\"272,-383 213,-383 213,-347 272,-347 272,-383\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"219.5\" y=\"-360.8\">RFF(-1)</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;RFF(&#45;1) -->\n",
       "<g class=\"edge\" id=\"edge17\"><title>RFF-&gt;RFF(-1)</title>\n",
       "<path d=\"M168.631,-427.959C180.675,-417.445 196.175,-403.945 210,-392 210.818,-391.294 211.647,-390.577 212.485,-389.855\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"214.833,-392.452 220.131,-383.277 210.267,-387.146 214.833,-392.452\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZGAP10 -->\n",
       "<g class=\"node\" id=\"node15\"><title>ZGAP10</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"274,-329 211,-329 211,-293 274,-293 274,-329\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"217.5\" y=\"-306.8\">ZGAP10</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZGAP10 -->\n",
       "<g class=\"edge\" id=\"edge13\"><title>RFF-&gt;ZGAP10</title>\n",
       "<path d=\"M155.984,-427.998C166.447,-405.548 186.282,-366.641 210,-338 210.482,-337.418 210.978,-336.837 211.485,-336.26\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"214.092,-338.601 218.573,-329.001 209.083,-333.711 214.092,-338.601\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZPIC30 -->\n",
       "<g class=\"node\" id=\"node17\"><title>ZPIC30</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"271,-275 214,-275 214,-239 271,-239 271,-275\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"220.5\" y=\"-252.8\">ZPIC30</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZPIC30 -->\n",
       "<g class=\"edge\" id=\"edge5\"><title>RFF-&gt;ZPIC30</title>\n",
       "<path d=\"M151.897,-427.578C159.238,-395.954 177.389,-330.279 210,-284 210.27,-283.617 210.546,-283.237 210.828,-282.858\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"213.515,-285.103 217.481,-275.278 208.254,-280.485 213.515,-285.103\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZGAP30 -->\n",
       "<g class=\"node\" id=\"node18\"><title>ZGAP30</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"274,-221 211,-221 211,-185 274,-185 274,-221\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"217.5\" y=\"-198.8\">ZGAP30</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZGAP30 -->\n",
       "<g class=\"edge\" id=\"edge14\"><title>RFF-&gt;ZGAP30</title>\n",
       "<path d=\"M149.678,-427.771C153.998,-388.666 168.259,-295 210,-230 210.253,-229.606 210.513,-229.215 210.781,-228.826\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"213.504,-231.026 217.227,-221.107 208.13,-226.539 213.504,-231.026\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RRFF -->\n",
       "<g class=\"node\" id=\"node20\"><title>RRFF</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"269.5,-167 215.5,-167 215.5,-131 269.5,-131 269.5,-167\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"224.5\" y=\"-144.8\">RRFF</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;RRFF -->\n",
       "<g class=\"edge\" id=\"edge18\"><title>RFF-&gt;RRFF</title>\n",
       "<path d=\"M148.338,-427.833C149.957,-382.155 159.1,-260.159 210,-176 210.242,-175.599 210.493,-175.202 210.75,-174.807\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"213.494,-176.981 217.064,-167.005 208.052,-172.577 213.494,-176.981\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZGAP05 -->\n",
       "<g class=\"node\" id=\"node21\"><title>ZGAP05</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"274,-113 211,-113 211,-77 274,-77 274,-113\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"217.5\" y=\"-90.8\">ZGAP05</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZGAP05 -->\n",
       "<g class=\"edge\" id=\"edge1\"><title>RFF-&gt;ZGAP05</title>\n",
       "<path d=\"M147.429,-427.717C146.624,-375.97 149.943,-225.538 210,-122 210.113,-121.805 210.228,-121.611 210.345,-121.418\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"213.302,-123.314 216.646,-113.261 207.763,-119.035 213.302,-123.314\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- ZRFF30 -->\n",
       "<g class=\"node\" id=\"node22\"><title>ZRFF30</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"273,-59 212,-59 212,-23 273,-23 273,-59\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"218.5\" y=\"-36.8\">ZRFF30</text>\n",
       "</g>\n",
       "<!-- RFF&#45;&gt;ZRFF30 -->\n",
       "<g class=\"edge\" id=\"edge9\"><title>RFF-&gt;ZRFF30</title>\n",
       "<path d=\"M149.344,-427.663C154.49,-360.866 174.464,-131.179 210,-68 210.11,-67.8038 210.223,-67.6084 210.337,-67.4138\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"213.303,-69.2951 216.565,-59.2149 207.729,-65.0607 213.303,-69.2951\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RFFRULE -->\n",
       "<g class=\"node\" id=\"node7\"><title>RFFRULE</title>\n",
       "<polygon fill=\"#63b8ff\" points=\"79.5,-518 4.5,-518 4.5,-482 79.5,-482 79.5,-518\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"11\" y=\"-495.8\">RFFRULE</text>\n",
       "</g>\n",
       "<!-- RFFRULE&#45;&gt;RFF -->\n",
       "<g class=\"edge\" id=\"edge7\"><title>RFFRULE-&gt;RFF</title>\n",
       "<path d=\"M77.584,-481.869C88.2516,-476.276 100.009,-470.112 110.722,-464.495\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"112.584,-467.471 119.815,-459.728 109.333,-461.271 112.584,-467.471\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RFF_AERR -->\n",
       "<g class=\"node\" id=\"node11\"><title>RFF_AERR</title>\n",
       "<polygon fill=\"yellow\" points=\"84,-464 0,-464 0,-428 84,-428 84,-464\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"6\" y=\"-441.8\">RFF_AERR</text>\n",
       "</g>\n",
       "<!-- RFF_AERR&#45;&gt;RFF -->\n",
       "<g class=\"edge\" id=\"edge4\"><title>RFF_AERR-&gt;RFF</title>\n",
       "<path d=\"M84.0043,-446C92.5245,-446 101.445,-446 109.779,-446\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"109.946,-449.5 119.946,-446 109.946,-442.5 109.946,-449.5\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- RFFMIN -->\n",
       "<g class=\"node\" id=\"node16\"><title>RFFMIN</title>\n",
       "<polygon fill=\"yellow\" points=\"74.5,-410 9.5,-410 9.5,-374 74.5,-374 74.5,-410\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"16\" y=\"-387.8\">RFFMIN</text>\n",
       "</g>\n",
       "<!-- RFFMIN&#45;&gt;RFF -->\n",
       "<g class=\"edge\" id=\"edge3\"><title>RFFMIN-&gt;RFF</title>\n",
       "<path d=\"M74.7438,-408.642C86.1242,-414.609 99.0216,-421.371 110.686,-427.486\" fill=\"none\" stroke=\"black\"/>\n",
       "<polygon fill=\"black\" points=\"109.242,-430.68 119.723,-432.224 112.492,-424.481 109.242,-430.68\" stroke=\"black\"/>\n",
       "</g>\n",
       "<!-- DMPTRSH -->\n",
       "<g class=\"node\" id=\"node19\"><title>DMPTRSH</title>\n",
       "<polygon fill=\"yellow\" points=\"81.5,-356 2.5,-356 2.5,-320 81.5,-320 81.5,-356\" stroke=\"black\"/>\n",
       "<text fill=\"blue\" font-family=\"Times New Roman,serif\" font-size=\"14.00\" text-anchor=\"start\" x=\"9\" y=\"-333.8\">DMPTRSH</text>\n",
       "</g>\n",
       "<!-- DMPTRSH&#45;&gt;RFF -->\n",
       "<g class=\"edge\" id=\"edge10\"><title>DMPTRSH-&gt;RFF</title>\n",
       "<path d=\"M73.0063,-356.044C76.861,-358.848 80.6323,-361.863 84,-365 101.275,-381.091 117.372,-402.389 128.832,-419.107\" fill=\"none\" stroke=\"black\"/>\n",
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       "</g>\n",
       "</g>\n",
       "</svg>"
      ],
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = mfrbus.RFF.draw(up=1,down=1,HR=0,svg=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Show causal structure (only current year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2880x2880 with 1 Axes>"
      ]
     },
     "metadata": {
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig   = draw_adjacency_matrix(mfrbus.endograph,mfrbus.precoreepiorder,\n",
    "                                          mfrbus._superstrongblock,mfrbus._superstrongtype,size=(40,40))"
   ]
  }
 ],
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