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16 | 16 | },
|
17 | 17 | {
|
18 | 18 | "cell_type": "code",
|
19 |
| - "execution_count": null, |
20 | 19 | "metadata": {},
|
21 |
| - "outputs": [], |
22 | 20 | "source": [
|
23 | 21 | "import copy\n",
|
24 | 22 | "\n",
|
|
30 | 28 | " compute_taxes_and_transfers,\n",
|
31 | 29 | " create_synthetic_data,\n",
|
32 | 30 | ")"
|
33 |
| - ] |
| 31 | + ], |
| 32 | + "outputs": [], |
| 33 | + "execution_count": null |
34 | 34 | },
|
35 | 35 | {
|
36 | 36 | "cell_type": "markdown",
|
|
56 | 56 | },
|
57 | 57 | {
|
58 | 58 | "cell_type": "code",
|
59 |
| - "execution_count": null, |
60 | 59 | "metadata": {},
|
61 |
| - "outputs": [], |
62 | 60 | "source": [
|
63 | 61 | "environment = PolicyEnvironment.for_date(\"2020\")"
|
64 |
| - ] |
| 62 | + ], |
| 63 | + "outputs": [], |
| 64 | + "execution_count": null |
65 | 65 | },
|
66 | 66 | {
|
67 | 67 | "cell_type": "markdown",
|
|
74 | 74 | },
|
75 | 75 | {
|
76 | 76 | "cell_type": "code",
|
77 |
| - "execution_count": null, |
78 | 77 | "metadata": {},
|
79 |
| - "outputs": [], |
80 | 78 | "source": [
|
81 | 79 | "print(*environment.params.keys(), sep=\"\\n\")"
|
82 |
| - ] |
| 80 | + ], |
| 81 | + "outputs": [], |
| 82 | + "execution_count": null |
83 | 83 | },
|
84 | 84 | {
|
85 | 85 | "cell_type": "markdown",
|
|
90 | 90 | },
|
91 | 91 | {
|
92 | 92 | "cell_type": "code",
|
93 |
| - "execution_count": null, |
94 | 93 | "metadata": {},
|
95 |
| - "outputs": [], |
96 | 94 | "source": [
|
97 | 95 | "print(*environment.params[\"kindergeld\"].keys(), sep=\"\\n\")"
|
98 |
| - ] |
| 96 | + ], |
| 97 | + "outputs": [], |
| 98 | + "execution_count": null |
99 | 99 | },
|
100 | 100 | {
|
101 | 101 | "cell_type": "markdown",
|
|
116 | 116 | },
|
117 | 117 | {
|
118 | 118 | "cell_type": "code",
|
119 |
| - "execution_count": null, |
120 | 119 | "metadata": {},
|
121 |
| - "outputs": [], |
122 | 120 | "source": [
|
123 | 121 | "environment.params[\"kindergeld\"][\"kindergeld\"]"
|
124 |
| - ] |
| 122 | + ], |
| 123 | + "outputs": [], |
| 124 | + "execution_count": null |
125 | 125 | },
|
126 | 126 | {
|
127 | 127 | "cell_type": "markdown",
|
|
136 | 136 | },
|
137 | 137 | {
|
138 | 138 | "cell_type": "code",
|
139 |
| - "execution_count": null, |
140 | 139 | "metadata": {},
|
141 |
| - "outputs": [], |
142 | 140 | "source": [
|
143 | 141 | "policy_params_new = copy.deepcopy(environment.params)"
|
144 |
| - ] |
| 142 | + ], |
| 143 | + "outputs": [], |
| 144 | + "execution_count": null |
145 | 145 | },
|
146 | 146 | {
|
147 | 147 | "cell_type": "markdown",
|
|
152 | 152 | },
|
153 | 153 | {
|
154 | 154 | "cell_type": "code",
|
155 |
| - "execution_count": null, |
156 | 155 | "metadata": {},
|
157 |
| - "outputs": [], |
158 | 156 | "source": [
|
159 | 157 | "# Loop through policy paramaters to add the special child bonus.\n",
|
160 | 158 | "for n in policy_params_new[\"kindergeld\"][\"kindergeld\"]:\n",
|
161 | 159 | " policy_params_new[\"kindergeld\"][\"kindergeld\"][n] += 20"
|
162 |
| - ] |
| 160 | + ], |
| 161 | + "outputs": [], |
| 162 | + "execution_count": null |
163 | 163 | },
|
164 | 164 | {
|
165 | 165 | "cell_type": "markdown",
|
|
170 | 170 | },
|
171 | 171 | {
|
172 | 172 | "cell_type": "code",
|
173 |
| - "execution_count": null, |
174 | 173 | "metadata": {},
|
175 |
| - "outputs": [], |
176 | 174 | "source": [
|
177 | 175 | "policy_params_new[\"kindergeld\"][\"kindergeld\"]"
|
178 |
| - ] |
| 176 | + ], |
| 177 | + "outputs": [], |
| 178 | + "execution_count": null |
179 | 179 | },
|
180 | 180 | {
|
181 | 181 | "cell_type": "markdown",
|
|
195 | 195 | },
|
196 | 196 | {
|
197 | 197 | "cell_type": "code",
|
198 |
| - "execution_count": null, |
199 | 198 | "metadata": {},
|
200 |
| - "outputs": [], |
201 | 199 | "source": [
|
202 | 200 | "data = create_synthetic_data(\n",
|
203 | 201 | " n_adults=2,\n",
|
|
224 | 222 | " \"sum_ges_rente_priv_rente_m\"\n",
|
225 | 223 | "]\n",
|
226 | 224 | "data.head()"
|
227 |
| - ] |
| 225 | + ], |
| 226 | + "outputs": [], |
| 227 | + "execution_count": null |
228 | 228 | },
|
229 | 229 | {
|
230 | 230 | "attachments": {},
|
|
238 | 238 | },
|
239 | 239 | {
|
240 | 240 | "cell_type": "code",
|
241 |
| - "execution_count": null, |
242 | 241 | "metadata": {},
|
243 |
| - "outputs": [], |
244 | 242 | "source": [
|
245 | 243 | "kindergeld_status_quo = compute_taxes_and_transfers(\n",
|
246 | 244 | " data=data,\n",
|
|
249 | 247 | ")\n",
|
250 | 248 | "\n",
|
251 | 249 | "kindergeld_status_quo[[\"kindergeld_m_hh\"]]"
|
252 |
| - ] |
| 250 | + ], |
| 251 | + "outputs": [], |
| 252 | + "execution_count": null |
253 | 253 | },
|
254 | 254 | {
|
255 | 255 | "cell_type": "markdown",
|
|
260 | 260 | },
|
261 | 261 | {
|
262 | 262 | "cell_type": "code",
|
263 |
| - "execution_count": null, |
264 | 263 | "metadata": {},
|
265 |
| - "outputs": [], |
266 | 264 | "source": [
|
267 |
| - "environment_new = PolicyEnvironment(environment.functions, policy_params_new)\n", |
| 265 | + "environment_new = environment.replace_all_parameters(policy_params_new)\n", |
268 | 266 | "kindergeld_new = compute_taxes_and_transfers(\n",
|
269 | 267 | " data=data,\n",
|
270 | 268 | " environment=environment_new,\n",
|
271 | 269 | " targets=\"kindergeld_m_hh\",\n",
|
272 | 270 | ")\n",
|
273 | 271 | "kindergeld_new[[\"kindergeld_m_hh\"]]"
|
274 |
| - ] |
| 272 | + ], |
| 273 | + "outputs": [], |
| 274 | + "execution_count": null |
275 | 275 | },
|
276 | 276 | {
|
277 | 277 | "cell_type": "markdown",
|
|
284 | 284 | },
|
285 | 285 | {
|
286 | 286 | "cell_type": "code",
|
287 |
| - "execution_count": null, |
288 | 287 | "metadata": {},
|
289 |
| - "outputs": [], |
290 | 288 | "source": [
|
291 | 289 | "# Group data by household id and sum the gross monthly income.\n",
|
292 | 290 | "total_income_m_hh = data.groupby(\"hh_id\")[\"bruttolohn_m\"].sum()\n",
|
293 | 291 | "total_income_m_hh.tail(10)"
|
294 |
| - ] |
| 292 | + ], |
| 293 | + "outputs": [], |
| 294 | + "execution_count": null |
295 | 295 | },
|
296 | 296 | {
|
297 | 297 | "cell_type": "code",
|
298 |
| - "execution_count": null, |
299 | 298 | "metadata": {},
|
300 |
| - "outputs": [], |
301 | 299 | "source": [
|
302 | 300 | "# Create DataFrame with relevant columns for plotting.\n",
|
303 | 301 | "df = pd.DataFrame()\n",
|
|
306 | 304 | "df[\"hh_id\"] = data[\"hh_id\"]\n",
|
307 | 305 | "df = df.drop_duplicates(\"hh_id\").set_index(\"hh_id\")\n",
|
308 | 306 | "df[\"Income (per household)\"] = total_income_m_hh"
|
309 |
| - ] |
| 307 | + ], |
| 308 | + "outputs": [], |
| 309 | + "execution_count": null |
310 | 310 | },
|
311 | 311 | {
|
312 | 312 | "cell_type": "markdown",
|
|
317 | 317 | },
|
318 | 318 | {
|
319 | 319 | "cell_type": "code",
|
320 |
| - "execution_count": null, |
321 | 320 | "metadata": {},
|
322 |
| - "outputs": [], |
323 | 321 | "source": [
|
324 | 322 | "fig = px.line(\n",
|
325 | 323 | " data_frame=df,\n",
|
|
331 | 329 | " xaxis_title=\"Monthly gross income in € (per household)\",\n",
|
332 | 330 | " yaxis_title=\"Kindergeld in € per month\",\n",
|
333 | 331 | ")"
|
334 |
| - ] |
| 332 | + ], |
| 333 | + "outputs": [], |
| 334 | + "execution_count": null |
335 | 335 | },
|
336 | 336 | {
|
337 | 337 | "cell_type": "markdown",
|
|
354 | 354 | "name": "python",
|
355 | 355 | "nbconvert_exporter": "python",
|
356 | 356 | "pygments_lexer": "ipython3"
|
| 357 | + }, |
| 358 | + "kernelspec": { |
| 359 | + "name": "python3", |
| 360 | + "language": "python", |
| 361 | + "display_name": "Python 3 (ipykernel)" |
357 | 362 | }
|
358 | 363 | },
|
359 | 364 | "nbformat": 4,
|
|
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