{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4441f94b",
   "metadata": {},
   "source": [
    "# 03 결과 — 표·그림과 검증\n",
    "\n",
    "02의 산출물만 읽어 본문 표와 그림을 만들고, 마지막 검증 셀에서 본문 수치·4장 공표 수치·보고서1 5장 수치와 대조한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0b0fe339",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:14.750052Z",
     "iopub.status.busy": "2026-10-08T05:49:14.749552Z",
     "iopub.status.idle": "2026-10-08T05:49:15.831550Z",
     "shell.execute_reply": "2026-10-08T05:49:15.831047Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python 3.12.10 · pandas 2.2.3 · numpy 2.4.6 · matplotlib 3.11.0\n",
      "  판: 2026-10 정비판 기준 · Λ 0.5 · 드리프트 목표 1.8% · ONLINE=0(스냅샷) · Event Registry 키 없음\n",
      "  설문 통계표(비공개)    있음  data\\private\\AI수용도조사_통계표_260417.xlsx\n",
      "  설문 원자료(비공개)    있음  data\\private\\AI수용도조사_원자료_n2297.xlsx\n"
     ]
    }
   ],
   "source": [
    "import os, hashlib\n",
    "import numpy as np, pandas as pd\n",
    "import config as C\n",
    "import ai_index as I, ai_varx as X, ai_forecast as F, varx_engine as V, alt_run as R\n",
    "pd.set_option(\"display.float_format\", lambda v: f\"{v:,.3f}\")\n",
    "pd.set_option(\"display.width\", 200)\n",
    "C.setup()\n",
    "import matplotlib.pyplot as plt\n",
    "import koreanize_matplotlib  # noqa: F401  (한글 글꼴)\n",
    "O = lambda f: os.path.join(C.OUTPUT, f)  # noqa: E731\n",
    "comp = pd.read_csv(O(\"ai_index_quarterly.csv\"), index_col=0)\n",
    "ex = pd.read_csv(O(\"ai_exposure_21.csv\"), index_col=0)\n",
    "rho = pd.read_csv(O(\"exposure_rank_corr.csv\"), index_col=0).iloc[:, 0]\n",
    "summ = pd.read_csv(O(\"summary_variants.csv\"), index_col=0)\n",
    "P62 = pd.read_csv(O(\"premium_62_variants.csv\"), index_col=0)\n",
    "diag2 = pd.read_csv(O(\"alt2_diagnostics.csv\"), index_col=0)[\"값\"]\n",
    "bct = pd.read_csv(O(\"alt2_baseline_change.csv\"), index_col=0)\n",
    "dec = pd.read_csv(O(\"spillover_diag.csv\"), index_col=0)\n",
    "chk = pd.read_csv(O(\"model_check.csv\"), index_col=0)[\"값\"]\n",
    "tri = pd.read_csv(O(\"triangulation_rank_corr.csv\"), index_col=0)\n",
    "ktot = pd.read_csv(O(\"keis_r14_total.csv\"), index_col=0)[\"값\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a669d30b",
   "metadata": {},
   "source": [
    "## 표 1. 사양별 AI 확산 효과(2035년, Λ = 0.5%p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "16de164d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:15.832554Z",
     "iopub.status.busy": "2026-10-08T05:49:15.832554Z",
     "iopub.status.idle": "2026-10-08T05:49:15.842601Z",
     "shell.execute_reply": "2026-10-08T05:49:15.842097Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AI 확산 2035(조 원)</th>\n",
       "      <th>기준 대비(조 원)</th>\n",
       "      <th>연평균 차이(%p)</th>\n",
       "      <th>산업 프리미엄 최소(%p)</th>\n",
       "      <th>산업 프리미엄 최대(%p)</th>\n",
       "      <th>음(−)인 산업 수</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사양</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>현행(직접)</th>\n",
       "      <td>2,692.703</td>\n",
       "      <td>83.675</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안1a 설문·장기</th>\n",
       "      <td>2,690.796</td>\n",
       "      <td>81.768</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안1b 노출·장기</th>\n",
       "      <td>2,690.588</td>\n",
       "      <td>81.560</td>\n",
       "      <td>0.314</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.652</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안1c 고용정보원·장기</th>\n",
       "      <td>2,690.570</td>\n",
       "      <td>81.542</td>\n",
       "      <td>0.314</td>\n",
       "      <td>-0.040</td>\n",
       "      <td>0.856</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>참고 노출·직접</th>\n",
       "      <td>2,692.702</td>\n",
       "      <td>83.674</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.388</td>\n",
       "      <td>0.647</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>진단 설문·동시항</th>\n",
       "      <td>2,689.780</td>\n",
       "      <td>80.752</td>\n",
       "      <td>0.311</td>\n",
       "      <td>-0.405</td>\n",
       "      <td>0.906</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안2 설문 표본오차</th>\n",
       "      <td>2,690.798</td>\n",
       "      <td>81.770</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안2 계층(경험적 베이즈)</th>\n",
       "      <td>2,690.798</td>\n",
       "      <td>81.770</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 AI 확산 2035(조 원)  기준 대비(조 원)  연평균 차이(%p)  산업 프리미엄 최소(%p)  산업 프리미엄 최대(%p)  음(−)인 산업 수\n",
       "사양                                                                                                  \n",
       "현행(직접)                 2,692.703      83.675       0.322           0.400           0.620           0\n",
       "대안1a 설문·장기             2,690.796      81.768       0.315           0.393           0.624           0\n",
       "대안1b 노출·장기             2,690.588      81.560       0.314           0.385           0.652           0\n",
       "대안1c 고용정보원·장기          2,690.570      81.542       0.314          -0.040           0.856           1\n",
       "참고 노출·직접               2,692.702      83.674       0.322           0.388           0.647           0\n",
       "진단 설문·동시항              2,689.780      80.752       0.311          -0.405           0.906           9\n",
       "대안2 설문 표본오차            2,690.798      81.770       0.315           0.393           0.624           0\n",
       "대안2 계층(경험적 베이즈)        2,690.798      81.770       0.315           0.393           0.624           0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t1 = summ[[\"AI_2035_조\", \"수준차이_조\", \"차이_%p\", \"프리미엄_최소\", \"프리미엄_최대\", \"음의_산업수\"]].copy()\n",
    "t1.columns = [\"AI 확산 2035(조 원)\", \"기준 대비(조 원)\", \"연평균 차이(%p)\", \"산업 프리미엄 최소(%p)\", \"산업 프리미엄 최대(%p)\", \"음(−)인 산업 수\"]\n",
    "t1.to_csv(O(\"table1_variants.csv\"), encoding=\"utf-8-sig\")\n",
    "display(t1.round(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39e47742",
   "metadata": {},
   "source": [
    "## 표 2. 기존 전망의 변화(기준 시나리오, 미래 AI 갭 0)\n",
    "\n",
    "대안 1은 기존 계수를 그대로 쓰므로 변화가 0이다. 대안 2는 AI 갭을 넣어 다시 추정한 모형의 결과이다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "81b145de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:15.843601Z",
     "iopub.status.busy": "2026-10-08T05:49:15.843601Z",
     "iopub.status.idle": "2026-10-08T05:49:15.849033Z",
     "shell.execute_reply": "2026-10-08T05:49:15.849033Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>바텀업_기존_조</th>\n",
       "      <th>바텀업_재추정_조</th>\n",
       "      <th>바텀업_변화_%</th>\n",
       "      <th>벤치마킹후_최대_%</th>\n",
       "      <th>벤치마킹후_최소_%</th>\n",
       "      <th>벤치마킹후_절대중앙_%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사전분포</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>대안 1(기존 계수 고정)</th>\n",
       "      <td>2,793.745</td>\n",
       "      <td>2,793.745</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안 2(설문 표본오차)</th>\n",
       "      <td>2,793.745</td>\n",
       "      <td>2,786.618</td>\n",
       "      <td>-0.255</td>\n",
       "      <td>0.864</td>\n",
       "      <td>-0.298</td>\n",
       "      <td>0.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>대안 2(계층(경험적 베이즈))</th>\n",
       "      <td>2,793.745</td>\n",
       "      <td>2,786.618</td>\n",
       "      <td>-0.255</td>\n",
       "      <td>0.864</td>\n",
       "      <td>-0.298</td>\n",
       "      <td>0.120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   바텀업_기존_조  바텀업_재추정_조  바텀업_변화_%  벤치마킹후_최대_%  벤치마킹후_최소_%  벤치마킹후_절대중앙_%\n",
       "사전분포                                                                                  \n",
       "대안 1(기존 계수 고정)    2,793.745  2,793.745     0.000       0.000       0.000         0.000\n",
       "대안 2(설문 표본오차)     2,793.745  2,786.618    -0.255       0.864      -0.298         0.120\n",
       "대안 2(계층(경험적 베이즈)) 2,793.745  2,786.618    -0.255       0.864      -0.298         0.120"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t2 = pd.concat([pd.DataFrame([{\"사전분포\": \"대안 1(기존 계수 고정)\", \"바텀업_기존_조\": chk[\"바텀업_2035_조\"], \"바텀업_재추정_조\": chk[\"바텀업_2035_조\"],\n",
    "                               \"바텀업_변화_%\": 0.0, \"벤치마킹후_최대_%\": 0.0, \"벤치마킹후_최소_%\": 0.0, \"벤치마킹후_절대중앙_%\": 0.0}]).set_index(\"사전분포\"),\n",
    "                bct.rename(index=lambda s: f\"대안 2({s})\")])\n",
    "t2.to_csv(O(\"table2_baseline_change.csv\"), encoding=\"utf-8-sig\")\n",
    "display(t2.round(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b383036",
   "metadata": {},
   "source": [
    "## 표 3. 산업별 프리미엄 — 현행과 대안 1b의 차이가 큰 산업(%p)\n",
    "\n",
    "대안 1c(한국고용정보원 2017년 혁신 시나리오 배분)도 함께 싣는다. 업종 순위의 일치 정도는 표 4에 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8120e15e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:15.850537Z",
     "iopub.status.busy": "2026-10-08T05:49:15.850537Z",
     "iopub.status.idle": "2026-10-08T05:49:15.857621Z",
     "shell.execute_reply": "2026-10-08T05:49:15.857116Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>현행(직접)</th>\n",
       "      <th>대안1a 설문·장기</th>\n",
       "      <th>대안1b 노출·장기</th>\n",
       "      <th>대안1c 고용정보원·장기</th>\n",
       "      <th>진단 설문·동시항</th>\n",
       "      <th>1b−현행</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56.교육서비스업</th>\n",
       "      <td>0.580</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.450</td>\n",
       "      <td>-0.040</td>\n",
       "      <td>0.770</td>\n",
       "      <td>-0.140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21.금속가공제품</th>\n",
       "      <td>0.480</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.750</td>\n",
       "      <td>-0.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.가죽제품</th>\n",
       "      <td>0.480</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.220</td>\n",
       "      <td>0.010</td>\n",
       "      <td>-0.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.섬유ㆍ의복</th>\n",
       "      <td>0.480</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.220</td>\n",
       "      <td>-0.050</td>\n",
       "      <td>-0.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17.의료ㆍ의약품</th>\n",
       "      <td>0.490</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.450</td>\n",
       "      <td>-0.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18.고무ㆍ플라스틱제품</th>\n",
       "      <td>0.490</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.470</td>\n",
       "      <td>-0.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36.수상운송업</th>\n",
       "      <td>0.460</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.410</td>\n",
       "      <td>-0.260</td>\n",
       "      <td>0.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38.창고ㆍ운송보조서비스업</th>\n",
       "      <td>0.460</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.410</td>\n",
       "      <td>-0.340</td>\n",
       "      <td>0.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37.항공운송업</th>\n",
       "      <td>0.460</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.410</td>\n",
       "      <td>-0.400</td>\n",
       "      <td>0.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49.부동산업</th>\n",
       "      <td>0.440</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51.연구개발업</th>\n",
       "      <td>0.470</td>\n",
       "      <td>0.470</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.850</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53.과학기술관련전문서비스업</th>\n",
       "      <td>0.470</td>\n",
       "      <td>0.470</td>\n",
       "      <td>0.550</td>\n",
       "      <td>0.860</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 현행(직접)  대안1a 설문·장기  대안1b 노출·장기  대안1c 고용정보원·장기  진단 설문·동시항  1b−현행\n",
       "56.교육서비스업         0.580       0.580       0.450         -0.040      0.770 -0.140\n",
       "21.금속가공제품         0.480       0.450       0.380          0.130      0.750 -0.090\n",
       "10.가죽제품           0.480       0.490       0.400          0.220      0.010 -0.080\n",
       "9.섬유ㆍ의복           0.480       0.490       0.400          0.220     -0.050 -0.080\n",
       "17.의료ㆍ의약품         0.490       0.490       0.420          0.380      0.450 -0.070\n",
       "18.고무ㆍ플라스틱제품      0.490       0.490       0.420          0.390      0.470 -0.070\n",
       "36.수상운송업          0.460       0.480       0.520          0.410     -0.260  0.060\n",
       "38.창고ㆍ운송보조서비스업    0.460       0.480       0.520          0.410     -0.340  0.060\n",
       "37.항공운송업          0.460       0.480       0.520          0.410     -0.400  0.060\n",
       "49.부동산업           0.440       0.430       0.500          0.560      0.500  0.060\n",
       "51.연구개발업          0.470       0.470       0.550          0.850      0.630  0.070\n",
       "53.과학기술관련전문서비스업   0.470       0.470       0.550          0.860      0.630  0.080"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = [\"현행(직접)\", \"대안1a 설문·장기\", \"대안1b 노출·장기\", \"대안1c 고용정보원·장기\", \"진단 설문·동시항\"]\n",
    "d = (P62[\"대안1b 노출·장기\"] - P62[\"현행(직접)\"]).sort_values()\n",
    "t3 = P62.loc[list(d.index[:6]) + list(d.index[-6:]), cols].assign(**{\"1b−현행\": d})\n",
    "t3.to_csv(O(\"table3_premium_diff.csv\"), encoding=\"utf-8-sig\")\n",
    "display(t3.round(2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c125db9",
   "metadata": {},
   "source": [
    "## 표 4. 세 자료의 업종 순위상관(21개 업종, 스피어만)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5e33c1e1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:15.858620Z",
     "iopub.status.busy": "2026-10-08T05:49:15.858124Z",
     "iopub.status.idle": "2026-10-08T05:49:15.862459Z",
     "shell.execute_reply": "2026-10-08T05:49:15.861955Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>설문 E4-1</th>\n",
       "      <th>객관 노출 지수</th>\n",
       "      <th>고용정보원(2017) ΔVA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>설문 E4-1</th>\n",
       "      <td>1.000</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>객관 노출 지수</th>\n",
       "      <td>0.490</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>고용정보원(2017) ΔVA</th>\n",
       "      <td>0.050</td>\n",
       "      <td>0.610</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 설문 E4-1  객관 노출 지수  고용정보원(2017) ΔVA\n",
       "설문 E4-1            1.000     0.490            0.050\n",
       "객관 노출 지수           0.490     1.000            0.610\n",
       "고용정보원(2017) ΔVA    0.050     0.610            1.000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(tri.round(2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24a3f3bf",
   "metadata": {},
   "source": [
    "## 그림 1. AI 확산 총량 지수와 갭"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0366adc4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:15.863459Z",
     "iopub.status.busy": "2026-10-08T05:49:15.862959Z",
     "iopub.status.idle": "2026-10-08T05:49:16.089238Z",
     "shell.execute_reply": "2026-10-08T05:49:16.088733Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x560 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1, figsize=(8, 5.6), sharex=True, gridspec_kw={\"height_ratios\": [2, 1]})\n",
    "x = range(len(comp))\n",
    "for c, s in [(\"특허\", \":\"), (\"논문\", \"--\"), (\"뉴스\", \"-.\")]:\n",
    "    ax[0].plot(x, comp[c], s, lw=1, label=c)\n",
    "ax[0].plot(x, comp[\"총량지수\"], lw=2.2, color=\"k\", label=\"총량 지수\")\n",
    "ax[0].plot(x, comp[\"추세\"], lw=1, color=\"0.5\", label=\"HP 추세\")\n",
    "ax[0].set_ylabel(\"로그 편차(2015–2024 평균 = 0)\"); ax[0].legend(ncol=5, fontsize=8, loc=\"upper left\")\n",
    "ax[1].bar(x, comp[\"갭\"], color=[\"#2b6cb0\" if v >= 0 else \"#c05621\" for v in comp[\"갭\"]])\n",
    "ax[1].axhline(0, color=\"k\", lw=.6); ax[1].set_ylabel(\"갭\")\n",
    "ticks = [i for i, q in enumerate(comp.index) if q.endswith(\"Q1\")]\n",
    "ax[1].set_xticks(ticks); ax[1].set_xticklabels([comp.index[i][:4] for i in ticks], fontsize=8)\n",
    "fig.tight_layout(); fig.savefig(O(\"fig1_ai_index.png\"), dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8380c2f",
   "metadata": {},
   "source": [
    "## 그림 2. 업종별 AI 노출 지수(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bf274e2b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:16.090238Z",
     "iopub.status.busy": "2026-10-08T05:49:16.090238Z",
     "iopub.status.idle": "2026-10-08T05:49:16.239833Z",
     "shell.execute_reply": "2026-10-08T05:49:16.239329Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = ex[\"노출지수_z\"].sort_values()\n",
    "fig, ax = plt.subplots(figsize=(7, 6))\n",
    "ax.barh([s.split(\". \")[1] for s in e.index], e, color=[\"#2b6cb0\" if v >= 0 else \"#a0aec0\" for v in e])\n",
    "ax.axvline(0, color=\"k\", lw=.6); ax.set_xlabel(\"노출 지수(자료원별 z의 평균)\")\n",
    "fig.tight_layout(); fig.savefig(O(\"fig2_exposure.png\"), dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01ad5afa",
   "metadata": {},
   "source": [
    "## 그림 3. 산업별 2035년 프리미엄 — 현행과 대안 비교(62개 산업)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "17bb6452",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:16.241333Z",
     "iopub.status.busy": "2026-10-08T05:49:16.240833Z",
     "iopub.status.idle": "2026-10-08T05:49:16.660825Z",
     "shell.execute_reply": "2026-10-08T05:49:16.660322Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x1100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "o = P62.sort_values(\"현행(직접)\").index\n",
    "fig, ax = plt.subplots(figsize=(8, 11))\n",
    "yy = range(len(o))\n",
    "ax.scatter(P62.loc[o, \"진단 설문·동시항\"], yy, s=14, marker=\"x\", color=\"#c05621\", label=\"진단: 설문·동시항\")\n",
    "ax.scatter(P62.loc[o, \"대안1c 고용정보원·장기\"], yy, s=14, marker=\"^\", color=\"#718096\", label=\"대안 1c: 고용정보원(2017)·장기\")\n",
    "ax.scatter(P62.loc[o, \"대안1b 노출·장기\"], yy, s=16, color=\"#2b6cb0\", label=\"대안 1b: 노출·장기\")\n",
    "ax.scatter(P62.loc[o, \"현행(직접)\"], yy, s=18, facecolors=\"none\", edgecolors=\"k\", label=\"현행(직접)\")\n",
    "ax.set_yticks(list(yy)); ax.set_yticklabels([s.split(\".\", 1)[1][:14] for s in o], fontsize=7)\n",
    "ax.axvline(0, color=\"k\", lw=.6); ax.set_xlabel(\"2035년 AI 프리미엄(연 %p)\"); ax.legend(fontsize=8, loc=\"lower right\")\n",
    "fig.tight_layout(); fig.savefig(O(\"fig3_premium_variants.png\"), dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77107bd8",
   "metadata": {},
   "source": [
    "## 검증\n",
    "\n",
    "1. **4장과의 정합.** '현행(직접)' 사양은 4장 방식과 같은 구조이므로 4장 결과(`config.S4_PUBLISHED`)를 재현해야 한다. 시점 가중치를 분기로 보간하는 차이 때문에 2035년 수준은 1조 원 안에서, 연평균 차이와 산업 프리미엄은 공표 자릿수의 반올림 범위 안에서 같으면 통과로 본다.\n",
    "2. **보고서1과의 정합.** 기존 계수로 다시 낸 바텀업 합계(드리프트 재설정 후)가 보고서1 5장 표의 2,794조 원과 같아야 한다.\n",
    "3. **대안 1의 기존 전망 불변.** 대안 1은 기준 시나리오에서 AI 항이 0이므로 바텀업 변화가 정확히 0이다(표 2 첫 행).\n",
    "4. **본문 수치.** 이 장 본문의 수치(`config.PUBLISHED`)가 계산 결과와 반올림 범위 안에서 같아야 한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fa971655",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-08T05:49:16.661826Z",
     "iopub.status.busy": "2026-10-08T05:49:16.661826Z",
     "iopub.status.idle": "2026-10-08T05:49:16.674729Z",
     "shell.execute_reply": "2026-10-08T05:49:16.674225Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>구분</th>\n",
       "      <th>항목</th>\n",
       "      <th>계산</th>\n",
       "      <th>기준값</th>\n",
       "      <th>허용오차</th>\n",
       "      <th>통과</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4장 정합</td>\n",
       "      <td>AI_2035_조</td>\n",
       "      <td>2,692.703</td>\n",
       "      <td>2,692.220</td>\n",
       "      <td>1.000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4장 정합</td>\n",
       "      <td>AI_차이_%p</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4장 정합</td>\n",
       "      <td>정보통신_프리미엄_%p</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4장 정합</td>\n",
       "      <td>교육_프리미엄_%p</td>\n",
       "      <td>0.584</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4장 정합</td>\n",
       "      <td>문화_프리미엄_%p</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>보고서1 정합</td>\n",
       "      <td>바텀업_2035_조</td>\n",
       "      <td>2,793.745</td>\n",
       "      <td>2,794.000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>본문</td>\n",
       "      <td>1a_차이_%p</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>본문</td>\n",
       "      <td>1b_차이_%p</td>\n",
       "      <td>0.314</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_차이_%p</td>\n",
       "      <td>0.311</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_음의_산업수</td>\n",
       "      <td>9.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_최소_%p</td>\n",
       "      <td>-0.405</td>\n",
       "      <td>-0.400</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_최대_%p</td>\n",
       "      <td>0.906</td>\n",
       "      <td>0.910</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>본문</td>\n",
       "      <td>1b_최소_%p</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>본문</td>\n",
       "      <td>1b_최대_%p</td>\n",
       "      <td>0.652</td>\n",
       "      <td>0.650</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>본문</td>\n",
       "      <td>1a_현행_최대차_%p</td>\n",
       "      <td>0.052</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>본문</td>\n",
       "      <td>1b_교육_차_%p</td>\n",
       "      <td>-0.137</td>\n",
       "      <td>-0.140</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>본문</td>\n",
       "      <td>노출_순위상관</td>\n",
       "      <td>0.491</td>\n",
       "      <td>0.490</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_차이_%p</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_beta_t</td>\n",
       "      <td>0.902</td>\n",
       "      <td>0.900</td>\n",
       "      <td>0.050</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_유의_산업수</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_tau2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_바텀업_변화_%</td>\n",
       "      <td>-0.255</td>\n",
       "      <td>-0.260</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_벤치_최대_%</td>\n",
       "      <td>0.864</td>\n",
       "      <td>0.860</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_벤치_최소_%</td>\n",
       "      <td>-0.298</td>\n",
       "      <td>-0.300</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>본문</td>\n",
       "      <td>지수_2015Q1</td>\n",
       "      <td>-1.534</td>\n",
       "      <td>-1.530</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>본문</td>\n",
       "      <td>지수_2025Q4</td>\n",
       "      <td>1.242</td>\n",
       "      <td>1.240</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>본문</td>\n",
       "      <td>교차계수_음수비율</td>\n",
       "      <td>0.459</td>\n",
       "      <td>0.460</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>본문</td>\n",
       "      <td>1c_차이_%p</td>\n",
       "      <td>0.314</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>본문</td>\n",
       "      <td>1c_최소_%p</td>\n",
       "      <td>-0.040</td>\n",
       "      <td>-0.040</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>본문</td>\n",
       "      <td>1c_최대_%p</td>\n",
       "      <td>0.856</td>\n",
       "      <td>0.860</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>본문</td>\n",
       "      <td>고용정보원_전산업_%p</td>\n",
       "      <td>0.467</td>\n",
       "      <td>0.470</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>본문</td>\n",
       "      <td>순위상관_설문_고용정보원</td>\n",
       "      <td>0.051</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>본문</td>\n",
       "      <td>순위상관_노출_고용정보원</td>\n",
       "      <td>0.610</td>\n",
       "      <td>0.610</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>본문</td>\n",
       "      <td>1a_최소_%p</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>본문</td>\n",
       "      <td>1a_최대_%p</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_최소_%p</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_최대_%p</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>본문</td>\n",
       "      <td>1c_음의_산업수</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>본문</td>\n",
       "      <td>1c_연구개발_%p</td>\n",
       "      <td>0.854</td>\n",
       "      <td>0.850</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>본문</td>\n",
       "      <td>노출_정보통신</td>\n",
       "      <td>2.023</td>\n",
       "      <td>2.020</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>본문</td>\n",
       "      <td>노출_음식숙박</td>\n",
       "      <td>-1.305</td>\n",
       "      <td>-1.310</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>본문</td>\n",
       "      <td>노출_교육</td>\n",
       "      <td>-0.436</td>\n",
       "      <td>-0.440</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_항공운송_%p</td>\n",
       "      <td>-0.405</td>\n",
       "      <td>-0.400</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>본문</td>\n",
       "      <td>진단_장기음수_산업수</td>\n",
       "      <td>10.000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_자료비중_최대</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>본문</td>\n",
       "      <td>대안2_beta</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.005</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         구분             항목        계산       기준값  허용오차    통과\n",
       "0     4장 정합      AI_2035_조 2,692.703 2,692.220 1.000  True\n",
       "1     4장 정합       AI_차이_%p     0.322     0.320 0.005  True\n",
       "2     4장 정합   정보통신_프리미엄_%p     0.620     0.620 0.005  True\n",
       "3     4장 정합     교육_프리미엄_%p     0.584     0.580 0.005  True\n",
       "4     4장 정합     문화_프리미엄_%p     0.400     0.400 0.005  True\n",
       "5   보고서1 정합     바텀업_2035_조 2,793.745 2,794.000 0.500  True\n",
       "6        본문       1a_차이_%p     0.315     0.310 0.005  True\n",
       "7        본문       1b_차이_%p     0.314     0.310 0.005  True\n",
       "8        본문       진단_차이_%p     0.311     0.310 0.005  True\n",
       "9        본문      진단_음의_산업수     9.000     9.000 0.500  True\n",
       "10       본문       진단_최소_%p    -0.405    -0.400 0.005  True\n",
       "11       본문       진단_최대_%p     0.906     0.910 0.005  True\n",
       "12       본문       1b_최소_%p     0.385     0.380 0.005  True\n",
       "13       본문       1b_최대_%p     0.652     0.650 0.005  True\n",
       "14       본문   1a_현행_최대차_%p     0.052     0.050 0.005  True\n",
       "15       본문     1b_교육_차_%p    -0.137    -0.140 0.005  True\n",
       "16       본문        노출_순위상관     0.491     0.490 0.005  True\n",
       "17       본문      대안2_차이_%p     0.315     0.310 0.005  True\n",
       "18       본문     대안2_beta_t     0.902     0.900 0.050  True\n",
       "19       본문     대안2_유의_산업수     1.000     1.000 0.500  True\n",
       "20       본문       대안2_tau2     0.000     0.000 0.005  True\n",
       "21       본문   대안2_바텀업_변화_%    -0.255    -0.260 0.005  True\n",
       "22       본문    대안2_벤치_최대_%     0.864     0.860 0.005  True\n",
       "23       본문    대안2_벤치_최소_%    -0.298    -0.300 0.005  True\n",
       "24       본문      지수_2015Q1    -1.534    -1.530 0.005  True\n",
       "25       본문      지수_2025Q4     1.242     1.240 0.005  True\n",
       "26       본문      교차계수_음수비율     0.459     0.460 0.005  True\n",
       "27       본문       1c_차이_%p     0.314     0.310 0.005  True\n",
       "28       본문       1c_최소_%p    -0.040    -0.040 0.005  True\n",
       "29       본문       1c_최대_%p     0.856     0.860 0.005  True\n",
       "30       본문   고용정보원_전산업_%p     0.467     0.470 0.005  True\n",
       "31       본문  순위상관_설문_고용정보원     0.051     0.050 0.005  True\n",
       "32       본문  순위상관_노출_고용정보원     0.610     0.610 0.005  True\n",
       "33       본문       1a_최소_%p     0.393     0.390 0.005  True\n",
       "34       본문       1a_최대_%p     0.624     0.620 0.005  True\n",
       "35       본문      대안2_최소_%p     0.393     0.390 0.005  True\n",
       "36       본문      대안2_최대_%p     0.624     0.620 0.005  True\n",
       "37       본문      1c_음의_산업수     1.000     1.000 0.500  True\n",
       "38       본문     1c_연구개발_%p     0.854     0.850 0.005  True\n",
       "39       본문        노출_정보통신     2.023     2.020 0.005  True\n",
       "40       본문        노출_음식숙박    -1.305    -1.310 0.005  True\n",
       "41       본문          노출_교육    -0.436    -0.440 0.005  True\n",
       "42       본문     진단_항공운송_%p    -0.405    -0.400 0.005  True\n",
       "43       본문    진단_장기음수_산업수    10.000    10.000 0.500  True\n",
       "44       본문    대안2_자료비중_최대     0.000     0.000 0.001  True\n",
       "45       본문       대안2_beta     0.080     0.080 0.005  True"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "검증 통과: 4장 정합 5개, 보고서1 정합 1개, 본문 40개 — 모두 46개 항목이 반올림 범위 안에서 일치한다.\n"
     ]
    }
   ],
   "source": [
    "def p62(prefix, col=\"현행(직접)\"):\n",
    "    return float(P62.loc[[c for c in P62.index if c.startswith(prefix)], col].iloc[0])\n",
    "s = summ\n",
    "calc4 = {\"AI_2035_조\": s.loc[\"현행(직접)\", \"AI_2035_조\"], \"AI_차이_%p\": s.loc[\"현행(직접)\", \"차이_%p\"],\n",
    "         \"정보통신_프리미엄_%p\": p62(\"44.\"), \"교육_프리미엄_%p\": p62(\"56.\"), \"문화_프리미엄_%p\": p62(\"59.\")}\n",
    "rows = [{\"구분\": \"4장 정합\", \"항목\": k, \"계산\": calc4[k], \"기준값\": v, \"허용오차\": tol} for k, (v, tol) in C.S4_PUBLISHED.items()]\n",
    "v5, dg5 = C.S5_BOTTOMUP_2035_조\n",
    "rows.append({\"구분\": \"보고서1 정합\", \"항목\": \"바텀업_2035_조\", \"계산\": chk[\"바텀업_2035_조\"], \"기준값\": v5, \"허용오차\": C.tolerance(dg5)})\n",
    "calc = {\n",
    "    \"1a_차이_%p\": s.loc[\"대안1a 설문·장기\", \"차이_%p\"], \"1b_차이_%p\": s.loc[\"대안1b 노출·장기\", \"차이_%p\"],\n",
    "    \"진단_차이_%p\": s.loc[\"진단 설문·동시항\", \"차이_%p\"], \"진단_음의_산업수\": s.loc[\"진단 설문·동시항\", \"음의_산업수\"],\n",
    "    \"진단_최소_%p\": s.loc[\"진단 설문·동시항\", \"프리미엄_최소\"], \"진단_최대_%p\": s.loc[\"진단 설문·동시항\", \"프리미엄_최대\"],\n",
    "    \"1b_최소_%p\": s.loc[\"대안1b 노출·장기\", \"프리미엄_최소\"], \"1b_최대_%p\": s.loc[\"대안1b 노출·장기\", \"프리미엄_최대\"],\n",
    "    \"1a_현행_최대차_%p\": (P62[\"대안1a 설문·장기\"] - P62[\"현행(직접)\"]).abs().max(),\n",
    "    \"1b_교육_차_%p\": p62(\"56.\", \"대안1b 노출·장기\") - p62(\"56.\"),\n",
    "    \"노출_순위상관\": rho[\"노출 지수\"],\n",
    "    \"대안2_차이_%p\": s.loc[\"대안2 설문 표본오차\", \"차이_%p\"],\n",
    "    \"대안2_beta_t\": diag2[\"beta_t\"], \"대안2_유의_산업수\": diag2[\"유의(|t|>1.96)_산업수\"], \"대안2_tau2\": diag2[\"tau2_계층\"],\n",
    "    \"대안2_바텀업_변화_%\": bct.loc[\"설문 표본오차\", \"바텀업_변화_%\"],\n",
    "    \"대안2_벤치_최대_%\": bct.loc[\"설문 표본오차\", \"벤치마킹후_최대_%\"], \"대안2_벤치_최소_%\": bct.loc[\"설문 표본오차\", \"벤치마킹후_최소_%\"],\n",
    "    \"지수_2015Q1\": comp[\"총량지수\"].iloc[0], \"지수_2025Q4\": comp[\"총량지수\"].iloc[-1],\n",
    "    \"교차계수_음수비율\": chk[\"교차계수_음수비율\"],\n",
    "    \"1c_차이_%p\": s.loc[\"대안1c 고용정보원·장기\", \"차이_%p\"], \"1c_최소_%p\": s.loc[\"대안1c 고용정보원·장기\", \"프리미엄_최소\"],\n",
    "    \"1c_최대_%p\": s.loc[\"대안1c 고용정보원·장기\", \"프리미엄_최대\"], \"고용정보원_전산업_%p\": float(ktot[\"전산업_KIET_3구간평균\"]),\n",
    "    \"순위상관_설문_고용정보원\": tri.loc[\"설문 E4-1\", \"고용정보원(2017) ΔVA\"], \"순위상관_노출_고용정보원\": tri.loc[\"객관 노출 지수\", \"고용정보원(2017) ΔVA\"],\n",
    "    \"1a_최소_%p\": s.loc[\"대안1a 설문·장기\", \"프리미엄_최소\"], \"1a_최대_%p\": s.loc[\"대안1a 설문·장기\", \"프리미엄_최대\"],\n",
    "    \"대안2_최소_%p\": s.loc[\"대안2 설문 표본오차\", \"프리미엄_최소\"], \"대안2_최대_%p\": s.loc[\"대안2 설문 표본오차\", \"프리미엄_최대\"],\n",
    "    \"1c_음의_산업수\": s.loc[\"대안1c 고용정보원·장기\", \"음의_산업수\"], \"1c_연구개발_%p\": p62(\"51.\", \"대안1c 고용정보원·장기\"),\n",
    "    \"노출_정보통신\": ex.loc[\"13. 정보통신\", \"노출지수_z\"], \"노출_음식숙박\": ex.loc[\"15. 음식숙박\", \"노출지수_z\"], \"노출_교육\": ex.loc[\"19. 교육\", \"노출지수_z\"],\n",
    "    \"진단_항공운송_%p\": p62(\"37.\", \"진단 설문·동시항\"), \"진단_장기음수_산업수\": int((dec[\"합계_장기\"] < 0).sum()),\n",
    "    \"대안2_자료비중_최대\": diag2[\"자료비중_최대[설문 표본오차]\"],\n",
    "    \"대안2_beta\": diag2[\"beta\"],\n",
    "}\n",
    "assert set(calc) == set(C.PUBLISHED), \"검증 항목과 본문 수치 항목이 다르다: \" + str(set(calc) ^ set(C.PUBLISHED))\n",
    "for k, (v, dg) in C.PUBLISHED.items():\n",
    "    rows.append({\"구분\": \"본문\", \"항목\": k, \"계산\": calc[k], \"기준값\": v, \"허용오차\": C.tolerance(dg)})\n",
    "res = pd.DataFrame(rows)\n",
    "res[\"통과\"] = (res[\"계산\"] - res[\"기준값\"]).abs() <= res[\"허용오차\"] + 1e-12\n",
    "res.to_csv(O(\"verification.csv\"), index=False, encoding=\"utf-8-sig\")\n",
    "display(res)\n",
    "assert res[\"통과\"].all(), \"공표 수치와 계산 결과가 다르다 — 위 표에서 통과=False 항목을 확인한다\"\n",
    "print(f\"검증 통과: 4장 정합 {len(C.S4_PUBLISHED)}개, 보고서1 정합 1개, 본문 {len(C.PUBLISHED)}개 — 모두 {len(res)}개 항목이 반올림 범위 안에서 일치한다.\")"
   ]
  }
 ],
 "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": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
