{ "cells": [ { "cell_type": "markdown", "id": "eeac2bf2", "metadata": {}, "source": [ "# 03 결과 도출 — 원고 표·그림, 제출용 엑셀, 검증\n", "\n", "`02_분석.ipynb`의 산출물로 원고 「전망치」 장의 표 1–4, 그림 1–2, 제출용 엑셀을 만들고, 정비 전후 비교표(표 5)를 낸다.\n", "마지막 셀은 정비판 공표 수치(`config.PUBLISHED`)와 계산 결과를 대조하고, 같은 계산을 이전 판 기준 시나리오에 적용한 결과가\n", "이전 판 공표 수치(`config.PREVIOUS`)를 재현하는지 확인한다(반올림 범위 안에서 일치해야 통과).\n", "\n", "**2026-10 정비판.** 보고서1의 기준 시나리오가 정비되었다. BOKDPM 장기 정상상태를 고치고(잠재성장률 1.8%, 물가안정목표 2%, 실질유가 불변),\n", "실질금리를 1차 차분으로 투입하며, 시나리오 외생 경로의 레버를 연결한 뒤 산업 전망과 정합화를 다시 실행한 결과이다.\n", "이 판은 그 기준 시나리오(`data/inputs/base_va_62.csv`·`base_va_69.csv`)만 교체하였고, **AI 확산 층(산업 배분 A1, Λ 보정, 고용 중립 취업계수)은 이전 판과 같다.**\n", "이전 판 기준 시나리오는 `data/published_prev/`에 두고 정비 전후 비교와 이전 판 재현 점검에만 쓴다." ] }, { "cell_type": "code", "execution_count": 1, "id": "01ae1bbb", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:27.213083Z", "iopub.status.busy": "2026-10-08T00:08:27.212585Z", "iopub.status.idle": "2026-10-08T00:08:28.082381Z", "shell.execute_reply": "2026-10-08T00:08:28.081877Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python 3.12.10 · pandas 2.2.3 · numpy 2.4.6 · openpyxl 3.1.5 · matplotlib 3.11.0\n", " 판: 2026-10 정비판 · 배분 A1 · 취업계수 neutral · Λ 중심 0.5\n", " 기준 62 있음 data\\inputs\\base_va_62.csv\n", " 기준 69 있음 data\\inputs\\base_va_69.csv\n", " 이전 판 기준 62 있음 data\\published_prev\\base_va_62_prev.csv\n", " 이전 판 기준 69 있음 data\\published_prev\\base_va_69_prev.csv\n", " 크로스워크 있음 data\\crosswalk_21_62.csv\n", " 분화표 있음 data\\carveout_69.csv\n", " 설문 통계표(비공개) 있음 data\\private\\AI수용도조사_통계표_260417.xlsx\n" ] } ], "source": [ "import os, hashlib\n", "import numpy as np, pandas as pd\n", "import config as C\n", "import ai_forecast as F\n", "pd.set_option(\"display.float_format\", lambda v: f\"{v:,.3f}\")\n", "C.setup()\n", "import matplotlib.pyplot as plt\n", "import koreanize_matplotlib # noqa: F401 (한글 글꼴)\n", "sens = pd.read_csv(os.path.join(C.OUTPUT, \"lambda_sensitivity.csv\"))\n", "va62 = pd.read_csv(os.path.join(C.OUTPUT, \"ai_va_62.csv\"))\n", "va69 = pd.read_csv(os.path.join(C.OUTPUT, \"ai_va_69.csv\"))\n", "lab62 = pd.read_csv(os.path.join(C.OUTPUT, \"ai_premium_labor_62.csv\"), index_col=0)\n", "lab69 = pd.read_csv(os.path.join(C.OUTPUT, \"ai_premium_labor_69.csv\"), index_col=0)\n", "var = pd.read_csv(os.path.join(C.OUTPUT, \"allocation_variants.csv\"), index_col=0)\n", "cmp = pd.read_csv(os.path.join(C.OUTPUT, \"compare_prev.csv\"))\n", "tot = va62.groupby([\"시나리오\", \"연도\"])[\"실질VA_십억원\"].sum().unstack(0) / 1e3" ] }, { "cell_type": "markdown", "id": "e7bcd211", "metadata": {}, "source": [ "## 표 1. 시나리오별 전산업 실질부가가치 전망" ] }, { "cell_type": "code", "execution_count": 2, "id": "c46ba7da", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.083380Z", "iopub.status.busy": "2026-10-08T00:08:28.083380Z", "iopub.status.idle": "2026-10-08T00:08:28.129825Z", "shell.execute_reply": "2026-10-08T00:08:28.129320Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

시나리오	2025(조원)	2035(조원)	연평균(%)	기준 대비(%p)
기준	2,178	2,609	1.82	+0.00
AI 확산(Λ=0.3)	2,178	2,659	2.01	+0.19
AI 확산(Λ=0.5)	2,178	2,692	2.14	+0.32
AI 확산(Λ=0.8)	2,178	2,743	2.33	+0.51

\n" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "b25, b35 = tot.loc[C.START, \"기준(S1)\"], tot.loc[C.END, \"기준(S1)\"]\n", "t1 = [{\"시나리오\": \"기준\", \"2025(조원)\": b25, \"2035(조원)\": b35, \"연평균(%)\": F.cagr(b25, b35, 10), \"기준 대비(%p)\": 0.0}]\n", "for _, r in sens.iterrows():\n", " t1.append({\"시나리오\": f\"AI 확산(Λ={r['Λ(%p)']:.1f})\", \"2025(조원)\": b25, \"2035(조원)\": r[\"2035 AI확산(조원)\"],\n", " \"연평균(%)\": r[\"CAGR(%)\"], \"기준 대비(%p)\": r[\"기준 대비(%p)\"]})\n", "t1 = pd.DataFrame(t1)\n", "t1.to_csv(os.path.join(C.OUTPUT, \"table1_totals.csv\"), index=False, encoding=\"utf-8-sig\")\n", "t1.style.format({\"2025(조원)\": \"{:,.0f}\", \"2035(조원)\": \"{:,.0f}\", \"연평균(%)\": \"{:.2f}\", \"기준 대비(%p)\": \"{:+.2f}\"}).hide(axis=\"index\")" ] }, { "cell_type": "markdown", "id": "6cee1ff3", "metadata": {}, "source": [ "## 표 2. 산업별 AI 부가가치 프리미엄(2035년, 연 %p) — 상·하위" ] }, { "cell_type": "code", "execution_count": 3, "id": "cb6a2b0c", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.130824Z", "iopub.status.busy": "2026-10-08T00:08:28.130824Z", "iopub.status.idle": "2026-10-08T00:08:28.136337Z", "shell.execute_reply": "2026-10-08T00:08:28.136337Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

	구분	AI 프리미엄(%p)
산업
44.컴퓨터 프로그래밍ㆍ시스템통합관리업	상위	+0.62
45.정보서비스업	상위	+0.62
40.출판업	상위	+0.62
41.영상ㆍ오디오기록물제작 배급업	상위	+0.62
42.방송업	상위	+0.62
43.통신업	상위	+0.62
56.교육서비스업	상위	+0.58
23.의료ㆍ정밀ㆍ광학기기ㆍ시계	상위	+0.56
39.음식점ㆍ숙박업	하위	+0.43
33.건설업	하위	+0.42
59.문화서비스업	하위	+0.40
60.스포츠ㆍ오락서비스업	하위	+0.40
62.수리ㆍ개인서비스업	하위	+0.40

\n" ], "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "p = lab62[\"VA프리미엄_2035_%p\"].sort_values(ascending=False)\n", "t2 = pd.concat([p.head(8).rename(\"AI 프리미엄(%p)\").to_frame().assign(구분=\"상위\"),\n", " p.tail(5).rename(\"AI 프리미엄(%p)\").to_frame().assign(구분=\"하위\")])\n", "t2.to_csv(os.path.join(C.OUTPUT, \"table2_premium_top_bottom.csv\"), encoding=\"utf-8-sig\")\n", "t2[[\"구분\", \"AI 프리미엄(%p)\"]].style.format({\"AI 프리미엄(%p)\": \"{:+.2f}\"})" ] }, { "cell_type": "markdown", "id": "ea1bade7", "metadata": {}, "source": [ "## 그림 1. 기준 대 AI 확산 전산업 부가가치 경로(2025–2035)" ] }, { "cell_type": "code", "execution_count": 4, "id": "b70feece", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.137337Z", "iopub.status.busy": "2026-10-08T00:08:28.137337Z", "iopub.status.idle": "2026-10-08T00:08:28.260692Z", "shell.execute_reply": "2026-10-08T00:08:28.260692Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8, 4.2))\n", "yrs = tot.index\n", "ax.plot(yrs, tot[\"기준(S1)\"], marker=\"o\", color=\"#1f4e79\", label=\"기준\")\n", "ax.plot(yrs, tot[\"AI확산(Λ=0.5)\"], marker=\"o\", color=\"#a9781f\", label=\"AI 확산(Λ=0.5)\")\n", "ax.set_ylabel(\"조 원(2020년 연쇄가격)\"); ax.grid(alpha=.3); ax.legend(frameon=False)\n", "ax.set_title(\"전산업 실질부가가치: 기준 대 AI 확산\", loc=\"left\")\n", "fig.tight_layout(); fig.savefig(os.path.join(C.OUTPUT, \"fig1_paths.png\"), dpi=150)" ] }, { "cell_type": "markdown", "id": "366ce0b4", "metadata": {}, "source": [ "## 그림 2. 62개 산업 AI 부가가치 프리미엄(2035년)" ] }, { "cell_type": "code", "execution_count": 5, "id": "ea987e7f", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.261692Z", "iopub.status.busy": "2026-10-08T00:08:28.261692Z", "iopub.status.idle": "2026-10-08T00:08:28.642063Z", "shell.execute_reply": "2026-10-08T00:08:28.641558Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "q = lab62[\"VA프리미엄_2035_%p\"].sort_values()\n", "fig, ax = plt.subplots(figsize=(8, 11))\n", "ax.barh([s.split(\".\", 1)[1] for s in q.index], q.values, color=\"#1f4e79\")\n", "ax.set_xlabel(\"연 %p\"); ax.grid(axis=\"x\", alpha=.3); ax.tick_params(axis=\"y\", labelsize=7)\n", "ax.set_title(\"산업별 AI 부가가치 프리미엄(중심 Λ=0.5, 2035)\", loc=\"left\")\n", "fig.tight_layout(); fig.savefig(os.path.join(C.OUTPUT, \"fig2_premium_62.png\"), dpi=150)" ] }, { "cell_type": "markdown", "id": "fa93ccaf", "metadata": {}, "source": [ "## 표 3. 69분류 분화 산업 — 기준 대 AI 확산(2035년)" ] }, { "cell_type": "code", "execution_count": 6, "id": "1d87bcc7", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.643062Z", "iopub.status.busy": "2026-10-08T00:08:28.643062Z", "iopub.status.idle": "2026-10-08T00:08:28.651149Z", "shell.execute_reply": "2026-10-08T00:08:28.651149Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

시나리오	AI확산(Λ=0.5)	기준(S1)	AI 프리미엄(%p)
산업
반도체	235.8	227.6	+0.56
이차전지	9.4	9.1	+0.56
신재생에너지	7.7	7.5	+0.44
조선업	9.8	9.5	+0.50
철강	12.6	12.2	+0.48
택배	12.6	12.2	+0.46
건물건설건축보수	57.3	55.8	+0.42
토목건설	24.5	23.9	+0.42

\n" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "carve = list(pd.read_csv(C.CARVEOUT)[\"69분화산업\"])\n", "w = va69[va69[\"연도\"] == C.END].pivot(index=\"산업\", columns=\"시나리오\", values=\"실질VA_십억원\").loc[carve] / 1e3\n", "w[\"AI 프리미엄(%p)\"] = lab69.loc[carve, \"VA프리미엄_2035_%p\"]\n", "w.to_csv(os.path.join(C.OUTPUT, \"table3_carveout_69.csv\"), encoding=\"utf-8-sig\")\n", "w.style.format({\"기준(S1)\": \"{:,.1f}\", \"AI확산(Λ=0.5)\": \"{:,.1f}\", \"AI 프리미엄(%p)\": \"{:+.2f}\"})" ] }, { "cell_type": "markdown", "id": "b40cfcba", "metadata": {}, "source": [ "## 표 4. AI 확산에 따른 취업계수 연변화(2035년, %p) — 고용 중립(중심)과 설문 탄력성(하방 민감도)" ] }, { "cell_type": "code", "execution_count": 7, "id": "f2b86b86", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.652152Z", "iopub.status.busy": "2026-10-08T00:08:28.652152Z", "iopub.status.idle": "2026-10-08T00:08:28.657727Z", "shell.execute_reply": "2026-10-08T00:08:28.657727Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

	VA프리미엄_2035_%p	취업계수변화_고용중립_%p	고용탄력성_ε(설문)	취업계수변화_설문탄력성_%p
산업
10.가죽제품	+0.48	-0.48	-1.81	-1.35
9.섬유ㆍ의복	+0.48	-0.48	-1.81	-1.35
19.비금속광물제품	+0.46	-0.46	-1.52	-1.15
26.자동차	+0.50	-0.50	-1.14	-1.08
27.기타 운송장비	+0.50	-0.50	-1.14	-1.08
56.교육서비스업	+0.58	-0.58	-0.80	-1.05
5.금속ㆍ비금속광업	+0.44	-0.44	-0.06	-0.47
58.사회복지 서비스업	+0.47	-0.47	+0.11	-0.42
57.의료ㆍ보건업	+0.47	-0.47	+0.11	-0.42
61.사회단체	+0.47	-0.47	+0.11	-0.42

\n" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "e = lab62[\"취업계수변화_설문탄력성_%p\"].sort_values()\n", "t4 = lab62.loc[list(e.head(6).index) + list(e.tail(4).index),\n", " [\"VA프리미엄_2035_%p\", \"취업계수변화_고용중립_%p\", \"고용탄력성_ε(설문)\", \"취업계수변화_설문탄력성_%p\"]]\n", "t4.to_csv(os.path.join(C.OUTPUT, \"table4_labor_coef.csv\"), encoding=\"utf-8-sig\")\n", "t4.style.format(\"{:+.2f}\")" ] }, { "cell_type": "markdown", "id": "fcdb3b0d", "metadata": {}, "source": [ "## 표 5. 정비 전후 비교 — 정비판 대 이전 판\n", "\n", "이전 판 값은 같은 AI 확산 층을 이전 판 기준 시나리오에 적용해 다시 계산한 것이다(`02_분석.ipynb` 8절, 검증 셀에서 이전 판 공표 수치와 대조).\n", "AI 확산의 총량 효과(기준 대비 연평균 차이)는 Λ로 보정되므로 정비 전후가 거의 같고, 수준은 기준 시나리오를 따라 움직인다." ] }, { "cell_type": "code", "execution_count": 8, "id": "f6983c39", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.658733Z", "iopub.status.busy": "2026-10-08T00:08:28.658733Z", "iopub.status.idle": "2026-10-08T00:08:28.667269Z", "shell.execute_reply": "2026-10-08T00:08:28.667269Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "산업별 프리미엄 비율(정비판/이전 판): 최소 1.002474 · 최대 1.002474 (62개 산업)\n" ] }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

	이전 판	정비판	차이
기준 2025(조원)	2,178.49	2,178.49	0.00
기준 2035(조원)	2,688.52	2,609.03	-79.49
기준 연평균(%)	2.13	1.82	-0.31
AI 확산(Λ=0.5) 2035(조원)	2,774.24	2,692.22	-82.02
AI 확산(Λ=0.5) 연평균(%)	2.45	2.14	-0.31
AI 확산(Λ=0.5) 기준 대비(%p)	0.32	0.32	-0.00
AI 확산(Λ=0.5) 2035 수준 차이(조원)	85.72	83.19	-2.53
AI 확산(Λ=0.5) 2035 수준 차이(%)	3.19	3.19	0.00
AI 확산(Λ=0.3) 2035(조원)	2,739.66	2,658.66	-81.00
AI 확산(Λ=0.3) 기준 대비(%p)	0.19	0.19	-0.00
AI 확산(Λ=0.8) 2035(조원)	2,826.84	2,743.26	-83.58
AI 확산(Λ=0.8) 기준 대비(%p)	0.51	0.51	-0.00
AI 프리미엄 44.컴퓨터 프로그래밍ㆍ시스템통합관리업(%p)	0.62	0.62	0.00
AI 프리미엄 45.정보서비스업(%p)	0.62	0.62	0.00
AI 프리미엄 40.출판업(%p)	0.62	0.62	0.00
AI 프리미엄 41.영상ㆍ오디오기록물제작 배급업(%p)	0.62	0.62	0.00
AI 프리미엄 42.방송업(%p)	0.62	0.62	0.00
AI 프리미엄 43.통신업(%p)	0.62	0.62	0.00
AI 프리미엄 56.교육서비스업(%p)	0.58	0.58	0.00
AI 프리미엄 23.의료ㆍ정밀ㆍ광학기기ㆍ시계(%p)	0.56	0.56	0.00
AI 프리미엄 39.음식점ㆍ숙박업(%p)	0.43	0.43	0.00
AI 프리미엄 33.건설업(%p)	0.42	0.42	0.00
AI 프리미엄 59.문화서비스업(%p)	0.40	0.40	0.00
AI 프리미엄 60.스포츠ㆍ오락서비스업(%p)	0.40	0.40	0.00
AI 프리미엄 62.수리ㆍ개인서비스업(%p)	0.40	0.40	0.00
반도체 기준 2035(조원)	256.05	227.62	-28.43
반도체 AI 확산 2035(조원)	265.18	235.76	-29.42
반도체 AI 프리미엄(%p)	0.56	0.56	0.00

\n" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "LABEL = {\"기준_2025_조\": \"기준 2025(조원)\", \"기준_2035_조\": \"기준 2035(조원)\", \"기준_CAGR\": \"기준 연평균(%)\",\n", " \"AI_2035_조\": \"AI 확산(Λ=0.5) 2035(조원)\", \"AI_CAGR\": \"AI 확산(Λ=0.5) 연평균(%)\", \"AI_차이_%p\": \"AI 확산(Λ=0.5) 기준 대비(%p)\",\n", " \"AI_수준차이_조\": \"AI 확산(Λ=0.5) 2035 수준 차이(조원)\", \"AI_수준차이_%\": \"AI 확산(Λ=0.5) 2035 수준 차이(%)\",\n", " \"L03_2035_조\": \"AI 확산(Λ=0.3) 2035(조원)\", \"L03_차이_%p\": \"AI 확산(Λ=0.3) 기준 대비(%p)\",\n", " \"L08_2035_조\": \"AI 확산(Λ=0.8) 2035(조원)\", \"L08_차이_%p\": \"AI 확산(Λ=0.8) 기준 대비(%p)\"}\n", "tt = cmp[cmp[\"구분\"] == \"총량\"].set_index(\"항목\").loc[list(LABEL), [\"이전 판\", \"정비판\", \"차이\"]].rename(index=LABEL)\n", "pp = cmp[cmp[\"구분\"] == \"62 프리미엄(%p)\"].set_index(\"항목\").loc[list(t2.index), [\"이전 판\", \"정비판\", \"차이\"]]\n", "pp.index = [f\"AI 프리미엄 {c}(%p)\" for c in pp.index]\n", "sm = cmp[cmp[\"항목\"] == \"반도체\"].set_index(\"구분\").loc[[\"69 분화 기준 2035(조원)\", \"69 분화 AI 2035(조원)\", \"69 분화 프리미엄(%p)\"], [\"이전 판\", \"정비판\", \"차이\"]]\n", "sm.index = [\"반도체 기준 2035(조원)\", \"반도체 AI 확산 2035(조원)\", \"반도체 AI 프리미엄(%p)\"]\n", "t5 = pd.concat([tt, pp, sm])\n", "t5.to_csv(os.path.join(C.OUTPUT, \"table5_vs_previous.csv\"), encoding=\"utf-8-sig\")\n", "r = cmp[cmp[\"구분\"] == \"62 프리미엄(%p)\"]\n", "r = r[\"정비판\"] / r[\"이전 판\"]\n", "print(f\"산업별 프리미엄 비율(정비판/이전 판): 최소 {r.min():.6f} · 최대 {r.max():.6f} (62개 산업)\")\n", "t5.style.format(\"{:,.2f}\")" ] }, { "cell_type": "markdown", "id": "146fde17", "metadata": {}, "source": [ "## 제출용 엑셀\n", "\n", "한국고용정보원 전달용으로 62·69분류 기준·AI 확산 실질부가가치(2025–2035), 산업별 프리미엄·탄력성·취업계수 변화, 민감도, 정비 전후 비교(표 5)를 한 파일에 담는다." ] }, { "cell_type": "code", "execution_count": 9, "id": "eb9a0331", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.668272Z", "iopub.status.busy": "2026-10-08T00:08:28.668272Z", "iopub.status.idle": "2026-10-08T00:08:28.732023Z", "shell.execute_reply": "2026-10-08T00:08:28.732023Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "저장: AI확산_부가가치_취업계수_전망_62_69_2025-2035.xlsx\n" ] } ], "source": [ "xl = os.path.join(C.OUTPUT, \"AI확산_부가가치_취업계수_전망_62_69_2025-2035.xlsx\")\n", "note = pd.DataFrame({\"항목\": [\"단위\", \"기준 시나리오\", \"AI 확산 시나리오\", \"Λ\", \"산업 배분\", \"취업계수 변화\", \"작성\"],\n", " \"내용\": [\"실질부가가치 십억 원(2020년 연쇄가격), 프리미엄·취업계수 변화는 연 %p\",\n", " f\"보고서1 5장 정합화 후 S1, {C.VERSION}(2025 실적, 2026–2035 전망)\",\n", " \"기준 성장률 + 산업별 AI 프리미엄 누적\",\n", " \"2035년 실질부가가치 가중평균 프리미엄 0.5%p(민감도 0.3·0.8)\",\n", " f\"{C.ALLOCATION}: E4-1 2040년 점수 − 1(척도 최저점) × 시점 램프\",\n", " \"중심: 고용 중립(ε=0) → −프리미엄. 민감도: (ε − 1) × 프리미엄, ε는 E4·E5(2024년 대비 2040년 기대 증감)로 구한 고용 탄력성\",\n", " \"aiforalab · 보고서2 4장 재현 패키지\"]})\n", "with pd.ExcelWriter(xl, engine=\"openpyxl\") as wr:\n", " note.to_excel(wr, sheet_name=\"설명\", index=False)\n", " for g, va in [(\"62\", va62), (\"69\", va69)]:\n", " for sc in [\"기준(S1)\", \"AI확산(Λ=0.5)\"]:\n", " va[va[\"시나리오\"] == sc].pivot(index=\"산업\", columns=\"연도\", values=\"실질VA_십억원\").to_excel(\n", " wr, sheet_name=f\"{g}_{'기준' if sc.startswith('기준') else 'AI확산'}\")\n", " lab62.to_excel(wr, sheet_name=\"62_프리미엄_취업계수\")\n", " lab69.to_excel(wr, sheet_name=\"69_프리미엄_취업계수\")\n", " t1.to_excel(wr, sheet_name=\"Λ민감도\", index=False)\n", " var.to_excel(wr, sheet_name=\"배분방식_비교\")\n", " t5.to_excel(wr, sheet_name=\"정비전후_비교\")\n", "print(\"저장:\", os.path.basename(xl))" ] }, { "cell_type": "markdown", "id": "c563ea81", "metadata": {}, "source": [ "## 검증 — 정비판 공표 수치와 이전 판 재현\n", "\n", "1. **정비판**: 위 표·그림을 만든 산출물(`lambda_sensitivity.csv`, `ai_va_62.csv`, `ai_va_69.csv`, `ai_premium_labor_62.csv`)에서 계산한 값과\n", " `config.PUBLISHED`(정비 실행에서 기록한 공표 수치, 정수 조 원·소수 첫째 또는 둘째 자리 %)의 차이가 반올림 범위 안에 있어야 한다.\n", "2. **이전 판 재현**: 같은 AI 확산 층을 이전 판 기준 시나리오에 적용한 결과(`compare_prev.csv`의 이전 판 열)가\n", " 이전 판 공표 수치(`config.PREVIOUS`, 이전 판 원고·패키지의 값)를 반올림 범위 안에서 재현해야 한다. 이 점검이 통과하면 정비 전후의 차이는 기준 시나리오 교체에서만 온다." ] }, { "cell_type": "code", "execution_count": 10, "id": "d0eed9fe", "metadata": { "execution": { "iopub.execute_input": "2026-10-08T00:08:28.733526Z", "iopub.status.busy": "2026-10-08T00:08:28.733526Z", "iopub.status.idle": "2026-10-08T00:08:28.748580Z", "shell.execute_reply": "2026-10-08T00:08:28.748580Z" } }, "outputs": [ { "data": { "text/html": [ "

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	구분	항목	계산	기준값	허용오차	통과
0	정비판	기준_2025_조	2,178.489	2,178.000	0.500	True
1	정비판	기준_2035_조	2,609.028	2,609.000	0.500	True
2	정비판	기준_CAGR	1.820	1.820	0.005	True
3	정비판	AI_2035_조	2,692.217	2,692.000	0.500	True
4	정비판	AI_CAGR	2.140	2.140	0.005	True
5	정비판	AI_차이_%p	0.320	0.320	0.005	True
6	정비판	AI_수준차이_조	83.189	83.000	0.500	True
7	정비판	AI_수준차이_%	3.189	3.200	0.050	True
8	정비판	L03_2035_조	2,658.662	2,659.000	0.500	True
9	정비판	L03_차이_%p	0.192	0.190	0.005	True
10	정비판	L08_2035_조	2,743.259	2,743.000	0.500	True
11	정비판	L08_차이_%p	0.512	0.510	0.005	True
12	정비판	정보통신_프리미엄_%p	0.620	0.620	0.005	True
13	정비판	교육_프리미엄_%p	0.584	0.580	0.005	True
14	정비판	문화_프리미엄_%p	0.400	0.400	0.005	True
15	정비판	반도체_2035_기준_조	227.623	228.000	0.500	True
16	정비판	반도체_2035_AI_조	235.756	236.000	0.500	True
17	정비판	정보통신_취업계수_%p	-0.620	-0.620	0.005	True
18	정비판	건설_취업계수_%p	-0.425	-0.420	0.005	True
19	이전 판 재현	기준_2025_조	2,178.489	2,178.000	0.500	True
20	이전 판 재현	기준_2035_조	2,688.518	2,689.000	0.500	True
21	이전 판 재현	기준_CAGR	2.126	2.130	0.005	True
22	이전 판 재현	AI_2035_조	2,774.242	2,774.000	0.500	True
23	이전 판 재현	AI_CAGR	2.447	2.450	0.005	True
24	이전 판 재현	AI_차이_%p	0.321	0.320	0.005	True
25	이전 판 재현	AI_수준차이_조	85.724	86.000	0.500	True
26	이전 판 재현	AI_수준차이_%	3.189	3.200	0.050	True
27	이전 판 재현	L03_2035_조	2,739.664	2,740.000	0.500	True
28	이전 판 재현	L03_차이_%p	0.193	0.190	0.005	True
29	이전 판 재현	L08_2035_조	2,826.838	2,827.000	0.500	True
30	이전 판 재현	L08_차이_%p	0.514	0.510	0.005	True
31	이전 판 재현	정보통신_프리미엄_%p	0.619	0.620	0.005	True
32	이전 판 재현	교육_프리미엄_%p	0.583	0.580	0.005	True
33	이전 판 재현	문화_프리미엄_%p	0.399	0.400	0.005	True
34	이전 판 재현	반도체_2035_기준_조	256.053	256.000	0.500	True
35	이전 판 재현	반도체_2035_AI_조	265.179	265.000	0.500	True
36	이전 판 재현	정보통신_취업계수_%p	-0.619	-0.620	0.005	True
37	이전 판 재현	건설_취업계수_%p	-0.424	-0.420	0.005	True

\n", "

" ], "text/plain": [ " 구분 항목 계산 기준값 허용오차 통과\n", "0 정비판 기준_2025_조 2,178.489 2,178.000 0.500 True\n", "1 정비판 기준_2035_조 2,609.028 2,609.000 0.500 True\n", "2 정비판 기준_CAGR 1.820 1.820 0.005 True\n", "3 정비판 AI_2035_조 2,692.217 2,692.000 0.500 True\n", "4 정비판 AI_CAGR 2.140 2.140 0.005 True\n", "5 정비판 AI_차이_%p 0.320 0.320 0.005 True\n", "6 정비판 AI_수준차이_조 83.189 83.000 0.500 True\n", "7 정비판 AI_수준차이_% 3.189 3.200 0.050 True\n", "8 정비판 L03_2035_조 2,658.662 2,659.000 0.500 True\n", "9 정비판 L03_차이_%p 0.192 0.190 0.005 True\n", "10 정비판 L08_2035_조 2,743.259 2,743.000 0.500 True\n", "11 정비판 L08_차이_%p 0.512 0.510 0.005 True\n", "12 정비판 정보통신_프리미엄_%p 0.620 0.620 0.005 True\n", "13 정비판 교육_프리미엄_%p 0.584 0.580 0.005 True\n", "14 정비판 문화_프리미엄_%p 0.400 0.400 0.005 True\n", "15 정비판 반도체_2035_기준_조 227.623 228.000 0.500 True\n", "16 정비판 반도체_2035_AI_조 235.756 236.000 0.500 True\n", "17 정비판 정보통신_취업계수_%p -0.620 -0.620 0.005 True\n", "18 정비판 건설_취업계수_%p -0.425 -0.420 0.005 True\n", "19 이전 판 재현 기준_2025_조 2,178.489 2,178.000 0.500 True\n", "20 이전 판 재현 기준_2035_조 2,688.518 2,689.000 0.500 True\n", "21 이전 판 재현 기준_CAGR 2.126 2.130 0.005 True\n", "22 이전 판 재현 AI_2035_조 2,774.242 2,774.000 0.500 True\n", "23 이전 판 재현 AI_CAGR 2.447 2.450 0.005 True\n", "24 이전 판 재현 AI_차이_%p 0.321 0.320 0.005 True\n", "25 이전 판 재현 AI_수준차이_조 85.724 86.000 0.500 True\n", "26 이전 판 재현 AI_수준차이_% 3.189 3.200 0.050 True\n", "27 이전 판 재현 L03_2035_조 2,739.664 2,740.000 0.500 True\n", "28 이전 판 재현 L03_차이_%p 0.193 0.190 0.005 True\n", "29 이전 판 재현 L08_2035_조 2,826.838 2,827.000 0.500 True\n", "30 이전 판 재현 L08_차이_%p 0.514 0.510 0.005 True\n", "31 이전 판 재현 정보통신_프리미엄_%p 0.619 0.620 0.005 True\n", "32 이전 판 재현 교육_프리미엄_%p 0.583 0.580 0.005 True\n", "33 이전 판 재현 문화_프리미엄_%p 0.399 0.400 0.005 True\n", "34 이전 판 재현 반도체_2035_기준_조 256.053 256.000 0.500 True\n", "35 이전 판 재현 반도체_2035_AI_조 265.179 265.000 0.500 True\n", "36 이전 판 재현 정보통신_취업계수_%p -0.619 -0.620 0.005 True\n", "37 이전 판 재현 건설_취업계수_%p -0.424 -0.420 0.005 True" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "검증 통과: 정비판 공표 수치 19개 항목과 이전 판 재현 19개 항목, 모두 38개 항목이 반올림 범위 안에서 일치한다.\n" ] } ], "source": [ "P = C.PUBLISHED\n", "def pick(df, prefix, col):\n", " return df.loc[[c for c in df.index if c.startswith(prefix)], col].iloc[0]\n", "a35 = tot.loc[C.END, \"AI확산(Λ=0.5)\"]\n", "v69 = va69[(va69[\"연도\"] == C.END) & (va69[\"산업\"] == \"반도체\")].set_index(\"시나리오\")[\"실질VA_십억원\"] / 1e3\n", "sv = sens.set_index(\"Λ(%p)\")\n", "calc = {\n", " \"기준_2025_조\": b25, \"기준_2035_조\": b35, \"기준_CAGR\": F.cagr(b25, b35, 10),\n", " \"AI_2035_조\": a35, \"AI_CAGR\": F.cagr(b25, a35, 10), \"AI_차이_%p\": F.cagr(b25, a35, 10) - F.cagr(b25, b35, 10),\n", " \"AI_수준차이_조\": a35 - b35, \"AI_수준차이_%\": (a35 / b35 - 1) * 100,\n", " \"L03_2035_조\": sv.loc[0.3, \"2035 AI확산(조원)\"], \"L03_차이_%p\": sv.loc[0.3, \"기준 대비(%p)\"],\n", " \"L08_2035_조\": sv.loc[0.8, \"2035 AI확산(조원)\"], \"L08_차이_%p\": sv.loc[0.8, \"기준 대비(%p)\"],\n", " \"정보통신_프리미엄_%p\": pick(lab62, \"44.\", \"VA프리미엄_2035_%p\"), \"교육_프리미엄_%p\": pick(lab62, \"56.\", \"VA프리미엄_2035_%p\"),\n", " \"문화_프리미엄_%p\": pick(lab62, \"59.\", \"VA프리미엄_2035_%p\"),\n", " \"반도체_2035_기준_조\": v69[\"기준(S1)\"], \"반도체_2035_AI_조\": v69[\"AI확산(Λ=0.5)\"],\n", " \"정보통신_취업계수_%p\": pick(lab62, \"44.\", \"취업계수변화_2035_%p\"), \"건설_취업계수_%p\": pick(lab62, \"33.\", \"취업계수변화_2035_%p\"),\n", "}\n", "assert set(calc) == set(P) == set(C.PREVIOUS) == set(C.PUBLISHED_SPEC), \"검증 항목과 공표 수치 항목이 다르다\"\n", "rows = []\n", "for k, (grp, item, dg) in C.PUBLISHED_SPEC.items():\n", " tol = C.tolerance(dg)\n", " rows.append({\"구분\": \"정비판\", \"항목\": k, \"계산\": calc[k], \"기준값\": P[k], \"허용오차\": tol, \"통과\": abs(calc[k] - P[k]) <= tol})\n", "for k, (grp, item, dg) in C.PUBLISHED_SPEC.items():\n", " tol, v = C.tolerance(dg), F.lookup(cmp, \"이전 판\", grp, item)\n", " rows.append({\"구분\": \"이전 판 재현\", \"항목\": k, \"계산\": v, \"기준값\": C.PREVIOUS[k], \"허용오차\": tol, \"통과\": abs(v - C.PREVIOUS[k]) <= tol})\n", "res = pd.DataFrame(rows)\n", "res.to_csv(os.path.join(C.OUTPUT, \"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", "n_new, n_prev = (res[\"구분\"] == \"정비판\").sum(), (res[\"구분\"] == \"이전 판 재현\").sum()\n", "print(f\"검증 통과: 정비판 공표 수치 {n_new}개 항목과 이전 판 재현 {n_prev}개 항목, 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 }