fix(ecos): correct all 6 ECOS API stat/item codes #task-292

- GDP: 111Y002/10111 -> 902Y015/KOR (international comparative stats)
- Unemployment: 901Y027/3 -> 901Y027/I61BC (correct item for rate)
- CD rate: 817Y002/010502000 -> 721Y001/2010000 (market interest rates)
- CPI: now computes YoY growth from level index (pct_change)
- Leading index: monthly (M) fetch + annual average (no annual data available)
- Fix DataFrame merge: dedup index, dropna before concat
- Fix NaN in scenario Z paths: fallback to z_scenario
- Update config.yaml with verified stat codes

data/macro_data.py

@@ -136,10 +136,10 @@ def collect_macro_data(
     
     # -------------------------------------------------------
     # 1) GDP 실질성장률 (%)
-    # 통계표: 111Y002 (국민계정 - 주요지표 - 경제성장률)
+    # 통계표: 902Y015 (국제 주요국 경제성장률) / 항목: KOR
     # -------------------------------------------------------
     logger.info("GDP 성장률 조회 중...")
-    df_gdp = api.fetch_stat("111Y002", "A", start, end, "10111")
+    df_gdp = api.fetch_stat("902Y015", "A", start, end, "KOR")
     if not df_gdp.empty:
         gdp_series = df_gdp.set_index("TIME")["DATA_VALUE"].astype(float)
         gdp_series.index = gdp_series.index.astype(int)
@@ -148,10 +148,10 @@ def collect_macro_data(
     
     # -------------------------------------------------------
     # 2) 실업률 (%)
-    # 통계표: 901Y027 (고용 - 주요고용지표)
+    # 통계표: 901Y027 (경제활동인구) / 항목: I61BC (실업률)
     # -------------------------------------------------------
     logger.info("실업률 조회 중...")
-    df_unemp = api.fetch_stat("901Y027", "A", start, end, "3", " ")
+    df_unemp = api.fetch_stat("901Y027", "A", start, end, "I61BC")
     if not df_unemp.empty:
         unemp_series = df_unemp.set_index("TIME")["DATA_VALUE"].astype(float)
         unemp_series.index = unemp_series.index.astype(int)
@@ -172,10 +172,10 @@ def collect_macro_data(
     
     # -------------------------------------------------------
     # 4) CD(91일) 금리 (%)
-    # 통계표: 817Y002
+    # 통계표: 721Y001 (시장금리) / 항목: 2010000 (CD 91일)
     # -------------------------------------------------------
     logger.info("CD 금리 조회 중...")
-    df_cd = api.fetch_stat("817Y002", "A", start, end, "010502000")
+    df_cd = api.fetch_stat("721Y001", "A", start, end, "2010000")
     if not df_cd.empty:
         cd_series = df_cd.set_index("TIME")["DATA_VALUE"].astype(float)
         cd_series.index = cd_series.index.astype(int)
@@ -184,32 +184,57 @@ def collect_macro_data(
     
     # -------------------------------------------------------
     # 5) 소비자물가지수 상승률 (%)
-    # 통계표: 901Y009
+    # 통계표: 901Y009 / 항목: 0 (총지수)
+    # 지수(level)로 조회 후 전년대비 상승률(%) 계산
     # -------------------------------------------------------
     logger.info("소비자물가 상승률 조회 중...")
-    df_cpi = api.fetch_stat("901Y009", "A", start, end, "0")
+    # 전년도까지 필요 → start를 1년 앞당겨 조회
+    df_cpi = api.fetch_stat("901Y009", "A", str(start_year - 1), end, "0")
     if not df_cpi.empty:
-        cpi_series = df_cpi.set_index("TIME")["DATA_VALUE"].astype(float)
-        cpi_series.index = cpi_series.index.astype(int)
-        macro_vars["CPI_GROWTH"] = cpi_series
+        cpi_level = df_cpi.set_index("TIME")["DATA_VALUE"].astype(float)
+        cpi_level.index = cpi_level.index.astype(int)
+        cpi_level = cpi_level.sort_index()
+        # 전년대비 증가율 (%)
+        cpi_growth = cpi_level.pct_change() * 100
+        cpi_growth = cpi_growth.loc[start_year:end_year]
+        macro_vars["CPI_GROWTH"] = cpi_growth
     time.sleep(0.5)
     
     # -------------------------------------------------------
-    # 6) 경기선행지수 순환변동치
-    # 통계표: 901Y067
+    # 6) 경기선행종합지수
+    # 통계표: 901Y067 / 항목: I16A (선행종합지수)
+    # 월별만 존재 → 월별 조회 후 연평균 산출
     # -------------------------------------------------------
     logger.info("경기선행지수 조회 중...")
-    df_leading = api.fetch_stat("901Y067", "A", start, end, "I16A")
+    df_leading = api.fetch_stat(
+        "901Y067", "M",
+        f"{start_year}01", f"{end_year}12",
+        "I16A"
+    )
     if not df_leading.empty:
-        leading_series = df_leading.set_index("TIME")["DATA_VALUE"].astype(float)
-        leading_series.index = leading_series.index.astype(int)
-        macro_vars["LEADING_INDEX"] = leading_series
+        monthly = df_leading[["TIME", "DATA_VALUE"]].copy()
+        monthly["DATA_VALUE"] = monthly["DATA_VALUE"].astype(float)
+        monthly["YEAR"] = monthly["TIME"].str[:4].astype(int)
+        annual_avg = monthly.groupby("YEAR")["DATA_VALUE"].mean()
+        annual_avg = annual_avg.loc[start_year:end_year]
+        macro_vars["LEADING_INDEX"] = annual_avg
     
-    # DataFrame 결합
+    # DataFrame 결합 (각 Series의 인덱스를 정리하여 결합)
     if macro_vars:
-        result = pd.DataFrame(macro_vars)
+        # 각 Series의 인덱스를 정수로 통일, 중복 제거
+        clean_vars = {}
+        for name, series in macro_vars.items():
+            s = series.copy()
+            s.index = s.index.astype(int)
+            s = s[~s.index.duplicated(keep='first')]  # 중복 제거
+            s = s.dropna()
+            clean_vars[name] = s
+        
+        result = pd.DataFrame(clean_vars)
         result.index.name = "YEAR"
         result = result.sort_index()
+        
+        logger.info(f"ECOS API 데이터 수집 완료: {len(result)}개 연도, {len(result.columns)}개 변수")
         return result
     else:
         logger.warning("거시경제 데이터 수집 실패. 내장 fallback 데이터 사용.")