<essential_principles>
<principle name="fiscal_trap_definition">
**財政陷阱定義**
「人口-財政陷阱」(Demographic-Fiscal Trap) 是指：當高齡化撫養比持續攀升、政府債務/GDP 居高不下、官僚體系低效膨脹、且名義成長無法覆蓋利息支出時，政府傾向透過「金融抑制」(financial repression) 或「通膨稀釋」(inflation erosion) 來削減實質負債。
此陷阱的核心特徵：
- 人口結構剛性：老年撫養比上升是不可逆的長期趨勢
- 債務自我強化：r > g 時債務比率自動膨脹
- 政治阻力：削減福利支出的政治成本極高
- 貨幣出口：當財政改革無路可走，貨幣稀釋成為「最小阻力路徑」
</principle>
<principle name="four_pillar_framework">
**四支柱分析架構**
本技能採用四維度評分框架：
| 支柱 | 權重(預設) | 核心指標 |
|---|
| 老化壓力 (Aging Pressure) | 35% | 老年撫養比水準 + 10年斜率 |
| 債務動態 (Debt Dynamics) | 35% | 債務/GDP + 5年斜率 + (r-g) |
| 官僚膨脹 (Bloat Index) | 15% | 政府消費/GDP + 政府支出/GDP |
| 成長拖累 (Growth Drag) | 15% | 名義GDP成長率（負向計分） |
最終
= Σ(權重 × z-score) 加權總和
</principle>
<principle name="inflation_incentive">
**通膨激勵指數**
通膨激勵指數 (Inflation Incentive Score) 衡量政府選擇「通膨稀釋」路徑的動機強度：
inflation_incentive =
0.40 × zscore(debt_level) # 高債務 → 強動機
+ 0.20 × zscore(r - g) # r > g → 難以自然去槓桿
+ 0.20 × zscore(neg_real_rate_share) # 負實質利率持續 → 已在執行
+ 0.20 × zscore(bloat_index) # 高官僚膨脹 → 難以削減支出
當此指數 > 1.5 時，表示該經濟體有強烈動機維持負實質利率環境。
</principle>
<principle name="data_hierarchy">
**資料來源層級**
本技能採用公開可重現的資料源：
| 資料類型 | 首選來源 | 次選來源 | API/下載方式 |
|---|
| 撫養比 | World Bank WDI | UN WPP | API / CSV |
| 政府債務 | IMF WEO | World Bank | API / CSV |
| 政府支出 | IMF GFS | World Bank | API / CSV |
| 健康支出 | WHO GHED | World Bank | API / CSV |
| 名義GDP成長 | World Bank | IMF WEO | API |
| CPI通膨 | World Bank | IMF | API |
| 10年公債殖利率 | OECD / 各國央行 | Trading Economics | API / 爬蟲 |
所有指標均可透過
、
或直接 API 取得。
</principle>
<principle name="zscore_normalization">
**Z-Score 標準化**
為使跨國比較有意義，所有原始指標均轉換為 z-score：
python
zscore(x) = (x - μ_cross_section) / σ_cross_section
其中 μ 和 σ 為同期跨國截面統計量。
這使得：
- z > 1.5 → 顯著高於平均（警戒）
- z > 2.0 → 極端值（紅燈）
- z < -1.0 → 顯著優於平均
</principle>
<principle name="quadrant_classification">
**象限分類系統**
根據 Aging Pressure 和 Debt Dynamics 兩主軸，將經濟體分為四象限：
| 象限 | 老化壓力 | 債務動態 | 典型國家 | 政策空間 |
|---|
| Q1: 雙高危機 | 高 (>1) | 高 (>1) | 日本、義大利、希臘 | 極窄 |
| Q2: 老化主導 | 高 (>1) | 低 (<1) | 德國、南韓 | 中等（債務可用） |
| Q3: 債務主導 | 低 (<1) | 高 (>1) | 美國、巴西 | 中等（人口紅利） |
| Q4: 相對健康 | 低 (<1) | 低 (<1) | 印度、印尼 | 寬廣 |
Q1 象限國家最可能進入「財政陷阱」並選擇通膨稀釋路徑。
</principle>
</essential_principles>
<objective>
本技能的目標是：
- 量化財政脆弱度：計算各國/地區的 與
inflation_incentive_score
- 識別結構風險：透過四支柱分解，診斷哪個維度貢獻最大風險
- 象限定位：將經濟體歸類至四象限，判斷其政策空間
- 趨勢預警：利用撫養比預測至 2050 年，前瞻性評估陷阱演化
- 跨國比較：支援多國並排比較，識別相對風險排序
</objective>
<quick_start>
<essential_principles>
<principle name="fiscal_trap_definition">
**Definition of Fiscal Trap**
The "Demographic-Fiscal Trap" refers to: When the aging dependency ratio continues to rise, government debt/GDP remains high, the bureaucratic system is inefficiently expanded, and nominal growth cannot cover interest payments, the government tends to reduce real liabilities through "financial repression" or "inflation erosion".
Core characteristics of this trap:
- Rigid population structure: The rise in the old-age dependency ratio is an irreversible long-term trend
- Self-reinforcing debt: When r > g, the debt ratio automatically expands
- Political resistance: The political cost of cutting welfare spending is extremely high
- Currency dilution: When fiscal reform is not feasible, currency dilution becomes the "path of least resistance"
</principle>
<principle name="four_pillar_framework">
**Four-Pillar Analysis Framework**
This skill adopts a four-dimensional scoring framework:
| Pillar | Weight (Default) | Core Indicators |
|---|
| Aging Pressure | 35% | Old-age dependency ratio level + 10-year slope |
| Debt Dynamics | 35% | Debt/GDP + 5-year slope + (r-g) |
| Bloat Index | 15% | Government consumption/GDP + Government expenditure/GDP |
| Growth Drag | 15% | Nominal GDP growth rate (negative scoring) |
Final
= Σ(Weight × z-score) weighted sum
</principle>
<principle name="inflation_incentive">
**Inflation Incentive Score**
The Inflation Incentive Score measures the strength of the government's motivation to choose the "inflation erosion" path:
inflation_incentive =
0.40 × zscore(debt_level) # High debt → Strong motivation
+ 0.20 × zscore(r - g) # r > g → Difficult to deleverage naturally
+ 0.20 × zscore(neg_real_rate_share) # Sustained negative real rates → Already in implementation
+ 0.20 × zscore(bloat_index) # High bureaucratic expansion → Difficult to cut spending
When this index > 1.5, it indicates that the economy has a strong motivation to maintain a negative real interest rate environment.
</principle>
<principle name="data_hierarchy">
**Data Source Hierarchy**
This skill uses publicly reproducible data sources:
| Data Type | Preferred Source | Alternative Source | API/Download Method |
|---|
| Dependency Ratio | World Bank WDI | UN WPP | API / CSV |
| Government Debt | IMF WEO | World Bank | API / CSV |
| Government Expenditure | IMF GFS | World Bank | API / CSV |
| Health Expenditure | WHO GHED | World Bank | API / CSV |
| Nominal GDP Growth | World Bank | IMF WEO | API |
| CPI Inflation | World Bank | IMF | API |
| 10-Year Government Bond Yield | OECD / National Central Banks | Trading Economics | API / Web Scraping |
All indicators can be obtained via
,
or direct API.
</principle>
<principle name="zscore_normalization">
**Z-Score Normalization**
To make cross-country comparisons meaningful, all raw indicators are converted to z-scores:
python
zscore(x) = (x - μ_cross_section) / σ_cross_section
Where μ and σ are cross-sectional statistics across countries in the same period.
This enables:
- z > 1.5 → Significantly above average (alert)
- z > 2.0 → Extreme value (red light)
- z < -1.0 → Significantly better than average
</principle>
<principle name="quadrant_classification">
**Quadrant Classification System**
Based on the two main axes of Aging Pressure and Debt Dynamics, economies are divided into four quadrants:
| Quadrant | Aging Pressure | Debt Dynamics | Typical Countries | Policy Space |
|---|
| Q1: Dual Crisis | High (>1) | High (>1) | Japan, Italy, Greece | Extremely narrow |
| Q2: Aging-Driven | High (>1) | Low (<1) | Germany, South Korea | Moderate (debt available) |
| Q3: Debt-Driven | Low (<1) | High (>1) | United States, Brazil | Moderate (demographic dividend) |
| Q4: Relatively Healthy | Low (<1) | Low (<1) | India, Indonesia | Broad |
Countries in Quadrant Q1 are most likely to enter the "fiscal trap" and choose the inflation erosion path.
</principle>
</essential_principles>
<objective>
The objectives of this skill are:
- Quantify fiscal vulnerability: Calculate the and
inflation_incentive_score
- Identify structural risks: Diagnose which dimension contributes the most risk through four-pillar decomposition
- Quadrant positioning: Categorize economies into four quadrants to judge their policy space
- Trend early warning: Use dependency ratio projections up to 2050 to proactively assess trap evolution
- Cross-country comparison: Support side-by-side comparison of multiple countries to identify relative risk rankings
</objective>
<quick_start>