Dr. Dudi Duta Akbar

Quantitative Easing dan Stabilitas Ekonomi Indonesia dalam Kerangka New Monetary Trinity

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dudidutaakbar@gmail.com
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Latar Belakang Konseptual

Kebijakan Quantitative Easing (QE) muncul sebagai respons atas keterbatasan instrumen suku bunga konvensional, khususnya saat ekonomi menghadapi krisis dan mendekati Zero Lower Bound (ZLB). Dalam konteks negara berkembang seperti Indonesia, implementasi QE tidak hanya memengaruhi inflasi dan output, tetapi juga nilai tukar, stabilitas keuangan, dan independensi kebijakan moneter.

Artikel ini memposisikan QE dalam kerangka New Monetary Trinity, yaitu:

  1. stabilitas moneter (inflasi),
  2. stabilitas nilai tukar,
  3. stabilitas keuangan.

Kerangka ini merupakan perluasan dari Impossible Trinity, dengan menambahkan dimensi stabilitas keuangan sebagai respons terhadap global financial cycle.

Tujuan dan Data Penelitian

Tujuan utama penelitian adalah menganalisis dampak QE terhadap stabilitas ekonomi Indonesia dengan mempertimbangkan:

  • perbedaan kondisi ekonomi (rezim volatilitas),
  • perubahan dinamika kebijakan lintas waktu.

Data:

  • Triwulanan 2007–2023

Variabel utama:

  • BI rate (BI),
  • Inflasi (INF),
  • Pertumbuhan PDB (GDP),
  • Nilai tukar efektif riil (REER),
  • IHSG,
  • Surat Utang Negara (SUN).

Kerangka Model dan Metodologi

a. Threshold Vector Autoregression (TVAR)

TVAR digunakan untuk menangkap nonlinearitas dan perbedaan rezim.

Bentuk umum:Yt={A1Yt−1+εt,qt≤γA2Yt−1+εt,qt>γY_t = \begin{cases} A_1 Y_{t-1} + \varepsilon_t, & q_t \leq \gamma \\ A_2 Y_{t-1} + \varepsilon_t, & q_t > \gamma \end{cases}

dengan:

  • qtq_t​: variabel threshold (GDP),
  • γ\gamma: nilai ambang (threshold).

Hasil estimasi menunjukkan GDP sebagai threshold optimal, membagi ekonomi ke dalam:

  • low-volatility regime,
  • high-volatility regime.

b. Bayesian VAR (BVAR)

BVAR digunakan untuk mengatasi masalah overparameterisasi VAR klasik dan meningkatkan kestabilan estimasi.

Posterior parameter:p(θ∣Y)∝p(Y∣θ)×p(θ)p(\theta|Y) \propto p(Y|\theta) \times p(\theta)

Pendekatan ini memungkinkan integrasi informasi awal (prior) dengan data aktual, sehingga hasil estimasi lebih robust terhadap ketidakpastian.

c. Time-Varying Parameter VAR (TVP-VAR)

TVP-VAR menangkap perubahan perilaku kebijakan moneter dari waktu ke waktu.

Model dasar:Yt=BtYt−1+εtY_t = B_t Y_{t-1} + \varepsilon_t

dengan evolusi parameter:Bt=Bt−1+νtB_t = B_{t-1} + \nu_t

Model ini penting untuk menganalisis dinamika QE selama periode krisis, khususnya pandemi COVID-19.

Temuan Utama

  1. Dampak QE bersifat tidak linear
    Efektivitas QE berbeda antara kondisi stabil dan kondisi volatil tinggi.
  2. Low-volatility regime
    QE relatif efektif dalam:
    • menjaga inflasi,
    • menopang stabilitas obligasi (SUN),
    • menjaga stabilitas makroekonomi.
  3. High-volatility regime
    QE:
    • meningkatkan tekanan pada pertumbuhan ekonomi,
    • mempersempit ruang independensi kebijakan moneter,
    • memperkuat peran nilai tukar sebagai saluran transmisi eksternal.
  4. Peran strategis SUN
    SUN berfungsi sebagai instrumen penyangga utama dalam stabilitas keuangan dan kanal koordinasi fiskal–moneter.
  5. Dinamika kebijakan berubah lintas waktu
    Hasil TVP-VAR menunjukkan bahwa respons kebijakan moneter Indonesia bersifat adaptif, khususnya selama periode krisis.

Implikasi Akademik dan Kebijakan

  • QE di negara berkembang tidak dapat diperlakukan sebagai kebijakan netral; efektivitasnya sangat bergantung pada rezim ekonomi.
  • New Monetary Trinity menuntut kebijakan moneter yang adaptif dan terkoordinasi dengan kebijakan fiskal.
  • Stabilitas keuangan harus menjadi tujuan eksplisit dalam desain kebijakan moneter non-konvensional.

Intisari Singkat

QE di Indonesia efektif sebagai alat stabilisasi dalam kondisi normal, namun berisiko mengikis independensi moneter saat volatilitas tinggi, sehingga memerlukan pendekatan adaptive monetary governance.

Academic Notes

Quantitative Easing and Economic Stability in Indonesia within the New Monetary Trinity Framework

1. Conceptual Background

Quantitative Easing (QE) emerged as a non-conventional monetary policy in response to the limitations of interest-rate instruments, particularly under Zero Lower Bound (ZLB) conditions. In emerging economies such as Indonesia, QE affects not only inflation and output but also exchange rate dynamics, financial stability, and monetary policy independence.

This study situates QE within the New Monetary Trinity framework, which extends the traditional Impossible Trinity by explicitly incorporating financial stability alongside:

  1. price stability,
  2. exchange rate stability,
  3. monetary autonomy.

This extension reflects the realities of global financial cycles and heightened capital mobility.

2. Research Objective and Data

The main objective is to examine the impact of QE on Indonesia’s macroeconomic stability, accounting for:

  • regime-dependent dynamics,
  • time-varying policy behavior.

Data:

  • Quarterly observations from 2007–2023

Key variables:

  • Policy interest rate (BI),
  • Inflation (INF),
  • GDP growth (GDP),
  • Real Effective Exchange Rate (REER),
  • Stock market index (IHSG),
  • Government bonds (SUN).

3. Econometric Framework and Models

a. Threshold Vector Autoregression (TVAR)

TVAR captures nonlinear dynamics and regime switching.

General form:Yt={A1Yt−1+εt,qt≤γA2Yt−1+εt,qt>γY_t = \begin{cases} A_1 Y_{t-1} + \varepsilon_t, & q_t \leq \gamma \\ A_2 Y_{t-1} + \varepsilon_t, & q_t > \gamma \end{cases}

where:

  • qtq_t​ is the threshold variable (GDP),
  • γ\gamma denotes the threshold value.

GDP is identified as the optimal threshold, separating low-volatility and high-volatility regimes.

b. Bayesian Vector Autoregression (BVAR)

BVAR is employed to mitigate over-parameterization and enhance estimation stability.

Posterior distribution:p(θ∣Y)∝p(Y∣θ)×p(θ)p(\theta \mid Y) \propto p(Y \mid \theta) \times p(\theta)

This Bayesian framework combines sample information with prior beliefs, producing more robust inference under uncertainty.

c. Time-Varying Parameter VAR (TVP-VAR)

TVP-VAR allows parameters to evolve over time, capturing adaptive monetary policy behavior.

Model specification:Yt=BtYt−1+εtY_t = B_t Y_{t-1} + \varepsilon_t

Parameter evolution:Bt=Bt−1+νtB_t = B_{t-1} + \nu_t

This approach is particularly relevant for analyzing policy responses during crisis episodes, such as the COVID-19 pandemic.

4. Main Findings

  1. QE effects are nonlinear
    The impact of QE varies significantly across economic regimes.
  2. Low-volatility regime
    QE effectively supports:
    • inflation control,
    • government bond market stability,
    • overall macroeconomic balance.
  3. High-volatility regime
    QE:
    • exerts pressure on GDP growth,
    • weakens monetary policy independence,
    • amplifies exchange rate sensitivity to external shocks.
  4. Strategic role of government bonds (SUN)
    Government bonds serve as a key financial stability anchor and a crucial channel for fiscal–monetary coordination.
  5. Time-varying policy dynamics
    TVP-VAR results confirm that Indonesia’s monetary policy response is adaptive rather than static, particularly during crisis periods.

5. Academic and Policy Implications

  • QE in emerging markets cannot be treated as a neutral instrument; its effectiveness is highly regime-dependent.
  • The New Monetary Trinity framework requires adaptive monetary policy supported by strong fiscal–monetary coordination.
  • Financial stability must be explicitly integrated into the design of non-conventional monetary policy.

6. Key Takeaway

In Indonesia, QE functions as an effective stabilization tool under normal conditions, but during periods of high volatility it may erode monetary autonomy, underscoring the need for adaptive monetary governance.