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1. Tujuan Buku | Book Objective

ID
Buku ini memberikan kerangka ekonometrika terapan untuk menganalisis data keuangan dan makro, dengan fokus pada dinamika waktu, risiko, volatilitas, dan hubungan jangka panjang.

EN
This book provides an applied econometrics framework for analyzing financial and macroeconomic data, emphasizing time dynamics, risk, volatility, and long-run relationships.

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2. Fondasi Matematis & Statistik | Mathematical & Statistical Foundations (Ch. 1–2)

Model Inti | Core Model$$\min_{\beta}(y-X\beta)'(y-X\beta)$$

Return Keuangan | Financial Return$$r_t = \ln P_t – \ln P_{t-1}$$

ID
Harga aset umumnya tidak stasioner, sehingga return digunakan sebagai variabel utama.

EN
Asset prices are typically non-stationary; therefore, returns are used for econometric modeling.

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3. Regresi Linear Klasik (OLS) | Classical Linear Regression (Ch. 3–4)

Model$$y_t = \beta_0 + \beta_1 x_{1t} + \cdots + \beta_k x_{kt} + u_t$$

Estimator$$\hat{\beta}=(X’X)^{-1}X’y$$

ID
OLS menjadi fondasi inferensi statistik dan titik awal seluruh model lanjutan.

EN
OLS serves as the statistical foundation and baseline for advanced econometric models.

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4. Diagnostic Testing | Uji Diagnostik (Ch. 5)

Masalah Utama | Key Problems

• Heteroskedastisitas:

$$Var(u_t|X)\neq\sigma^2$$

• Autokorelasi:

$$u_t=\rho u_{t-1}+\varepsilon_t$$

• Structural break:

$$\beta_t\neq\beta_{t-1}$$

ID
Tanpa uji diagnostik, hasil regresi berisiko bias dan tidak valid.

EN
Without diagnostic testing, regression results may be biased and unreliable.

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5. Time Series Univariate | Model Deret Waktu Tunggal (Ch. 6)

Model

• AR(p):

$$y_t=c+\sum_{i=1}^p\phi_i y_{t-i}+u_t$$

• MA(q), ARMA(p,q)

ID
Digunakan untuk menangkap dinamika waktu dan melakukan peramalan.

EN
Used to capture temporal dynamics and generate forecasts.

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6. Multivariate Time Series (VAR) | VAR Model (Ch. 7)

Model$$Y_t=c+\sum_{i=1}^pA_iY_{t-i}+u_t$$

Analisis Turunan | Derived Analysis

• Granger causality
• Impulse Response Function (IRF)
• Forecast Error Variance Decomposition (FEVD)

ID / EN
Standar analisis transmisi kebijakan moneter.

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7. Cointegration & VECM | Hubungan Jangka Panjang (Ch. 8)

VECM$$\Delta Y_t=\Pi Y_{t-1}+\sum\Gamma_i\Delta Y_{t-i}+u_t,\quad \Pi=\alpha\beta’$$

ID
Menggabungkan keseimbangan jangka panjang dan penyesuaian jangka pendek.

EN
Combines long-run equilibrium with short-run dynamics.

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8. Volatility Modeling | Pemodelan Volatilitas (Ch. 9)

GARCH(1,1)$$\sigma_t^2=\omega+\alpha u_{t-1}^2+\beta\sigma_{t-1}^2$$

ID
Menangkap volatility clustering dan risiko pasar.

EN
Captures volatility clustering and market risk.

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9. Regime Switching & State Space (Ch. 10)

Markov Switching$$y_t=\beta_{s_t}x_t+u_t$$

State Space$$\begin{aligned} y_t&=Z_t\alpha_t+\varepsilon_t\\ \alpha_t&=T_t\alpha_{t-1}+\eta_t \end{aligned}$$

ID / EN
Digunakan untuk analisis krisis dan parameter yang berubah sepanjang waktu.

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10. Panel & Discrete Choice | Data Panel & Pilihan Diskrit (Ch. 11–12)

Panel FE$$y_{it}=\alpha_i+\beta x_{it}+\varepsilon_{it}$$

Logit$$P(y=1|x)=\frac{e^{x\beta}}{1+e^{x\beta}}$$

EN
Applied in cross-country, firm-level, and policy probability analysis.

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11. Simulation & Advanced Finance | Simulasi & Teknik Lanjutan (Ch. 13–14)

Bootstrap$$\hat{\theta}^*=f(X^*)$$

Event Study$$CAR=\sum AR_t$$

GMM$$E[g(Z_t,\theta)]=0$$

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12. Research Design | Perancangan Riset (Ch. 15)

ID
Buku menutup dengan panduan menyusun riset empiris yang valid dan siap publikasi.

EN
The final chapter guides readers in designing valid and publishable empirical research.

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🔑 Ringkasan Inti | Core Takeaway

ID
Buku ini menyusun jalur metodologi lengkap:
OLS → Time Series → VAR → VECM → GARCH → Regime → Panel → Advanced Finance

EN
The book establishes a complete econometric pathway from basic regression to advanced financial models.