JAWABAN LATIHAN SOAL EKONOMETRIKA - 02 - i'm darmanto

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18 Sep 2012 ... In matrix terms, the vector of coefficients in multiple regression is calculated by the formula: – b = (x'x)-1 X'Y. 18/09/2012. 3. MK. Ekonometrika ...

JAWABAN LATIHAN SOAL EKONOMETRIKA - 02

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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1. Hasil analisis model linier:

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• Regression coefficients – The formula for the coefficient or slope in simple linear regression is:

– The formula for the intercept (b0) is: – In matrix terms, the vector of coefficients in multiple regression is calculated by the formula: – b = (x'x)-1 X'Y 18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• Standard error of the coefficient (SE Coeff) – For simple linear regression, the standard error of coefficient is:

– The formula for standard error of coefficient for multiple regression is:

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• R2 (R-sq) – Coefficient of determination; indicates how much variation in the response is explained by the model. The higher the R2 , the better the model fits your data. The formula is:

• Adjusted R2 – Accounts for the number of predictors in your model and is useful for comparing models with different numbers of predictors. The formula is:

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• Sum of squares (SS) – The sum of squared distances. SS Total is the total variation in the data. SS Regression is the portion of the variation explained by the model, while SS Error is the portion not explained by the model and is attributed to error. The calculations are:

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• Degrees of freedom (DF) – Indicates the number of independent pieces of information involving the response data needed to calculate the sum of squares. The degrees of freedom for each component of the model are:

18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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• Hasil Model Non-Linier (variabel)

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• Konsep analisis dan interpretasi: 1. Jika ada dua pilihan model linier dan model nonlinier  Pilih fungsi mana yang paling tepat untuk Fungsi Konsumsi. 2. Tanda koefisien regresi  sesuai dengan hipotesa dalam teori ekonomi 3. Koefisien determinasi R2 [ linier  linier ; non-linier  non-linier]  R2 yang paling tinggi dipilih 4. Intersep fungsi konsumsi linier = tingkat subsistensi (nafkah hidup) kehidupan, sebab manusia harus tetap hidup walau tanpa pendapatn (Y = 0) sehingga intersep harus (+). Untuk model non-linier  antiln (1-α) atau antilog (1-α) 18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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5. Hasrat marjinal konsumsi (MPC/Marginal Propensity Consumtion) harus positif lebih kecil dari 1. 6. R2%  Variasi pengeluaran konsumsi mampu dijelaskan oleh perubahan pendapat disposebel. 7. MPC (Linier)  Perubahan pendapatan disposebel ratarata Rp. 1M akan mengubah pengeluaran konsumsi agregat rata-rata sebesar β x Rp. 1M dengan arah yang sama, ceteris paribus. 8. Koefisien elastisitas (Non-linier)  Perubahan pendapatan disposebel rata-rata sebesar 1% akan mengubah pengeluaran konsumsi agregat rata-rata sekitar β% dengan arah yang sama, ceteris paribus. 9. Intersep tidak signifikan  Kesalahan spesifikasi model. 18/09/2012

MK. Ekonometrika | Darmanto, S.Si.

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2. Hasil analisis:

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MK. Ekonometrika | Darmanto, S.Si.

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• Confidence interval – The range in which the estimated mean response for a given set of predictor values is expected to fall. The formula is:

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MK. Ekonometrika | Darmanto, S.Si.

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• atau

1  xi  x  Y i  t 1 ,n  p s  2  2  n x i

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MK. Ekonometrika | Darmanto, S.Si.

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• Selang kepercayaan untuk Qt dari model duga:

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MK. Ekonometrika | Darmanto, S.Si.

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