Saran - PENGARUH KEBIJAKAN MONETER SYARIAH TERHADAP INDEKS PRODUKSI INDUSTRI TAHUN

BAB V : PENUTUP

B. Saran

Berdasarkan kesimpulan yang telah dijelaskan diatas, maka peneliti dapat

menyampaikan beberapa saran sebagai berikut:

1. Hasil dalam penelitian ini menunjukkan bahwa dalam jangka panjang

variabel SBIS dan Pembiayaan bank syariah dapat meningkatkan

Indeks Produksi Industri (IPI). Hal ini menunjukkan bahwa transmisi

kebijakan moneter syariah jalur pembiayaan memberikan kontribusi

positif terhadap pertumbuhan sektor riil. Untuk itu, diharapkan bagi

pembuat kebijakan dalam hal ini pemerintah untuk berupaya dalam

2. Penelitian ini hanya melihat bagaimana pengaruh dari variabel

instrumen moneter syariah dan pembiayaan bank syariah dalam

mempengaruhi Indeks Produksi Industri (IPI). Disarankan pada

penelitian selanjutnya untuk menggunakan variabel konvensional agar

terlihat perbandingan mana transmisi kebijkan moneter yang lebih baik

antara variabel jalur pembiayaan pada perbankan syariah dengan

variabel jalur kredit pada perbankan konvensional dalam

Daftar Pustaka

Ascarya. 2008. Akad & Produk Bank Syariah, Jakarta: PT RajaGrafindo Persada.

Ascarya. 2012. ”Alur Transmisi dan Efektivitas Kebijakan Moneter Ganda di Indonesia”. Buletin Ekonomi Moneter dan Perbankan. Vol. 14, No. 3, hlm. 283 – 315.

Ascarya. 2010. “Peran Perbankan Syariah dalam Transmisi Kebijakan Moneter Ganda”. Iqtishodia, Jurnal Ekonomi Islam Republika, 26 Agustus 2010.

Asngari, Imam. 2014. “Pengaruh Pembiayaan Bank Syariah Terhadap Pertumbuhan Ekonomi Indonesia”. Prosiding. Seminar Nasional Hasil-Hasil Penelitian Dan Silatnas IV Fordebi.

Asnuri, Wulan. 2013. “Pengaruh Instrumen Moneter Syariah Dan Ekspor Terhadap Pertumbuhan Ekonomi Di Indonesia”. Al-Iqtishad, Vol. V, No. 2, hlm. 276 – 288.

Beik, „Ayuniyyah, dan Arsyianti. 2013. “Dynamic Analysis of Islamic Bank and Monetary Instrumenowards Real Output and Inflation in Indonesia”. Proceeding of Sharia Economics Conference-Hannover, 9 February 2013.

Daniar. 2016. “Transmisi Kebijakan Moneter Syariah: Sebuah Analisa”. FALAH Jurnal Ekonomi Syariah, Vol. 1. No. 1, hlm. 91 – 102.

Fitriani, Aziz, dan Amalia. 2012. “Keterkaitan Indikator Moneter Syariah Terhadap Pendapatan Domestik Bruto”. Signifikan, Vol. 1, No. 1, hlm. 45 – 52.

Istiqomah. 2012. “Dinamika Interaksi Antara Variabel Moneter Dan Pasar Modal Syariah Terhadap Pertumbuhan Ekonomi Indonesia”. Skripsi. Bogor : Institut Pertanian Bogor.

Latifah, Nur Aini. “Kebijakan Moneter Dalam Perspektif Ekonomi Syariah”. MODERNISASI, Vol. 11, No. 2, hlm. 124 – 133.

Lestari, Nuri Ayu. 2012. “Efektivitas Instrumen Keuangan Syariah Terhadap Kinerja Perbankan Syariah di Indonesia dengan Metode Vector Autu Regression (VAR) / Vector Error Correction Model (VECM)”. Skripsi. Bandung : Politeknik Negeri Bandung.

Magdalena, Ingrit dan Wahyu Ario Pratomo. 2014. “Analisis Efektivitas Transmisi Kebijakan Moneter Ganda di Indonesia”. Jurnal Ekonomi dan Keuangan, Vol. 2, No. 11, hlm. 657 – 671.

Majid, M. Shabri Abd. Dan Salina H. Kassim. 2015. "Assessing the contribution of Islamic finance to economic growth". Journal of Islamic Accounting and Business Research, Vol. 6 Iss 2, pp. 292 – 310.

Muhammad. 2002. “Kebijakan Fiskal dan Moneter Dalam Ekonomi Islami”, Jakarta: Salemba Empat.

Muhammad. 2005. “Manajemen Pembiayaan Bank Syariah”, Yogyakarta : Akademi Manajemen Perusahaan YKPN.

Nugroho, Ris Yuwono Yudo. 2009. “Analisis Faktor-Faktor Penentu Pembiayaan Perbankan Syariah Di Indonesia: Aplikasi Model Vector Error Correction”. Tesis. Bogor: Institut Pertanian Bogor.

Pohan, Aulia. 2008. “Kerangka Kebijakan Moneter dan Implementasinya di Indonesia”, Jakarta : PT RajaGrafindo Persada.

Pratama, Yoghi Citra. 2013. “Effectiveness of Conventional and Syariah Monetary Policy Transmission”. Tazkia Islamic Finance and Business Review, Vol. 8, No. 1, hlm. 79 – 96.

Rafsanjani, Haqiqi dan Raditya Sukmana. 2014. “Pengaruh Perbankan Atas Pertumbuhan Ekonomi: Studi Kasus Bank Konvensional dan Bank Syariah di Indonesia”. Jurnal Aplikasi Manajemen (JAM), Vol. 12, No 3, hlm. 492 – 502.

Sangidi, Wulandari. 2014. “Efektivitas Mekanisme Transmisi Moneter Melalui Jalur Pembiayaan Bank Syariah Di Indonesia”. Skripsi. Bogor :Institut Pertanian Bogor.

Setiawan, Rifki Yudi dan Karsinah. 2016. “Mekanisme Transmisi Kebijakan Moneter Konvensional Dan Syariah Dalam Mempengaruhi Inflasi Dan Pertumbuhan Ekonomi Di Indonesia”. Economics Development Analysis Journal, Vol. 5, No. 4, hlm. 421 – 435.

Simorangkir, Iskandar. 2014. “Pengantar Kebanksentralan Teori dan Praktik di Indonesia”, Jakarta : PT RajaGrafindo Persada.

Soemitra, Andri. 2014. “Bank dan Lembaga Keuangan Syariah”, Jakarta: Kencana.

Sugianto, Hermain, dan Harahap. 2015. “Mekanisme Transmisi Kebijakan Moneter di Indonesia Melalui Sistem Moneter Syariah”. Human Falah, Vol.2,No. 2, hlm. 50 – 74.

Sukmana, Raditya dan Salina H. Kassim. 2010. "Roles of the Islamic banks in the monetary transmission process in Malaysia", International Journal of Islamic and Middle Eastern Finance and Management, Vol. 3 Iss 1, pp. 7 – 19.

Susilo, Joko dan Nirdukita Ratnawati. 2015. “Analisis Pengaruh Pembiayaan Bank Syariah Dan Tenaga Kerja Terhadap Peningkatan Produk Domestik Bruto (Pdb): Analisis Sektoral Tahun 2006 – 2013”. Seminar Nasional Cendekiawan.

Warjiyo, Perry dan Solikin. 2003. “Kebijakan Moneter di Indonesia”. Buku Seri Kebanksentralan No. 6, Pusat Pendidikan dan Studi Kebanksentralan (PPSK), Bank Indonesia.

Zein, Aliman Syahuri. 2015. “Apa Dan Bagaimana: Mekanisme Transmisi Kebijakan Moneter Syariah Di Indonesia”, At-Tijaroh, Vol. 1, No. 1, hlm. 91 – 122.

96 LAMPIRAN

1. Uji Stasioneritas Data

Null Hypothesis: LOGIPI has a unit root Exogenous: Constant

Lag Length: 2 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -0.937731 0.7702 Test critical values: 1% level -3.531592

5% level -2.905519

10% level -2.590262

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: D(LOGIPI) has a unit root Exogenous: Constant

Lag Length: 1 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -9.770761 0.0000 Test critical values: 1% level -3.531592

5% level -2.905519

10% level -2.590262

*MacKinnon (1996) one-sided p-values.

Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -4.336528 0.0008 Test critical values: 1% level -3.528515

5% level -2.904198

10% level -2.589562

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: D(LOGPEMBIAYAAN) has a unit root Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -7.614862 0.0000 Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: SBIS has a unit root Exogenous: Constant

Lag Length: 1 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -1.685770 0.4338 Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: D(SBIS) has a unit root Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -5.567650 0.0000 Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: PUAS has a unit root Exogenous: Constant

Lag Length: 1 (Automatic - based on SIC, maxlag=10)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -1.785881 0.3844 Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

*MacKinnon (1996) one-sided p-values.

Null Hypothesis: D(PUAS) has a unit root Exogenous: Constant

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -12.23222 0.0001 Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

*MacKinnon (1996) one-sided p-values.

2. Uji Lag Optimal

VAR Lag Order Selection Criteria

Endogenous variables: LOGIPI LOGPEMB SBIS PUAS Exogenous variables: C

Date: 02/19/17 Time: 19:36 Sample: 2011M01 2016M10 Included observations: 62

Lag LogL LR FPE AIC SC HQ

0 24.40368 NA 6.09e-06 -0.658183 -0.520949 -0.604302 1 268.1653 448.2068 3.93e-09 -8.005331 -7.319159* -7.735923* 2 288.0563 34.00727* 3.49e-09* -8.130849* -6.895739 -7.645914 3 302.2952 22.50658 3.75e-09 -8.074038 -6.289990 -7.373576 4 313.8780 16.81381 4.47e-09 -7.931549 -5.598563 -7.015560 5 325.9762 16.00085 5.35e-09 -7.805685 -4.923761 -6.674169 6 343.4568 20.86389 5.54e-09 -7.853445 -4.422583 -6.506402 7 362.0005 19.74008 5.76e-09 -7.935500 -3.955700 -6.372930 8 379.2997 16.18310 6.57e-09 -7.977409 -3.448671 -6.199312

* indicates lag order selected by the criterion

100

FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion

3. Uji Stabilitas VAR

Roots of Characteristic Polynomial

Endogenous variables: LOGIPI LOGPEMB SBIS PUAS Exogenous variables: C Lag specification: 1 2 Date: 02/19/17 Time: 19:56 Root Modulus 0.961341 0.961341 0.904003 0.904003 0.644518 - 0.029284i 0.645183 0.644518 + 0.029284i 0.645183 -0.378076 0.378076 -0.285829 0.285829 0.098990 - 0.132264i 0.165205 0.098990 + 0.132264i 0.165205

No root lies outside the unit circle. VAR satisfies the stability condition.

101

4. Uji Kointegrasi

Date: 02/19/17 Time: 19:42

Sample (adjusted): 2011M04 2016M10 Included observations: 67 after adjustments Trend assumption: Quadratic deterministic trend Series: LOGIPI LOGPEMB SBIS PUAS Lags interval (in first differences): 1 to 2

Unrestricted Cointegration Rank Test (Trace)

Hypothesized Trace 0.05

No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.333690 68.32135 55.24578 0.0023 At most 1 * 0.314186 41.11932 35.01090 0.0099 At most 2 0.138274 15.85035 18.39771 0.1097 At most 3 * 0.084014 5.879556 3.841466 0.0153

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05

No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None 0.333690 27.20203 30.81507 0.1299 At most 1 * 0.314186 25.26897 24.25202 0.0366 At most 2 0.138274 9.970796 17.14769 0.4000 At most 3 * 0.084014 5.879556 3.841466 0.0153

102

Max-eigenvalue test indicates no cointegration at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level

**MacKinnon-Haug-Michelis (1999) p-values

Date: 02/19/17 Time: 20:18 Sample: 2011M01 2016M10 Included observations: 68

Series: LOGIPI LOGPEMB SBIS PUAS Lags interval: 1 to 1 Selected (0.05 level*) Number of Cointegrating Relations by Model

Data Trend: None None Linear Linear Quadratic Test Type No Intercept Intercept Intercept Intercept Intercept

No Trend No Trend No Trend Trend Trend

Trace 1 2 2 3 2

Max-Eig 1 2 2 3 2

*Critical values based on MacKinnon-Haug-Michelis (1999)

Information Criteria by

Rank and Model

103

Rank or No Intercept Intercept Intercept Intercept Intercept No. of CEs No Trend No Trend No Trend Trend Trend

Log Likelihood by Rank (rows) and Model (columns) 0 256.0085 256.0085 267.2793 267.2793 276.4792 1 279.6803 280.0349 282.3706 287.0731 295.9613 2 285.7955 294.1814 294.3814 302.0646 309.5549 3 289.1652 298.7718 298.7899 312.7522 314.0325 4 289.2308 301.2159 301.2159 316.8162 316.8162 Akaike Information Criteria by Rank (rows) and Model (columns) 0 -7.059074 -7.059074 -7.272922 -7.272922 -7.425860 1 -7.520010 -7.501028 -7.481489 -7.590385 -7.763569 2 -7.464575 -7.652394 -7.599453 -7.766605 -7.928084* 3 -7.328389 -7.522700 -7.493820 -7.816242 -7.824484 4 -7.095022 -7.329880 -7.329880 -7.671064 -7.671064 Schwarz Criteria by Rank (rows) and Model (columns) 0 -6.536837 -6.536837 -6.620125 -6.620125 -6.642504

104

1 -6.736654* -6.685032 -6.567574 -6.643830 -6.719095 2 -6.420100 -6.542640 -6.424419 -6.526292 -6.622491 3 -6.022797 -6.119188 -6.057668 -6.282171 -6.257773 4 -5.528311 -5.632609 -5.632609 -5.843234 -5.843234

5. Uji Kausalitas Granger

Pairwise Granger Causality Tests Date: 02/10/17 Time: 10:50 Sample: 2011M01 2016M10 Lags: 1

Null Hypothesis: Obs F-Statistic Prob.

LOGPEMBIAYAAN does not Granger Cause LOGIPI 69 11.0125 0.0015 LOGIPI does not Granger Cause LOGPEMBIAYAAN 0.77771 0.3810

PUAS does not Granger Cause LOGIPI 69 0.31454 0.5768 LOGIPI does not Granger Cause PUAS 0.19585 0.6595

SBIS does not Granger Cause LOGIPI 69 0.53743 0.4661 LOGIPI does not Granger Cause SBIS 0.14230 0.7072

PUAS does not Granger Cause LOGPEMBIAYAAN 69 2.02882 0.1591 LOGPEMBIAYAAN does not Granger Cause PUAS 0.72979 0.3960

SBIS does not Granger Cause LOGPEMBIAYAAN 69 0.35893 0.5512 LOGPEMBIAYAAN does not Granger Cause SBIS 0.36051 0.5503

SBIS does not Granger Cause PUAS 69 12.4090 0.0008 PUAS does not Granger Cause SBIS 1.39050 0.2426

105

6. Uji Estimasi VECM

Vector Error Correction Estimates Date: 02/19/17 Time: 19:43

Sample (adjusted): 2011M04 2016M10 Included observations: 67 after adjustments Standard errors in ( ) & t-statistics in [ ]

Cointegrating Eq: CointEq1

LOGIPI(-1) 1.000000 LOGPEMB(-1) 0.218332 (0.07046) [ 3.09877] SBIS(-1) 0.069852 (0.01999) [ 3.49409] PUAS(-1) -0.097313 (0.02297) [-4.23735] @TREND(11M01) -0.007926 C -5.482640

Error Correction: D(LOGIPI) D(LOGPEMB) D(SBIS) D(PUAS)

CointEq1 -0.232353 0.077332 0.449007 6.649976 (0.10219) (0.08220) (0.82847) (1.65097) [-2.27364] [ 0.94082] [ 0.54197] [ 4.02792]

106 D(LOGIPI(-1)) -0.346846 -0.003005 0.017204 -4.605916 (0.12139) (0.09764) (0.98408) (1.96108) [-2.85729] [-0.03077] [ 0.01748] [-2.34867] D(LOGIPI(-2)) -0.348861 -0.139844 0.273635 -3.217523 (0.11468) (0.09224) (0.92964) (1.85260) [-3.04217] [-1.51617] [ 0.29434] [-1.73676] D(LOGPEMB(-1)) 0.093385 -0.134751 -5.778292 -6.363733 (0.16931) (0.13618) (1.37252) (2.73517) [ 0.55157] [-0.98954] [-4.20998] [-2.32663] D(LOGPEMB(-2)) 0.045737 0.133940 -0.553175 -8.166979 (0.21013) (0.16901) (1.70350) (3.39475) [ 0.21765] [ 0.79248] [-0.32473] [-2.40577] D(SBIS(-1)) 0.038294 -0.003025 0.246324 -0.170829 (0.01897) (0.01526) (0.15380) (0.30648) [ 2.01853] [-0.19824] [ 1.60164] [-0.55739] D(SBIS(-2)) 0.005550 0.003449 0.189505 0.154682 (0.01461) (0.01175) (0.11842) (0.23599) [ 0.37990] [ 0.29353] [ 1.60023] [ 0.65545] D(PUAS(-1)) -0.008460 -0.002737 0.062860 -0.165456 (0.00958) (0.00771) (0.07768) (0.15480) [-0.88291] [-0.35518] [ 0.80924] [-1.06886] D(PUAS(-2)) -0.002503 -0.007366 0.003356 -0.042375 (0.00785) (0.00631) (0.06360) (0.12674)

107 [-0.31898] [-1.16724] [ 0.05276] [-0.33434] C 0.002986 0.035433 0.213428 0.549136 (0.01342) (0.01080) (0.10882) (0.21686) [ 0.22242] [ 3.28184] [ 1.96126] [ 2.53221] @TREND(11M01) 1.30E-05 -0.000491 -0.003111 -0.008067 (0.00024) (0.00019) (0.00194) (0.00387) [ 0.05422] [-2.55238] [-1.60382] [-2.08698] R-squared 0.346505 0.283830 0.427452 0.459532 Adj. R-squared 0.229809 0.155943 0.325212 0.363020 Sum sq. resids 0.041772 0.027023 2.745232 10.90205 S.E. equation 0.027312 0.021967 0.221409 0.441225 F-statistic 2.969303 2.219377 4.180843 4.761391 Log likelihood 152.1686 166.7586 11.95783 -34.24154 Akaike AIC -4.213988 -4.649510 -0.028592 1.350494 Schwarz SC -3.852023 -4.287546 0.333373 1.712458 Mean dependent 0.002888 0.017324 -0.012239 -0.021194 S.D. dependent 0.031121 0.023911 0.269533 0.552837

Determinant resid covariance (dof adj.) 2.97E-09 Determinant resid covariance 1.45E-09

Log likelihood 301.5154

Akaike information criterion -7.567624

Schwarz criterion -5.988142

Pairwise Granger Causality Tests Date: 02/19/17 Time: 20:02 Sample: 2011M01 2016M10 Lags: 1

Null Hypothesis: Obs F-Statistic Prob.

LOGPEMB does not Granger Cause LOGIPI 69 11.0125 0.0015 LOGIPI does not Granger Cause LOGPEMB 0.77771 0.3810

SBIS does not Granger Cause LOGIPI 69 0.53743 0.4661 Pairwise Granger Causality Tests

Date: 02/19/17 Time: 20:02 Sample: 2011M01 2016M10 Lags: 1

Null Hypothesis: Obs F-Statistic Prob.

LOGPEMB does not Granger Cause LOGIPI 69 11.0125 0.0015 LOGIPI does not Granger Cause LOGPEMB 0.77771 0.3810

108

7. Uji Impulse Response Function (IRF)

Respo nse of LOGIPI:

Period LOGIPI LOGPEMB SBIS PUAS

1 0.027312 0.000000 0.000000 0.000000 2 0.013444 -0.000170 0.006285 0.005908 3 0.007487 -0.004866 0.003482 0.006074 4 0.014355 -0.005915 0.002338 0.005484 5 0.014054 -0.005621 0.003217 0.007150 6 0.011417 -0.006144 0.002897 0.007131 7 0.012391 -0.006625 0.002380 0.006793 8 0.013048 -0.006287 0.002461 0.007022 9 0.012443 -0.006276 0.002499 0.007107 10 0.012346 -0.006357 0.002375 0.006984 11 0.012616 -0.006304 0.002344 0.006999 12 0.012550 -0.006245 0.002369 0.007031 13 0.012455 -0.006264 0.002351 0.007014 14 0.012507 -0.006258 0.002331 0.007003 15 0.012525 -0.006240 0.002335 0.007012 16 0.012493 -0.006238 0.002334 0.007012 17 0.012495 -0.006240 0.002327 0.007008 18 0.012506 -0.006235 0.002326 0.007009 19 0.012500 -0.006233 0.002327 0.007010 20 0.012497 -0.006233 0.002325 0.007009

109

8. Uji Forecast Error Variance Decomposition

Varian ce Decom position of LOGIPI:

Period S.E. LOGIPI LOGPEMB SBIS PUAS

1 0.027312 100.0000 0.000000 0.000000 0.000000 2 0.031640 92.56398 0.002899 3.946349 3.486775 3 0.033613 86.97684 2.098141 4.569798 6.355220 4 0.037503 84.52359 4.172997 4.059696 7.243717 5 0.041195 81.68978 5.320258 3.974403 9.015556 6 0.043868 78.81211 6.653609 3.941066 10.59322 7 0.046622 76.83849 7.910170 3.749664 11.50168 8 0.049384 75.46572 8.670994 3.590409 12.27287 9 0.051863 74.18080 9.326108 3.487495 13.00560 10 0.054194 73.12553 9.916996 3.385852 13.57162 11 0.056483 72.30657 10.37500 3.289189 14.02924 12 0.058668 71.59808 10.74978 3.211892 14.44024 13 0.060754 70.96911 11.08745 3.144863 14.79857 14 0.062778 70.43540 11.37751 3.083159 15.10393 15 0.064742 69.96957 11.62674 3.028976 15.37471 16 0.066642 69.55141 11.84944 2.981400 15.61776 17 0.068489 69.17902 12.04898 2.938233 15.83376 18 0.070289 68.84662 12.22667 2.899197 16.02752 19 0.072043 68.54544 12.38710 2.864046 16.20341 20 0.073755 68.27168 12.53310 2.832038 16.36319 21 0.075428 68.02252 12.66602 2.802733 16.50873

110 22 0.077065 67.79437 12.78757 2.775900 16.64216 23 0.078667 67.58447 12.89939 2.751228 16.76491 24 0.080238 67.39095 13.00251 2.728440 16.87810 25 0.081778 67.21194 13.09787 2.707346 16.98284 26 0.083290 67.04579 13.18637 2.687771 17.08008 27 0.084775 66.89117 13.26872 2.669549 17.17056 28 0.086235 66.74696 13.34553 2.652546 17.25496 29 0.087670 66.61212 13.41735 2.636647 17.33389 30 0.089082 66.48575 13.48465 2.621747 17.40786 31 0.090472 66.36709 13.54784 2.607755 17.47731 32 0.091841 66.25546 13.60729 2.594590 17.54266 33 0.093189 66.15025 13.66332 2.582182 17.60425 34 0.094519 66.05091 13.71623 2.570466 17.66240 35 0.095830 65.95697 13.76625 2.559387 17.71739 36 0.097123 65.86801 13.81363 2.548894 17.76946 37 0.098400 65.78363 13.85857 2.538942 17.81886 38 0.099660 65.70349 13.90125 2.529490 17.86577 39 0.100904 65.62728 13.94183 2.520502 17.91039 40 0.102133 65.55471 13.98048 2.511943 17.95286

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