BULETIN EKONOMI MONETER DAN PERBANKAN Volume 7, Nomor 3, Desember 2004 BANK INDONESIA 343 359 387 461 437 Tinjauan umum Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia Firman Mokhtar Illustrative Subsidy Variations to Attract Investors (using the EMERALD Indonesian multi-regional CGE model) Daniel Pambudi dan Andi Alfian Parewangi Determinan Tingkat Suku Bunga Pinjaman di Indonesia Tahun 1983 - 2002 Taufik Kurniawan Perbandingan Early Warning Systems (EWS) untuk Memprediksi Kebangkrutan Bank Umum di Indonesia Liza Angelina, SE, Msi, Akt
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i
BULETIN EKONOMI MONETERDAN PERBANKAN
Volume 7, Nomor 3, Desember 2004
BANK INDONESIA
343
359
387
461
437
Tinjauan umum
Fiscal and Monetary Policy Interaction :Evidences and Implication for Inflation Targeting in IndonesiaFirman Mokhtar
Illustrative Subsidy Variations to Attract Investors(using the EMERALD Indonesian multi-regional CGE model)Daniel Pambudi dan Andi Alfian Parewangi
Determinan Tingkat Suku Bunga Pinjaman di Indonesia Tahun 1983 - 2002Taufik Kurniawan
Perbandingan Early Warning Systems (EWS) untuk MemprediksiKebangkrutan Bank Umum di IndonesiaLiza Angelina, SE, Msi, Akt
343Tinjauan umum
Sampai dengan triwulan IV-2004, perekonomian Indonesia menunjukkan
perkembangan yang semakin baik. Kestabilan ekonomi makro dapat dipertahankan yang
disertai dengan peningkatan pertumbuhan ekonomi. Laju inflasi tetap dapat dikendalikan
dalam tingkat yang rendah dan tetap sesuai dengan proyeksi yang telah ditetapkan pada
awal tahun. Nilai tukar rupiah relatif stabil dengan volatilitas yang rendah. Seiring dengan
itu, suku bunga di dalam negeri tetap stabil pada tingkat yang relatif rendah sehingga kondusif
bagi perkembangan dunia usaha. Sektor keuangan, khususnya perbankan dan pasar modal,
juga menunjukkan perkembangan yang semakin mantap. Sementara itu, sejalan dengan
meningkatnya kegiatan investasi serta tetap tingginya konsumsi, pertumbuhan ekonomi
dalam triwulan IV-2004 diperkirakan mencapai 5,0%-5,5% (yoy).
Dalam triwulan IV-2004, laju inflasi mengalami peningkatan dari triwulan sebelumnya.
Kenaikan harga pada triwulan terakhir bersifat musiman yang hampir terjadi setiap tahun
yang terkait dengan perayaan hari besar keagamaan dan waktu liburan. Meskipun mengalami
kenaikan pada triwulan laporan, secara keseluruhan dalam tahun 2004 inflasi IHK tetap
dapat dikendalikan yaitu sebesar 6,4% (yoy) atau berada dalam kisaran proyeksi inflasi
yang ditetapkan pada awal tahun yaitu 5,5% + 1% (yoy). Tetap terkendalinya harga-harga
di dalam triwulan laporan tersebut tidak terlepas dari kebijakan moneter yang ditempuh
dalam mengendalikan tekanan inflasi yang bersumber dari interaksi permintaan-penawaran,
mengendalikan gejolak nilai tukar, maupun mencegah memburuknya ekspektasi. Selain
itu, berbagai langkah yang ditempuh Pemerintah dalam mengupayakan kecukupan dan
kelancaran pasokan barang dan jasa juga turut berperan dalam pencapaian laju inflasi
yang relatif rendah tersebut.
Sementara itu, nilai tukar rupiah bergerak stabil dengan tingkat volatilitas yang rendah.
Stabilnya nilai tukar pada triwulan laporan tidak terlepas dari terdapatnya pasokan valas
yang berasal dari capital inflows yang didukung oleh kepercayaan pasar atas prospek
ekonomi makro Indonesia, perbaikan persepsi risiko, serta dampak dari pelemahan dolar
TINJAUAN UMUM
344 Buletin Ekonomi Moneter dan Perbankan, September 2004
AS secara global. Stabilnya nilai tukar tersebut didukung pula oleh perkembangan Neraca
Pembayaran Indonesia (NPI) dalam triwulan IV-2004 yang tetap tercatat surplus sehingga
cadangan devisa masih dalam posisi yang aman dan memadai.
Seiring dengan peningkatan permintaan domestik, pertumbuhan ekonomi triwulan
IV-2004 meningkat dibandingkan triwulan sebelumnya. Peningkatan pertumbuhan tersebut
diikuti dengan semakin seimbangnya pola ekspansi ekonomi yang tercermin dari
peningkatan investasi dan ekspor. Peningkatan investasi tersebut tidak terlepas dari
dorongan konsumsi dan dukungan pembiayaan perbankan serta pasar modal. Sementara
perbaikan ekspor yang telah berlangsung sejak triwulan II-2004 terus berlanjut hingga
triwulan laporan.
Berbagai indikator moneter dan keuangan dalam triwulan IV-2004 masih terkendali
dan menunjukkan perkembangan yang relatif stabil. Hal tersebut seperti tercemin pada
perkembangan uang primer, uang beredar, nilai tukar, suku bunga serta diikuti kondisi
kondisi pasar modal yang mengalami perkembangan cukup pesat. Meningkatnya permintaan
uang oleh masyarakat menjelang perayaan beberapa hari besar keagamaan dan tahun
baru telah menyebabkan pertumbuhan uang primer meningkat, namun masih dalam batas
yang aman. Sejalan dengan pertumbuhan uang primer, jumlah uang beredar juga mengalami
pertumbuhan seiring dengan meningkatnya kegiatan perekonomian.
Sejalan dengan kestabilan ekonomi makro, peran dan kinerja perbankan nasional
terus menunjukkan kestabilan dan perbaikan yang berarti. Fungsi intermediasi perbankan
nasional secara bertahap menunjukkan perbaikan tercermin dari peningkatan kredit
perbankan khususnya kredit kepada UMKM. Di sisi lain, kualitas kredit perbankan juga
relatif membaik yang ditunjukkan oleh penurunan NPL gross maupun net. Dana pihak ketiga
(DPK) juga meningkat, mencerminkan tetap terjaganya kepercayaan terhadap perbankan.
Profitabilitas perbankan juga menunjukkan peningkatan, dan sejalan dengan itu aspek
permodalan tercatat tetap memadai.
Ke depan, sejalan dengan berbagai upaya pemulihan ekonomi yang akan terus
diperkuat disertai dengan ekspansi ekonomi yang lebih seimbang di tahun 2005, kestabilan
ekonomi makro diperkirakan akan berlanjut di tahun 2005. Pertumbuhan ekonomi Indonesia
triwulan I-2005 diperkirakan akan berkisar antara 5,0%-6,0% (yoy). Tekanan inflasi khususnya
di triwulan I-2005 diperkirakan akan meningkat terutama terkait dengan rencana untuk
menaikkan harga BBM oleh Pemerintah serta meningkatnya permintaan barang dan jasa
dalam rangka produksi dan konsumsi. Pergerakan nilai tukar yang stabil dalam triwulan I-
2005 diperkirakan akan memberikan pengaruh yang positif terhadap ekspektasi harga.
345Tinjauan umum
Perkiraan stabilitas nilai tukar tersebut sejalan dengan kinerja NPI yang diperkirakan tetap
menunjukkan perkembangan yang baik.
Menghadapi potensi meningkatnya tekanan inflasi tersebut, kebijakan moneter ke
depan tetap diarahkan pada upaya mencapai sasaran inflasi yang telah ditetapkan, namun
dengan tetap menjaga momentum pertumbuhan yang sedang terjadi. Secara operasional,
kebijakan moneter tersebut dilakukan dengan mengarahkan uang primer berada pada proyeksi
indikatifnya yakni rata-rata tumbuh sebesar 11,5 - 12,5% pada tahun 2005. Untuk meningkatkan
efektivitas kebijakan moneter Bank Indonesia akan menggunakan suku bunga sebagai
instrumen kebijakan moneter pada pertengahan tahun 2005. Penggunaan target operasional
suku bunga sebagai pengganti base money dalam pengendalian moneter ini juga dimaksudkan
agar kebijakan moneter lebih fleksibel dalam merespon dinamika perekonomian yang terjadi
serta agar sinyal kebijakan ini dapat lebih mudah dibaca oleh pasar.
Di bidang perbankan, seiring dengan membaiknya perekonomian, kinerja perbankan
pada tahun 2005 diperkirakan akan membaik dan fungsi intermediasi terus mengalami
peningkatan. Kebijakan perbankan akan diarahkan untuk melanjutkan stabilitas sistem
perbankan yang telah ada dan mengakselerasi upaya-upaya untuk mendorong fungsi
intermediasi perbankan. Selain itu, dengan semakin meningkatnya persaingan dan mulai
diterapkannya skim penjaminan LPS, bank-bank perlu memperhatikan adanya risiko
likuiditas. Dalam mengantisipasi munculnya risiko tersebut, Bank Indonesia akan
mengarahkan industri perbankan nasional untuk dapat mempercepat proses konsolidasi
dan penguatan institusional. Selain itu, dengan semakin meningkatnya integrasi dan
keterlibatan bank dalam kegiatan pasar modal dan besarnya risiko dari kegiatan ini, Bank
Indonesia akan segera menyempurnakan dan memperkuat monitoring terhadap
pelaksanaan berbagai peraturan yang terkait dengan prinsip kehati-hatian dalam kegiatan
tersebut. Sejalan dengan arah kebijakan tersebut, dalam bulan Januari 2005 Bank
Indonesia mengeluarkan Paket Kebijakan Perbankan yang berisikan beberapa
penyempurnaan ketentuan perbankan
1. EVALUASI PERKEMBANGAN EKONOMI MAKRO DAN INFLASI
1.1. Kondisi Ekonomi Makro
Dalam triwulan IV-2004, kinerja perekonomian diperkirakan lebih baik dibandingkan
triwulan sebelumnya dan mencapai 5,0%-5,5% (yoy). Pertumbuhan ekonomi tersebut
terutama didorong oleh pertumbuhan konsumsi terutama konsumsi swasta. Meskipun
346 Buletin Ekonomi Moneter dan Perbankan, September 2004
demikian, secara umum pola pertumbuhan tersebut telah menunjukkan perbaikan, yang
ditandai oleh meningkatnya peran investasi dan ekspor dalam mendorong perekonomian.
Di sisi lain, tingginya permintaan telah mendorong pesatnya peningkatan impor sebagai
upaya untuk memenuhi peningkatan utilisasi maupun kapasitas produksi terpasang.
Pada triwulan IV-2004, konsumsi diperkirakan tumbuh lebih tinggi sebesar 5,4% -
5,9%, dibandingkan dengan triwulan sebelumnya yang hanya tumbuh sebesar 4,2%.
Peningkatan pengeluaran konsumsi rumah tangga tersebut sejalan dengan hasil survei
Penjualan Eceran, survei JETRO, serta sejalan dengan membaiknya kondisi kepercayaan
konsumen. Namun demikian, pertumbuhan konsumsi swasta tersebut masih berada di bawah
rata-rata pertumbuhan pada periode sebelum krisis (1993 sd pertengahan 1997) yang
mencapai 9,9% (yoy) sehingga cukup wajar.
Peningkatan konsumsi masyarakat diikuti juga dengan peningkatan investasi. Kegiatan
investasi pada triwulan IV-2004 tumbuh sebesar 14,5 – 15,0% (yoy), meningkat dibandingkan
triwulan sebelumnya yang mencapai 13,1% (yoy). Kontribusi investasi terhadap pertumbuhan
ekonomi pada triwulan laporan juga meningkat menjadi 2,96%. Peningkatan investasi
tersebut terutama didukung oleh tersedianya pembiayaan oleh perbankan yang cenderung
meningkat.
Secara sektoral, seluruh sektor ekonomi kecuali sektor pertambangan mengalami
pertumbuhan pada ekonomi triwulan IV-2004. Peningkatan kinerja tersebut utamanya
disebabkan oleh adanya beberapa perayaan hari besar di akhir tahun serta dukungan
yang semakin meningkat di sisi pembiayaan. Di sisi lain terus meningkatnya permintaan
diharapkan juga akan mendorong kegiatan ekonomi sektoral untuk meningkatkan utilisasinya
sehingga iklim investasi akan semakin bergairah dan perekonomian secara keseluruhan
bergerak ke arah yang semakin baik.
Perkembangan Neraca Pembayaran Indonesia (NPI) dalam triwulan IV-2004
menunjukkan perkembangan yang terus positif sebagaimana tercermin dari surplus NPI
sebesar USD1,5 miliar disepanjang triwulan laporan. Surplus tersebut mengakibatkan posisi
cadangan devisa menjadi USD 36,3 miliar atau setara dengan 5,8 bulan impor dan
pembayaran utang Pemerintah, atau lebih tinggi dari yang diperkirakan semula. Surplus
tersebut utamanya disebabkan oleh terjadinya surplus pada transaksi berjalan (current
account) yang disebabkan oleh peningkatan pertumbuhan ekspor khususnya migas yang
pada triwulan ini mengalami pertumbuhan sebesar 47,5%. Neraca modal pada triwulan IV-
2004 tetap tercatat mengalami surplus yang diperkirakan mencapai USD749 juta
347Tinjauan umum
1.2. Inflasi
Secara umum inflasi dalam triwulan IV-2004 menunjukkan peningkatan sejalan
meningkatnya permintaan barang dan jasa sehubungan dengan perayaan hari keagamaan
dan liburan akhir tahun. Inflasi IHK selama triwulan IV-2004 mencapai 2,51% (qtq) meningkat
cukup tinggi dibandingkan dengan triwulan sebelumnya yang hanya sebesar 0,5% (qtq).
Sampai dengan akhir tahun 2004, inflasi IHK tercatat sebesar 6,40% (yoy), lebih tinggi bila
Tabel 1.1. Indikator Makroekonomi
Trw IV Trw I Trw II Trw III Trw IVIndikator
2003 2004
IHK (%)Triwulanan (quarter to quarter)Tahunan (year on year)
PDB (% pertumbuhan, tahunan)Dari sisi permintaan :
Konsumsi TotalInvestasi Total
Dari sisi produksi :PertanianPertambanganIndustri Pengolahan
Sektor eksternal :Ekspor non migas (fob, % pertumbuhan tahunan)Impor non migas (c&f, % pertumbuhan tahunan)Transaksi berjalan (juta USD)Posisi Utang LN (juta USD)
1) Rata-rata tertimbang akhir periode2) REER adalah indeks nilai tukar rupiah per mata uang negara mitra dagang yang dibobot dengan total ekspor dan impor dari 8 mitra dagang utama Indonesia.* : Perkiraan Bank Indonesia menggunakan tahun dasar 2000** : Angka Sementara*** : Angka November 2005 Sumber : BPS (diolah) dan Bank Indonesia
2,515,06
4,35
5,01-6,71
-0,173,193,87
2,368,55
1.624135.402
166.474223.799955.692
8,314,656,62
15,0715,68
8.42088,468.468
0,915,11
4,46
6,434,24
5,43-2,315,23
1,48-0,71-554
136.679
142.817219.087935.249
7,425,875,86
14,6115,12
8.56486,038.580
2,356,83
4,32
5,359,25
1,67-7,225,98
3,87,5315
133.138
155.466223.726975.166
7,304,246,23
14,1014,64
9.40081,579.392
2,516,40
5,0 – 5,5*
5,4 – 5,9*14,5 –15,0*
3,1 – 3,6*-6,4 - -5,9*
4,9 – 5,4*
9,8**4,6**
2.713**134.329**
199.446**250.222***1.000.339***
7,433,76
6,36***13,57***14,18***
933590,329.120
0,515,06
5,03
4,2113,09
2,39-5,965,28
23,330,7
2.503131.838**
175.351240.911986.806
7,394,136,31
13,8014,33
8.42094,749.163
348 Buletin Ekonomi Moneter dan Perbankan, September 2004
dibandingkan dengan tahun sebelumnya yang mencapai 5,06% (yoy). Namun demikian,
peningkatan permintaan tersebut masih dapat direspon dengan cukup baik oleh sisi
penawaran meskipun terdapat beberapa bencana alam di beberapa daerah. Dengan kondisi
tersebut, realisasi inflasi IHK 2004 masih sesuai dengan proyeksi Bank Indonesia di awal
tahun sebesar 5,5% ± 1,0% (yoy).
Peningkatan inflasi IHK dalam triwulan IV-2004 terutama disebabkan adanya faktor
musiman seperti beberapa perayaan hari raya keagamaan dan akhir tahun serta kenaikan
harga BBM yaitu elpiji, Pertamax dan Pertamax Plus. Meskipun kenaikan harga barang-
barang administered price tersebut memberikan kontribusi terhadap peningkatan inflasi
pada periode tersebut, namun dampak kenaikan tersebut dapat diminimilisasi mengingat
tidak adanya perubahan harga barang-barang administered yang strategis seperti seperti
harga BBM bersubsidi, tarif dasar listrik dan cukai rokok. Berdasarkan kelompok barang,
kelompok barang yang dominan dalam menyumbang inflasi adalah kelompok bahan
makanan dan kelompok perumahan, air, listrik, gas dan bahan bakar.
Sementara itu, perkembangan inflasi inti relatif stabil selama periode laporan.
Perkembangan ini terlihat dengan kebijakan moneter Bank Indonesia yang ditempuh dalam
mengendalikan sisi permintaan agregat yang dilakukan melalui kebijakan moneter yang
cenderung ketat.
2. EVALUASI PERKEMBANGAN DAN KEBIJAKAN MONETER
Secara umum, pelaksanaan kebijakan moneter dalam triwulan IV-2004 tetap diarahkan
pada pencapaian sasaran inflasi dalam jangka menengah-panjang dengan mengendalikan
faktor-faktor yang menjadi penyebab utama inflasi, yaitu nilai tukar rupiah, permintaan
domestik dan ekspektasi. Dalam operasionalnya, kebijakan yang ditempuh dilakukan dengan
kebijakan moneter yang cenderung ketat (tight bias) melalui upaya penyerapan kelebihan
likuiditas sistem perbankan secara optimal. Penerapan kebijakan moneter ini merupakan
bentuk tindakan antisipatif kebijakan moneter dalam rangka mencapai dan mengamankan
sasaran inflasi jangka menengah yang telah diputuskan Pemerintah dan berlaku untuk 3
(tiga) tahun ke depan sejak 2005. Selain itu, penerapan kebijakan tight bias ini juga
dimaksudkan untuk tetap mendukung proses pemulihan ekonomi yang saat ini masih
berlangsung.
Sejalan dengan itu, besaran-besaran moneter dalam triwulan IV-2004 menunjukkan
perkembangan yang relatif stabil dan sebagian besar masih sesuai dengan prakiraan semula.
Sesuai dengan pola musiman pada akhir tahun, perkembangan uang primer menunjukkan
349Tinjauan umum
peningkatan namun masih dapat dikendalikan sesuai dengan kebutuhan perekonomian.
Suku bunga SBI 1 bulan dan 3 bulan bergerak relatif stabil dan masih sesuai dengan
pencapaian proyeksi inflasi jangka menengah, yang diikuti oleh relatif stabilnya suku bunga
perbankan. Nilai tukar rupiah juga bergerak stabil dengan volatilitas yang rendah, meskipun
terdapat tekanan depresiasi.
Secara umum, nilai tukar rupiah selama triwulan IV-2004 bergerak stabil dengan tingkat
volatilitas yang cukup rendah. Namun demikian, menjelang akhir tahun rupiah sempat
mengalami tekanan terkait dengan faktor eksternal atas antisipasi pasar menjelang FOMC
dan faktor koreksi atas pelemahan USD yang terlalu cepat di bulan sebelumnya, ditengah
upaya untuk merealisasikan keuntungan menjelang akhir tahun serta meningkatnya
permintaan valas oleh sejumlah korporasi untuk pembayaran impor dan utang luar negeri.
Cukup terjaganya stabilitas nilai tukar ditengah tekanan depresiasi khususnya pada akhir
tahun, tidak terlepas dari peranan capital inflows yang didukung meningkatnya kepercayaan
pasar (market confidence), membaiknya persepsi risiko, serta dampak kecenderungan
melemahnya USD secara global yang dipicu oleh isu twin-deficit AS. Rata-rata nilai tukar
rupiah selama triwulan IV-2004 berada pada level Rp9.120/USD tetapi masih dalam rentang
perkiraan sebesar Rp8.700 – Rp9.300 per dollar AS.
Sejalan dengan kebijakan moneter yang tight bias dan langkah penyerapan likuiditas
yang secara optimal dilakukan Bank Indonesia, suku bunga SBI dalam triwulan IV-2004
dipertahankan stabil hingga pada akhir triwulan IV-2004. Suku bunga SBI 1 bulan hanya
meningkat sebesar 4 bps menjadi 7,41% dibandingkan dengan triwulan III-2004. Sementara
itu, suku bunga SBI 3 malah menunjukkan sedikit penurunan dibandingkan dengan triwulan
sebelumnya menjadi sebesar 7,29% atau menurun sebesar 2 bps. Perkembangan suku
bunga instrumen tersebut telah berpengaruh terhadap perkembangan suku bunga perbankan
dan kredit. Selain itu, masih tingginya kondisi likuiditas di pasar uang telah menyebabkan
suku bunga pasar uang menurun. Suku bunga deposito 1 bulan dalam triwulan ke IV-2004
mengalami sedikit peningkatan sebesar 5 bps dibandingkan dengan triwulan sebelumnya
atau menjadi 6,36%. Kenaikan suku bunga ini juga terjadi pada suku bunga deposito 3 dan
6 bulan yang meningkat sebesar masing-masing 5 dan 17 bps dibandingkan triwulan
sebelumnya menjadi masing-masing 6,66% dan 7,06%.
3. EVALUASI PERKEMBANGAN DAN KEBIJAKAN PERBANKAN
Selama triwulan IV-2004, kebijakan perbankan tetap difokuskan untuk melanjutkan
berbagai langkah dalam mempertahankan stabilitas sistem perbankan guna menciptakan
350 Buletin Ekonomi Moneter dan Perbankan, September 2004
stabilitas sistem keuangan dan mendorong fungsi intermediasi perbankan. Kebijakan tersebut
ditempuh melalui beberapa langkah antara lain melalui pemantauan risiko-risiko yang
dihadapi industri perbankan, pemantauan persiapan pelaksanaan manajemen risiko,
pemantauan intensif terhadap pelaksanaan rencana bisnis bank yang telah disetujui Bank
Indonesia, pemantauan pemberian kredit baru dan kredit hasil restrukturisasi terutama di
bank-bank besar, pemantauan action plan dari bank-bank terkait dengan kondisi permodalan
(Capital Adequacy Ratio/CAR) dan kualitas kredit bermasalah (Net Performing Loan/NPL),
serta penyempurnaan pengaturan dan pengawasan bank.
Dalam hal pengaturan perbankan, dalam triwulan IV-2004 Bank Indonesia telah
mengeluarkan ketentuan yang menyangkut pengaturan bank umum yang melaksanakan
kegiatan usaha berdasarkan prinsip syariah dan pengaturan rencana bisnis umum, serta
pengaturan mengenai penerapan manajemen risiko pada bank yang melakukan kerjasama
pemasaran dengan perusahaan asuransi (bancassurance). Untuk meningkatkan efektivitas
pengawasan bank khususnya dalam penanganan tindak pidana bank, dalam triwulan laporan
Bank Indonesia telah melakukan penandatanganan MoU dengan Kapolri dan Kejagung.
Sejalan dengan berbagai upaya konsolidasi internal dan program restrukturisasi
perbankan yang telah dilaksanakan sejak beberapa tahun lalu, secara umum kinerja
perbankan sampai dengan akhir triwulan IV-2004 menunjukkan perkembangan yang positif.
Hal ini ditunjukkan dari peningkatan aset, dana pihak ketiga dan kredit yang diberikan.
Peningkatan kredit tersebut menunjukkan bahwa fungsi intermediasi perbankan secara
bertahap menunjukkan perbaikan. Sejalan dengan perbaikan struktur aset, kualitas kredit
bermasalah semakin membaik serta kualitas aset, pendapatan dan efisiensi perbankan
juga terus menunjukkan peningkatan.
Sejalan dengan kondisi ekonomi makro yang stabil, Bank Indonesia terus berupaya
untuk mendorong perbankan untuk meningkatkan fungsi intermediasi dengan tetap
mengedepankan prinsip kehati-hatian. Beberapa indikator perbankan menunjukkan kestabilan
dan perbaikan sebagaimana tercermin dari memadainya permodalan, menurunnya risiko kredit,
meningkatnya profitabilitas perbankan serta perbaikan secara gradual intermediasi perbankan.
Upaya ini terutama dilakukan terhadap peningkatan jumlah kredit Usaha Mikri, Kecil, dan
Menengah (UMKM) serta sektor-sektor usaha tertentu yang belum terjangkau oleh pelayanan
bank. Langkah ini dipandang telah menunjukkan hasil yang menggembirakan sejalan dengan
semakin meningkatnya kredit UMKM dan kredit baru perbankan.
Berdasarkan data November 2004, penghimpunan dan penyaluran dana perbankan
menunjukkan peningkatan. Pertumbuhan DPK juga meningkat sebesar Rp43,9 triliun atau
351Tinjauan umum
4,9% sehingga tercatat sebesar Rp932,5 triliun. Sementara kredit perbankan yang diberikan
meningkat sebesar Rp96,2 triliun atau sekitar 20,2% sehingga posisinya menjadi Rp573,4
triliun (November 2004). Posisi UMKM yang disalurkan perbankan telah mencapai Rp270,5
triliun (posisi Oktber 2004) atau 51% dari total kredit perbankan (tanpa chanelling). Sementara
itu, pertumbuhan DPK juga meningkat sebesar Rp43,9 triliun atau 4,9% sehingga tercatat
sebesar Rp932,5 triliun. Dengan pertumbuhan kredit yang lebih besar dari pertumbuhan
DPK telah mendorong perbaikan LDR perbankan dari 43,2% pada tahun sebelumnya menjadi
49,5%. Kualitas kredit menunjukkan perbaikan sebagaimana tercermin dari membaiknya
NPLs gross dari 8,2% pada tahun sebelumnya menjadi 6,6% (November 2004). Sementara
NPLs net juga membaik dari 3,04% pada tahun sebelumnya menjadi 2,01% (November
2004). Rendahnya NPL juga memperbaiki kinerja profitabilitas perbankan. Pendapatan bunga
bersih (NII) meningkat 28% sementara efisiensi meningkat yang ditandai oleh menurunnya
rasio BOPO dari 88,8% pada akhir tahun 2003 menjadi 80,8%. Dari sisi permodalan, CAR
perbankan berada pada level yang memadai dan relatif stabil yakni 19,7%.
Sejalan dengan perkembangan bank umum, perkembangan perbankan syariah dan
BPR juga menunjukkan perkembangan yang meningkat. Kegiatan usaha perbankan syariah
menunjukkan pertumbuhan yang cukup baik, tercermin dari jumlah aset yang tumbuh 6,3%
dari triwulan sebelumnya hingga mencapai 13,5 triliun. Pertumbuhan volume usaha ini juga
didukung oleh pertumbuhan jumlah bank yang melaksanakan kegiatan usaha berdasarkan
prinsip syariah. Peningkatan yang sama juga ditunjukkan dari total dana pihak ketiga yang
dihimpun yang meningkat 4,12% menjadi Rp10,1 triliun, dan penyaluran dana yang
meningkat 5,9% menjadi sebesar Rp10,7 triliun. Dengan laju pertumbuhan pembiayaan
yang melebihi pertumbuhan dana yang dihimpun tersebut, maka FDR perbankan syariah
meningkat menjadi 105,8%.
4. EVALUASI PERKEMBANGAN DAN KEBIJAKAN SISTEM PEMBAYARAN
Secara umum, selama triwulan IV-2004 kebijakan yang ditempuh dalam sistem
pembayaran tunai adalah upaya untuk memenuhi kebutuhan uang kartal di masyarakat
dalam jumlah nominal yang cukup, jenis pecahan yang sesuai, tepat waktu dan dalam
kondisi yang layak edar.
Dalam triwulan laporan, Bank Indonesia telah mengeluarkan dan mengedarkan uang
kertas emisi baru pecahan Rp100.000,00 dan Rp20.000,00 yang dilakukan pada tanggal
29 Desember 2004. Pengeluaran dan pengedaran uang kertas emisi baru tersebut dilakukan
antara lain berdasarkan pertimbangan bahwa usia edar yang telah cukup lama serta bertujuan
352 Buletin Ekonomi Moneter dan Perbankan, September 2004
untuk menstandarisasi ukuran uang kertas, meningkatkan kualitas unsur pengaman yang
mudah dan cepat dikenali masyarakat antara lain dengan menerapkan optical variable ink
(OVI) dan memperlebar ukuran benang pengaman, serta memasukkan unsur blind code.
Dalam rangka memenuhi kebutuhan masyarakat menjelang hari raya keagamaan, Bank
Indonesia melakukan peningkatan pelayanan penukaran uang di seluruh Kantor Bank
Indonesia (KBI) serta meningkatkan peran penukaran uang pecahan kecil kepada
masyarakat oleh Perusahaan Penukaran Uang Pecahan Kecil (PPUPK) dengan
penambahan plafon, membuka loket sementara di tempat-tempat strategis, meningkatkan
pelayanan penukaran di tempat-tempat keramaian, serta menginformasikan kegiatan dan
lokasi tempat penukaran oleh PPUPK melalui media cetak dan elektronik.
Sejalan dengan terdapatnya faktor musiman khususnya hari raya keagamaan dalam
triwulan IV-2004, beberapa indikator pengedaran uang seperti jumlah uang yang diedarkan
(UYD), aliran uang masuk (inflow) dan aliran uang keluar (outflow) menunjukkan peningkatan
dibandingkan triwulan sebelumnya. Jumlah uang kartal yang diedarkan (UYD) pada posisi
akhir triwulan IV-2004 tercatat sebesar Rp126,90 triliun atau meningkat sebesar 9,33%
dibandingkan dengan posisi akhir triwulan sebelumnya. Dilihat dari jumlah bilyet/keping
uang kartal yang diedarkan Bank Indonesia, 89,5% merupakan uang pecahan Rp5.000 ke
bawah, dan sisanya sebesar 10,5% merupakan uang kertas pecahan besar (Rp10.000 ke
atas). Dari seluruh pecahan besar tersebut, uang yang paling banyak beredar di masyarakat
adalah pecahan Rp50.000 dan Rp10.000 masing-masing sebesar 48,6% dan 20,6%. Aliran
uang keluar (outflow) dari Bank Indonesia pada triwulan IV-2004 meningkat sebesar 30,1%
dibandingkan triwulan sebelumnya, sedangkan aliran uang masuk (inflow) hanya meningkat
sebesar 16,3% dari sebesar Rp64,51 triliun menjadi Rp74,99 triliun. Peningkatan outflow
yang cukup signifikan pada triwulan IV-2004 tersebut terutama didorong oleh meningkatnya
permintaan uang tunai untuk memenuhi kebutuhan masyarakat selama periode hari raya
keagamaan dan tahun baru.
Di sistem pembayaran non tunai, dalam triwulan IV-2004 kebijakan diarahkan pada
upaya penurunan risiko dan peningkatan efisiensi sistem pembayaran. Guna merealisasikan
tujuan tersebut, Bank Indonesia melakukan serangkaian kegiatan antara lain penyusunan
mekanisme Failure to Settle (FtS), pengembangan Sistem Kliring Nasional (SKN) dan
Penerbitan Peraturan Bank Indonesia tentang Penyelenggaraan Kegiatan Alat Pembayaran
Dengan Menggunakan Kartu.
Dalam triwulan IV-2004, total aktivitas BI-RTGS mencapai nilai Rp5.736 triliun dengan
jumlah transaksi sebanyak 1.365 ribu. Dibandingkan triwulan III-2004, total aktivitas BI-
353Tinjauan umum
RTGS tersebut meningkat sebesar 19,7% dari sebelumnya sebesar Rp4.790 triliun,
sementara volume transaksi meningkat sebesar 3% dari sebelumnya sebesar 1.324 ribu
transaksi. Kondisi tersebut menyebabkan rata-rata harian (RRH) nominal transaksi meningkat
menjadi sebesar Rp94 triliun, sementara RRH volume transaksi meningkat menjadi sebesar
22.383 transaksi. Berdasarkan asal perintah untuk transaksi antar bank yang melalui RTGS,
maka bank umum swasta nasional merupakan pihak yang paling banyak melakukan transaksi
baik secara nominal maupun volume. Hal tersebut disebabkan oleh banyaknya transfer
dana untuk untung nasabah, besarnyanya aktivitas pasar uang antar bank, serta transaksi
fasilitas Bank Indonesia. Secara keseluruhan, transaksi antar bank untuk untung nasabah
memiliki volume yang paling signifikan di dalam sistem RTGS. Hal ini menunjukkan bahwa
nasabah sebagai pengguna akhir merupakan pihak yang paling diuntungkan dengan
keberadaan sistem RTGS.
Sementara itu, dari sisi kliring, dalam triwulan IV-2004 menunjukkan bahwa total
nominal kliring penyerahan secara nasional mencapai Rp322,9 triliun dengan warkat
sejumlah 18,7 juta lembar. Dibandingkan triwulan sebelumnya, nilai transaksi menurun
sebesar 10,5% dari sebelumnya Rp371,8 triliun serta volume transaksi menurun 15,5%
dari sebelumnya sebesar 22 juta transaksi.
5. PROSPEK EKONOMI DAN MONETER
5.1. Prospek Ekonomi Makro
Kondisi pemulihan ekonomi dengan disertai ekspansi pertumbuhanyang lebih
seimbang pada tahun 2004 diperkirakan akan tetap berlanjut di tahun 2005. Kondisi ini juga
sangat didukung oleh komitmen Pemerintah untuk mengoptimalkan upaya perbaikan iklim
investasi termasuk diantaranya upaya mengakselerasi pembangunan infrastruktur.
Sementara itu kondisi ekonomi global, meskipun tidak secerah tahun sebelumnya, dinilai
juga masih kondusif untuk menopang kegiatan ekonomi dalam negeri yang berorientasi
ekspor. Meskipun demikian, prospek ekonomi ke depan juga masih dihadapkan dengan
beberapa permasalahan struktural ekonomi yang apabila tidak diatasi akan menyebabkan
perekonomian Indonesia masih rentan terhadap beberapa shock yang yang terjadi baik
dari dalam maupun luar negeri. Beberapa faktor risiko tersebut antara lain terkait dengan
perkembangan harga minyak yang masih dapat bergejolak tinggi serta struktur arus modal
masuk jangka pendek yang rentan terhadap terjadinya pembalikan arus modal (capital
reversal).
354 Buletin Ekonomi Moneter dan Perbankan, September 2004
Dengan beberapa perkembangan tersebut, pertumbuhan ekonomi Indonesia triwulan
I-2005 diperkirakan akan berkisar antara 5,0%-6,0% (yoy). Semua komponen pengeluaran
diperkirakan akan mencatat pertumbuhan yang positif, dengan komponen pendorong
pertumbuhan terbesar berturut-turut adalah ekspor, konsumsi, dan diikuti investasi. Peningkatan
konsumsi swasta masih akan terus terjadi pada awal triwulan 2005 ini, yang didorong oleh
peningkatan pendapatan masyarakat sejalan dengan naiknya pertumbuhan ekonomi. Hasil
proyeksi ini didukung oleh hasil survey konsumen yang menunjukkan semakin membaiknya
ekspektasi konsumen. Dari sisi pembiayaan, kredit konsumsi yang terus meningkat juga turut
memberikan sumbangan bagi kenaikan konsumsi. Dengan pertimbangan tersebut, maka
konsumsi swsata diperkirakan akan tumbuh pada kisaran 5,0%-6,0% (yoy). Kegiatan investasi
diperkirakan akan mencatat pertumbuhan yang cukup tinggi dalam kisaran 11,8%-12,3%
(yoy). Peningkatan kegiatan investasi terutama didorong oleh peningkatan kepercayaan
investor atas perbaikan iklim investasi. Hal tersebut diindikasikan dari komitmen Pemerintah
dalam mendorong investasi serta penguatan kepercayaan pebisnis yang terungkap dari hasil
Survey Kegiatan Dunia Usaha (SKDU). Kegiatan ekspor diperkirakan juga akan tumbuh relatif
tinggi antara lain didukung oleh perkiraan meningkatnya kapasitas produksi di sejumlah sub
sektor industri. Seiring dengan peningkatan permintaan domestik dan ekspor, maka kegiatan
impor diperkirakan juag mengalami peningkatan.
Sementara di sisi penawaran, peningkatan nilai tambah diperkirakan akan berasal
dari sektor industri pengolahan, pengangkutan, listrik dan bangunan. Industri pengolahan
diperkirakan akan tumbuh lebih tinggi dibandingkan triwulan sebelumnya atau pada kisaran
5,2%-6,2% di triwulan I-2005. Sub sektor industri alat angkutan, sub sektor kimia serta sub
sektor semen diperkirakan akan tumbuh cukup tinggi. Seiring dengan itu, penggunaan
pengolahan pun diperkirakan akan mengalami peningkatan dan secara rata-rata akan berada
pada tingkat di atas 70%. Sektor pertanian diperkirakan mengalami sedikit perlambatan
pertumbuhan terkait dengan mundurnya pelaksanaan musim tanam Oktober-Maret pada
sebagian areal tanam, khususnya areal tadah hujan. Namun demikian, penundaan tersebut
hanya akan menyebabkan penurunan produksinya pada awal triwulan. Dengan kondisi
tersebut sektor pertanian akan tumbuh berkisar 2,8-3,8% di triwulan I-2005. Sektor bangunan
diperkirakan akan tumbuh dalam kisaran 7,2-8,2% seiring dengan dimulainya pembangunan
beberapa proyek besar.
5.2. Prospek Inflasi
Secara umum prospek Inflasi triwulan I-2005 akan dipengaruhi oleh rencana kenaikan
355Tinjauan umum
harga BBM oleh Pemerintah. Namun demikian, besarnya dampak dari kenaikan administered
prices tersebut masih tergantung pada magnitude dan timing dari implementasi kebijakan
Pemerintah, serta dampak tunda dari pengaruh tahap kedua (second round effect)
administered prices.
Di sisi penawaran, pasokan bahan makanan baik dari sisi produksi domestik maupun
impor diperkirakan masih akan tetap terjaga meskipun terdapat beberapa bencana alam di
beberapa daerah. Di samping itu, tekanan inflasi dari sektor ekstenal diperkirakan akan
relatif minimal dengan perkembangan nilai tukar ke depan yang diperkirakan semakin
membaik. Kedua faktor positif tersebut diharapkan akan mampu meredam tekanan inflasi
yang berasal dari kenaikan harga akibat kenaikan harga BBM.
5.3. Prospek Nilai Tukar
Dalam triwulan I-2005, kestabilan nilai tukar diperkirakan akan berlanjut dan bahkan
cenderung menguat. Optimisme pergerakan rupiah tersebut didukung oleh cukup
kondusifnya kondisi eksternal dan internal yang mempengaruhi terjaganya kondisi penawaran
dan permintaan valas, yang pada gilirannya turut menjaga kestabilan nilai tukar rupiah. Di
sisi permintaan valas, seiring dengan meningkatnya kegiatan investasi dan konsumsi,
kegiatan impor diperkirakan juga akan meningkat. Di sisi lain, pasokan valas yang berasal
dari ekspor diperkirakan meningkat sejalan dengan kinerja ekspor non-migas yang semakin
membaik. Pasokan valas lain diperkirakan bersumber dari aliran modal asing (capital inflows)
terutama yang berjangka pendek yang diperkirakan terus berlanjut. Berbagai faktor positif
dalam negeri akan mempengaruhi insentif investor asing dalam menanamkan dananya.
Peningkatan rating serta proyeksi utang oleh beberapa lembaga selama tahun 2004
merupakan bukti membaiknya risiko domestik yang pada gilirannya dapat meningkatkan
kepercayaan investor kepada Indonesia. Faktor lain yang menjadi daya tarik Indonesia
sebagai alternatif investasi terutama jangka pendek, yakni masih cukup menariknya imbal
hasil rupiah.
Meski prospek ke depan cukup positif, namun beberapa perkembangan dari sisi
eksternal perlu diwaspadai. Pergerakan USD yang cenderung terdepresiasi dalam jangka
panjangnya akibat permasalahan twin deficit, dapat berfluktuasi (terkoreksi) dalam jangka
pendeknya terutama terkait dengan berlanjutnya siklus pengetatan AS. Dalam triwulan I-
2005, Fedres merencanakan adanya FOMC sebanyak dua kali yaitu pada awal Februari
dan pertegahan Maret. Bila data perekonomian AS membaik maka pasar akan kembali
melakukan antisipasi terhadap kenaikan suku bunga Fedres. Fenomena ini berpeluang
356 Buletin Ekonomi Moneter dan Perbankan, September 2004
membuat rupiah akan mengalami tekanan melalui transmisi ekspektasi kenaikan suku bunga
luar negeri.
6. ARAH KEBIJAKAN BANK INDONESIA KE DEPAN
Memperhatikan prospek ekonomi-moneter ke depan khususnya pencapaian sasaran
inflasi jangka menengah serta faktor risiko yang berpotensi memberikan tekanan pada
kestabilan ekonomi, dalam triwulan mendatang arah kebijakan Bank Indonesia di bidang
moneter, perbankan, dan sistem pembayaran sebagai berikut :
Di bidang moneter, kebijakan moneter dalam triwulan mendatang tetap diarahkan
pada upaya mencapai sasaran inflasi yang telah ditetapkan, namun dengan tetap menjaga
momentum pertumbuhan yang sedang terjadi. Secara operasional, kebijakan moneter akan
ditempuh dengan dengan mengarahkan uang primer berada pada proyeksi indikatifnya
yakni rata-rata tumbuh sebesar 11,5 - 12,5% pada tahun 2005. Untuk meningkatkan
efektivitas kebijakan moneter Bank Indonesia akan menggunakan suku bunga sebagai
instrumen kebijakan moneter pada pertengahan tahun 2005. Penggunaan target operasional
suku bunga sebagai pengganti base money dalam pengendalian moneter ini juga
dimaksudkan agar kebijakan moneter lebih fleksibel dalam merespon dinamika
perekonomian yang terjadi serta sinyal kebijakan ini yang lebih mudah dibaca oleh pasar.
Di bidang perbankan, kebijakan dalam triwulan mendatang diarahkan untuk
melanjutkan upaya-upaya untuk mempertahankan stabilitas sistem keuangan dan perbankan
serta mendorong peningkatan fungsi intermediasi perbankan dsiesuaikan dengan arah
kebijakan perbankan kedepan yakni : (i) Mengakselerasi proses konsolidasi industri
perbankan melalui penyelesaian proses konsolidasi individual bank dalam tahun 2005, (ii)
Mengimplementasi langkah-langkah penguatan infrastruktur sistem keuangan antara lain
melalui pendirian LPS, penyempurnaan ketentuan yang terkait dengan good corporate
governance perbankan, melanjutkan program sertifikasi manajemen risiko, persiapan
pembentukan Credit Bureau; (iii) Penguatan aspek-aspek prudential dan peningkatan fungsi
intermediasi melalui penyempurnaan ketentuan BMPK, Sistem Informasi Debitur (SID), dan
Sekuritisasi Aset, Kualitas Aktiva Aset, Pinjaman luar negeri, serta penyelesaian pengaduan
nasabah dan perlindungan nasabah dan transparansi informasi produk perbankan.
Penguatan aspek-aspek pridensial dan peningkatan fungsi intermediasi tersebut melalui
penyempurnaan beberapa ketentuan tersebut akan dikeluarkan pada bulan Januari 2005
dalam bentuk Paket Kebijakan Perbankan. Dalam paket kebijakan tersebut, juga akan diatur
pula perlakukan khusus terhadap kredit bank umum di Provinsi NAD dan Kabupaten Nias.
357Tinjauan umum
Di bidang sistem pembayaran tunai, kebijakan tetap diarahkan pada upaya untuk
memenuhi kebutuhan uang kartal di masyarakat dalam jumlah nominal yang cukup, jenis
pecahan yang sesuai, tepat waktu dan dalam kondisi yang layak edar. Terkait dengan hal
tersebut, pada triwulan mendatang Bank Indonesia tetap mengupayakan pemenuhan
kebutuhan uang tunai di seluruh wilayah di Indonesia sesuai dengan rencana distribusi
serta memantau kecukupan persediaan kas. Sementara itu, dalam rangka memenuhi
kebutuhan uang kartal di wilayah bencana di Propinsi Nangroe Aceh Darusalam ditempuh
beberapa langkah antara lain dengan mengoperasikan kegiatan pelayanan kas sementara
bertempat di rumah dinas Bank Indonesia, memfungsikan KBI Lhokseumawe untuk men-
supply uang tunai ke KBI Banda Aceh di bawah koordinasi KKBI Medan, serta mengirimkan
tenaga kasir Kantor Pusat untuk membantu operasional perkasan di KBI Banda Aceh maupun
KBI Lhokseumawe. Selain itu, Bank Indonesia akan melanjutkan langkah-langkah
penanggulangan uang palsu antara lain melalui perluasan jejaring dan kerjasama dengan
pihak-pihak terkait pada langkah penanggulangan uang palsu. Sejalan dengan itu, upaya-
upaya publikasi dalam rangka pengenalan masyarakat atas ciri-ciri keaslian uang Rupiah
akan dilanjutkan melalui media elektronik dan media cetak.
Di bidang sistem pembayaran non tunai, kebijakan tetap diarahkan untuk melanjutkan
upaya-upaya pengurangan risiko pembayaran, peningkatan kualitas dan kapasitas layanan
sistem pembayaran serta pengaturan pengawasan sistem pembayaran guna mewujudkan
sistem pembayaran yang cepat, aman, dan efisien. Dalam rangka meminimalkan risiko,
meningkatkan efisiensi dan kesetaraan (fairness) dalam sistem pembayaran serta adanya
perlindungan konsumen bagi pemakai jasa sistem pembayaran, maka dalam tahun 2005
Bank Indonesia akan mengimplementasikan beberapa program yang telah disusun pada
tahun 2004 dan penyusunan ketentuan antara lain pelaksanaan FtS, Sistem Kliring Nasional,
pelaksanaan pengawasan sistem pembayaran dengan menggunakan kartu dan sosialisasi
untuk memperlancar implementasi Daftar Hitam Nasional (DHN).
359Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
A b s t r a c t
Fiscal and Monetary Policy Interaction :Evidences and Implication for Inflation Targeting in Indonesia
Firman Mochtar 1
September 2004
Paper ini menganalisa interaksi kebijakan fiskal dan moneter di Indonesia pada masa sebelum
dan sesudah krisis, dengan melakukan estimasi atas quasy fiscal activity (QFA) Bank Indonesia dan
mengurai interaksi antara kebijakan fiskal dan moneter. Penulis menemukan bahwa selama masa
krisis, aktifitas ini (QFA) ada dan dilakukan oleh bank sentral Indonesia. Hal ini berbeda dengan masa
sebelum krisis dimana QFA memiliki besaran yang netral. Dalam kaitan interaksi kebijakan fiskal-
moneter, fakta ini menunjukkan dominasi kebijakan fiskal pada masa setelah krisis.
Analisa interaksi antara kebijakan fiskal dan moneter ini membawa implikasi kebijakan di Indo-
nesia yakni perlunya disiplin dalam kebijakan fiskal dan perlunya komitmen untuk mempertahankan
sustainability kebijakan tersebut. Kegagalan mencapai kebijakan fiskal yang optimal akan mengurangi
efektifitas kebijakan moneter dalam rangka mengontrol inflasi meski dalam kerangka inflation target-
ing yang secara parsial sudah diimplementasikan oleh Bank Indonesia.
Keyword: Quasi Fiscal Activities, Fiscal Policy, Monetary Policy, Inflation Targeting
JEL: E11, E31, E52, E62
1 Bank Indonesia. This paper was written while the author visited Bank for International Settlement. I am grateful toPalleAndersen, Madhusudan Mohanty, David Lebow, Feng Zhu, Piti Disyatat, Diana Permatasari and Reza Anglingkusumoforhelpful suggestions and detailed comments. Author would like also to thank all the colleagues in MacroeconomicMonitoringsection and Emerging Market Issues Section for the hospitality and the discussion. Any opinions expressed arethose of theauthor and not necessarily those of the Bank Indonesia or the Bank for International Settlement.
360 Buletin Ekonomi Moneter dan Perbankan, September 2004
1. INTRODUCTION
Intensive challenges in conducting macroeconomic policies emerged in Indonesia
since the Asian crises hit in 1997. Monetary policy was engaged with exhaustive challenges.
Exchange rate depreciated sharply while monetary base grew rapidly triggered by central
bank’s liquidity support. Under these circumstances, inflation increased sharply in 1998 to
reach 82%. On fiscal policy side, the sharp depreciation of the exchange rate inevitable
raised the foreign debt burden in term of domestic currency. Moreover, a huge amount of
expenditure was still required regarding the policy to restore the banking system and also to
finance other government operational expenditures.
Macroeconomic policies pursued afterwards expressed the effort to solve the problem.
Tight monetary policy was conducted to absorb a huge amount of excess liquidity. From fiscal
side, central government had issued domestic debt both for replacing the central bank’s liquidity
support and for recapitalizing banking system during period September 1998 and October 2000
(Bank Indonesia, 1999 and Hawkin, 1999). Furthermore, starting 2002 government has also
issued different types of bond to finance the state budget deficit2 . The total government debt,
both domestic and external, rose from 25% of GDP at end-1996 to 96% at the end of 2000.
This paper is intended to test empirically fiscal and monetary policy interaction during
that period of macroeconomic adjustment. The interaction will be viewed from the plausibility
quasi fiscal activities by central bank (QFA)3 and be extended to test fiscal versus monetary
dominance. The QFA estimation is motivated by the fact that during the period adjustment,
the fiscal side come under a heavy burden while in monetary side accorded a sharp increase.
On assumption that consolidated government budget identity holds this fact generates some
suspicion of fiscal monetization in Indonesia during that period. Conceptually, this
circumstance could lead to QFA since QFA emerges if total public sector spending is above
additional central government public debt. As residual of those two variables, QFA is required
to finance the central government financial gap.
Moving forward from QFA issue, fiscal versus monetary dominance test is also gauged
to confirm the QFA result. Still on assumption that consolidated government budget identity
holds, the presence of QFA could also imply the presence of the fiscal dominance in view of
fiscal and monetary policy interaction. Under this circumstance, fiscal policy which is reflected
2 Boediono (2004) explained that the increase of the domestic debt was associated with the effort to support banking systemand classified them into three main policy namely (i) policy to overcome the shortage of liquidity in banking systemthrough Bank Indonesia’s liquidity support, (ii) policy to guarantee public’s deposit in banking system and (iii) policy torecapitalize banking system.
3 The acronym QFA will be used frequently to express the quasi fiscal activities by central bank
361Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
in present value of primary balance will move exogenously to the initial total public debt and
sequentially required monetary policy to satisfy consolidated budget identity.
Extending method proposed by Buiter (1993), Budina-Wijnbergen (2000) and
Markiewicz (2001) for the QFA estimation, the paper finds that fiscal and monetary interaction
in Indonesia the during the crises has created QFA phenomenon. Most of the source behind
the figure since 1998 inevitably was the effect of rescue operation held by the central bank
associated with the financial system which has consecutively deteriorated central bank
balance sheet. In addition to this source, huge increase in central bank securities also
contribute to QFA because it has enlarged the cost of central bank on monetary instrument
and again sequentially worsen central bank balance sheet position. Parallel to the QFA
result, the paper also finds that fiscal policy is likely to be more dominant in view of fiscal
and monetary policy interaction during the crises. Utilizing method employed by Canzoneri
et.al (2001) and Tanner and Ramos (2002), paper obtains that fiscal policy has moved
exogenously to debt performance post 1997 such that could lead to the emergence of fiscal
dominance classification.
Based on the findings, the paper finds some implication for monetary policy in Indonesia.
The nature of fiscal and monetary policy interaction implies that imposing monetary policy
effectiveness in Indonesia still call for a higher fiscal discipline and commitment of the
government to maintain the sustainability. Parallel to some arguments4 , this paper’s results
imply the failure to solve fiscal performance optimally could deteriorate monetary policy
effectiveness to control inflation even under inflation targeting framework which has been
partially implemented in Indonesia.
Paper will be organized into five parts. Part two estimates the QFA by central bank in
Indonesia. Employing part two result, part three presents the test of fiscal versus monetary
policy dominance. Part four addresses some implications of the results for the effectiveness
of monetary policy in Indonesia under inflation targeting framework. Part five concludes the
paper.
2. ESTIMATING QUASI FISCAL ACTIVITIES BY CENTRAL BANK
In this part, firstly we estimate quasi fiscal activities by central bank. Indeed the
estimation will only provide an approximation of QFA, not a precise number because the
method used to estimate only applies to the aggregation level. This approach provides a
good direction of QFA if the precise information of QFA is not available (Markiewicz, 2001).
4 See Loyo (1999), Blanchard (2004), Favero and Giavazzi (2004)
362 Buletin Ekonomi Moneter dan Perbankan, September 2004
QFA in this estimation is obtained from the simple manipulation of consolidated government
budget constraint which is formed from central government budget constraint and central
bank financial account. As explained in many macroeconomic and monetary theory text
books5 , consolidated government budget constraint defines that in addition to revenue from
tax, to meet the spending, government sells bonds to public and/or to the central bank. On
assumption that consolidated government budget identity holds, QFA will be acquired if
total public sector borrowing requirement6 is higher than additional central government public
debt which eventually finance from central bank to fill central government financial gap.
2.1. Analytical Review
To describe the QFA in Indonesia, I modified and extended the Buiter (1993), Budina-
Wijnbergen (2000) and Markiewicz (2001) analytical framework such that it could represent
Indonesia’s consolidated public budget identity ‘prototype’. As explained earlier, to derive
QFA, firstly we should form consolidated government budget constraint which is amalgamated
from central government budget constraint and central bank’s financial account.
Government Budget Constraint
As explained in many standard analyses, central government budget constraint can
be depicted as:
(2.1)
where G – the non interest government spending, T – government domestic revenue
including non-tax revenue, i – nominal interest rate, Bt - total government‘ domestic debt,
DCg - credit to government from central bank, DEPg - government deposits at the central
bank, B*- government’ foreign debt, E – nominal exchange rate, CBT – transfer from central
bank which obtained from some proportion of central bank profit. The asterisk * denotes
variable in foreign currency, ∆ indicates the absolute change in the expression that follows
and ^ denotes a percentage change in variable.
By defining D = G –T as primary deficit, equation (2.1) describes that funding
requirement for the general government primary deficit, interest paid on domestic government
debt, interest paid on domestic credit extended by the central bank to the government minus
government deposit at the central bank plus interest on foreign debt expressed in terms of
CBTÄDEPÄDCE)Ä(BÄB
EB1])i)(1E[(1iDEPiDCiBTGgg*t
1*
1*g
1g
1t1-
+−++=
−+++−++− −−−−
5 See Walsh (2003, chapter 4) for the an example6 which is also called overall budget balance obtained from tax revenue minus total government spending
363Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
domestic currency should be equal to the financing sources i.e. government’s domestic and
foreign debt issue, net credit to government extended by the central bank and transfer from
central bank.
Following Budina-Wijnbergen (2000) and Markiewicz (2001) to capture the impact of
the exchange rate on domestic value of foreign debt, changes in the value of government
foreign liabilities are broken down into the change in stock of foreign debt, exchange rate
changes and cross-term product:
(2.1a)
Combining (2.1a) to (2.1) to obtain the central government budget constraint that has
eliminated the effect of exchange rate devaluation on the government foreign debt:
(2.2)
The Central Bank’s Financial Account
The central bank’s financial account is formed trough central balance sheet and central
bank’s profit and loss account. Referring to Bank Indonesia’s balance sheet, we have the
following identity:
(2.3)
where M – monetary base, Bg - government bond held by the central bank, Bm - central
bank securities used as monetary instrument, Cp - credit to non-governmental sector
(commercial bank and private sector), NFA – net foreign asset, NW – net worth obtained
from profit of central bank minus CBT.
Equation (2.3) show different characteristic from the standard central bank balance
sheet in many in industrial countries. Equation (2.3) provides the use of central bank securities,
Bm , in the identity and later will have some implications to the result of QFA. The contribution
of central bank securities in QFA is also parallel to Rodriguez (1994) and Beckerman (1995)
arguments for Argentina experience in 1989-1990 which showed a considerable QFA due
to the large use of central bank securities in Argentina’s monetary management at that time.
As Van’t dack (1999) and Hawkin (2004) survey experiences of emerging countries and
show that many central banks use them for open market operation.
Meanwhile from the profit and loss account, the central bank’s ‘net’ profit is defined
as:
EÄBEB ÄBEE)Ä(B **1
*1-
* ∆+∆+= −
CBTÄDEPÄDCEÄB)EÄB(ÄB
EBi)E(1iDEPiDCiBDgg*
1-*t
1*
1*g
1g
1t1-
+−+∆++=
++−++ −−−−
E)Ä(NFAÄCÄDEPÄDCÄBÄBÄMNW *pgggm ++−+=++
364 Buletin Ekonomi Moneter dan Perbankan, September 2004
(2.4)
Combining balance sheet (2.3) and profit and loss account of the central bank (2.4)
and eliminating the exchange rate effect will reproduce central bank’s financial account as:
(2.5)
Consolidated Government Budget Identity
By defining B=Bt - Bg as the government debt held by the private or commercial bank
and substituting into combined government budget constraint (2.2) and central bank financial
account (2.5), we get the total public sector budget constraint. However, because we are
trying to focus on the changes of net foreign debt then the small changes of exchange rate
can be ignored to obtain:
(2.6)
Equation (2.6) expresses consolidated government budget constraint. The deficit of
public sector can be financed by increasing domestic – including central bank securities- -
or foreign debt, money creation or increasing liabilities (in foreign currencies or in domestic
currency for non-governmental entities) of the central bank. Unlike standard consolidated
government budget constraint, the central bank securities appears as a part of government
spending in consolidated sense and can be part of the total public debt held by the private.
Approximation of Quasi Fiscal Activities
Indeed, the proxy of QFA could be captured from equation (2.6) if the total public
sector borrowing requirement as described from the left hand side of equation (2.8) is above
additional central government public debt. QFA can be obtained from the residual of those
two variables because it implies the money needed to finance the central government financial
gap. Nevertheless, this approach could bring some misleading result if government borrowing
requirement grow faster than government deficit. Following Markiewicz (2001), to overcome
the problem equation (2.6) will be slightly manipulated by separating the source of financing
from central bank and government as follows:
(2.7)
CBT}iBENFA1])Ei*)(1[(1iCiBiDEPiDC{NW m11
*1
p1
g1
g1
g1 −−−+++++−= −−−−−−−
ÄMÄC)ÄNFA B(EÄBÄB
CiE)NFA-B(i)E(1BiBiDp**
1-m
p11
*1
*1
*m11-
+−−∆++=
−++++ −−−−−
CBTÄMÄNFAE NFAÄEÄCÄDEPÄDCÄBÄB
ENFAi)E(1CiBiBiDEPiDCi**
1-pggmg
1*
1*p
1m1
g1
g1
g1
+−∆+∆++−+−=
+++−+− −−−−−−−
]ÄCÄM)NFA(EÄB-DEP-DC[-]DEP-DC)B(EÄB[
ÄMÄC)ÄNFA B(EÄBÄBp*
1-mgggg*
1-
p**1-
m
+−∆+∆∆∆∆+∆+
=+−−∆++
365Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
ÄNOIÄCÄM)NFA(EÄB-DEP-DC p*1-
mgg =+−∆+∆∆
ÄNOIÄCÄM)NFA(EÄB-DEP-DC p*1-
mgg =+−∆+∆∆ÄNOIÄCÄM)NFA(EÄB-DEP-DC p*
1-mgg =+−∆+∆∆
ÄNOIÄCÄM)NFA(EÄB-DEP-DC p*1-
mgg =+−∆+∆∆
The right hand side of (2.7) describe the borrowing requirements of the general
government and borrowing requirement of the central bank. The second part of the right
hand side of (2.7) expresses the net other items in central bank behaviour which will be the
main part of analysis or exclusively be defined as:
(2.8)
Equation (2.8) is the centre of analysis of the QFA which describes the amount of
money required by the central bank to balance the fiscal operation by central government
such that can satisfy the consolidated government budget constraint in equation (2.6).
Equation (2.8) implies the amount of money created by central bank as part of public entities
to finance the central government spending. By definition, indeed equation (2.8) indirectly
also reflects the flows of central bank’s net worth for a certain period because it also shows
the difference between bank’s asset and its liabilities7 . The negative value of NOI could
reflect that liabilities of the bank has exceeded asset and could indirectly provide the fragility
of the central bank’s financial position. With respect to our case, the negative value of NOI
could indicate a QFA by central bank at that period.
One of the source of the deficit in equation (2.8) is a higher of . This equation
implied that any shock that could rise and subsequently will lead a deficit in QFA.
Following Mackenzie and Stella (1996), the source of rise could be initiated from the
central bank rescue operation related to the financial system which can take a variety of
form – from a simple infusion of capital, to an assumption of nonperforming loans, to an
Further discussion could be addressed to the role of central bank securities (ABm) in
estimating the QFA. By definition equation (2.8) implied that sterilization by central bank
through increasing ABm implies will raise QFA. Nevertheless, by practice this hypothesis
could not be always occurred because when base money (AM) would also contract the
same amount when central bank sterilize the money supply by selling the central bank
securities. The higher ABm would raise the QFA only if AM does not change due to other
source of monetary policy expansion which is higher that central bank policy contraction
through that central bank securities. The Argentina’s experience in 1989-1990 referred by
7 Stella (1997) distinguished definition between net worth and capital in view of central bank balance sheet. He defined networth as the price a fully informed risk neutral investor would pay to purchase the bank under normal condition. Meanwhilecapital was defined as the amount directly invested by shareholder plus accumulated retained earning minus losses. Theterm of net worth is more appropriate to our paper because it captures the changes in the value assets and liabilities bothfor past and future changes.
....
..
..
366 Buletin Ekonomi Moneter dan Perbankan, September 2004
Rodriguez (1994) and Beckerman (1995) could be parallel to this hypothesis because tight
monetary policy employed central bank securities caused a monetization and could not be
Total Debt excluding Govt Debt in BIForeign Debt StockDomestic Debt including in BI
Source : Bank Indonesia, Ministry of Finance, author’s calculation
0
2
4
6
8
10
5,000
10,000
15,000
20,000
25,000
30,000
1984 1987 1990 1993 1996 1999 2002
Source : Bank Indonesia, author’s calculation
Liquidity Credits (billion Rp - left scale)Ratio to GDP (% - right scale)
369Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
Another item contributed to the QFA in this region relates to the managed floating
exchange rate regime adopting during this period. Following Mackenzie and Stella (1996)
classification, operation to exchange rate system can be classified into QFA by central bank
because it both provide a hidden subsidy to the market that should paid by the central bank
by maintaining the level of the exchange rate at certain range. Central banks in this period
pursued sterilization policy of capital inflow in foreign exchange market such that could
prevent the further domestic currency appreciation at that time (Graph 4). Hence, this
managed floating exchange rate system inevitably reduces the central bank reserve and
bring down the QFA level lower than the government primary balance.
Graph 2.4. Rupiah Exchange Rate 1995 – 1997:Intervention Band and Actual Rate
The third period was occurred since the Asia financial crises hit. The issue emerged
in this region is apparently loose monetary policy stance as reflected by the deficit number
in NOI while fiscal stance keep trying to maintain government primary surplus balance. In
the fiscal side performance, the primary balance indeed still reflects a government idea to
keep concerning to debt sustainability. The sharp depreciation of Indonesia’s exchange rate
lead an increase in foreign government debt in term of domestic currency (Graph 2).
Unavoidably, this problem cause higher principal and interest repayment debt that ultimately
cause deficit in overall balance.
This unfortunate debt burden performance has both limited the government stimuli to
the economy and restricted financing to restore the banking system. Fiscal problem had
forced the government to issue the domestic debt. From September 1998 to October 2000,
government issued two different domestic bonds i.e. bonds to replace the central bank’s
2,200
2,300
2,400
2,500
2,600
2,700
2,800
2,200
2,300
2,400
2,500
2,600
2,700
2,800
Dec Mar Jun Aug Nov Feb May Aug
Lowest Band Highest BandMid Band Market Rate
Source : Bank Indonesia
199719961995
370 Buletin Ekonomi Moneter dan Perbankan, September 2004
liquidity support8 and bonds to recapitalize the banking system (Bank Indonesia, 1999 and
Hawkin, 1999). In addition, starting 2002 government also issued domestic bond through
market auction to finance the government budget deficit. This additional debt consequently
brought to the higher burden of interest debt repayment than primary surplus obtained which
reached the peak on 2000 (Graph 2).
Interesting figures emerge since 1998 from the monetary side. Two type of analysis of
equation (2.10) employed current exchange rate and constant exchange rate generally
indicated that in this regime central bank run a high quasi fiscal deficit. The difference between
current exchange rate result and 1997 constant exchange result is only in the year of 1998
which obtained a surplus number for the NOI. However, this figure could bring a misleading
interpretation because those are more affected by the sharp depreciation effect of the
exchange rate such that could raise the net foreign assets (NFA) in term of domestic currency
value. Referring equation (2.1a) and (2.6) we should focus on the changes of the stock of
the net foreign asset instead of the effect of exchange rate changes. Therefore, the rest of
analysis, we will focus on 1997 constant exchange rate.
The general justification of this post 1997 performance was the effect of rescue
operation held by the central bank associated with the financial system. In 1998 central
bank engaged deficit of NOI amounted -4.7% of GDP while in 1999 deficit was apparently
getting higher. Those figures were contributed from liquidity support from central bank as
lender of the last resort (Bank Indonesia, 1998, 1999). Mackenzie and Stella (1996) survey
in some developing countries showed the possibility of the similar rescue operation could
generate QFA were mostly contributed from an infusion of capital to a troubled institution,
an assumption of non-performing loans, or an exchange rate guarantees by the central
bank. Those sources of QFA probably existed in Indonesia while the crises occurred.
In addition, some aspect in the central bank operation also contributes the deficit.
Following equation (2.8), the positive central bank securities could also contribute to the
deficit QFA. Following Mackenzie and Stella (1996) argument, increase of open market
operation to sterilize the liquidity injection of the financial rescue operation could be classified
to QFA because this central bank open market operation will enlarge the cost of central
bank. Similar arguments were also proposed by Rodriguez (1994) and Beckerman (1995)
for the case of Argentina in 1989-90. For Indonesia case, this relates to the sharp increase
of central bank securities (SBI) as shown since 1998 and subsequently has generate higher
cost for monetary expenses of the central bank (Graph 5).
8 These liquidity support were issued to prevent bank run and payment system failure
371Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
3. TEST OF FISCAL VERSUS MONETARY DOMINANCE
Part two results emphasize Mackenzie and Stella (1996) argument that central bank
can affect the overall public sector balance without affecting the surplus in government
primary balance. Period three of Indonesia fiscal adjustment and monetary movement
justify this argument by showing that the central bank has supported the consolidated
government financing. This fact is indicated from deficit figures of NOI while primary balance
still obtained surplus. These results lead a further question whether the sequential
government primary surplus sufficiently expresses fiscal commitment and discipline
regarding to debt performance and can be classified into monetary dominance in term of
fiscal and monetary interaction sense.
To answer these questions, the study will be extended to investigate the fiscal versus
monetary dominance in view of macroeconomic policy coordination. In this test, if government
does not adjust the primary balance sufficiently to reach sustainable debt level while the
central bank is forced to drive up the debt, then such regime will be classified into fiscal
dominant regime. By contrast, if the government could always ensure the primary balance
to balance intertemporal budget in balance while monetary policy is set independently, then
the economy is under monetary dominant (MD)8 . As we will in the next section, the answer
of this question will have some further implication to the monetary independence to maintain
the price stability.
Graph 2.5. Central Bank Securities: Stock, InterestRate and Monetary Operation Expenses
-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
4
6
8
10
12
14
16
18
2000 2001 2002 2003
Source : Bank Indonesia’s annual report
Monetary Operation Expenses (billion Rp - left scale)SBI Stock average (billion Rp - left secale)1 Mont SBI Interest Rate - average (% - right scale)
9 The distinction between MD and FD regimes is due to Sargent and Wallace (1981)
372 Buletin Ekonomi Moneter dan Perbankan, September 2004
3.1. Analytical Framework
This test basically is also initiated from the public sector budget one-period identity as
described in (2.6). Recall that Dt = G
t - T
t and ∆ indicates the absolute change from the
previous number for the respective variable. Use that definition and also define AM=St as
the nominal value of seigniorage then we rewrite (2.6) as the following form:
(2.6a)
Assume uncovered interest parity holds i.e it* = i
t ⁄ E
t and define net total public
liabilities excluding seigniorage as :
(2.6b)
then equation (2.6a) can be simplified:
(3.1)
where the small case letters have expressed the scaling of the respected variable to
nominal GDP. Following Walsh (2003), let assume the interest factor i is a constant and
positive, equation (3.1) can be solved forward to yield :
(3.2)
If discounted value of government liabilities approaches zero over an infinite horizon
in the last term of equation (3.2) ie.
(3.2a)
then equation (3.2) and (3.2a) summarize that the present discounted value of all and
future non-debt central government and seigniorage revenue should be equal to the present
discounted value of all current and future government expenditure plus current outstanding
net public liabilities plus interest.
Let as the net government primary balance that has involved seignoirage then the
intertemporal budget implies from (3.2):
(3.3) or
..
tp
1-tpt
*1-t
*t
*1-t
*tt
m1-t
mt1-tt
p1-t1-t1-t
*1-t
*1-t
*1-t1-t
m1-t1-t1-t1-ttt
S)C(C)]NFA(NFA )BB[(E)BB()B-B(
CiE)NFA-B(i)E(1BiBiTG
+−−−−−+−+=
−++++−
pt
*t
*tt
mtt
gt C)NFA B(EBBL −−++=
tg
t-g
ttgt-t-t sllli g +−+=+ 111 τ
0)1(
lim =++
×♦ k
gkt
k i
l
→∞
×
=
+×♦
+×
=
+×
=
+− +
++
++
=+
++000
1 )1(lim
)1()1()1()1(
kk
gkt
kkkt
kk
kt
kk
ktgt i
l
i
s
ii
gli
τΣ∞
Σ∞
Σ∞
→∞
×
=
+− +
−=+0
1)1(
)1(k
kktg
ti
pbli Σ
∞
373Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
(3.3a)
Equation (3.3) describes that government should react negatively to the current
outstanding government liabilities. The higher government debt liabilities should lead the
lower present value of primary deficit decrease (ie. the government should run a primary
surplus in the present value). By definition, this equation implies that primary balance surplus
can be generated through adjustment in expenditures, taxes or seigniorage.
3.2. Empirical Result: Since the crises fiscal plays dominant role
To test empirically the existence fiscal or monetary dominance, equation (3.3) will be
applied into VAR method which is similar to Canzoneri et.al (2001) and Tanner and Ramos
(2002)10 . Following Tanner and Ramos (2002), equation (3.3a) can also be manipulated
into changes form. To obtain this, add the net government primary balance from both side of
equation (3.3). Because represent the additional
liabilities (L) required to finance the operational deficit then (3.3) is re-written as:
(3.4)
Equation (3.4) interpret current additional debt required to finance operational deficit is
equal to the sum of discounted changes in the primary deficit. Following Tanner and Ramos
(2002) argument that refer to Campbell (1987) logic11 , the VAR implied from this theory is:
(3.5)
where , ai is a vector of coefficients, and is a vector of error
term. In standard form, assume that each element of the error vector vt is in turn composed
of own error term and contemporaneous correlation with other error:
(3.6)
where B is a 2 x 2 matrix whose diagonal element (“own correlation”) equal one and
whose non zero off-diagonal elements reflect contemporaneous correlation among the error
term. Equation (3.6) also obtains impulse response functions that describe the effects of
current innovations wt on values of X. Like any VAR framework, system (3.5) estimates
relationships of time-series causality that run in both directions.
??
++−=+
×
=
+−
11
)1()1(
kk
ktt
gt
i
pbEpbli Σ
∞
{ }
∑∞
=−+
∆−=1
1)1(kk
t
i
pbadl
gt
gt
gtt LLlipbadl 11)1( −− −=++≡
t2t21t10t vXaXaaX ++++= −− K
[ ]adlpb,∆=X ( )adlpb v,v=tv
( )adlpb w,wt
=tw
tt wBv =
10 Komulaenen and Pirttilä (200) used other VAR technique to investigate empirically fiscal and monetary dominance issue11 Campbell (1987) employed the similar idea to test the permanent income hypothesis in US data
374 Buletin Ekonomi Moneter dan Perbankan, September 2004
To interpret VAR result which estimates in both directions of the variables then the
interpretation of checking fiscal or monetary dominance should be treated in similar way
and still need to consult to equation (3.3a). Following Tanner and Ramos (2002), first consider
the effect of additional debt ( adlt ) innovation to future primary balance ( pbt+1 ). The equation
(3.3a) interpret that the fiscal dominance (FD) will exist under this type of shock if primary
balance are determined exogenously and unrelated to the level of previous additional debt
and therefore the nominal and or discount factor must adjust in equilibrium to satisfy the
equation. In addition, Tanner and Ramos (2002) also argue that the positive relationship
could also indicate FD because it reflects that the primary deficits respond to liabilities in
unstable fashion.
On contrast, monetary dominance (MD) exist in this type of shock if primary balance
is determined in such way that (3.3a) is always satisfied, regardless the nominal income
and discount factor behave. According to this interpretation and equation (3.3a), the
relationship between primary balance and the additional government liabilities should be
negative and significant because they indicate that primary deficits compensate the changes
in liabilities to help limit debt accumulation. Walsh (2003) classified this as a traditional
analysis in which fiscal policy always adjust to ensure government’s intertemporal budget
identity while monetary policy is free to set nominal money stock or nominal of interest rate.
A second type of shock is to consider the effect of current primary balance innovation
to future additional debt. The FD will appear if there is no significant impact on the additional
future debt of the positive innovation of primary balance. Meanwhile, the MD will occur in
this type of shock if current innovation to the primary deficit should be positively related to
the additional future government debt and hence adlt . This figure imply that if the government
run the surplus primary balance then it can pay down the debt and hence reduce additional
future debt. Another interpretation also appears in MD regime if we extend the assumption
to a variable real interest rate. Under this scenario, negative relationship between primary
balance innovation and future debt should appear because it reflect a negative government
response of reduction of primary deficit by lower (higher) expected future interest payment
and hence could make a more (less) additional borrowing. Table 2 reproduce Tanner and
Ramos (2002) economic interpretation of the VAR system result regarding to the issues.
Employing quarterly data since 1984:2 to 2003:2, the estimations are grouped into
three sub-periods as indicated by QFA result i.e. period prior 1990, period between 1990
and 1997 and period after 1997. Some quarterly raw data are obtained from author’s
calculations from old government budget format. Since the quarterly data for external
375Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
government debt stock is not available prior 1990, the external debt stock before 1990 was
calculated from net inflow government debt from balance of payment data of Bank Indonesia.
The primary surplus/deficit of government prior 1997 is generated by excluding the interest
and principal repayment foreign government debt from government budget.
The estimation result apparently confirms the QFA result estimation. The Granger
causality test in table 3 indicates the whole sample does not provide a significant relationship
between primary balance and additional debt required to finance the operational deficit.
This performance generally was supported from the sub-periods prior 1990 that do not
demonstrate a considerable relationship. The significant and negative relationship between
those two variables only appears in period between 1990 and 1997. This 1990-1997 result
is not a surprise result. Empirical data support this indication. An accumulated primary surplus
was move contrastly to the decreasing of the ratio of foreign government debt to GDP which
somehow could imply some sustainable fiscal policy.
The Granger causality test is also supported by impulse response function of VAR
result that implied an effort from fiscal policy to response future debt growth by accumulating
the government primary surplus. For period prior 1990 and since 1997 the impulse response
function does not show a significant response to the each innovation, regardless the order.
The significant impact only appear in period between 1990 and 1997 where the impulse
response function for 1990-1997 period estimation obtain a negative and significant changes
on public liabilities to an innovation of primary surplus for at least 1-2 periods (Table 4).
Tabel 2.Hypothetical Economic Interpretation, System (3.5), X=[∆pb, adl]
Positive
Zero
Negative
Government pays down future debt, consistent with fiscal dominance regime
Primary deficit exogenous, consistent with fiscal dominance regime
Government anticipates future interest bill or other obligation, consistent with monetarydominance regime
Positive
Zero
Negative
Unstable policy, consistent with fiscal dominance regime
Primary deficit exogenous, consistent with fiscal dominance regime
Government pay down past debt, consistent with monetary dominance regime
F-test value of the hypothesis. P-value in parentheses
∆ pbt ---> adt+i H0 : ∆ pbt does not granger cause adlt+iadlt ---> ∆ pbt+i H0 : adt does not granger cause ∆ pbt*, **, *** indicate statistical significance at the 1, 5 and 10 percent level, respectively
Tabel 4.Impulse Response Function Result X=[∆PDEF, ODEF]
NS: Not Significant ; NEG: Negative and Significant
377Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
argument, QFA was also quite neutral such that not sufficient enough to classify monetary
policy as sub-ordinate of fiscal policy. At some degree, the result of period 1990-1997 indicates
that monetary policy played dominant role with respect to fiscal and monetary policy
interaction.
Nevertheless the story changed abruptly while the crises hit the mid of 1997.
Although the lack of observation numbers may affect the story, the result indicated a
different portrait appeared. The sharp and huge depreciation of domestic currency, big
amount of issuing additional domestic debt and the unavoidable liquidity support from
central bank policy in 1997 – 1999 consecutively brought a big burden to fiscal policy
such that also involved monetary policy. This performance apparently indicates that
fiscal policy play more exogenously in this regime. Indeed, the study has also tried to
exclude the central bank securities to capture ‘real’ government debt and to see its
response to the primary balance performance. However, the result does not change
and keep showing similar conclusion.
4. IMPLICATION FOR INFLATION TARGETING IN INDONESIA
The results from two previous parts suggest several summaries to fiscal and monetary
policy interaction in Indonesia. First, prior crises 1997, generally fiscal policy have ensured
fiscal sustainability by accumulating primary surplus to reduce the debt ratio to GDP. Following
Leeper (1991) terms, fiscal policy during this period tended to be a passive policy because
it always tried to satisfy government budget constraint12 . Meanwhile, monetary policy plays
an active role which was confirmed by neutral position of QFA. This result apparently shows
that fiscal policy commitment on fiscal solvency lead macroeconomic policy during 1990-
1997 under monetary dominance regime.
Second, since the 1997 the fiscal and monetary policy interaction exhibits a big different
portrait. Fiscal policy seems not be able to generate sufficient amount of primary surplus
balance to cover the rise of government debt burden both from external and domestic debt.
In addition to this, banking crises also generated deficit in QFA since 1998 which mostly
caused by central bank liquidity support to banking system. In addition to this, government
policies to withdraw their deposit in central bank also provide another reason the emergence
of QFA. In general, those two environments tend to lead the conclusion fiscal policy behaves
exogenously in view of fiscal and monetary interaction framework since 1997.
12 Leeper (1991) defined passive fiscal policy as a situation in which fiscal policy always adjust their primary balance tosatisfy government’s intertemporal budget. On contrast, if fiscal policy is set independently such that could generateseigniorage from monetary authority then fiscal policy is defined under active fiscal policy.
378 Buletin Ekonomi Moneter dan Perbankan, September 2004
How this fiscal and monetary interaction result could affect central bank objective to
control inflation while in other side degree of monetary policy independence probably has
increased due to the new central bank law enacted in 1999? Referring to Leeper (1991)
terms, the result of fiscal and monetary interaction after 1997 and also higher independent
in monetary policy could implies both active in fiscal and monetary policy regime was occurred
in Indonesia since 1999. Fiscal policy is exogenous to debt performance while monetary
policy restraint the policy only to inflation. This macroeconomic policy environment has
different implications to the effectiveness monetary policy objective to control the inflation
even under inflation targeting framework which implicitly has been adopted by Indonesia.
Much of discussion corresponds to the implication of those fiscal and monetary policy stance
on inflation behaviour were put under fiscal theory of price level (FTPL) literature13 . Under
this theory, inflation is not the sole of territory of the central bank but it is also contributed by
fiscal authority.
Carlstrom and Fuerst (1999, 2000) summarized two version of FTPL namely weak
form FTPL and strong form FTPL. Under weak form FTPL which is parallel to fiscal dominance
environment in this paper, inflation is indeed monetary phenomenon but money growth is
dictated by fiscal authority because an increase in future deficits must result in either a one
time increase in money (a one-time jump in the price level) or an increase in future money
growth (future inflation). This form is analogy to game of chicken emerges in which monetary
authority loses and is forced to “blink” for this behaviour.
Meanwhile the strong form FTPL argues that even if money growth is unchanged,
fiscal policy independently affect price level and inflation rate. Strong FTPL assumes that in
order to uniquely determine price, the additional restriction of government budget constraint
is needed. Prices will adjust so that the real of government debt can adjust to a level consistent
with the fiscal budget constraint even if monetary policy is unchanged. To summarize, those
two forms of FTPL subsequently imply that the central bank may be ineffective to commit to
an inflation target, either because central bank does not control the money supply (weak
form) or because inflation is not necessarily a monetary phenomenon (strong form).
Does this FTPL emerge in Indonesia in this period after 1997? This is empirical question
and even still provides long line debatable answers for the plausible existence of the theory
at least for strong form FTPL14 . Carlstrom and Fuerst (1999, 2000) argued that strong FTPL
has some empirical problem because it needs large elasticity in real interest rate in order for
13 See Leeper (1991), Koncherlakota and Phelan (1999), Cochrane (1998) and Woodford (1996, 2001) and Walsh (2003) forthis FTPL literature.
14 Some critics relates to the existence of FTPL see Carlstrom and Fuerst (1999, 2000), Buiter (2002, 2001, 1999),
379Fiscal and Monetary Policy Interaction : Evidences and Implication for Inflation Targeting in Indonesia
self-fulfilling circle to occur. Those large real interest rate that is apparently unrealistic requires
three large elaticities: (1) a large interest of money demand; (2) a large response of output
to a decline in real balances and (3) large response of the real to decline in current output.
Parallel to Carlstrom and Fuerst (1999, 2000) argument, strong form of FTPL likely also
present empirical problem in case of Indonesia because all those assumptions seem not
appear in Indonesia economy as suggested in recent empirical studies in Indonesia regarding
to those issue 15 .
From the weak form of FTPL, the empirical situations in Indonesia also show similar
hints to strong form. So far, weak form of FTPL can not be identified clearly especially since
1999 when the central bank obtained more monetary policy independence through the new
central bank act. Since that time, central bank does not provide Bank Indonesia liquidity
credit (KLBI) as shown before 1999. In addition, the new act also prohibits government
intervention to monetary policy including seigniorage from the central bank. Despite QFA by
central bank show deficit number, some evidences support the idea that fiscal policy keep
trying to avoid financing from central bank. Except in 2003, domestic financing from central
bank tend to be negative which implies accumulating government deposit in the central
bank (Table 5). Instead, the sources of deficit financing were source from government bond
issuance and privatization of state enterprises. In addition to it, base money also grew at a
low level.
To sum up, the empirical data identified can not clearly identify FTPL occurrence in
Indonesia since 1999 for both strong and weak from of FTPL. The QFA in central bank
seems can be classified into monetary policy discretion due to liquidity support problem
while the fiscal dominance conclusion using VAR approach in part three test might still be
an ambiguous result due to the lack of data. Zoli (2004) employed data from some emerging
countries argues that VAR method could provide an ambiguous result. This result implies
that monetary policy could be still dominance in term of fiscal and monetary interaction
since period 1999.
Despite those empirical results rejection on FTPL and the tendency of monetary policy
dominance in Indonesia, some literatures still show that fiscal performance can still affect
the effectiveness of monetary policy even under inflation targeting. Using Brazil experience,
Blanchard (2004) indicated that expectation channel of fiscal performance deterioration
could cause a reversal effect of monetary policy to control inflation. Employing fiscal
dominance term to represent the deterioration of domestic government debt, Blanchard
15 Among others see Anglingkusumo (2004) and Simorangkir (2002) that examined demand for money function in Indonesia.Macroeconometric model of Bank Indonesia (MODBI) also show a small elasticity result of interest rate impact on output.
380 Buletin Ekonomi Moneter dan Perbankan, September 2004
Tabel 4.Government Budget, 1997 - 2003 (Central Government Operation1) (% of GDP, Otherwise stated))
1997/98 1998/99 1999/00 2000 2001 2002 2003
Level Level Level Level Level Level Level
Total revenue and grants 112,276.0 156,408.5 200,643.7 205,334.5 301,077.7 300,185.9 342,787.0
(using the EMERALD Indonesian multi-regional CGE model)
Daniel PambudiAndi Alfian Parewangi1
Paper ini membahas dampak ekonomi dari subsidi terhadap industri yang dapat menarik minat
investor pada daerah tertentu. Dengan mempergunakan EMERALD (Equilibrium Model with Economic
Regional Analysis Dimensions) yang merupakan model CGE multi region untuk Indonesia, paper ini
menganalisa beberapa simulasi alternatif pembiayaan subsidi industri Tekstil di Jawa Tengah.
Hasil yang diperoleh menunjukkan bahwa subsidi atas industri Tekstil dengan sumber pendanaan
bukan pajak akan meningkatkan daya saing industri Tekstil diatas biaya sektor tradable secara
keseluruhan. Secara riil, subsidi ini akan meningkatkan PDRB Jawa Tengah sebesar 0.21%. Jika
subsidi tersebut dibiayai dari pengenaan pajak atas rumah tangga, akan meningkatkan PDRB Jawa
Tengah sebesar 0.11%.
Keyword: Regional, Computable General Equilibrium, investment, subsidy
JEL: C68, D92, E62, O18
1 Pambudi is PhD student at the Centre of Policy Studies (CoPS), Monash University, supervised by Dr. Mark Horridge.Pambudi’s interest is in the application of multi-sectoral and multi-regional economic model for policy analysis. AndiAlfian Parewangi was visiting scholar at CoPS, Monash University under supervision of Dr. Glyn Wittwer and also lecturerat Department of Economic, University of Indonesia.
388 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
1. BACKGROUND1.1. Introduction
The aim of this research is to construct a bottoms-up CGE model for Indonesia that
can be used for studying and analysing regional policies comprehensively. This model makes
us possible to simulate regional based polices scenario to obtain the regional and national
results.
This model adopts the TERM model structure for comparative static analyses. We
use the new model to study the policy implications of competitive bidding between regions
to attract investment. Tax concessions, for instance, are sometimes viewed as an attractive
instrument to boost regional and national welfare. However, national approaches differ. For
example, Australian states subsidize some investors and the Federal Government taxes
them. Vietnam taxes them. The model may suggest which approach is better. Also, the
long-run effects of taxing (or subsidizing) investments may differ from the short-run effects.
Again, national interest may conflict with those of individual regions. The model will be used
to examine some of these issues.
To construct this big multiregional model, we require data on regional supplies and
demands. Moreover, the necessary inter-regional flows data showing, for example, what
share of bananas eaten in Kalimantan come from Java are rarely available. To overcome
these problems, innovations will be needed. In preparing and making data which used for
this model, we adopt a data making process from Horridge, such as using the gravity approach
to produce inter-regional data.
Three existing CGE models, each heavily influenced by the ORANI model (Dixon et
al. 1982), provide components which may be adapted to contribute to a new multiregional
model. These three models are MMRF (the Monash Multi Regional Forecasting Model), the
Indonesian ORANI (INDORANI) and the default model of the Global Trade Analysis Project
(GTAP).
• MMRF is a multiregional multisectoral model of Australia based on the single region
ORANI model of the Australian economy (Adams, Horridge and Parmenter, 2000).
• INDORANI (Abimanyu, 2000), based on ORANI-G (Horridge 2000; see also Horridge, et
al. 1993), is a multisectoral model of the Indonesian economy with “tops-down” approach.
Both models will provide with necessary ingredients: “bottoms-up” approach and
Indonesian data in constructing the new model.
• GTAP, a world trade model, includes trade links between all regions for all commodities
389Illustrative Subsidy Variations to Attract Investors
(Hertel and Tsigas, 1997). It is useful to follow the GTAP in attributing competition among
regions in the new model.
We plan to explain the model into four sections. Section 2 contains structure of the
database, graphical description of nesting and computational efficiency. Section 3 contains
model equations. Section 4 contains database. Section 5 contains simulation results of
subsidy variations to attract investors.
1.2. Development CGE model in Indonesia
The previous models of Indonesia have used “tops-down” approach. In a “tops-down”
model, regional results merely are a decomposition of national results. By contrast, in a
“bottoms-up” model each region is modeled independently. There is interaction between
each regional and national agent and also among regional agents. This approach is
preferable.
2. STRUCTURE OF THE DATABASE AND NESTING2.1. Introduction
EMERALD is a bottoms-up regional CGE model which treats each region as a separate
economy. This is particularly suitable for Indonesia, with its 32 diverse provinces. In a
“bottoms-up” model each region is modeled independently. The “bottoms-up” method allows
us to capture differences between regional economies and to model the effects of region-
specific supply-side shocks. Unfortunately computational constraints have hitherto hindered
the construction of CGE models with as many as 32 separate regions.
2.2. The structure of the database
Figure 2.1 shows the basic structure of the model based on each region’s input-output
database. The rectangles indicate matrices of flows. Core matrices (those stored on the
database) are shown in bold type; other matrices may be calculated from the core matrices.
The dimensions of the matrices are indicated by indices (s, c, m, etc) which correspond to
the sets in Table 2.1.
EMERALD recognises three sets of regions: regions of use (d), of origin (r), and of
origin of margins (p) (i.e., the origins of margins services used to deliver a commodity from
(r) to (d)). In fact, the three sets are the same: they are labeled according to the context of
use.
390 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
EMERALD assigns three different value flows:
• basic values, or output prices for domestically-produced commodities and CIF prices for
imports;
• delivered values (= basic plus margins);
• purchasers’ values which equals delivered plus taxes.
As a consequence, EMERALD produces price indices which distinguish between
different points of sale by commodities and regions. Each region has its own set of supply,
demand and trade matrices. This allows simulations of policies that have region-specific
price effects.
The matrices on the left-hand side in Figure 2.1 resemble (for each region) a
conventional single-region input-output database. For example, the matrix USE(c,s,u,d) at
the top left shows the delivered value of demand for each good (c in COM) whether domestic
or imported (s in SRC) in each destination region (DST) for each user (user, comprising the
industries, IND, and 4 final demanders: households, investment, government, and exports).
Some typical element of USE might show:
• USE(“Agriculture”,”dom”,”TCF”,”DIY”) is domestically-produced Agriculture; used by the
TCF industry in region DIY.
• USE(“Mining”,”imp”,”EXP”,”DKI”) is the imported value of mining re-exported from a port
in DKI.
Tabel 2.1.Main Sets of The EMERALD
Index Set Name Description Typical Size
s SRC Domestic or imported (ROW) sources 2
c COM Commodities 19
m MAR Margin commodities 2
i IND Industries 19
o OCC Skills 9
d DST Regions of use (destination) 26
r ORG Region of origin 26
p PRD Region of margin production 26
f FINDEM Final demanders (HOU, INV, GOV, and EXP) 4
u USER Users = IND union FINDEM 23
391Illustrative Subsidy Variations to Attract Investors
As the last example shows, the data structure allows for re-export (at least in principle).
All these USE values are “delivered”: they include the value of any trade or transport margins
used to bring goods to the user. Notice also that the USE matrix contains no information
about the regional sourcing of goods.
The TAX matrix of commodity tax revenues contains an element corresponding to
each element of USE. Together with matrices of primary factor cost and production taxes,
these add up to the cost of production (or value of output) of each regional industry.
In principle, each industry is capable of producing any good. The MAKE matrix at the
bottom of Figure 2.1 shows the value of output of each commodity by each industry in each
region d.
EMERALD recognises inventory changes in a limited way. First, changes in stocks of
imports are ignored. For domestic output, stocks are unsold industry outputs, so the dimension
of stocks is STOCK (i,d) rather than STOCK(c,d).
USE(c,s,u,d) is the delivered value of commodity c from source s used by users u in
region d. Delivered value means basic plus margin values. To produce USE(c,s,u,d) from
the DELIVRD(c,s,r,d), EMERALD assumes that all users of a given good (c,s) in a given
region (d) have the same sourcing (r) mix. In effect, for each good (c,s) and region of use (d)
there is a broker who decides for all users in d from which source region, r, supplies will be
obtained. We use the Armington (1969, 1970) sourcing assumption that DELIVRD_R (c,s,d)
is a CES composite (over r in ORG) of the DELIVRD(c,s,r,d).
The DELIVRD(c,s,r,d) matrix shows the delivered value of demand of commodity c,
source s, from region r to region d. For each flow there is a quantity and a price variable. For
example, pdeliverd(c,s,r,d) and xtrad(c,s,r,d) are price and quantity variables corresponding
to the matrix DELIVRD(c,s,r,d).
Using a CES nest, the quantity of goods from different regions of r to destination d,
xtrad(c,s,r,d), is proportional to the quantity of goods summed over r, xtrad_r(c,s,d) and to a
price term powered by elasticities of substitution, SIGMADOMDOM(c), between the source
regions for each commodity c. The price term is composed of relative price, pdeliverd(c,s,r,d)
to puse(c,s,d). Changes in the relative prices of commodity between r induce substitution in
favour of relatively cheapening goods.
Because DELIVRD(c,s,r,d) is comprised of TRADE(c,s,r,d) plus sum{m,MAR,
TRADMAR (c,s,m,r,d)}, we used xtrad(c,s,r,d) as a quantity variable for both DELIVRD(c,s,r,d)
and TRADE(c,s,r,d). The delivered prices variable, pdelivrd(c,s,r,d), is used for
392 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
DELIVRD(c,s,r,d) and basic prices, pbasic(c,s,r) for TRADE(c,s,r,d). Note that pdelivrd(c,s,r,d)
is composed of pbasic(c,s,r) and margin prices, psuppmar_p(m,r,d). For TRADMAR
(c,s,m,r,d), we used a quantity variable xtradmar(c,s,m,r,d). We will discuss how these
variables relate to nesting system in Section 2.3.
TRADMAR(c,s,m,r,d) shows the value of margin goods (m) which is required to
facilitate trade flows. Since TRADMAR(c,s,m,r,d) has no information on where a margin
flow is produced, EMERALD requires matrix SUPPMAR(m,r,d,p). It assumes that for all
usage of margin goods used to transport any goods from region r to d, the same proportion
of margin, m, produced in region p.
A balancing requirement for the EMERALD database is that the sum over user (u) of
USE(c,s,u,d), USE_U(c,s,d), shall equal DELIVERD_R(c,s,d) which is the summation over
regional sources (r) of the DELIVERD(c,s,r,d).
It remains to reconcile demand and supply for domestically-produced goods. In Figure
2.1 the connection is made by arrow linking the MAKE_I matrix with the TRADE and
SUPPMAR matrices. For non-margin goods, the domestic part of the TRADE matrix must
sum (over d in DST) to the corresponding element in the MAKE_I matrix of commodity
supplies. For margin goods, we must take into account both the margins required
SUPPMAR_RD and direct demands TRADE_D.
For many purposes it is useful to break down investment according to destination
industry. The satellite matrix INVEST (subscripted c in COM, i in IND, and d in DST) serves
this purpose. It allows us to distinguish the commodity composition of investment according
to industry: for example, we would expect investment in agriculture to use more machinery
(and less construction) than investment in dwellings.
2.3. Graphical description of demand nesting
Figure 2.2 represents the household demand sourcing of TCF in region DKI. As all
users in the EMERALD have the same demand sourcing by commodities and regions, we
can apply this figure for all commodities, users and regions. From the top to the bottom,
there are two different nests (CES and Leontief) indicating different types of substitution in
the model. They cover all mechanisms of demand sourcing of TCF and its margin from
different regions to DKI. At the top, a CES nest determines domestic and imported TCF
used by households in DKI. This nest corresponds to the value of flows (shown in upper
case) with price, ppur_s(c,u,d) and quantity, xhou_s(c,d) variables. The dimensions of the
393Illustrative Subsidy Variations to Attract Investors
model correspond to the matrices in Figure 2.1. Note that these flows are purchasers values
which are the sum of USE(c,s,u,d) and TAX(c,s,u,d) matrices. The Armington elasticity 2.6
represents a CES in choosing between imported (from other country) and domestic TCF.
Figure 2.1The EMERALD flows Database
USER x DST
IND
USE
(c,s,u,d)
Delivered value of demands:
basic + margins (ex_tax)
quantity: xint(c,s,i,d)
price: puse(c,s,d)
INVEST (c,i,d)purchasers value of good c usedfor investment in industry i in d
price: pinvest (c,d)quantity: xinvi(c,i,d)
TAX
(c,s,u,d)
Commodity taxes
COM
x SRC
FACTORS
LAB (i,o,d) labour
CAP (i,d) capital rental
LND (i,d) land rentals
PRODTAX (i,d) production tax
+
+
=
=
MAKE
(c,i,d)
output of good c by industry i in d
update: xmake(c,i,d)*pdom(c,d)
IND x DST
+
COM
= =
DST
CES
ORG x DST
DELIVRD
(c,s,r,d)
= TRADE(c,s,r,d)
+ sum{m,MAR, TRADMAR(c,s,m,r,d)}
price: pdelivrd(c,s,r,d)
quantity: xtrad(c,s,r,d)
=
TRADE(c,s,r,d)
goods c, s, from r to d at basic pricesprice: pbasic(c,s,r)
quantity: xtrad(c,s,r,d)
TRADMAR
(c,s,m,r,d)
margin m on good c, s from r to d
price: psuppmar_p(m,r,d)
quantity: xtradmar(c,s,m,r,d)
SUPPMAR(m,r,d,p)
Margins supplied by p on goods passingfrom r to d
update:xsuppmar(m,r,d,p) * pdom(m,p)
MAKE_I(m,p)=SUPPMAR_RD(m,p) +TRADE_D(m,"dom",p)
TRADMAR_CS(m,r,d)
SUPPMAR_P(m,r,d)
CES sum over p in REGPRD
sum over COM and SRC
=sum over
i in IND
MAKE_I(c,r)
=TRADE_D
(c,"dom",r)
=
= Leontief
+
INDUSTRY OUTPUT:VTOT(i,d)
INVENTORIES: STOCKS (i,d)
DST ORG x DST
INDEX Set Description
c COM Commoditiess SRC Domestic or imported (ROW) sources
m MAR Margin commodities
r ORG Region of origind DST Region of use (destination)
p PRD Region of margin productionf FINDEM Final demanders (HOU, INV, GOV, EXP)
i IND Industriesu USER Users = IND union FINDEM
IMPORT
(c,r)
USE_U(c,s,d)
=DELIVRD_
R(c,s,d)
price:pdelivrd_r
(c,s,d)
FINDEM(HOU, INV,
GOV, EXP)final demands
by 4 users atdelivered price:
puse(c,s,d)quantities:
xhou(c,s,d)xinv(c,s,d)
xgov(c,s,d)xexp(c,s,d)
COM
x SRC
MAKE_I(c,d)
domestic
commoditysupplies
(c,s,d)
394 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
Demand for domestic TCF in DKI is summed over users to give total value
USE_U(c,s,d) which is measured in delivered value (basic plus margin but excluding user-
specific commodity taxes). Note that this nest is not user-specific. This nest represents
demand for domestic TCF in DKI supplied by all origin of TCF. The CES determines the
allocations with substitution elasticities ranging from 5 (merchandise) to 0.2 (services).
This CES implies that the region with lowered production costs compared to other regions
will tend to increase its market share. The sourcing decision is made on the basis of
delivered prices so not only basic costs affect regional market share but also margin
costs. Note that variables in this nest lack a user (u) subscript. The decision is made on an
all-user basis. The implication is that, in DKI, the proportion of TCF which come from
JaTeng is the same for all users.
The next level indicates how a “delivered” TCF from JaTeng is a Leontief composite
of basic TCF, corresponding with matrix TRADE(c,s,r,d), and the various margin goods,
TRADMAR (c,s,m,r,d). The share of each margin in the delivered price is specific to a particular
combination of origin, destination, commodity and source. For example, we should expect
transport costs to form a larger share for region pairs which are far apart, or for heavy or
bulky goods. The number of margin goods will depend on how aggregated is the model
database. Under the Leontief specification we prevent substitution between road and trade
margins.
The bottom part shows that the margin on TCF passing from JaBar to DKI could be
produced in different regions. The figure shows the sourcing mechanism for the road margin.
We might expect this to be drawn more or less equally from origin (JaTeng), the destination
(DKI) and regions between (JaBar). There would be some scope for substitution (s=1),
since trucking firms can relocate depots to cheaper regions. For retail margins, on the other
hand, a larger share would be drawn from destination region, and scope for substitution
would be less (s=0.1). Once again, this substitution decision takes place at an aggregated
level. The assumption is that the share for example, JaBar, in providing road margin on trips
from JaTeng to DKI, is the same whatever good is being transported. This corresponds to
TRADMAR_CS(m,r,d) which has no c and s scripts. Although not shown in Figure 2.2, a
parallel system of sourcing is also modelled for imported TCF, tracing them back to port of
entry instead of region of production.
2.4. Graphical description of production nesting
The EMERALD adapts production nests from ORANI. This allows each industry to
395Illustrative Subsidy Variations to Attract Investors
produce several commodities, using as inputs domestic and imported commodities, labour
of several types, land, capital and ‘other costs’ which are all distinguished by region. The
multi-input, multi-output production specification is kept manageable by a series of
separability assumptions, illustrated by the nesting shown in Figure 2.3. For example, the
assumption of input-output separability implies that the generalised production function
for some industry:
F(inputs, outputs) = 0 (1)
may be written as:
G(inputs) = X1TOT = H(outputs) (2)
where X1TOT is an index of industry activity. Assumptions of this type reduce the
number of estimated parameters required by the model. Figure 2.3 shows that the H
function in (2) is derived from a CET (constant elasticity of transformation) aggregation
function.
The G function is broken into a sequence of nests. At the top level, commodity
composites, a primary-factor composite and production costs are combined using a Leontief
production function.
Consequently, they are all demanded in direct proportion to X1TOT. Each
commodity composite is a CES (constant elasticity of substitution) function of a domestic
good and the imported equivalent. We adopt the Armington (1969; 1970) assumption
that imports are imperfect substitutes for domestic supplies2 . The primary-factor
composite is a CES aggregation of land, capital and composite labour. Composite labour
is a CES aggregation of occupational labour types. Although all industries share this
common production structure, input proportions and behavioural parameters may vary
between industries.
The nested structure is mirrored in the TABLO equations—each nest requiring 2 sets
of equations, determining quantity and price.
2 Armington PS (1969) The Geographic Pattern of Trade and the Effects of Price Changes, IMF Staff Papers, XVI, July, pp176-199.— (1970) Adjustment of Trade Balances: Some Experiments with a Model of Trade Among Many Countries, IMF StaffPapers, XVII, November, pp 488-523.
396 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
Excerpt 17 describes industry specific investment demands. The gross rate of return,
GRET(i,d), is determined as a ratio of capital rental to price of new capital. The investment
by industries, XINVITOT(i,d) is capital usage, XCAP(i,d), multiplied by the gross growth rate
of capital, GGRO(i,d). Where GGRO(i,d) is determined by the DPSV (Dixon et al. 1982)
investment rule3 .
3 As explained in excerpt 31 of the Oranig03.tab, above equation comes from substituting the values 0.33 and 2.0 whichcorrespond to the DPSV ratios [1/G.Beta] and Q (= ratio, gross to net rate of return) and are typical values of these ratios. InDPSV invslack was called “omega” and was interpreted as the “economy-wide rate of return”.
414 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
! Excerpt 17 of TABLO input file: !
! Industry-specific investment demands !
GRET(i,d) Gross rate of return = rental/[price of new capital]
GGRO(i,d) Gross growth rate of capital = investment/capital
FINV1(i,d) Investment shift variable
INVSLACK Investment slack variable for exogenizing national investment
Table 5.2 shows trade inflows to JaTeng. There are three sources of TCF used in
JaTeng: local (47%), other regions (45%) and import (8%).
Tabel 5.2.Source of TCF used in JaTeng (in billions of Rupiah)
Local Production Other Regions ROW Import Total
8890 8608 1474 18972
46.86% 45.37% 7.77% 100%
420 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
5.3. Closure
We used a long-run closure for most of the experiments: within each region, labour is
completely mobile between sectors. A wage differential is needed to induce labour movement
between regions. The national labour supply is fixed. Rates of return (ROR) are exogenous
and capital for each regional industry is in elastic supply. Foreign currency prices of imports
are naturally exogenous. Population is also held constant. Other exogenous variables include
changes in rate of production tax, technology, price and quantity shift variables.
On the regional expenditure side, nominal household consumption moves with nominal
labour income. Real aggregate investment follows regional demands for capital. Real
government consumption follows real household consumption. Export demand elasticities
and export prices determine export volumes.
Most national results are no more than the sum of the corresponding regional results.
However a few constraints were imposed at the national, rather than the regional, level.
National employment is fixed, while real wages adjust. National real household consumption
moves with real GDP. The exchange rate is fixed as numeraire. Table 5.3 shows that for
exogenous variables, main macro results for both Indonesia as a whole and JaTeng, are
zero. Other than unfunded subsidy, we examine three alternative ways of financing the
subsidy: to shift the cost of the subsidy either to JaTeng consumers, to JaTeng industries or
to reduce JaTeng government demands.
To shift the cost of the subsidy either to JaTeng consumers or to JaTeng industries, we
use two slightly different closures to hold indirect tax (commodity plus production tax) revenue
constant. In the first closure, rates of commodity taxes for JaTeng households adjust uniformly
to finance the subsidy. In the second closure, production tax rates for JaTeng industries are
raised to finance the TCF subsidy. To finance the subsidy by reduction in JaTeng government
demands, we reduce government demand by a sum equal to the cost of the subsidy 4 .
5.4. Shock
To subsidise the Textiles, Clothing and Footwear industry (TCF) in JaTeng, we shocked
the model by shifting down the supply curve for TCF5 . Since labour and capital in long run
are mobile between sectors, EMERALD has very flat long run regional industry supply curves.
4 We apply variable fgovtot2 which represents government demand shifter.5 We shocked the model by applying delPTXrate(“TCF”,”JaTeng”)=-0.01. This variable has two dimensions, industry and
region. The ‘delPTXrate’ represents an ordinary change in an ad valorem production tax rate. The negative figure “-0.01”means that we subsidise JaTeng Textiless, Clothing and Footwear industry by 1% of the value of output.
421Illustrative Subsidy Variations to Attract Investors
Figure 5.1 illustrates the interaction between JaTeng TCF demand and supply. The
initial equilibrium is at point E. The shock moves the supply curve down from S to S’. As a
result, the equilibrium moves from point E to E’, which has lower price and higher quantity
than initially. Because of input-output linkages, employment, wages and household income
all rise. As a result, the demand curve will shift upward from D to D’. It creates a new
equilibrium at point E” which greater quantity than point E’.
Figure 5.1 Interaction between demandand supply for JaTeng TCF
5.5. Simulation results
Simulation results appear in Table 5.3 to Table 5.6—they differ according to the financial
approaches to the TCF subsidy. We discuss the results in the following order: (1) unfunded
subsidy, (2) subsidy paid for by consumers, (3) subsidy paid for by industries, followed by
(4) subsidy funded by reduction in local government demands. Returning to the unfunded
subsidy, we focus on a neighbouring region and on national results. Each table of results
shows main macro variables, TCF sector variables, and sectoral outputs.
5.5.1. Unfunded subsidy
Table 5.3 shows three results columns. The first column shows results for JaTeng
(Central Java), the second results for DIY (District of Yogyakarta, a neighbouring region)
and the third, national results. In this section, our discussion focuses on column (1).
Price
D’
D
1%
Shift
E
E’
E’’
S
S’
Quantity
422 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
JaTeng TCF sector (Table 5.3, column (1))
When we subsidise JaTeng TCF by 1%, output price of TCF decreases further, by 1.1%.
This is because intermediate input cost falls by 0.24% to dominate increases in other cost
(capital rental by 0.034% and wages by 0.25%). Note that 26% of TCF input is TCF output.
Since domestic prices fall, not only do international exports of TCF increase by 5.5%,
but also exports to other regions increase by 5.0%. Imports lose market share so that local
TCF sales increase by 7%. This causes TCF output to increase by 5.96%. Consequently,
demands for inputs also increase. Employment rises by 5.89% and capital rises by 6.0%.
To attract labour from other regions, wages had to rise by 0.25%. Capital rentals rose
by 0.034% (the latter are indexed to the investment price index). Since wages rose more
than capital rentals, TCF employment rose by less than TCF output, while capital use rose
by more (MPL is positive function of K/L ratio).
Imports of TCF from other regions only increase by 1.7% mainly because the local
demand shifts toward JaTeng TCF. We see from local TCF used locally increases by 7%.
JaTeng macro results (Table 5.3, column (1))
In the macro results, JaTeng real household consumption rises by 0.42% in line with
nominal labour income (employment increases by 0.21% plus nominal wages by 0.25%).
The 0.25% increase in nominal wages is composed of an increase in average real wage of
0.24%, plus a 0.012% increase in CPI.
Again, real government consumption grows by 0.42% to follow real household
consumption. Since we assume gross growth rates of capital to be fixed, investment follows
capital growth. Hence, JaTeng real investment grows by 0.22% and aggregate capital stock
by 0.22%.
The export price index falls by 0.097% (due to a domestic price fall, i.e, price of GDP
falls by 0.032%). So export volumes grow by 0.29%. Import volumes used grow by 0.43%
because demand expands and imports lose market share. Hence, real GDP grows by 0.21%.
JaTeng sectoral output (Table 5.3, column (1))
In national or trade-exposed industries which compete with the same industries from
other regions, the wage rise increases costs, leading to loss of market shares. So output
and employment shrink.
423Illustrative Subsidy Variations to Attract Investors
However, industries less exposed to competition grow. For example, utilities grow by
0.40% and government services by 0.31%. Since local goods are produced and consumed
locally, demand for local goods grows to follow absorption (which is itself driven by labour
income). Since input costs to JaTeng firms rise, output prices also rise except in TCF sector.
Traded industries ranging from agriculture to manufactures shrink; machines and
electronics by 0.15% and mining by 0.16%. In turn, their demands for inputs contract.
Except for TCF exports, rising input costs cause exports to shrink. For example, in
agriculture domestic prices rise by 0.017% and exports shrink by 2.3%.
Jobs grow in TCF (by 5.9%) and in non-traded sectors, but shrink in trade-exposed
sectors.
5.5.2. Unfunded subsidy: effect on neighbour and nation
The effects on neighbour and nation of a long-run unfunded subsidy are shown in
Table 5.3, DIY (column (2)) and National (column (3)). Note that DIY is a neighbour region
surrounded by JaTeng. It is interesting to observe that effects on DIY are similar to effects
on JaTeng (but smaller). DIY also benefits, again led by increased TCF output. The reason
is that TCF partly from JaTeng is a big input into DIY TCF—so cheaper TCF imports benefit
DIY TCF also. National results are also positive, although small. One reason is that national
results are no more than the sum of the corresponding regional results.
TCF sector (Table 5.3, column (2, 3))
Since 24% of TCF in DIY is from JaTeng: a fall in JaTeng TCF domestic price by 1.1%
causes DIY TCF domestic prices to fall by 0.065%. As consequences, TCF output in DIY
expands by 0.57%. Then the demand of inputs rises, capital by 0.58% and labour by 0.55%.
To attract labour from other regions, wages had to rise by 0.077% relative to capital rentals
by 0.015% (the later are indexed to investment price index).
Due to TCF price falls, TCF output, export to ROW increases by 2.78%, and exports
to other regions increase by 0.75%. Import from other regions also increase by 1.6% because
of demand expansion. Again, local demand for local TCF rises by 0.11%.
Column (3) shows that national output prices for TCF falls by 0.16%. As results, TCF
output and exports all rise by 0.90% and by 1.42%. This sector sucks in employment from
other sectors by 0.90%. Note that national employment is fixed.
424 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
Macro results (Table 5.3, column (2, 3))
In DIY, even though export prices fall by 0.031%, export volume falls by 0.046%. This
indicates that domestic demand is stronger than export. We can see from a rise in GDP
price index by 0.036%.
DIY also sucks in labour and capital from other regions. Aggregate employment and
capital stock in DIY increase by 0.029% and 0.021%. This causes real GDP to grow by
0.023%. Since labour income rises, household expenditures and government expenditure
all rise by 0.059%. Real investment grows by 0.016% to follow a growth in capital stock.
Again, import volume used increases by 0.095% to follow expansion in economy activity.
Tabel 5.3.Unfunded subsidy to TCF industry in JaTeng
RealHou Real Household Expenditure 0.418 0.059 0.001RealInv Real Investment Expenditure 0.219 0.016 0.001RealGov Real Government Expenditure 0.418 0.059 0.003ExpVol Export Volume 0.285 -0.046 0.027Xdomexp_c Export to other regions 0.261 0.060 -Xdomimp_c Import from other regions 0.378 0.058 -ImpVolUsed Import Volume Used 0.425 0.095 0.026ImpsLanded Import Volume Landed 0.332 0.130 0.026RealGDP Real GDP 0.206 0.023 0.001AggEmploy Aggregate Employment 0.208 0.029 0.000AveRealWage Average Real Wage 0.241 0.062 0.033AggCapStock Aggregate Capital Stock 0.220 0.021 0.002GDPPI Price GDP -0.032 0.036 0.000CPI Consumer Price Index 0.012 0.015 0.001ExportPI Export Price Index -0.097 -0.031 -0.012
DescriptionTCF Sector Variable
xexpsho(“TCF”) Direct exports to Row 5.533 2.776 1.416xtot(“TCF”) Industry output 5.962 0.565 0.902plab_o(“TCF”) Nominal wage 0.253 0.077 -xlab_o(“TCF”) Employment 5.892 0.547 0.898pcapsho(“TCF”) Capital rentals 0.034 0.015 -xcap(“TCF”) Capital 6.008 0.578 -pint(“TCF”) Intermediate cost -0.236 -0.120 -pdom(“TCF”) Domestic prices -1.111 -0.065 -0.160xdomexp(“TCF”) Export to other regions 4.975 0.747 -xdomimp(“TCF”) Import from other regions 1.732 1.574 -xdomloc(“TCF”) TCF made and used locally 7.000 0.108 -
425Illustrative Subsidy Variations to Attract Investors
Long-run national effects
As comparison, Figure 5.2 shows regional real GDP results. JaTeng wins most with a
growth in real GDP followed by DIY. In contrast, other regions lose slightly.
Subsidising JaTeng TCF is good for the whole nation. Table 5.3, column (3) shows
that real GDP grows by 0.001%. All spending rise, for example, real household expenditure
and investment by 0.001%. Since we assume national aggregate employment is fixed, a
0.002% growth in capital determines a 0.001% growth in national GDP. Ordinary change in
share of real trade balance to real GDP increases by 0.002%.
Sectoral output (Table 5.3, column (2, 3))
Local industries grow in DIY such as utilities by 0.26% and government service by
0.12%. On the other hand, trade-exposed industries shrink for instance, food and drink by
0.14% and wood paper by 0.16%. It is because of substitution toward other regions product
as a result from a DIY rising costs. Again, national sectoral output follows the sum of the
corresponding regional results for example in column (3), food and drink shrinks by 0.12%
and wood paper by 0.084%. Except TCF, growing sectors include utilities by 0.033%,
construction by 0.001% and government service by 0.002%
xtot(“OtherManuf”) Other Manufactures -0.040 -0.340 -0.380 -0.155
xtot(“ElecGasWater”) Electricity, Gas, and Water 0.395 -0.293 0.103 0.259
xtot(“Construction”) Construction 0.097 -0.204 -0.107 0.035
xtot(“Trade”) Trade 0.066 -0.224 -0.157 -0.014
xtot(“ HotelRest”) Hotel and Restaurant 0.335 -0.430 -0.095 0.074
xtot(“Transport”) Transport 0.102 -0.261 -0.159 0.001
xtot(“OtherServ”) Other Services 0.191 -0.310 -0.119 0.018
xtot(“GovSrvces”) Government Services 0.307 -0.363 -0.056 0.030
432 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
cut then discuss column (3): the total effects.
Since the first column is nearly the same as the unfunded subsidy in the previous
section, here we focus on the second and total columns.
JaTeng TCF sector (Table 5.6, column (2, 3))
Column (2), the effect of the government spending cut, shows that when government
releases labour and capital, wages fall by 0.11% and capital rentals fall by 0.013%. Also,
intermediate input cost falls by 0.012%. So, TCF output price falls by 0.025%. Then, output
expands by 0.13%. In turn, export to ROW and to other regions expand by 0.14% and by
0.13%. Import from other regions only expands by 0.009% due to substitution toward local
TCF (TCF produced and used locally increases by 0.13%).
Column (3), the total effect shows that TCF output grows by 6.1%. Government
spending cut can be interpreted as a subsidy to TCF sector by reducing production cost. In
comparison to the previous simulations, TCF domestic price under this policy falls by more,
1.14%. Consequently, TCF output, export to ROW and export to other regions all expand.
JaTeng macro results (Table 5.6, column (2))
Even though regional costs are decreasing, real household expenditure falls by 0.16%.
This is because JaTeng labour income decreases [Note that aggregate employment falls by
0.084% and real wage falls by 0.092% and 0.084% + 0.092% ~ 0.16%]. In contrast, real
investment grows by 0.052%, following a 0.05% growth in aggregate capital stock.
Since local prices decrease, export volumes increase by 0.44% (mainly to ROW) and
import volumes fall by 0.065%. The changes in exports and imports causes the share of real
trade balance in real GDP to grow by 0.016%.
Perhaps counterintuitively, the government cuts leads to a small GDP rise. This is
because we follow a rule6 that the average real wage and a labour migration elasticity
determine labour supply. If we apply an elasticity value of 3 (in this we used 1) real GDP
shrinks by 0.045%.
Falling wages induce JaTeng price indexes to fall. For example the CPI falls by 0.017%,
the export prices index by 0.016%, the investment price index by 0.013% and the government
price index by 0.052%, and so the GDP price index falls by 0.040%.
6 XLAB_IO(d)=AVEREALWAGE(d)^1*FLABSUP(d)*LABSLACK; where AVEREALWAGE(d)=average real wage; 1=labour migration elasticity; XLAB_IO(d)=inter-regional labour migration or labour supply; FLABSUP(d)=Labour migrationshifter; LABSLACK=Slack to allow aggregate employment constraint
433Illustrative Subsidy Variations to Attract Investors
Note that welfare cost of sacking government officers, for example teachers, are not
captured by this experiment.
JaTeng macro results (Table 5.6, column (3))
Column (3), the total effect, shows that all spending (except government) expand: for
example investment grows by 0.27%. JaTeng sucks in labour and capital— labour is up
0.12% and capital 0.28%. As a result, real GDP expands by 0.21%.
The export price index falls by 0.11%, but the CPI, only by 0.005%. This is because
the share of JaTeng TCF for export is about as twice as much for households. This causes
GDP price index to fall by 0.073%.
Since export price decreases, export volume increases by 0.73%. Again, import volume
expands by 0.36% as a result from expanding in production (driven by TCF sector).
JaTeng sectoral output (Table 5.6, column (2, 3))
Column (2), the effect of government spending cut, shows that government services,
hotel and restaurant, utilities and other services shrink because they released labours. On
the other hand, other sectors employed more labours so they grow.
Tabel 5.6.Subsidy funded by reduction in local government demands (JaTeng results)
(1) Efex of Subsidy
= (3) - (2)
(2) Efex of
gov cut(3) TotalDescriptionMain Macro Variable
RealHou Real Household Expenditure 0.416 -0.158 0.258
RealInv Real Investment Expenditure 0.219 0.052 0.271
RealGov Real Government Expenditure 0.408 -2.185 -1.777
ExpVol Export Volume 0.283 0.444 0.728
Xdomexp_c Export to other regions 0.262 0.093 0.355
Xdomimp_c Import from other regions 0.377 -0.063 0.314
ImpVolUsed Import Volume Used 0.424 -0.065 0.359
RealGDP Real GDP 0.206 0.000 0.206
AggEmploy Aggregate Employment 0.207 -0.084 0.124
AveRealWage Average Real Wage 0.240 -0.092 0.149
AggCapStock Aggregate Capital Stock 0.220 0.058 0.278
GDPPI Price GDP -0.033 -0.040 -0.073
CPI Consumer Price Index 0.012 -0.017 -0.005
ExportPI Export Price Index -0.097 -0.016 -0.113
434 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
Column (3), the total effect, shows that all local sectors (except government services)
grow but trade-exposed sectors (except TCF) shrink. The effect of the subsidy dominates
the effect of the government cut except for government services.
5.6. Conclusion
In the long-run closure, the unfunded subsidy causes JaTeng TCF to become more
1 Penulis adaIah Mahasiswa Peraih Beasiswa Penelitian Ekonomi dan Moneter Kerja Sama Bank Indonesia dan FakultasEkonomi Universitas Negeri Sebelas Maret Surakarta
438 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
I. PENDAHULUAN
Deputi Senior Gubernur Bank Indonesia (BI) Anwar Nasution mengatakan Bank
Indonesia mengimbau kepada perbankan untuk menurunkan suku bunga pinjamannya
berkaitan dengan terus turunnya Sertifikat Bank Indonesia (SBI). Secara teori bahwa tingkat
suku bunga pinjaman merupakan gabungan dari jumlah cost of fund ditambah biaya
intermediasi dan biaya resiko macet (Solopos, Jum’at 27 Juni 2003).
Akhir-akhir ini banyak tuntutan dari para pelaku bisnis (pengusaha) dan juga pakar
ekonomi yang menuntut agar Bank Indonesia selaku penguasa moneter mempengaruhi
suku bunga deposito dan juga suku bunga pinjaman berkaitan dengan turunnya SBI agar
dapat meningkatkan / mengembangkan kembali sektor riil lewat kegiatan investasinya. Tetapi
tuntutan itu belum atau baru sedikit dipenuhi oleh Bank Indonesia, karena mungkin Bank
Indonesia melihat banyak faktor yang perlu dipertimbangkan untuk mempengaruhi suku
bunga khususnya suku bunga pinjaman dalam arti nominal.
Banyak negara berkembang telah melaksanakan deregulasi keuangannya dengan
cara menghapuskan pagu kredit dan tingkat bunga, misalnya Korea, Malaysia, Sri langka,
Filipina, dan Indonesia. Tujuan utama deregulasi keuangan ini seperti deregulasi ekonomi
pada umumnya adalah mendorong efisiensi dan pertumbuhan ekonomi. Salah satu tujuan
deregulasi adalah mempercepat proses berlangsungnya pendalaman finansial. Pendalaman
finansial (financial deep) menunjukkan seberapa jauh sistem finansial terutama sektor
perbankan dapat menjangkau masyarakat penabung dan mengalokasikan dana tersebut
kepada sektor usaha dan pengguna dana yang paling produktif dan efisien.
Sektor keuangan mempunyai peranan yang penting, bukan hanya sebagai perantara
finansial tetapi juga sebagai pihak yang membatasi, menilai dan mendistribusikan resiko
yang berkaitan dengan berbagai kegiatan finansial. Pada mekanisme pasar, peranan ini
memungkinkan terjadinya keseimbangan antara keuntungan yang diperoleh dengan resiko
yang dihadapi. Pendalaman finansial menjamin terjadinya biaya transaksi yang makin rendah,
distribusi resiko yang semakin optimal, alokasi dana yang semakin terarah pada pilihan
investasi yang terbaik. Dengan demikian pendalaman finansial mendorong peningkatan
efisiensi ekonomi dan berjalan seiring dengan perkembangan ekonomi.
Di beberapa negara ASEAN seperti Malaysia, Singapura, Thailand, Filipina, dan
Indonesia, perkembangan pendalaman finansial kelihatan menonjol setelah negara-negara
tersebut melakukan deregulasi sistem finansialnya. Sebelum adanya deregulasi, sistem
finansial negara-negara tersebut ditandai oleh banyaknya peraturan yang kurang mendorong
terjadinya pendalaman finansial seperti penentuan tingkat bunga oleh otoritas moneter,
439Determinan Tingkat Suku Bunga Pinjaman di Indonesia Tahun 1983 - 2002
penetapan pagu kredit, cadangan wajib minimum yang tinggi. Tingkat bunga yang ditetapkan
akan cenderung jauh di bawah tingkat bunga keseimbangan dan tingkat inflasi. Dengan
demikian, laju inflasi jauh lebih besar daripada tingkat bunga nominal sehingga tingkat bunga
rill menjadi negatif. Hal ini dapat menimbulkan distorsi dalam sistem keuangan karena
kurangnya mobilisasi dana. Sistem ini juga mengganggu efisiensi pembangunan sistem
perbankan. Bank-bank sangat tergantung pada dana dari Bank Indonesia dan tidak dapat
mengatur dananya secara efisien.
Tingginya suku bunga pada September 1988 menjadi sejarah tersendiri. Dimulai
dengan pernyataan Prof Mohammad Sadli, kemudian Gubemur BI Adrianus Mooy, tentang
perlunya perbankan menekan lagi tingkat suku bunga yang dinilai sangat tinggi dan tidak
mampu menggairahkan investasi. Penyebab utamanya tingginya suku bunga bank pada
waktu itu adalah mahalnya biaya memperoleh dana sendiri.Sebagian besar dana bank
diperoleh dari deposito dengan tingkat bunga berada diatas 15 - 21 %, baik untuk jangka
waktu 1 bulan, 3 bulan, 6 bulan, maupun 12 bulan. Melihat bunga deposito yang demikian
tinggi, wajar jika bunga kredit pun sangat tinggi karena biaya intermediasi dari bank. Biaya
tersebut antara lain biaya overheat, biaya resiko, dan marjin laba yang jumlahnya masih
sekitar 4 %, berarti besar bunga kredit pada waktu itu diperkirakan antara 19,5 % sampai
25 % (Sasongko Tedjo, 1994 : 110).
Pengalaman buruk dibidang moneter terulang lagi bahkan lebih buruk, yaitu
saat krisis ekonomi dan moneter menimpa bangsa-bangsa Asia termasuk Indonesia
pada tahun 1997 - 1998. Pada periode bulan Juli - Agustus 1997 pemerintah
menerapkan kebijakan empat kali menaikkan tingkat suku bunga SBI dari bulan Agustus
sebesar 7 % menjadi 30 % dalam setahun. Pergerakan suku bunga SBI menjadi tolok
ukur bagi tingkat suku bunga lainnya. Sehingga kenaikan suku bunga SBI ini dengan
sendirinya mendorong kenaikan suku bunga dana antar bank dan suku bunga deposito.
Kenaikan suku bunga deposito akhimya mengakibatkan kenaikan suku bunga pinjaman
di bank-bank, terutama karena sebelumnya sudah ada peraturan bahwa tingkat suku
bunga di bank komersial ditetapkan 150 % diatas suku bunga SBI. Suku bunga
perbankan untuk deposito dan pinjaman (kredit) di Indonesia adalah tertinggi di
kawasan ASEAN bahkan seluruh dunia (Tulus T.H. Tambunan: 1998: 114).
Beberapa literatur peneIitian tentang tingkat suku bunga seperti tingkat bunga dan
dari regresi ECM tingkat suku bunga pinjaman ditunjukkan oleh besamya koefisien pada
variabel-variabel jangka pendek di atas sedangkan koefisien regresi jangka panjang dengan
simulasi dari regresi ECM tingkat suku bunga pinjaman diperoleh dari :
Konstanta : β0/β
12 = 0,477521/0,394 717 = 1,2098
DSIBOR : (β1 + β
12) /β
12 = ( 0,152662 + 0,394717)/0,394717 = 1,3868
DJUB : (β2 + β
12) /β
12 = ( 4,768627 + 0,394717)/0,394717 = 13,0811
Dinflasi : (β3 + β
12)/ β
12 = (-0,472520 + 0,394717)/0,394717 = -2,1971
DSBI : (β4 + β
12)/ β
12 = ( 0,278416 + 0,394717)/0,394717 = 1,7054
DPDB : (β5 + β
12)/ β
12 = (-0,088556 + 0,394717)/0,394717 = 0,7756
450 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
SIBOR( -1), inflasi (-1), SBI( -1), JUB( -1), dan PDB( -1) merupakan variabel yang
menunjukkan parameter dalam jangka pendek. Sedangkan koefisien-koefisiennya
menunjukkan besarnya pengaruh yang dilakukan pada penyesuaian variabel dependen
terhadap perubahan variabel independen dalam jangka pendek. Misalnya DSIBOR( -1)
yang memiliki koefisien sebesar 0,152652 ini berarti bahwa akan kenaikan tingkat suku
bunga pinjaman sebesar 0,152652% jika terjadi kenaikan pada suku bunga internasional
SIBOR sebesar 1%. Variabel DSIBOR, DJUB, Dinflasi, DSBl, dan DPDB merupakan variabel
yang menunjukkan parameter jangka panjang. Hal ini berarti jika ECT-nya signifikan pada
tingkat signifikansi 5% maka ada hubungan antara ECM dan uji kointegrasi, sehingga
koefisien regresi variabel jangka panjang merupakan besarnya kekuatan pengaruh variabel
dependen oleh perubahan pada variabel independen dalam jangka panjang dan merupakan
koefisien asli. Karena pengaruh jangka panjang juga bisa dilihat pada koefisien kointegrasi
jika ECT signifikan, maka besamya koefisien regresi variabel jangka panjang pada ECM
dengan kointegrasi menunjukkan parameter yang hampir sama.
IV.5. Uji Statistik dan Ekonometrik
Uji F ini digunakan untuk menguji variabel independen secara keseluruhan dan
bersama-sama, untuk melihat apakah variabel independen secara keseluruhan
mempengaruhi variabel dependen secara signifikan. Kriteria pengujian nilai F adalah jika
F hitung > F tabel dengan taraf keyakinan 95% maka Ho ditolak yang berarti bahwa ada
pengaruh secara serempak atau secara bersama-sama dari keseluruhan variabel
independen terhadap variabel dependen. Sebaliknya jika F hitung < F tabel maka Ho diterima
yang berarti bahwa tidak ada pengaruh secara serempak atau secara bersama-sama dari
keseluruhan variabel independen terhadap variabel dependen. Nilai Fhitung
adalah 7,615138
dengan probabilitas sebesar 0,006397. Sedangkan nilai Ftabel
dengan tingkat signifikansi < 5%
20 - 13 = 7 ; 12 adalah 4,46. Karena Fhitung
> Ftabel
, maka Ho ditolak dan Ha diterima. Hal ini
berarti secara bersama-sama faktor jangka pendek dan jangka panjang tingkat bunga
internasional SIBOR, jumlah uang beredar, inflasi, Sertifikat Bank Indonesia, dan Produk
Domestik Bruto mempunyai pengaruh yang signifikan / nyata terhadap tingkat suku bunga
pada derajat signifikansi < 5%.
Uji determinasi untuk mengetahui berapa persen perubahan variasi variabel
independen dapat menjelaskan oleh perubahan variasi variabel dependen. Berdasarkan
hasil etimasi menunjukkan bahwa nilai R2 adalah sebesar 0,922879 yang berarti 92,2879%
faktor jangka pendek dan jangka panjang tingkat bunga internasional SIBOR, jumlah uang
beredar, inflasi, Sertifikat Bank Indonesia dan Produk Domestik Bruto dapat menjelaskan
451Determinan Tingkat Suku Bunga Pinjaman di Indonesia Tahun 1983 - 2002
variasi perubahan tingkat suku bunga pinjaman sedangkan sisanya 7,7121 % dipengaruhi
diluar model.
Uji multikolinieritas digunakan metode Klein yang dikemukakan oleh L.R. Klein. Metode
ini membandingkan lower case (korelasi antar masing-masing variabel independen). Jika
R2y Xi,X
j,... X
n > r2X
i,X
j maka tidak terjadi masalah multikolinieritas. Hasil uji Klein untuk
mendeteksi masalah multikolinieritas menunjukkan bahwa untuk semua korelasi antar
variabel bebas memiliki r2 yang lebih kecil dari R2 (r2 < R2). Hal ini memberi kesimpulan
bahwa semua variabel bebas daIam spesifikasi model yang digunakan terlepas dari masalah
multikolinieritas.
Heteroskedastisitas terjadi jika gangguan muncul dalam fungsi regresi yang
mempunyai varian yang tidak sarna, sehingga penaksir OLS tidak efisien baik daIam
sampel kecil maupun sampel besar. Untuk mendeteksi ada atau tidaknya masalah
Heteroskedastisitas adalah dengan menggunakan Uji Glejser. Adapun tahap-tahap daIam
Uji Glejser yaitu :
(1) Lakukan regresi terhadap model yang digunakan
(2) Setelah mendapatkan nilai residual ei dan regresi OLS, selanjutnya regresikan nilai
absolut ei, , terhadap variabel X yang diduga mempunyai hubungan erat dengan
σi2
Model = β0 + βi Xi + Ui
dimana :
= Nilai absolut residual.
Xi = Variabel penjelas.
Ui = Variabel penggangu.
Hipotesis yang digunakan :
Ho : βi = 0 (Tidak Ada Masalah Heteroskedastisitas)
Ha : βi 0 (Ada Masalah Heteroskedastisitas)
Apabila thitung
> ttabel
, maka Ho ditolak dan Ha diterima, berarti ada masalah
heteroskedastisitas. Sedangkan jika thitung
< ttabel
, maka Ho diterima dan Ha ditolak berarti
tidak ada masalah heteroskedastisitas / homokedastisitas (Gujarati, 1991: 177). Untuk
lebih jelasnya dapat dilihat pada Tabel 4.7 sebagai berikut :
ei
ei
ei
=
452 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
Tabel 4.7.Hasil Pengujian Heteroskedastisitas
SIBOR (-1) 0,633720 2,228 Tidak terjadi heteroskedastisitasLn-JUB (-1) 0,25247 2,228 Tidak terjadi heteroskedastisitasinflasi(-1) 2,095225 2,228 Tidak terjadi heteroskedastisitasSBI (-1) 0,868729 2,228 Tidak terjadi heteroskedastisitasPDB (-1) 0,771346 2,228 Tidak terjadi heteroskedastisitasDSIBOR -1,620586 2,228 Tidak terjadi heteroskedastisitasDLn-JUB -0,029791 2,228 Tidak terjadi heteroskedastisitasDinflasi 1,556347 2,228 Tidak terjadi heteroskedastisitasDSBI -2,030783 2,228 Tidak terjadi heteroskedastisitasDPDB -1,500736 2,228 Tidak terjadi heteroskedastisitas
Variabel t hitung t tabel Keterangan
Sumber : Hasil Print Out Komputer, 2003 (Lampiran hal. 20)
Berdasarkan Tabel 4.7. di atas menunjukkan bahwa semua variabel mempunyai
distribusi t hitung < t tabel, ini berarti bahwa Ho diterima Ha ditolak sehingga dapat disimpulkan
bahwa model yang dipakai terhindar dari masalah heteroskedastisitas pada tingkat keyakinan
95% (α = 5%).
Autokorelasi untuk model dinamis, seperti ECM percobaan d tidak bisa digunakan
untuk menguji ada tidaknya autokorelasi, karena DW statistik secara asimtotik akan biasa
mendekati nilai 2 (Sritua Arief, 1993 : 15). Oleh karena alasan tersebut maka digunakan
langrange Multiplier Test, yakni berupa regresi atas semua variabel bebas dalam persamaan
regresi ECM tersebut dan variabel lag t dari nilai residual regresi ECM. Adapun hasil
persamaan regresi ECM dapat dituliskan sebagai berikut :
Residi = bo + b
1 DSIB
t + b
2 DJUB
t + b
3 DINF
t + b
4 DSBI
t + b
5 DPDB
t + b
6 SIB
t-1 + b
7 JUB
t-1 +
b8 INF
t-1 + b
9 SBl
t-1 + b
10 PDB
t-1 + b
11 ECT + b
12 Resid
t-1
Dari model tersebut akan didapat nilai R2, kemudian nilai ini dimasukkan dalarn rumus
sebagai berikut : (n- 1 )R2, dimana n adalah jumlah observasi, kemudian dilakukan pengujian
dengan hipotesa sebagai berikut :
Ho : ρ=0 berarti tidak ada masalah autokorelasi
Ho : ρ 0 berarti ada masalah autokorelasi
Selanjutnya nilai (n-1)R2 diperbandingkan dengan X2 (0,05). Dimana X2 (0,05) adalah
nilai kritis Chi Square yang ada dalam tabel statistik Chi Square. Jika (n-1)R2 lebih besar
dari X2, maka terdapat masalah autokorelasi, dan jika sebaliknya maka tidak terjadi masalah
autokorelasi.
=
453Determinan Tingkat Suku Bunga Pinjaman di Indonesia Tahun 1983 - 2002
Hasil perhitungan Lagrange Multiplier Test dari persamaan tersebut dengan prograrn
E-Views ditunjukkan oleh TabeI 4.8, sebagai berikut :
Tabel 4.8.Hasil Lagrange Multiplier Test Autokorelasi
Syamsudin Mahmud, 1985. Ekonomi Moneter Indonesia, Edisi Pertama. Jakarta:
Yayasan Kesejahteraan Umat.
Tulus T.H. Tambunan, 1998. Penyebab Krisis Moneter di Indonesia, Jakarta : lKADIN
Indonesia.
Umar Juoro, 1995. Pengaruh Pinjaman Luar Negeri dan PMA Terhadap
Pertumbuhan Ekonomi Indonesia. Makalah Seri Dialog Politik Dalam Negeri ke -10,
Jakarta : CIDES.
Y. Sri Susilo, dkk, 2000. Bank dan Lembaga Keuangan Non Bank, Jakarta: UI press
461Perbandingan Early Warning System (EWS) untuk Memprediksi Kebangkrutan Bank Umum di Indonesia
PERBANDINGAN EARLY WARNING SYSTEMS (EWS) UNTUKMEMPREDIKSI KEBANGKRUTAN BANK UMUM DI INDONESIA1
Liza Angelina, SE, Msi, Akt
1 Terima kasih kepada Bank Indonesia yang telah memberikan bantuan dana dalam penelitian ini. Terima kasih pula kepada Prof. James Kolari dari Texas A&M University yang telah bersedia memberikan program TR
yang dibutuhkan penulis dalam penelitian ini
A b s t r a k s i
This research is testing the capability of several forewarning system models to predict bank
bankruptcy. We apply these models on Indonesian commercial bank data during the period of 1994/
1995 - 1999/2000. Considering the data incompleteness and or their inexistence, our data finally
contains of 74 failed-banks and 81 non failed-banks.
Our result shows the Trait Recognition model (TR) is more pre-eminent than Logit and Multiple
Keterangan :FCC : Jumlah bank yang gagal yang diklasifikasikan secara tepatPF : Jumlah bank yang diprediksikan akan gagalAF : Jumlah bank yang benar-benar gagalCC : Prosentase dari bank yang diklasifikasikan secara tepatWE : Efisiensi yang dibobot
Tabel 4. Weighted Efficiency Scores (Pengukuran Efisiensi Yang Dibobot)Dengan Model Logit, Multiple Discriminant Analysis Dan Trait Recognition
FCC PF AF CC WE
V. PENUTUPV.1 Kesimpulan
Dari tabel tersebut di atas dan dari perhitungan-perhitungan dengan menggunakan
masing-masing model dapat diketahui bahwa model TR memiliki akurasi prediksi yang
paling tinggi. Selain itu, model TR tidak hanya dapat digunakan untuk memprediksi
tingkat kegagalan bank, tapi juga dapat mengetahui dengan tepat bank-bank mana saja
yang akan mengalami kegagalan. Hal ini tidak bisa dilakukan dengan model logit maupun
MDA. Ini membuktikan bahwa hipotesis dalam penelitian ini, yang berbunyi EWS dengan
model TR memiliki ketepatan peramalan yang lebih baik dari model MDA dan model
logit, benar-benar terbukti; yang artinya, penelitian ini konsisten dengan penelitian yang
dilakukan oleh peneliti terdahulu.
481Perbandingan Early Warning System (EWS) untuk Memprediksi Kebangkrutan Bank Umum di Indonesia
V.2 Implikasi
Hasil penelitian ini dapat dijadikan bahan pertimbangan bagi penelitian-penelitian di
bidang keuangan yang menggunakan model ekonofisika dan mendorong arah riset di bidang
keuangan untuk menggunakan model-model ekonofisika. Sedangkan bagi dunia perbankan,
khususnya Bank Indonesia sebagai bank sentral di Indonesia, hasil penelitian ini dapat
menjadi bahan masukan dan acuan untuk memprediksi kebangkrutan bank, khususnya
dengan menggunakan model TR.
V.3 Saran
Untuk penelitian-penelitian yang akan datang, peneliti dapat mempertimbangkan
penggunaan holdout sample dalam melakukan perhitungan, karena kemungkinan dengan
digunakannya holdout sample dalam perhitungan, dapat lebih memperkuat perhitungan
yang dilakukan dan prediksi yang dihasilkan. Selain itu, untuk penelitian-penelitian yang
akan datang, peneliti diharapkan dapat menciptakan suatu program dengan bahasa
pemrograman yang lebih user friendly, sehingga lebih mudah digunakan. Peneliti dapat
juga membandingkan model TR ini dengan model prediksi kebangkrutan bank lainnya,
yang belum pernah dilakukan di Indonesia.
V.4 Keterbatasan
Selain keunggulan-keunggulan yang dimiliki oleh model TR, model TR yang dibuat
dalam penelitian ini memiliki kelemahan dalam hal program yang digunakan untuk
melakukan perhitungan, dimana program yang dibuat ini menggunakan bahasa Fortran
yang tidak terlalu lazim digunakan, sehingga tidak user friendly. Namun permbuatan
program dengan menggunakan bahasa Fortran ini memiliki alasan, karena bahasa ini
merupakan bahasa pemrograman tingkat tinggi yang sangat rinci, sehingga keakuratan
perhitungannya sangat tinggi.
482 Buletin Ekonomi Moneter dan Perbankan, Desember 2004
DAFTAR PUSTAKA
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in California and Nevada”, Geological Society of America Bulletin, Vol. 88
Coats, P.K. and L.F. Fant, 1993, Recognizing Financial Distress Patterns Using a