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ABSTRAKPenelitian ini bertujuan untuk memprediksi kemungkinan terjadinya fiscal distress
kabupaten/kota di Indonesia Tahun 2010-2013 dengan memodifikasi variabel
Trussel dan Patrick (2009) dalam memprediksi fiscal distress.Penelitian ini
merupakan penelitian kuantitatif dengan menggunakan metode regresi logistik
biner dengan jumlah sampel sebanyak 1.820 kabupaten/kota-tahun.Hasil
penelitian menunjukkan adanya indikasi fiscal distress di beberapa
kabupaten/kota di Indonesia utamanya di tahun 2010. Lebih lanjut penelitian
membuktikan bahwa terdapat lima variabel yang signifikan dalam memprediksi
kemungkinan terjadinya fiscal distress, yaitu Pendapatan Asli Daerah sebagai
persentase pendapatan dengan korelasi positif, dana perimbangan sebagai
persentase dari pendapatan dengan korelasi positif, belanja modal sebagai
persentase dari pendapatan dengan korelasi positif dan pertumbuhan pendapatan
dengan korelasi negatif serta variabel dummy kabupaten dengan korelasi negatif.
ABSTRACTThis study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.;This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation., This study aims to predict the likelihood of fiscal distress in districts/cities in
Indonesia in 2010-2013 by modifying Trussel and Patrick (2009) variables in
predicting fiscal distress. This research is a quantitative study using binary logistic
regression method with a total sample of 1.820 districts/cities-years. The results
show indications of fiscal distress in some districts/cities in Indonesia especially
in 2010. Furthermore, the study shows that there are five significant variables in
predicting the likelihood of fiscal distress, namely local own-revenue as a
percentage of revenue with a positive correlation, intergovernmental funds as a
percentage of revenue with a positive correlation, capital expenditures as a
percentage of revenue with a positive correlation and revenue growth with a
negative correlation and dummy variabel district with a negative correlation.]
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