scholarly journals ANALISIS PEMBIAYAAN DAN KREDIT SEKTOR KONSTRUKSI DI INDONESIA: STUDI PERBANKAN SYARIAH DAN KONVENSIONAL

2018 ◽  
Vol 6 (1) ◽  
pp. 21-40
Author(s):  
Nidaa Nazaahah Kusumawati ◽  
Nunung Nuryartono ◽  
Irfan Syauqi Beik

The construction sector is an important sector in supporting development projects in Indonesia. The development of the construction sector requires the role of the banking sector to provide access of capital through credit or financing. This study aims to analyze the factors affecting construction financing and credit in Islamic and Conventional Banking in Indonesia and among regions in Indonesia. This study uses Vector Autoregression/ Vector Error Correction Model (VAR/VECM) with monthly data from 2006 until 2014 and panel data analysis with yearly data from 2009 until 2013. The study results that the factors affecting financing and credit on Construction Sector in Indonesia are Third Party Funds (DPK), Wholesale price index, fee of SBIS (interest rate of SBI), percentage of Non Performing Financing (Non Performing Loan), Consumer Price Index and equivalent rate of financing (Interest rate of Credit). Furthermore, the factors affecting financing and credit on Construction Sector among regions in Indonesia are Third Party Funds, Gross Domestic Regional Product of Construction Sector, Gross Domestic Regional Product per Capita and percentage of Non Performing Financing (Non Perfoming Loan). Keywords: Construction, Credit, Financing, Panel data, VAR/VECM

2018 ◽  
Vol 6 (1) ◽  
pp. 21-40
Author(s):  
Nidaa Nazaahah Kusumawati ◽  
Nunung Nuryartono ◽  
Irfan Syauqi Beik

The construction sector is an important sector in supporting development projects in Indonesia. The development of the construction sector requires the role of the banking sector to provide access of capital through credit or financing. This study aims to analyze the factors affecting construction financing and credit in Islamic and Conventional Banking in Indonesia and among regions in Indonesia. This study uses Vector Autoregression/ Vector Error Correction Model (VAR/VECM) with monthly data from 2006 until 2014 and panel data analysis with yearly data from 2009 until 2013. The study results that the factors affecting financing and credit on Construction Sector in Indonesia are Third Party Funds (DPK), Wholesale price index, fee of SBIS (interest rate of SBI), percentage of Non Performing Financing (Non Performing Loan), Consumer Price Index and equivalent rate of financing (Interest rate of Credit). Furthermore, the factors affecting financing and credit on Construction Sector among regions in Indonesia are Third Party Funds, Gross Domestic Regional Product of Construction Sector, Gross Domestic Regional Product per Capita and percentage of Non Performing Financing (Non Perfoming Loan). Keywords: Construction, Credit, Financing, Panel data, VAR/VECM


2021 ◽  
pp. 121-128
Author(s):  
Ersan Özgür

With the implementation of free market economy in Turkey starting from 1980, restrictions on foreign capital flows began to be abolished. Within the scope of international expansion in financial aspects, steps for integration with global financial markets were taken, and regulations were made. Accordingly, the number of foreign banks in Turkish banking system have increased since 1980, and reached an important scale in the sector. The share of foreign deposit banks’ total assets in the entire banking sector is at 22,8% level as of 2019. In this study, panel data analysis was performed to identify the factors affecting the Turkish currency assets of foreign deposit banks. The 11-year data for the 2009-2019 period were utilized in the study. Turkish Currency Assets / Total Assets was determined as the dependent variable in the analysis. The factors affecting the Turkish currency assets of foreign deposit banks were identified as Turkish Currency Liability / Total Liability [TPYUK], Turkish Currency Deposits / Total Deposits [TPMEV], and Turkish Currency Loans / Total Loans [TPKREDI]. Based on the study results the model formed was significant, and the ratio of independent variables for explaining the dependent variable in the model was approximately 48%. The independent variables TPYUK and TPKREDI were revealed to have a statistically significant positive effect on the dependent variable at 5% significance level. A 1-unit raise in TPYUK increased the dependent variable by 0,436 unit, and a 1-unit raise in TPKREDI by 0,033 unit. No statistically significant effect of TPMEV as the other independent variable was identified on the dependent variable.


2020 ◽  
Vol 3 (1) ◽  
pp. 1-15
Author(s):  
Min Hou ◽  
Chunmei Gu ◽  
Jiakai Wang ◽  
Ping Hou

PurposeA large number of competitors springing up at the same time is a unique phenomenon to emerging markets. How to promote product sales and improve platform performance through appropriate advertising communication strategies is not only an actual problem for the P2P platforms that are committed to long-term and stable operations but also an academic problem in marketing.Design/methodology/approachThis study collected a total of 1960 pieces of panel data of the P2P platforms and constructed a panel data analysis model after filtering.FindingsThe empirical analysis reveals the following: the prevention-focus advertising has a greater impact on platform trading volume, compared with the promotion-focus advertising, and the impact is positively significant; the platform which has a third-party cooperation should use promotion-focus advertising, while prevention-focus advertising is a better choice for the platform without a third-party cooperation. Furthermore, the effects of prevention-focus advertising and promotion-focus advertising on the platforms using individual projects and platforms using organization projects differ.Originality/valueThe results of this study have some reference to the selection of advertising communication strategies for the high-risk financial products.


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Mohsen Bayati ◽  
Mehrnoosh Emadi

Abstract Objective Hospital deaths account for a large number of community deaths. Moreover, one of the main indicators of inpatient services quality is the hospital death. This study was performed to investigate the factors affecting hospital death rate in Iran using panel data analysis. Results The net death rates in teaching and not-teaching hospitals were 6.24 and 5.58 per 1000 patients, respectively. Models' estimates showed, in teaching hospitals the number of surgeries (P < 0.05) and special beds (P < 0.01) had a significant positive relationship with death rate. In non-teaching hospitals, outpatient admissions (P < 0.01), number of surgeries (P < 0.05), number of special beds (P < 0.01), and length of stay (P < 0.01) had a positive and the number of inpatient admissions (P < 0.05) and active beds (P < 0.01) had a negative relationship with death rate. Policy-making towards optimization of hospital service size and volume, standardization of length of stay, interventions to control nosocomial infections, and planning to control the complications of surgeries and anesthesia could effectively reduce hospital death rate.


2015 ◽  
Vol 15 (3) ◽  
pp. 51-56
Author(s):  
Juan Gaytan-Cortes ◽  
Gonzalo Maldonado-Guzman ◽  
Juan Bargas-Baraza

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