scholarly journals PENGARUH GUNCANGAN OUTPUT GAP DAN INFLASI TERHADAP SUKU BUNGA SEBAGAI SASARAN OPERASIONAL KEBIJAKAN MONETER DI INDONESIA

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Utami Baroroh
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Error Correction ◽  
Time Series Data ◽  
Series Data ◽  
Output Gap ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error

The objectives of this study are to observe interest rate response because shock/innovation of inflation and output gap. The data sample used in this study are quarterly time series data from 1983.1 – 2008.4. Those data are SBI interest rate, inflation (CPI) and output gap. A method of analysis in this study is Vector Error Correction Model (VECM). The empirical results of impulse response show that the effect of inflation and output gap shock to interest rate is positifDOI: 10.15408/sjie.v1i2.2601

scholarly journals Vector error correction model to analyze energy uses, environmental quality and economic growth during Covid-19 Pandemic

2021 ◽  
Vol 926 (1) ◽  
pp. 012066
Author(s):  
I Fahria ◽  
I Sulistiana
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Environmental Quality ◽  
Time Series Data ◽  
Series Data ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Cointegration Relationship

Abstract Time series data commonly show are interconnected behaviour and non-stationer interrelated variables, so a model that able to obtain a good forecasting result from a non-stationary multivariate variables time series data are needed. Vector Error Correction Model (VECM) is one of multivariate time series model which is a vector form of Vector Autoregressive Boundary (VAR) for non-stationary time series data and has a cointegration relationship. The purpose of this study is to identify the VECM model in analyzing the relationship between energy use, environmental quality (CO2), and economic growth (GDP) during the Covid-19 pandemic that plagued Indonesia. The results of this study explained energy uses and and environmental quality (CO2) and economic growth (GDP) are interrelated and have a long-term cointegration relationship due to the influence of the Covid-19 pandemic.

scholarly journals Relationship between Trade Openness and Inflation: Empirical Evidences from Pakistan (1976-2010).

2011 ◽  
Vol 50 (4II) ◽  
pp. 853-876 ◽  
Author(s):  
Sehar Munir ◽  
Adiqa Kausar Kiani
Keyword(s):  
Error Correction ◽  
Trade Openness ◽  
Value Added ◽  
Error Correction Model ◽  
Series Data ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Unit Root Testing ◽  
Vector Error

This study empirically verifies the existence of significant relationship between inflation and trade openness for Pakistan using annual time-series data for the period of 1976 to 2010. The basic objective of this study is to examine the Romer‘s hypothesis for Pakistan with real agriculture value added, real exchange rate, real gross domestic product, financial market openness, money and quasi money and used trade openness, import openness and export openness ratios separately as explanatory variables with inflation rate as dependent variables. For this purpose, we have used multivariate Johansen (1998) and Johansen and Juselius (1990) Maximum Likelihood Cointegration Approach and a Vector Error Correction Model (VECM) and the expected empirical findings shows that there is a significant positive long-run relationship between inflation and trade openness, which rejects the existence of Romer‘s hypothesis for Pakistan. JEL classification: B26, E31, P24, P44 Keywords: Trade Openness, Inflation, Unit Root Testing, Multivariate Cointegration Approach, Vector Error Correction Model, Pakistan

Does Fiscal Deficit Affect Interest Rate in India? An Empirical Investigation

2016 ◽  
Vol 5 (2) ◽  
pp. 87-103 ◽  
Author(s):  
Ritu Rani ◽  
Naresh Kumar
Keyword(s):  
Interest Rate ◽  
Error Correction ◽  
Money Supply ◽  
Real Interest Rate ◽  
Vector Error Correction Model ◽  
Fiscal Deficit ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run

Fiscal deficit above a certain limit is not good for the country because high government borrowings raise the interest rate and crowd out private investment. This article is an attempt to analyze the impact of fiscal deficit on real interest rate in India over the time period of 1980–1981 to 2013–2014. Autoregressive distributed lags bound testing approach for cointegration and vector error correction model for Granger casualty are used in a multivariate framework in which money supply and inflation are included as additional variables. Bound test results confirm the long-run equilibrium relationship among the competing variables. Further, the rate of interest and fiscal deficit are positively related with each other in long run, whereas money supply and inflation are found to be negative and statistical significant. In addition, results of vector error correction model showed that there is unidirectional causality running from inflation to real interest rate in short run. Based on the findings, it is suggested that that proper fiscal consolidation is required to control high fiscal deficit and burgeoning interest rate in India. Further, government should move from market borrowing to tax revenue to offset fiscal deficit.

MODEL PERMINTAAN UANG DI INDONESIA DENGAN PENDEKATAN VECTOR ERROR CORRECTION MODEL

2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Imam Mukhlis
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Error Correction ◽  
Error Correction Model ◽  
Vector Error Correction Model ◽  
Demand For Money ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run

This research aims to estimate the demand for money model in Indonesia for 2005.22015.12. The variables used in this research are demand for money, interest rate, inflation, and exchange rate (IDR/US$). The stationary test with ADF used to test unit root in the data. Cointegration test applied to estimate the long run relationship between variables. This research employed the Vector Error Correction Model (VECM) to estimate the money demand model in Indonesia. The results showed that all the data was stationer at the difference level (1%). There were long run relationship between interest rate, inflation and exchange rate to demand for money in Indonesia. The VECM model could not explain interaction between explanatory variables to independent variables. In the short run, there were not relationship between interest rate, inflation and exchange rate to demand for money in Indonesia for 2005.2-2015.12.

scholarly journals Causality analysis between exports, imports and economic growth of Pakistan

2017 ◽  
Vol 1 (1) ◽  
pp. 45-52
Author(s):  
Syyeda Farhana Shah ◽  
Saleem Khan ◽  
Abdur Rauf
Keyword(s):  
Time Series Data ◽  
Causal Relation ◽  
Series Data ◽  
Vector Error Correction Model ◽  
Causality Analysis ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run ◽  
Adf Test

The objective of study is to identify causal relationships among the variables such as exports, imports and Gross Domestic Product (GDP) in case of Pakistan. The study uses time series data for the period from 1981-2016. Stationarity is checked with the Augmented Dickey Fullers' (ADF) test, and the Engle Grange approach is utilized to determine the long run relationship among variables of the study. Moreover, causality among the selected variables is tested by using the Vector Error Correction Model (VECM). We found that the causality runs from GDP to imports and exports. Furthermore, no causal relation is found from exports to GDP and from imports to GDP, but the causality goes from GDP to these two variables. The causality from GDP to exports and imports are positive and significant. Finally, the results indicate that the causal relationship between GDP and imports is stronger than the GDP and exports.

scholarly journals Empirical evidence on Non-Performing Loans and credit frictions: banking sector in Tunisia

2020 ◽  
Vol 2 (3) ◽  
pp. 171-183
Author(s):  
Salha Ben Salem ◽  
◽  
Moez Labidi ◽  
Nadia Mansour ◽  
◽  
...  
Keyword(s):  
Interest Rate ◽  
Error Correction ◽  
Money Supply ◽  
Banking Sector ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Market Interest Rate ◽  
Credit Frictions

Purpose: This paper explores the most important determinants of friction in the Tunisian credit market. The previous literature argued that friction is largely explained by the increase in Non-Performing Loans Nkusu, 2011; Abadi et al. 2014; Rulyasri et al.2017, Roland et all, 2013. Research methodology: We constructed a multivariate Vector Error Correction Model, with five macroeconomic variables (industrial production index, the money supply, money market interest rate) to examine the impact of Non-Performing Loans increase in amplifying the Tunisian credit frictions. Results: The Vector Error Correction Model (VECM) regression results show a negative and important relationship between economic growth and Non-Performing Loans (NPL) ratio, which is very robust during the political crisis of 2011. The money market interest rate and the money supply are positively related to the Non-Performing loan ratio. Limitation: This study was only focused on Tunisian banking sector as one of the pillars of the Tunisian economy. Contributions: This highlights that the nature of the monetary policy adopted by the monetary authority of Tunisia plays a significant role in the fluctuation of the Non-Performing Loans ratio. Bank capitalization is positively and statistically significant with Non-Performing Loan ratio, implying that banks with a low level of capital are more likely to have a riskier credit portfolio that causes the increase of Non-Performing Loans in their balance sheet.

Analisis Kekakuan dan Faktor-faktor yang Memengaruhi Tingkat Suku Bunga Perbankan di Indonesia

2013 ◽  
Vol 8 (2) ◽  
pp. 26
Author(s):  
Eko Listiyanto ◽  
Telisa Aulia Falianty
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Interest Rates ◽  
Error Correction ◽  
Time Series Data ◽  
Error Correction Model ◽  
Least Square ◽  
Capital Adequacy ◽  
Series Data ◽  
Correction Model

<p align="center"><em>ABSTRACT</em></p><p><em>The research discusses the rigidity of interest rates on deposits and loans to changes in interest rate policies in the three groups of banks in Indonesia, and the factors that influence the interest rates on deposits and loans in the banking system. Rigidity of bank interest rates were analyzed with error correction model approach (Error Correction Model / ECM) using panel data. While the factors that influence the development of the banking interest rates were analyzed with multiple linear regression approach method of Generalized Least Square (GLS) using time series data. The period of data used from July 2005-March 2010.</em></p><p><em>Error Correction Model shows the slackness of interest rates response on deposits and loans toward the policy of interest rate. The rigidity of interest rates on deposits and loans in Indonesia is relatively slow when compared to some other countries.</em></p><p><em>Regression results with GLS method proves that the banking efficiency factor, bad credit and market share significantly influence the interest rates on deposits. While the borrowing rate is influenced by the rate of inflation, capital adequacy ratio, as well as bad credit. The results of this study suggest the importance of watching bad credit factors in making monetary policy because it can affect the interest rates on deposits and lending interest rates.  </em></p><p>ABSTRAK</p><p>Penelitian ini membahas kekakuan suku bunga deposito dan pinjaman untuk perubahan kebijakan suku bunga dalam tiga kelompok bank di Indonesia, dan faktor-faktor yang mempengaruhi suku bunga deposito dan pinjaman dalam sistem perbankan. Kekakuan suku bunga perbankan dianalisis dengan pendekatan error correction model (Error Correction Model / ECM) menggunakan data panel. Sedangkan faktor-faktor yang mempengaruhi perkembangan suku bunga perbankan dianalisis dengan metode pendekatan regresi linier berganda dari Generalized Least Square (GLS) dengan menggunakan data time series. Periode data yang digunakan dari Juli 2005-Maret 2010.</p><p>Error Correction Model menunjukkan kelambanan dari suku bunga respon deposito dan pinjaman terhadap kebijakan tingkat suku bunga. Kekakuan suku bunga deposito dan pinjaman di Indonesia relatif lambat jika dibandingkan dengan beberapa negara lain.</p><p>Hasil regresi dengan metode GLS membuktikan bahwa faktor efisiensi perbankan, kredit macet dan pangsa pasar secara signifikan mempengaruhi suku bunga deposito. Sementara tingkat pinjaman dipengaruhi oleh tingkat inflasi, rasio kecukupan modal, serta kredit macet. Hasil penelitian ini menunjukkan pentingnya menonton faktor kredit macet dalam membuat kebijakan moneter karena dapat mempengaruhi suku bunga deposito dan suku bunga kredit.</p>

scholarly journals Estimation of peach supply response in Colombia using a Vector Error Correction Model

ENTRAMADO ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 250-260
Author(s):  
Susan Elsa  Cancino ◽  
Giovanni Orlando Cancino-Escalante
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Time Series Data ◽  
Series Data ◽  
Correction Coefficient ◽  
Vector Error Correction ◽  
Supply Response ◽  
Vector Error ◽  
Long Run ◽  
Augmented Dickey Fuller

An empirical study of peach supply response to own-price and yield in Colombia using time series data from 2000 to 2018 was undertaken. A quantitative, correlational and non-experimental research design was selected and the Johansen´s co-integration as well as the vector error correction framework were employed. The Augmented Dickey-Fuller test showed that the time series were integrated of order one and the Johansen´s co-integration confirmed the existence of a long-term relationship between the variables. Moreover, the short and long run coefficients for own-price and yield were statistically significant and presented the expected signs, however, estimated own-price elasticity was below unit suggesting it is not an important factor in peach supply response. Furthermore, the vector error correction coefficient (-0.32) was negative and in line with theory, which showed that in the long-run, the model converges towards equilibrium, however at a relatively slow pace. Therefore, it can be concluded that, overall, the proposed model contributes to the understanding of the dynamics in peach output supply.

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