scholarly journals DETERMINANT OF GOVERNMENT BOND YIELDS

2020 ◽  
Vol 1 (1) ◽  
pp. 86-99
Author(s):  
Priyo Adiwibowo ◽  
Pardomuan Sihombing
Keyword(s):  
Forecast Error ◽  
Impulse Response Function ◽  
Oil Prices ◽  
Error Variance ◽  
Government Bond ◽  
Bond Yields ◽  
Determinant Factors ◽  
Bank Rate ◽  
Forecast Error Variance

This study aims to analyze the influence of determinant factors: (i) exchange rates, (ii) inflation, (iii) CDS spreads, (iv) bid-ask spreads, (v) overnight rate, (vi) CB’s rate (Central Bank Rate), and (vii) oil prices on Government bond yields. The data used are monthly data in the period 2012 - 2018. The research method used is the Vector Auto Regression (VAR) approach. Our analysis indicated that the determinant factors have impact on government bond yields. Based on the analysis of the impulse response function (IRF), the yield is to respond to any shocks given by the long term. While through forecast error variance decomposition (FEVD) analysis, found that CDS spreads and oil prices contributed significantly to the movement of Government bond yields.

scholarly journals Oil Prices and the U.S. Dollar Exchange Rate: Evidence from the Monetary Model

2018 ◽  
Vol 10 (4) ◽  
pp. 17
Author(s):  
Moayad H. Al Rasasi
Keyword(s):  
Exchange Rate ◽  
Forecast Error ◽  
Negative Relationship ◽  
Impulse Response Function ◽  
Decomposition Analysis ◽  
Oil Prices ◽  
Error Variance ◽  
Monetary Model ◽  
Forecast Error Variance ◽  
Positive Shock

This paper analyzes how changes in global oil prices affect the US dollar (USD) exchange rate based on the monetary model of exchange rate. We find evidence indicating a negative relationship between oil prices and the USD exchange rate against 12 currencies. Specifically, the analysis of the impulse response function shows that the depreciation rate of the USD exchange rate ranges between 0.002 and 0.018 percentage points as a result of a one-standard deviation positive shock to the real price of crude oil. In the same vein, the forecast error variance decomposition analysis reveals that variation in the USD exchange rate is largely attributable to changes in the price of oil rather than monetary fundamentals. In last, the out-of-sample forecast exercise indicates that oil prices enhance the predictability power of the monetary model of exchange rate.

scholarly journals KAJIAN AKTIVITAS EKONOMI LUAR NEGERI INDONESIA TERHADAP PERTUMBUHAN EKONOMI INDONESIA PERIODE 1998-2014

2017 ◽  
Vol 9 (2) ◽  
pp. 119
Author(s):  
Ryan Hawari ◽  
Fitri Kartiasih
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Exchange Rate ◽  
Direct Investment ◽  
Forecast Error ◽  
Foreign Debt ◽  
Trade Openness ◽  
Impulse Response Function ◽  
Error Variance ◽  
Forecast Error Variance

Indonesia is a developing country which adopts an “open economic”. That caused Indonesia economic is strongly influenced by factors that come from outside of Indonesia. External factors in this research is referred to foreign debt, foreign direct investment, trade openness and exchange rate of rupiah with USD. The analytical method in this research used Vector Error Correction Model (VECM) which will focused on Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD). Based on result of IRF, exchange rate had a positive effect to economic growth, while foreign debt, foreign direct investment and trade openness had a negative effect to economic growth. Based on result of FEVD, shock on economic growth in Indonesia affected by economic growth itself (43.21%), followed by foreign debt (26.30%), trade openness (14.16%), foreign direct investment (8.29%) and exchange rate (8.04%) Keywords: economic growth, trade openness, VECM, IRF, FEVD

scholarly journals Measuring monetary policy by money supply and interest rate: evidence from emerging economies

2021 ◽  
Vol 21 (3) ◽  
pp. 347-367
Author(s):  
Trung Thanh Bui ◽  
Kiss Dávid Gábor
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Money Supply ◽  
Emerging Economies ◽  
Forecast Error ◽  
Impulse Response Function ◽  
Error Variance ◽  
Limited Effect ◽  
Forecast Error Variance

Abstract Although measuring monetary policy is a contentious issue in the literature, much less evidence on this issue is available for emerging economies. This paper aims to investigate the role of interest rate and money supply in measuring monetary policy in twelve emerging economies that target inflation through the analysis of Granger causality, impulse response function, and forecast error variance decomposition. The empirical results show that both money supply and interest rate are useful predictors for changes in inflation. Moreover, both show a comparable power to explain the variation of inflation. However, a rise in interest rate increases rather than decreases inflation, whereas money supply has a positive and expected effect on inflation. These findings suggest that interest rate may not fully capture the overall stance of monetary policy or interest rate has a limited effect on inflation.

Is Money Supply Exogenous? Evidence from India

2017 ◽  
Vol 11 (2) ◽  
pp. 167-195
Author(s):  
Santosh Kumar Dash
Keyword(s):  
Error Correction ◽  
Money Supply ◽  
Forecast Error ◽  
Impulse Response Function ◽  
Error Variance ◽  
Jel Classification ◽  
Quarterly Data ◽  
Causality Tests ◽  
Forecast Error Variance ◽  
Major Factors

Against the backdrop of the claim that the rising growth rate of money is one of the major factors behind India’s recent bout of elevated and sticky inflation, this article asks: Is money supply exogenous or endogenous, and can it predict future inflation. This question is investigated using the monetarist framework of inflation. In the empirical analysis of data spanning from 1970–71 to 2009–10, the results of both the monetarist and the error-correction models suggest that money supply accounts for inflation in India. There is also the presence of an error-correction mechanism among money, inflation and output. However, a monetarist equation does not tell anything about causality. Thus, the vector autoregression (VAR) method is used to detect the direction of causality between money supply and the inflation rate. Findings from Granger causality tests suggest weak evidence of inflation (Granger) causing money supply. As a robustness check, we estimate VAR models using quarterly data and, further, using core inflation. The results of the causality tests from the quarterly data, the impulse response function and forecast error variance decomposition suggest that money supply is weakly endogenous. JEL Classification: E31, E51, E52

Information Spillover Between Crude Oil and Stock Markets: Evidence from Subsidy Cut for RON95 Fuel Price in Malaysia

2017 ◽  
Vol 19 (4) ◽  
pp. 889-901
Author(s):  
Go You-How ◽  
Chin Lai-Kwan ◽  
Kuah Yoke-Chin ◽  
Wei Chooi-Yi
Keyword(s):  
Crude Oil ◽  
Forecast Error ◽  
Composite Index ◽  
Oil Prices ◽  
Error Variance ◽  
Fuel Price ◽  
Forecast Error Variance ◽  
Retail Prices ◽  
The Government ◽  
Information Spillover

Malaysia has been enjoying fixed retail prices for research octane number (RON) 95 petrol and diesel as a form of subsidy from the government since 1983. As of December 2014, the pricing of RON95 and diesel officially went on a managed float mechanism. Therefore, this study examines how information on oil shocks is transmitted to FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBM KLCI) upon the announcement of subsidy cut for RON95 fuel price on 2 October 2014. The sample period of September 2013–December 2014 is separated into the pre-announcement (3 September 2013–1 October 2014) and post-announcement (2 October 2014–28 November 2014) periods. Using the forecast error variance decomposition, the results indicate that Brent crude oil prices dominate information spillover during the post-announcement period. From the perspective of investors’ behaviour, this study suggests that investors’ sensitivity towards information on oil price is elevated by the announcement of subsidy cut and steers their consciousness towards information on oil prices in making decisions.

scholarly journals Contribution of conventional bank lending for agricultural sector in Indonesia

2021 ◽  
Vol 9 (4) ◽  
pp. 331-342
Author(s):  
Hari Setia Putra ◽  
Yunnise Putri ◽  
Ali Anis ◽  
Zul Azhar
Keyword(s):  
Interest Rates ◽  
Agricultural Sector ◽  
Forecast Error ◽  
Impulse Response Function ◽  
Error Variance ◽  
Bank Lending ◽  
Long Run ◽  
Negative Effect ◽  
Forecast Error Variance ◽  
Conventional Bank

This study examines the determinant contribution of conventional bank lending for the agricultural sector in Indonesia. The analysis method used in this research is the Vector Correction Model (VECM). The results showed that in the short term, there was no significant effect of the Non-Performing Loan (LogNPL), GDP of Agricultural Sector (LogPDB), and Agricultural Sector Credit Interest Rates (SBK). However, there is an effect of the LogNPL and LogPDB on the conventional bank lending for the agricultural sector in the long term. The LogNPL has a significant positive effect on the contribution of conventional bank lending to the agricultural sector. While the LogPDB has a significant negative effect on the contribution of conventional bank lending for the agricultural sector. The Impulse Response Function (IRF) analysis results show that shocks to the LogNPL respond negatively in the long run, shocks to the LogPDB respond positively in the long run, and shocks to the SBK respond negatively in the long run by conventional bank lending for the agricultural sector. Through the analysis of FEVD (Forecast Error Variance Decomposition), it is known that the biggest contribution to conventional bank lending for the agricultural sector is agricultural credit and GDP.

scholarly journals Inflation in Malaysia

2010 ◽  
Author(s):  
Wong Hock Tsen
Keyword(s):  
Forecast Error ◽  
Price Change ◽  
Impulse Response Function ◽  
Import Price ◽  
Error Variance ◽  
Variance Decomposition ◽  
Oil Price ◽  
Forecast Error Variance ◽  
The Impact

This study examines the determination of inflation in Malaysia. The results of the generalised forecast error variance decomposition show that real import price change is the most important factor in the determination of inflation. The impact of real oil price change on inflation is marginal. An increase in real oil price has a more significant impact on inflation than a decrease in real oil price. The results of the generalised impulse response function show the impact of variables examined on inflation is relatively short. There is evidence that real oil price change Granger causes inflation.  

scholarly journals Assessing the impacts of global economic policy uncertainty and the long-term bond yields on oil prices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oguzhan Ozcelebi
Keyword(s):  
Economic Activity ◽  
Oil Prices ◽  
Policy Uncertainty ◽  
Government Bond ◽  
Bond Yields ◽  
Content Type ◽  
Economic Policy Uncertainty ◽  
The Usa ◽  
The Impact

Purpose Might the impact of the global economic policy uncertainty (GEPU) and the long-term bond yields on oil prices be asymmetric? This paper aims to consider the effects of the GEPU and the US long-term government bond yields on oil prices using quantile-based analysis and nonlinear vector autoregression (VAR) model. The author hypothesized whether the negative and positive changes in the GEPU and the long-term bond yields of the USA have different effects on oil prices. Design/methodology/approach To address this question, the author uses quantile cointegration model and the impulse response functions (IRFs) of the censored variable approach of Kilian and Vigfusson (2011). Findings The quantile cointegration test showed the existence of non-linear cointegration relationship, whereas Granger-causality analysis revealed that positive/negative variations in GEPU will have opposite effects on oil prices. This result was supported by the quantile regression model’s coefficients and nonlinear VAR model’s IRFs; more specifically, it was stressed that increasing/decreasing GEPU will deaccelerate/accelerate global economic activity and thus lead to a fall/rise in oil prices. On the other hand, the empirical models indicated that the impact of US 10-year government bond yields on oil prices is asymmetrical, while it was found that deterioration in the borrowing conditions in the USA may have an impact on oil prices by slowing down the global economic activity. Originality/value As a robustness check of the quantile-based analysis results, the slope-based Mork test is used.

scholarly journals Trade Openness Effect on Income Inequality: Empirical Evidence from Indonesia

2018 ◽  
Vol 7 (1) ◽  
pp. 1-14
Author(s):  
Lestari Agusalim ◽  
Fanny Suzuda Pohan
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Negative Impact ◽  
Forecast Error ◽  
Trade Openness ◽  
Impulse Response Function ◽  
Secondary Data ◽  
Error Variance ◽  
Long Run ◽  
Forecast Error Variance

This research analyzed the effect of international trade openness to income inequality in Indonesia using Vector Error Correction Model (VECM). The data used is the secondary data, which are the export-import value, gross domestic product (GDP), GDP per capita, open unemployment rate, and Gini index. The results of this study indicate that in the short term the trade openness has negative impact significantly on the income inequality. However, in the long-run, it does not show any significant effect in decreasing the income inequality rate. The impulse response function (IRF) concluded that income inequality gives a positive response, except on the third year. Based on the forecast error variance decomposition (FEDV), the trade openness does not provide any significant contribution in effecting the income inequality in Indonesia, but economic growth does. Nevertheless, in long-term, the economic growth makes the income inequality getting worse than in the short-term.DOI: 10.15408/sjie.v7i1.5527

scholarly journals The Integration of International Capital Market from Indonesian Investors’ Perspective: Do Integration Still Give Diversification Benefit

2017 ◽  
Vol 9 (9) ◽  
pp. 157
Author(s):  
Sabilil Hakimi Amizuar ◽  
Anny Ratnawati ◽  
Trias Andati
Keyword(s):  
Emerging Markets ◽  
Financial Integration ◽  
Forecast Error ◽  
Impulse Response Function ◽  
Error Variance ◽  
International Diversification ◽  
Developed Markets ◽  
Forecast Error Variance ◽  
Vector Error Correction Models ◽  
Diversification Benefit

The objective of this study is to analyze whether, despite the international equity liberalization and growing world financial integration, Indonesian investors can be beneficial from international diversification. The study covers both emerging markets (Indonesia, Philippines, Malaysia, Thailand, Korea, China, and Taiwan) and developed markets (USA, UK, Japan, Singapore, and Australia) over the period of January 1st, 2007 to April 30st, 2017. It uses several state-of-the-art techniques: multivariate cointegration and vector error correction models (VECM) with the analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) to analyze the long-term level of integration and time-varying correlations with the Dynamic Conditional Correlation (DCC) aproach to analyze short term level of integration. The analysis provides the evidence of integration berween Indonesian market and international markets. The findings suggest that Indonesian investors have more chance to gain international diversification benefit from developed markets rather than emerging markets as the Indonesian market has low level of integration compared to developed markets.

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