Restricted Vector Autoregressive Research Articles

Pengaruh Uang Elektronik dan Surat Berharga Syariah Negara (SBSN) terhadap Jumlah Uang Beredar di Indonesia


 As the central bank of the Republic of Indonesia, Bank Indonesia has three main responsibilities: creating and implementing monetary policy, regulating and maintaining a seamless payment system, including cash and non-cash payments, and financial system stabilization. To achieve this goals, Bank Indonesia can use one of the sharia monetary instruments, specifically Government Islamic Securities and it is authorized to provide efficient payment instruments such as non-cash electronic money payment instruments, the development of which may have an effect on the money supply. The goal of this study was to determine the effect of electronic money and Government Islamic Securities on Indonesia's money supply. The data used in this analysis is secondary data in the form of a time series of 84 observations that includes monthly data on electronic money, Government Islamic Securities and the money supply from Bank Indonesia publications for the period January 2015 to December 2021. Using the EViews 10 program, this study technique employs the restricted VAR (Vector Autoregression)/VECM (Vector Error Correction Model) analysis method. The results of this study reveal that the variable of electronic money in the short term does not significantly affect the money supply. Electronic money, on the other hand, has a long-term positive influence on the money supply. The variable of Government Islamic Securities in the short term does not significantly affect the money supply. Meanwhile, Government Islamic Securities have a negative impact on the money supply in the long term.
 Keywords: Electronic Money, Government Islamic Securities and Money Supply.

Has Foreign Growth Contributed to Stagnation and Inequality in Japan?

This paper examines the contributions of foreign growth (particularly in China), on Japan’s domestic economic performance and inequality. While the standard approach to external sources of inequality has emphasized transmission through trade and labor markets, here the emphasis is on financial flows. We begin by exploring this link using a three factor, three sector, two-region dynamic computable general equilibrium model (CGE), in which the regions are interlinked by both trade and financial flows. To provide an empirical perspective, a lag-augmented vector autoregression (LA-VAR) and a sign restricted vector autoregression (Sign restricted VAR) are estimated. We find convincing evidence through numerical simulations that strong growth in a near neighbor not only retards domestic performance but also raises home inequality. Empirical results suggest that growth in China has a significant delayed effect in aggravating Japanese inequality and its importance in explaining Japanese inequality increases in magnitude over time.

Vector Error Correction Model to Forecasting Spot Prices for Coffee Commodities During Covid-19 Pandemic

Forecasting time series commonly shows non-stationer behavior and involves interrelated variables, so a method that able to obtain a good forecasting result from a non-stationary multivariate time series data is needed. Vector Error Correction Model (VECM) as one of multivariate time series model is a vector form of restricted Vector Autoregressive (VAR) for non-stationary data which has Cointegrity relationship. Prices of agricultural commodities futures usually show variability and unsystematic behavior, especially in times of facing the Covid-19 pandemic as it is today, so getting complete information about data requires data handling while still considering the concept data-driven. Coffee, as one of agricultural commodity data, is often not known for its stationarity. The purpose of this study is to identify the reliability of VECM to predict the spot price of commodities futures coffee during the Covid-19 pandemic in Indonesia. The used data is several observed variables, there are: spot price of Robusta Coffee, futures prices of Robusta Coffee, exchange rates and daily case positive Covid-19 in Indonesia. The results of this study described the Robusta Coffee data in Indonesia as non-stationary and there is a long-term cointegration relationship to the Robusta Coffee futures price movement due to the influence of the Covid-19 pandemic.

A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sector.

The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the US becoming the epicenter of COVID-19 cases since late March. As the US begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing US wholesale electricity markets with COVID-19 case, weather, mobile device location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we rigorously uncover a significant reduction in electricity consumption that is strongly correlated with the number of COVID-19 cases, degree of social distancing, and level of commercial activity.

The Nexus between Macro-Prudential Banking Regulation, Interest Rate Spread and Monetary Policy in South Africa

This study is an empirical attempt to investigate the nexus between macro-prudential banking regulation, interest rate spread and monetary policy in South Africa. The effectiveness of monetary policy and alarmingly wide interest rate spread has been a contentious issue in the corridors of central banks across the globe in this lifetime. This has been largely because monetary policy alone proved to be less efficient in mitigating the effects of systemic risk, particularly during the 2007 financial crisis, necessitating the need for macro-prudential banking regulation. Time series dataset spanning from 1994Q1 to 2016Q4 is employed to carry out this study using the restricted Vector Autoregressive (VAR) model, that is, the Vector Error Correctional Model (VECM). The results show that there is no long-run causality running from trade openness, real exchange rate financial depth interest rate spread and credit growth to the repo rate in South Africa. A short run causality running from credit growth to the repo rate exists from the estimated model. In addition, the empirical results exhibited evidence that interest rate spread has a dampening effect on monetary policy but in the long-run this effect seems reversible in South Africa. Therefore, in order to ensure financial stability, care has to be taken by the South African Reserve Bank and government in choosing the best tool-kit of macro-prudential banking regulation as it can be used to disguise the symptoms of a lax monetary policy framework.

The effectiveness of monetary policy in small open economies

This paper examines the relative effectiveness of the use of direct and indirect monetary policy instruments in Barbados, Jamaica and Trinidad and Tobago, by estimating a restricted Vector Autoregressive model with Exogenous Variables (VARX). The model captures the dynamic interaction of the key sectors in the economy and it accounts for the fact that the banking system in those countries is characterized by high levels of excess reserves. Also, the study assumes that the central bank conducts monetary policy using a Taylor-type rule, and it evaluates the effects of a reserve requirement policy. The results show that although a positive shock to the policy interest rate has a direct effect on commercial banks’ interest rates, there is a weak transmission to the real variables. Furthermore, an increase in the required reserve ratio is successful in reducing private sector credit and excess reserves, while at the same time alleviating pressures on the exchange rate. The findings therefore indicate that central banks in small open economies should consider using reserve requirements as a complement to interest rate policy, to achieve their macroeconomic objectives.

Exploring the Nexus between Crude Oil Price and Stock Prices in Sub-Saharan Africa: A Case Study of Nigeria

Objective: The objective of this article is to investigate the connection between unrefined oil price and stock prices in Sub-Saharan Africa with particular accentuation on the Nigerian economy. Research Design & Methods: Based on the time series data used, we applied co-integration test and a restricted Vector Autoregressive Approach to verify the existence of each short and long-term relationship among the variables of interest. Findings: The results revealed that there is very little correlation between crude oil price and stock indices, thereby implying that such an impact cannot be completely expected in the short run. Moreover, the study showed causality relation running from crude oil price and real rate of exchange to stock indices. Implications & Recommendations: Since the study disclosed that petroleum price and rate of exchange values have far more impact on stock market indices in the long run than in the short run in Nigeria with rate of exchange contributing more to the general changes in available market indices throughout the study period, thereby suggesting that stock exchange indices are insensitive to crude oil price variations in the short run and thus resulting in loss of confidence by the investors. Consequently, the study recommends that the sitting government ought to utilise the revenue generated on the sales of petroleum to diversify the economy. Contribution & Value Added: In this study, we tried to point out the responses of crude price shocks to stock prices, particularly throughout the previous and current administration in Nigeria. The study was able to discover that changes in unrefined oil do not impact the stock indices.

Dimension reduction of frequency-based direct Granger causality measures on short time series

BackgroundThe mainstream in the estimation of effective brain connectivity relies on Granger causality measures in the frequency domain. If the measure is meant to capture direct causal effects accounting for the presence of other observed variables, as in multi-channel electroencephalograms (EEG), typically the fit of a vector autoregressive (VAR) model on the multivariate time series is required. For short time series of many variables, the estimation of VAR may not be stable requiring dimension reduction resulting in restricted or sparse VAR models. New methodThe restricted VAR obtained by the modified backward-in-time selection method (mBTS) is adapted to the generalized partial directed coherence (GPDC), termed restricted GPDC (RGPDC). Dimension reduction on other frequency based measures, such the direct directed transfer function (dDTF), is straightforward. ResultsFirst, a simulation study using linear stochastic multivariate systems is conducted and RGPDC is favorably compared to GPDC on short time series in terms of sensitivity and specificity. Then the two measures are tested for their ability to detect changes in brain connectivity during an epileptiform discharge (ED) from multi-channel scalp EEG. Comparison with existing method(s)It is shown that RGPDC identifies better than GPDC the connectivity structure of the simulated systems, as well as changes in the brain connectivity, and is less dependent on the free parameter of VAR order. ConclusionsThe proposed dimension reduction in frequency measures based on VAR constitutes an appropriate strategy to estimate reliably brain networks within short-time windows.

Modelling and forecasting inflation in Uganda (2005-2014)

The study was set to fit appropriate auto-regressive integrated moving average (ARIMA) and vector auto-regressive (VAR) models for forecasting Uganda's core inflation; to compare their forecasting capabilities and establish whether the forecasts produced were significantly different. The study employed Box and Jenkins (1976) and Sims (1980) modelling techniques on monthly time series data for core inflation index, broad money supply (M2), nominal official exchange rate and short-term 91-day Treasury bill rates for the period July 2005 to December 2014. The appropriate ARIMA model was evaluated and found to be ARIMA(3, 1, 3). Pairwise Granger causality test confirmed that money supply, nominal Ushs/USD exchange rate and short-term Treasury bill rate caused core inflation. Thus, the appropriate restricted VAR (VECM) model was estimated and found to produce more accurate core inflation forecast for longer time horizons while ARIMA was better for shorter forecast horizons. However, the forecasts from both models were not significantly different.

The Effectiveness of Monetary Policy in Small Open Economies: An Empirical Investigation

This paper examines the relative effectiveness of the use of indirect and direct monetary policy instruments in Barbados, Jamaica and Trinidad and Tobago, by estimating a restricted Vector Autoregressive model with Exogenous Variables (VARX). The study assumes that the central bank conducts monetary policy using a Taylor-type rule and it evaluates the effects of a reserve requirement policy. The results show that although a positive shock to the policy interest rate has a direct effect on commercial banks' interest rates, there is a weak transmission to the real variables. Furthermore, an increase in the required reserve ratio is successful in reducing private sector credit and excess reserves, while at the same time alleviating pressures on the exchange rate. The findings therefore indicate that central banks in small open economies should consider using reserve requirements as a complement to interest rate policy, to achieve their macroeconomic objectives.

The Effectiveness of Monetary Policy in Small Open Economies: An Empirical Investigation

This paper examines the relative effectiveness of the use of indirect and direct monetary policy instruments in Barbados, Jamaica and Trinidad and Tobago, by estimating a restricted Vector Autoregressive model with Exogenous Variables (VARX). The study assumes that the central bank conducts monetary policy using a Taylor-type rule and it evaluates the effects of a reserve requirement policy. The results show that although a positive shock to the policy interest rate has a direct effect on commercial banks' interest rates, there is a weak transmission to the real variables. Furthermore, an increase in the required reserve ratio is successful in reducing private sector credit and excess reserves, while at the same time alleviating pressures on the exchange rate. The findings therefore indicate that central banks in small open economies should consider using reserve requirements as a complement to interest rate policy, to achieve their macroeconomic objectives.

Pattern of capital inflows in BRICS: Aspects to ponder for policy implementation

Surge in capital inflows can stimulate economic growth in developing countries and also lead to macroeconomic fluctuations of varied nature. This makes the analysis of determinants of capital inflows in developing countries interesting. The behavior of capital inflows in the long and short run has been under study. Such analysis could help to avoid undesirable consequences of surge in capital inflows. Traditional literatures on determinants of capital inflows are bifurcated into push and pull factors. The present research focuses on pull factors determining the inflows of capital. This research tries to identify main determinants of capital inflows in BRICS using Vector Autoregression (VAR) technique. Johansen cointegration and Augmented Dickey fuller test are used for data analysis. The Vector Error Correction model (VECM) which is a restricted VAR is used for the analysis since Johansen cointegration test suggested cointegration among the variables in the long run for BRICS. The lag length of the model is determined by performing Schwarz Information Criterion. Impulse response function is used to gauge the effects of shocks on capital inflows with World Bank’s annual data (1992-2012). The variables used in the study include capital inflows (sum of FDI and portfolio equity), inflation, exchange rate, Gross Capital Formation and Gross Domestic Product. All the variables are constant at 2005 U.S. dollars. All the diagnostic testing done for BRICS countries made it relevant to estimate the equations using OLS estimate. In Brazil, capital inflows are influenced by lagged and current values of GDP, GCF and Exchange rate. The Vector Error Correction Model (VECM) estimates of Russian economy indicates cointegration of capital inflows with GDP and Inflation in the long run. Capital inflows in Indian economy is determined by inflation and exchange rate. In China higher GCF plays an important role in attracting capital inflows. In South Africa only inflation is causative factor which determines capital inflows. The Gross Domestic Product is observed to be the vital factor determining the capital inflows to BRICS. The study forecasts improvement of investment climate for attracting capital inflows into BRICS. Economic stability of BRICS is found to be one of the major factors influencing capital inflows in BRICS. The study forecast that in economies of Russia, India and South Africa emergency measures should be taken to curb inflation. Inflation, GDP, GCF and exchange rate are critical factors in attracting capital inflows, which helps in formulating appropriate policies for improving the performance of domestic economy.

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Analysis of the performance of agro-based companies in the Nigerian stock exchange

Purpose – Given the potential of the stock market to provide required capital for agro-based companies, a time series analysis of the performance of major agricultural-based companies in the Nigerian stock exchange (NSE) was carried out. Design/methodology/approach – Monthly records of volume of shares traded (VOL) as well as its determinants – current market price (CMP), dividend (DIV), earnings per share (EPS), price-earning ratio (PER), earning yield (EARN) and dividend yield (YIELD) were obtained from the NSE as indicators of performance through 11 years (1998-2008). Non-stationarity of the variables under consideration led to re-conceptualisation of the model as a vector autoregressive (VAR) system. Existence of more than one co-integrating vector in the data through the Johansen test, led to estimation of restricted VAR using the Vector Error Correction Model (VECM) imposing normalisation of VOL and PER. Findings – The result of the analysis revealed that VOL is positively related to YIELD and CMP while it is inversely related to EARN, EPS and DIV. On the other hand PER increases with increasing EPS and DIV but reduces with increase in EARN and CMP. Short-run adjustment coefficients were generally large ranging from four months to ten years. Research limitations/implications – However, variables coefficients were more elastic in the long run. Originality/value – This paper is an original article and has not been done by any other researcher. Furthermore, this paper has not been submitted to any other publishing house prior to this.

A Study of Inflation Dynamics in India: A Cointegrated Autoregressive Approach

This study explores the inflation dynamics after following new economic policy in Indian economy by employing Restricted Vector Autoregressive technique. Inflation variable has cointegrating relationship with other macro economic variables. Money supply turned out to be most important variable in explaining the variation in inflation overtime followed by import index variable. IIP has inflation discouraging affect. Besides, apart from the economic variables, moral suasion factor has also been proved to be important in controlling Indian inflation. Cointegrating relationship among the variables has considerable bearing on the inflation dynamics. Moreover, inflation bears stable and correcting relationship with CPI and import index variables, however such relationship is unstable and explosive with money supply and IIP.

The Evaluation of the USD Currency and the Oil Prices: A Var Analysis

Dollar devaluation creates a huge problem in the world oil industry, leading to a vast decrease in the revenues of the oil producers, though the local oil producers use the local currencies to operate and the oil price is evaluated in dollars. The depreciation of the US dollar reduces the effect of the high prices in oil, making it rather cheap for all the countries and especially for the Eurozone area. The record high exchange rate of the Euro vis-a-vis dollar followed by a subsequent high of the crude oil price, suggests on a relation between the price of the oil and the evaluation of the US dollar. The main aim of this research is to construct an restricted Vector Autoregressive estimation model to simulate the relation between the exchange rate of the U.S. dollar and Euro against the West Texas Intermediate (WTI) prices for light crude oil, in connection with the impulse response of the prices to the various shocks. Lastly, a co integration test will illuminate the possibility of simultaneous long term integration along with Granger causality test to estimate the direction of causality in variables.

Bayesian testing of restrictions on vector autoregressive models

In this study, we propose a prior on restricted Vector Autoregressive (VAR) models. The prior setting permits efficient Markov Chain Monte Carlo (MCMC) sampling from the posterior of the VAR parameters and estimation of the Bayes factor. Numerical simulations show that when the sample size is small, the Bayes factor is more effective in selecting the correct model than the commonly used Schwarz criterion. We conduct Bayesian hypothesis testing of VAR models on the macroeconomic, state-, and sector-specific effects of employment growth.

Determinants of interest rates in Nigeria: An error correction model

SUMMARY AND CONCLUSION The goal of this paper has been to examine the influence and relative importance of various domestic and foreign factors in the determination of interest rates, particularly the Treasury Bill Rate (TBR) in Nigeria. Using a sample of quarterly observations from January 2000 to April 2008, analyzed by descriptive and econometric tech-niques. Evidence from this study shows that the series of TBR in Nigeria and its hypothesized determinants are generally I(1) series. Johansen (1992, 1995) system based co-integration tests revealed that two (2) co-integrating equations (CE) exist between linear combina-tions of the series. Results based on normalization of the restricted Vector Autoregressive (VAR) system in respect of TBR and real outputs, with two CE imposed, revealed that increase in real money supply (RMS) and expected foreign returns (EFR) exert significant (p<0.01) and negative influence on TBR, while simultaneously exerting significant (p<0.01) and positive influence on domestic outputs in the long-run. This shows that the performance of the domestic economy is better enhanced in the long-run, when government’s monetary and exchange rate policies are targeted at enhancing RMS, promoting reasonable depreciation of Naira relative to other foreign currencies and in the process, lowering the TBR in Nigeria. Evidence based on the short-run component of the estimated Vector Error Correction Model (VECM) and the associated variance decomposition, revealed that the equilibrium relationship between TBR and its determi-nants is stable, exogenous shocks due to TBR being corrected within 1.04 quarters (92 days), while those due

Simulation-based tests of forward-looking models under VAR learning dynamics

In this paper we propose a simulation-based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one-shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p-values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non-stationary cointegrated processes. Application to the ‘hybrid’ New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward-looking component of inflation dynamics is much larger than the backward-looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984–2005. Copyright © 2010 John Wiley & Sons, Ltd.

Parameter Estimate Uncertainty in Probabilistic Debt Sustainability Analysis

This paper extends the probabilistic debt sustainability analysis (DSA) developed by Celasun, Debrun, and Ostry (2006) to account explicitly for parameter estimation errors in the debt projection algorithm. This extension highlights public debt projection uncertainty resulting from both the intrinsic volatility of debt determinants and the inaccuracy of the parameter estimates of econometric models employed in the projections. The revised algorithm is applied to conduct a debt sustainability analysis of Uruguay. As part of this exercise, a restricted vector autoregression and a country-specific fiscal reaction function are employed. The resulting increase in the variance of the debt projections that account for the uncertainty of parameter estimates in the forecast is smaller than may have been anticipated, as the improved specification of the underlying econometric model reduces the variance of debt projections. Hence, more precise estimates of economic fundamentals and fiscal policy reaction allow for a feasible debt forecast with a more accurate depiction of its inherent forecast uncertainty.