scholarly journals Monte Carlo Analysis of Forecast Error Variance Decompositions under Alternative Model Identification Schemes

2018 ◽  
Vol 5 (338) ◽  
pp. 115-131
Author(s):  
Anna Staszewska-Bystrova
Keyword(s):  
Monte Carlo ◽  
Forecast Error ◽  
Model Identification ◽  
Error Variance ◽  
Estimation Errors ◽  
Identification Schemes ◽  
Long Run ◽  
Forecast Error Variance ◽  
Short Run ◽  
The Impact

The goal of the paper is to investigate the estimation precision of forecast error variance decomposition (FEVD) based on stable structural vector autoregressive models identified using short‑run and long‑run restrictions. The analysis is performed by means of Monte Carlo experiments. It is demonstrated that for processes with roots close to one, selected FEVD parameters can be esti­mated more accurately using recursive restrictions on the long‑run multipliers than under recursive restrictions on the impact effects of shocks. This finding contributes to the discussion of pros and cons of using alternative identification schemes by providing counterexamples for the notion that short‑run identifying restrictions lead to smaller estimation errors than long‑run restrictions.

scholarly journals Relationship between Technological Advancement and Agricultural Production: Evidence from India

2020 ◽  
Vol 8 (6) ◽  
pp. 2088-2094
Keyword(s):  
Agricultural Production ◽  
Forecast Error ◽  
Error Variance ◽  
Technological Advancement ◽  
Food Grains ◽  
Long Run ◽  
Forecast Error Variance ◽  
Short Run ◽  
Impact Of Technology ◽  
The Impact

Indian economy has more than 60% of the work force engaged in it and with the sectoral contribution of 17- 18% to country's GDP in 2018-19. Despite such heavy dependence and high significance of the agricultural sector, per capita productivity in agriculture over the past few decades is less in comparison to the productivity in other sectors. Available statistics shows that agricultural production has rose marginally during the period of green revolution (starting in 1960s) which was driven by the technology revolution. Technology revolution here means- ‘seed-fertiliser-water technology’ or modern technology. In the present study, a detailed time series analysis for a time period of 36 years (1981-2017) is made to study the impact of technology in production in both the short run and long run. Firstly, the present status of technology use is studied and secondly a crop-output model is considered depicting the role of technology in production of India. Here, the impact of technology is measured using variables such as gross irrigated area, Pesticide use, Synthetic nitrogen fertilizer (NPK) uses, use of improved seed varieties (HYVs) etc. and their impact upon agricultural production (food grains as well as non-food grains) is tested using various econometric tests such as Johansen Co-integration test, regression estimates etc. A composite index has been constructed using PCA method as a proxy to technology. To examine the linkage between technological advancement and agricultural production in India, we employed the Vector auto regression (VAR) model proposed by Sims. To draw inferences on the results of VAR, we also used forecast error variance decomposition (FEVD) which gives both short-run impact and long-run impact of each variable in explaining the forecast error variance of the dependent variable.

scholarly journals Exchange Rate Volatility and Monetary Policy Shocks

2022 ◽  
Author(s):  
Gbalam Peter Eze ◽  
Tonprebofa Waikumo Okotori
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Forecast Error ◽  
Exchange Rate Volatility ◽  
Error Variance ◽  
Variance Decomposition ◽  
Long Run ◽  
Forecast Error Variance ◽  
Short Run ◽  
The Exchange Rate

The study investigated the influence of innovations in monetary policy on the rate of exchange volatility in Nigeria. The research adopted vector error correction model as well as impulse response function and forecast error variance decomposition function in the estimation using two models derived in the study. Monthly data between the periods 2009 and 2019 were adopted for the research. Our findings show that in the long run; all the monetary policy variables have a significant long run correlation with volatility in the exchange rate; but that money supply and the rate of exchange seem to have significant short run impact on volatility in the exchange rate, the other variables such as liquidity ratio or monetary policy rate did not show a significant short run relationship with the volatility in the exchange rate. Further findings on the volatility impulse response and the forecast error variance decomposition suggest a significant link between volatility in the exchange rate and money supply though the link was much more pronounced. The use of monthly data shows that the managed exchange rate regime by the CBN seems to have the desired effect in exchange rate volatility and thus having a critical impact on inflationary spikes.

scholarly journals Covered Interest Parity Deviations Between India And The US

2011 ◽  
Vol 11 (1) ◽  
pp. 83 ◽  
Author(s):  
Vadhindran K. Rao
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
The United States ◽  
Country Risk ◽  
Forward Premium ◽  
Permanent Shocks ◽  
Forecast Error Variance ◽  
Covered Interest Parity ◽  
Interest Parity ◽  
The Impact

Prior studies have tested Covered Interest Parity (CIP) between India and the United States and found substantial deviations. The main objective of the current study is to econometrically model and explain deviations from CIP. Further, the study contributes to the literature by proposing an approach to testing CIP after allowing for country risk. A preliminary analysis suggests that there are two types of shocks that impact the CIP deviation, also referred to as the Covered Interest Differential (CID): permanent shocks and temporary shocks. The permanent shocks may be interpreted as reflecting a change in the country risk premium and the temporary shocks as reflecting transient effects and disequilibrium. The paper uses a bivariate Vector Autoregression (VAR) approach to model the joint dynamics of the CID and the forward premium, and applies the methodology of Blanchard and Quah (1989) to separate the impact of the two types of shocks. Impulse-Response analysis shows that a one standard deviation permanent shock has an immediate, substantial impact on the CID. However, forecast error variance decomposition reveals that less than 30% of the variability in the CID is caused by such permanent shocks. Further, permanent shocks account for less than 5% of the forecast error variance of the forward premium, which suggests that covered interest arbitrage activity has limited influence on the forward premium. Temporary shocks appear to be related to transient volatility in the forward premium, and such shocks initially affect both the forward premium and the CID to approximately the same extent. The manner in which the CID responds to a temporary shock suggests considerable impediments to arbitrage. However, the fact that the CID recovers at a slightly faster rate than the forward premium, especially in the initial periods, suggests that capital restrictions are not completely binding.

Do ‘Shariah’ indices surpass conventional indices? A study on Dhaka Stock Exchange

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Md. Bokhtiar Hasan Aarif ◽  
Muhammad Rafiqul Islam Rafiq ◽  
Abu N.M. Wahid
Keyword(s):  
Stock Exchange ◽  
Forecast Error ◽  
Error Variance ◽  
Impulse Response Functions ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Significant Difference ◽  
Short Run ◽  
Two Indices

Purpose This paper aims to examine whether the Sharīʿah indices outperform the conventional indices as evident from Dhaka Stock Exchange (DSE). To achieve the objective, the study, first, assesses the risk adjusted returns of the Sharīʿah and conventional indices and compares the same between the two indices. Second, it examines the short-run and long-run associations between the two indices. Design/methodology/approach The DSEX Sharīʿah index and DSE broad index of the DSE are used as representatives of the Sharīʿah and conventional indices, respectively. The study uses monthly data for the period 2014–2018 and applies a number of techniques such as risk adjusted returns, Johansen’s cointegration test, vector error correction model, Granger causality test, forecast error variance decomposition and impulse response functions techniques. Findings The study reveals that albeit there is no significant difference in simple mean between the two indices, the Sharīʿah index outperforms its conventional counterpart based on the risk adjusted returns. The two indices are associated only in the long-run, while no causal relationship is spotted between them. The overall results show that the Sharīʿah index has dominance over the conventional index in Bangladesh. Research limitations/implications The study could use more pairs of indices, including additional variables such as financial crisis and macroeconomic variables. Practical implications The study has important implications to investors, especially the religious Muslims and ethical ones, who are suggested to invest their funds in the Sharīʿah index without sacrificing returns, rather be monetarily more benefited. Moreover, the other investors can generate diversification benefits by adding both Sharīʿah and conventional indices in their portfolios in the short-run. Originality/value Unlike previous studies, this study endeavors to use a comprehensive methodology to conduct its analysis. Moreover, this is supposedly the first ever effort to conduct such a study in the context of Bangladesh.

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 Public Expenditure and Economic Growth in India: An Empirical Analysis Using Vector Autoregression (VAR) Model

2020 ◽  
Vol 5 (2) ◽  
pp. 45-58
Author(s):  
Rashmi Gupta ◽  
Swati Shastri
Keyword(s):  
Economic Growth ◽  
Public Expenditure ◽  
Forecast Error ◽  
Granger Causality Test ◽  
Error Variance ◽  
Var Model ◽  
Impulse Responses ◽  
Causality Test ◽  
Long Run ◽  
Forecast Error Variance

Objective – The objective of this study is to test direction of causality between components of public expenditure and economic growth in India. Methodology/Technique – The paper uses annual data for the period 1980-2015. To measure public expenditure, plan expenditure and non-plan expenditure are used. The econometric methodology employed is Vector Auto regression (VAR) model. Findings – First, the stationary properties of the data were tested using Augmented Dickey-Fuller (ADF) test, Dickey-Fuller (DF) test, and the Phillip-Perron (PP) test and found that variables were non-stationary in level, but stationary in first differences. Then, Johansen- Jueslius cointegration test was employed to test the long-run association among the variables and results suggest an absence of any long-run association between plan expenditure and non-plan expenditure and economic growth in India. The Granger Causality test suggests there is unidirectional causality running from economic growth and non-plan expenditure and plan expenditure and non-plan expenditure and absence of causality public expenditure and economic growth. Novelty – The results of the Forecast Error Variance Decompositions test indicated that innovations in the variables are mostly explained by their own shocks. The impulse responses of the economic growth, plan expenditure and non-plan expenditure with respect to identified shocks are consistent with the results of Variance Decomposition Analysis. Type of Paper: Empirical. JEL Classification: O4, O49, O53. Keywords: Plan Expenditure; Non-plan Expenditure; Economic Growth; Unit Root; Cointegration Test; Granger Causality Test; Forecast Error Variance Decomposition; Impulse Responses. Reference to this paper should be made as follows: Gupta, R; Shastri, S. 2020. Public Expenditure and Economic Growth in India: An Empirical Analysis Using Vector Autoregression (VAR) Model, J. Bus. Econ. Review 5(2) 45– 58 https://doi.org/10.35609/jber.2020.5.2(1)

scholarly journals THE OPENNESS AND ITS IMPACT TO INDONESIAN ECONOMY: A STRUCTURAL VAR APPROACH

2008 ◽  
Vol 10 (3) ◽  
Author(s):  
Iskandar Simorangkir
Keyword(s):  
Economic Performance ◽  
Forecast Error ◽  
Trade Openness ◽  
Error Variance ◽  
Structural Var ◽  
Financial Openness ◽  
Cross Sectional ◽  
Forecast Error Variance ◽  
The Impact ◽  
The Relationship

There have been long running disputes on the relationship between the degree of openness and economic performance. Based on cross-country analyses, a number of studies found that the relationship between openness and economic performance is quite mixed. Some studies discovered a positive relationship, while others found a negative or simply neutral relationship.Unlike previous studies using cross-sectional data, this study uses structural vector auto-regression (SVAR) to explore the impact of trade openness and financial openness on the Indonesian economy. The findings shows that trade openness and financial openness have negative impacts on output. The results of trade openness are quite robust; since a lack of preparation to anticipate trade openness weakens the competitiveness of Indonesian products relative to foreign products and, finally, lower output. The findings of financial openness are also robust because greater financial openness leaves the Indonesian economy more vulnerable to capital reversal, which endangers economic performance.Keywords: Openness, SVAR, forecast error variance decomposition, impulse response function.JEL Classification: F41, F43

scholarly journals Eurozone or national inflation projections: Which has greater impact on consumer expectations?

2020 ◽  
pp. 14-14
Author(s):  
Magdalena Szyszko ◽  
Karolina Tura-Gawron
Keyword(s):  
Central Bank ◽  
Forecast Error ◽  
Probabilistic Method ◽  
Error Variance ◽  
Response Analysis ◽  
Inflation Expectations ◽  
Causality Test ◽  
Consumer Expectations ◽  
Forecast Error Variance ◽  
The Impact

We compare the dependence of consumer inflation expectations on European Central Bank (ECB) inflation projections with that on national central bank (NCB) projections in four economies: Austria, Belgium, Finland, and Germany. We aim to assess whether the information published by central banks affects consumers, and whether inflation projections published by NCBs are more relevant to consumers than those published for the entire Eurozone. Inflation expectations were obtained from the Business and Consumer Surveys conducted by the Directorate General for Economic and Financial Affairs of the European Commission and quantified using the probabilistic method. The methodology covers: (1) forecast encompassing tests, (2) the Granger causality test, and (3) impulse response analysis complemented by (4) forecast error variance decomposition. The results suggest that the ECB outlook constitutes a more important factor in expectation formation. This article adds to the existing literature by comparing the impact of common and national projections on consumer expectations.

scholarly journals An Empirical Study of Dividend Payout and Future Earnings in Singapore

2010 ◽  
Vol 13 (02) ◽  
pp. 267-286 ◽  
Author(s):  
King Fuei Lee
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
Response Analysis ◽  
Causality Test ◽  
Dividend Payout ◽  
Vector Error Correction ◽  
Future Earnings ◽  
Vector Error ◽  
Long Run ◽  
Forecast Error Variance

The main purpose of this paper is to apply Johansen's vector error-correction model (VECM) to investigate the existence of the dividend signalling effect in the Singapore aggregate market through impulse response analysis, forecast error variance decomposition and Granger-causality test. Our findings show that a unit shock increase in dividend payout leads to a permanent increase in future earnings over time. These results imply that there exists informational/signalling content in dividend payout in the Singapore market over the long run. We further find that at least half of the forecast error variance in earnings can be accounted for by innovations in the dividend payout. In addition, the payout ratio is also shown to Granger-cause earnings in the Singapore market.

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