Vector Autoregression (VAR) and Structural Vector Autoregression (SVAR)
LASSO vector autoregression structures for very short-term wind power forecasting
... the vector autoregression (VAR) model using the Least Absolute Shrinkage and Selection Operator (LASSO) ...different VAR-LASSO variants and create a scalable forecasting method supported by ...
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Deficit Financed Public Expenditure in Argentina: A Structural Vector Autoregression Analysis
... The goal of our research project is to analyze the importance of government debt in the propagation of fiscal shocks in the Argentine economy. For that reason we augment a standard fiscal policy vector ...
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The Endogeneity of Oil Price Shocks and Their Effects on Indonesia: A Structural Vector Autoregression Model
... A Structural Vector Autoregression ...A structural Vector Autoregression (SVAR) model was constructed extending Kilian (2009) model by employing several lags constraints ...
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Investigation of asymmetric impulse responses between average consumption propensity and average food consumption propensity of household in Korea
... the Structural Vector Autoregression (SVAR) model, ACP and AFCP are analysed to have asymmetric responses to negative and positive shocks, regardless of whether the shock is imposed on the own ...
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On the Linkages between India VIX and US Financial Stress Index
... comprising Vector Autoregression model (VAR), Granger causality test, Generalized impulse response func- tions and Variance Decomposition Analysis (VDA) to account for linkages among the respective ...
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The Roadmap of Interest Rate Liberalization in China
... A Vector autoregression model (VAR) is estimated to investigate the effectiveness of Chinese market interest rates, Shanghai Interbank Offered Rate (SHIBOR), and repo rates against different factors ...
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Central Bank Communication, Ambiguity and Market Interest Rates: A Case Study
... A Structural Vector Autoregression model is estimated and the results show that am- biguous messages were able to affect agents’ expectations for a limited period after a speech by ECB members; more- ...
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Vector autoregression with varied frequency data
... The Vector Autoregression (VAR) proposed by Christopher Sims (1980) is a workhorse model for forecasting as well as studying cause and effect in the ...An autoregression model implicitly ...
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The macroeconomic and financial effects of oil price shocks
... use vector autoregression (VAR) model to examine two hypotheses based on the current data: (i) Impact of crude oil price change can affect Real Gross Domestic Product (GDP), Consumer Price Index ...
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Exchange Rate Pass Through:Evidence Based on Vector Autoregression with Sign Restrictions
... underlying structural shocks, but rather concentrate on identifying only one ...all structural disturbances, but introduce minimal restrictions that are sufficient to identify the exchange rate shock and ...
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The impact of TV mass media campaigns on calls to a national quitline and the use of prescribed nicotine replacement therapy: a Structural vector autoregression analysis
... Prior to estimation, we checked the mean and vari- ance properties of the series to look for non-stationarity (i.e. strong trends and changing variance) using standard unit root tests [27,28]. The results indicated the ...
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International linkages of Japanese bond markets: an empirical analysis
... the vector autoregression (VAR) model and the vector error correction (VEC) model to monthly observations of nominal bond yields and exchange rate-adjusted bond yields over the 25-year period, ...
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Crude oil price variability and its impact on ethanol prices
... Abstract: The world annual biofuel production has exceeded 100 billion litres in 2009. The development of the biofuel production is partly influenced by the government support programs and partly by the development of ...
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Essays on Economic and Policy Time Variations in Small Open Economies
... varying VAR models ability to forecast key Australian macroeconomic variables: real GDP growth, CPI inflation and a short-term interest ...and VAR models, regime switching models, rolling-window models and ...
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Multivariate count autoregression
... of vector of counts is not equal to the correlation induced by the copula imposed to the vector of waiting ...the vector of waiting times and should be done with ...
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Very-short-term probabilistic wind power forecasts by sparse vector autoregression
... It has been demonstrated that the proposed approach pro- duces forecasts that are a non-negligible improvement on two competitive benchmarks in terms of several skill scores and reliability, while also offering ...
8
Economy, Environment and Government: Study on the Path of Supply Side Reform Forced by the Fog Haze
... The current paper focuses on the linear relationship between industrial struc- ture, energy use efficiency and fog-haze pollution, for example [9]-[18]. There are studies on supply-side structural reforms, for ...
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Forecasting Hong Kong economy using factor augmented vector autoregression
... There is no factor model forecasting literature on the Hong Kong economy. Our objective is to find out whether factor forecasting of using a large dataset can improve forecast performance of the Hong Kong economy. We ...
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Oil Price Shocks and Uncertainty: How stable is their relationship over time?
... Our results can be outlined as follows. The responses of the uncertainty indicators to the three oil price shocks, as these were estimated by the SVAR model, reveal that oil supply shocks do not exercise any ...
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Causal Ordering Between Inflation and Productivity of Labor and Capital: An Empirical Approach for Pakistan
... capital, in Pakistan’s economy by covering the period from 1960'M1 to 2007'M12. For this purpose Vector Autoregression (VAR) approach is used, which is based on error correction model (ECM). Using ...
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