Vector Autoregression Estimates for crisis subsample
Noncausal vector autoregression
... Our first application is concerned with fiscal foresight, ie, the phenomenon that due to lags in implementation, agents receive signals about a future change in the tax rate or government spending before they actually ...
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Factor Proportions Wages in a Structural Vector Autoregression
... serially correlated, and many economic variables are highly persistent. Estimating (5) is appropriate for simple comparative statics but wage adjustments may take time. There may also be potential feedback relations ...
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FORECASTING INFLATION IN NIGERIA: A VECTOR AUTOREGRESSION APPROACH
... the autoregression estimates, we observe that the most important variable that can be used to forecast the future path of inflation is the past one year value of inflation ...
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Monetary transmission mechanism in Vietnam after the Asian financial crisis (1999-2006) : a structural vector autoregression model
... foreign exchange m a n a g e m e n t s for residents'^, enterprises'^ and foreign indirect i n v e s t m e n t " . Second, by requiring S O C B s to satisfy the foreign exchange demands according to certain stated ...
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Testing for rational bubbles in a co-explosive vector autoregression
... of estimates of the underlying asset pricing ...of estimates is consistent both with and without a bubble, whereas the second set is only consistent in the absence of a ...
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A vector autoregression approach to the effects of monetary policy in South Africa
... financial crisis, its effects onto the rest of the world and how US Federal Reserve ...financial crisis and the subsequent global recession in ...mortgage crisis effects were transmitted onto the ...
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A Panel Vector Autoregression Analysis of Sudden Stops and Banking Crises
... Finally, VAR 3 in Table 2 shows equation (3) estimated when both crises occur jointly. RGDP is impacted through both the financial account channel and the domestic credit channel. The magnitude of the impact from ...
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Deficit Financed Public Expenditure in Argentina: A Structural Vector Autoregression Analysis
... One practical issue, stemming from our desire to include so many controls in our model is that we end up with eight dummy variables (a dummy for government spending, deficit, taxes, GDP, GDP deflator, debt to GDP, period ...
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Exchange Rate Pass Through:Evidence Based on Vector Autoregression with Sign Restrictions
... a vector autoregreesion (VAR) model that includes the distribution chain of ...literature, estimates of pass-through based on the sign restriction procedure are ...
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Non-parametric Bayesian Vector Autoregression using Multi-subject Data
... The estimates under the rgPDPM-VAR exhibit a very high degree of correlation, almost entirely > 0.8. On the other hand, the correlation for the majority of the elements is less than 0.5 under SS-VAR, with only 10 ...
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Exchange Rate Pass-Through:Evidence Based on Vector Autoregression with Sign Restrictions
... a vector autoregreesion (VAR) model that includes the distribution chain of ...literature, estimates of pass-through based on the sign restriction procedure are ...
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Exchange Rate Pass-Through:Evidence Based on Vector Autoregression with Sign Restrictions
... a vector autoregreesion (VAR) model that includes the distribution chain of ...literature, estimates of pass-through based on the sign restriction procedure are ...
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Interest Rate Channel and Real Economy in Nigeria: A Bayesian Vector Autoregression Approach
... power and the estimates not affected by non stationarity of data (Koop and Korobilis, 2009; Spulbar and Nitoi 2013). From IRF, MPR is effective in reducing inflation as all the variables behaved according to ...
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Noncausal Vector Autoregression
... forecasts can be considered as investors’ expectations. If these expectations are rational, i.e., they do not systematically deviate from the observed values, this together with the expectations hypothesis imposes ...
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Vector Autoregression and Vector Error-Correction Models
... A key distinction in understanding and applying VARs is between the innovation terms v in the VAR and underlying exogenous, orthogonal shocks to each variable, which we shall call ε. The innovation in y t is the part of ...
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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 assumes data ...
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Vector Autoregression with Mixed Frequency Data
... parameters, as proposed by Mariano and Murasawa (2003). However, the coefficient matrix in the observation equation remains cyclical. It does not pose a problem in theory, but a time-varying model is inconvenient for ...
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Supplementary appendix to "noncausal vector autoregression"
... the eigenvalues of are smaller than one in absolute value whereas the former condition in (2) implies that the zeros of a (z) lie outside the unit disc... Consider the covariance matrix [r] ...
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Vector Autoregression with Mixed Frequency Data
... parameters, as proposed by Mariano and Murasawa (2003). However, the coefficient matrix in the observation equation remains cyclical. It does not pose a problem in theory, but a time-varying model is inconvenient for ...
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Searching for the Causal Structure of a Vector Autoregression
... identification. 2 A VAR identified through restrictions on contemporaneous variables is known as a structural vector autoregression (SVAR). It is widely believed that there is no empirical or statistical ...
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