# Questions tagged [vector-autoregression]

Vector Auto-Regression, a multivariate time-series model / method. Under VAR, each univariate time-series is a linear combination of its own previous values and the previous values of the other series.

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### Can I impose an inflation floor for a VAR model?

I am trying to forecast inflation using a VAR. After Granger causality and carefully analyzing impulse response functions, I have selected three variables to include in the VAR. My issue is that while ...
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### How to implement ordering for VAR impulse response functions in statsmodels (python)

I'm trying to implement an impulse response function for a VAR system. However, I'm not sure how to implement the variable ordering. Does this correspond to the order of the columns in the data frame? ...
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### Is my approach to compute Granger causality valid?

I have two time-series, let us call them A (colored in red) and B (colored in blue). There are ~770 data points per time-series. Note: Both time-series are in fact not the recorded raw signals, but ...
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### Interpretation and Analysis of a Multivariate Threshold Autoregressive Model

I'm looking to study the asymmetric affect a market rate, like the Fed Funds rate has on an interest rate. In other words, I would like to study the response of interest rate adjustments in different ...
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### Why does the serial.test function from the vars package in R yield contradictory results for type='BG', 'ES', and 'PT.asymptotic'?

I fitted a VAR model, individually all the residuals do not have autocorrelation, but if I use the serial.test I get different results: Type 'ES' Edgerton and Shukur (1999) Test p.value=0.99 Type 'BG'...
1 vote
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### Time series model specification

I want to run a regression analysis in R to explain the variation of my DV g_law_tot which is the growth rate of total budget from t-1 to t. I have yearly data from 1994 to 2023. I have some political,...
1 vote
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### Impulse response function for discontinous time series

I have monthly time series on forecasts (for the months of August, September, October, November, December, and January.) The data is only available for these months and doesn't exist for other months. ...
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1 vote
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### Estimating VECM with Exogenous variable

I'm currently working on a project that requires estimating a Vector Error Correction Model (VECM), potentially extending to a structural VECM, that incorporates at least one exogenous variable. The ...
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### How to choose the best one model from ARIMAX, ARCH/GARCH and VAR?

Now I have 3 models to find what economic factors have an effect on gold price: ARIMAX model ARCH/GARCH model VAR model What is the tool to find the best model? In linear regression, we can ...
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### Forecasting cash inflow using network load usage - timeseries vs GAM (or similar)

I have two datasets of daily cash_inflows & network consumption (load) for past 4 years. Network load consumption is the single source of income. There will be some lag between load consumption &...
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1 vote
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### Efficient way to compute covariance matrix of Vector Autoregressive Process of order 1 (VAR)

For a VAR process $$X_t = A_1 X_{t-1} + \epsilon_t$$ The covariance of $X_t$ can be computed in the following way: $$\text{vec}(\Sigma) = (I -(A \otimes A))^{-1} \text{vec}(\Sigma_{\epsilon})$$ ...
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### Normality assumption n=48 [closed]

Regarding normality assumptions for model evaluation I have been told by my supervisor that it is not needed in the case of analyzing but is needed in forecasting only. i am looking for an explanation....
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### Interpreting the VECM: which variable corrects towards which one?

I am trying to understand the vector-autoregressive error correction model, but I am having a hard time understanding the error correction part. Imagine that we have a VAR(1) model of 2 dimensions: \...
1 vote
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### BVAR model: Draws and Burn-In?

This is a very basic question. I am trying to understand how a BVAR model works. One thing I dont get is why we are using a burn-in period and what we are making "draws" from. I simply can ...
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### Difficulties with estimation and strange fitted values for BVAR (BVAR R package)

I'm using the BVAR package in R to estimate a Bayesian vector autoregression involving the following monthly variables: US Capacity utilization, US Total Employees, US PCE index, and 5,10,20,30 year ...
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### VECM model unable to predict approximately but able to learn the pattern

In the below image VECM model has learnt the pattern but did not predict properly there is a difference in actual and prediction Have used the below dataset to predict the meanpressure:- https://www....
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### In VAR model, can I include not-granger-causing variables in impulse response anaysis?

In a VAR model, I have 6 endogenous variables(X: dependent, others: independent) Having run Granger Causality test, I found that only 2 independent variables granger cause X. Can I include other 3 ...
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### Autocorrelation of residuals in my VAR model

I am running a VAR model to predict the flow of consumer loans (dependent variable). I have three independent variables (consumption of durables goods, employment rate and households GFCF). Each ...
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### Asymmetric VAR Models

I know that VARs employ the same number of lags for each variable in the model. However, what if we were dealing with a scenario where each variable in the VAR model has a unique number of lags. Thus, ...
1 vote
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### Interpretation of impulse response analysis - Cholesky decomposition output in R

I am doing an impulse response analysis involving 3 time series A, B, and C in R. Following Lutkepohl approach, I used the log and diff functions to make them stationary. After creating the VAR model, ...
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### Likelihood function of VAR-MGARCH-BEKK model?

I am doing my dissertation on the spillover effect between countries' markets and looking to use VAR-MGARCH model to do it. For example how would a change/shock of US market index affect Thailand ...
1 vote