"VAR" stands for *vector auto-regression*, which is a multiple time-series model / method. VAR is common in econometrics, & allows each time-series to be modeled based on its own previous values, & also the previous values of each of the other series, simultaneously. Thus, the series are given equal ...

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Visualising ECM model

I'm presenting an error correction model to a somewhat non-technical audience and want to make as much of the presentation as possible visual. Does anyone have any tips or hints that could be ...
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1answer
9 views

Degrees of Freedom in VAR

A colleague of mine is using a VAR for quarterly data (deseasonalized). Typically it is customary to use lag of 4 or 5. However, they used two lags based on a single test result, the SC criteria. Of ...
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27 views

Fitting a VARMAX model using MTS library in R

I am trying to fit a VARMAX (vector autoregressive moving-average with exogenous variables) model to some synthetically generated data using the MTS library available in R. I found that there is only ...
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1answer
25 views

Predict VAR when exogenous variable was used

I estimated my model with VAR() of the vars package in R. I included an exogenous variable. ...
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24 views

cumulative Impulse Response Functions in R, error?

I am trying to calculate impulse response functions using vars package of Bernhard Pfaff. I am getting somehow confusing results. Running the following code: ...
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17 views

Cumulative vs. non-cumulative IRFs in R

I am using irf function from vars package. I am trying to derive cumulative IRFs. The following code describes the case of deriving cumulative IRFs: ...
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34 views

What is the correct unit root/stationarity test for this variable? Why do different tests provide different conclusions?

This is something of a follow up question to a previous question I had here: Can over differencing cause a singular matrix in a VAR model? A brief recap of what I am trying to accomplish: I want to ...
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24 views

Can over differencing cause a singular matrix in a VAR model?

I am using a VAR model to forecast employment in a city. I have 2nd differenced all of my variables and checked for unit roots via ADF tests. When running a VAR model on this data through R, I am ...
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21 views

t-test and Granger Causality give conflicting results?

I have run a VAR(1) model with 3 endogenous variables on Eviews, where all time-series of interest are stationary. It might be important to mention that the 3 variables are the reverse logistic ...
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10 views

How to specify VAR dynamics of factors in Dynamic Factor Model in R

I'm working on a forecasting model. The standard form for it is: $y_t=\Lambda^*f_t+u_t\\f_t=A_1f_{t-1}+...+A_pf_{t-p}+e_t$ where $f_t$ is a vector of factors obtained from Principal Component ...
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10 views

Covariance matrix of estimated parameters of SVAR

How to get covariance matrix of estimated parameters of structural VAR? Any reference, if possible. Thank you in advance.
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13 views

non significance of variables in my VAR estimate

I am running a VAR model with 7 variables, but less than 10 out of 49 independent variables are significance. What could be the problem please?
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18 views

Multivariate binary time series

I have several concurrent time-series, which have binary response: Yi = (yi1, ... , yiT) where yit = 1 or 0 at an observed time t. i = 1, ...,n (where n is the total number of concurrent time ...
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27 views

Unit root test results not stationary, can I apply VAR?

I am working on my project methodology, and I am planning to use VAR model. In order to proceed with VAR, I run my data thru unit root test in Stata, and found that my data is not stationary. Can I ...
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5 views

Robustness to deviation from normality with regularized VAR model - references

I was listening to a talk where the presenter was talking about using regularized estimation approaches in a VAR(1) model $$X_t = \Gamma X_{t-1} + \epsilon_t, \quad \epsilon_t \sim ...
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21 views

Software or workarounds for vector autoregression on count data?

I have a research question that fits nicely in a VAR framework but my data are count data. They are much closer to a Poisson or negative binomial distribution than they are to a normal. This will ...
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1answer
54 views

Theoretical concept of adding constraints to a VAR?

I was wondering whether someone can explain why one would add constraints to a VAR model. Recommendations to books / articles explaining these concepts in detail are greatly appreciated.
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1answer
42 views

Correct Unit Root Testing

I have a few time series of variables with each 40 monthly observations. Now I want to test each variable for Unit Root (non-stationarity). My Question: How to choose the optimal lag length when ...
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1answer
27 views

Vector autoregression model with unit root in the exogenous variable and endogenous variables

I was wondering whether I should worry about the fact that I have one unit root in my exogenous variable. I think based on what I understand that I should first difference the variable with unit root, ...
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13 views

Interpreting mean of coefficients by accessing $Beta in BMR package in R

I've been using BMR (Bayesian Macroeconometrics in R) package to carryout BVAR(Bayesian Vector Auto Regression). When defining the Minnesota prior for my monthly dataset and have obtained mean of each ...
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31 views

Vector Autoregressive Model: residual's kurtosis proportional to number of lags?

I have some transformed data set (windspeeds that are nearly-weibull-distributed). I transformed this data which results in near-normal distribution (close to no excess kurtosis and skewness of zero). ...
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23 views

Testing for structural break in the covariance

I estimated a bivariate VAR(p) model and assume that there exist two covariance regime $\Sigma_1$ for the period 1 to $T_B$ and $\Sigma_2$ for the period $T_B+1$ to $T$. I am now interest in testing ...
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6 views

Relation Between Lag length of ADF test and Lag of VAR After that

Suppose I have three variable and they are difference stationary at different lags. How should I decide the no of optimum lags in the VAR of the three variable? I understand the lag length criteria of ...
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43 views

What is the difference between “lag order” and “maximum lags”

The R Vars package has a Vector Auto Regression function called var. The arguments include (among other things) "p" defined as the "Integer for the lag order" and "lag.max," which is defined as ...
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2answers
30 views

How can I forecast interrelated hierarchies?

I need to model demand for server components. Server 1 & Server 2 both use Hard Drive B, Server 1 uses Network Card A, and Server 2 uses Network Card C. ...
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30 views

How to quantify the impact of a variable in a VAR model equation?

Given a VAR model (the equations that make the model, coefficient significance and the adjusted $R^2$ value for each equation), is there a way to calculate the impact of a variable over the other?
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1answer
56 views

Linear VAR impulse responses - sensitivity of confidence interval bands to shock size

My main question is: is the statistical significance of an impulse response in a linear VAR dependent on the size of the shock? Or put alternatively, how do the upper/lower confidence interval bands ...
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18 views

Estimate VAR model from data about lags

Does anybody have any idea how i would write the var model based on this table? What coefficients should be included? Any hint will be much appreciated. Thank you!
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1answer
35 views

Why Granger causality test gives same result for restricted and unrestricted VAR models

I applied granger causality test 1st in unrestricted 2 dimensional VAR(1) model and then restricted model (t>2). Both are giving the same result (the result of unrestricted VAR model). Actually ...
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15 views

All of the series used in a model must be stationary at the same order of differencing

While practicing VAR analysis, all of the series used in the model must be stationary at the same order of differencing. Is this correct? For example, let $X$~$I(1)$ and $Y$~$I(2)$. Can I use these ...
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1answer
44 views

Does VECM use the stationary series or the originals ones?

I have some cointegrated series and I decided to build a VECM model. (I differentiated them twice in order to get stationary series and that led me to believe that they might be cointegrated - I ...
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1answer
54 views

Finding optimal lag order for an exogenous regressor in a VAR model

I can't use VARselect as it gives lags in a VAR model which considers all the variables to be endogenous. In my case, one of the variables is exogenous and affects dependent variable with a certain ...
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1answer
65 views

VAR Model- Impulse Response Function Y-axis

I read different papers which try to analyse the relationship between oil and macroeconomics with the help of a VAR model. The results are explained in graphics which show the impulse response ...
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28 views

Bayesian VAR, IRFs and unit roots

I estimated VAR using Bayesian inference. Then I calculated roots of the characteristic function of this VAR. The biggest root was greater than one. Also I tried to make all series stationary before ...
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2answers
94 views

What is the best model for time series data with independent and dependent variables

I have two different variables across a time series over a couple thousand time steps. I want to predict the values of the dependent variable (y) based values of the independent variable (x) in the ...
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29 views

Augmented Dickey-Fuller test with time trend term

I have time series variable X, Y and Z. I need to analyse these variables by using a VAR model. Before running a regression I did augmented Dickey-Fuller test and found that one variable is stationary ...
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1answer
65 views

Lag length selection for a VAR model

The model I am working on has 4 time series (X, X1, X2, X3). Lag lengths are 5, 1, 4 and 6, respectively. X1, X2 and X3 are stationary at level and X is stationary at second difference. I am applying ...
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39 views

Inverting a VAR - looking for a good resource

I am having trouble with something that should be pretty basic. I need to invert a VAR (vector autoregression). Everything I have read just brushes past the actual inversion process, taking for ...
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67 views

How to explain to laypeople that in a VAR model some variable explaines its own variance?

Background: I observed that people not familiar with vector autoregressive (VAR) models often struggle with the interpretation of a forecast error variance decomposition. I am frequently asked, why a ...
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1answer
115 views

Interpretation of VAR and causality

I have two time series(X1 and X2) each having 900 records. I wanted to establish relationship between them and put it in ...
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1answer
51 views

Jarque-Bera test mandatory for VECM and VAR?

What tests do I need to perform for VECM and VAR to be considered robust? I know LM test for residual autocorrelation is mandatory, but what about Jarque-Bera test? Is that necessary?And what should I ...
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1answer
148 views

Time series Analysis - VAR or VECM

I have 4 time series. One of them is stationary and rest of them are not. I need to find relation between them. I will use AIC to decide lag length. Should I use VAR or VECM to find relation between ...
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25 views

Contemporaneous regression in R (VAR model)

I have two time series and I want to check the relation between them. I am using a VAR(3) model. I would also like to include the contemporary variable, something like this: Can we do this ...
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117 views

VECM model output - where is the long run relationship?

So I'm getting the following EViews output, but where on earth is the long run relationship? Do I have to estimate it separately using OLS? If you have to estimate it yourself via OLS, I've already ...
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40 views

lag number in VAR

I am trying to determine the optimal lag number in 2-equation VAR as follows: 1. choose lag based on information criteria 2. estimate the model using # of lags determined above and test for ...
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82 views

Vector autoregressive model selection process and relationship with cointegration

Let's say you're looking at two securities that trade closely with one another and you suspect you can somehow trade the spread. How can you use VAR models to estimate the relationship between the ...
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67 views

orthogonalized impulse response's contradictory forms in a VAR(p) model

I have so far discovered three different ways of utilizing the Cholesky decomposition for calculating the OIRFs of a VAR(k). The different methods seem contradictory so I would like some input on ...
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1answer
81 views

What can be inferred from “covariance matrix of residuals” and “correlation matrix of residuals” after VAR?

I have this VAR: summary(VAR(V6CADModelSt45obs1D.df[,c(5,3,2,6,1,4)], p=5, type="none", ic="SC")) The following is the result of this VAR: ...
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29 views

Out of sample VAR in R [closed]

I am looking to write code in R for out-of-sample forecasting with a VAR model. My data is quarterly from 1985:Q2 to 2013:Q4. I use an initial sample of 1985:Q1 - 1994:Q4 and expanding samples ...
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37 views

Calculating Marginal Data Density for VAR Model

I am currently estimating Bayesian vector autoregressive (BVAR) models and I would like to do model comparison with Bayes factors. I have read about the Gelfand-Day method, the Geweke (1999) modified ...