"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 ...

learn more… | top users | synonyms

0
votes
1answer
7 views

Is ARCH test mandatory for VAR?

Is ARCH test mandatory for VAR? If so, what lag length of the ARCH test should I use? The same as the lag length of my VAR or VEC model?
0
votes
0answers
18 views

Why do VAR forecasted values radically change depending on which month historical data end?

I am building a model to forecast housing variables using vector autoregression. I am encountering spurious results. My forecasted values change dramatically depending in which month the historical ...
-1
votes
0answers
9 views

What to do about “sounds like spam” error? [migrated]

I attempted to post a detailed question, focused on conceptual and statistical issues, not coding. The site rejected my post with an unexplained error message that my post looked like spam. I also ...
0
votes
1answer
70 views

Testing for cointegration and building a VEC model

I have 3 variables which are all stationary at 2nd order difference. I want to check for cointegration using the piece of code below. If I run pairwise cointegration analysis then I get these results: ...
0
votes
1answer
22 views

R: vector autoregression with penalty for non-cointegrated factors

I can perform a vector autoregression using the "vars" package in R. library(vars) data(Canada) VAR(Canada, p = 2, type = "none") But as I understand it, vector ...
1
vote
0answers
16 views

Testing for differences in variation between variables

I am trying to find out whether it is true that variation in expenditure is greater, for more narrow subsets. e.g. is it more likely that an individual buys an orange instead of an apple, than it is ...
2
votes
1answer
28 views

VAR model interpretation: Coef vs Impulse response functions

In courses such as time series analysis, we learned that the relationships derived from impulse response functions or Granger causalties are more interesting than the estimation output. I was ...
0
votes
0answers
50 views

VAR model selection, auto-correlation specification issues

I am encountering the following problems and I don't really know which model a should pick. All model selection criteria indicate that I should take the model with 1 lag. After building the ...
0
votes
0answers
19 views

How to impose exclusion restriction on cointegrating vector? R reproducible example

The code given below estimates a VEC model with 2 cointegrating vectors. It is a reproducible code, so just copy and paste into your R console (or script editor). ...
1
vote
0answers
24 views

Comparing unit root tests

When comparing the results of different unit root tests (in this case DF-GLS test with and ADF test), should I keep the lag length fixed for both tests, or am-I allowed to use predefined/suggested ...
0
votes
1answer
25 views

VAR model: include all lags up to AIC-suggested order or just the significant ones?

I'm building a regression model in which I have a dependent variable OSE, and two independent variables, MSCI and Brent. In this model I wish to include lagged variables. I performed an AIC for my ...
0
votes
1answer
12 views

Global VARX model?

I am looking for a way to compute IRFs for the following setup. Cross country dimension (country level data) Time dimension (60 periods quarterly data) 3 endogenous variables (VAR) 1 Exogenous ...
0
votes
0answers
19 views

Should I use a VAR or VECM to model a time series in which one variable is stationary?

I was wondering which of the above two models would be most suitable. I'm modelling the relationship between interest rates, unemployment, CPI, GDP and London house prices (all UK data). I was going ...
1
vote
0answers
10 views

Compute Forecast Error Variance Decomposition for variables outside the Vector Autoregression

I am replicating the paper of Ang and Piazzesi (2003) in the Journal of Monetary Economics (link: here) where they estimate a Vector Autoregression for both unobservable factors and observable ...
1
vote
0answers
41 views

Breusch–Godfrey test under heteroskedasticity

Do I need to account for heteroskedasticity when performing the (vector) AR1-2 test? The Autocorrelation (AR) 1-2 test is defined as follows - often reffered to as the Breusch–Godfrey test (Wiki ...
1
vote
0answers
11 views

VAR impulse response interpretation when differencing

I am trying to formulate a way of how to think about differencing when interpreting impulse responses produced by VARs. There are two different views I came up with. First view is that a temporary ...
0
votes
1answer
23 views

Impulse response stablity in a VAR model

I am trying to fit a 3 variable VAR model and I need to check if the qualitative features of impulse responses are approximately stable across subsamples. But I am not sure what impulse response ...
1
vote
0answers
49 views

Estimating a restricted (sparse) VAR in R [closed]

Assume that I want to estimate a VAR or SVAR model for some monthly economical time series without a long history (i.e. in the range of 2000-2016, which consists of only ~180 data per variable). ...
1
vote
0answers
21 views

Replicate cointegration rank statistics using a 9 variable VAR(2)

I am trying to replicate Tables 3 and 4 from the paper "A Long Run Structural Macroeconometric Model OF the UK" by Garratt et al (2003). Using the Akaike criterion the authors decide to proceed with ...
0
votes
1answer
20 views

Autocorrelation of VAR residuals

I am fitting a VAR model on 50+ timeseries that both have two variables, x and y. I am trying to identify if my bivariate VAR model has sufficient amount of lags. AIC nad SBIC both suggest using 2 ...
0
votes
0answers
23 views

How to code dummy variables for structural breaks in VAR

This question is really 2-in-1: 1) How do I code dummy variables for the following series that has 2 structural breaks in trend; an initial upward trend, then a much flatter upward trend, then ...
3
votes
1answer
39 views

Variance of a multivariate AR(1) process

I have a multivariate AR(1) process (first-order vector autoregression, VAR(1)) of the form $$ \pmb X_{t+1} = A \pmb X_t + \zeta_t $$ where $\pmb X_t$ is a vector, $A$ is a matrix and $\zeta_t \sim ...
1
vote
0answers
11 views

Nonstationary (but not I(1)) components in VAR model. What should I do?

I have several time-series, which are non-stationary, but it looks like they have a number of structural breaks, resulting in different trend coefficients. I need to estimate a VAR model and make ...
0
votes
0answers
29 views

lag length selection in VAR model

I want to study the impulse response function and the variance decomposition by fitting a var model. The lag length criteria gave me this result. What's the problem ?
0
votes
1answer
56 views

Choices of priors for time-varying-parameter VAR in Primiceri (2005)

The main idea of the question is how to choose priors' parameters for the time-varying-parameter VAR model. I am really confused in the way Primiceri (2005) constructed priors in his paper under the ...
0
votes
1answer
17 views

GARCH Markov representation

I'm studying the Markov representation of a GARCH(p,q) process, i.e. $$\boldsymbol{v_t} = \boldsymbol{u_t} + M_t\boldsymbol{v_{t-1}}$$ where \begin{equation} \boldsymbol{u_t} = \begin{pmatrix} ...
0
votes
1answer
58 views

Why can't I get rid of serial correlation in lag length selection?

I'm doing a statistical study based on the USD price of Bitcoin, including explanatory variables like Google Trends data, Dollar strength, stock exchange etc. Setting up a VAR in levels for lag ...
0
votes
1answer
33 views

Counterintuitive impulse responses in a SVAR model, why?

I did a study with structural vector autoregression (SVAR model) corresponding to the IS-LM model (a macroeconomic model). I have four variables that are I(1). I have fitted the SVAR model to the ...
1
vote
1answer
50 views

VAR - ARCH LM Test results are conflicting

I'm using the R package vars to model multivariate series with VAR of order p = 5. The multivariate series is: $$ Y_t = ...
0
votes
0answers
26 views

Inclusion of exogenous variables and prediction of TVAR models (tsDyn package in R)

I'm trying to use the function TVAR from tsDyn package in R, but I'm having problems in including exogenous variables. Also, I still haven't found a way to predict ...
1
vote
1answer
36 views

Marginal vs. conditional models of vector autoregression (VAR)

I have a vector autoregression, VAR(1). All random variables are weakly stationary and our white noises are all iid: ...
1
vote
0answers
78 views

Difference between VAR vs SVAR

I've problem with the difference between the VAR and the structural VAR. I've read books and articles but I don'get the difference between these two since we use lower triangular matrix when imposing ...
1
vote
0answers
33 views

Choosing lag length for VAR

I've got 2 questions about this. I'm fitting a VAR in levels in order to select lag length for Johansen cointegration tests. All my data are in natural logarithms. 1) All my variables are I(1) except ...
0
votes
1answer
83 views

Interpreting VAR impulse response

In R, I have two variables, x and y, and a basic VAR model with just one lag, i.e. (as I understand it) the model basically is: ...
1
vote
1answer
71 views

VAR model: many parameters, but short time series

We are wondering how many degrees of freedom are sensible in a model and if there is a rule of thumb. We have a time series of 57 periods, with 4 endogenous variables and 3 exogenous variables in a ...
1
vote
0answers
31 views

Cointegration test with I(1) and I(0) variables

I have four variables, three of them are I(1) and one of them is I(0). I'm using STATA as my software. Can I use Johansen's test to check for cointegration? I understood that all variables should be ...
0
votes
0answers
12 views

Regular vs long run SVAR estimates

What is the difference between regular and long run SVAR model? I don't understand how the matrices with restriction are different. Is there a different number of restrictions for the long run case?
1
vote
0answers
20 views

What would be an apporiate model for regressing multiple non-stationary time series data?

I have non-stationary time-series data (stationarity tested using ADF Test) for variables such as stock market returns, money supply, interest rates, exchange rate, inflation,etc. and I want to study ...
2
votes
0answers
34 views

Lag length selection in levels-VAR before VECM: inclusion of exogenous variables

I am trying to estimate a VECM and I read in Asteriou´s book "Applied Econometrics" that "The most common procedure in choosing the optimal lag length is to estímate a VAR model including all ...
0
votes
1answer
20 views

Inverting logarithmic output from VAR model

I'm working on a VAR model and am doing a log transformation of the raw data. x = log(x) After differencing, running various tests and running a VAR(2) model, I ...
1
vote
1answer
34 views

VAR-model with a contemporaneous variable

I have two time series and I want to check the relationship between them. I would like to use vector autoregression (VAR) model to do this. I'd like to specify the model so that both variables will ...
0
votes
0answers
12 views

Interpretation of signs for first differenced lagged variable

Question: How to interpret a coefficient sign switch for lagged variables when theoretically they should have the same sign. This can be in for example a VAR framework. Example: I do a regression ...
0
votes
1answer
50 views

Forecasting methodology and k-fold cross validation for a vector autoregression

This is a follow up question the question that can be found here, and is a result of me having implemented (after as careful evaluation as I'm capable of) the alterations and changes suggested. Below ...
0
votes
0answers
12 views

What should be variables stationary status in var model?

what should be in var model stationary status ? ı mean should we add variables level status or their first difference I(I) ? I know variables should be stationary ay first difference but are we adding ...
1
vote
0answers
21 views

Should maximum likelihood estimate give same result as MLS for VAR model with time trend?

Question: For a VAR with a time trend, like (1), should the MLS estimator be the same as the maximum likelihood estimator? A more lengthy discussion/statement of the question follows: So I have been ...
1
vote
0answers
13 views

How many lags do I use for a VEC model with 4 endogenous variables for Residual Analysis?

I have 4 endogenous variables with 120 observations each. I would want to test for Autocorrelation using Portmanteau Test and LM-Type Test, for ARCH Effects using Multivariate ARCH LM Test, and for ...
1
vote
0answers
58 views

SVAR with sign restriction in R

I am working on a structural VAR model in R, and I'm trying to implement sign restriction. I have the model below, but instead of the zeros in the matrix in equation 18, I need to limit the values to ...
0
votes
0answers
20 views

Vector Autoregression for modelling log-returns?

I am wondering if Vector Autoregression (and other autoregressive models) is a sound modelling for the daily (not high-frequency!) log-returns of time series from liquid financial markets. One can ...
1
vote
1answer
98 views

ARIMAX vs VAR comparison

With a time series Y of interest and another time series X that possible explains a part of Y, I came up with using ARIMAX and VAR models to model. What is the difference? Thanks,
3
votes
0answers
36 views

Variable selection / identification of genuine effects in a large-dimensional VAR model

There are 100 commodities that I am tracking. As I attempt to improve my time series models, VAR and VARMA look like they might provide some improved predictions. All of the literature I find on ...