"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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7 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 ...
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12 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 ...
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0answers
18 views

Using VAR in R to estimate the effect of oil prices on stock returns [on hold]

I am having some problems with estimating a VAR in R. I am trying to replicate a study from Park and Ratti 2008 Using a time period from January 1997 to February 2016, I have been able to perform ...
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0answers
7 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 ...
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0answers
30 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 ...
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7 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 ...
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1answer
20 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 ...
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0answers
34 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). ...
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18 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 ...
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1answer
17 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 ...
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0answers
15 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
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1answer
36 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 ...
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0answers
10 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 ...
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0answers
23 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 ?
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1answer
51 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 ...
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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} ...
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1answer
55 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 ...
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0answers
23 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
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1answer
37 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 = ...
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0answers
21 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
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1answer
32 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
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0answers
62 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 ...
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0answers
31 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
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1answer
52 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
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1answer
38 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 ...
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0answers
28 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 ...
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0answers
10 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?
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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 ...
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0answers
27 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 ...
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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
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1answer
30 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 ...
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0answers
11 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 ...
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1answer
48 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 ...
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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 ...
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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 ...
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0answers
12 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 ...
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0answers
40 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
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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 ...
0
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1answer
72 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
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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 ...
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0answers
11 views

VAR model for variables of different frequencies

I am trying to capture the transmission of monetary policy in India. I am willing to take into account the effect of Non Performing Assets (NPAs) on the transmission from the policy rate to bank ...
1
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0answers
45 views

How to implement a SVAR with sign restrictions

I am trying to estimate a bi-variate sign-restricted SVAR with daily oil and stock prices and two shocks (demand and supply). The ultimate goal is to explain how much of the recent fall in oil ...
1
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1answer
90 views

Multicollinearity, variable selection for cointegration testing in ARDL and VECM/VAR frameworks

I have 15 variables some of which are highly correlated. I want to run a cointegration test in the ARDL and VAR/VECM frameworks. Due to the correlation multicollinearity is a big problem; however, I ...
4
votes
2answers
120 views

Covariance of two time series driven by a restricted VAR(1) model

Suppose that I have two time series $X_n$ and $Y_n$ where: $$ X_n = \rho_x X_{n-1} + \epsilon_n $$ and $$ Y_n = \rho_y Y_{n-1} + \rho_{xy}X_n +z_n $$ Here, $z_n,\epsilon_n$ are independent random ...
3
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1answer
69 views

Modelling stationary and integrated time series in one system

I am currently investigating commodities and their impact on the oil price. I have 8 variables of different stationarities $y$ = dependent variable (oil price) is non-stationary I(1); three ...
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0answers
67 views

Vector autoregression: many variables (10), short sample (100)

Suppose there are ten observation sites along the road. A, B, C, D, E, F, G, H, I, J. We obtain data at each site once in a day, in this order. That is, first go to the site A at 9:00a.m., and when ...
0
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1answer
105 views

VAR/VECM/ARDL optimal lag selection

Question 1: Is it necessary to consider AIC and the BIC criteria when selecting the lag for a VAR, VECM or ARDL model OR can I use something else? Example: Can I pick 12 lags because the model simply ...
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1answer
61 views

Varying orders of integration - VAR/VECM model

I am building a VAR model, and have gotten a thorough set of guidelines through a question I asked a little while ago. However, I am left with some questions based on the following quote from Step 3 ...
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1answer
58 views

Vector autoregression for mix of stationary and nonstationary variables

I am currently investigating the impact of certain indicators such as GDP and inflation on the stock market. However some of my variables are non-stationary and some stationary in levels. All ...
0
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0answers
10 views

GLS estimator of a VAR process

I'm studiying how to derive the GLS estimator of a VAR process. I have studied the basics well, but I don't get the last passage here: Why the product can be rewritten as a quadratic form? Intuitively ...