"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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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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15 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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25 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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31 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
35 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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20 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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20 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 ...
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2answers
115 views

How to calculate the impulse response function of a VAR(1)? (With example)

How to calculate: 1) Simple IRF 2) Orthological IRF (Y2 -> Y1) Of an unrestricted VAR(1) model: $Y_{1, t} = A_{11}Y_{1, t-1} + A_{12} Y_{2, t-1} + e_{1,t}$ , $Y_{2, t} = A_{21}Y_{1, t-1} + A_{22} ...
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1answer
27 views

How can we determine the sign of Granger causality in a >2 dimensional VAR?

As the title suggests, I'm trying to test for the sign of Granger causality in a large VAR. For exposition, consider the following three-dimensional VAR: \begin{align} \vec y_t=\vec ...
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30 views

Flat impulse response function

I'm doing a VAR at the moment involving 3 variables. CPI, interest rate and unemployment. Im getting strange results for my orthogonal impulse response function in that all of the impulses on ...
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1answer
49 views

How many lags should I include in the VAR-model

When building a VAR-model with six variables I had the following situation: after building a VAR(1) the overall portmanteau test says that the residuals are ok (p=0.85, p_adjusted=0.22). But when I ...
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36 views

SVAR with Taylor Rule

I am trying to replicate this paper (Stock, James H., and Mark W. Watson. 2001. "Vector Autoregressions." Journal of Economic Perspectives, 15(4): 101-115.) I am having trouble with the SVAR. They ...
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48 views

determinstic trend in VAR-models

I'm asking myself the following question. I want to build a VAR-Model with 6 time series A, B, C, D, E and F. I analysed every series univariate and I found out that A, D, E and F are stationary and B ...
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0answers
29 views

What is the logic behind using Adstock VS VAR style lag analysis for marketing mix models?

I'd like to discern why the adstock transformation is the default method to introduce lagged influence of prior time points i marketing mix models over a standard linear method as in VAR? I understand ...
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1answer
41 views

VAR Impulse response with dummies

I have dummy variables (DV) which measure policy reforms (e.g. Independence of the judiciary, barriers-to-entry in a market etc.). These can be either “0,1” or, say, “0,1,2,….. upper”. Say I have a ...
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0answers
24 views

Forecasting with use of PCA variables as independent and one ternary dependent variable in R

I'm having trouble in taking a direction of my research project. I have independent variables that are commonly used as economic indicators and I want to include variables/indicators that are not ...
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1answer
33 views

Vector Autoregression

I have a general question on VAR-methodology. In the case of asymmetric modelling I employ FGLS to exploit off diagonal covariance between residuals due to non-unique regressors between equations. Ok, ...
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1answer
29 views

Identities in a VAR model

I am working on a VAR model where one of the equations is an identity. For example: $$ \begin{cases} A_t = \alpha_{11} + \alpha_{12} A_{t-1} + \alpha_{13} B_{t-1} + \alpha_{14} C_t + ...
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15 views

Help forming a VAR model

Can anyone help me for a very basic VAR model for regressing Inflation (CPI first difference) on energy prices and money supply. any suggestions be appreciated.
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14 views

VARMA with t-student innovations

I'm wondering if there is a possibility to estimate VARMA model with t-student innovations in R. I found package MTS, but all models here seem to be estimated assuming multivariate normal ...
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0answers
62 views

Vector Autoregression, how to interpret Impulse Response Function (IRF)

I have an IRF that shows the GDP shock to GDP. Let's say I have a 5-year forecast of GDP. If there is an immediate 1% decrease in GDP today, can I adjust the original 5-year forecast by using the ...
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0answers
15 views

VAR model selection for forecasting one variable

Suppose I have a VAR model for variables $x_1$ through $x_K$. I will use the model to forecast $x_1$ a few steps ahead and will do this iteratively rather than directly. I am not interested in ...
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43 views

Forecasting with a VAR estimated by GLS versus OLS

Suppose I have a VAR model with different regressors in different equations (this could be due to restricting some coefficients of a full VAR($p$) model to zero or having some different exogenous ...
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1answer
86 views

Estimating VAR by GLS versus OLS: efficiency

Suppose I have a VAR model with different regressors in different equations (this could be due to restricting some coefficients of a full VAR($p$) model to zero or having some different exogenous ...
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0answers
14 views

Why do orthogonal complements come into play in the Granger representation?

Consider the Granger representation of a VAR model. (See : here). Can anyone explain me how in this representation Equation 1, page 4 the orthogonal complements of $\alpha$ and $\beta$ come into ...
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1answer
62 views

How do you simulate two correlated AR(p) time series?

I would be interested in the mathematical framework plus code in R if possible. Basically I want to find out the parameters of the two AR(p) models if I already specificed a certain cross-correlation ...
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0answers
17 views

Connection between discrete VAR(1) model and simple discrete Markov Chain

I have studied both Markov chains and Vector Autoregressive Models, and I am interested in the connections between the following models: Markov Chain: $$X_{t+1}=T*X_{t}$$ Where X is a vector ...
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0answers
67 views

lag length selection in Vector Error Correction Models

I am doing a VECM analysis in R using vars R package. My problem is to find the lag length of the VECM model to be specified. I a previous post I was suggested to use the VARSelect function. However I ...
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36 views

Vector autoregression (VAR)

In a VAR I use two price-variables which are co- integrated. Is that a problem, the literature is somewhat mixed? With three lags there are no problems with serial correlation between them ...
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1answer
36 views

Prediction in VAR models

I am currently developing a Vector Autoregressive Model, and I have the model fully specified as follows: $$X_t=AX_{t-1} +Z_t$$ where $X$ and $Z$ are $n \times 1$ column vectors, and $A$ is an ...
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0answers
35 views

Custom Impulse Response Functions for VAR

I am working on a VAR model for the Safe Assets in the U.S. economy. The demand for Safe Assets has increased as needs to pledge them as collateral, or the response after the '08 crisis has been risk ...
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129 views

Vector Autoregression - Model Selection in R

I have 50 time series and I'd like to form a VAR equation for each of the time series. I'm looking for a method to find the best subset required for each time series VAR equation. For instance only ...
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59 views

How many times can one difference time series data? [closed]

I am going to work on the impact of taxation on economic growth and I want to use VAR model and Stata software. What I want to ask is I have three types of taxes in my country, direct domestic tax, ...
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1answer
39 views

How could I use VAR model for nonstationary series?

I have five independent variables: oil (stationary at level), f (stationary at level), k ...
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1answer
119 views

Timeseries Analysis

I have the weekly time series data from 2011 to 2014 with 6 variables (Gross_Revenue, Attendence, Enrollmentcount etc.) and its having seasonality. I want forecast the Gross_Revnue for 2015 1st 15 ...
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1answer
40 views

Why is GARCH better?

I estimated Value at Risk of a portfolio using 10 years of daily data. The values of VaR I got by three methods is: ...
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0answers
71 views

Selecting an appropriate VAR model

I would like to receive critical comments on an idea explained below. Suppose I have variables $x_1$ through $x_K$, and this is a time series setting. My aim is forecasting. I know that all the ...
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1answer
48 views

Are VAR and VEC models theoretically neutral?

I have recently been introduced to Vector Autoregression (VAR) and Vector Error Correction (VEC) models in an Econometrics class, where both approaches were presented as a neutral way to test economic ...
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81 views

VAR model for price forecasting in multiple time-series context. How to get “real figures” as forecasts?

Sorry for the rather long introduction, but since I was (legitimately) critizised for not explaining my cause and questions enough, I will do so now. I would like to conduct a (price)-forecast based ...
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1answer
83 views

What does the Argument “type” in VAR() - function do?

Right now I am working with vector autoregressive models in order to make 3 months forecasts for a commodity good (sawlogs) y. I have several time-series of "follow-up-products" of sawlogs that should ...
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41 views

lag length selection for VAR

to estimate the VAR on which i then do the trace and max tests of cointegration, I use 4 different information criteria to decide how many lags. However, when testing the residuals, none of the lag ...
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0answers
52 views

How many lags for johansen and vecm model?

I want to use VECM model for return as dependent variable and I have 5 variables as independent; my data is monthly ...and my questions are: How could I know if I should use linear or non linear for ...
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0answers
191 views

Understanding / Interpreting VARselect function in R

Atm I am playing around with VAR-Models and I was asking myself how to properly use the VARselect function. My question is the following: What should I give R as y? In the Help it just states "Data ...
1
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1answer
126 views

Fit a VAR model with R

I have a bivariate time series z_t where z_1t is the change in monthly US treasury bills (maturity 3 months) and ...
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0answers
45 views

Time series forecasting with multiple series with constraints

Hello and thanks in advance. I am using ARIMA or VAR models to forecast sales revenue. Suppose I have three different time series in each of three categories (making 9 series in total). The first ...
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0answers
50 views

What is the source of nonstationarity in this VAR model?

I am trying to forecast a VAR model, which consists out of 5 variables with a monthly frequency. The problem is that the VAR model produces an unstable forecast and I am not sure what the source of ...
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0answers
30 views

VaR using GARCH

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1answer
40 views

What's the deal with VARs?

I'm new to econometrics/statistics. Why are Vector Autoregressive (VAR) equations considered a separate class of models in textbooks, apart from ARs? Isn't it true that you can estimate the equations ...
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1answer
77 views

Maximum lag length in cointegration?

I've got two conflicting answers when I search the internet for my question. Since cointegration is sensitive to maximum lag length, it is important to choose maximum lag length wisely. According to ...
2
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1answer
41 views

Does the average of the square roots of random variables mean anything?

I recently made a plot for work that used a signed square-root scale on the $y$ axis, for visual clarity. The $y$ observations are impulse response functions (IRF) of vector autoregressions computed ...