"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
17 views

How could I use VAR model for nonstationary series?

I have five independent variables: oil (stationary at level), f (stationary at level), k ...
0
votes
1answer
54 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 weeks ...
0
votes
1answer
28 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: ...
1
vote
0answers
29 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 to forecast variable $x_1$. I know ...
0
votes
1answer
27 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 ...
0
votes
0answers
20 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 ...
-1
votes
1answer
37 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 ...
0
votes
0answers
9 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 ...
0
votes
0answers
23 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 ...
0
votes
0answers
46 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
vote
0answers
52 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 z_2t the inflation rate,in percentage, of the U.S. monthly consumer price index ...
0
votes
0answers
29 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 ...
0
votes
0answers
42 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 ...
0
votes
0answers
15 views

VaR using GARCH

...
2
votes
1answer
29 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 ...
0
votes
1answer
35 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
votes
1answer
39 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 ...
4
votes
0answers
72 views

Restriction matrix for a VAR

In New Introduction to Multiple Time Series Analysis by Luetkepohl (2005), section 5.2.1, it says that one can specify linear restraints for a VAR, $Y = \beta X + U$, in the form $$ ...
0
votes
1answer
134 views

VAR and Granger causality test

Is it necessary to calculate VAR before Granger causality test so that we can have the lag length to be used in Granger causality test
1
vote
0answers
71 views

Effective Sample Size for posterior

I am trying to implement unsuccessfully a function in matlab, to compute the effective sample size after a MCMC chain, with a posterior with 3 coefficients. Source: Sims MCMC $ VAR(1) / Y_t=\mu ...
1
vote
0answers
88 views

Guides to VARMA modelling in R

I'm looking at using a VARMA model to both determine the driver so value in some advertising campaigns and also to forecast future activity. I'm looking at the paper by Takada and Bass as a reference ...
0
votes
0answers
56 views

Granger Causality test with dummy variables

I intend to assess Granger Causality between three endogenous variables, where one of these variables is a dummy variable, indicating specific events during the continuous time frame. I was ...
0
votes
0answers
19 views

Holtz-eakin, Whitney, Rosen Panel VAR

I'm trying to write a bit if R code to run the estimator in "Estimating Vector Autoregressions with Panel Data" Econometrica 56-6 (1988). I'm stuck on equation (3.12) I feel like $Z_{ir}$ and ...
1
vote
0answers
12 views

References suggested for multivariate analysis of several similar time series

I have a time series dataset that reports the hourly page views and social media shares of online news stories. What I hope to obtain is the relationship between the two variables. I would imagine ...
0
votes
0answers
24 views

VAR model and forecasting

I worked on obtaining a stable vector autoregression (VAR) model for my dataset consisting of 3 different dependent variables. Then I tried to forecast each of the variables. As I looked at the ...
1
vote
0answers
27 views

Interaction in time series analysis

I have three different physiological variables--heart rate, respiratory rate and blood oxygen saturation, each as a time series. I am trying to study the interaction between the variables as they ...
0
votes
0answers
11 views

Comparing IRFs derived from Bayesian VARs with other extraneous information

I was wondering if anyone here could help me with the following: I estimate a standard Bayesian VAR with Normal-Inverse Wishart priors. I identify some policy shock in it, and then derive the IRF for ...
0
votes
0answers
121 views

Outlier treatment in Vector Autoregression (VAR) Model using vars package in r

I have the same problem as the following post, but I have more samples and the index of the outlier is known. Outlier treatment in Vector Autoregression (VAR) Model I tried deleting the outliers; ...
2
votes
2answers
67 views

How to analyze multiple variable time series - suggest references

I have multiple environmental time series variables (for example: temperature, dissolved oxygen, conductivity, depth) measured every few minutes for several months. The variables are measured at ...
0
votes
0answers
24 views

Postestimation results after VAR analysis show autocorrelation in residuals

I'm performing a VAR analysis on news effects and S&P500 returns. Now, I specified the number of lags (5) according to Schwarze's Bayesian Information Criterion (SBIC) and ran some postestimation ...
1
vote
0answers
42 views

Should I log transform my volatility variable?

I'm wondering if my volatility factor is specified correctly. My data consists of log returns on the S&P 500 index, a measure of news sentiment, and a newscount variable (# of articles published ...
0
votes
0answers
36 views

What is the difference between vector error correction model and UVECM?

What is the difference between vector error correction model and UVECM? Which one is better to use for a 30 years time series data (to study long term and short term relationship) which has some ...
0
votes
0answers
18 views

Initial Parameters for VARMA models?

I want to estimate parameters of VARMA model using maximum likelihood estimation using real data. The problem I face with is that I don't know how to set the initial values for the parameters. I ...
0
votes
0answers
160 views

Autocorrelation tests for time series VAR models

I have a VAR model in which I regress the monthly unemployment rate on itself lagged one month, the monthly GDP percent growth lagged by two months and two dummy variables. I am trying to test for the ...
0
votes
1answer
39 views

VAR model with zero coefficients

ll, I'm working with a bivariate time series $(X_{t},Y_{t})$. Looking at the two time series separately, $X_{t}$ appears to be white noise. This is supported by looking at the empirical ACF and PACF ...
2
votes
0answers
95 views

Understanding vec2var conversion in R

I'm using Bernhard Pfaff's packages {urca} and {vars} to analyze 3 time series. Each is I(1) and cointegrated with $r =2$ cointegrating relationships. The vec2var() command should make the ...
1
vote
2answers
76 views

how to do conditional forecasting with cointegration model?

I'm confused about multistep forecasting from VECM model for 2 cointegrated series. The model is pretty simple, in error-correction form: $$ \Delta x_{t+1} = \alpha_1 (y_t - \beta x_t -\beta_0) ...
0
votes
0answers
21 views

Construct matrix of stacked variables in VAR regression

I am trying to NOT use packages for the estimation of models in order to have a deeper understanding of how things work. Currently, I am trying to estimate a VAR(1) (vector autoregression of first ...
2
votes
0answers
72 views

SVAR Model with Short run restrictions

I am currently working on implementing SVAR model in an economic analysis. I have 10 variables in my analysis and currently struggling to incorporate the short run ...
0
votes
0answers
27 views

Estimating the parameters of a model, which method should I use?

I am trying to estimate a system of macroeconomic (simultaneous) equations, and I've learned about the 'existence' of various methods including Structural Equation Models, Simultaneous Equations ...
1
vote
0answers
40 views

Long Run VAR alpha and beta significance levels

I am using a VAR with 2 variables and 4 lags. I am combining the coefficients of these variables to get an overall alpha and beta value for in the form $Y = \alpha + \beta X$. In order to get the long ...
0
votes
0answers
64 views

VAR / VEC in levels or difference depending on Cointegration

Thanks in advance. I have four I(1) variables I'm trying to model by VAR/VEC. I know that it is only okay to model non-stationary variables in levels only if they are cointegrated. What I would ...
0
votes
0answers
60 views

Cointegration difficulties using Stata

I am working on a time series analysis with 52 quarterly data concerning a variety of possible determinants of CO$_2$ emissions by transport (CO$_2$ taxes, GDP, load factor, transport volume). This ...
0
votes
0answers
23 views

1-day VaR scaling for higher horizons

I have been reading about VaR scaling in "Market Risk Analysis" by Carol Alexander. It talks about square root of time (horizon) scaling is valid only if returns distribution is normal. For stable ...
1
vote
0answers
41 views

What is the best approach for a set of data that is irregular and uneven

I have a dataset with 975 observations from 112 different categories. The timespan of this dataset is 18 years. However, the data is unevenly spaced and even acquired: While some categories have only ...
1
vote
0answers
117 views

Alternating signs of significant estimates in VAR model

I have 6 variables and 125 observations, which I am modelling using a VAR model, in which I put all variables in as edogenous, as all relationships interest me (the bidirectionality). I have carried ...
2
votes
1answer
526 views

Significance of an impulse response function

I've read several paper that all compare different cumulative IRF of the same VAR equation for statistically significant difference. The IRF they use are simply the sum of the coefficients of the VMA ...
1
vote
1answer
836 views

Optimal lag length in VECM using vars R package

I have some series that are cointegrated, so I know that I should fit a VECM model. Nevertheless I found no guidance in finding the optimal lag length, say lagLength. I am using vars R package. ...
3
votes
0answers
66 views

Computing a multi-sample (i.e., pooled) Akaike Information Criterion

I have a set of multivariate time series observations that I am trying to model using VAR processes, using AIC to choose the best model. However, instead of determining the best model order for each ...
2
votes
0answers
131 views

VAR model with time series of different frequencies

In case I want to see the effect of two or more endogenous time series on each other, I use a VAR model. But how do I proceed if one data set is monthly, and the other one daily?