Questions tagged [var]

Vector Auto-Regression, 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 status.

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How to obtain Covariance-variance matrix for VECM

I am trying to conduct a causality analysis with a VECM, and I am looking for ways to extract the Covariance-Variance matrix and the correlation matrix from the fitted VECM using the already existing ...
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VAR obtained from vec2var() and and regular VAR giving different IRF and OIRF

I am currently trying to generate the orthogonal impulse response functions (OIRF) of a VECM with two variables. Both variables are I(1) and there is definitely a cointegration at all levels as tested ...
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Unstable panel VAR / PVAR

Quick question on PVARs. I am using Stata's user-written pvar package. After running the unit root tests using xtunitroot, I ...
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21 views

Stationary VAR( 1) process : complex eigenvalues

For a stationary Vector autoregressive process of order 1, eigenvalues of A should be smaller than one. However, I am getting some eigenvalues as a complex number after the estimation. however, the ...
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14 views

Impulse Responses Generation in Vector AutoRegression in EViews

I have all the positive time series data of 6 variables. On these six variables, I have applied VAR model and want to generate impulse response functions. But impulse response functions are not ...
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VECM: Why does Speed of adjustment/Error Correction Term have to be a matrix?

From what I understand, Loading matrix, or alpha, is the same as Error Correction Matrix, which also refers to the speed of adjustment. However, if the speed of adjustment measures how many percentage ...
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28 views

Level VAR stability for VECM estimation

I am trying to estimate VECM model for I(1) and cointegrated data. First, I try to find the optimal number of lags by using VARselect by following the below steps: level data is given to VARselect, ...
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Granger Causality: Sum of errors vs. determinant

I have been measuring Granger Causality between pairs of vectors processes (i.e. 2 vectors consisting of multiple time-series variables). Most of the equations I find in references utilize a ...
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How to apply VAR model for a I(1) and other I(0) variable? Objective is to forecast [duplicate]

I am modeling liquidity variable, real money growth with real asset price returns. The former is I(1) and the latter is I(0). The objective is to see the predictive power and forecast. However, can we ...
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How to interpret impulse response analysis in VAR when using standardized variables?

How to interpret impulse response analysis when using standardized variables (ie., subtracting the mean and divide by standard deviation) in vector autoregression analysis? The reason why I ...
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How to choose drivers for forecasts based on vector autoregression

as mentioned in the title my question is how to choose from a large set of time series the best Driver for a forecast based on vector autoregression. I am sure that this question is very general. I ...
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Vector Autoregression with Trials

I want to use VAR model on my data. In addition to typical two dimensions (variables, time steps), I have a third dimension, namely the repetitions of the same experiment. Can you recommend a ...
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28 views

How to generate a VAR(1) model? [closed]

I already written the code but something went wrong and I don't know why... here is the code. ...
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103 views

Open source code for factor-augmented VAR (FAVAR) model

I am looking for an open source package (R, Python, Julia) that has an implemented FAVAR (factor-augmented VAR) class for time-series prediction problem. I've already tried to use several solutions ...
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Removing Influence of Other Time Series in Multivariate TS Analysis

I have some non-periodic time series that are all correlated. In the absence of the others, each time series would consist of a set of responses to events. I don't know the duration or shape of each ...
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32 views

Omitting certain time periods in VAR

I am using a vector autoregression with a monthly lag, and wish to not include certain months, as they are outliers in my analysis and may distort findings. Is estimating such a VAR (using OLS, then ...
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Can VARMA handle non-linear data?

I know that traditional ARIMA models cannot handle non-linear data but I was unable to find any place where it states whether if VARMA can handle non-linear data or only linear. Please clarify this ...
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Is there any benefit of using GLS when the regressors are identical

I am reading Greene, Econometric Analysis, 7th Addition, I am seeking a point of clarrification. "The case of identical regressors is quite common [think a VAR mode].... In this special case, ...
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53 views

Estimating a VAR using OLS vs GLS

I have read in several places that I can estimate a VAR model equation by equation using OLS instead of using GLS, if I have the same explanatory variables. Do I need to make any assumptions about ...
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Estimating a VAR model via OLS

I am looking at Vilasuso (2001), who says that when using least-squares to estimate causality in mean, there is significant size distortion if the conditional variances are correlated. My question ...
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Heteroscedasticity in VAR Residuals and Least Squares

If I have a VAR model, think of the simple case with two variables $y_1$ and $y_2$, Vilasuso (2001): says that if the conditional variances of $y_1$ and $y_2$ are correlated, significant size ...
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Orthogonalised Impulse Response Functions in Stata

This might be a really basic question for some of you but I have been looking up how to interpret impulse responses but most of the answers that were presented did not quantify the responses but ...
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53 views

VARX model on non -stationary timeseries

I am going through the lecture notes on VARX by Dr Tsay Pg 11-22 Link Plot of endogenous and exogenous series shows that these are not stationary. Pg 15 shows lag 2 VAR model is fit at level. Not ...
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68 views

Deriving the Cointegrating Equation in a VECM model

I am teaching myself econometrics and I am having trouble understanding how the cointegrating equation in VECM is derived. Lets say we have two variables, Consumption and Income. As I understand it, ...
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24 views

Inference in cointegated VAR model

I am estimating the following VAR model: \begin{equation*} x_t = k + A_1 x_{t-1} + A_2 x_{t-2} + \dots + A_p x_{t-p} + \epsilon_t, \end{equation*} where $x_t$ is a vector of variables and notation is ...
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121 views

AIC, BIC values keep changing with lag.max in VAR model

I'm using a VARselect function from vars package in R to select order for my model. My data set has 2 time series with 21 data points. When I give ...
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Do vector autoregressive models require stationarity?

Some say yes and some no (note I am ignoring here the issue of cointegration). Say there is no cointegration.
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112 views

Vector Autoregression - How do we choose the correct value of p?

I am following this article: https://otexts.com/fpp2/VAR.html#fn24 ...
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35 views

Panel VAR impulse response interpretation?

Quick question on panel VARs. The equation is: $$Y_{it}=a_i+\Pi Y_{it-1}+\epsilon_{it}$$ In estimating these models the fixed effect $a_i$ is often removed by differencing or forward demeaning, and ...
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22 views

Can I use VAR model on I(1) series with cointegration? [duplicate]

I have four I(1) series, and the Johansen test(ca.jo()) shows there is one cointegration. My purpose is to forecast, so I want to compare the forecasting results of VAR and VECM model. Is this ...
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Approximation in Impulse response calulation

I am dealing with the calculation of the impulse response functions in a VAR Model and I'm not sure I got it right. What I understand: The orthogonal Impulse Response function is a $MA(\infty)$ ...
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37 views

what does it mean to run a time series model in levels?

I have seen the phrases running a var in levels and running a var in difference very frequently, either on this site or elsewhere. I understand running a var in difference basically means to ...
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Why do we need a VECM specification if the I(1) processes are cointegrated?

I happened to question the rationale of employing VECM, since some empirical studies like Basu (2017) employed a VAR model to obtain impulse-response analysis. As far as I know, one should consider ...
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VAR order in Cointegration Test

I am studying Johansen's Test using Tsay's book (Multivariate Time Series Analysis). The book has given some sample results of function ca.jo in r package ...
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How can I recover full dimensional VAR model coefficients after fitting a VAR model to a dimensionality reduced (via PCA) dataset?

I am using PCA to reduce dimensionality prior to fitting a multivariate time-series dataset to a VAR (vector autoregressive) model. Is there any way to convert a PCA-derived VAR model to a full ...
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Are trend-stationary series I(0)?

I have time-series of different interest rates. Graphs of all series show existence of trend. For some of these series ADF-test with constant rejects null hypothesis. For others, null hypothesis is ...
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67 views

How to determine the bandwidth parameter? Newey-West

How to determine the bandwidth parameter? Following from the below paragraph is it easy to understand how Newey and West determine the bandwidth? "The heteroskedasticity consistent estimator (HCE) ...
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Simulate stationary VAR(p)

I would like to simulate a stationary VAR(p) coefficient matrix. However, I only found the following (inefficient) solution: Simulate a coefficient matrix (n x n*p) drawing each coefficient from a ...
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Residual variance-covariance matrix in vector autoregression

It's my understanding that the general form of a variance-covariance matrix has variance terms on the diagonal and covariance terms on the off-diagonal. I have seen in multiple references (for ...
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In Cointegration, adf test or for VAR models. What makes difference in having trend + Constant, Constant alone, and non

In Cointegration, adf test or for VAR models. What makes difference in having trend + Constant, Constant alone, and non. in below link http://www.econ.uiuc.edu/~econ508/R/e-ta8_R.html It said ...
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How to perform Granger-causality?

I have a question regarding Granger-causality. I want to test if 1) [y2 and y3] do not Granger-cause y1 and test if 2) [y2] does Granger-cause y1. The equation is as follows: y1-3, t = ...
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68 views

non-stationary time series for VAR model forecasting

I'm working with a VAR model to do forecast involving two non-stationary time series (quarterly frequency). The literature indicates to verify if there is cointegration and, otherwise, to use the ...
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Selecting lag length for VAR Model. Differences or Levels?

I'm currently testing for optimal VAR lag length using the information criteria. I found that my variables are non-stationary (i.e. they have to be first differenced). When I identify the number of ...
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186 views

Panel VAR / Panel VECM

I have an unbalanced panel with N=800 and T=72 (quarterly frequency). After conducting some unit root tests, all reject the null that all panels are not stationary (the alternative is that at least ...
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Generating multivariate heteroskedastic data

I am trying to estimate a VAR model with heteroskedastic error terms. $e_{it}$ is given by $η_{i,t} √h_{ii,t}$, where $η_{i,t}$ is iid, N(0,1). I am trying to get $e_{it}$ Does anyone have any ...
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Correcting for ARCH effect in VAR and impulse response results

I find significant ARCH effect in my series when running a VAR analysis $Y_t=(y_{1,t};y_{2,t};y_{3,t};y_{4,t};y_{5,t})^\top$ I have two questions: Does the ARCH effect impact the impulse response ...
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Importing and transforming new time series quarterly data into Stata

Date Crude Oil Production (Thousands barrels/day) Economic Activity 1980 Jan 62348.011 34.913651 Data runs up to ...
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(multiple) fractional outcomes & autoregression

Let me start with a broad description of the problem and I will then describe my approach (that might be totally inappropiate). The big goal is to predict the distribution of population of a given age ...