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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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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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Vector autoregressions [on hold]

Suppose running a VAR system featuring the central bank interest rate, inflation and GDP. Start by estimating each equation by OLS. How should you interpret the OLS residuals to these equations? My ...
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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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28 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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19 views

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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25 views

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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44 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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36 views

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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26 views

Inconsistency of Bayesian time varying VAR model

I'm estimating time-varying parameter VAR model of Joushi Nakajima (2011), the model simulates the time-varying parameters using MCMC algorithm and the priors are estimated by implementing standard ...
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10 views

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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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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43 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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1answer
23 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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1answer
60 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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29 views

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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66 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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1answer
28 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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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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24 views

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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1answer
34 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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1answer
29 views

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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16 views

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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1answer
33 views

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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36 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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70 views

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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41 views

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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42 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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49 views

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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110 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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34 views

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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58 views

(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 ...
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If I recover VAR model coefficients from PCA-derived coefficients, do I need to ensure that the model has zero cross-correlation in the residuals?

I am investigating how to appropriately combine PCA with VAR modeling. I am using PCA to reduce the number of vars I fit to a VAR model, and am attempting to recover the non-dim. reduced coefficients ...
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1answer
60 views

Implement VAR model in R with HAC corrected standard errors [closed]

I have fitted a VAR model in R (with function VAR) and would like to use HAC corrected standard errors. How is that possible?
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1answer
381 views

Interpretation of the Impulse Response Function - VAR Estimation

I have some issues while discussing and interpreting this impulse response function (the graphics analysis). What do they mean and represent economically? What can the conclusions be? Basically ...
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56 views

Jarque-Bera Test for Normal Distrbances in a VAR

I did the test of he null hypothesis of Normal disturbances and found that it is rejected for Dlop and Dunp. Does this mean that I have a problem with my model specification? Or how can I rectify this ...
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162 views

Granger Causality Interpretation using Stata

I am trying to characterise temporal sequence of influences in a VAR and wanted to use the Granger Causality. Based on these results, am I right to say that the change in oil prices (Dlop) do not ...
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20 views

Cross Correlation

Given that my variables exhibit non-stationary (i.e lrgdp and lop) and I intend on estimating a VAR model, would it make sense to correlate them in their first differences instead (dlrgdp and dlop) ...
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41 views

VAR Model using Stata

I'm relatively new to the VAR model and have been using Sean Becketti's 'Introduction to Time Series Using State' as reference and wanted to check if I am on the right track. As of now, I have 5 ...
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1answer
37 views

VAR, test for normality, autocorrelation and heteroskedasticity- should I use stationary first differences for these tests?

I am checking thhe long-term relationship between unemployment and labor force participation rate. I have a integration order I(1) and I want to run VAR. As far as I understand I need to use first ...
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17 views

Rescaling Linear Impulse Response Functions, Innovations, and Confidence Bands

all. I am using a VAR model to do a bit of analysis. I obtain cumulative (linear) orthogonalized impulse response functions (COIRF). Because I am conducting similar analysis across different time ...
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33 views

Can VAR models capture all frequency interactions reliably and to the same extent?

I would like to assess how a set of ~50-100 time-series variables causally interact with each other. To do this, I am fitting a VAR model and using cross-validation to estimate model-order. After the ...
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VAR with stationary and non-stationary in R

I'm working on using Granger causality of some variables and I have 4 stationary time series (X1, X2, X3, X4) and one that is not (X5). I've seen here that If (A) then first-difference each of the ...