# Questions tagged [vector-autoregression]

Vector Auto-Regression, a multivariate time-series model / method. Under VAR, each univariate time-series is a linear combination of its own previous values and the previous values of the other series.

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### Multivariate ARIMA model with irregular time-series

I have a financial time-series dataset consisting of prices of 12 different products (financial futures contracts) that expire x months away from now. So if I plot these 12 contracts with end-of-day ...
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### Model for panel VAR with a lot missing values

I have the following panel data with two variables: and There are around 1,000 individuals and 16 time periods. The variable is only available in times 4, 8, 12, and 16. I have the following panel ...
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### VECM - interpreting output from cajorls()

I am a bit puzzled on how to interpret the test results cajorls() from the urca-package. This function returns the OLS ...
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### Can we estimate VAR model using monthly data for 7 years?

I am interested in estimating the long run relation between electricity shortfall and industrial output with other variables. It forms a 6*6 matrix. Can I get reliable estimates? I am very much ...
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### PC-Vector Autoregression (PC-VAR)

When using PC-VAR model for forecasting purposes, can we define it in the following manner? where a k-dimensional vector of intercepts is denoted by φ0 , Φ represents a k × k matrix of coefficients ...
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### Identifying positive and negative shocks in impulse responses

Dear StackExchange community, I'd have a question on impulse responses that I have not found an answer to in econometrics textbooks. Specifically, I would want to know how to interpret impulse ...
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### IRF of Structural VAR equal to Standar VAR?

I´m doing a traditional Phillips curve approach with a VAR model, in particular, I used the methodology of Blanchar and Quah (1989) to obtain the structural VAR, but when comparing the IRF graph of ...
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### Constrained Matrix Decomposition

I am working on a structural vector autoregression that requires imposing constraints on a matrix factorization. In particular, I have an N-dimensional positive definite matrix $\Sigma$ that I need to ...
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### How to fit a scalable Bayesian VAR model in Stan/JAGS

I am trying to fit a Bayesian vector auto regressive model but I am struggling with the computation. I tried both JAGS and Stan to fit the model but I have never been able to fit it successfully. It ...
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### Differences between Static Factors, Dynamic factors and Exploratory factor analysis in Time Series

I came across many types of factor analysis techniques in the context of time series data. I am not sure whether exploratory factor analysis refers to the same static factor analysis methodology. If ...
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### Residual Diagnostics in Vector Autoregression (VAR) model

My target is to forecast GDP and I have 5 predictors. I estimated a VAR model and the reason why I employed a VAR is that since it considers all variables as endogenous. Since I am only interested in ...
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### Does existence of Cointegration mean that VECM is preferred to VAR?

I have some data which had to be logged and differenced once to induce stationary. I ran the Johansen test for cointegration and found that it is present in my data set. Does this fact tell me that ...
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### How to calculate (by hand) the R-squared of a VAR time series model built using R?

I have created a VAR model in R (using the command VAR) and my model reports an R-squared of about 0.8 for the variable I'm most interested in. I'm trying to replicate that result by calculating the R-...
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### Forecasting using PC-VAR

I am trying to forecast an index by using a PC-VAR. When performing the PCA, can I exclude the response variable from the dataset and find the PCs and later build a VAR with the response variable and ...
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### Why forecast accuracy is very high in Restricted VAR but not in individual OLS estimate?

When a VAR is estimated and tested on the test data the RMSE of the model was around 25. However when I estimated a restricted VAR by setting coefficients of the lagged terms of the dependent variable ...
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### Does it make sense to plot impulse response functions for insignificant variables in Granger-causality tests?

I have 4 endogenous variables: call them w, x, y, and z. I am interested in the reduced form VAR where w is the dependent variable. Having run Granger tests, I found that only x and y Granger-cause w ...
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### How to estimate a Vector Autoregression model using ARCH estimation (VAR-GARCH)?

I estimated a vector autoregression (VAR) model using 3 lags and 5 variables. However, when I estimated the equation using OLS, heteroskedasticity was present. In this sort of a situation, what is the ...
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### What is the coefficient that shows whether there is a positive or negative relationship between variables in vector error correction models? [closed]

I am trying to estimate the long-run and short-run relationship between variables. Based on the Johansen cointegration analysis it was concluded, that there is one cointegrating relationship. The next ...
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### How to compare which variable has more effect in VAR model?

I am using VAR model. I have six endogenous variable and I am using pairwise Granger causality tests to identify the causality, but I am interested also which one has biggest effect in one endogenous ...
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### How to estimate moderators of persistence in a panel?

I have a panel dataset of $n$ groups (i), observed at a given time (t), where we observe a DV (...
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### Multivariate TS analysis for Carbon Prices

I am new here so please pardon me if I make any mistakes. I am trying to understand the determinants of carbon RGGI prices from 2012-2021, using quarterly data available from the website. Basically, ...
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### 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 ...
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### Multivariate forcasting when variable observations are not contemporaneous: lag logic

I am looking at various VAR models for several time series, doing one-ahead forecasts. Within each period of observation there are sub-periods. Variable x is ...
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### 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 ...
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### How to deal with a mix of I(1) and I(2) variables?

I have one dependent variable which becomes stationary after the first difference I(1). There are 4 independent variables, out of which 2 become stationary after the first difference and the other two ...
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### VAR Impulse response with a dummy variable

I have a var model : y=dummy + other variables where dummy =1 if the firm is having a negative return on stock and 0 otherwise. Y is the return on stock. Is it appropriate to use the VAR model to ...
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### Transforming a generic $ARIMA(p,d,q)$ process to make it stationary

I am trying to build a VAR model with 6 variables. In addition to performing the ADF and KPSS tests for stationarity, I thought it might be interesting to use the ...
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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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### Selecting lag order for VAR model with *weekly* seasonal data

If this has been asked elsewhere, I apologize - I've looked around and while there is lots of discussion about selecting lag order for VAR models, I haven't found anything addressing my specific ...
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### Why Granger causality test gives same result for restricted and unrestricted VAR models

I applied granger causality test 1st in unrestricted 2 dimensional VAR(1) model and then restricted model (t>2). Both are giving the same result (the result of unrestricted VAR model). Actually ...
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### Impulse response function of the exogenous variable in a VARX model

I am learning about VAR models "by doing", so to speak. I am using statsmodels; comparing the documentation on VAR and VARX models, I would like to ...
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### Imposition of Long Run and Short-Run restrictions in SVAR in R language

I 'd like to ask a question about the imposition of LR and SR restrictions on an structural vector autoregressive model (SVAR) framework of analysis. I read the documentation of the vars and svars ...
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### Why does the prediction of a VAR dgp diverge from the test set?

I'm working on a multivariate data set consisting in 44 observations (which have to be splitted: the first 34 observations are in the training set, the remaining ones in the testing set) of 9 ...
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### Quantifying the significance of impulse response functions

I use Stock and Watson's classic reference on vector autoregressions for this question. They carry out a VAR on inflation, unemployment and the interest rate and thereby produce the following matrix ...
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### 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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### Residual autocorrelation in VAR with non stationary data

I am running VAR model with non-stationary time series. I am going to have a look only at impulse response functions, so I've read that I can use VAR for non-stationary time series. My model includes ...
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### Predictive or Error Tests for Vector Autoregressive Models (VAR)

I have two questions relating to VAR and would kindly appreciate any assistance/opinion: Question 1: I am having difficulty finding a proper predictive ability test for my VAR model to conclude if my ...
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### What number of lags for multivariate Portmanteau, Breusch-Godfrey, and Ljung-Box tests?

There are 3 types of tests for the residual autocorrelations here (I have a relatively small sample(58 obs): ...