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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363 views

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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295 views

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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476 views

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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312 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 ...
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Information Criteria in State-Dependent VAR models

I am estimating a state-dependent VAR model with two states \begin{align} \mathbf{y}_t = \mathbf{x}_t'\mathbf{B}^I + \lambda_t\mathbf{x}_t'\mathbf{B}^{II} + \varepsilon_t, \end{align} where $\mathbf{x}...
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Modeling temporal change with 2 data points

Study Context: I am studying the relationship between a biomarker of cellular aging (telomere length) and menopause. We have 2 datapoints for a subset of the women. Therefore, our participants could ...
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Using a VAR model to predict stock prices

I ran into an issue while trying to predict stock prices using a Vector Autoregression (VAR) model. After noticing that all the series are non-stationary (see example below): I took first differences ...
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Is possible use bootstrapping using only the forecast error variance decomposition matrix?

I am working with the Spillovers developed by Diebold & Yilmaz (2009, 2012). They are based in the Forecast error variance decomposition (FEVD) of a VAR model and the structure is something like ...
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338 views

How to get Impulse Response Function for non stationary data

I am currently working on a model where I am trying to compute the response of macroeconomic variables like gdp and CPI as well as Gini Koefficient to monetary policy shocks. My problem now is I have ...
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Least stupid way to forecast a short multivariate time series

I need to forecast the following 4 variables for the 29th unit of time. I have roughly 2 years worth of historical data, where 1 and 14 and 27 are all the same period (or time of year). In the end, I ...
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Vector Autoregressive model with series of different integration orders

I am trying to estimate VAR using 8 series. 7 of them are I(0) and one is I(1). I tried to use a python to model, but when I make the I(1) stationary by differencing, it will loose one time point from ...
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4k 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 ...
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Modeling a time series of ordered vectors

I have a series of ordered vectors, $\pmb{x}^o(1), \ldots, \pmb{x}^o(n)$. Here, $\pmb{x}^o$ means the ordered vector of $\pmb{x}$. For example, if $\pmb{x} = (2,5,1)^\top$, then $\pmb{x}^o = (1,2,5)^\...
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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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353 views

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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1answer
504 views

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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582 views

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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1answer
69 views

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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1answer
467 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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1answer
457 views

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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27 views

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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2k views

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): ...
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Do we need stationarity for non autoregressive time-series models?

Most of the literature around time-series models focuses on models with AR terms. Here I have a slightly different and potentially less complicated case. Suppose you have a time-series model with the ...
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Problems with VAR: Autocorrelation when imposing restrictions, ARCH effects and non-normality at all times

I am estimating a VAR model for log-returns of: copper prices, USD/local currency exchange rate, and the local stock market index. Using VARselect I estimated a VAR(...

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