Questions tagged [cointegration]

Two or more non-stationary, integrated variables are cointegrated if there exists a linear combination of those variables which is integrated of a lower order, e.g. stationary.

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Cointegration testing; order of the pantula principle?

In my times series course we learnt about using the Johansen Procedure to determine, if there are cointegrating relationships within a VAR model. My teacher gave us a function to implement it in R. ...
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Cointegration tests, what if Johansen trace and eigenavalue tests disagree?

I have run a both Johansen's trace and eigenvalue test to determine if there is cointegration in my set of variables. But surprisingly they seem to disagree. Specifically the trace test suggests r = 2 ...
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How should I treat a binary variable for VAR/VECM?

I have a binary variable (2 values) and I plan to implement a VAR/VECM model. The model aims to focus more on how a change in this binary variable affect the other variables in the system rather than ...
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Is logged data considered level data?

Hi I'm new to VECM/VAR models. I read that we can use VECM when data is non-stationary at level but some form of cointegration exists. By "level" does it mean it has to be the raw data? Or ...
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Hypothesis testing on cointegration vector

I am studying cointegration theory in time series using online resources. As per https://www.econometrics-with-r.org/16-2-ooiatdfglsurt.html DF-GLS test is implemented in the package urca can be used ...
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Is the Python Johansen cointegration test trustworthy?

I'm trying to learn how to do Johansen's cointegration test. I am using the Python's "statsmodels.tsa.vector_ar.vecm.coint_johansen". I have run 10 tests, each with 5 series. All series ...
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What's the relationship between cointegration and linear regression?

If two non-stationary processes are cointegrated, that means a linear combination of the two processes are stationary. In a simple linear regression, we have the model form: $y = b_0 + b_1x + e$ If ...
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How to correctly pre-whiten time series

I'm trying to find cross -correlation between two-time series and as it so happens, they are auto-correlated(2), nonstationary and co-integrated. As I read about them, it appears that pre-whitening ...
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What is the use of cointegration?

From what I have briefly read, seems like cointegration is used to determine if there is a statistically significant relationship between two unit root processes (as opposed to spurious correlation). ...
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Question about latent variables in Co-integration Regression

I have a question about cointegration regression models as follows: Is it common to have latent variables or regressors with measurement error in the cointegrating regression model? Is it highly ...
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Bivariate Cointegration Test using Johansen Test

I am currently working on my final thesis on the subject of pairs trading and have to carry out a large number of cointegration tests. The reason for this is that I want to compare 100 foreign shares ...
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Relationship among futures, options and stock prices [closed]

I have the data of past 10 years of NIFTY (the National Stock Exchange of India) stock, futures and options and I want to show the lead-lag relationship (which reacts first, futures, options or stocks)...
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What is the right model structure for spike-and-diminish feature?

I am asked to build a model for detecting anomalies/monitoring the usage of some machines. The x-axis is time in minutes, and the y-axis is the resource usage of a machine (you can think of something ...
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Is there such a thing as a Vector ARDL model? ARDL (AutoRegressive Distributed Lag) vs VAR (Vector AutoRegressive)

Question 1: I am confused with the difference between ARDL and VAR. If VAR only allows for modelling of I(0) variables and variables are required to have the same lags in the model (i.e. each equation)...
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Co-integration test using aTSA package in R

I am learning more about co-integration test. I would like to compare two series: one that has the return and the other one that has a price. I used the aTSA package, and got the following result: <...
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Understanding the output from the Johansen Cointegration test in R

I have a VECM model that Im using to determine the revenues for a firm, based on factors like Interest rates, S&P 500 and company specific variables, as follows: Stage 1: $$z_t= a+ bX_t+e_t$$ ...
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Should I use a ARDL if I have more than one cointegrating relationship?

I have a four time series variables. They are a mix of I(0) and I(1) variables. There is also more than one cointegrating relationship among the variables. If there is more than one cointegrating ...
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Looking for the right model of non-stationary asset market variables

I need help finding an appropriate model given the below criteria. Objective: to derive fitted value for front-month gold futures prices (dependent variable) based on cross-asset market independent ...
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What if series are not cointegrating

what if there are four series all non stationary at level 0 but all stationary at level 1 but they are not co integrating can we still go granger causality and which granger causality var or vecm
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How to statistically test relationship between two variables?

I am trying to investigate the stability of spread between two short-term interest rates by the example of 1M and 12M Euribor. I don't think only looking at correlations over time is statisically ...
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Cointergration of seasonal time series

I'm studying monthly state-wise rates of certain diseases and suspect that they may be related (there is some physiological explanation for their relationship). As far as I understood, to avoid ...
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Contradictory findings from Dickey-Fuller test and Breusch-Godfrey test

I wanted to check the cointegration of 3-Month Treasury Constant Maturity Rate and 10-Year Treasury Constant Maturity Rate. Therefore, I have conducted Dickey-Fuller test and Breusch-Godfrey test. ...
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Will the coefficients of an error correction or lasso-penalized model usually reveal spurious correlation?

As time goes by I have learned of more and more ways that correlations can be spurious and more and more tests and correction procedures intended to avoid taking such correlations as meaningful. My ...
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Different way to obtain Cointegration Impulse response

If my memory is correct, we can obtain the impulse response function (irf) with bivariate VECM . However, I read some researcher just difference the variables under the pre-specified relation. For ...
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positive Error correction term, what could be wrong

here is the basic regression: log(Robots per capita)~share of midage+share of older+log(gdp) I obtain good results but all my variables are unit root. So I tried correcting this doing the following. (...
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reading the output from cointegration test

I am trying to understand the output from the tables below. The model I have assumed is one which has a intercept and a trend & I have run this function on two time series. My understanding is ...
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calculate residuals

I am stepping through some code trying to understand a cointegration function. There is one function that has me very confused. y is a 1800 x 2 matrix of difference & x is the same dimension just ...
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detrending data for cointegration analysis

0 I am trying to under the code written in this module to understand cointegration. My model has an intercept and a deterministic linear trend. So I call the function below with the parameters shown....
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OLS regression on linear time series model

I am dealing with macro-economic data in EVIEWS11: new firms founded per year scaled by population ENT real gdp per capita Y stock market capitalisation scaled by population and in real terms MK ...
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Do I absolutely need cointegration if I have unit root but no autocorrelation?

I am trying to assess the impact of aging on robot adoption in one country. I made the following regression ...
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¿How can I tell if I have a spurious regression for panel data?

I have a strange case. In a model N=150, T=17 (i.e. 150 countries observed across 17 years) I run the model in which I regress GDP against some variables. I get R-2=0.95 and all independent variables ...
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Interpretation of Johanson co-integration test results

if the Max-eigenvalue test indicates no cointegration at the 0.05 level, while the Trace test indicates 2 cointegrating eqn(s) at the 0.05 level, how do i interpret the results?
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Fitting a VEC model: suggestions on procedure and results

I'm having some hard times trying to do a simple but statistically sound analysis on 4 cointegrated daily time series which I analyzed through VEC. I ask the community: is the procedure I followed ...
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25 views

Cointegration of order 2

Can we use the Johansen Test of Cointegration when the we have 7 variables that 6 of them are i(2) and one of them is i(0)?
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Time series regression with stationary and integrated variables using local projections

I am estimating structural impulse response functions of a five-variable model (say $x_1$, ... , $x_5$) using Jorda's local projection method and an external shock series. The local projections are an ...
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VECM Cointegration Relationship Coefficient(s) Interpretation [duplicate]

Theory dictates that when there is one cointegration relationship, it's coefficient in a VECM must be statistically significant and negative to maintain the long-run equilibrium. Nonetheless, when ...
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Eviews VECM with a cointegrating rank of 2

Using Eviews, I have performed a Johansen cointegration test on three variables, suggesting 2 cointegrating relationships. I am now trying to estimate a VECM model, but when following Brooks (2014) pg....
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Johansen and VECM

If the Johansen tests say that there are 3 cointegrating relationships (All 5 tests) for a 4 variable system, is it allowed/accepted to use less than 3 cointegrating equations for the VECM? Thanks!
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Time series - measure impact of another time series variable

I am looking for some techniques that would help me measure the (over-time) impact of a variable to another. So let's say we have annual time series data for GDP for 5 countries and I wanted to see ...
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1answer
91 views

Trouble interpreting cointegration test results

I'm struggling with testing the cointegration of 2 time series (or rather interpreting the test results properly). So I got 2 time series x and ...
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VECM when only one variable is cointegrated

What does it imply for my VECM model if only one variable is cointegrated? ...
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22 views

Cointegration test, three I(1) variables, and one I(0) variable

I have four time series, three of which are I(1), and one is I(0). I know an I(0) and an I(1) timeseries can not be cointegrated, but if I run a Johansen test could the other I(1) variables be ...
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Better alternatives to linear regression and $AR(1)$ for modeling cointegrated time series

In a cointegration framework, I would like to improve the two-step Engle-Granger cointegration procedure. My idea is to: replace the linear regression with some non-linear model; replace the $AR(1)$ ...
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59 views

How can i correct or interpret a negative but an insignificant error correction term?

The variables that are used for cointegration are I(1). I got the error correction term as negative but it not significant. So how should i proceed for the results?
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Cointegrated VAR impulse response function

I have two variables Consumption(c) and Earning(e). According to the thesis, c and e are cointegrated. So the author differences to two variables to be Diff_C and ct-et and get the stationary part. ...
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49 views

What is the order of integration of AR + MA

Consider the following bivariate DGP for ($y_t,z_t$): $y_t = \gamma(z_{t-1} + \theta_{21}\epsilon_{2,t-1} + u_{2,t}) + \theta_{11} \epsilon_{1,t-1} + u_{1,t} $ $z_t = z_{t-1} + \theta_{21}\epsilon_{...
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44 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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Panel cointegration test

I have a panel data in which one variable is stationary at I(0) and two variables are at I(1). I want two test the coingeration. Which method would you suggest is the best one in that case and why?
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When can you apply the bootstrap to time series models?

Under what circumstances can you apply re-sampling techniques to quantify the uncertainty about the parameters of a time series model? Say that I have a model such as below: $ Y_t = X_t\beta + e_t$...
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Cointegration in error correction model with only one nonstationary variable

I have three time series variables, two variables are stationary and one is non-stationary. Can we still search for the cointegration and use the error correction model or should I take the first ...

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