2
votes
Accepted
Inclusion of a squared independent variable in a Distributed Lag model
I don't think your line of reasoning justifies the inclusion of the lagged term. We don't actually require that $X_t \perp X_{t-1}$ to obtain unbiased and efficient estimates of the model effects. ...
- 64.8k
2
votes
Accepted
Time series model without ARMA component and with exogenous variables
what you have is fine ( no ARIMA terms necessary ) but three things to consider:
should the X's be lagged by one time unit ? or do they really occur so that the current X's influence the current 𝑌 ?
...
- 2,845
2
votes
Lag between forecasted and actual values ARDL
This is quite common in time series forecasting, and there is little you can do about it. If the time series is close to a random walk, the best prediction is close to the last observed value, as the ...
- 69.5k
2
votes
How to deal with a mix of I(1) and I(0) variables?
Standard VAR model is applicable to integrated variables, after adding more lags to accommodate the degree of integration. For example, if maximum degree of integration among the variables is 2, one ...
- 3,368
2
votes
The relationship between autoregressive model and distributed-lag model
There wasn't enough space in my comment to explain it clearly but this should clarify. Take the koyck distributed lag:
$y_t = \rho y_{t-1} + x_t + \epsilon_t$.
Now, using the lag operator, this can ...
- 2,845
1
vote
Accepted
Does ARDL model require stationarity?
ARDL does not require stationarity. It is possible to use ARDL with integrated time series. Actually, use can have I(0), I(1) and I($d$) with $0<d<1$ in the same ARDL model. See Dave Giles' blog ...
- 69.5k
1
vote
Accepted
Can I compute a VAR Model and then work on only one OLS equation?
Yes. Working with a single equation form a VAR model is fine. On its own, it would be called autoregressive distributed lag (ARDL) model. (In a way, ARDL is more flexible than a VAR, as you can choose ...
- 69.5k
1
vote
Accepted
ARDL with I(1) variables for calculating long-run multiplier
Hi: I don't want to go into all the details ( I'm tired and it's late and the references explain it better than I could anyway ) but you can't keep it in I(1) form because you'll get the well known ...
- 2,845
1
vote
Accepted
ARDL Model in First Differences For Non-Cointegrated Time Series?
The specification you are proposing is not among the ones considered in the paper. In the paper, each specification includes at least one of the variables in levels. This could be problematic when the ...
- 69.5k
1
vote
Accepted
Cointegration test; model with different number of explanatory variables
Let $y$ be the response variable and $x_1,x_2,x_3$ be the explanatory variables. It could be that the pair $(y,x_1)$ is not cointegrated while the 4 variables $(y,x_1,x_2,x_3)$ are cointegrated. This ...
- 69.5k
1
vote
Accepted
Analyzing relationships in 5 time series (cointegration)
Cointegration analysis requires that all time series are integrated to begin with. In your case, only one is integrated, so cointegration is not relevant. Since you mentioned ARDL (a model involving ...
- 69.5k
1
vote
Panel ARDL Bounds steps?
Okay, so I found out that the paper "The ARDL Method in the Energy-Growth Nexus Field; Best Implementation Strategies" by A. Menegaki was pretty helpful.
I'm posting this so that people who ...
- 21
1
vote
Reason for I(1) integration order limit in ARDL regression
...I(1) integration order limit of independent (or dependent) variable in
ARDL regression...
It's not specified exactly in what context this statement is made, but in principle there's no such "...
- 3,368
1
vote
R - Deriving short and long run effects in ARDL model
Before estimating long-run equation you need to apply bounds cointegration test to see whether your data has long-run relationship or not.
- 153
1
vote
Pesaran ARDL Model for testing cointegration relationship - How many variables?
as per my knowledge ARDL is applicable when some of your variables are I(O) and some are I(1), even you can use FOR ALL I(0) variables provided you don't have any spurious regression results. The idea ...
1
vote
Do the dependent variable in a ARDL model have to be I(1) or can it be I(0)?
It does not 'have to', but this will be a degenerate case (see Pesaran, Shin & Smith, 2001, p. 294).
Two degenerate cases arise. First, [. . .] $y_t$ is (trend) stationary or $y_t\sim I(0)$ [. . ....
- 216
1
vote
ARDL/Error Correction Model: long vs. short run, restricted vs. unrestricted
On question 1:
In this setting we assume that $Y$ and $x$ are not stationary. If they were stationary there'd be little sense in talking about a long-run relationship -- $E[Y_t]$ would be some $\mu$ ...
- 302
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