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5 votes
Accepted

Durbin Watson Test for an AR(1) process

Nerlove and Wallis (1966) result Nerlove and Wallis (1966) have discussed this issue. Their Equation (3) derives the probability limit of the Durbin-Watson statistic as: $$\mathrm{plim}\, d^* = 2 \...
chan1142's user avatar
  • 2,114
3 votes
Accepted

Need Clarification of Terms: Innovation v.s. Disturbance

They are virtually the same thing but you should not use them completely interchangeably. Disturbance Term Disturbance term is a synonym for an error term. For example, as explained in Verbeek's A ...
1muflon1's user avatar
  • 57.1k
3 votes

Conditional variance vs. unconditional variance in ARCH model

I cannot directly answer your question, but I think I can shed some light. What I seem to show is that under some restrictions, the unconditional variance is finite. However, I am not sure how to ...
Elias's user avatar
  • 983
3 votes

Replicate Romer and Romer (2004) results

Sorry for any confusion in my previous answer but there are 2 steps to this process 1) tracing out the impact on the $\Delta$y's and the lags of the shocks and then 2) accumulating the shocks to get ...
Andrew M's user avatar
  • 426
2 votes

How do I apply the distance-weighting matrix in a spatial autoregressive model

The weight matrix that you have illustrated needs to be row-normalized, i.e. the row-sum must be one in order for the rho parameter to have the proper parameter bounds, i.e. between (-1/lambda,1), ...
Donald Lacombe's user avatar
1 vote

What type of data we use to predict volatility of an asset with GARCH or ARCH models?

B: % of the difference between daily prices over-time. This, or rather the closely related logarithmic returns, is what is typically used as inputs to GARCH and ARCH models. GARCH and ARCH model the ...
Richard Hardy's user avatar
1 vote
Accepted

What type of data we use to predict volatility of an asset with GARCH or ARCH models?

It depends on the specific GARCH model you want to estimate. Traditional GARCH takes in squared % returns (C) assuming no mean equation. But there are other GARCH formulations that take in different ...
RA334's user avatar
  • 239
1 vote
Accepted

Autocorrelation test for AR(p) (Breusch-Godfrey LM test)

(Before applying serial correlation tests to the residuals, you want to visually inspect the residuals for whiteness---look at the sample ACF and PACF. Serial correlation test statistics are often ...
Michael's user avatar
  • 2,619
1 vote

Autocorrelation test for AR(p) (Breusch-Godfrey LM test)

Yes you can use Breusch–Godfrey (BG) test for autocorrelation also in AR(p) models and dynamic models in general (see Verbeek Guide to Modern Econometrics where BG is applied to dynamic models in ...
1muflon1's user avatar
  • 57.1k
1 vote

Johansen test explanation

I think that the wikipedia steps are not completely correct. When you perform Johansen cointegration test you first have to pretest the data to find if they have the same order of integration. That is ...
1muflon1's user avatar
  • 57.1k
1 vote

Aggregate production function, factor shares and cointegration

Intuitively, you test for cointegration because if two variables are cointegrated, they represent only a "one dimensional" family of data points - even if you have a million data points from that ...
Ege Erdil's user avatar
  • 691
1 vote
Accepted

How to calculate inflation rate in order to perfom VAR model?

Stock and Watson use log approximation and quarterly data. Premultiplying the log approximation by 400 could be due to data being quarterly. Your second method is fine too.
london's user avatar
  • 2,010
1 vote

What is the reason why ARIMA(0,1,0) on $y_t$ and ARIMA(0,0,0) on diff($y_t$) are not identical time-series models?

I believe that @Andrew_M is right, this is caused by differences in default options in the implementations of ARIMA across statistical applications. ...
BKay's user avatar
  • 16.3k

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