DOLS and FMOLS are superior to the OLS for many reasons so let me give you the key ones: (1) OLS estimates are super- consistent , but the t-statistic gotten without stationary 0r I(0) terms are only approximately normal. Even though, OLS is super-consistent , in the presence of "a large finite sample bias' convergence of OLS can be low in finite samples (2) OLS estimates may suffer from serial correlation, heteroskedasticity since the omitted dynamics are captured by the residual so that inference using the normal tables will not be valid -even asymptotically. Therefore, "t" statistics for the estimates OLS estimates are useless (3) DOLS &FMOLS take care endogeneity by adding the leads & lags (DOLS). In addition, white heteroskedastic standard errors are used. FMOLS does the same using a nonparametric approach, see Arize, Malindretos and Ghosh (2015) in International Review of Economics and Finance. Also, see Arize, Osang and Slottje (2000) in Journal of Business & Economic Statistics

Thanks, Chuck.

DOLS seeks to address asymptotic bias contained in the OLS estimate by including leads and lags of the difference d series.According to Kao and Chiang (2000) DOLS outperforms FMOLS approach. Not only DOLS is computationally simpler but it reduces bias better than FMOLS. The t statistic  from DOLS approximates the standard normal density much better than the statistic from OLS or FMOLS.

DOLS requires leads and lags of first difference independent variables and also Newey-West estimator, but it performance like FMOLS dependent a on the data generating process.All estimator can preform badly depending on the DGP. That is, reliance on a single estimator can often yield misleading inference.?

Also take a look at :

http://www.vcharite.univ-mrs.fr/colloques/2008/davidson_2008/Papiers/Bispham.pdf

In general, as I write in my paper which you can find here

https://www.researchgate.net/publication/308201567_Non-performing_loans_in_the_euro_area_Are_core-periphery_banking_markets_fragmented

"FMOLS is a non-parametric approach used to dealing with serial correlation. Dynamic OLS (DOLS) is an alternative (parametric) approach in which lags and leads are introduced to cope with the problem irrespectively of the order of integration and the existence or absence of cointegration."

Thank you all.

I have used FMOLS in a single-equation cointegration test that is no panel, is that ok?

Give me a day, I will provide you with some.

Chuck, did you forget about me? ;)

Please Lars, this is final exam, I will look for it.With papers every where in my office and RA's gone it is not easy for m, especially bending down. I know some of head but I need to be sure. This weekend, I promise to give you one. A must!. You are a guy I respect

Until Moday,

Here is one cited in a paper of mine: It is a Monte Carlo study by Maki .D. (2011:1111-1121) "Pitfalls in Estimating Cointegrating Vector when Cointegration Relationship Has Nonlinear Adjustment," Communication in Statistics and Computation Vol.40

Thanks a lot Chuck!

Here is another Monte Carlo study study by Cappuccio, N and Lubian, D. (2001, Vol 20, Issue1: 61-84) " Estimation and Inference on Long-Run Equilibria: A Simulation Study" Econometric Reviews.

Looks at FMLS, DLS and Johansen estimators

Another is

Hargreaves, P.C. (1994)

You may find this interesting wr to DOLS and ARDL with Bewley transformation ,

http://www.tandfonline.com/doi/abs/10.1080/00036846.2011.608647 , a working paper version is available on my page.

Thanks!

Lars, these too!!

Inder (1993) simulation examined the simulation results of Philips and Hansen (1990). See Montaalvo, J. .G (!995) "Comparing Cointegrating Regression Estimators: Some Additional Monte Carlo Results," Economic Letters, 49:229-234.

Inder, B. (1993) Journal of Econometrics, 57:53-68

"Estimating Long-run Relationships in Economics "

See also Simulation work above by James Forest and Paul Turner in Applied Economics 2013

Hello all,

What are the differences between stationary and no-stationary?

Search me within this RG answers, I have provided some

answers on a similar question

@Maryam

The simple way to look at a stationary variabl is to see it as one where it is fixed in terms of its mean and variance such as the first difference of most variable.

Then Nonstationary should be that the mean and the variances (for example a variable x, that is the level of the variable) are fluctuating or shifting. Once you have that in your brain when reading in this area, it will make this easy to understand what is being said. Thank you.

Many thanks dear Chuck A Arize for your answer, it was helpful to me.

Both DOLS and FMOLS are usually preferred to the OLS estimator because they take care of small sample bias and endogeneity bias by taking the leads and lags of the first-differenced regressors. However, the parametric DOLS is preferred to the non-parametric FMOLS in that the latter (unlike the former) imposes additional requirements that all variables should be integrated of the same order [i.e.,I(1)] and that the regressors themselves should not be cointegrated (for an application of DOLS, see A. M. M. Masih and R. Masih (1996), Energy Economics, October, 18(4), 315 - 334).

Hi;

You can read these articles , i hope they will help...

Kirikkaleli, D. (2016). Interlinkage between economic, financial, and political risks in the Balkan countries: Evidence from a panel cointegration. Eastern European Economics, 54(3), 208-227.

Yorucu, V., & Bahramian, P. (2015). Price modelling of natural gas for the EU-12 countries: Evidence from panel cointegration. Journal of Natural Gas Science and Engineering, 24, 464-472.

Yorucu, V., & Kirikkaleli, D. (2017). Empirical Modeling of Education Expenditures for Balkans: Evidence from Panel FMOLS and DOLS Estimations. Revista de Cercetare si Interventie Sociala, 56.

Please share me the best answer might you get...

the three papers recommended by Dervis Kirikkaleli above will give you clear idea.

Thanks All.

youtube videos on DYNAMIC OLS AND MODIFIED OLS are required

I am wondering, can we use variables integrated of order I(0) and I(1) both in FMOLS regression model. Can anyone guide.

DOLS takes into consideration the nonstationary status of the series and ensures that the variables do not enter into the model in their explosive manner

Papers suggested by Dervis Kirikkaleli will help you a lot.

https://www.elibrary.imf.org/doc/IMF001/08870-9781451868500/08870-9781451868500/Other_formats/Source_PDF/08870-9781451913033.pdf

https://www.mdpi.com/2227-9717/7/8/496