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Andy_20
Fluorite | Level 6

Hello there goods friends,

 I am modeling factors for FDI Decision by analyzing macroeconomic indicators namely Inflation rate(%), GDP growth rate(%), exchange rate(TZS/USD), interest rate(%) as Independent Variables against FDI INFLOWS (Million USD), the dependent variable. The EXCHANGE RATE and Real GDP Growth rate series seem to follow a normal distribution but rest do not.

The problem comes in transforming the data already in percentage into logarithm whose coefficients are interpreted as percentage change, can do that? What are possible consequences? 

NB: All of the observations are positive but with some Variable having outliers.

 

 

I opted to use ARDL MODEL as the data are integrated of mixed orders I(0) and I(1)...!

I now ask you help me if I can transform the data to esnure normality as well as reduce the Heteroskedasticity on the error term

Thank you in advance,

Blessings

 

2 REPLIES 2
sbxkoenk
SAS Super FREQ

Hello,

 

ARDL needs no pre-testing of order of integration of the variables, and that it is applicable for a mixture of I(0) and I(1) variables with no variable being I(2). But, it requires that the dependent variable should be I(1).

 

The ARDL model requires that the error terms should have no autocorrelation with each other. There should not occur any heteroscedasticity in the data. In simple terms, the variance and mean should remain constant throughout the model. The data should follow normal distribution.

 

Read these 3 blog articles (same author) if you want to know how NOT to violate the ARDL assumptions :

 

See also here :

"SAS Forecasting and Econometrics" board
Autoregressive Distributed Lag Model
https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Autoregressive-Distributed-Lag-Model...

 

Good luck,

Koen

 

 

 

Andy_20
Fluorite | Level 6

Thank you Koen, let me go through the links

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