Dear Colleagues,
I ran an Error Correction Model, obtaining the results depicted below. The model comes from the literature, where Dutch disease effects were tested in the case of Russia. My dependent variable was the real effective exchange rate, while oil prices (OIL_Prices), terms of trade (TOT), public deficit (GOV), industrial productivity (PR) were independent variables. My main concern is that only the Error Correction Term, the dummy variable, and the intercept are statistically significant. Moreover, residuals are not normally distributed, while also the residuals are heteroscedasdic. There is no serial correlation issue according to the LM test. How can I improve my findings? Thank you beforehand.
Best
Ibrahim
LITERATURE based variables may be confirmed or disaffirmed. Prior literature may not be valid if the underlying conditions in the economy changed. For instance, if the literature was prior to the digital age, in the age of the Internet such literature may not hold the same validity.
INDEPENDENT VARIABLES for effective exchange rate normally include interest rates, confidence, the current account on balance of payments, economic growth and relative inflation rates. Some of your Xs look problematic. While TOT is correct, other factors such as OIL, GOV and PR are not the direct measure of factors affective REER.
REPORT your finding as you have found "as us". Point out that these factors from the literature could not be confirmed by your case study.
Good day Ibrahim
Please find an attached article which adopted the VECM, it will definitely assist you.
Kind regards
Solly Molepo
I have my own rule of thumb about this kind of issue: "If the number of significant variables is less than the in-significant variables, it is better to change the model or estimation method."
Dear Ibrahim.
I also agree @ Carlos Mangunsong that if your number of significant variables are less then your insignificant variables, then change your technique of estimation.
Regards
I notice the following about your specification. (1) Your inclusion of a constant (and its subsequent significance) means you allow for (and find) a trend in the real exchange rate independent of any trends in the other variables. Is that economically reasonable? (2) I assume the CRISIS variable is a zero-one dummy for time periods with a "crisis" of some sort. Apparently it is not in the cointegration vector. Why not? If it were, then I'd expect to find CRISIS differences in the error correction equation. Instead, you have it in levels. Thus you specify that a temporary crisis has a permanent effect of the level of the real exchange rate independent of the other variables. Is that what you intend? (3) You do not include the lagged difference of the real exchange rate in the error correction equation. Why not? Normally it would be there.
Thank you, dear Carlos Mangunsong
However, this rule of thumb can significantly limit the researcher if the research is novel and data is scarce. But it is a good approach as a constructive self-ctiricism.
Best
Ibrahim
Dear Professor David O. Cushman
Thank you for your questions and suggestions.
1) Usually the inclusion of a constant is highly expected. I did not know that I have to devote special attention to the inclusion of a constant in the modeling process.
2) It is a good idea to take the difference of the dummy variable as well to see the temporary effects of the crisis instead assuming its permanent impact.
3) So far, the papers I was interested in have not shown me the lagged variable of the dependent variable in ECM.
Best
Ibrahim