Hello,

I regress a bank's one balance sheet item(Y) on GDP, FX (foreign exchange rate), and the interaction term as follows: (all in percentage changes whereas the data includes 63 consecutive quarters for all)

lnY= β0 + β1 lnGDP + β2 lnFX + β3 (lnGDP x lnFX) + ξ

My questions are:

1-) Is it the correct code: reg lnY lnGDP lnFX c.lnFX#c.lnGDP,r

2-) What is the interpretation for β3? (

3-) FX is much more than GDP in percentage terms. So, how can I create a regression to calculate the joint effect of, for example, 1% change in GDP and 10% change in FX at the same time on Y?

4-) I want to show the effects of GDP and FX separately on Y as well as the effect of a simultaneous change on both GDP and FX on Y as the third scenario. So, which regression(s) should I run to illustrate these three scenarios? (Only the aforementioned one or three different regressions?)

5-) In this regression, both regressors and regressand may be subject to a nonstationarity problem, being vulnerable to a spurious estimation problem. However, since my objective is to measure the percentage change of the Y in response to one percent change in i. GDP, ii. FX, and iii. GDP&FX (simultaneously); is it the right model estimating β1,β2,β3 in this double log form? Also, do you suggest adding some control variables (e.g. other balance sheet items and/or the total size of the balance sheet)?

Kind regards,
Lütfi