# Interpretating IRF correctly

We have following Impulse Response Function:

# Load data and apply VAR
library("vars")
data <- data.frame(data[,1:2])
var <- VAR(data, p=3, type = "both")
plot(irf(var, impulse = "e", response = "prod", boot = T, cumulative = FALSE, n.ahead = 20, ci=0.95))


Output: Now I want to make sure to give the right interpretation here:

1. The orthogonal response of prod after an impulse of e is the highest at lag 3.
2. A 1% increase of e causes a 15% increase of prod at lag 3.
3. With a 95% confidence, the response value of prod for a 1% increase of e is between -15% and +35%, meaning that it is not 100% positive. It's only that the largest part of the confidence interval that is positive.
4. Otherwise, the response of prod after an 1% impulse of e is negative from lag 6-20+. It's particularly negative at lags 10-15. The cumulative IRF is therefore also negative for the observed lags.

Are these observations correct?

Bonus quiz: 5. If I multiply all the values (irf, or here on the axis) by 100, what do I get then?