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I would like to ask a question regarding the interpretation of log-log interaction term in the Two-way fixed effect model. I have the following regression model:

y_it = 𝛽_0 + 𝛽2[ln(price_it)*ln(area_it)] + myu_i + phi_t + u_it

here, y is years of schooling (continuous), price is housing price (continuous), and area is house size.

If 𝛽2 is 0.5, then how can I interpret point estimate in the logarithm setting?

For example, 1% change in house price and 1% change in house area at the same time leads to 0.5 more years of schooling?

I am not familiar with the log*log interpretation here and would like to get some help!

Thank you so much in advance for your help!

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  • $\begingroup$ There's nothing special, because logarithms are just numbers. Search our site for many, many answers. $\endgroup$
    – whuber ♦
    May 25 at 19:48
  • $\begingroup$ There's a potential problem, as this seems to include a product of two predictors in an interaction without including the predictors individually. See this page for why that's not usually a good idea. $\endgroup$
    – EdM
    May 25 at 21:23

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