Hi

I am new to econometrics and stata, and appreciate some help for the following qns related to my dissertation. I am investigating property price impact due to opening of rail station in year 2010.

The intention is to develop a fixed effect model with panel dataset, using difference-in-difference concept where there is treated and controlled transactions.
(a) find price growth within 0-1km, 1-2km (treated) against 2-3km (control) of rail stations
(b) investigate any anticipation effect i.e. which year did the price start increasing before year 2010 and how much each year/percentage. Also the increase trend after year 2010.

I have property transactions from 1995 to 2019 and using GIS software, i have filtered the transactions within 0-1km, 1-2km and 2-3km of stations. And i have created a column name buffer_km with 1/2/3 to denote the corresponding distance.

However i am rather confused over category variable and where to put 0 and 1. I have done two methods and it gave very different coefficients for buffer_km1/2 and r1km/r2km.

Code:
gen logprice = log(price)
encode type, gen(typehouse)
gen YearsStr = substr(date,1,4)
encode YearsStr, gen(YearsS)
encode lsoa11, gen(LSOA_num)
encode tenure, gen(Tenure)
gen YearsN = real(YearsStr)
gen r1km = (YearsN>=2010 & buffer_km==1)
gen r2km = (YearsN>=2010 & buffer_km==2)
gen r3km = (YearsN>=2010 & buffer_km==3)
xtset LSOA_num

xtreg logprice ib4.typehouse ib2.Tenure i.YearsS ib3.buffer_km, fe
xtreg logprice ib4.typehouse ib2.Tenure i.YearsS r1km r2km, fe
Which method should i use to answer qn (a) above that reflects the price growth within 0-1km and 1-2km comparing transactions before and after year 2010?

For qn (b) on the anticipation effect, i was told i have to find a way to regress against year 2010 but i don't really know how to do it. What do the coefficient in the results output under YearsS 1996 to 2019 mean in statistical terms?

Grateful for any advice to the queries above. Thank you!


Regards
Cleo