realestData {qape}

Population data - real estate in Poland at NUTS 4 level

Description

A data frame with 1504 observations on the following 7 variables (NUTS 4 units with masked values of the variables due to Statistical confidentiality has been removed).

Arguments

year

year.

NUTS4

NUTS 4 code (powiats).

NUTS2

NUTS 2 code (voivodships).

NUTS4type

type of NUTS 4 (1 - land counties, 2 - city counties/cities with powiat status).

premises

number of residential premises sold in market transactions (in thousands).

area

usable floor area of residential premises sold in market transactions (in millions of square meters).

price

sum of prices of residential premises sold (in billions of Polish zloty).

Source

Statitics Poland, https://bdl.stat.gov.pl/eng

Examples

data(realestData)
hist(realestData$price[realestData$year==2018])
boxplot(realestData$price~realestData$year)
boxplot(realestData$price[realestData$year==2018]~realestData$NUTS2[realestData$year==2018])
boxplot(realestData$price[realestData$year==2018]~realestData$NUTS4type[realestData$year==2018])


library(lme4)
attach(realestData)

N <- nrow(realestData[(year == 2015),]) # population size in the first period
n <- 75 # sample size in the first period
set.seed(123456)
sampled_elements_in_2015 <- sample(N,n) 
con2015 <- rep(0,N)
con2015[sampled_elements_in_2015] <- 1

sampled_elements_in_2016 <- sample(N,n)
con2016 <- rep(0,N)
con2016[sampled_elements_in_2016] <- 1

sampled_elements_in_2017 <- sample(N,n)
con2017 <- rep(0,N)
con2017[sampled_elements_in_2017] <- 1

sampled_elements_in_2018 <- sample(N,n)
con2018 <- rep(0,N)
con2018[sampled_elements_in_2018] <- 1

con=as.logical(con2015, con2016, con2017, con2018)

model1 <- lmer(price ~ premises + area + (1|NUTS2)+(0+premises|NUTS2) + 
(1|NUTS4type)+(0+area|NUTS4type), subset=con)
AIC(model1)
model2 <- lmer(price ~ premises + area + (0+premises|NUTS2) + (0+area|NUTS4type), subset = con)
AIC(model2)