This article produces a gallery of figures and tables produced by this package for reference.
library(cmfproperty)
ratios <-
cmfproperty::reformat_data(
data = cmfproperty::example_data,
sale_col = "SALE_PRICE",
assessment_col = "ASSESSED_VALUE",
sale_year_col = "SALE_YEAR",
)
#> [1] "Filtered out non-arm's length transactions"
#> [1] "Inflation adjusted to 2019"
stats <- cmfproperty::calc_iaao_stats(ratios)
regression_tests
|
|
Dependent Variable
|
|
|
|
ASSESSED_VALUE
|
log(ASSESSED_VALUE)
|
RATIO
|
|
(1)
|
(2)
|
(3)
|
|
SALE_PRICE
|
0.77***
|
|
-0.0000***
|
|
(0.001)
|
|
(0.00)
|
|
|
|
|
log(SALE_PRICE)
|
|
0.91***
|
|
|
|
(0.001)
|
|
|
|
|
|
Constant
|
34,702.12***
|
0.95***
|
0.96***
|
|
(256.32)
|
(0.01)
|
(0.001)
|
|
|
|
|
|
Observations
|
308,031
|
308,031
|
308,031
|
R2
|
0.84
|
0.86
|
0.03
|
Adjusted R2
|
0.84
|
0.86
|
0.03
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
kableExtra::kable(summary_info)
Model
|
Value
|
Test
|
T Statistic
|
Conclusion
|
Model Description
|
paglin72
|
34702.1237052
|
> 0
|
135.385620
|
Regressive
|
AV ~ SP
|
cheng74
|
0.9136623
|
< 1
|
1348.353690
|
Regressive
|
ln(AV) ~ ln(SP)
|
IAAO78
|
-0.0000001
|
< 0
|
-97.596795
|
Regressive
|
RATIO ~ SP
|
kochin82
|
0.9359248
|
< 1
|
1348.353690
|
Regressive
|
ln(SP) ~ ln(AV)
|
bell84
|
20314.8672457
|
> 0
|
77.266036
|
Regressive
|
AV ~ SP + SP^2
|
|
0.0000000
|
< 0
|
-157.626702
|
Regressive
|
AV ~ SP + SP^2
|
sunderman90
|
11111.3515478
|
> 0
|
5.063213
|
Regressive
|
AV ~ SP + low + high + low * SP + high * SP
|
iaao_graphs
iaao_rslt <-
cmfproperty::iaao_graphs(
stats,
ratios,
min_reporting_yr = 2015,
max_reporting_yr = 2019,
jurisdiction_name = "Cook County, Illinois"
)
Coefficient of Dispersion (COD)
print(iaao_rslt[[1]])
#> [1] "For 2019, the COD in Cook County, Illinois was 18.19 which <b>did not meet</b> the IAAO standard for uniformity. "
iaao_rslt[[2]]
monte_carlo_graphs
m_rslts <- cmfproperty::monte_carlo_graphs(ratios)
gridExtra::grid.arrange(m_rslts[[1]],
m_rslts[[2]],
m_rslts[[3]],
m_rslts[[4]],
m_rslts[[5]],
m_rslts[[6]],
nrow = 3)
diagnostic_plots
plots <-
diagnostic_plots(stats,
ratios,
min_reporting_yr = 2015,
max_reporting_yr = 2019)
gridExtra::grid.arrange(plots[[6]],
plots[[7]],
plots[[8]],
plots[[9]],
ncol = 2,
nrow = 2)
binned_scatter
binned <-
cmfproperty::binned_scatter(
ratios,
min_reporting_yr = 2015,
max_reporting_yr = 2019,
jurisdiction_name = "Cook County, IL"
)
print(binned[[1]])
#> [1] "In 2019, the most expensive homes (the top decile) were assessed at 87.1% of their value and the least expensive homes (the bottom decile) were assessed at 102.0%. In other words, the least expensive homes were assessed at <b>1.17 times</b> the rate applied to the most expensive homes. Across our sample from 2015 to 2019, the most expensive homes were assessed at 83.4% of their value and the least expensive homes were assessed at 109.4%, which is <b>1.31 times</b> the rate applied to the most expensive homes."
binned[[2]]
pct_over_under
pct_over <-
cmfproperty::pct_over_under(
ratios,
min_reporting_yr = 2015,
max_reporting_yr = 2019,
jurisdiction_name = "Cook County, IL"
)
print(pct_over[[1]])
#> [1] "In Cook County, IL, <b>68%</b> of the lowest value homes are overassessed and <b>39%</b> of the highest value homes are overassessed."
pct_over[[2]]