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 nonarm'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

R^{2}

0.84

0.86

0.03

Adjusted R^{2}

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]]