calculate_fisher: Calculate direct index according to the Fisher hedonic double...

In cbsREPS: Hedonic and Multilateral Index Methods for Real Estate Price Statistics

Calculate direct index according to the Fisher hedonic double imputation method

Description

By the parameters 'dependent_variable', 'continue_variable' and 'categorical_variables' as regression model is compiled. With the model, a direct series of index figures is estimated by use of hedonic regression.

Usage

calculate_fisher(
  dataset,
  period_variable,
  dependent_variable,
  continuous_variables,
  categorical_variables,
  reference_period = NULL,
  number_of_observations = FALSE
)

Arguments

dataset	table with data (does not need to be a selection of relevant variables)
period_variable	variable in the table with periods
dependent_variable	usually the sale price
continuous_variables	vector with quality determining numeric variables (no dummies)
categorical_variables	vector with quality determining categorical variables (also dummies)
reference_period	period or group of periods that will be set to 100 (numeric/string)
number_of_observations	number of observations per period (default = TRUE)

Details

N.B.: the independent variables must be entered transformed (and ready) in the parameters. Hence, not: log(floor_area), but transform the variable in advance and then provide log_floor_area. This does not count for the dependent variable. This should be entered untransformed

Within the data, it is not neccesary to filter the data on relevant variables or complete records. This is taken care of in the function.

Value

table with index, imputation averages, number of observations and confidence intervals per period

Author(s)

Farley Ishaak

cbsREPS documentation built on June 8, 2025, 9:38 p.m.