Skip to contents

Function to calculate investment thresholds and identify large deviation jumps

Source: R/ffp_invest.R
ffp_hfid_invest_jump.Rd

This function takes a data frame of asset loan data and calculates investment thresholds based on standard deviation. It then identifies large deviation jumps in the investment variables.

Usage

ffp_hfid_invest_jump(
  df_asset,
  fl_sd_ithres = stats::qnorm(0.99),
  svr_hhid = "id",
  svr_time = "month",
  verbose = FALSE,
  verbose_detail = FALSE,
  it_verbose_detail_nrow = 100
)

Arguments

df_asset

A data frame containing asset data

fl_sd_ithres

Standard deviation threshold for investments

svr_hhid

Variable name for household ID

svr_time

Variable name for time

verbose

Logical indicating whether to print verbose output (default is TRUE)

verbose_detail

Logical indicating whether to print detailed verbose output (default is TRUE)

it_verbose_detail_nrow

Number of rows to print for detailed verbose output (default is 100)

Value

A data frame with identified investment jumps and auxiliary variables

References

PrjThaiHFID-issue-1, step 1 and 4

Author

Fan Wang, http://fanwangecon.github.io

Examples

df <- tstm_asset_loan
fl_sd_ithres <- stats::qnorm(0.99)
ffp_hfid_invest_jump(df, fl_sd_ithres = fl_sd_ithres)
#> # A tibble: 800,296 × 8
#> # Groups:   id, ivars [5,607]
#>       id month ivars     value value_df value_df_sd bl_value_jump thres_inv_dfsd
#>    <dbl> <dbl> <chr>     <dbl>    <dbl>       <dbl>         <dbl>          <dbl>
#>  1 70201     0 agg_BS_… 1.52e5     NA          187.             0           2.33
#>  2 70201     1 agg_BS_… 1.52e5    -21.9        187.             0           2.33
#>  3 70201     2 agg_BS_… 1.52e5    -21.5        187.             0           2.33
#>  4 70201     3 agg_BS_… 1.52e5    -21.1        187.             0           2.33
#>  5 70201     4 agg_BS_… 1.52e5    -20.7        187.             0           2.33
#>  6 70201     5 agg_BS_… 1.52e5    -20.4        187.             0           2.33
#>  7 70201     6 agg_BS_… 1.52e5    -20.0        187.             0           2.33
#>  8 70201     7 agg_BS_… 1.52e5    -19.7        187.             0           2.33
#>  9 70201     8 agg_BS_… 1.52e5    -19.3        187.             0           2.33
#> 10 70201     9 agg_BS_… 1.52e5    -19.0        187.             0           2.33
#> # ℹ 800,286 more rows