Benchmark household unique investment dates — tstm_invdates

Household and investment (unique start and end months) as units of observation. This is a file derived from tstm_invest, considering only unique investment spans.

Usage

tstm_invdates_uniq

Format

Household and investment (unique start and end) file

id: Household ID
hh_inv_ctr: Unique household investment span counter
mth_inv_start: Start time of unique investment span
mth_inv_end: End time of unique investment span
thres_inv_mgap: Month gap allowed to merge investment jump together as one investment
thres_inv_dfds: Standard deviation threshold for counting investment jump

Source

Regenerated by vignettes/ffv_invest_loan_bridge.qmd via ffp_hfid_invest_loan_linked_abc_investloan_char_gateway() (PrjThaiHFID-#32). Set bl_replace_data_output <- TRUE in the vignette to overwrite data/*.rda. MBF filters: investment months 14–144, fl_min_invest_size = 10000, ar_st_vars_to_keep = c("agg_BS_1021", "agg_BS_1012", "agg_BS_1011"). Packaged inputs: tstm_loans_panel, tstm_asset_loan (see ?tstm_loans_panel). Household IDs are anonymized tmid_hh (id or hhid_Num), aligned with tstm_asset_loan. Three paper asset ivars only; hh_inv_ctr spans kept ivars (gateway early filter). Unique spans across kept ivars only. See also issue-1, step 2.

Details

Benchmark file with benchmark investment standard deviation, and investment gap allowance parameters. Multiple alternative investment variables are jointly considered and unique investment windows from across investment variables are found. Within household, investment spans can overlap due to them coming from different investment variable definitions.

Examples

data(tstm_invdates_uniq)
ffp_preview_dataset(tstm_invdates_uniq)
#> 
#> ── tstm_invdates_uniq ──────────────────────────────────────────────────────────
#> Dimensions: 3066 rows × 6 columns(181.9 Kb)
#> 
#> ── Column names (6) ──
#> 
#> • 1. thres_inv_mgap
#> • 2. thres_inv_dfsd
#> • 3. id
#> • 4. hh_inv_ctr
#> • 5. mth_inv_start
#> • 6. mth_inv_end
#> 
#> ── Summary statistics (all variables) ──
#> 
#>  thres_inv_mgap thres_inv_dfsd        id         hh_inv_ctr    
#>  Min.   :2      Min.   :2.326   Min.   :1003   Min.   : 1.000  
#>  1st Qu.:2      1st Qu.:2.326   1st Qu.:3108   1st Qu.: 2.000  
#>  Median :2      Median :2.326   Median :5486   Median : 3.000  
#>  Mean   :2      Mean   :2.326   Mean   :5449   Mean   : 3.108  
#>  3rd Qu.:2      3rd Qu.:2.326   3rd Qu.:7701   3rd Qu.: 4.000  
#>  Max.   :2      Max.   :2.326   Max.   :9996   Max.   :13.000  
#>  mth_inv_start     mth_inv_end    
#>  Min.   :  1.00   Min.   :  1.00  
#>  1st Qu.: 39.00   1st Qu.: 39.00  
#>  Median : 75.00   Median : 75.00  
#>  Mean   : 75.81   Mean   : 75.91  
#>  3rd Qu.:112.00   3rd Qu.:112.00  
#>  Max.   :160.00   Max.   :160.00  
#> ── Sample rows (first 6) ──
#> 
#> # A tibble: 6 × 6
#> # Groups:   id [3]
#>   thres_inv_mgap thres_inv_dfsd    id hh_inv_ctr mth_inv_start mth_inv_end
#>            <dbl>          <dbl> <int>      <int>         <dbl>       <dbl>
#> 1              2           2.33  1003          1             1           1
#> 2              2           2.33  1031          1             9           9
#> 3              2           2.33  1031          2            71          71
#> 4              2           2.33  1031          3            80          80
#> 5              2           2.33  1031          4           154         154
#> 6              2           2.33  1046          1             1           1