update pycps docstring. update wage groups, add 2015 targets for pens…

…ion contribution imputations.

docs/book/content/data/puf_file_doc.md

@@ -17,4 +17,6 @@ Coming soon...
 
 ## Final Prep
 
-Coming soon...
+### Imputing Pension Contributions
+
+Target data source: [IRS SOI W-2 statistics](https://www.irs.gov/statistics/soi-tax-stats-individual-information-return-form-w2-statistics)

taxdata/cps/pycps.py

@@ -327,13 +327,15 @@ def pycps(cps: list, year: int, ctam_benefits: bool, verbose: bool) -> pd.DataFr
     Parameters
     ----------
     cps: List where each element is a household in the CPS
+    year: CPS year to use
+    ctam_benefits: If true, attach C-TAM benefits to the CPS
+    verbose
     """
     tax_units = []
-    ctam_benefits = True
     if year not in C_TAM_YEARS and ctam_benefits:
         raise ValueError(f'C-TAM Benefits not available for year {year}')
     for hh in tqdm(cps):
-        tax_units += create_units(hh, year - 1, ctam_benefits=ctam_benefits)
+        tax_units += create_units(hh, year - 1, ctam_benefits=ctam_benefits, verbose=verbose)
     # create a DataFrame of tax units with the new
     tax_units_df = pd.DataFrame(tax_units)
 

taxdata/puf/impute_pencon.py

@@ -39,16 +39,10 @@
 for details.
 """
 from __future__ import print_function
-import sys
 import numpy as np
 import pandas as pd
 from pathlib import Path
 
-if sys.version_info[0] < 3:
-    from StringIO import StringIO
-else:
-    from io import StringIO
-
 
 CURPATH = Path(__file__).resolve().parent
 DUMP0 = False
@@ -96,7 +90,7 @@ def targets(year):
     1e6,
     2e6,
     5e6,
-    30e6,
+    124e6,
 ]
 
 
@@ -156,7 +150,8 @@ def wage_group(row):
 # several times each with a different value of HIWAGE_PROB_SF.
 
 
-# specify maximum legal elective deferral amount for DC pensions in 2011
+# specify maximum legal elective deferral amount for DC pensions in each year
+# the PUF is supported
 MAX_PENCON_AMT = {2011: 16500, 2015: 1800}