Merge pull request #71 from jdebacker/fix_calib_run

Merging

MANIFEST.in

@@ -1 +1,2 @@
 include ogzaf/ogzaf_default_parameters.json
+include ogzaf/ogzaf_default_parameters_multisector.json

examples/run_og_zaf.py

@@ -6,20 +6,18 @@
 import json
 import time
 import copy
+import importlib.resources
 import matplotlib.pyplot as plt
 from ogzaf.calibrate import Calibration
 from ogcore.parameters import Specifications
 from ogcore import output_tables as ot
 from ogcore import output_plots as op
 from ogcore.execute import runner
-from ogcore.utils import safe_read_pickle, param_dump_json
+from ogcore.utils import safe_read_pickle
+from ogzaf.utils import is_connected
 
 # Use a custom matplotlib style file for plots
-style_file_url = (
- "https://raw.githubusercontent.com/PSLmodels/OG-Core/"
- + "master/ogcore/OGcorePlots.mplstyle"
-)
-plt.style.use(style_file_url)
+plt.style.use("ogcore.OGcorePlots")
 
 
 def main():
@@ -30,8 +28,9 @@ def main():
 
  # Directories to save data
  CUR_DIR = os.path.dirname(os.path.realpath(__file__))
- base_dir = os.path.join(CUR_DIR, "OG-ZAF-Example", "OUTPUT_BASELINE")
- reform_dir = os.path.join(CUR_DIR, "OG-ZAF-Example", "OUTPUT_REFORM")
+ save_dir = os.path.join(CUR_DIR, "OG-ZAF-Example")
+ base_dir = os.path.join(save_dir, "OUTPUT_BASELINE")
+ reform_dir = os.path.join(save_dir, "OUTPUT_REFORM")
 
  """
  ---------------------------------------------------------------------------
@@ -46,33 +45,16 @@ def main():
  output_base=base_dir,
  )
  # Update parameters for baseline from default json file
- p.update_specifications(
- json.load(
- open(
- os.path.join(
- CUR_DIR, "..", "ogzaf", "ogzaf_default_parameters.json"
- )
- )
- )
- )
+ with importlib.resources.open_text(
+ "ogzaf", "ogzaf_default_parameters.json"
+ ) as file:
+ defaults = json.load(file)
+ p.update_specifications(defaults)
  # Update parameters from calibrate.py Calibration class
- c = Calibration(p)
- updated_params = c.get_dict()
- p.tax_func_type = "linear"
- p.age_specific = False
- p.update_specifications(updated_params)
- # set underlying growth rate to zero, as value from data is negative
- p.g_y = 0.0
- # set tax rates
- p.update_specifications(
- {
- "cit_rate": [[0.27]],
- "etr_params": [[[0.22]]],
- "mtrx_params": [[[0.31]]],
- "mtry_params": [[[0.25]]],
- "tau_c": [[0.15]],
- }
- )
+ if is_connected(): # only update if connected to internet
+ c = Calibration(p)
+ updated_params = c.get_dict()
+ p.update_specifications(updated_params)
 
  # Run model
  start_time = time.time()
@@ -90,7 +72,7 @@ def main():
  p2.baseline = False
  p2.output_base = reform_dir
 
- # additional parameters to change
+ # Parameter change for the reform run
  updated_params_ref = {
  "cit_rate": [[0.30]],
  }
@@ -128,12 +110,12 @@ def main():
 
  # create plots of output
  op.plot_all(
- base_dir, reform_dir, os.path.join(CUR_DIR, "OG-ZAF_example_plots")
+ base_dir, reform_dir, os.path.join(save_dir, "OG-ZAF_example_plots")
  )
 
  print("Percentage changes in aggregates:", ans)
  # save percentage change output to csv file
- ans.to_csv("ogzaf_example_output.csv")
+ ans.to_csv(os.path.join(save_dir, "OG-ZAF_example_output.csv"))
 
 
 if __name__ == "__main__":

examples/run_og_zaf_multiple_industry.py

@@ -6,27 +6,29 @@
 import json
 import time
 import copy
-import numpy as np
-
-# from taxcalc import Calculator
-from ogzaf.calibrate import Calibration
+import importlib.resources
+import matplotlib.pyplot as plt
 from ogcore.parameters import Specifications
 from ogcore import output_tables as ot
 from ogcore import output_plots as op
 from ogcore.execute import runner
 from ogcore.utils import safe_read_pickle, param_dump_json
 
+# Use a custom matplotlib style file for plots
+plt.style.use("ogcore.OGcorePlots")
+
 
 def main():
  # Define parameters to use for multiprocessing
- client = Client()
  num_workers = min(multiprocessing.cpu_count(), 7)
+ client = Client(n_workers=num_workers, threads_per_worker=1)
  print("Number of workers = ", num_workers)
 
  # Directories to save data
  CUR_DIR = os.path.dirname(os.path.realpath(__file__))
- base_dir = os.path.join(CUR_DIR, "OG-ZAF-CIT_Example", "OUTPUT_BASELINE")
- reform_dir = os.path.join(CUR_DIR, "OG-ZAF-CIT_Example", "OUTPUT_REFORM")
+ save_dir = os.path.join(CUR_DIR, "OG-ZAF-MultipleIndustry-example")
+ base_dir = os.path.join(save_dir, "OUTPUT_BASELINE")
+ reform_dir = os.path.join(save_dir, "OUTPUT_REFORM")
 
  """
  ---------------------------------------------------------------------------
@@ -41,32 +43,11 @@ def main():
  output_base=base_dir,
  )
  # Update parameters for baseline from default json file
- p.update_specifications(
- json.load(
- open(
- os.path.join(
- CUR_DIR, "..", "ogzaf", "ogzaf_default_parameters.json"
- )
- )
- )
- )
- # Update parameters from calibrate.py Calibration class
- p.M = 4
- p.I = 5
- c = Calibration(p)
- updated_params_tax = {
- # order of industries is primary, energy, tertiary, secondary ex energy
- "Z": [[0.5, 0.4, 1.7, 1.0]],
- "epsilon": [1.0, 1.0, 1.0, 1.0],
- "gamma": [0.67, 0.50, 0.45, 0.53],
- "gamma_g": [0.0, 0.0, 0.0, 0.0],
- "alpha_c": c.alpha_c,
- "io_matrix": c.io_matrix,
- }
- p.update_specifications(updated_params_tax)
-
- # dump params to json
- param_dump_json(p, os.path.join(base_dir, "model_params.json"))
+ with importlib.resources.open_text(
+ "ogzaf", "ogzaf_default_parameters_multisector.json"
+ ) as file:
+ defaults = json.load(file)
+ p.update_specifications(defaults)
 
  # Run model
  start_time = time.time()
@@ -84,12 +65,14 @@ def main():
  p2.baseline = False
  p2.output_base = reform_dir
 
- # additional parameters to change
+ # Example reform is a corp tax rate cut (phased in) for all
+ # industries EXCEPT for secondary ex energy, which has a one point
+ # increae in the CIT rate
  updated_params_ref = {
  "cit_rate": [
- [0.28, 0.28, 0.28, 0.28],
- [0.28, 0.28, 0.28, 0.28],
- [0.27, 0.27, 0.27, 0.27],
+ [0.27, 0.27, 0.27, 0.28],
+ [0.26, 0.26, 0.26, 0.28],
+ [0.25, 0.25, 0.25, 0.28],
  ],
  "baseline_spending": True,
  }
@@ -129,12 +112,14 @@ def main():
  op.plot_all(
  base_dir,
  reform_dir,
- os.path.join(CUR_DIR, "OG-ZAF_CIT_multi_industry_plots"),
+ os.path.join(save_dir, "OG-ZAF-MultipleIndustry-example_plots"),
  )
 
  print("Percentage changes in aggregates:", ans)
  # save percentage change output to csv file
- ans.to_csv("ogzaf_CIT_multi_industry_output.csv")
+ ans.to_csv(
+ os.path.join(save_dir, "OG-ZAF-MultipleIndustry-example_output.csv")
+ )
 
 
 if __name__ == "__main__":

ogzaf/calibrate.py

@@ -2,6 +2,7 @@
 from ogzaf import input_output as io
 import os
 import numpy as np
+import datetime
 from ogcore import demographics
 
 
@@ -11,8 +12,8 @@ class Calibration:
  def __init__(
  self,
  p,
- estimate_tax_functions=False,
- estimate_chi_n=False,
+ macro_data_start_year=datetime.datetime(1947, 1, 1),
+ macro_data_end_year=datetime.date.today(),
  demographic_data_path=None,
  output_path=None,
  ):
@@ -21,9 +22,6 @@ def __init__(
 
  Args:
  p (OG-Core Specifications object): model parameters
- estimate_tax_functions (bool): whether to estimate tax
- function parameters
- estimate_chi_n (bool): whether to estimate chi_n
  demographic_data_path (str): path to save demographic data
  output_path (str): path to save output to
 
@@ -35,11 +33,11 @@ def __init__(
  if output_path is not None:
  if not os.path.exists(output_path):
  os.makedirs(output_path)
- self.estimate_tax_functions = estimate_tax_functions
- self.estimate_chi_n = estimate_chi_n
 
  # Macro estimation
- self.macro_params = macro_params.get_macro_params()
+ self.macro_params = macro_params.get_macro_params(
+ macro_data_start_year, macro_data_end_year
+ )
 
  # io matrix and alpha_c
  if p.I > 1: # no need if just one consumption good
@@ -96,8 +94,6 @@ def __init__(
  # method to return all newly calibrated parameters in a dictionary
  def get_dict(self):
  dict = {}
- # if self.estimate_chi_n:
- # dict["chi_n"] = self.chi_n
  dict.update(self.macro_params)
  dict["e"] = self.e
  dict["alpha_c"] = self.alpha_c

ogzaf/income.py

@@ -313,7 +313,7 @@ def get_e_interp(S, age_wgts, age_wgts_80, abil_wgts, plot_path=None):
 
 
 def get_e_orig(age_wgts, abil_wgts, plot_path=None):
- """
+ r"""
  This function generates the 80 x 7 matrix of lifetime earnings
  ability profiles, corresponding to annual ages from 21 to 100 and to
  paths based on income percentiles 0-25, 25-50, 50-70, 70-80, 80-90,

ogzaf/input_output.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import numpy as np
+from ogzaf.utils import is_connected
 from ogzaf.constants import CONS_DICT, PROD_DICT
 
 """
@@ -8,13 +9,16 @@
 # Read in SAM file
 storage_options = {"User-Agent": "Mozilla/5.0"}
 SAM_path = "https://www.wider.unu.edu/sites/default/files/Data/SASAM-2015-Data-Resource.xlsx"
-SAM = pd.read_excel(
- SAM_path,
- sheet_name="Micro SAM 2015",
- skiprows=6,
- index_col=0,
- storage_options=storage_options,
-)
+if is_connected():
+ SAM = pd.read_excel(
+ SAM_path,
+ sheet_name="Micro SAM 2015",
+ skiprows=6,
+ index_col=0,
+ storage_options=storage_options,
+ )
+else:
+ SAM = None
 
 
 def get_alpha_c(sam=SAM, cons_dict=CONS_DICT):