/Disaggregating-input-output-models-with-incomplete-information

Implementation of "Disaggregating input-output models with incomplete information" by Lindner et al. (2012) in Python.

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Disaggregating input-output models with incomplete information

Implementation of Lindner et al. (2012) in Python with NumPy and Pandas.

Lindner, Sören, Julien Legault, and Dabo Guan. 2012. ‘Disaggregating Input–Output Models with Incomplete Information’. Economic Systems Research 24 (4): 329–47. https://doi.org/10.1080/09535314.2012.689954.

The comments in main.py originate from cesr_a_689954_sup_27358897.docx (accessed 12.12.2022).

The script of Lindner et al. (2012) contains one aspect of randomness:

  • base(p,:) = rand(1,Nv) in the original Matlab script and ...
  • ... base[p, :] = np.random.rand(1, Nv) in the Python script.

For verification purposes, e.g. np.random.seed(1337) (Python) and rand('twister', 1337) (Matlab) can be inserted to render the random numbers predictable.

Verification

The content of D.

Matlab

main.m

Python

main.m