create_sensitivity

Create model with sensitivity scenarios

Define, simulate, and validate stock-flow consistent (SFC) macroeconomic models. The godley R package offers tools to dynamically define model structures by adding variables and specifying governing systems of equations. With it, users can analyze how different macroeconomic structures affect key variables, perform parameter sensitivity analyses, introduce policy shocks, and visualize resulting economic scenarios. The accounting structure of SFC models follows the approach outlined in the seminal study by Godley and Lavoie (2007, ISBN:978-1-137-08599-3), ensuring a comprehensive integration of all economic flows and stocks. The algorithms implemented to solve the models are based on methodologies from Kinsella and O'Shea (2010) <doi:10.2139/ssrn.1729205>, Peressini and Sullivan (1988, ISBN:0-387-96614-5), and contributions by Joao Macalos.

Elżbieta Jowik

godley

Stock-Flow-Consistent Model Simulator

create_sensitivity function

<dl><dt>model_pass</dt>
<dd>SFC model object that will be used as a baseline for sensitivity calculation</dd>
<dt>variable</dt>
<dd>string name of the variable that will be used</dd>
<dt>lower</dt>
<dd>numeric lower bound value of the variable</dd>
<dt>upper</dt>
<dd>numeric upper bound value of the variable</dd>
<dt>step</dt>
<dd>numeric step between upper and lower bounds for the variable to take value</dd></dl>

Arguments

Create model with sensitivity scenarios — create_sensitivity

<dl>

<dt>model_pass</dt>
<dd>SFC model object that will be used as a baseline for sensitivity calculation</dd>


<dt>variable</dt>
<dd>string name of the variable that will be used</dd>


<dt>lower</dt>
<dd>numeric lower bound value of the variable</dd>


<dt>upper</dt>
<dd>numeric upper bound value of the variable</dd>


<dt>step</dt>
<dd>numeric step between upper and lower bounds for the variable to take value</dd>

</dl>

create_sensitivity: Create model with sensitivity scenarios

Description

Usage

Value

Arguments