Abstract
Yes it is. We rigorously demonstrate the equivalence of any stock flow consistent (SFC) model to a directed acyclic graph (DAG) using condensation graphs. The equivalence between stock flow models and DAGs is useful both for visualising large-scale macroeconomic models of this type and for inferring causality within these models. We developed a new package to build and simulate any SFC model and generate the corresponding DAGs, and we provide an example of this package using a well known model from the literature.
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Notes
Estimation is the process of discovering constant parameters using econometric methods such as ordinary least squares, maximum likelihood, Bayesian techniques, etc. Calibration, on the other hand, consists in finding a value for each parameter, in each period, such that the model replicates the data set.
This process is similar to the more well-known dynamic stochastic general equilibrium class of models, see Heer and Maussner (2009, Chap. 1) for an introduction.
These exogenous innovation terms will not be included in our formal description of the models.
The Github repository for the code is at github.com/S120/PKSFC, where the complete R package and documentation can be freely downloaded.
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Acknowledgments
We thank Dan Neilsen and Oliver Burrows for useful comments on an earlier draft. Kinsella gratefully acknowledges the support of the Institute for New Economic Thinking under grant number INO1300030.
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Fennell, P.G., O’Sullivan, D.J.P., Godin, A. et al. Is It Possible to Visualise Any Stock Flow Consistent Model as a Directed Acyclic Graph?. Comput Econ 48, 307–316 (2016). https://doi.org/10.1007/s10614-015-9521-8
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DOI: https://doi.org/10.1007/s10614-015-9521-8