Estimating and Calibrating MFMod : A Panel Data Approach to Identifying the Parameters of Data Poor Countries in the World Bank's Structural Macro Model
This paper summarizes the World Bank's approach to identifying parameters for key equations in its macro structural model for countries where short sample sizes or major structural changes render traditional time-series approaches infeasible o...
| Main Authors: | , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2019
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/662391562848917501/Estimating-and-Calibrating-MFMod-A-Panel-Data-Approach-to-Identifying-the-Parameters-of-Data-Poor-Countries-in-the-World-Banks-Structural-Macro-Model http://hdl.handle.net/10986/32059 |
| Summary: | This paper summarizes the World
Bank's approach to identifying parameters for key
equations in its macro structural model for countries where
short sample sizes or major structural changes render
traditional time-series approaches infeasible or yield
unstable estimates. To identify parameters that could be
used in such cases, a cointegrating panel approach is
followed that yields a common long-run estimate of
parameters for key equations (to test the theoretical
restrictions imposed in the model) and short-run
disequilibrium estimates that vary by country. This approach
is preferred to pure calibration or Bayesian estimation,
because the functional forms imposed in the panel are
consistent with those used in the macro structural model. |
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