Modern End-to-End Programming: Data Preparation, Model Building & Debugging

Slide Note
Embed
Share

Prepare, build, debug models covering historical data. Make assumptions, solve equations, ensure data, economic consistency. Iterative processes for accurate simulations.


Uploaded on Mar 05, 2024 | 3 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

E N D

Presentation Transcript


  1. MFMSA_MKD MODEL BUILD BACK-END PROGRAMMING

  2. MFMSA_MKD MODEL BUILD PROCESS Prepare Data Build Model Debug Model Write and estimate equations over historical data Make assumptions for exogenous/global variables Make assumptions on add-factors Compile and solve model Adjust front-end to be consistent with Eviews model Data consistency: historical data consistent with model equations/identity Coefficients make sense: trade-off between data fitting vs. economic/simulatio n properties Long-run properties observed Simulation properties observed Collect relevant data Make necessary transformations to ensure accounting and economic consistency Iterative Process!

  3. MFMSA_MKD MODEL BUILD PROCESS: 00_master.prg Prepare Data Build Model Debug Model Collect relevant data 01_read_data.prg Make necessary transformations to ensure accounting and economic consistency 02_create_data.prg 02a_create_potl.prg Write and estimate equations over historical data 03_equations.prg Make assumptions for exogenous/global variables Make assumptions on add-factors 04_extend_exog.prg Compile and solve model 05_solve_model.prg Adjust front-end to be consistent with Eviews model 06_interface.prg Data consistency: historical data consistent with model equations/identity Coefficients make sense: trade-off between data fitting vs. economic/simulation properties Long-run properties observed 07_convergence.prg Simulation properties observed 08_IRF.prg Iterative Process!

  4. MFMSA_MKD MODEL BUILD PROCESS: DATA Model\Data\MKDdataforupdate.xlsx Time series data MKDdataforupdate : N. Macedonia s macro, fiscal, external, monetary data (history) global : trade, tourism- and remittance-sending countries imports, exchange rate, inflation, and nominal GDP (historical + forecast) commodities : World Bank s commodity price (history + forecast) hnp_pop_proj : World Bank s population (history + forecast) Fixed parameters remittance_matrix : top 10 remittance-sending countries and their weights trade_matrix : top 10 importing partners and their weights tourism_matrix: top 10 tourist-sending partners and their weights for Nepal Note: Commodity (imports & exports) matrices (with the raw data and calculations) are in the Commodity_Matrix_Update subfolder.

  5. MFMSA_MKD MODEL BUILD PROCESS: EVIEWS Set global parameters: sample periods, solver, diagnostic triggers Sequence of Eviews program to execute automatically 00_master. prg Read country-specific and global data from MKDdataforupdate.xlsx 01_read_da ta.prg 02_create_data.prg: transform, calculate, balance country and global data 02a_create_potl.prg: estimate capital stock, TFP, potential output 02_*.prg Estimate behavioral equations; reinforce identities and quasi-identities using historical data 03_equatio ns.prg Provide forecast for global, exogenous variables and structural parameters 04_extend_ exog.prg Compile and solve model over history; generate add-factors Extend add-factor into forecast period solve out of sample 05_solve_m odel.prg Set interface page setting options 06_interfac e.prg 07_convergence.prg: graph long-run and ECM dynamics 08_IRF: impulse response simulations 07_converg ence.prg; 08_IRF.prg

  6. MFMSA_MKD MODEL BUILD PROCESS GUIDE Workshop homepage:https://isimulate.worldbank.org/mfm_admin/Mission/MKD Model layout (theory + equations): 04_ModelLayout_MKD.pptx Model build data files and programs (Eviews): Build folder ; most important Master input data file: MKDdataforupdate.xlsx Master Eviews program: 00_master.prg Reading MFMSA mnemonics and equations: 05_ReadingMFMSA.pptx Changing Excel front-end: PPT: 11_MakingChangesFrontEnd.pptx Eviews program: 06_interface.prg

  7. MFMSA_MKD MODEL BUILD PROCESS GUIDE: UPDATE EXAMPLE 1 Change history end date to 2023 (currently 2022) Questions to consider before proceeding: Is the change in history or forecast? Where can we put in this change (macroeconomic account, file .)? Does the new value have the intended unit and scale? Equations and identities involving this this variable in our model? Expected change and adjustment?

  8. MFMSA_MKD MODEL BUILD PROCESS GUIDE: UPDATE EXAMPLE 2 Adjust an identity: remove Revenue Sharing between Provincial and Local under Provincial Account Questions to consider before proceeding: Is the change in history or forecast? Where can we put in this change (macroeconomic account, file .)? Does the new value have the intended unit and scale? Equations and identities involving this this variable in our model? Expected change and adjustment?

  9. MFMSA_MKD MODEL BUILD PROCESS GUIDE: UPDATE EXAMPLE 3 Adjust an identity: adjust CIT to just a fixed share of GDP at Factor Cost Questions to consider before proceeding: Is the change in history or forecast? Where can we put in this change (macroeconomic account, file .)? Does the new value have the intended unit and scale? Equations and identities involving this this variable in our model? Expected change and adjustment?

  10. MFMSA_MKD MODEL BUILD PROCESS GUIDE: UPDATE EXAMPLE 4 ADD TFP, CAPITAL STOCK, AND EMPLOYMENT AS CONTRIBUTION TO GROWTH OF POTENTIAL OUTPUT IN REPORTS TAB Tips: (1) Cobb-Douglas Production functional form for Potential Output ??= ??? ?? ?? 1 (2) Growth decomposition in log form ??= ??? + ? ? + 1 ? ?? 1 1 ?

Related


More Related Content