Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/102583
Title: | STEMM : short-term quarterly econometric forecasting model for Malta |
Other Titles: | Economic Policy Department Ministry for Finance |
Authors: | Camilleri, Gilmour Cassar Overend, Andrew Lewney, Richard Buttigieg, Sean Agius, Lynette Vella, Melchior Camilleri, Denise Vella, Kevin |
Keywords: | Econometric models -- Malta Macroeconomics Prices -- Malta Stock price forecasting -- Malta |
Issue Date: | 2019 |
Publisher: | Malta. Ministry for Finance |
Citation: | Vella, K., Camilleri, G., Cassar Overand, A., Lewney, R., Buttigieg, S., Agius, L.,...Camilleri, D. (2019). STEMM : short-term quarterly econometric forecasting model for Malta. Malta : Ministry for Finance. |
Abstract: | The Short-Term Quarterly Econometric Forecasting Model for Malta (STEMM) is the basis for the official macroeconomic projections, the fiscal projections and the fiscal targets of the Government of Malta. STEMM is a Keynesian model where aggregate demand determines output in the presence of price rigidities in the short-term. The model was originally developed in 2001 by the Economic Policy Department through the assistance of Cambridge Econometrics (UK). The model is medium-scale, consisting of six main blocks. It is composed of 47 identity equations and 69 behavioural equations, most of them specified as an error correction model specification estimated on quarterly European System of Accounts (ESA) 2010 chain-linked data from 1995 to 2016 in accordance with the Engle-Granger two-stage approach. Moreover, there are 47 exogenous variables, consisting of economic variables related to our trading partners, exchange rates, commodity prices, fiscal variables and dummy variables. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/102583 |
Appears in Collections: | Scholarly Works - FacEMAEco |
Files in This Item:
File | Description | Size | Format | |
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STEMM_short_term_quarterly_econometric_forecasting_model_for_Malta_2019.pdf | 1.63 MB | Adobe PDF | View/Open |
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