MACROECONOMIC IMPACT MODEL OVERVIEW FOR PENNSYLVANIA. by Adam Rose University of Southern California. Objective. Explain macroeconomic modeling of potential climate change mitigation/sequestration options : - Macroeconometric model (REMI) - Data requirements - Application.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
University of Southern California
- Macroeconometric model (REMI)
- Data requirements
(REMI differs in that it includes these key relationships but is based on a more bottom-up approach. In fact, it makes use of the finely-grained sectoring detail of an I-O model.)
- integrates I-O, CGE, econometric & econ geography methods
- dynamic, with forecasts & simulations generated on annual basis
- behavioral responses to wage, price, and other economic factors
- relatively straightforward structure.
- five major blocks:
1) Output and Demand
2) Labor and Capital Demand
3) Population and Labor Supply
4) Wages, Prices and Costs
5) Market Shares
A. Model Performance Criteria
B. CGE ModelModel Specifications
C. CGE ModelParameter Values
A. Model Performance Criteria
1. Accuracy. REMI is capable of a high level of accuracy. It is widely used, indirectly testifying to their abilities on this score. While there are goodness of fit measures for some macroeconometric models, they are not available for individual equations or the entirety of REMI. Still, the inferential statistical approach used to construct REMI is considered the soundest economic modeling approach.
A high level of sectoral resolution improves the accuracy of the model. Care in factoring in special features of mitigation options, and future technological and structural changes improves accuracy, as does care in modeling mitigation options and linking them to the appropriate variables.
Of course, there is a tradeoff between cost and accuracy.
2. Scope. REMI is capable of analyzing the entire state economy and the major macroeconomic indicators of interest to this study.
3. CGE ModelDetail. The REMI model is disaggregated to as fine a level of detail as desired in terms of economic sectors. For example, the utilities sector clearly distinguishes gas and electricity.
4. Transparency. REMI is not a black box. The workings of REMI can be readily explained by using simple economic principles. Individual functional relationships can be extracted for further examination.
5. Manageability. The REMI model is relatively straightforward to use and comes with a user’s guide.
6. Cost. REMI is a modestly priced model.
7. Forecasting ability. REMI is able to generate forecasts for future baselines.
B. Model Specifications CGE Model
1. Geographic area of coverage. The REMI model covers the entire state of PA.
2. Time of analysis. The model is capable of analyzing the entire time period of 2009-20.
3. Macroeconomic Indicators. REMI is adept at evaluating impacts on both GSP and employment.
4. Sectoral Resolution. The REMI model contains 169 sectors, which is adequate for the task.
C. Parameter Values CGE Model
1. Flexibility. The REMI model can be used in a variety of ways and under a variety of critical assumptions.
2. Productivity and Competitiveness. REMI has a formal and comprehensive approach to assessing these.
3. Economic Growth. REMI can do this in its forecasts.
4. Population Growth. REMI can do this in its forecasts.
5. Trend Factors. REMI can do this through the inclusion of exogenous variables.
D. Technology Transfer. REMI is the most widely used state-level macroeconometric model. The company provides excellent training and technical support.