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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.

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macroeconomic impact model overview for pennsylvania

MACROECONOMIC IMPACT MODEL OVERVIEW FOR PENNSYLVANIA

by

Adam Rose

University of Southern California

objective
Objective
  • Explain macroeconomic modeling of potential climate change mitigation/sequestration options :

- Macroeconometric model (REMI)

- Data requirements

- Application

macroeconometric modeling
Macroeconometric Modeling
  • a forecasting model that covers the entire economy, typically in a “top-down” manner, based on macroeconomic aggregate relationships such as consumption and investment.

(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.)

  • based on inferential statistical estimation of key parameters
  • based on time series (historical) data; but also I-O data

www.climatestrategies.us

remi policy insight plus model
REMI Policy Insight Plus Model
  • Structural economic forecasting and policy analysis 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

  • Thousands of simultaneous equations:

- 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

modeling steps
Modeling Steps
  • Test REMI Model
  • Obtain data on mitigation/sequestration options
  • Link data to REMI policy variables
  • Simulate one option at a time
  • Simulate all options together
  • Analyze results
evaluative criteria and related considerations
Evaluative Criteria and Related Considerations

A. Model Performance Criteria

  • Accuracy
  • Scope
  • Detail
  • Transparency
  • Manageability
  • Cost
  • Other

www.climatestrategies.us

slide14
B.Model Specifications
  • Geographic area of coverage
  • Time of analysis
  • Macroeconomic Indicators
  • Sectoral Resolution

www.climatestrategies.us

slide15
C.Parameter Values
  • Flexibility
  • Productivity
  • Economic Growth
  • Population Growth
  • Trend Factors
  • Discount Rate

www.climatestrategies.us

model evaluation comparison with cge
Model Evaluation (Comparison with CGE)

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.

slide17
3. Detail. 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.

slide18
B. Model Specifications

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.

www.climatestrategies.us

slide19
C. Parameter Values

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.

overall assessment
Overall Assessment
  • Based on the analysis of above, the REMI Model is best qualified to be used to analyze the macroeconomic impacts of policies and measures to address climate change in Pennsylvania.
  • It is not the superior to all alternatives according to all indicators, but it is for most indicators.
  • Part of the advantage stems from the fact that the research team has experience using the REMI Model. Other major advantages stem from it’s econometric foundation, including its forecasting ability.
timetable for the project
Timetable for the Project
  • Finalize input data on options – July 15
  • Link policy options to REMI variables – Aug 1
  • Run preliminary simulations – Aug 14
  • Receive feedback on preliminary – Aug 21
  • Final runs and draft report – August 31
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