A Multiregional Macroeconomic Framework for Analyzing Energy Policies

Frederick R. Treyz, Scott Nystrom and Zilin Cui[2]

 

Introduction

As of 2009, more than thirty states in the United States have adopted a Renewable Portfolio Standard (RPS), requiring a specified minimum amount of electricity sales to come from renewable resources at an increasingly larger percentage.[3] Missouri is the twenty-seventh state to adopt a Renewable Energy Standard (RES), doing so in 2008. Implemented by the Missouri Public Service Commission (PSC), it requires all investor-owned utility companies (IOUs) to provide at least 15% of their electric power from renewable sources by 2021 and with a specific solar carve-out of 0.3% of the total sales.[4] Renewable energy sources exclude nuclear power, which produces around 11% of Missouri’s electricity.[5] In addition, the RPS statute includes a 1% cost cap in the future growth rates of retail electricity prices, which is designed to protect consumers in the face of an expect rise in prices.[6] For solar, all IOUs are required to offer a standard rebate of $2.00 per watt (up to 25kW) for solar electric systems installed by households or on farm buildings.[7]

 

Literature Review

Prior research found an RPS a statistically significant driver of development of renewable power generation development.[8] Wind is arguably the primary beneficiary of renewable policies, making up 94% of renewable energy development in the United States.[9] In Missouri, the leading source of renewable energy is also wind, making up 2.06% of all electricity generation in 2009, followed by 0.57% from hydropower.[10]

 

Other RPS studies have taken the following approaches: comparison between RPS states and their non-RPS counterparts,[11] benefit-cost analysis,[12] and in-state economic impact analysis.[13] The comparison method may overlook different baseline conditions between RPS and non-RPS states. A benefit-cost analysis cannot capture the economic impacts on jobs and specific industries by deriving a multiplier for investment in renewable energy, and in-state impact analysis may exaggerate impacts by assuming no trade flows and migration that spread the renewable energy growth beyond the state borders.

 

The REMI PI+ model overcomes these limitations in the following ways. Foremost, REMI PI+ creates a more accurate reference case by comparing simulations to the same region under a no-project circumstance, thus avoiding possible apples-to oranges comparisons in results. Second, REMI PI+ captures industry-specific impacts beyond a benefit-cost ratio by integrating input-output tables (I-O models), computable general equilibrium theory (CGE), econometric estimates, and New Economic Geography (NEG). PI+ also allows custom-designed scenarios to gauge the full impact of RPS, overcoming the limitation of available data by creating alternative, full cost-recovery scenarios. In addition, the dynamic model captures interstate trade flows and year-by-year population migration, which distinguishes net new economic activities from relocation of existing economic activity, as well as short-term impacts in comparison to long-term results.

 

 

Methodology

The REMI PI+ model for this study consists of five blocks:

(1) Output and Demand consist of output, demand, consumption, investment, government spending, exports and imports, as well as feedback from output changes due to the change in the productivity of intermediate inputs.

(2) Labor and Capital Demand include the determinants of labor productivity, labor intensity, and the optimal capital stocks.

(3) Population and Labor Supply include labor force participation and the economic migration equation, where demography responds to economic factors.

(4) Compensation, Prices, and Costs include composite prices, determinants of production costs, the consumption price deflator, housing prices, and the compensation equation.

(5) Market Shares consist of proportion of local, inter-regional, and export markets captured by each region. Figure 1 contains all model blocks, their components, and linkages without the New Economic Geography linkages, which Figure 1 highlights.

 

The inherent linkages capture exogenous shocks by tracing their ripple and feedback effects throughout the macro-economy, reflecting in impacts on not only the sectors and regions directly affected by the policy shift, but all industries and regions nationwide.

 

Figure 1

REMI model diagram (excluding New Economic Geography linkages)

 

 

 

Figure 2

New Economic Geography linkages

 

This study provides a framework for an accurate prediction of the economic impact of energy policy. Changes to indicators, such as output, employment, prices, and specific sectors come from an assumption of ceteris paribus from other states’ RPS implementation independent to that of Missouri.

 

To capture a full range of potential RPS impacts, this study crosses two types of cost estimates (high and low) for equipment installation with two financing options (payment “upfront” versus long-term bonding). This diagram illustrates the resulting four scenarios:

 

Table 1

 

The study assumes that an RPS replaces, rather than reduces, overall electricity sales projected by the EIA[16] by the statutory percentage required. In addition, we simplify the transition to a switch from the leading source of conventional electricity generation (coal) to the leading source of renewable generation (wind). The following table outlines the electricity production breakdown with the solar mandate and percentages of coal, wind, and other sources according to the assumption. Demand for commercial-scale wind farms result in intermediate demand for inputs of construction, turbine manufacturing, design, and management. Demand for farm- and home-based solar panels result in demand for semiconductor manufacturing, construction, and reallocation of household spending.

 

Table 2

 

Based on the average annual generation of each solar installation (15,000kWh) and each wind turbine (10,000kWh)[18] and the amount of renewable energy needed above, one can obtain the number of panels and turbines needed. We calculate the total costs of the RPS by multiplying the unit costs of panels ($35,000-$45,000) and turbines ($35,000-$50,000[19]), while taking into account panel rebates of $2/W up to 25kW. To adjust for declining cost of new technology, we adjust solar costs downward by 2.86% and wind energy 0.3-0.75% per annum.[20] Additionally, solar panels depreciate at 4.0% and wind turbines at 5%,[21] annually, which we counted as the operations and maintenance (O&M) costs. To specify industry-specific demand impacts of renewable equipment, the total costs of wind turbines are broken down into 72.5% for turbine manufacturing, 17.5% for construction, 5% for architecture and design, and 5% for management and administration.[22]


Simulation Results

The simulation results address the RPS impact on these economic indicators: total employment, gross domestic product (GDP), real disposable income per capita, economic migration, electricity prices, utilities revenue, and utilities employment. Then, we compare the results for Missouri against another region, a region that consists of the other forty-nine states of the United States.

 

(1) Impact on total employment

Bond financing and the price cap yield opposite effects on Missouri employment over future years. An increase in future price hikes by 1% costs jobs in the short-run, but they recover to baseline conditions after the RPS goals come to fruition. Bond financing yields model job creation in the short-run but lower forecasts in the long-run as loans come mature. By comparing the rest of the nation against Missouri, as well, we see that jobs created from the bond financing for other regions come at a cost to Missouri’s job market during the same timeframe.

 

Figure 3

 

(2)    Impacts on real GDP

 

Closely mimicking employment patterns, an RPS expands gross domestic product in the rest of the nation at the cost of Missouri’s own economy. Missouri suffers, relatively speaking, from higher electricity prices due to the RPS, which reduces the state’s favorability to businesses and its cost of living to the population. Bond financing yields a short-term GDP increase of about $200 million in Missouri and about $700 million in the rest of the nation. A 1% price cap results in the long-term expansion of GDP in other states and the national economy after the completion of the RPS in 2021.

 

Figure 4

 

 

 

(3)    Impacts on personal real disposable income per capita

 

As households face higher electricity rates, real disposable income drops lower than baseline in the short-run (until 2021 for bond option and until 2023-2025 for 1% option). Short-term energy bill saving from home-generated solar generation is insufficient to offset overall higher electricity prices and installation expense. However, Missouri benefits in the end, with about 0.02% more in disposable income than baseline around 2035 regardless of RPS financing option. The effects on the rest of the nation and the United States as a whole are negligible.

 

 

Figure 5

 

 

 

(4)    Impacts on economic migration patterns

 

As employment conditions and cost of living changes, people move to states with more favorable conditions—a phenomenon captured a “net economic migration” in REMI PI+. The growth of renewable energy generation results in more jobs out of Missouri and higher electricity prices inside the state itself, which moves people out of the state due to higher costs of living and reduced employment opportunities. Once the RPS infrastructure is in place, Missouri becomes a more economically attractive region. We see the reversed pattern thereafter, with an inflow of people seeking better economic prospects.

 

Figure 6

 

 

(5)    Impacts on the utilities industry

  1. a. Impacts on electricity prices

 

Figure 7

 

 

Electricity prices rise under all scenarios. Bond financing softens price hike impacts in the short-run, but continues them into the longer window by deferring costs into the future. This extends the price increase up to 2035, resulting in higher prices than price-cap financing scenarios from 2023 to 2035.



b.     Impacts on the utilities sector revenue

 

Figure 8

 

 

The utilities industry expands because of the RPS pushing up electricity prices. Regardless of financing option, utility revenues expand in all regions short-term as a response to RPS. As demand for electricity is relatively inelastic, increased prices will result in increased revenue. Price cap financing induces slower, smoother increases that last longer out to 2023-2025 with $130-$186 million additional revenue, while financing results in spikes in utility revenue with $138-$200 million over the baseline from 2019 to 2021. However, it fades out soon afterwards and turns slightly lower than baseline due to prolonged bond payments.

 

 

c.       Impacts on utilities sector employment

 

Figure 9

 

 

The utilities sector employment follow the growth pattern of utilities sector revenue, increasing as the sector expands through 2021 (under bond financing) and 2023-2025 (under 1% price increase). Of some note, Missouri’s utilities sector expands despite overall lower employment forecast for all industries. In summary, an RPS benefits the utilities sector in all regions and overall job markets outside of Missouri. The RPS-induced growth results in short-term boom of the utilities sector and its supporting industries.

 

 

Conclusion

The Missouri RPS has differing effects on the economy, depending on the timeframe and the specific regional breakdown in question. In the short-term, the RPS causes an expansion in the utility industry in all regions in terms of both revenue and employment. In Missouri, as electricity prices and the costs of living rise, real personal disposable income shrinks and the opportunities of the job market decline, at least in the short-haul with upfront financing. People leave the state as a result, mitigating the net negative impact in the short-run on the national level. The sacrifice in Missouri in employment and GDP under the price cap results in positive impacts to the national and out-of-state economy. Most of the “green” jobs in the renewable sector fade away by 2025, while the other indirect and induced jobs outside of Missouri remain until 2035. As the RPS reaches implementation by 2012, disposable income crests above the baseline projections, and people move back into the state as Missouri becomes economically attractive to businesses and households.

 

REMI PI+, as a dynamic evaluation tool, allows for a panoramic view of the economy, by enabling a comparison between different policy options and “do nothing” scenarios. It also allows for an examination of inter-regional trade flows beyond a static, benefit-cost analysis or a simple one-region investigation. This provides information for policy evaluation, recommendation, as well as a separation of short-term and long-term impacts according to planning and policy priorities.

. Wind Energy Basics. http://archive.awea.org/f

 

 

 

References

 

American Wind Energy Association aq/wwt_basics.html>

Ancona, Dan and McVeigh, Jim. Princeton Energy Resources International, LLC. Wind Turbine—Materials and Manufacturing Fact Sheet. August 29, 2001. <http://www.perihq.com/documents/WindTurbine-MaterialsandManufacturing_FactSheet.pdf>

Brito, Dagobert and Juan Rosselon. Baker Institute for Public Policy. Energy and Nanotechnology: Prospects for Solar Energy in the 21st Century: The Political Economy of Solar Energy. December 2005.

Chen, Cliff, Ryan Wiser and Mark Bolinger. Ernest Orlando Lawrence Berkeley National Laboratory. Weighing the Costs and Benefits of State Renewable Portfolio Standards: A Comparative Analysis of State-Level Policy Impact Projections. March 2007.

European Commission, Directorate-General for Energy. Wind Energy–the Facts. Volume 2: Costs, Prices, and Values.

Hearps, Patrick and Dylan McDonnell. Melbourne Energy Institute. Renewable Energy Technology Cost Review. May 2011. >

Holtzman, James M. Benefit Cost Analysis for the Application of PV Solar in Missouri. Feb 2009.

Miller, Steven, Dan Wei, and Adam Rose. Center for Climate Strategies. The Macroeconomic Impact of the Wisconsin Clean Energy Jobs Act on the State’s Economy. Feb 2010.

Missouri Department of Natural Resources. Missouri’s Solar Energy Resource. <http://www.dnr.mo.gov/energy/renewables/solardata.htm>

Union of Concerned Scientists. Missouri Renewable Energy Standard Summary. <http://www.ucsusa.org/assets/documents/clean_energy/Missouri.pdf>

Treyz, Frederick, R. Macroeconomics of Green Energy.

U.S. Department of Energy. States with Renewable Portfolio Standards. Energy Efficiency and Renewable Energy (EERE) online information portal.

< http://apps1.eere.energy.gov/states/maps/renewable_portfolio_states.cfm>

U.S. Energy Information Administration (EIA). Electricity Data (Main Portal). <http://205.254.135.24/electricity/data.cfm>

U.S. Environmental Protection Agency. Renewable Portfolio Standard Factsheet. <http://www.epa.gov/chp/state-policy/renewable_fs.html>

Wiser, Ryan, Galen Barbose, and Edward Holt. Ernest Orlando Lawrence Berkeley National Laboratory. Supporting Solar Power in Renewable Portfolio Standards: Experience from the United States. October 2010.

Wiser, Ryan, Christopher Namovicz, Mark Gielecki, and Robert Smith. Ernest Orlando Lawrence Berkeley National Laboratory. Renewable Portfolio Standards: A Factual Introduction to Experience from the United States. April 2007. <http://eetd.lbl.gov/ea/ems/reports/62569.pdf>

Yin, H., and N. Powers. 2010. Energy Policy 38 (2). Do state renewable portfolio standards promote in-state renewable generation? <http://www.sciencedirect.com/science/article/pii/S0301421509008283>

 


[1] This article is copyrighted and reprinted by permission from the International Association for Energy Economics (IAEE). The material herein first appeared in the online and conference proceedings of the thirtieth USAEE/IAEE North American Conference in Washington, DC during October 2011.

[2] Regional Economic Models, Inc. (REMI) Amherst, Massachusetts - fred@remi.com

[3] U.S. Environmental Protection Agency, Renewable Portfolio Standard Factsheet.

[4] Union of Concerned Scientists, Missouri Renewable Energy Standard Summary.

[5] U.S. Energy Information Administration (EIA), 2009 Electricity Production Data by Source.

[6] Ibid., 2.

[7] Ibid., 2.

[8] Yin, H, and N. Powers, Do state renewable portfolio standards promote in-state renewable generation?

[9] Wiser, Ryan, Galen Barbose, and Edward Holt, Supporting Solar Power in Renewable Portfolio Standards: Experience from the United States.

[10] Ibid., 3.

[11] Wiser, Ryan, Christopher Namovicz, Mark Gielecki, and Robert Smith, Renewable Portfolio Standards: A Factual Introduction to Experience from the United States.

[12] Chen, Cliff, Ryan Wiser, and Mark Bolinger, Weighing the Costs and Benefits of State Renewable Portfolio Standards: A Comparative Analysis of State-Level Policy Impact Projections.

[13] Holtzman, James M., Benefit Cost Analysis for the Application of PV Solar in Missouri.

[14] Union of Concerned Scientists, Missouri Renewable Energy Standard Summary.

[15] The 3.25% APR was the bank prime rate for October 2011.

[16] DOE/EIA-0383 (April 2011), EIA Annual Energy Outlook 2011: with Projections to 2035.

[17] U.S. Energy Information Administration (EIA), 2009 Electricity Production Data by Source.

[18] Missouri Department of Natural Resources, Missouri’s Solar Energy Resource.

[19] American Wind Energy Association, Wind Energy Basics.

[20] Hearps, Patrick and Dylan McDonnell, Melbourne Energy Institute, Renewable Energy Technology Cost Review (annual rate calculated based on average decrease in percentage from 2000 to 2005).

[21] National Energy Solutions estimate of the twenty-five year lifespan of solar panels. For further information, see the European Commission study estimating the twenty-year lifecycle of wind farms.

[22] Princeton Energy Resources International, LLC, Wind Turbine – Materials and Manufacturing Fact Sheet.

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