USING REMI IN FORECASTING SAN FRANCISCO BAY AREA
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1 USING REMI IN FORECASTING AND PROJECTIONS FOR THE SAN FRANCISCO BAY AREA Cynthia Kroll, Chief Economist, Assistant Director Integrated Planning and Research, Association of Bay Area Governments (ABAG) and Metropolitan Transportation Commission (MTC) REMI Webinar: Regional Planning and Economic Modeling August 29, 2017
2 INTRODUCING THE SAN FRANCISCO BAY AREA 9 counties (7.6 M People) 101 cities San Jose (1.0 M) San Francisco (0.9M) Oakland (0.4M) Diverse economy (4.1 M Jobs) Multimedia and social networking High tech manufacturing Health and education Leisure and tourism Agriculture and wineries North Bay West Bay East Bay South Bay
3 CONTEXT ABAG and MTC jointly produce a Sustainable Communities Strategy (SCS) and Regional Transportation Plan as Plan Bay Area Plan for 25 to 30 years in the future The SCS includes specific policy requirements House all of the population Reduce GHG emissions
4 ABAG/MTC FORECASTING PROCESS 3 STAGES REGIONAL TOTALS ABAG Regional Forecasts - Population* - Economy* - Households (*) - Income Distribution (*) - Commute(*), Regional Housing Control Total GEOGRAPHIC DISTRIBUTION ABAG; MTC ABAG: - Subregional Analysis - Local Policy Input MTC: - UrbanSim Calibrations TRAVEL DEMAND, GHG PRODUCTION MTC Travel Model - Travel demand - GHG Estimates Parcel and TAZ projections REMI ROLE * direct output (*) input to other modules
5 WHY REMI FOR THE REGIONAL FORECAST? Integrated structure to examine employment, population, labor force, income and output growth Provided in-house capacity to test sensitivity to different assumptions Model could be used in the future for impact analysis Forecast based on REMI ABAG version for 9 counties aggregated into 4 regions plus region 5, the rest of California.
6 ADJUSTING REMI TO PRODUCE A SFBA FORECAST Adjust national control for construction, transportation and warehousing, information, trade (Adjusted National Control 1.6%>REMI 1.7.8, 1.7%< REMI 2.1) Adjust regional control Residential and nonresidential investment Capped at highest historic level Relative real estate prices Adjusted based on measured actual levels Employment levels Policy adjustment rather than update Translate employment results from BEA jobs to BLS + self-employed equivalent
7 FORECAST RESULTS Source: ABAG analysis using ABAG REMI model version
8 FROM THE REGIONAL FORECAST TO SMALL AREA AND TRAVEL PROJECTIONS REMI output uses, regional level: Household module: # based on headship rates Income distribution module: Linked to REMI income, employment by sector, and age mix In-Commute Estimate: Net increase from outside the region Regional Housing Control Total: Households, in-commuters, vacancy REMI output uses, geographic distribution and transportation Urban Sim: Population, households, jobs by sector, income mix Travel Model 1: Population, jobs, income mix
9 ALL OF THE PLAYERS IN THE FORECAST Households (in-house) Technical Modeling REGIONAL Population Model (Pitkin Myers) Economic Model (REMI) Household Income (in-house) Regional Housing Control Total (in-house) GEOGRAPHIC DISTRIBUTION ABAG Preliminary Ranges (in-house) In-Commute Households (in-house) UrbanSim Analysis (MTC with ABAG) Outside Review, Public Input REMI and Pitkin technical assistance UrbanSim TA CCSCE consultant Legal Process PDA Feasibility Study Technical Advisory Committee Public Meetings, Comments, Conversations Advocat es Developer Advisors Local Agency and Elected Official Review CEQA Requirements, Experts
10 NEXT STEPS Impacts of an earthquake on the Hayward Fault Revised forecast for Plan Bay Area 2021
11 THE ABAG TEAM Cynthia Kroll Bobby Lu Aksel Olsen Johnny Jaramillo Hing Wong (retired) 2040.planbayarea.org/sites/default/files/ /Regional Forecast Supplemental Report_Final_7-2017_0.pdf
12 ADJUSTMENTS TO NATIONAL CONTROL Sectors Update with BLS Growth Rates Apply BLS ROG forecast to 2022 Return to REMI projected ROG Construction 2013, 14, 15 Information Extend BLS ROG Calculated new growth path Tapered over time internet 2013, 14, 15 publishing 2013, 14, 15 telecomm 2014, 2015 motion pics 2013, 14, 15 Retail Wholesale Transport / Warehouse Result: Adjusted national control (NC3) 2040 employment is 1.6% higher than REMI national standard control for 1.7.8, 1.7% lower than REMI 2.1 National Standard Control.
13 Billions of fixed (2009) dollars RESIDENTIAL INVESTMENT ADJUSTMENT RESULTS 100 Figure A-1: Residential Investment (Unconstrained and Capped at Historic Peak) REMI Standard Cap Input Cap Output Source: Plan Bay Area 2040, Regional Forecast of Jobs and Housing, Appendix A
14 Ratio of Bay Area to US Housing Price RELATIVE REAL ESTATE PRICES Figure A-2: REMI and ABAG Estimated Relative Housing Prices 2010 and Projected 2020 and 2040 East Bay North Bay South Bay West Bay 2010 REMI 2010 ABAG Est 2020 REMI NC3-SC 2020 REMI NC3RC REMI NC3-SC 2040 REMI NC3RC1 Source: Plan Bay Area 2040, Regional Forecast of Jobs and Housing, Appendix A
15 FROM BEA TO BLS PLUS SELF-EMPLOYED Why adjust? BEA counts all jobs regardless of month BLS averages across months Closer map to job/person Calculate ratio of BEA employment to BLS Wage and Salary Employment plus Census Self Employed for Base Year (2012) Representative ratios: Government 1.03 Professional and Managerial 1.3 Financial and Leasing 2.4 Arts/recreation/other 1.4
16 VALIDATING THE FORECAST Alternative population forecast (Pitkin-Myers) Employment trend analysis comparisons Technical advisory committee
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Section II: Reports on additional findings requiring further investigation and recommended next steps.
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