Louisiana Employment Projections and Star Jobs Overview

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Louisiana Workforce Commission provides long-term and short-term employment projections through a two-step process by industry and occupation. The methodology involves analyzing economic trends, incorporating feedback from driver firms, and considering economic development initiatives. Statistical modeling examples post-Katrina illustrate forecasting challenges, emphasizing the importance of local knowledge in certain sectors. Key points highlight the role of good statistical models, the mix of science and judgment in forecasts, and the significance of driver firms in Louisiana's business landscape.

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Louisiana Long-term and Short-term Employment Projections and Star Jobs Overview Ava Dejoie Louisiana Workforce Commission

Process Overview: Occupational Forecast & Star-Rating System Occupational projections Updated annually upon receipt of new employment data Two-step process: Projections by Industry Projections by Occupation Star-Rating system Updated annually based on new demand projections, wage data, and openings data Ratings by Occupation

Methodology: Industry Projections 94 distinct industries in each RLMA (statewide + 8 regions 846 total) - 2 forecasts per industry-region: short-term (2017) & long-term (2024) Produce baseline statistical model projections, using historical data and Projections Suite software Review and refine baseline projections: - Analyze prevailing economic trends: develop & evaluate several alternative candidate models - Contact Louisiana driver firms and incorporate their comments (additional input from industry associations and regional economic development organizations) - Incorporate economic development initiatives and major announcements including expansions and layoffs

Example of Simple Statistical Modeling Post-Katrina 200,000 180,000 160,000 140,000 120,000 100,000 80,000 1990 1995 2000 2005 2010 2015 LA_FOOD LA_FOODF LA_FOODFS

Example Where Statistical Models Struggle 4,800 4,400 4,000 3,600 3,200 2,800 2,400 1990 1995 2000 2005 2010 2015 SHR_AUTO SHR_AUTOF

Key Points Good statistical models should always be the starting point Forecasts are always a mix of science and judgment Louisiana has numerous exogenous shocks that are large relative to industry size, which make life harder In some sectors, local knowledge trumps statistical models

How Important are Driver Firms? 2% of LA businesses have 100 or more employees Employ over 44% of LA workers Contribute $4.67 billion in direct wages Create total Louisiana Sales of $61.89 billion Large firms are more likely to generate funds from outside LA that support the local economy Don t ignore small firms!

Converting: Industry to Occupation Staffing Patterns Mix of occupations in each industry Based on recent historical data specific to LA regions Change Factors How proportion of occupation relative to entire industry changes over time Replacement Rates Attrition rate, due to retirement or permanently leaving job for any reason

Augmenting Data Sources: Change Factors Change Factors HWC Reports Increase for Primary Care and Mid-level providers Increasing role of IT in healthcare LA State Board of Nursing Registered Nurse license and survey data LED announcements and firm engagement Planned expansions/ relocations that will impact staffing ratios of relevant industries in upcoming years Continued theme of increasing importance of IT professionals Driver Firm interviews

Augmenting Data Sources: Replacement Rates Replacement Rates WARN (Worker Adjustment and Retraining Notification) and Pre-WARN Notices Healthcare Occupations: Health Works Survey, 2012 & 2013 LA State Board of Nursing license data Specialty Trade Contractors/ Heavy & Civil Engineering Construction: Alliance Safety Council annual training data SW LA Construction Users Council (SLCUC) data on age profile of existing craft workforce Other Occupations Driver firm interviews

Augmenting Data Sources: Regional Stakeholder Inputs The following organizations contributed by providing driver firm contacts, data, or reviewing forecasts and providing feedback ABC AFL-CIO GBRIA LABI LCA LED LHA LMOGA BRAC CLEDA GNO Inc LEDA NELEA NLEP One Acadiana SWLA EDA WDB 40 WDB 41 WDB 61 LABSWE LSBN LSBME LSBOE LSBPNE

Occupational Forecast Summary Short-Term Occupation through 2017 Average Annual Job Growth 17,686 Average Annual Replacement Demand: 51,218 Total Annual Demand: 68,904 Long-Term Occupation through 2024 Average Annual Total Job Growth 15,934 Average Annual Replacement Demand: 50,836 Total Annual Demand: 66,770

Rating Occupations: Stars LWC website provides info on available jobs: Wages Educational requirements Star Rating Star Rating: decision aid for job-seekers, employers, and policy planners Rates a job by how well it pays, and the occupation s outlook Intended to reflect opportunity offered by an occupation, rather than measure subjective job quality

Star Rating System: Structure Star Rating components for each occupation: Short-term outlook Long-term outlook Current Openings Wages Rank each component, based on decile Convert the average of component rankings to Stars

Star Rating System: Vetting Process Developed in partnership with LSU s Economic Research Policy Group. Reviewed by Occupational Forecasting Council Approved by Workforce Investment Council

4-5 Star Jobs Span Across Educational Spectrum Associate s Degree Star RatingOccupational Title Registered Nurses Diagnostic Medical Sonographers Electrical and Electronics Engineering Technicians Occupational Therapy Assistants Average Annual Wage $62,455 $59,479 $55,985 Annual Total Demand 1,910 40 50 20 $54,050 Bachelor s Degree Star Rating Occupational Title Mechanical Engineers Computer Systems Analysts Software Developers, Applications Chemical Engineers Average Annual Wage Annual Total Demand $98,308 $72,539 $78,102 $113,844 120 90 90 90 Postsecondary Non-degree Star Rating Occupational Title Electricians Industrial Machinery Mechanics Riggers Average Annual Wage $48,709 $51,962 $38,276 Annual Total Demand 530 420 200