©2007 The Centre for Spatial Economics Developing an Occupation Supply Modelling Strategy FLMM Meeting, Vancouver October 18, 2007 Ernie Stokes Managing Director

©2007 The Centre for Spatial Economics Presentation Objectives Introduction Occupation system components Current Canadian approaches (Fairholm) Key factors in choosing an approach A suggested approach (CSC experience)

©2007 The Centre for Spatial Economics Projection System Components DataModels Analysts Clients Projection Process

©2007 The Centre for Spatial Economics Occupation Model Components Demand –total employment/hours requirements of the economy (expansion/contraction demand) Supply –outflows associated with deaths, retirements, and other factors such as migration (replacement demand) –inflows including new entrants into the labour force such as school leavers, entrants from other occupations, and migration –changes in hours worked on the supply side Education linkage Demand-Supply interaction

©2007 The Centre for Spatial Economics COPS Approach Strengths –Detailed labour market projections at National level –Includes several aspects of education –Includes some Provincial aspects –Most detailed inclusion of immigration in the World Weaknesses –D/S imbalances have no impact on demand or supply –Incomplete replacement demand –Incomplete supply side –Provincial aspects incomplete

©2007 The Centre for Spatial Economics Provinces Approaches Provinces Monitor Labour Force Developments –Many Provinces monitor labour markets using simple statistics and charts –Some have developed labour market indicators –Most meet with representatives from other government departments, industry and associations Larger Provinces Tend to Have Models –Ontario models/forecasts labour force withdrawals –Quebec has a detailed and sophisticated model/forecast –Alberta has a detailed bottom up model/forecast

©2007 The Centre for Spatial Economics Provinces Approaches - More Smaller Provinces Do Not Have Models –Lack of models and general quantitative techniques –Rely more on external providers –Conference Board and COPS –Rely more on qualitative techniques –Ad hoc analysis

©2007 The Centre for Spatial Economics Key Choice Factors Purpose Usefulness –Accuracy –Consistency –Transparency –Education Data Resources

©2007 The Centre for Spatial Economics Purpose Forecasting and scenario analysis Governments Policies and planning –Labour market programs and education –Time horizon: medium to long term –Require great detail Private sector Human resource planning –Time horizon: short to medium term

©2007 The Centre for Spatial Economics Usefulness The purpose of forecasting and scenario analysis is to reduce uncertainty about the future A projection or forecasting system is said to be “useful” if it reduces the level of uncertainty about the future to below that which existed before the system is used This definition, of course, should be thought of in terms of the condition that the marginal benefits associated with reducing the uncertainty is greater than or equal to the costs of developing and using the system

©2007 The Centre for Spatial Economics Accuracy Accuracy refers to the proximity of the projection to the actual results (a more accurate forecast is generally a more useful one) The ability of a projection technique to achieve a high degree of predictive accuracy depends on such factors as the –time horizon of the projection (long term more difficult than short term) –cyclical volatility of the economic indicators to be projected (food expenditures or housing starts) In scenario analysis accuracy is important in the sense that the model should predict well if the assumptions are correct

©2007 The Centre for Spatial Economics Consistency Is the approach “consistent” with the theory behind the phenomenon in question? A model is a description of the process (data generating mechanism) that generates the actual labour market outcomes The approach must use a model that produces results consistent with the views in this regard held by the clients (otherwise it will not be useful) Since there are always differences in individual views, Occam’s Razor can be employed (limited consensus)

©2007 The Centre for Spatial Economics Transparency The transparency of the projection and its methodology is important if one expects to get the consumers of the projections to buy into it (otherwise it will not be useful) To be transparent the projections and methodology have to be documented and presented in such a manner that projection users have a good understanding of how the methodology works and what assumptions have been employed to produce the projection In this case, analysts could, if desired, duplicate the results obtained by other analysts

©2007 The Centre for Spatial Economics Education Decision making characterized by uncertainty requires a good understanding of the issues surrounding the decision. Numbers are not enough! What are the key drivers behind future labour market developments? What are the major risks associated with the future performance of labour markets? A system that delivers this information is useful, particularly in cases where forecasting is difficult (when isn’t it?)

©2007 The Centre for Spatial Economics Data The type and amount of data that are available for the development of a system have a very important impact on its development and use If there are few data for the desired model inputs and outputs, then it is not possible or very difficult to develop a detailed system If the analysts are required to create estimates of the data, then additional resources will be required to develop and use the system on an on-going basis Most of us working in LMI are working with very limited data

©2007 The Centre for Spatial Economics Resources The real, financial, and time resources available to the forecasting organization are important factors when choosing a projection approach More complicated and detailed approaches require greater resources to develop, maintain, and use Organizations can use internal and/or external resources, as evidenced by current labour market forecasting organizations

©2007 The Centre for Spatial Economics A Suggested Development Process Set up an LMI team –Clients and analysts –Need to involve an LMI expert (someone with experience in developing LMI systems) Identify needs and priorities – What is needed in general and what should be given the highest priority for development? Survey LMI approaches Assess existing resources and resource needs –Can the system be developed with existing staff? –Is there sufficient funds to hire additional staff or external help? Set up a plan for “on-going” system development

©2007 The Centre for Spatial Economics A Modest Beginning Develop a relatively simple, not too detailed, but still theoretically acceptable model (Occam’s Razor) to start Must demonstrate the usefulness of the system to clients as soon as possible Supply models require a lot of detail (age/sex groups for the components), start with fewer occupations (140 occupations rather than 520) Can use a top down approach, estimate total labour force change and some components leaving a residual component

©2007 The Centre for Spatial Economics CSC Experience The CSC started modelling employment and labour force for about 30 occupations/trades The components of labour force change were not explicitly modelled (reduced-form model) and there was no age-sex detail This approach was sufficient to meet the initial needs of clients and to get them involved in the process It also led to capacity building for the analysts and the clients

©2007 The Centre for Spatial Economics CSC Labour Force Model Possible Labour Force = Trade Requirements/Total Occupation Requirements * Total Labour Force Labour Force Change = Adjustment Coefficient *(Possible Labour Force – Labour Force Previous Year) Adjustment coefficient reflects time required for new entry, exits, and mobility (geographic and inter-occupational)

©2007 The Centre for Spatial Economics Build Capacity Over Time Once clients become familiar with the process they demand more information from the system Clients will identify what is needed and additions to the system can be added to meet their needs After the first year, CSC clients identified additional trades that should be included in the system and also expressed the need to examine replacement demand The CSC responded by adding new trades and developing a model that could explain the retirements and deaths parts of replacement demand

©2007 The Centre for Spatial Economics Retirements and Deaths Deaths (age,sex) = Labour Force (age,sex)* Death Rate (age,sex) Retirements (age,sex) = Labour Force(age,sex)*Retirement Rate(age,sex)

©2007 The Centre for Spatial Economics Developing an Occupation Supply Modelling Strategy QUESTIONS Ernie Stokes Managing Director