Contents Contents... 1 Introduction... 2 Why LMI?... 2 Why POMS?... 2 Data Reliability... 3 Document Content... 3 Key Occupation Labour Market Concepts... 4 Basic Labour Market Concepts... 4 Occupation Analysis Concepts... 8 Normal Unemployment... 8 Labour Force Demand and Expansion Demand... 8 Expansion Supply... 10 Total Demand and Supply Changes... 12 Labour Market Tightness Ranks... 12 POMS Occupation Labour Market Indicators... 13 Occupation Data... 15 Occupation Labour Market Analysis... 16 Gap Analysis... 16 Source Analysis... 18 Demand Flows... 18 Supply Sources... 19 Occupation Demand and Supply Models... 23 Employment... 23 Labour Force Demand and Supply... 23 Labour Force Change... 26 Appendix: NOC Occupations... 29 1 September 2014
Introduction This document describes the Canadian provincial occupational modelling system (POMS). POMS is able to conduct occupation demand and supply projections for each province and roll them up to produce projections for Canada as a whole. The occupation outlooks are consistent with the C 4 SE provincial economic outlooks. POMS can also be accessed by C 4 SE clients to produce projections using their own assumptions about the determinants drivers of occupation demand and supply. It should be noted that the description of POMS presented below also serves as a description of the regional occupation modelling systems used by C 4 SE and its clients Why LMI? The purpose of providing occupation labour market information (LMI) such as that produced by POMS is to assist organizations in ensuring that they are able to obtain sufficient numbers of employees with the right skills, at the right time, and in the right geographic location. With such information organizations can devise strategies to help them achieve their labour market goals. There are two types of analyses associated with attempting to achieve these goals. The first type focuses on examining the expected gap between the demand and supply of the occupations in question. Will the markets for the occupations be tight or loose in the sense of the degree of difficulty in obtaining the required employees? Will there be a shortage or a surplus of the occupations of interest? How large might these shortages or surpluses be? Does the size of the gap suggest that we need to look closely at possible sources of supply? Information regarding this type of analysis is called Gap Analysis. The second type of analysis looks at what is causing the changes in demand for and supply of employees. Will the demand for employees by an organization originate from the need for more employees to meet increased demand for their products or will it come from the need to replace employees that are retiring? What will be the sources of supply to meet the demand? Will the employees come from school leavers, employees from other geographic locations, other industries, or from other occupations? Information regarding this type of analysis is called Source Analysis. Why POMS? The impetus for developing POMS originates from work undertaken by the C 4 SE to assist clients conducting occupational analyses. There are serious challenges in attempting to undertake such analyses. The most important challenge has been and continues to be obtaining reliable historical data on occupation demand and supply. The largest challenge is obtaining data on occupation supply. While there is information on occupation employment and labour force published in the Census of Canada, National Household Survey and in the Labour Force Survey (LFS) it is very difficult if not impossible to find information to enable the modelling of the components of the change in occupation supply such as retirements from the labour force and the number of people leaving school to enter the labour force. There has been some modelling and forecasting undertaken by a number of organizations across the country. Nevertheless, this modelling and forecasting has a number of shortcomings when it comes to conducting comprehensive country wide occupation analyses. Many organizations focus on specific groups of occupations in specific industries using different assumptions about the occupation drivers. Others such as provincial governments that produce occupation outlooks normally focus on just one province. These outlooks are in almost all cases based on different assumptions about the occupation drivers and at conducted at different points in time. It is very difficult for an occupation analyst to put together this diverse set of information to conduct a comprehensive and consistent analysis for the occupations of interest. The goal in the development of POMS has been to provide occupation analysts with information that will allow them to conduct occupation analyses across the provinces at the highest level of occupation detail using consistent assumptions regarding the occupation drivers. Consistent in this context means that the information is produced at the same time using the same concepts and underlying assumptions about the occupation drivers. The assumptions about the drivers as mentioned above are obtained from the latest C 4 SE provincial economic forecast. The occupation information provided includes that needed to conduct gap and source analyses. In POMS the approach in modelling the demand and supply side differs from that used in almost all other models. The main difference is regarding how the modelers treat workforce supply. In POMS, workforce supply and demand are interdependent supply responds to changes in demand and changes in supply can impact demand. Almost all of the other approaches assume that workforce supply is an input to their workforce outlooks. That is, they assume that the demand and supply for the workforce are independent of each other. This approach allows them to show large persistent imbalances between supply and demand that are inconsistent with the way the world works. In the real world such large imbalances would cause wages and prices and other economic variables such interest rates, participation rates, and the exchange rate to adjust to reduce these imbalances. September 2014 2
The occupation projections made using POMS reflect a requirements approach for both demand and supply. This approach starts with the C 4 SE macroeconomic models where workforce demand and supply adjust over time to balance aggregate labour markets. An important part of this adjustment is an optimal immigration approach where the federal government is the residual source of workforce supply. Under this approach there are no persistent large imbalances at the aggregate level of the economy across the country. Nevertheless, there may be temporary shortages or surpluses for some occupations over the economic cycle that will need to be taken into account in workforce planning. In the POMS outlooks there is an outlook for demand requirements and the required supply to meet these demand requirements. The demand requirements are changes in employment, people retiring from the workforce, and people dying. The sources of supply to meet these requirements are young people entering the workforce after finishing school, both international and interprovincial net in-migrants, and other sources such as people changing occupations and deciding to enter the labour force because of more job opportunities and higher wages. While there are no major persistent labour market imbalances in the POMS outlooks, POMS does employ a labour market tightness ranking approach that takes into account the fact that the supply requirements computed may not be achieved. It attempts to identify occupations that may be difficult for organizations to find in the future. Occupations with relatively strong demand growth, for example, may be more difficult to find than those where demand growth is weaker. Moreover, occupations where supply requirements are largely met through migration may be at risk if the federal government does not accommodate these requirements through additional immigration, or, Canadian workers do not wish or are not available to move to the particular location in question. There may also be some tightness issues over economic cycles and for specific occupations. This tightness is incorporated in the ranking approach. Data Reliability It should be noted that the reliability of the information produced by POMS declines with the size of the occupation labour force in the provinces. The projections for occupations with few members say less than 100 should be treated with caution. There are not very many of the 500 occupations with less than 100 in the larger provinces, but a number of them are found in the smaller provinces. While the numbers produced for employment and labour force for these occupations may be useful in suggesting trends, there is certainly a danger in conducting analysis of precise supply-demand gaps for them. Document Content The next section of this document describes the labour market concepts used in POMS. This description includes that for labour market indicators published by Statistics Canada as well as that used in POMS and for occupation analysis. The third section contains an example of how the information produced by POMS can be used to conduct an occupation analysis. The final section is a more technical one that describes the approach used in POMS to provide this information. The Appendix contains a list of the industries and 2011 National Occupation Categories (NOCs) covered in POMS. 3 September 2014
Key Occupation Labour Market Concepts Before describing the approach used to produce information for occupation labour markets it is important to present the key concepts that are part of this approach. Without an understanding of these concepts it will be difficult to use and interpret the information produced by POMS. The types of concepts employed are examples of stock and flow variables. In examining possible shortages (gaps) of occupations the concern is with stock (level) variables such as the labour force. To identify sources of changes in the demand and supply of occupations the approach focuses on flow (change in stocks) variables such as retirements and migration. Stocks refer to variables measured at a point in time. An example of a stock variable is the size of the population on July 1, 2012. Flows refer to changes in variables measured between two points in time. The number of persons moving into Canada on a permanent basis from July 1, 2011 to June 30, 2012, which is called immigration, is an example of a flow variable. It is one of the flow variables along with births and deaths that measure the change in the size (stock) of the population between two points in time. Basic Labour Market Concepts The labour market information in the modelling system is derived from that provided by Statistics Canada in their Labour Force Survey and Census of Canada. Each month Statistics Canada publishes information about the labour force, employment, unemployment, the unemployment rate, source population, and the labour force participation rate for various jurisdictions across the country. The definitions of these labour market variables are as follows: Employment (stock): number of people who are working at a particular point in time. This number includes both full and part time employees; Labour force (stock): number of people working (employment) plus the number of people actively looking for work at a particular point in time; Unemployment (stock): persons who are actively looking for work but are unable to find it at a particular point in time calculated as labour force minus employment; Unemployment Rate: percentage of the labour force that is unemployed at a particular point in time calculated as unemployment divided by labour force multiplied by 100; Source Population (stock): number of persons in the population aged 15 years and over that is able to work. The source population excludes persons in institutions such as prisons and hospitals or those that are ill or disabled and unable to work; and Labour Force Participation Rate: the percentage of the source population that is in the labour force labour force divided by source population multiplied by 100. It is important to emphasize the part of the definition of the labour force that refers to actively looking for work. People who are not employed and who are not actively looking for work are not considered to be part of the labour force. Such persons are not available to organizations looking for workers and, therefore, are not counted as part of labour supply. The labour force is the measure of labour supply that is used in the occupational modelling system. For the economy as a whole it is defined algebraically as the product of the participation rate and the source population: Labour Force equals Labour Force Participation Rate divided by 100 multiplied by the Source Population As a result, the supply of labour as measured by the labour force changes in response to changes in the labour force participation rate and the source population. Changes in the source population are caused by the same factors as those that cause changes in the overall population. The change in the population in a province, for example, is equal to births minus deaths plus net in-migration to the province. In a particular year births do not influence the source population since the latter variable is comprised of population 15 years of age and over. Nevertheless, births will impact the source population 15 years from the particular year in question. There is a number of determinants of the labour force participation rate for the economy as a whole. The most important one is the need for individuals to obtain income to finance their purchases of goods and services. This need differs across the age groups in the population. September 2014 4
Young people participate relatively less in the labour force because they attend school to obtain the knowledge and skills required when they become more permanently (strongly) attached to the workforce. To finance their purchases they may borrow funds from financial institutions or their parents or find part-time work. Older people also participate relatively less starting after about 50 years of age as they decide to retire from the labour force. They finance their purchases through pensions or savings made through working at earlier ages. Some of them continue to work, but relatively more on a part-time basis. Changes in labour compensation and sources of income also influence the decision to enter or leave the labour force. Higher after-tax wages will tend to have the impact of increasing the labour force participation rate. Increased non-labour income such as from investments or government transfer payments will reduce the participation rate as there is less need to work to earn income. The labour force participation rate is also impacted by social and cultural factors. The decision by women to increase their participation in the labour force, for example, has been and continues to be a very important determinant of increases in the labour force. Examples of the evolution of employment, labour force and the unemployment rate for Canada as a whole are shown in Figure 1. Employment and labour force are measured on the left axis in thousands of persons and the unemployment rate is measured on the right axis in percentage terms. The unemployment rate represents the percentage gap between the labour force (top line) and employment (the line shown under the labour force). As can be seen from Figure 1, the unemployment rate, apart from exhibiting a downward trend, has tended to cycle up and down over the period. This cycling reflects changes in the level and growth of economic activity. The unemployment rate, for example, rose from 1989 to 1993 during a recession; it fell in the recovery from the recession; it rose again around 2000 with another economic slowdown; it declined in the following recovery; and then increased in the 2009 recession. Figure 1 Employment (000s), Labour Force (000s) and Unemployment Rate (%), Canada 1981-2010 20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 14 12 10 8 6 4 2 0 Employment (LHS) Labour Force (LHS) Unemployment Rate (RHS) Source: Statistics Canada, Labour Force Survey The rise and fall of the unemployment rate represents a tightening and loosening of the labour market as demand measured by employment increases relative to supply as measured by the labour force. The downward trend in the unemployment rate suggests an upward trend in the tightness of the labour market. The latter trend has been suggested to be partly a result of the aging of the workforce. 5 September 2014
Figure 2 shows the labour force participation rate left axis and the unemployment rate right axis. The labour force participation rate, like the unemployment rate, has cycled over the period 1981 to 2010 and for related reasons. The cycles nevertheless are inversely related. This relation is a result of what is called the Discouraged (Encouraged) Worker Effect. The latter effect states that as the economy goes into a recession or a noticeable growth slowdown and the unemployment rate rises, the percentage of the source population looking for work falls, as people find it difficult to find work and drop out of the labour force quit looking for work. Conversely, when the economy is picking up and entering a boom period the percentage of the source population looking for work rises as it is easier to find work and wages are increasing. The slight upward trend in the participation rate over the period would appear to reflect in part the tightening of the labour market. Figure 2 Labour Force Participation Rate and Unemployment Rate (%), Canada 1981-2010 68 67 66 65 64 63 62 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 14 12 10 8 6 4 2 0 Participation Rate (LHS) Unemployment Rate (RHS) Source: Statistics Canada, Labour Force Survey As mentioned above, an aspect of the labour force participation rate that is important for occupation labour market analysis is its age and sex distribution. Figure 3 shows estimates of the participation rates by age and sex for Canada for 2010 for ages 15 to 70 and over. As can be seen from the figure, the rates for males are higher than those for females and the rates for both males and females differ across age groups. For ages 15 to 30 the rates rise with age as more and more people enter the labour force on a more permanent basis after leaving school. From 30 years of age to the late 40s the rates are relatively constant. After 50 the rates decline at an increasing rate with age as workers retire from the labour force. Figure 4 shows the aggregate all ages participation rates for males and females over the 1981 to 2010 period. As can be seen from the figure, the participation rate for women has risen substantially since 1981 more than offsetting the decline in that observed for males. September 2014 6
Figure 3 Labour Force Participation Rates by Age and Sex, Canada, 2010 100 90 80 70 60 50 40 30 20 10 0 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 Females Males Source: Statistics Canada and C 4 SE Figure 4 Labour Force Participation Rate, Males and Females, Canada 1981-2010 90 80 70 60 50 40 30 20 10 0 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 Females Males Source: Statistics Canada, Labour Force Survey 7 September 2014
Occupation Analysis Concepts The concepts described above are those that are published by Statistics Canada and used in the media and by the public in regular conversations about the state of the labour market. In analyzing occupation labour markets additional concepts are required. These concepts define what is meant by the demand for and supply of occupations as well as the sources of changes in occupation demand and supply. The occupation modelling system on the demand side focuses on the workforce required by private and public organizations in the economy. Workforce here refers to the number of persons required, not the number of hours required from these persons. On the supply side, the available workforce, as measured by the labour force, is what is of interest for the modelling system. While it would be desirable to use hours to measure supply and demand such data are not available. The key concepts for an occupation are as follows: Labour Force Demand (stock): employment plus the normal level of unemployment for an occupation; Normal Unemployment (stock): unemployment normally observed for an occupation because of the nature of the work and the industries in which it is primarily employed; Labour Force Supply (stock): the labour force as described above; Excess Labour Force Supply (stock): labour force supply minus labour force demand; Normal Unemployment rate: the percentage of supply that is normally unemployed; Expansion Demand (flow): the change in occupation demand (stock) as defined above; Expansion Supply (flow): the change in occupation labour force (stock) as defined above; Total Demand Change, Job Openings, or Job Requirements (flow) is the sum of expansion demand (flow), retirements (flow), and deaths (flow); Total Supply Change (flow) is the sum of new entrants (flow) and other sources of supply (flow); and Labour Market Tightness Rank is a number that reflects the degree of tightness (difficulty of finding workers) in the labour market. The first four concepts are stocks and what are of interest when asking whether or not there is sufficient supply to meet demand for an occupation. The next four variables are flows and are of interest in describing the sources of change in the demand for and supply of an occupation. Normal Unemployment While it would be desirable for there to be no unemployment in the economy such a situation is not possible. Given the nature of the labour market it is necessary that there be some unemployment to facilitate its proper functioning. The latter unemployment is what is defined as normal unemployment. There are a number of different types of unemployment: Seasonal unemployment: many activities in the economy such as construction have a seasonal component where fewer or more workers are required at different times during the year. For these occupations a higher level of the labour force in relation to employment is required to meet peak demand for workers; Frictional unemployment: there is always a number of people between jobs either as they search to improve their careers or move to a different geographic location; Structural unemployment: as the economy changes over time there will always be some mismatch between the skills required and those possessed by workers in the local economy; and Cyclical unemployment: is the unemployment that is associated with recessions and recoveries as the economy goes through economic cycles. Normal unemployment refers to the first three types of unemployment. Normal unemployment rates differ across occupations reflecting differences in the seasonal and other aspects of a job. Managers, for example, have relatively low rates while those for construction related trades are relatively high as the work is seasonal and more labour force is required to meet peak levels of economic activity. Labour Force Demand and Expansion Demand Figure 5 shows an example of labour force demand for an occupation. It is comprised of employment and normal unemployment. The latter component represents about 4 percent of labour force demand for this occupation. September 2014 8
Figure 5 Labour Force Demand 3500 3000 2500 2000 1500 1000 500 0 2008 2010 2012 2014 2016 2018 2020 Employment Normal Unemployment Source: C 4 SE Expansion demand refers to changes in labour force (labour force demand) requirements for the occupations. The sources of change in expansion demand are the change in employment and the change in normal unemployment. The change in normal unemployment is directly related to changes in employment through the normal unemployment rate. If the normal unemployment rate is 5 percent, for every 100 new employees required for an occupation, an additional 5 would be needed for the labour force to keep the unemployment rate at 5 percent. The 100 new jobs add 100 new persons to employment and 105 persons to the labour force. Figure 6 shows the components of expansion demand for the occupation used in Figure 5. As can be seen from the figure, expansion demand can be both positive and negative as it represents the change in labour force demand shown above. The change in normal unemployment is always in the same direction as employment as described above. 100 50 0-50 -100-150 Figure 6 Expansion Demand -200 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Employment Change Normal Unemployment Change Source: C 4 SE 9 September 2014
Expansion Supply Expansion supply is the change in an occupation s labour force. This change is comprised of the following parts: Additions to Supply: New Entrants In-Migration Other In-Mobility Reductions in Supply: Deaths Retirements Out-Migration Other Out-Mobility In modelling the occupations, migration and mobility are expressed in net terms: net in-migration equals in-migration minus outmigration and net other in-mobility equals other in-mobility minus other out-mobility. Availability of data is an important reason for using this net approach. New Entrants The number of new entrants to the labour force refers to persons entering the labour force from the population in the 15 to 30 age group as described above. They represent additions to the labour force. Migrants or occupations such as managers or supervisors that require related labour market experience are not included in this category. This concept is meant to refer to persons that enter the labour force either for the first time after completing their education, or, if previously working part time while receiving their education, as they complete their education and start to work in their chosen occupation. While related to the concept of school leavers that is often used in occupation analysis, it is not the same concept. It also does not include people completing their apprenticeship, as these people normally apprentice after entering the labour force. An example of how new entrants differ from school leavers is a student who joins the labour force for 3 months in the summer while obtaining his or her education but does not work during the school year. This student would be counted as 0.25 persons 3 divided by 12 months in the labour force for the year as a whole. When they begin to work 12 months a year after completing their education they are counted as 1 person in the labour force their annual participation rate in the labour force jumps from 25 percent to 100 percent. New entrants would capture this latter labour force increase of.75, not 1 implied by school leavers. The increase in the participate rate from ages 15 to 30 shown in Figure 3 above reflects this type of activity. Retirements Retirements subtract from the labour force for an occupation. In occupation analysis, the concept of retirement is meant to refer to those persons who leave the economy s labour force they no longer work. Often the concept of retirement is not interpreted in this manner by the public. Some people retire from their job and then take up work in another job either in the same occupation or another occupation. In this case the person has not left the economy s labour force. If they work in another occupation then they represent inter-occupation mobility movement between occupations such as a person in the construction trades who retires from construction and works in a restaurant as a waiter on a part time basis. One of the problems encountered in occupation analysis is that information on retirements for occupations is normally not provided on the basis required. For example, it has recently been stated in a story in the paper that the average age at retirement for teachers in Ontario is 59. Does this mean that teachers no longer work in the labour force or that they are officially retired from teaching some teachers qualifying for retirement may retire and then take supply teacher positions or a job in a different occupation? To the extent that the reported retirement ages refer to the latter situation, retirements from the overall labour force will be overestimated. This does not affect the size of the overall labour force because in POMS the sum of the individual occupation labour forces is required to add to that for the economy as a whole the latter is an input to POMS. As a result, the overestimation or underestimation if the retirement rates are too high of retirements is allocated to net in-mobility largely inter-occupation mobility which is described below. The economy s total labour force is computed using labour force participation rates by age and sex. These rates implicitly show the percentage of people retiring from the labour force. As mentioned above in the discussion on participation rates, participation rates by age fall starting in the late 40s reflecting retirements from the labour force. As more and more people move into older age groups the number of retirements increase. September 2014 10
Deaths Deaths refer to those occurring from all causes, not just on-the-job deaths. Deaths subtract from the labour force. Net In-Mobility Net in-mobility is defined as the sum of net in-migration and other net in-mobility. This component of labour force change measures the change in the existing labour force that is required because withdrawals from the labour force deaths and retirements are not equal to new entrants to the occupation s labour force. Net In-Migration Net in-migration refers to persons moving into or out of a geographic area to take or find a job. Positive net in-migration adds to the labour force while negative net in-migration subtracts from the labour force. Other Net In-Mobility Other net in-mobility refers to net additions to an occupation s labour force from such sources as persons changing occupations inter-occupation mobility and changes in labour force participation rates for social or cyclical reasons as described above. Figure 6 illustrates the components of expansion supply for the example occupation. The bars represent the components while the line represents the value of expansion supply change in labour force. The new entrant component is always positive on or above the zero line. The retirements and death component is always negative on or below the zero line. Net in-mobility can be either positive or negative. As mentioned above net in-mobility is the amount required to offset the difference between new entrants and retirements and deaths to explain expansion supply. In Figure 6, new entrants trend downward slightly over the period. Retirements and deaths trend upwards. The latter trend reflects the aging of the population. The former trend reflects relatively low birth rates and, as a result, fewer young people entering the labour force. The large change in the labour force in 2008 and generally after 2011 requires positive net in-mobility to the labour force as the number of new entrants less deaths and retirements is insufficient to account for the labour force supply change. Both migration and other net in-mobility contribute to the amount of net in-mobility. Figure 6 Components of Expansion Supply (Labour Force Change) 150 100 50 0-50 -100-150 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Deaths & Retirements Net In-Mobility New Entrants Labour Force Change Source: C 4 SE 11 September 2014
The negative values of expansion supply in 2009 and 2010 decline in the labour force supply are a result of reductions in labour force demand. A major component of this decline is net in-mobility that results from a reduction in participation rates as described for the Discouraged Worker Hypothesis above. The positive value of net in-mobility from 2011 to 2013 is also partly a result of this effect in reverse. Increased in-migration also makes a positive contribution to net in-mobility during this period. Total Demand and Supply Changes Over the long run it is generally expected that labour force demand will be equated to labour force supply. In this case the change in demand will also be equal to the change in supply: Substituting the components of expansion supply: Rearranging the equation yields: Expansion Demand equals Expansion Supply Expansion Demand equals New Entrant minus Retirements and Deaths plus Net In-Mobility Expansion Demand plus Retirements and Deaths equals New Entrants plus Net In-Mobility The components on the left hand side of this equation represent total demand change while those on the left hand side represent total supply change in POMS. Expansion demand represents net new jobs, while retirements and deaths represent replacement demand. It should be noted that all retirements and deaths for an occupation need not be replaced if expansion demand is negative. For example, suppose expansion demand is -1000 and retirements and deaths are 2000. The total demand change is 1000. In this case only 1000 persons of the 2000 who died or retired need to be replaced. New entrants always add to the labour supply while net in-mobility can add or subtract from labour supply. The components of net in-mobility are really found on both sides of the equation as mentioned above. If net in-mobility is negative it is part of replacement demand, when it is positive it is part of supply. If people leave an occupation they may need to be replaced when the total demand change remains the same. Net in-mobility is usually negative in response to similar changes in expansion demand and vice versa. Labour Market Tightness Ranks The tightness ranks included with the POMS information are qualitative measures of the possible tightness of the labour market. There are three ranks measured from 1 to 3. A 1 represents a loose market characterized by excess supply, a 2 represents a normal market a type of market situation that does not show extremes regarding the difficulty or ease of finding workers and a 3 represents a tight labour market characterized by excess demand. Four ranking measures are adopted with POMS. The first measure, the gap rank, is created using actual and normal unemployment rates for an occupation. If the actual unemployment rate is in excess of 20 percent above the normal rate the tightness ranks is 3 (tight). If it is less than 20 percent below the normal unemployment rate the rank is 1 (loose). Otherwise the rank is 2 (normal). Analysts can compute their own measure of tightness by specifying the bands around the normal unemployment rate. The requirements approach adopted in POMS would not be expected to show large or widespread labour market imbalances as supply responds to demand. The gap rank on average over time will always be 2 showing a relatively balanced market. From the point of view of assessing the risk for organizations attempting to meet their labour requirements the gap rank provides little information in the context of POMS unless the gap for an occupation is relatively large. To better assess the risk two additional rank measures are employed. These measures assess the relative labour market tightness of the occupations. September 2014 12
The second ranking measure demand rank assesses the state of the relative demand for occupations. This measure is calculated using the growth in job openings or requirements for an occupation as a percentage of its labour force as shown in Table 1 below. The higher is this value the more difficult it will be to obtain these occupations given the available supply. The rank for this measure is computed as follows: Estimate the mean and standard deviation of the growth value over all occupations; For each occupation find where its job-openings as a percentage of labour force value falls in the overall distribution of the values; If the value for an occupation is within 1 standard deviation of the mean the rank is set at 2; If the value for an occupation is greater than 1 standard deviation above the mean its rank is 3; and If the value for an occupation is greater than 1 standard deviation below the mean its rank is 1; The third ranking measure supply rank focuses on the migration component of supply as a source of risk for finding the required workforce. This measure is calculated using the percentage of an occupation s labour force that needs to be sourced through migration. The higher is this percentage the more difficult it will be to find the workforce. The rank for this measure is calculated in the same manner as that for the second measure. A fourth ranking measure is computed that is a weighted average of the previous three measures. The default weights for the three ranks are 40 percent for each of the demand and supply ranks and 20 percent for the gap rank. Users of the outlook can set their own weights for these measures to compute the fourth ranking measures. POMS Occupation Labour Market Indicators Figure 7 illustrates the type of occupation indicators produced by POMS. Many of these indicators have been described above. Along with some of the indicators presented is the percentage change or level change in them from year to year. For the labour force change components a negative sign is placed in front of deaths and retirements as they represent reductions from the labour force. The death rate is presented as the number of deaths per 1000 persons in the labour force. For the other flow variables such as retirements and new entrants the percentage of the labour force (from the previous year) represented by the indicators is shown. In the case of retirements this percentage is the labour force retirement rate for the occupation. The percentage of the labour force provides some idea of the importance of the indicators to labour force change. For example, the percentage for retirements is 2.9 percent suggesting that that almost 3.0 percent of the labour force may need to be replaced that year. The average age of the labour force is also provided. The higher the average age the larger is likely to be the number of deaths and retirements as a percentage of the labour force for an occupation. Under gap analysis excess supply, which is the difference between labour force supply and labour force demand, is presented. The negative value suggests that supply is not meeting demand as defined in POMS and the occupation s labour market is or will be tight. The unemployment rate gap is the difference between the actual and normal unemployment rates. While the unemployment rate is positive, the unemployment rate gap is negative as the unemployment rate is below the normal unemployment rate, which suggests that it may be difficult to find employees in this occupation. Nevertheless, the tightness ranks in the table are all 2, suggesting that the labour market is balanced. Under flow analysis the components of total demand change of 794 are comprised of 284 new employees and normal unemployment expansion demand and 510 deaths and retirements that need to be replaced. The change in supply of 810 is met through 347 new entrants and 463 from net in-mobility of employees. As can be seen from the numbers in Figure 7, the latter is met by 112 migrants and 350 other net in-mobility there is some rounding error in the presentation of these numbers. 13 September 2014
Figure 7 Example Occupation Table Labour Force Demand 21562 % Change 0.5 Change 110 Employment 20112 % Change 0.5 Change 103 Normal Unemployment 1450 Labour Force Supply 21542 % Change 1.2 Change 262 Deaths 68 Death Rate (Per 1000 Persons) Retirements 304 % of Labour Force 1.4 New Entrants 462 % of Labour Force 2.1 Net In-Mobility 172 % of Labour Force 0.8 Net In-Migration 247 % of Labour Force 1.1 Other Net In-Mobility -75 % of Labour Force -0.3 Average Labour Force Age 41.03 Gap Analysis Excess Supply -21 Unemployment Rate 6.64 Normal Unemployment Rate 6.73 Unemployment Rate GAP -0.09 Weighted Labour Market Tightness Rank (1-3) 2 Demand Rank 2 Supply (Migration) Rank 2 Unemployment Rate Gap Rank 2 Flow Analysis Total Demand Change Sources 482 % of Labour Force 2.27 Expansion Demand 110 Deaths & Retirements 372 Total Supply Change Sources 634 New Entrants 462 Net In-Mobility 172 September 2014 14
Occupation Data The HRSDC NOC system of occupation definitions is adopted for the modelling system http://www5.hrsdc.gc.ca/noc/english/noc/2011/welcome.aspx. There are 4 levels of NOC occupations. An example of these levels is: 0 Management occupations 1 digit o 00 Senior management occupations 2 digit 001 Legislators and senior management 3 digit 0011 Legislators 4 digit The occupational modelling system works at the 4-digit level of occupation aggregation where there are 500 occupations. The occupation concepts described above are measured on a Place of Residence basis. The concepts refer to persons living in a province. Persons living in a province may have a Place of Work in the province or outside the province. The occupation modelling system focuses on the demand for workers in the province. To the extent that occupations work largely outside the province or are dominated by workers living outside the province, it will present a less accurate picture of Place of Residence measures for the province. The data for the modelling system are sourced from the Census of Canada or lately the National Household Survey (NHS) and the Labour Force Survey (LFS). They are measured on an LFS basis for the occupations as a whole. That is, the total labour force and total employment are equal to the LFS values each year. Nevertheless, the occupation data do not match the LFS occupation data published by Statistics Canada. The latter data have too small a sample size to provide reliable estimates of the occupations, particularly on a provincial basis. To estimate the occupation employment data, an occupation s share of Census (NHS) employment of Census (NHS) total employment in an industry is applied to the corresponding LFS industry employment. The occupation labour force data are estimated in a two-step procedure. In the first step the ratio of Census (NHS) labour force to Census (NHS) employment is applied to the LFS equivalent employment created above. Next, the resulting labour force estimates are normalized to total LFS labour force. For some occupations sample sizes were such that either information were not available or did not make sense because of Statistics Canada s random rounding procedure for data. In the latter case employment exceeded labour force, which is not possible. The solution to this situation was to set the labour force 3 percent above employment the unemployment rate is three percent. It should be noted that Statistics Canada warns users of their data about the poor reliability of data for occupations with few observations, which is particularly the case for provinces with relatively small populations. The employment share coefficients for the occupation employment part of the model were estimated as the ratio of an occupation s employment in an industry to the industry s total employment for the latest Census year. The normal unemployment rates are estimated using historical data on actual unemployment rates for the occupations and judgement regarding what the value of the rate should be to ensure properly functioning labour markets. The ratio of historical averages of the actual rates by occupation to that for the economy as a whole are first calculated. These ratios are then applied to the estimated economy wide rate over the projection period. In some cases minimum values for the rates were applied when it was felt that the rates were too low less than 3 percent. The unemployment rate data are obtained from Statistics Canada s LFS. The retirement rates are computed from data on the median age of retirement for the occupations. The latter data are obtained from information previously published by Statistics Canada. The estimation procedure involves fitting a retirement distribution around the median age at retirement using retirement rates by age. Because the Statistics Canada information is provided only at the 2-digit NOC level, other sources such as industry information are employed where possible. Data on retirement rates at the 4-digit level from Human Resources, Skills, and Development Canada are also used to calibrate the retirement rates. The death rates are derived from information published by Statistics Canada. It is assumed that the rates for each occupation are the same as those for the general population. Historical data are not available for the components of labour force change. These components are estimated in the past and into the future using the models equations for them. 15 September 2014
Occupation Labour Market Analysis The POMS produces information that can be used to help Labour Market Information (LMI) analysts to identify significant supplydemand gaps across the occupations and the possible sources of supply to remove these gaps. An example of how the LMI produced by POMS can be used is provided below. This example employs gap and source w analysis both within a province and across the country. In the example a Human Resource Analyst wishes to assess the existing and future state of the labour market for heavy equipment operators as the analyst s firm is planning to expand its oil sands operations in Alberta. The company would prefer to hire workers with related experience in the oil and gas industry in Alberta, but accepts that it may need to look to other industries and other provinces to obtain the operators. The oil sands industry is a relatively new one and there is unlikely to be significant local supply available given the planned expansion of the oil sands industry in the province over the next 10 years. Heavy equipment operators are found under NOC 7521. According to the NOC: Heavy equipment operators operate heavy equipment used in the construction and maintenance of roads, bridges, airports, gas and oil pipelines, tunnels, buildings and other structures; in surface mining and quarrying activities; and in material handling work. They are employed by construction companies, heavy equipment contractors, public works departments and pipeline, logging, cargo-handling and other companies. The analysis illustrated below examines a broader category than the exact type of person required for the oil sands firm, but does provide an indication of the labour market situation for persons that possess similar qualifications. This issue is similar for other NOC occupations where the occupations are often broadly defined. In the case of carpenters, for example, organizations may be looking for framers that work in residential construction while the carpenter NOC includes framers and carpenters that work building scaffolding largely in non-residential construction. Gap Analysis Gap analysis is used to assess the state of tightness in the labour market for operators. If there is generally an excess supply of operators, it should be relatively easy to find them. Otherwise, more effort will be required in the search for them. The measures used to conduct gap analysis include quantitative ones that employ a measure of excess supply including the use of actual and normal unemployment rates and a qualitative one that uses a ranking system regarding the perceived degree of excess demand or supply. Table 2 shows the information used for gap analysis for heavy equipment operators in the province. As can be seen from the table, a gap opens up between demand and supply in the medium term with supply falling below demand, this gap reaches 202 by 2019 excess supply is negative at -202. To get an idea of how serious a problem this situation is the degree of market tightness in the province Figure 12 shows the actual and normal unemployment rates for operators over the period. Table 2 Gap Analysis Information for Heavy Equipment Operators, Alberta 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Labour Force Demand 21562 22584 23069 23606 24171 24718 25251 25710 25804 25792 25816 Labour Force Supply 21542 22486 23073 23575 24081 24563 25050 25517 25672 25704 25770 Labour Force Excess Supply -21-97 4-30 -90-155 -202-192 -133-88 -45 Unemployment 1430 1422 1555 1557 1536 1508 1497 1537 1603 1647 1691 Unemployment Rate 6.6 6.3 6.7 6.6 6.4 6.1 6.0 6.0 6.2 6.4 6.6 Normal Unemployment Rate 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 Labour Market Tightness Rank (1-3) 2 2 2 2 2 2 2 2 2 2 2 September 2014 16
Figure 12 Actual and Normal Unemployment Rates for Heavy Equipment Operators, Alberta 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Unemployment Rate Normal Unemployment Rate Unemployment rates near the normal unemployment rate the value of the unemployment rate that is on average observed for operators in Alberta suggests a normal labour market, while unemployment rates noticeably above or below the normal rate suggests either a loose or tight market, respectively. Figure 12 contains a band that defines the values of the unemployment rate that represent a normal labour market as defined by the POMS ranking system. The chart suggests a normal market situation. The actual unemployment rate drops below the normal rate over the medium term of the forecast, but not by a significant amount. The labour market tightness rank of 2 over the forecast along with the unemployment rate gap suggests a normal rate of difficulty in finding operators in Alberta during this period. Given that it appears that the labour market for operators in Alberta will be normal it may not be necessary to go outside the province to find them. If they were to look outside the province however, the degree of difficulty in this effort will depend on the demand-supply situation in other provinces. To assess this situation it is necessary to create versions of Figure 12 for each province. Rather than displaying the additional figures here, Table 3 shows the labour market tightness rankings for operators across the provinces. In addition to using the rank values, the table employs different colours to represent the values. Red represents excess demand, green a normal situation for the labour market, and blue (not seen in this occupation) a situation of excess supply. This approach allows decision makers and other observers to easily understand and comment on the analysis. As can be seen from Table 3, most provinces will experience normal labour market tightness for heavy equipment operators in the future. The excess demand rankings in British Columbia, Manitoba, New Brunswick, Prince Edward Island and Newfoundland & Labrador in the short to medium term likely reflect upcoming major projects in these provinces, placing pressure on the demand for operators. Table 3 Labour Market Tightness Rankings for Heavy Equipment Operators, All Provinces 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 British Columbia 2 2 3 3 3 2 2 2 2 2 2 Alberta 2 2 2 2 2 2 2 2 2 2 2 Saskatchewan 2 2 2 2 2 2 2 2 2 2 2 Manitoba 2 2 2 3 3 2 2 2 2 2 2 Ontario 2 2 2 2 2 2 2 2 2 2 2 Quebec 2 2 2 2 2 2 2 2 2 2 2 New Brunswick 2 2 2 3 3 3 2 2 2 2 2 Nova Scotia 2 2 2 2 2 2 2 2 2 2 2 Prince Edward Island 2 2 2 2 2 2 3 2 2 2 2 Newfoundland & Labrador 2 3 2 2 2 2 2 2 2 2 2 17 September 2014