VANCOUVER – Never before have macro level trends had such a transformative impact on societies and economies. Through interconnected supply chains, globalization has increasingly integrated economies. Now fluctuations in one market are also being experienced in another. The rise of climate change has ushered in a new era of energy, resulting in a shift away from non-renewable fossil fuels to more renewable sources of energy. Technological change has upended entire industries, resulting in a rising demand for services over goods. The CoVID-19 pandemic is the most recent example, exposing new fault lines in our social and economic systems.
One of the quieter and perhaps more transformative macro level trends, however, is that of demographic change. Demographic forces are shaping societies in a multitude of ways. In recent years, demographic trends have been most widely noticeable in East Asia and Europe, as they struggle to cope with their rapidly aging populations. In Japan, for example, the dependency ratio, which is the ratio of the combined youth population (0-19) and senior population (65+) to that of the working age population (20-64) has risen from 44.9 dependents per 100 workers in 1970 to 68.3 today. In France, the average household size has shrunk from 3.1 in 1970 to approximately 2.2 today. As North America begins to feel the effects of an aging population, Canada and the United States are also expected to experience major shifts on the horizon. For example, with the baby boomer generation transitioning from their peak earning years to their peak leisure years, we are already witnessing the effects of demographic change in a number of areas. Examples of this can be seen in changing housing demands as well as shifting preferences and consumer spending patterns. Baby boomers are exiting large cities and moving to smaller communities. They are also consuming more services like healthcare and tourism and less manufactured goods. While on one hand, such trends appear to be foreseeable, on the other, few communities and businesses have positioned themselves to monitor trends and anticipate changes. Knowledge of the demographics can be useful in helping communities and businesses positively position themselves for the future.
"Demographic forces are shaping societies in a multitude of ways."
Demographics offers a powerful toolkit for understanding how our social and economic lives are changing. It does so by making use of a wide range of data, including population size, geographic distribution, births, deaths, in-migration, out-migration, ethnicity, age and gender and analyzes how changes in these trends are affecting markets and communities. According to the famed demographer Professor David Foot, demographics has the ability to explain two-thirds of nearly everything. The most powerful predictor being age. He argues that if we know the size of a particular age group and the probability that they will practice a behavior or participate in a particular event, we will have a powerful means for understanding the impact they will have on different aspects of society. As we factor in other population dynamics such as income groups, marital status and so on we can begin to piece together a more comprehensive story. Projecting such trends into the future presents us with an important outlook and illustrates what can be expected in the future. In this way, demographics offers a powerful toolkit for analyzing patterns and anticipating trends in society.
Demographic information is of critical importance in both public and private sector decision making. For the private sector, demographic information can be utilized to understand factors such as market size, market penetration rates and consumer preferences. Projected over time, this can help businesses analyze trends and anticipate future sales. It can also be utilized to inform hiring decisions, securing that businesses have the right people with the right skillsets. In the public sector, demographic information is useful in understanding the overall size and composition of the population and how different groups in society have different needs. Demographic forecasts can help decision makers anticipate how these groups and their needs are changing and prepare their communities accordingly. Such information is also useful for anticipating the probability of events on a per capita basis (ie. traffic fatalities or criminal activity). The alternative is that if the proper forecasts are not made, the outcome might result in a shortage of housing, overcrowded public facilities and overwhelmed infrastructure. Whether it is planning in the private sector (in terms of expansion) or in the public sector (in terms of rolling out public services) demographic information is the basis of informed decision making.
"Knowledge of the demographics can be useful in helping communities and businesses positively position themselves for the future."
While the logic behind demographic analysis may seem relatively straight forward, the tools can be rather arduous. Performing these techniques usually requires a firm understanding of statistics. This is perhaps why we don’t often come across demographers in our everyday lives. Instead, they are more often found in the data friendly environments of academia. This, however, does not make their tools any less suitable in the real world. The tools of demographic analysis have a wide applicability. In the private sector, they are often employed to compute market share and project sales forecasts, while in the public sector they are widely used in the allocation of public sector resources, such as spending on healthcare, education and policing. The results of these exercises are useful in alerting public and private sector officials about how major trends might affect their objectives, permitting them an opportunity to adjust their plans accordingly. Demographic tools are therefore a valuable resource in decision making and agenda setting.
In the case of community planning, one of the most widely applicable demographic tools is population forecasting. Population forecasting is a method to determine the expected population at a future date in time based on information from past trends. It is most often presented in the form of scenarios that include a low-growth scenario, a medium-growth scenario (which is usually the reference scenario used for decision making) and a high-growth scenario. These are built upon a number of assumptions; for example, whether or not recent policy decisions at the national level will lead to increases in births or migration. Depending on the composition of the population and how it is growing population forecasts can take on multiple forms. This is expressed in the form of mathematical functions. The following is a stylistic representation of some of the different functions used for predicting population growth at the sub-national level. To improve the accuracy of the forecast, it is necessary to identify the curve that best fits one’s circumstance; this decision is usually based on the current population trajectory and the most relevant assumptions.
Linear Function: A linear function refers to a population trend that is increasing or decreasing at a constant rate over a given period of time. It is the best fitting curve for understanding the growth trajectory of a relatively stable community.
Exponential Function: An exponential function is a population trend that is undergoing growth or decline at a constant rate of change. It is the most applicable curve for understanding changes in a population that are undergoing population change at a steady rate.
Polynomial Function: Similar to an exponential function, a polynomial function reflects a trend that is undergoing growth or decline. It differs in that it can handle greater degrees of non-linear change, meaning that it is changing at an increasing or decreasing rate. It is considered the best fitting curve for understanding communities that experience drastic fluctuations.
Modified Exponential Function: A modified exponential function differs from the others in that it has a defined upper or lower limit. As it approaches that limit it experiences a decreasing rate of change. This is considered the best fitting curve in communities that have strict zoning guidelines for regulating density.
The most sophisticated form of population projections, however, is the Cohort Component Model. The Cohort Component Model projects the total population size as well as the number of males and females that belong to each 5-year age cohort. The result is a projection of the total population at a future point in time disaggregated into 5-year age cohorts and divided by sex. This tool allows planners to not only forecast the future demand of the overall population, but also to examine the future needs of different segments of the population, such as children, elderly, those participating in the labour force and women during their reproductive years for example. This can be particularly useful information for planners as it helps them to understand the age and gender specific demand for various services such as housing, healthcare, the labour force and so on. Forecasts are usually prepared over 5-, 10- and 20-year time horizons.
"In the case of community planning, one of the most widely applicable demographic tools is population forecasting."
The Cohort Component Model is considered one of the more onerous population projection models. This is because it requires detailed information about the sex and age composition of the population, but also information pertaining to births, deaths, in-migration and out-migration. These are usually estimated through different statistical techniques such as fertility rates, survival rates and estimates of migration flows. Such data can be difficult to attain and is often subject to large degrees of volatility. Fertility rates, for example, can vary by age group and marital status, survival rates on the other hand are more subject to differences in age and health status, while migration estimates can vary depending on push or pull factors; push factors being those forces that dispel people from a location (ie. job loss), while pull factors are those that draw people to a location (ie. to attend university). The Cohort Component Model has different techniques dealing with each of these data challenges.
While population size is useful information for making strategic decisions about the future of a community, changes to the composition of a population also offers important value to planners and decision makers. For example, a population may remain the same in size over time, but it might experience significant changes in terms of age. Moreover, communities that are growing as a result of migration are very different than communities growing through births; this is because migrants are usually of working age and ready to participate in the labour force, whereas newborns will take approximately 19 years to enter the labour force. These characteristics also have important implications for the provision of certain public sector and private sector services. The following are a few key areas upon which demographic forecasts, in particular the Cohort Component Model, can help local administrations prepare for the future.
What will the population of my community look like over the next 5, 10 and 20 years?
Our Official Community Plan has limited growth opportunities, what are our land based needs to support a growing community over the next 20 years?
How are household sizes changing and what is the future housing demand for my community?
What are the specific labour force demands of my community over the next 5-10 years and how can we secure the right skillsets to fill them?
Based on evolving demographic trends, how should we be allocating resources and preparing our community for the future?
Which age cohorts are growing the most and what sector specific effects will this have (ie. education, healthcare, recreational activities, etc.)?
What are the commercial and retail needs to support our growing population and how can we help our local businesses better understand their customer base?
Are crime rates likely to increase or decrease over the next 10 years, and how should we be budgeting for policing?
Does our community have enough childcare facilities and what are the childcare needs of our community over the next 10 years?
We have noticed that many of the baby boomers are moving to our community for retirement reasons, how can we plan our housing strategy to accommodate them without displacing or pricing out the local population?
Communities are growing and changing for a multitude of reasons. If your business or community is interested in learning more about the demographic trends that are shaping it, please let us know.
Kyle Farrell is Managing Partner and Chief Urban Economist at Economic Pulse Analytics. He works closely with local governments to provide them with population, housing and employment forecasts to make more informed decisions about their future. He holds a PhD with specialized knowledge in Urban Economics and regularly consults for the United Nations.
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