Millennials were the largest generation group in the U.S. in 2023, with an estimated population of 72.7 million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. However, the group already makes up around 42.75 percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups, with the oldest Generation Alpha members aging into adolescents this year. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around seven million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

In 2023, Millennials were the largest generation group in the United States, making up about 21.71 percent of the population. However, Generation Z was not far behind, with Gen Z accounting for around 20.69 percent of the population in that year.

The statistic shows the number of people in the U.S. in 2011 and 2030, by generation. By 2030, the Millennial generation will have 78 million people whereas the Boomer generation will only have 56 million people in the United States.

As of 2023, there were approximately 13.57 million members of the Baby Boomer generation in the United Kingdom, ranging from the ages of 59 to 77. The most-common single year of age for Baby Boomers in this year was 59, at 915,735, while there were 521,896 who were 77, the least common year of age.

In 2023, there were approximately 14.69 million millennials in the United Kingdom, making it the largest generational cohort at that time. Millennials surpassed the Baby Boomer generation as the largest generation for the first time in 2019. The two youngest generations, Gen Z and Gen Alpha, numbered approximately 13.2 million, and 8.3 million respectively. Gen X are, as of the most recent year, the second-largest generation in the UK at 14.04 million people, with their parent's generation, the Silent Generation, numbering around 4.3 million people in the same year. There were estimated to be 85,920 people who belonged to the Greatest Generation, the parents of the Baby Boomer generation, who lived through major events such as the Great Depression and World War Two. Post-War Baby Boom The baby boomer generation was the largest generation for much of this period due to the spike in births that happened after the Second World War. In 1947 for example, there were over one million live births in the United Kingdom, compared with just 657,038 live births just thirty years later in 1977. Members of this generation are typically the parents of millennials, and were the driving force behind the countercultural movement of the 1960s, due to their large numbers relative to older generations at the time. The next generational cohort after Boomers are Generation X, born between 1965 and 1980. This generation had fewer members than the Boomer generation for most of its existence, and only became larger than it in 2021. Millennials and Gen Z As of 2022, the most common single year of age in the United Kingdom in 2020 was 34, with approximately 944,491 people this age. Furthermore, people aged between 30 and 34 were the most numerous age group in this year, at approximately 4.67 million people. As of 2022, people in this age group were Millennials, the large generation who came of age in the late 1990s and early 2000s. Many members of this generation entered the workforce following the 2008 financial crash, and suffered through high levels of unemployment during the early 2010s. The generation that followed Millennials, Generation Z, have also experienced tough socio-economic conditions recently, with key formative years dominated by the COVID-19 pandemic, climate change, and an increasingly unstable geopolitical situation.

In 2022, 51 percent of Generation Z in the United States were White. In comparison, 48 percent of Gen Alpha were White in that year, making it the first generation that does not have a majority White population in the United States.

The working-age population can be divided into two broad categories: the early-working age group (15-34) and the later working age group (35-64). The effect of fertility on the composition of these groups is obvious. The later working age group is largely composed of the baby-boomers (those born between 1946 and 1965), while the early working age group is composed of those born during the baby-bust period (1966-1974) and the children of baby-boomers. Thus, despite the fact that baby-boomers are now older, they still remain the largest group in the population. This is evident in the relatively large proportion (42.6%) of the population that belonged to the late working age group in 2006. The corresponding proportion was much smaller (31.3%) just 25 years ago in 1981. As a result of the entry into the working age group of the people born during the baby-bust period and the children of baby-boomers in 2006, only 26.0% of the population belonged to the 15 to 34 age group in 2006, compared with 36.5% in 1981.

This paper illustrates, based on an example, the importance of consistency between empirical measurement and the concept of variables in estimated macroeconomic models. Since standard New Keynesian models do not account for demographic trends and sectoral shifts, I propose adjusting hours worked per capita used to estimate such models accordingly to enhance the consistency between the data and the model. Without this adjustment, low-frequency shifts in hours lead to unreasonable trends in the output gap, caused by the close link between hours and the output gap in such models. The retirement wave of baby boomers, for example, lowers US aggregate hours per capita, which leads to erroneous permanently negative output gap estimates following the Great Recession. After correcting hours for changes in the age composition, the estimated output gap closes gradually instead following the years after the Great Recession.

According to Cognitive Market Research, the global senior living market will be worth USD XX million in 2024 and expand at a compound annual growth rate (CAGR) of 10.20% from 2024 to 2031.

North America held the major market of more than 30% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.4% from 2024 to 2031.
Europe accounted for over 25% of the global market size of USD XX million.
Asia Pacific held a market of around 36% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.2% from 2024 to 2031.
Latin America's market will have more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.6% from 2024 to 2031.
Middle East and Africa held the major market of around 4.00% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.9% from 2024 to 2031.
Assisted living held the highest Senior Living market revenue share in 2024.

Key Drivers of Senior Living Market

Increasing Demand for Senior Healthcare and Active Lifestyle to Propel the Growth

The increasing demand for senior healthcare is expected to boost the global senior living market significantly. As the global population ages, driven primarily by the aging baby boomer generation and improving healthcare, there is a growing need for specialized housing and healthcare services tailored to seniors. Further, medical technology and treatments have enabled seniors to live longer and healthier lives, increasing the demand for senior living options that provide access to high-quality healthcare and rehabilitation services.

Additionally, the preference for active lifestyles among seniors has led to a demand for senior living communities that offer a wide range of amenities, including fitness centers, recreational activities, and social engagement opportunities. Also, the COVID-19 pandemic has highlighted the importance of infection control and healthcare infrastructure in senior living communities, driving the need for innovative solutions and technologies to ensure the safety and well-being of residents.

Generally, the increasing demand for senior healthcare, coupled with evolving consumer preferences and regulatory changes, is expected to drive significant growth in the global senior living market in the coming years.

Aging Baby Boomer Population to Propel Market Growth

The aging baby boomer population is poised to drive substantial growth in the senior living market. As baby boomers age, there is an increasing need for specialized housing, healthcare services, and amenities tailored to their unique needs and preferences. This includes a growing demand for independent living communities, assisted living facilities, memory care units, and skilled nursing facilities. These accommodations offer varying levels of support and care, allowing seniors to maintain their independence while receiving assistance with daily activities or healthcare needs as necessary.

Furthermore, the absolute size of the baby boomer cohort means that their transition into older age is driving extraordinary demand for senior living options. This demand is not only for housing and healthcare but also for social engagement, recreational activities, and wellness programs designed to promote healthy aging and quality of life.

Moreover, the aging baby boomer population is influencing the development of innovative senior living solutions, including technology-enabled care, age-friendly design features, and personalized services to meet this demographic's diverse needs. The aging baby boomer population largely represents a significant driver of market growth in the senior living sector, shaping the demand for a wide range of housing, care, and lifestyle options for older adults.

Restraint Factors of Senior Living Market

Low Life Savings of Baby Boomers to Impede the Growth

The low life savings of baby boomers could pose a challenge to the growth of the senior living market. While the aging baby boomer population represents a significant demographic segment driving demand for senior living options, their financial preparedness for retirement varies widely. Many baby boomers face financial ...

In 2023, there were estimated to be 956,116 people who were aged 35 in the United Kingdom, the most of any age in this year. The two largest age groups during this year were 30-34, and 35 to 39, at 4.7 million and 4.64 million people respectively. There is also a noticeable spike of 693,679 people who were aged 76, which is due to the high number of births that followed in the aftermath of the Second World War. Over one million born in 1964 In post-war Britain, there have only been two years when the number of live births was over one million, in 1947 and in 1964. The number of births recorded in the years between these two years was consistently high as well, with 1955 having the fewest births in this period at 789,000. This meant that until relatively recently, Baby Boomers were the largest generational cohort in the UK. As of 2022, there were approximately 13.76 million Baby Boomers, compared with 14 million in Generation X, 14.48 million Millennials, and 12.9 million members of Gen Z. The youngest generation in the UK, Generation Alpha numbered approximately 7.5 million in the same year. Median age to hit 44.5 years by 2050 The population of the United Kingdom is aging at a substantial rate, with the median age of the population expected to reach 44.5 years by 2050. By comparison, in 1950 the average age in the United Kingdom stood at 34.9 years. This phenomenon is not unique to the United Kingdom, with median age of people worldwide increasing from 23.6 years in 1950 to a forecasted 41.9 years by 2100. As of 2022, the region with the oldest median age in the UK was South West England, at 43.9 years, compared with 35.9 in London, the region with the youngest median age.

In 2020, about 17.9 percent of the population in China had been 60 years and older. This share is growing rapidly and was estimated to reach 40 percent by 2050. China's aging population With China’s boomer generation growing old and life expectancy increasing at the same time, the number of people at an age of 60 or above nearly doubled between 2000 and 2020 and reached around 255 million. This development is even more pronounced for the age group of 80 and above, which nearly tripled and is expected to reach a size of roughly 132 million in 2050, up from only 32 million in 2020. At the same time, the share of the working-age population is forecasted to decrease gradually from 64 percent of the total population in 2020 to around 50 percent in 2050, which could pose a heavy economic strain on the social security system. The old-age dependency ratio, which denotes the relation of the old-age to the working-age population, is estimated to grow from 18.2 percent in 2020 to more than 50 percent in 2050, implying that by then, statistically, two working-age adults would have to support one elderly. Strain on the social security net During the last 15 years, China's government has successfully increased the coverage of the pension insurance and health insurance. Today, most of the people are covered by some kind of social insurance. Conditions in the pension system are generous, with a regular retirement age for males at 60 years and women at 50 or 55. With the number of retirees increasing quickly, the social insurance system is now under pressure. From an economic point of view, improving the productivity of China's economy would be the primary choice for mitigating alleged inconsistencies of the system. However, without increasing the burden on the working people while tightening payment conditions, balancing the social security net could prove to be challenging.

The working-age population can be divided into two broad categories: the early-working age group (15-34) and the later working age group (35-64). The effect of fertility on the composition of these groups is obvious. The later working age group is largely composed of the baby-boomers (those born between 1946 and 1965), while the early working age group is composed of those born during the baby-bust period (1966-1974) and the children of baby-boomers. Thus, despite the fact that baby-boomers are now older, they still remain the largest group in the population. This is evident in the relatively large proportion (42.6%) of the population that belonged to the late working age group in 2006. The corresponding proportion was much smaller (31.3%) just 25 years ago in 1981. As a result of the entry into the working age group of the people born during the baby-bust period and the children of baby-boomers in 2006, only 26.0% of the population belonged to the 15 to 34 age group in 2006, compared with 36.5% in 1981.

As of 2021, Millennials and Baby Boomers made up an equal share of the Australian population at around 21.5 percent each, making them the largest generational groups at the time. Those aged 75 years and over made up the smallest portion of the population, followed by Gen Alpha, or those aged 0 to 9 years at the time.

For more than three decades UCSUR has documented the status of older adults in the County along multiple life domains. Every decade we issue a comprehensive report on aging in Allegheny County and this report represents our most recent effort. It documents important shifts in the demographic profile of the population in the last three decades, characterizes the current status of the elderly in multiple life domains, and looks ahead to the future of aging in the County. This report is unique in that we examine not only those aged 65 and older, but also the next generation old persons, the Baby Boomers. Collaborators on this project include the Allegheny County Area Agency on Aging, the United Way of Allegheny County, and the Aging Institute of UPMC Senior Services and the University of Pittsburgh.

The purpose of this report is to provide a comprehensive analysis of aging in Allegheny County. To this end, we integrate survey data collected from a representative sample of older county residents with secondary data available from Federal, State, and County agencies to characterize older individuals on multiple dimensions, including demographic change and population projections, income, work and retirement, neighborhoods and housing, health, senior service use, transportation, volunteering, happiness and life satisfaction, among others. Since baby boomers represent the future of aging in the County we include data for those aged 55-64 as well as those aged 65 and older.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

In the first quarter of 2024, 51.8 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials owned around 9.4 percent of total wealth in the U.S. In terms of population distribution, there is almost an equal share of millennials and baby boomers in the United States.

There were approximately 14.69 million millennials in the United Kingdom in 2023. This generation, sometimes called Generation Y were born between 1981 and 1996 and are mainly the children of the post-war Baby Boomer generation. As of 2023, Millennials were the largest generational cohort in the UK, followed by Generation X at 14.04 million people, Baby Boomers at 13.57 million, and then by Generation Z at 13.2 million. The most numerous single-year of age for Millennials, and the UK as a whole, was 35 at 956,116. Boomerang generation The first cohort of millennials came of age at the turn of the century and have almost certainly been heavily influenced by the growth of internet accessibility during this time. The economic challenges faced by this generation may have a relation to the increasing share of young adults who live with their parents in the UK. This has led to the perhaps unfair, characterization of millennials as the boomerang generation, who failed to grow-up and mature. Some of these negative stereotypes regarding Millennials have since shifted to the next youngest generation, Generation Z, who have started to enter the workplace since the mid-2010s. Generation Remain One of the main challenges that British millennials currently face are their prospects after Brexit. Although the United Kingdom voted to leave the European Union in June 2016, there were clear divisions between regions, classes and age-groups. Most millennials voted to remain in the Brexit referendum with 73 percent of people aged 18 to 24, and 62 percent of those aged 25 to 34 voting to remain. In the next UK election, the majority of 25 to 49-year-olds intend to vote for the Labour Party, with only a slight majority of those over 65 planning to vote for the Conservative Party. Millennials also still appear to oppose Brexit, with approximately 65 percent of 25 to 49-year-olds believing Brexit to have been the wrong decision.

Mid-continent mallard breeding population estimates, model set predictions, and model weights from 1995-2018. This information is used to support decision making through the Adaptive Harvest Management program of the U.S. Fish and Wildlife Service.

In 2023, Millennials were the largest generational cohort in the United Kingdom, comprising approximately 21.5 percent of the population. Gen X was the next largest generation at 20.6 percent of the population, followed by Baby Boomers at 19.9 percent, and Gen Z on 19.4 percent.

Depression has strong negative impacts on how individuals function, leading to the assumption that there is strong negative selection on this trait that should deplete genetic variation and decrease its prevalence in human populations. Yet, depressive symptoms remain common. While there has been a large body of work trying to resolve this paradox by mapping genetic variation of this complex trait, there have been few direct empirical tests of the core assumption that there is consistent negative selection on depression in human populations. Here, we use a unique long-term dataset from the National Health and Nutrition Examination Survey that spans four generational cohorts (Silent Generation: 1928–1945, Baby Boomers: 1946–1964, Generation X: 1965–1980, and Millenials: 1981–1996) to measure both depression scores and fitness components (lifetime sexual partners, pregnancies, and live births) of women from the United States born between 1938–1994. We not only assess fitness consequences of depression across multiple generations to determine whether the strength and direction of selection on depression has changed over time, but we also pair these fitness measurements with mixed models to assess how several important covariates, including age, body mass, education, race/ethnicity, and income might influence this relationship. We found that, overall, selection on depression was positive and the strength of selection changed over time–women reporting higher depression had relatively more sexual partners, pregnancies, and births except during the Silent Generation when selection coefficients neared zero. We also found that depression scores and fitness components differed among generations—Baby Boomers showed the highest severity of depression and the most sexual partners. These results were not changed by the inclusion of covariates in our models. A limitation of this study is that for the Millenials, reproduction has not completed and data for this generation is interrupted by right censoring. Most importantly, our results undermine the common belief that there is consistent negative selection on depression and demonstrate that the relationship between depression and fitness changes between generations, which may explain its maintenance in human populations.

Climate change has been identified as one of the most important drivers of wildlife population dynamics. The in-depth knowledge of the complex relationships between climate and population sizes through density dependent demographic processes is important for understanding and predicting population shifts under climate change, which requires integrated population models (IPMs) that unify the analyses of demography and abundance data. In this study we developed an IPM based on Gaussian approximation to dynamic N-mixture models for large scale population data. We then analyzed four decades (1972-2013) of Mallard (Anas platyrhynchos) breeding population survey, band-recovery, and climate data covering a large spatial extent from North American prairies through boreal habitat to Alaska. We aimed to test the hypothesis that climate change will cause shifts in population dynamics if climatic effects on demographic parameters that have substantial contribution to population growth vary spatially. More specifically, we examined the spatial variation of climatic effects on density dependent population demography, identified the key demographic parameters that are influential to population growth, and forecasted population responses to climate change. Our results revealed that recruitment, which explained more variance of population growth than survival, was sensitive to the temporal variation of precipitation in the southern portion of the study area but not in the north. Survival, by contrast, was insensitive to climatic variation. We then forecasted a decrease in Mallard breeding population density in the south and an increase in the northwestern portion of the study area, indicating potential shifts in population dynamics under future climate change. Our results implied that different strategies need to be considered across regions to conserve waterfowl populations in the face of climate change. Our modelling approach can be adapted for other species and thus has wide application to understanding and predicting population dynamics in the presence of global change.