In 2022, the median age for the first wedding among women in the United States stood at 28.6 years. For men, the median age was 30.5 years. The median age of Americans at their first wedding has been steadily increasing for both men and women since 1998.

This statistic contains data on the estimated median age of Americans at their first wedding in the United States in 2021, by race and origin. In 2021, the median age for the first wedding among Asian women stood at 28.8 years.

Since the mid-2000s, the average age at first wedding in France has increased gradually, for both men and women. It seems to be common for the first marriage to be celebrated later and later in Western countries. For example, the median age at first marriage in the United States went from **** years old for males and ** years old for females in 1998, up to **** years old for males and **** for females in 2022. The same thing occurred in Europe, where Spain was the country where the median age at first wedding was the oldest in 2022. French people wait longer to marry According to the source, in 2004, the average age at first wedding for French men was **** compared to **** for women. If men still tend to be older than women at first marriage, the average age at marriage for both males and females increased from 2004 to 2024. In 2024, men were on average **** at their first wedding, compared to **** for women. Most marriages in France happened between men and women, despite the implementation of same-sex marriage in 2013. The mean age at gay marriages appears to be even older than in different-sex weddings. Marriage and divorce in France Thus, the percentage of married persons in France has decreased since 2006, while the share of single and divorced people rose. However, in 2016, France was the second European country with the highest number of marriages behind Germany. On the other hand, like most other Western nations, France also has a high divorce rate. In 2016, the number of French divorces was ** per 100 marriages.

Age at First Marriage in America

The Effect of Population Density

By Andy Kriebel [source]

About this dataset

This dataset contains information on the median age at first marriage for women in the United States. The data is broken down by county, and includes information on population density, FIPS code, and county type

How to use the dataset

This dataset contains information on the age at first marriage for women in the United States. The data is broken down by state, county, and year. To use this dataset, you can choose to either download the entire dataset or select specific states, counties, and years of interest. If you select specific states, counties, and years of interest, be sure to filter the data accordingly

Research Ideas

To find out which states have the oldest or youngest median ages at first marriage. To understand how population density may affect the median age at first marriage. To compare the median age at first marriage across different types of counties

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Median Age at First Marriage .csv | Column name | Description | |:---------------------------------|:---------------------------------------------------------------------------| | FIPS | The Federal Information Processing Standard code for each county. (String) | | Name | The name of the county. (String) | | Type | The type of county. (String) | | TimeFrame | The timeframe of the data. (String) | | Median Age | The median age at first marriage for women in the county. (Float) | | Population Density per Sq Mi | The population density of the county. (Float) |

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel.

81 percent of the Silent generation were married between the age of 23 and 38. This is true for only 44 percent of Millennials.

United States Marriage Statistics

Marriage rates by gender, age group, and year in the United States (2005-2017)

By Throwback Thursday [source]

About this dataset

This dataset, titled United States Marriage Status 2005-2017, provides detailed information on marriage rates and population estimates in the United States. The data is sourced from the U.S. Census Bureau's American Community Survey 1-Year Estimates.

The dataset includes several key attributes that offer insights into different aspects of marriage status. These attributes include Year, Gender, Age Group, Metric, Estimated Percent, and Estimated Population.

The Year attribute represents the year in which the data was collected, spanning from 2005 to 2017. It allows for analysis of trends and changes in marriage rates over time.

The Gender attribute categorizes the population groups based on their gender. This information helps explore any variations or differences between male and female populations in terms of marital status.

Age Group attribute classifies individuals into specific age categories within the population. By segmenting the data based on age groups, it becomes possible to analyze how different age demographics contribute to overall marriage rates.

Metric serves as a descriptor for specific measurements or indicators being reported within this dataset. This attribute provides further context for understanding different aspects related to marriage status and its calculation methods.

Estimated Percent denotes the estimated percentage of a particular population group falling into a specific category related to marital status. It offers valuable insights into relative proportions within each demographic group.

Estimated Population showcases estimated count figures representing various subgroups' populations classified by gender, age groupings, and metric categories specified previously. These estimates allow researchers to explore potential correlations between population sizes and marriage rates across various segments of society over time period covered by this dataset.

Overall, this comprehensive United States Marriage Status dataset provides a valuable resource for analyzing trends in marriage rates while considering gender demographics, age distributions within these populations along with respective metrics indicating changes occurring over time periods marked since 2005 until 2017 (date-range excluding exact dates provided). By exploring relationships among these factors using reliable census data available through American Community Survey 1-Year Estimates, researchers can gain deep understanding of marriage status dynamics in the United States

How to use the dataset

• Understand the Columns:

  • Year: This column represents the year in which the data was collected. It provides a timeline for analyzing marriage trends over time.
  • Gender: This column categorizes individuals based on their gender, providing insights into marriage rates and patterns specific to each gender.
  • Age Group: This column categorizes individuals based on their age group. It allows for a detailed analysis of marriage rates and statistics among different age groups.
  • Metric: This column specifies the type of data or measurement being reported, providing clarity on what aspect of marriage is being analyzed.
  • Estimated Percent: This column represents the estimated percentage of individuals within a population group falling into a particular category. It quantifies marriage rates as percentages.
  • Estimated Population: This column provides an estimation of the total population count within a specific category, offering insights into the size and distribution of different population groups.

• Analyzing Trends: Use this dataset to analyze trends in US marriage statistics by leveraging various combinations of columns:

  • Gender vs Metric: Compare different metrics (e.g., number of marriages, divorce rate) between genders, allowing for an understanding of any gender-specific variations in marital trends.
  • Year vs Metric: Study changes in various metrics over time (e.g., changes in average age at first marriage), identifying trends and potential shifts in societal attitudes towards marriage.
  • Age Group vs Metric/Gender/Year: Examine how different age groups contribute to overall marital statistics (e.g., comparing divorce rates among different age groups or analyzing changes over time within specific age cohorts).

• Interpreting Results: When analyzing this dataset's results, keep these factors in mind:

  • Size Differences: Ensure you factor in the estimated population count for eac...

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2012-2016 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2012-2016 American Community Survey 5-Year Estimates

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

In 2022, there were 67.85 million married men and 68.45 million married women living in the United States. This is compared to 3.7 million widowed men and 11.48 million widowed women.

Marriage in the United States

Nevada had the highest marriage rate in the United States in 2021, followed by Hawaii and Montana. This can be attributed to marriage accessibility in the state. Las Vegas weddings are known for being quick, easy, and inexpensive chapel weddings. In comparison to the cheap weddings available in Las Vegas, the average expenditure for a wedding in the United States was the highest in New Jersey, clocking in at 51,000 U.S. dollars.

Same-sex marriage

The number of Americans who think that same-sex marriage should be recognized by law has more than doubled since 1996, while the number of Americans who think it should not be valid has decreased. It was not until June 26, 2015 that the United States Supreme Court legalized same-sex marriage in all 50 states. Before then, it was up to the states to decide if they allowed same-sex marriage. States in the Southeast are the most opposed to same-sex marriage, whereas the strongest support comes from Northern coastal states.

This dataset provides valuable insights into the work and household characteristics of married individuals in the United States. With 753 observations representing individuals, the dataset offers a comprehensive view of various factors that influence work patterns and family dynamics.

Details

These data seem to have come from the same source as carData::Mroz, though each data set has variables not in the other. The variables that are shared have different names. On 2019-11-04 Bruno Rodrigues explained that Ecdat::Mroz['work'] had the two labels incorrectly swapped, and wooldridge::mroz['inlf'] was correct; wooldridge matches carData::Mroz['lfp'].

Source

Mroz, T. (1987) “The sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions”, Econometrica, 55, 765-799. 1976 Panel Study of Income Dynamics.

References

Greene, W.H. (2003) Econometric Analysis, Prentice Hall, https://archive.org/details/econometricanaly0000gree_f4x3, Table F4.1.

The Wedding Services industry provides a wide variety of wedding day services, apparel retailers and venues. Evolving social norms and medical advancements, which enable women to safely give birth later in life, have caused the marriage rate to decline in recent decades. Extended periods of cohabitation before marriage and family planning have increasingly become normal among young couples. As a result, the industry has contended with declining revenue over the past five years. Despite fewer couples getting married, increasing per capita disposable income has enabled those seeking to spend more on their big day, limiting revenue declines. Nonetheless, as couples postponed or downsized their weddings during the COVID-19 pandemic, industry revenue dropped significantly in 2020 alone. Consequently, industry revenue fell at a CAGR of 4.1% to $70.3 billion over the past five years, including a decrease of 0.6% in 2023 alone.Despite rising wedding budgets, which translated to higher revenue, heightened competition has hindered revenue per operator. Over the past five years, the barriers to entry for operators in this industry have decreased as more couples can find vendors through the internet. Online marketing and social media have increased visibility for wedding services and lowered marketing budgets, making it easier for new companies to enter the industry. But, coronavirus-related pressures forced many of these new entrants out of the industry. Also, limited demand because of the declining marriage rate has led to lower revenue per operator somewhat deterring new entrants.Moving forward, industry demand will continue to be pressured by the marriage rate, which will further decline over the next five years. Even so, continued pent-up demand from previously postponed weddings will support industry revenue. During the outlook period, rising consumer confidence indicates that individuals will be more willing to take on nonessential expenditures and incur high wedding costs. Also, the increasing average age of marriage and the length of engagements will give couples more time to plan and save money for their ceremonies. Overall, industry revenue will rise at a CAGR of 0.2% to $71.1 billion over the next five years.

This statistic shows the average income of married and unmarried men in the United States in 2016, by age. In that year, 45-year-old married men had an average income of **** thousand U.S. dollars, compared to 45-year-old unmarried men, who had an average income of **** thousand U.S. dollars.

The highest share of home buyers in the United States in 2024 across all age groups were married couples. Married couples made up at least ** percent of home buyers in all age groups that year, except for homebuyers aged between 18 and 25 years old.

The average American family in 2023 consisted of 3.15 persons. Families in the United States According to the U.S. Census Bureau, a family is a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered as members of one family. As of 2023, the U.S. Census Bureau counted about 84.33 million families in the United States. The average family consisted of 3.15 persons in 2021, down from 3.7 in the 1960s. This is reflected in the decrease of children in family households overall. In 1970, about 56 percent of all family households had children under the age of 18 living in the household. This percentage declined to about 40 percent in 2020. The average size of a family household varies greatly from state to state. The largest average families can be found in Utah, California, and Hawaii, while the smallest families can be found in Wisconsin, Vermont and Maine.

August was the most popular month for weddings in England and Wales in 2022, with 33,676 marriages taking place in this month. Unsurprisingly, the other Summer months of June and July were also popular choices, as well as September. With just 6,367 weddings occurring in January, this was the least popular month for weddings. When is the most popular day for a wedding? In 2022, Saturday was the most popular day of the week for weddings, with Friday a distant second. In fact, during that year, the top 31 dates for weddings were all Saturdays, with 3,500 weddings taking place on Saturday July 30, the most popular date for holding a wedding in that year. Monday was the least popular day of the week for a wedding in 2022, while Christmas Day (Sunday 25, December) had just three weddings taking place, the fewest of any date in that year. Cost of weddings on the rise The average cost of a wedding has increased from around 17,300 British pounds in 2021 to approximately 23,250 by 2024. Following the COVID-19 Pandemic, the cost of a wedding fell to 9,100 pounds in 2020, before recovering slightly to around by 2021. Wedding venues were the largest expense, costing around 6,286 pounds, with catering also setting people back by around 4,419 pounds. When compared with other countries, UK weddings cost less than those in the United States, Spain, Italy and Canada, but more than France, Portugal and Mexico, among other countries.

In 2022, the divorce rate in the United States stood at *** per 1,000 of the population. Divorce in the U.S. Divorce is the termination of a marital union. In the United States, as in most other countries, it is a legal process in which a judge or another legal authority dissolves the bonds of matrimony existing between two persons. The process of divorce also normally involves issues surrounding distribution of property, financial support of the former spouse, child custody and child support. A divorce also allows a person to marry again.In the United States, divorce is, like marriage, a matter for state governments, not the federal government. Although divorce laws vary from state to state, for example on which terms a divorce can be arranged, a divorce must be certified by a court of law to become effective. A declining divorce rate Over the last couple of years, both the marriage rate and the divorce rate have been declining in the United States. As of 2009, the average length of a first marriage in the U.S. was ***** years, while the average length of a second marriage was about ** years.

The homeownership rate was the highest among Americans in their early 70s and the lowest among people in their early 20s in 2024. In that year, approximately **** percent of individuals aged 70 to 74 resided in a residence they owned, compared to approximately ** percent among individuals under the age of 25. On average, **** percent of Americans lived in an owner-occupied home. The homeownership rate was the highest in 2004 but has since declined.

In 2023, about 39.47 percent of all family households in the United States had their own children under age 18 living in the household. This is compared to the approximate 48.5 percent of female-led households with their own children under 18.

In 2022, 97.4 percent of women between the ages of 15 and 19 years old in the United States were childless -- the most out of any age group. In the same year, 17.7 percent of women between the ages of 40 and 44 years old were childless. Demographics of women without children As of 2022, a little less than half of all women in the U.S. were childless. About 68.4 percent of women without children did not have a high school degree, which is in line with the largest percentage of childless women being between the ages of 15 and 19. Additionally, about 48 percent of Asian women in the United States did not have any children, more than the national average. Births in the U.S. Asian women in the United States have the lowest fertility rate per 1,000 women, while Native Hawaiian and Pacific Islander women had the highest fertility rate. The vast majority of all births in the U.S. were to women between the ages of 20 and 39, but it is worth noting that births in the United States have been declining over the past few decades.