By April 2026, it is projected that there is a probability of ***** percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.

The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.

During a 2025 survey in the United States, marketers' optimism level about the American economy declined to 62.2 points, down from 63.8 in Fall 2024. Optimism was at its lowest level since Fall 2022 - that year, Russia's invasion of Ukraine led to global economic uncertainty, while high inflation and recession fears also added to a general negative sentiment.

This dataset is about book subjects. It has 3 rows and is filtered where the books is The falling rate of profit in the postwar United States economy. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Hug page featuring Sioux Falls Dashboard - Economic Indicators - Finance - Unemployment Rate.

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Multi-Family Projects.

In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

Graph and download economic data for Gross Domestic Product: Private Goods-Producing Industries in Fall River County, SD (GDPGOODS46047) from 2001 to 2023 about Fall River County, SD; goods-producing; SD; private; industry; GDP; and USA.

Datasets extracted from the Fall Economic Statement 2018.

Graph and download economic data for Total Real Gross Domestic Product for Wichita Falls, TX (MSA) (RGMP48660) from 2001 to 2023 about Wichita Falls, TX, real, industry, GDP, and USA.

Graph and download economic data for Gross Domestic Product: All Industries in Twin Falls County, ID (GDPALL16083) from 2001 to 2023 about Twin Falls County, ID; ID; industry; GDP; and USA.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Economy, PA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Economy, PA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Economy households based on income levels.

Key observations

• For Family Households: In Economy, the majority of family households, representing 19.26%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.47%, have incomes falling $35,000 to $39,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Economy, the majority of non-family households, accounting for 14.99%, have income $50,000 to $59,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 1.54%, earn $35,000 to $39,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Economy, PA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Economy, PA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Economy, PA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Economy, PA

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Economy median household income. You can refer the same here

The author argues that the economic benefits of low gasoline prices for the U.S. economy have fallen substantially since the reemergence of America as a major oil producer. The old rule-of thumb that a 10% fall in the oil price raises inflation-adjusted U.S. GDP by 0.2% is too large—the impact on economic activity should be closer to zero, and may even be negative if consumption grows slowly. The reasons for this change are straightforward, if underappreciated: (i) the value of oil production accounts for a larger share of the U.S. economy; and (ii) consumers are not spending the windfall like they used to because of higher debt levels, limited access to credit, slow wage rowth, and an older population.

Fall Detection Devices for Seniors Market Outlook

The global market size for fall detection devices for seniors was estimated at USD 500 million in 2023 and is projected to reach approximately USD 1.2 billion by 2032, exhibiting a CAGR of 10.5% during the forecast period. The growth in this market is driven by the increasing aging population worldwide, heightened awareness regarding senior safety, and advancements in sensor technologies.

A significant growth factor in the fall detection devices for seniors market is the rapidly increasing elderly population. According to the World Health Organization (WHO), the global population aged 60 years and older is expected to reach 2 billion by 2050, up from 900 million in 2015. This demographic shift creates a substantial market for fall detection devices, as older adults are more prone to falls and related injuries. Consequently, there is a rising demand for effective fall detection systems to ensure the safety and independence of seniors.

Technological advancements in sensor and wearable technology are another crucial driver of market growth. Modern fall detection devices now incorporate sophisticated sensors like accelerometers, gyroscopes, and multi-sensor systems that offer higher accuracy and reliability in detecting falls. Integration with smart home systems and mobile apps further enhances the functionality of these devices, making them more user-friendly and efficient. Additionally, the development of AI and machine learning algorithms has improved the ability to differentiate between falls and non-fall activities, reducing false alarms and increasing user confidence in these devices.

The advent of Geriatric Cellular Phone technology is another promising development in the realm of senior safety. These phones are specifically designed to cater to the needs of elderly users, featuring larger buttons, simplified interfaces, and enhanced audio capabilities. They often come equipped with emergency response features, including fall detection, which can alert caregivers or emergency services in case of an incident. By integrating cellular technology with fall detection systems, these phones provide an additional layer of security and independence for seniors, allowing them to stay connected with family and healthcare providers while ensuring their safety.

Healthcare policy and economic factors also play a significant role in the market's expansion. Many countries have introduced supportive healthcare policies and insurance coverage for fall detection devices, recognizing the importance of preventing falls among seniors. For instance, Medicare in the United States covers certain aspects of fall detection devices, which reduces the financial burden on seniors and their families. Moreover, the economic burden of fall-related injuries, estimated to be in billions of dollars annually, drives the adoption of preventive measures like fall detection devices.

Regionally, North America and Europe are the primary markets for fall detection devices, driven by high awareness levels, robust healthcare infrastructure, and significant investments in senior healthcare. The Asia Pacific region is expected to witness the highest growth rate due to the increasing aging population, rising healthcare expenditure, and improvements in healthcare infrastructure. Emerging markets in Latin America and the Middle East & Africa also present growth opportunities due to improving economic conditions and increasing awareness.

Product Type Analysis

The fall detection devices for seniors market is segmented into wearable devices and non-wearable devices. Wearable devices include items such as smartwatches, pendants, and belts that are equipped with fall detection sensors. These devices are popular due to their portability and ease of use. They can be worn on the body, making them convenient for continuous monitoring. The advent of smartwatches with integrated fall detection features has significantly contributed to the market's growth. These devices not only detect falls but also offer additional functionalities like heart rate monitoring and GPS tracking, making them a comprehensive health monitoring tool for seniors.

Fall Detection Switches are becoming increasingly popular in both residential and institutional settings. These switches are strate

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Economy, PA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Economy, PA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Economy households based on income levels.

Key observations

• For Family Households: In Economy, the majority of family households, representing 14.12%, earn $100,000 to $124,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.37%, have incomes falling $150,000 to $199,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Economy, the majority of non-family households, accounting for 14.68%, have income $60,000 to $74,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.45%, earn $150,000 to $199,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Economy, PA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Economy, PA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Economy, PA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Economy, PA

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Economy median household income. You can refer the same here

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Employment Data.

Japan BSI: Economic Conditions: All Industries: LE: Declining data was reported at 5.000 % in Mar 2019. This records a decrease from the previous number of 5.500 % for Dec 2018. Japan BSI: Economic Conditions: All Industries: LE: Declining data is updated quarterly, averaging 15.450 % from Jun 2004 (Median) to Mar 2019, with 60 observations. The data reached an all-time high of 58.200 % in Mar 2009 and a record low of 5.000 % in Mar 2019. Japan BSI: Economic Conditions: All Industries: LE: Declining data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Japan – Table JP.S057: Business Outlook Survey: Business Survey Index.

Buffalo-Cheektowaga, NY - Economic Conditions Index for Buffalo-Cheektowaga-Niagara Falls, NY (MSA) (DISCONTINUED) was -0.47% in December of 2019, according to the United States Federal Reserve. Historically, Buffalo-Cheektowaga, NY - Economic Conditions Index for Buffalo-Cheektowaga-Niagara Falls, NY (MSA) (DISCONTINUED) reached a record high of 18.91 in August of 1998 and a record low of -16.01 in July of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for Buffalo-Cheektowaga, NY - Economic Conditions Index for Buffalo-Cheektowaga-Niagara Falls, NY (MSA) (DISCONTINUED) - last updated from the United States Federal Reserve on June of 2025.

A tabular summary of British Columbia's Fall 2020 Economic & Fiscal Update (Q2) - Fiscal Plan Update 2020/21 - 2022/23, 2020/21 Economic Outlook and Financial Forecast & Three Month Results July - September 2020