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.

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.

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q1 2025 about recession indicators, GDP, and USA.

From the Summer of 2007 until the end of 2009 (at least), the world was gripped by a series of economic crises commonly known as the Global Financial Crisis (2007-2008) and the Great Recession (2008-2009). The financial crisis was triggered by the collapse of the U.S. housing market, which caused panic on Wall Street, the center of global finance in New York. Due to the outsized nature of the U.S. economy compared to other countries and particularly the centrality of U.S. finance for the world economy, the crisis spread quickly to other countries, affecting most regions across the globe. By 2009, global GDP growth was in negative territory, with international credit markets frozen, international trade contracting, and tens of millions of workers being made unemployed.

Global similarities, global differences

Since the 1980s, the world economy had entered a period of integration and globalization. This process particularly accelerated after the collapse of the Soviet Union ended the Cold War (1947-1991). This was the period of the 'Washington Consensus', whereby the U.S. and international institutions such as the World Bank and IMF promoted policies of economic liberalization across the globe. This increasing interdependence and openness to the global economy meant that when the crisis hit in 2007, many countries experienced the same issues. This is particularly evident in the synchronization of the recessions in the most advanced economies of the G7. Nevertheless, the aggregate global GDP number masks the important regional differences which occurred during the recession. While the more advanced economies of North America, Western Europe, and Japan were all hit hard, along with countries who are reliant on them for trade or finance, large emerging economies such as India and China bucked this trend. In particular, China's huge fiscal stimulus in 2008-2009 likely did much to prevent the global economy from sliding further into a depression. In 2009, while the United States' GDP sank to -2.6 percent, China's GDP, as reported by national authorities, was almost 10 percent.

The statistic shows the gross domestic product (GDP) of the United States from 1987 to 2024, with projections up until 2030. The gross domestic product of the United States in 2024 amounted to around 29.18 trillion U.S. dollars. The United States and the economy The United States’ economy is by far the largest in the world; a status which can be determined by several key factors, one being gross domestic product: A look at the GDP of the main industrialized and emerging countries shows a significant difference between US GDP and the GDP of China, the runner-up in the ranking, as well as the followers Japan, Germany and France. Interestingly, it is assumed that China will have surpassed the States in terms of GDP by 2030, but for now, the United States is among the leading countries in almost all other relevant rankings and statistics, trade and employment for example. See the U.S. GDP growth rate here. Just like in other countries, the American economy suffered a severe setback when the economic crisis occurred in 2008. The American economy entered a recession caused by the collapsing real estate market and increasing unemployment. Despite this, the standard of living is considered quite high; life expectancy in the United States has been continually increasing slightly over the past decade, the unemployment rate in the United States has been steadily recovering and decreasing since the crisis, and the Big Mac Index, which represents the global prices for a Big Mac, a popular indicator for the purchasing power of an economy, shows that the United States’ purchasing power in particular is only slightly lower than that of the euro area.

From the onset of the Global Financial Crisis in the Summer of 2007, the world economy experienced an almost unprecedented period of turmoil in which millions of people were made unemployed, businesses declared bankruptcy en masse, and structurally critical financial institutions failed. The crisis was triggered by the collapse of the U.S. housing market and subsequent losses by investment banks such as Bear Stearns, Lehman Brothers, and Merrill Lynch. These institutions, which had become over-leveraged with complex financial securities known as derivatives, were tied to each other through a web of financial contracts, meaning that the collapse of one investment bank could trigger the collapse of several others. As Lehman Brothers failed on September 15. 2008, becoming the largest bankruptcy in U.S. history, shockwaves were felt throughout the global financial system. The sudden stop of flows of credit worldwide caused a financial panic and sent most of the world's largest economies into a deep recession, later known as the Great Recession. The World Economy in recession
More than any other period in history, the world economy had become highly interconnected and interdependent over the period from the 1970s to 2007. As governments liberalized financial flows, banks and other financial institutions could take money in one country and invest it in another part of the globe. Financial institutions and other non-financial companies became multinational, meaning that they had subsidiaries and partners in many regions. All this meant that when Wall Street, the center of global finance in New York City, was shaken by bankruptcies and credit freezes in late 2007, other advanced economies did not need to wait long to feel the tremors. All of the G7 countries, the seven most economically advanced western-aligned countries, entered recession in 2008, before experiencing an even deeper trough in 2009. While all returned to growth by 2010, this was less stable in the countries of the Eurozone (Germany, France, Italy) over the following years due to the Eurozone crisis, as well as in Japan, which has had issues with low growth since the mid-1990s.

Economic models that do not incorporate financial frictions only explain about 70 to 80 percent of the decline in world trade that occurred in the 2008-2009 crisis. We review evidence that shows financial factors also contributed to the great trade collapse and uncover two new stylized facts in support of it. First, we show that the prices of manufactured exports rose relative to domestic prices during the crisis. Second, we show that US seaborne exports and imports, which are likely to be more sensitive to trade finance problems, saw their prices rise relative to goods shipped by air or land.

The Great Recession was a period of economic contraction which came in the wake of the Global Financial Crisis of 2007-2008. The recession was triggered by the collapse of the U.S. housing market and subsequent bankruptcies among Wall Street financial institutions, the most significant of which being the bankruptcy of Lehman Brothers in September 2008, the largest bankruptcy in U.S. history. These economic convulsions caused consumer confidence, measured by the Consumer Confidence Index (CCI), to drop sharply in 2007 and the beginning of 2008. How does the Consumer Confidence Index work? The CCI measures household's expectation of their future economic situation and, consequently, their likely future spending and savings decisions. A score of 100 in the index would indicate a neutral economic outlook, with consumers neither being optimistic nor pessimistic about the near future. Scores below 100 are then more pessimistic, while scores above 100 indicate optimism about the economy. Consumer confidence can have a self-fulfilling effect on the economy, as when consumers are pessimistic about the economy, they tend to save and postpone spending, contracting aggregate demand and causing the economy to slow down. Conversely, when consumers are optimistic and willing to spend, this can have a reinforcing effect as wages and employment may rise when consumers spend more. CCI and the Great Recession As the reality of the trouble which the U.S. financial sector was in set in over 2007, consumer confidence dropped sharply from being slightly positive, to being deeply pessimistic by the Summer of 2008. While confidence began to slowly rebound up until September 2008, with the panic caused by Lehman's bankruptcy and the freezing of new credit creation, the CCI plummeted once more, reaching its lowest point during the recession in February 2008. The U.S. government stepped in to prevent the bankruptcy of AIG in 2008, promising to do the same for any future possible failures in the financial system. This 'backstopping' policy, whereby the government assured that the economy would not be allowed to fall further into crisis, along with the Federal Reserve's unconventional monetary policies used to restart the economy, contributed to a rebound in consumer confidence in 2009 and 2010. In spite of this, consumers still remained pessimistic about the economy.

The Global Financial Crisis (2007-2008), which began due to the collapse of the U.S. housing market, had a negative effect in many regions across the globe. The global recession which followed the crisis in 2008 and 2009 showed how interdependent and synchronized many of the world's economies had become, with the largest advanced economies showing very similar patterns of negative GDP growth during the crisis. Among the largest emerging economies (commonly referred to as the 'E7'), however, a different pattern emerged, with some countries avoiding a recession altogether. Some commentators have particularly pointed to 2008-2009 as the moment in which China emerged on the world stage as an economic superpower and a key driver of global economic growth. The Great Recession in the developing world While some countries, such as Russia, Mexico, and Turkey, experienced severe recessions due to their connections to the United States and Europe, others such as China, India, and Indonesia managed to record significant economic growth during the period. This can be partly explained by the decoupling from western financial systems which these countries undertook following the Asian financial crises of 1997, making many Asian nations more wary of opening their countries to 'hot money' from other countries. Other likely explanations of this trend are that these countries have large domestic economies which are not entirely reliant on the advanced economies, that their export sectors produce goods which are inelastic (meaning they are still bought during recessions), and that the Chinese economic stimulus worth almost 600 billion U.S. dollars in 2008/2009 increased growth in the region.

This thesis explores the devastating economic consequences that a hypothetical World War III could have on the global economy. Unlike the previous world wars, this conflict would unfold in a highly globalized, digitally interconnected world—meaning the economic damage would be even more widespread and severe.Drawing from history, the paper analyzes past wars like World War I and II, highlighting how those events caused GDP contractions, hyperinflation, destruction of infrastructure, and long-term debt. It uses these precedents to build realistic scenarios for what could happen if WWIII breaks out today. The study models short-term disruptions like stock market crashes, currency collapse, and trade blockades; medium-term issues like mass unemployment and inflation; and long-term impacts such as technological regression and widespread economic stagnation.The thesis provides regional assessments as well—evaluating how countries like the U.S., China, and nations in Europe and the Global South would fare in different war scenarios, from limited conflicts to full-scale nuclear exchanges. It also discusses secondary effects like energy and food shortages, famine, and the collapse of consumer demand in non-essential sectors.Importantly, the paper doesn’t stop at doom and gloom. It outlines strategic policy responses such as emergency fiscal controls, global debt restructuring, a possible new Bretton Woods system, and a modern-day Marshall Plan to help rebuild economies post-war.In conclusion, the research emphasizes that preventing World War III is not just a matter of global peace, but an absolute economic necessity. Even the strongest economies could collapse, and recovery could take decades—if at all. The thesis serves as both a warning and a call for proactive international diplomacy, economic safeguards, and collective accountability.

We use natural language processing methods to quantify the sentiment expressed in the Federal Reserve's anecdotal summaries of current economic conditions in the national and 12 Federal Reserve District-level economies as published eight times per year in the Beige Book since 1970. We document that both national and District-level economic sentiment tend to rise and fall with the US business cycle. But economic sentiment is extremely heterogeneous across Districts, and we find that national economic sentiment is not always the simple aggregation of District-level sentiment. We show that the heterogeneity in District-level economic sentiment can be used, over and above the information contained in national economic sentiment, to better forecast US recessions.

Between the Wall Street Crash of 1929 and the end of the Great Depression in the late 1930s, the Soviet Union saw the largest growth in its gross domestic product, growing by more than 70 percent between 1929 and 1937/8. The Great Depression began in 1929 in the United States, following the stock market crash in late October. The inter-connectedness of the global economy, particularly between North America and Europe, then came to the fore as the collapse of the U.S. economy exposed the instabilities of other industrialized countries. In contrast, the economic isolation of the Soviet Union and its detachment from the capitalist system meant that it was relatively shielded from these events. 1929-1932 The Soviet Union was one of just three countries listed that experienced GDP growth during the first three years of the Great Depression, with Bulgaria and Denmark being the other two. Bulgaria experienced the largest GDP growth over these three years, increasing by 27 percent, although it was also the only country to experience a decline in growth over the second period. The majority of other European countries saw their GDP growth fall in the depression's early years. However, none experienced the same level of decline as the United States, which dropped by 28 percent. 1932-1938 In the remaining years before the Second World War, all of the listed countries saw their GDP grow significantly, particularly Germany, the Soviet Union, and the United States. Coincidentally, these were the three most powerful nations during the Second World War. This recovery was primarily driven by industrialization, and, again, the U.S., USSR, and Germany all experienced the highest level of industrial growth between 1932 and 1938.

Crash Cushion Market Outlook

According to our latest research, the Global Crash Cushion Market size was valued at $1.2 billion in 2024 and is projected to reach $2.1 billion by 2033, expanding at a robust CAGR of 6.5% during 2024–2033. The primary growth driver for the global crash cushion market is the rising emphasis on road safety across both developed and emerging economies, spurred by increasing government investments in transportation infrastructure and stricter regulations for roadside safety installations. The growing incidence of road accidents and the subsequent need to minimize fatalities and property damage have heightened the demand for advanced crash cushion systems, making them an indispensable component of modern highways, urban roads, and critical infrastructure projects worldwide.

Regional Outlook

North America currently holds the largest share of the global crash cushion market, accounting for approximately 35% of the total market value in 2024. This region’s dominance is attributed to its mature transportation infrastructure, stringent regulatory frameworks, and early adoption of advanced road safety technologies. The United States, in particular, has witnessed significant investments in upgrading highways and urban roads, driven by federal and state-level initiatives aimed at reducing traffic fatalities. Additionally, the presence of leading crash cushion manufacturers and robust R&D activities have enabled continuous product innovation, further consolidating North America’s leadership in the global market. The region’s focus on integrating smart technologies and IoT-enabled safety solutions is also expected to sustain its market share over the forecast period.

The Asia Pacific region is projected to be the fastest-growing market for crash cushions, with a forecasted CAGR of 8.2% from 2024 to 2033. This rapid growth is fueled by massive infrastructure development projects in countries such as China, India, Japan, and Southeast Asian nations. Governments in this region are investing heavily in expanding and modernizing road networks, bridges, and airports to support urbanization and economic growth. The increasing rate of motorization and heightened public awareness of road safety have further accelerated the adoption of crash cushions. Moreover, international funding and public-private partnerships for infrastructure projects are creating lucrative opportunities for both local and global market players, driving market expansion at an unprecedented pace.

Emerging economies in Latin America, the Middle East, and Africa are gradually increasing their adoption of crash cushion technologies, albeit at a slower pace compared to developed regions. The primary challenges in these markets include limited budget allocations for road safety, lack of standardized regulations, and insufficient public awareness regarding the benefits of crash cushions. However, as these regions continue to urbanize and address their growing road safety concerns, there is a noticeable uptick in government-led initiatives and international collaborations. Localized demand is also being shaped by specific policy reforms and targeted investments in high-risk zones such as highways and urban intersections. Over the forecast period, these emerging markets are expected to contribute significantly to global market growth as infrastructural and regulatory landscapes evolve.

Report Scope

On October 29, 1929, the U.S. experienced the most devastating stock market crash in it's history. The Wall Street Crash of 1929 set in motion the Great Depression, which lasted for twelve years and affected virtually all industrialized countries. In the United States, GDP fell to it's lowest recorded level of just 57 billion U.S dollars in 1933, before rising again shortly before the Second World War. After the war, GDP fluctuated, but it increased gradually until the Great Recession in 2008. Real GDP Real GDP allows us to compare GDP over time, by adjusting all figures for inflation. In this case, all numbers have been adjusted to the value of the US dollar in FY2012. While GDP rose every year between 1946 and 2008, when this is adjusted for inflation it can see that the real GDP dropped at least once in every decade except the 1960s and 2010s. The Great Recession Apart from the Great Depression, and immediately after WWII, there have been two times where both GDP and real GDP dropped together. The first was during the Great Recession, which lasted from December 2007 until June 2009 in the US, although its impact was felt for years after this. After the collapse of the financial sector in the US, the government famously bailed out some of the country's largest banking and lending institutions. Since recovery began in late 2009, US GDP has grown year-on-year, and reached 21.4 trillion dollars in 2019. The coronavirus pandemic and the associated lockdowns then saw GDP fall again, for the first time in a decade. As economic recovery from the pandemic has been compounded by supply chain issues, inflation, and rising global geopolitical instability, it remains to be seen what the future holds for the U.S. economy.

Here is a concise and professional Zenodo dataset description based on your paper, suitable for use as the metadata summary:

Title:
Uncertainty Is Not What It Used to Be: EPU and the Collapse of Classical Risk Logic

Description:
This dataset accompanies the study "Regime-Contingent Uncertainty Pricing: Strategic Risk, Liquidity, and Political Shocks," which develops a theory of regime-dependent pricing of economic policy uncertainty (EPU) in U.S. equity markets. Using monthly data from 2009 to 2025, the analysis identifies nonlinear shifts in the EPU-return relationship during two major political-economic shocks: the COVID-19 pandemic and the 2025 U.S.–China Trade War. The study demonstrates that EPU effects on asset prices are not time-invariant but depend on macro-regime context, investor behavior, and liquidity conditions.

The repository includes:

• Monthly return data for SPDR S&P 500 ETF (SPY)

• U.S. Economic Policy Uncertainty Index (EPU) data

• Python scripts for data processing, OLS estimation, and Markov-switching modeling

• Figures and tables illustrating regime dynamics

• A complete README with replication instructions

Key Contributions:

• Demonstrates that financial market responses to EPU invert during structural crises (e.g., COVID-19) and revert during politically driven uncertainty (e.g., Trade War)

• Advances dynamic capabilities and institutional theory by modeling uncertainty sensitivity as regime-contingent

• Introduces the concept of "reactivated uncertainty sensitivity," emphasizing the return of classical risk pricing under renewed political stress

Keywords:
Economic Policy Uncertainty (EPU), regime switching, COVID-19, U.S.–China Trade War, Markov switching model, strategic foresight, uncertainty pricing, institutional theory

License:
CC BY 4.0 – Openly available for reuse and replication

Variable Recurring Payments for SMBs Market Outlook

According to our latest research, the Global Variable Recurring Payments for SMBs market size was valued at $2.1 billion in 2024 and is projected to reach $8.7 billion by 2033, expanding at a robust CAGR of 16.8% during the forecast period of 2025 to 2033. The primary growth driver for this market is the digital transformation sweeping across small and medium-sized businesses (SMBs), which increasingly require flexible, automated payment solutions to streamline operations and enhance customer experience. As SMBs embrace digitalization, the demand for variable recurring payments—which allow for dynamic, usage-based billing and seamless payment collection—has surged, enabling businesses to offer more personalized services and improve cash flow management.

Regional Outlook

North America currently dominates the Variable Recurring Payments for SMBs market, accounting for the largest share, with an estimated market value exceeding $900 million in 2024. This region’s leadership is underpinned by a mature financial technology ecosystem, widespread adoption of digital payment infrastructures, and favorable regulatory frameworks that encourage innovation. The United States, in particular, boasts a high concentration of SMBs with advanced digital capabilities, driving demand for sophisticated payment solutions. Moreover, the presence of leading fintech companies and continuous investment in payment automation technologies further reinforce North America’s dominant position in the global market.

The Asia Pacific region is projected to be the fastest-growing market for variable recurring payments for SMBs, with a forecasted CAGR of over 20% from 2025 to 2033. Rapid economic development, burgeoning e-commerce sectors, and widespread smartphone penetration are fueling the adoption of digital payment solutions across countries like China, India, and Southeast Asian nations. Government initiatives aimed at promoting cashless transactions and financial inclusion, coupled with increased venture capital investment in fintech startups, are accelerating market growth. The region’s dynamic business environment and growing SMB sector create fertile ground for innovative payment solutions tailored to local needs.

Emerging economies in Latin America, the Middle East, and Africa are witnessing steady adoption of variable recurring payments, though growth is tempered by infrastructural constraints and regulatory complexities. In these regions, SMBs often face challenges such as limited access to advanced banking services, fragmented payment ecosystems, and varying levels of digital literacy. However, localized demand for flexible payment solutions is rising, particularly in urban centers and among tech-savvy entrepreneurs. Policy reforms aimed at modernizing financial systems and increasing digital penetration are gradually reducing barriers, presenting new opportunities for market entrants and established players alike.

Report Scope

Driving Loafer Market Outlook

According to our latest research, the Global Driving Loafer market size was valued at $2.1 billion in 2024 and is projected to reach $3.8 billion by 2033, expanding at a CAGR of 6.7% during 2024–2033. The driving loafer market is experiencing robust growth worldwide, propelled by a rising consumer preference for stylish yet comfortable footwear that seamlessly blends formal and casual aesthetics. The increasing demand for versatile shoes suitable for both professional environments and leisure activities is a major factor fueling the expansion of this market. The trend toward premiumization, coupled with the growing influence of fashion-conscious consumers, is further accelerating the adoption of driving loafers globally.

Regional Outlook

North America holds the largest share of the global driving loafer market, accounting for nearly 32% of total revenue in 2024. This dominance is attributed to a mature footwear market, high disposable income, and a strong inclination toward luxury and designer brands. The region benefits from well-established distribution channels, including both brick-and-mortar specialty stores and rapidly growing online platforms. Additionally, fashion-forward consumers in the United States and Canada are particularly receptive to innovative designs and premium materials, such as Italian leather and suede. The presence of leading global brands and aggressive marketing strategies also contribute to North America’s leading position in the driving loafer market.

Asia Pacific is poised to be the fastest-growing region in the driving loafer market, with a projected CAGR of 8.2% from 2024 to 2033. This rapid expansion is driven by increasing urbanization, rising middle-class incomes, and a growing appetite for Western fashion trends among younger consumers. Countries like China, India, and Japan are witnessing a surge in demand for both premium and mid-range driving loafers, as international brands expand their retail footprints and local manufacturers innovate with affordable alternatives. Significant investments in e-commerce infrastructure and digital marketing are further boosting sales, making Asia Pacific a focal point for market players seeking high growth potential.

Emerging economies in Latin America and the Middle East & Africa are gradually embracing the driving loafer trend, albeit at a slower pace due to economic constraints and varying consumer preferences. In these regions, adoption is often hindered by limited brand presence, higher import duties, and relatively lower purchasing power. However, localized demand is growing, especially among urban professionals and expatriate communities. Governments’ efforts to modernize retail sectors and improve trade policies are expected to create new opportunities, although market penetration will depend on strategic pricing and targeted marketing to address unique cultural and lifestyle factors.

Report Scope

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Fall River: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 7(1.13%) households where the householder is under 25 years old, 265(42.81%) households with a householder aged between 25 and 44 years, 245(39.58%) households with a householder aged between 45 and 64 years, and 102(16.48%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the village of Fall River, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• 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
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Fall River median household income by age. You can refer the same here

Throughout the 1920s, prices on the U.S. stock exchange rose exponentially, however, by the end of the decade, uncontrolled growth and a stock market propped up by speculation and borrowed money proved unsustainable, resulting in the Wall Street Crash of October 1929. This set a chain of events in motion that led to economic collapse - banks demanded repayment of debts, the property market crashed, and people stopped spending as unemployment rose. Within a year the country was in the midst of an economic depression, and the economy continued on a downward trend until late-1932.

It was during this time where Franklin D. Roosevelt (FDR) was elected president, and he assumed office in March 1933 - through a series of economic reforms and New Deal policies, the economy began to recover. Stock prices fluctuated at more sustainable levels over the next decades, and developments were in line with overall economic development, rather than the uncontrolled growth seen in the 1920s. Overall, it took over 25 years for the Dow Jones value to reach its pre-Crash peak.