The statistic shows the percent change in U.S. manufacturing employment during recession periods from 1945 to 2009. During the recession from July 1990 to March 1991, employment in the manufacturing sector decreased by 3.2 percent.

The Industrial Production Index (IPI) fell sharply in the United States during the Great Recession, reaching its lowest point in June 2009. The recession was triggered by the collapse of the U.S. housing market and the subsequent financial crisis in 2007 and 2008, during which a number of systemically critical financial institutions failed or came close to bankruptcy. The crisis in the financial sector quickly spread to the non-financial economy, where firms were adversely hit by the tightening of credit conditions and the drop in consumer confidence caused by the crisis. The largest monthly drop in the IPI came in September 2008, as Lehman Brothers collapsed and the U.S. government was forced to step in to backstop the financial sector. Industrial production would begin to recover in the Summer of 2009, but remained far below its pre-crisis levels.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to May 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Germany's factory activity slump signals possible winter recession, highlighting manufacturing challenges and economic concerns.

In a V-shpaed recession, it is projected that European manufacturing companies will have a positive EBIT margin of four percent, already a significant decline from the pre-pandemic EBIT margin of seven percent. The V-shaped recession is the least severe type of recession. Different types of hypothetical economic scenarios paint a mixed picture of the effects of the COVID-19 pandemic on earnings produced by European manufacturing companies. Depending on the severity of the recession, the amount of profit a company would generate differs. A U-shaped recession would result in an EBIT margin contraction of two percent, while the most severe type of recession, the L-shaped recession, would result in an EBIT margin slump of 19 percent. Thus, in the last two scenarios, companies would face significant losses in profit compared to the pre-pandemic status.

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.

Explore the surprising 1% decline in German industrial production in October, signaling ongoing struggles and potential recession in Europe's largest economy.

Graph and download economic data for Nonfarm Private Manufacturing Payroll Employment (DISCONTINUED) (NPPMNF) from Apr 2002 to May 2022 about payrolls, nonfarm, private, manufacturing, employment, and USA.

View an estimate of the probability of recession based on employment, industrial production, real personal income, and real manufacturing and trade sales.

Dallas Fed Manufacturing Index in the United States increased to -15.30 points in May from -35.80 points in April of 2025. This dataset provides the latest reported value for - United States Dallas Fed Manufacturing Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Alberta’s manufacturing sector is currently in recession as a result of the dramatic drop in crude oil prices. Lower oil prices have translated into much lower selling prices of refinery products and are causing oil and gas companies to drastically lower their capital spending which translates into reduced demand for machinery and equipment produced by Alberta’s manufacturing and fabricated metals sectors.

From the 1920s until the Second World War, industrial output in the major economies of the Americas fluctuated greatly. Using manufacturing output in 1938 as a benchmark, the U.S. had fairly consistent output throughout the 1920s, before there was a significant drop after the Wall Street Crash in 1929 - by 1932, output fell to around two thirds of its 1929 level, and it would take another five years to recover thereafter. After the Recession of 1937-38, manufacturing output then doubled by the early-1940s, as the U.S. ramped up armament before it joined the Second World War. Output in 1943 was almost three times higher than it had been in 1938.

Canada's industrial output followed a similar trend to that of the U.S., whereas Mexico saw comparatively little change across the given period. Similar to Mexico, Brazil's manufacturing output was not drastically affected by the Great Depression, although Brazil saw the largest relative growth over the given period, with output in 1944 over five times higher than it had been in the mid-1920s - it should be noted, however, that both Latin American countries' manufacturing industries were at a much lower stage of development than the North American industries during this time.

Interview transcripts with a sample of advanced manufacturing firms(aerospace, electrical, pharmaceutical and automotive sectors), and related policy and business organisations, in the East Midlands, North West and Central Belt of Scotland. The results of a firm questionnaire survey with advanced manufacturing firms (aerospace, electrical, pharmaceutical and automotive sectors) in British manufacturing areas.

The recession from 2008, and the persistent sectoral and spatial imbalances in the recovery, have provoked political calls to 'rebalance' the economy. According to Government representatives, Britain needs to 'reindustrialise', to rediscover its talent for manufacturing. Strengthening manufacturing in the Midlands and North will aid economic stability, raise productivity, and promote a more even distribution of growth. It has been argued that traditional industrial regions should develop new types of high-technology, 'advanced' manufacturing activities.

Such calls for rebalancing have triggered a major debate on whether the British economy can in any way 're-industrialise'. Optimists point to resurgent clusters of manufacturing industries. Others are sceptical and argue that British manufacturing has been undermined by the 2008 recession, long-term weaknesses and an unsupportive institutional context. In this view, supply chains in British manufacturing are now too thin, fragmented and sparse to support industrial renewal on the scale required. There is evidence to show uneven regional trends in manufacturing, especially between the North and South of Britain and, according to some, advanced manufacturing is growing at a much faster rate in Southern England due to its research intensity and proximity to high-technology institutions. There is a pressing need to know how, and how far, industrial regions in Britain are developing advanced manufacturing.

Relatively little is known about any potential regional manufacturing renaissance and the significance of location. There are several hypotheses. Some argue that advanced manufacturing develops best in specialised clusters and in local 'ecosystems' in which firms benefit from shared capabilities, resources, spill-overs and intermediaries. Others emphasise broader-scale external economies across sectors, so that location in cities and regions with a wide range of growing industries is more important to manufacturing performance. There is also debate about the degree to which location in traditional industrial regions aids or hinders advanced manufacturing. In a 'phoenix industry' view, manufacturing can be revived in traditional industrial regions by networks of small firms and by the diversification and branching of new sectors. This project tackles these questions. It places the performance of advanced manufacturing firms in the context of changes in supply chains and examines whether there is increasing specialisation of regions and locations in particular tasks, roles and functions rather than in entire industries.

This project will examine the geographical, organisational and economic dynamics of four key manufacturing industries: electrical, computing and optical equipment; aerospace; pharmaceuticals; and motor vehicles. The project would proceed in three connected stages. The first stage would be to use and combine existing micro-data sources to examine the central issues on the relationships between manufacturing performance and location and investigate the key determinants of firm growth, performance and innovation in these industries. The project will use and combine several data-sets to provide a detailed analysis of change since the early 1970s. The second stage of the project will carry out a postal and online survey of firms in the four industries. This will explore the relationships between location and firm performance in more depth. For each industry, the survey aims to compare a set of firms within traditional industrial regions (in the North, Wales, Scotland or Midlands) with a similar group of firms in Southern regions. The final stage of the project will focus on manufacturers in these industries in four Midlands/Northern regions (selecting one region where each industry is well represented). In these areas, it will use firm interviews and focus groups to discuss findings, and identify and sound out key policy lessons and implications

Graph and download economic data for All Employees: Manufacturing: Durable Goods: Motor Vehicle Manufacturing in Michigan (SMU26000003133610001) from Jan 1990 to Apr 2025 about MI, vehicles, durable goods, goods, manufacturing, employment, and USA.

The Global Footwear Manufacturing industry has seen a downturn in recent years because of various global challenges. Amid mounting geopolitical tension, unpredictable economic climates, and shifting consumer trends, the industry has experienced a turbulent journey. One influential factor has been the increasing instability in the global price of crude oil - a vital component in rubber production, which is the primary material for footwear. Also, concerns of recession and inflation pressures in 2022 and 2023 had put a strain on industry performance, despite robust spending rebounds in some regions. Industry revenue has declined at a CAGR of 1.9% over the past five years and is expected to total $235.8 billion in 2024, when revenue will hike by an estimated 1.5%. Over the past five years, the Global Footwear Manufacturing industry has benefited from the rise in e-commerce platforms, making choices more accessible to a larger consumer base. Another trend noticed during this period is an increased demand for sustainable and ethically produced footwear. Key market players like Adidas and Nike led by example, introducing innovative products made from recyclable and environmentally friendly materials. Moreover, western countries' demand for luxury footwear also rose during this time, driven by an expansion in disposable income and the cultural trend of following celebrity fashion. The global footwear market is poised for robust growth in the foreseeable future, albeit punctuated by challenges like escalating production costs and intensifying competition from direct-to-consumer brands. Despite these probable headwinds, niche markets like sustainable footwear, driven by consumer demand for environmentally friendly and ethically sourced products, could potentially unlock new opportunities. Moreover, breakthroughs in technology can usher in more streamlined production methods and enhance supply chain efficiencies. Revenue is expected to inch downwards at a CAGR of 2.3% over the five years through 2029 to $263.6 billion.

Electronic article surveillance (EAS) manufacturers have experienced negative long-term headwinds. Over the past several years, consumers have increasingly favored online retailers, driven by greater productivity, technological advances and the rise of e-commerce giants like Amazon. This has weakened demand for EAS products, as online retailers don’t face shoplifting concerns. Resultingly, this has induced declines in revenue and profit over the past five years. More recently, economic shifts have bolstered revenue volatility among providers. The pandemic triggered sharp revenue drops due to constrained consumer spending, while the subsequent recovery briefly stabilized demand as retailers increased their investment in EAS products. However, rising interest rates curbed spending, further depressing revenue in 2023 and 2024. Meanwhile, falling crime rates have slowed demand for EAS systems. While revenue growth overall has slowed, exports of EAS products have remained solid, especially to developing countries. Imports have also risen, especially from Malaysia, as China's market share fell amid trade tensions, pushing up competition for US manufacturers. Overall, revenue for EAS manufacturers has plunged at a CAGR of 3.0% over the past five years, reaching $650.7 million in 2025. This includes a 1.5% decline in that year. From 2025 to 2030, demand for EAS products will grow slowly instead of weakening as online shopping saturates and e-commerce expansion decelerates. This will constrain the popularity of online retailers, giving providers a lifeline. Long-term economic growth is set to boost consumer spending, providing a useful revenue stream for the industry. Despite this, the US faces significant economic uncertainty, especially after new tariffs have been imposed by the Trump administration, raising the risk of recession and potentially suppressing economic growth and, therefore, revenue growth for the EAS manufacturers. Technological innovations—such as RFID and AI—will benefit larger providers but could replace traditional EAS products, threatening demand. Consumer focus on sustainability will drive investment in eco-friendly, recyclable EAS solutions, benefiting providers that prioritize green practices in a challenging market. Overall, revenue for EAS product makers is forecast to inch upward at a CAGR of 0.1% over the next five years, reaching $654.6 million in 2030.

As of June 2022, 43 percent of electronics manufacturers were extremely worried about inflation. Moreover, 47 percent of them were somewhat worried about the downturn in Chinese production due to COVID lockdowns, while 46 percent about the Russia-Ukraine war. Finally, 52 percent of manufacturers were somewhat worried about economic recession in 2023.

Semiconductor machinery manufacturers supply capital equipment for various processes in semiconductor manufacturing. While semiconductors have become the foundation of nearly every technology today, years of outsourcing semiconductor manufacturing put Canada in a weak position globally. Rising import penetration has been specifically challenging to the domestic industry. East Asian countries dominate semiconductor production, where enormous scale, massive R&D investment and lower-cost labour make it near impossible for domestic manufacturers to compete.But, an explosion in semiconductor demand during the COVID-19 pandemic led to supply shocks, boosting machinery purchases from domestic and foreign manufacturers expanding production volume. High interest rates and concerns about how consumers will respond to a recession are curtailing equipment sales – and profit – in 2023. In all, industry-wide revenue has been declining at a CAGR of 33.3% to total an estimated $145.0 million in 2023, when revenue will jump an expected 1.9%.The pandemic's havoc on the semiconductor supply chain showcased its weaknesses. To lower its dependence on foreign suppliers, the Canadian government announced a $240.0 million investment into bolstering domestic production in 2022. Investment in domestic semiconductor production leaves equipment manufacturers well-positioned, as manufacturers can't create semiconductors without equipment. Developing Canada's semiconductor industry can't come without cooperation with the US– leading the countries to partner in establishing a bilateral semiconductor manufacturing corridor.Semiconductors will remain the backbone of tech transformation, but the industry's trajectory will depend on if the Canadian economy enters a downturn. Prolonged high interest rates and a recession would cause consumers to rethink spending and industrial capacity to slow. In a downturn, semiconductor manufacturers don't invest in new production lines or fabrication facilities, dropping new equipment sales. Still, tech advances will push semiconductor development ahead, specifically benefiting equipment manufacturers specializing in advanced machines for components in areas like AI or electric vehicles. Semiconductor equipment manufacturing revenue is expected to increase at a CAGR of 1.5% to $156.0 million over the next five years.

Between 1914 and 1969, weekly wages in manufacturing industries in the United States grew by a factor of 12. In the first half of the century, the most significant periods of increase came during the World Wars, as manufacturing industries were at the core of the war effort. However, wages then fell sharply after both World Wars, due to post-war recessions and oversaturation of the job market as soldiers returned home. Interwar period Wage growth during the interwar period was often stagnant, despite the significant economic growth during the Roarin' 20s, and manufacturing wages remained steady at around 24 dollars from 1923 to 1929. This was, again, due to oversaturation of the job market, as employment in the agricultural sector declined due to mechanization and many rural workers flocked to industrial cities in search of employment. The Great Depression then saw the largest and most prolonged period of decline in manufacturing wages. From September 1929 to March 1933, weekly wages fell from 24 dollars to below 15 dollars, and it would take another four years for them to return to pre-Depression levels. Postwar prosperity After the 1945 Recession, the decades that followed the Second World War then saw consistent growth in manufacturing wages in almost every year, as the U.S. cemented itself as the foremost economic power in the world. This period is sometimes referred to as the Golden Age of Capitalism, and the U.S. strengthened its economic presence in Western Europe and other OECD countries, while expanding its political and military presence across Asia. Manufacturing and exports played a major role in the U.S.' economic growth in this period, and wages grew from roughly 40 dollars per week in 1945 to more than 120 dollars by the late 1960s.

This paper develops non-linear smooth transition autoregressive (STAR) models with two additive smooth transition components to capture the business cycle characteristics of UK real consumers' expenditure and industrial production. The results indicate consumption has essentially two business cycle regimes: recession and expansion. Industrial production, however, is characterized by the three regimes of recession, normal growth and high growth. The transitions describing recovery from recession are very similar for the two variables. Stochastic simulations illustrate the dynamic responses of these models and emphasize that they are locally linear. Our results also indicate that the two-transition STAR models have some forecast advantages over other specifications for periods of contraction.