45 datasets found
  1. Total imports, total exports, and trade balance of the U.S. 1790-1970

    • statista.com
    Updated Apr 10, 2025
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    Statista Research Department (2025). Total imports, total exports, and trade balance of the U.S. 1790-1970 [Dataset]. https://www.statista.com/topics/9494/the-great-depression-us/
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    During the 19th century, the United States generally had a negative trade balance, importing more than it exported, particularly from the British Empire. This changed at the turn of the 20th century, and the U.S. consistently had a positive trade balance between 1896 and 1970. The greatest periods of fluctuation came during the world wars, as well as an observable decline following the Wall Street Crash of 1929.

    While inflation rates increased the total value of imports and exports over time, the rate of growth did increase significantly from 1900 onwards. The early 20th century saw the U.S. move away from its traditional isolationist policies (apart from a brief period during the great Depression) and emerge as a global superpower. Following the Second World War, the U.S. used its economic power to maintain its influence across the globe, as it sought to suppress the expansion of communism.

  2. Dow Jones: average and yearly closing prices 1915-2021

    • statista.com
    Updated Apr 10, 2025
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    Aaron O'Neill (2025). Dow Jones: average and yearly closing prices 1915-2021 [Dataset]. https://www.statista.com/topics/9494/the-great-depression-us/
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Aaron O'Neill
    Description

    The Dow Jones Industrial Average is (DJIA) is possibly the most well-known and commonly used stock index in the United States. It is a price-weighted index that assesses the stock prices of 30 prominent companies, whose combined prices are then divided by a regularly-updated divisor (0.15199 in February 2021), which gives the index value. The companies included are rotated in and out on a regular basis; as of mid-2022, the longest mainstay on the list is Procter & Gamble, which was added in 1932; whereas Amgen, Salesforce, and Honeywell were all added in 2020. As one of the oldest indices for stock market analysis, the impact of major events, recessions, and economic shocks or booms can be tracked and contextualized over longer periods of time.

    Due to inflation, unadjusted figures appear to be more sporadic in recent years, however the greatest fluctuations came in the earliest years of the index. In the given period, the greatest decline came in the wake of the Wall Street Crash in 1929; by 1932 average values had fallen to just one fifth of their 1929 average, from roughly 314 to 65.

  3. Annual GDP and real GDP for the United States 1929-2022

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). Annual GDP and real GDP for the United States 1929-2022 [Dataset]. https://www.statista.com/statistics/1031678/gdp-and-real-gdp-united-states-1930-2019/
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    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  4. o

    Replication data for: Understanding the Great Recession

    • openicpsr.org
    Updated Jan 1, 2015
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    Lawrence J. Christiano; Martin S. Eichenbaum; Mathias Trabandt (2015). Replication data for: Understanding the Great Recession [Dataset]. http://doi.org/10.3886/E114095V1
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    Dataset updated
    Jan 1, 2015
    Dataset provided by
    American Economic Association
    Authors
    Lawrence J. Christiano; Martin S. Eichenbaum; Mathias Trabandt
    Description

    We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions. We reach this conclusion by looking through the lens of an estimated New Keynesian model in which firms face moderate degrees of price rigidities, no nominal rigidities in wages, and a binding zero lower bound constraint on the nominal interest rate. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small drop in inflation that occurred during the Great Recession. (JEL E12, E23, E24, E31, E32, E52)

  5. Volcker Shock: federal funds, unemployment and inflation rates 1979-1987

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Volcker Shock: federal funds, unemployment and inflation rates 1979-1987 [Dataset]. https://www.statista.com/statistics/1338105/volcker-shock-interest-rates-unemployment-inflation/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1979 - 1987
    Area covered
    United States
    Description

    The Volcker Shock was a period of historically high interest rates precipitated by Federal Reserve Chairperson Paul Volcker's decision to raise the central bank's key interest rate, the Fed funds effective rate, during the first three years of his term. Volcker was appointed chairperson of the Fed in August 1979 by President Jimmy Carter, as replacement for William Miller, who Carter had made his treasury secretary. Volcker was one of the most hawkish (supportive of tighter monetary policy to stem inflation) members of the Federal Reserve's committee, and quickly set about changing the course of monetary policy in the U.S. in order to quell inflation. The Volcker Shock is remembered for bringing an end to over a decade of high inflation in the United States, prompting a deep recession and high unemployment, and for spurring on debt defaults among developing countries in Latin America who had borrowed in U.S. dollars.

    Monetary tightening and the recessions of the early '80s

    Beginning in October 1979, Volcker's Fed tightened monetary policy by raising interest rates. This decision had the effect of depressing demand and slowing down the U.S. economy, as credit became more expensive for households and businesses. The Fed funds rate, the key overnight rate at which banks lend their excess reserves to each other, rose as high as 17.6 percent in early 1980. The rate was allowed to fall back below 10 percent following this first peak, however, due to worries that inflation was not falling fast enough, a second cycle of monetary tightening was embarked upon starting in August of 1980. The rate would reach its all-time peak in June of 1981, at 19.1 percent. The second recession sparked by these hikes was far deeper than the 1980 recession, with unemployment peaking at 10.8 percent in December 1980, the highest level since The Great Depression. This recession would drive inflation to a low point during Volcker's terms of 2.5 percent in August 1983.

    The legacy of the Volcker Shock

    By the end of Volcker's terms as Fed Chair, inflation was at a manageable rate of around four percent, while unemployment had fallen under six percent, as the economy grew and business confidence returned. While supporters of Volcker's actions point to these numbers as proof of the efficacy of his actions, critics have claimed that there were less harmful ways that inflation could have been brought under control. The recessions of the early 1980s are cited as accelerating deindustrialization in the U.S., as manufacturing jobs lost in 'rust belt' states such as Michigan, Ohio, and Pennsylvania never returned during the years of recovery. The Volcker Shock was also a driving factor behind the Latin American debt crises of the 1980s, as governments in the region defaulted on debts which they had incurred in U.S. dollars. Debates about the validity of using interest rate hikes to get inflation under control have recently re-emerged due to the inflationary pressures facing the U.S. following the Coronavirus pandemic and the Federal Reserve's subsequent decision to embark on a course of monetary tightening.

  6. g

    Inflation Expectations and Recovery in Spring of 1933

    • datasearch.gesis.org
    • openicpsr.org
    Updated Aug 27, 2016
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    Rua, Gisela; Jalil, Andrew (2016). Inflation Expectations and Recovery in Spring of 1933 [Dataset]. http://doi.org/10.3886/E76028V1
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    Dataset updated
    Aug 27, 2016
    Dataset provided by
    da|ra (Registration agency for social science and economic data)
    Authors
    Rua, Gisela; Jalil, Andrew
    Description

    This paper uses the historical narrative record to determine whether inflation expectations shifted during the second quarter of 1933, precisely as the recovery from the Great Depression took hold. First, by examining the historical news record and the forecasts of contemporary business analysts, we show that inflation expectations increased dramatically. Second, using an event-study approach, we identify the effect of the key events that shifted inflation expectations on financial markets. Third, we gather new evidence—both quantitative and narrative—that indicates that the shift in inflation expectations played a causal role in stimulating the recovery.

  7. o

    Replication data for: Inflation Persistence, the NAIRU, and the Great...

    • openicpsr.org
    Updated May 1, 2014
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    Mark W. Watson (2014). Replication data for: Inflation Persistence, the NAIRU, and the Great Recession [Dataset]. http://doi.org/10.3886/E112790V1
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    Dataset updated
    May 1, 2014
    Dataset provided by
    American Economic Association
    Authors
    Mark W. Watson
    Description

    The rate of inflation fell far less over the period 2007-2013 than in the period 1979-1985 despite similar large increases in the unemployment rate. This paper asks why. Possible explanations include a change in the persistence of inflation, changes in NAIRU, and other shocks. A change in the persistence of inflation, with inflation more anchored in the period 2007-2013 than in the period 1979-1985, is found to be important. The level and change in the NAIRU cannot be precisely estimated, but the data suggest an increase of nearly 1 percentage point since 2007.

  8. U

    Inflation Data

    • dataverse.unc.edu
    • dataverse-staging.rdmc.unc.edu
    Updated Oct 9, 2022
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    UNC Dataverse (2022). Inflation Data [Dataset]. http://doi.org/10.15139/S3/QA4MPU
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    Dataset updated
    Oct 9, 2022
    Dataset provided by
    UNC Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a demographic shift of an ageing population and significant technological automation. So if you think that stocks or equities or ETFs are the best place to put your money in 2022, you might want to think again. The crash of the OTC and small-cap market since February 2021 has been quite an indication of what a correction looks like. According to the Motley Fool what happens after major downturns in the market historically speaking? In each of the previous four instances that the S&P 500's Shiller P/E shot above and sustained 30, the index lost anywhere from 20% to 89% of its value. So what's what we too are due for, reversion to the mean will be realistically brutal after the Fed's hyper-extreme intervention has run its course. Of course what the Fed stimulus has really done is simply allowed the 1% to get a whole lot richer to the point of wealth inequality spiraling out of control in the decades ahead leading us likely to a dystopia in an unfair and unequal version of BigTech capitalism. This has also led to a trend of short squeeze to these tech stocks, as shown in recent years' data. Of course the Fed has to say that's its done all of these things for the people, employment numbers and the labor market. Women in the workplace have been set behind likely 15 years in social progress due to the pandemic and the Fed's response. While the 89% lost during the Great Depression would be virtually impossible today thanks to ongoing intervention from the Federal Reserve and Capitol Hill, a correction of 20% to 50% would be pretty fair and simply return the curve back to a normal trajectory as interest rates going back up eventually in the 2023 to 2025 period. It's very unlikely the market has taken Fed tapering into account (priced-in), since the euphoria of a can't miss market just keeps pushing the markets higher. But all good things must come to an end. Earlier this month, the U.S. Bureau of Labor Statistics released inflation data from July. This report showed that the Consumer Price Index for All Urban Consumers rose 5.2% over the past 12 months. While the Fed and economists promise us this inflation is temporary, others are not so certain. As you print so much money, the money you have is worth less and certain goods cost more. Wage gains in some industries cannot be taken back, they are permanent - in the service sector like restaurants, hospitality and travel that have been among the hardest hit. The pandemic has led to a paradigm shift in the future of work, and that too is not temporary. The Great Resignation means white collar jobs with be more WFM than ever before, with a new software revolution, different transport and energy behaviors and so forth. Climate change alone could slow down global GDP in the 21st century. How can inflation be temporary when so many trends don't appear to be temporary? Sure the price of lumber or used-cars could be temporary, but a global chip shortage is exasperating the automobile sector. The stock market isn't even behaving like it cares about anything other than the Fed, and its $billions of dollars of buying bonds each month. Some central banks will start to taper about December, 2021 (like the European). However Delta could further mutate into a variant that makes the first generation of vaccines less effective. Such a macro event could be enough to trigger the correction we've been speaking about. So stay safe, and keep your money safe. The Last Dance of the 2009 bull market could feel especially more painful because we've been spoiled for so long in the markets. We can barely remember what March, 2020 felt like. Some people sold their life savings simply due to scare tactics by the likes of Bill Ackman. His scare tactics on CNBC won him likely hundreds of millions as the stock market tanked. Hedge funds further gamed the Reddit and Gamestop movement, orchestrating them and leading the new retail investors into meme speculation and a whole bunch of other unsavory things like options trading at such scale we've never seen before. It's not just inflation and higher interest rates, it's how absurdly high valuations have become. Still correlation does not imply causation. Just because inflation has picked up, it doesn't guarantee that stocks will head lower. Nevertheless, weaker buying power associated with higher inflation can't be overlooked as a potential negative for the U.S. economy and equities. The current S&P500 10-year P/E Ratio is 38.7. This is 97% above the modern-era market average of 19.6, putting the current P/E 2.5 standard deviations above the modern-era average. This is just math, folks. History is saying the stock market is 2x its true value. So why and who would be full on the market or an asset class like crypto that is mostly speculative in nature to begin with? Study the following on a historical basis, and due your own due diligence as to the health of the markets: Debt-to-GDP ratio Call to put ratio

  9. g

    Arbeitslosigkeit und Inflation in der Bundesrepublik Deutschland, 1960 –...

    • search.gesis.org
    • da-ra.de
    Updated Apr 13, 2010
    + more versions
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    Kromphardt, Jürgen (2010). Arbeitslosigkeit und Inflation in der Bundesrepublik Deutschland, 1960 – 1997 [Dataset]. http://doi.org/10.4232/1.8199
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    (77899)Available download formats
    Dataset updated
    Apr 13, 2010
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    Kromphardt, Jürgen
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Time period covered
    1960 - 1997
    Area covered
    Germany
    Description

    The Question “Why unemployment?” is one of the most central topics of economic theory since the great depression. Unemployment remains one of the most important problems of economic policies in industrial countries. Unemployment has different causes and therefore also different countermeasures are required. “Together with the destruction of environment unemployment and inflation are in the focus of economic and political discussions on macroeconomic problems and are considered as the greatest challenges of economic policy. Depending on the level of unemployment there is a higher focus on inflation or on unemployment, if both are on an alarming level at the same time they are in the shot simultaneously. In anyway both issues need to be analyzed together because they are not independent from each other. Experiences from the recent years have shown that combating inflation leads to an increase in unemployment, at least temporarily but probably also permanently. The other way around; combating unemployment may under certain circumstances also lead to an increase in inflation… Unemployment and inflation are macroeconomic problems. The level of both undesirable developments is determined by the relations in the entire economy. Therefor it is necessary to use macroeconomic theory which deals the general economic context for the analysis. Both problems are enhanced by structural factors which also need to be analyzed. In contrast to microeconomic theory which focuses on different individual decision makers, in macroeconomic theory decision makers and decisions are summarized in macroeconomic aggregates. The common procedure is to summarize decision makers into aggregates like “private households”, “enterprises” and “the state” and the decision makers concerning the use of income into “private consumption”, “investments” and “public expenditure” (Kromphardt, Jürgen, 1998: Arbeitslosigkeit und Inflation (unemployment and inflation). 2., newly revised A. Göttingen: Vandenhoeck & Ruprecht, p. 17-18). Macroeconomic approaches on the explanation of unemployment and inflation are highly controversial in economic theory. Therefore the author starts with the attempt to present different explanations for unemployment and inflation from different macroeconomic positions. There are different unemployment: classical unemployment (reason: real wages to high), Keynesian unemployment (reason: demand for goods to low), unemployment due to a lack of working places (reason: capital stock to low). These positions give conflicting explanations and recommendations because they are based on different perceptions of the starting position. Therefor the author confronts central positions with empirical data on the macro level with the following restriction: “It is impossible to prove theories as correct (to verify). This is a reason for the fact that macroeconomic controversies do not come to a conclusion but are continued in a modified way. Furthermore economic statements in this field always affect social and political interests as all economic policies favor or put as a disadvantage interests of distinct social groups in a different way.“ (Kromphardt, a.a.O., S. 20).

    Data tables in HISTAT (1) Development of employment: Presented by the development of annual average unemployment rates and the balance of labor force of the institute for labor market and occupation research (IAB, Nuremberg) after the domestic concept(employment with Germany as the place of work) For characterizing the overall economic developments, those values are used which play an important role in the reports of the German central bank: (2) Inflation: Rate of differences in the price index for costs of living compared to the previous year (3) Currency reserves of German federal banks and the German central bank: measure for foreign economic situation and the payment balance of the central bank (4) Development of economic growth: Presented by the nominal and real growth rate of the GDP (5) Inflation rate of the GDP, money supply, growth rate of the price index of the GDP (6) Labor productivity (= GDP per employee, domestic concept) (7) Real wage per employee (8) Exchange rate: DM/$ (monthly averages) (9) Growth of DGP, productivity, economically active population, real incomes, unemployment rate and adjusted wages (10) Time series connected with labor demand (11) GDP, labor volume, employees, working hours and labor productivity (12) Employee compensation, wages and ...

  10. Global inflation rate from 2000 to 2030

    • statista.com
    • abripper.com
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    Statista, Global inflation rate from 2000 to 2030 [Dataset]. https://www.statista.com/statistics/256598/global-inflation-rate-compared-to-previous-year/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2025
    Area covered
    Worldwide
    Description

    Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

  11. i

    Inflation and the Nation: A Global Recession’s Potential Effects on the...

    • ibisworld.com
    Updated Oct 19, 2022
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    IBISWorld (2022). Inflation and the Nation: A Global Recession’s Potential Effects on the Australian Economy [Dataset]. https://www.ibisworld.com/blog/inflation-global-recession/61/1131/
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    Dataset updated
    Oct 19, 2022
    Dataset authored and provided by
    IBISWorld
    Time period covered
    Oct 19, 2022
    Area covered
    Australia
    Description

    IBISWorld examines the potentially significant effects of a global recession on domestic industries, businesses and consumers.

  12. k

    The Phillips Curve and the Missing Disinflation from the Great Recession

    • kansascityfed.org
    pdf
    Updated Oct 4, 2021
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    (2021). The Phillips Curve and the Missing Disinflation from the Great Recession [Dataset]. https://www.kansascityfed.org/research/economic-review/2q19-vanzandweghe-phillips-curve-missing-disinflation-great-recession/
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    pdfAvailable download formats
    Dataset updated
    Oct 4, 2021
    Description

    Expectations shaped by monetary policy kept inflation stable during the Great Recession despite disinflationary pressure from high unemployment.

  13. F

    Real-time Sahm Rule Recession Indicator

    • fred.stlouisfed.org
    json
    Updated Sep 5, 2025
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    (2025). Real-time Sahm Rule Recession Indicator [Dataset]. https://fred.stlouisfed.org/series/SAHMREALTIME
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    jsonAvailable download formats
    Dataset updated
    Sep 5, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Real-time Sahm Rule Recession Indicator (SAHMREALTIME) from Dec 1959 to Aug 2025 about recession indicators, academic data, and USA.

  14. m

    Tradedynamics

    • data.mendeley.com
    Updated Aug 7, 2025
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    Somayeh Mardaneh (2025). Tradedynamics [Dataset]. http://doi.org/10.17632/k38c8f8c75.1
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    Dataset updated
    Aug 7, 2025
    Authors
    Somayeh Mardaneh
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is to replicate the results reported in the paper "Trade Dynamics in the Middle East: A GAMLSS Analysis of Economic and Conflict Variables". Data and information are gathered for 17 countries in the Middle East, namely Bahrain, Cyprus, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, Turkey, the United Arab Emirates, Yemen, and Palestine (in alphabetical order).
    World Bank Open Data, Metadata from the World Bank Group, and OECD National Accounts data files serve as the primary sources of the data. International trade policy changes in response to the recent global crisis during the COVID-19 pandemic. The definition of the variables is as follows:
    Trade share (trade_shr): Trade (% of GDP); Trade is the sum of exports and imports of goods and services measured as a share of gross domestic product. GDP Growth (GDP_gr): GDP growth (annual %); annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for the depreciation of fabricated assets or for the depletion and degradation of natural resource. Inflation (infl): Inflation, consumer prices (annual %); the consumer price index measures inflation and reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used. Dummy Variable for War (D1_War): The years in which countries are involved in war took the value of 1, and other years took the value of 0. Dummy Variable for Domestic Conflicts (D2_DC): The years in which countries are involved in domestic conflicts took the value of 1, and other years took the value of 0. Dummy Variable for Global Crisis (D3_GC): The years in which countries faced a global crisis took the value of 1, and other years took the value of 0. The global crises in this paper are as follows:
    Great Depression (1929-1939) 1973-1974 Oil Price Shock 1979-1980 Oil Crisis Global Financial Crisis (2007-2008) Eurozone Crisis (2010-2014) COVID-19 Pandemic (2020-2022)

  15. o

    Data and Code for: State Dependent Government Spending Multipliers: Downward...

    • openicpsr.org
    delimited
    Updated Jan 15, 2024
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    Yoon Joo Jo; Sarah Zubairy (2024). Data and Code for: State Dependent Government Spending Multipliers: Downward Nominal Wage Rigidity and Sources of Business Cycle Fluctuations [Dataset]. http://doi.org/10.3886/E197641V1
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    delimitedAvailable download formats
    Dataset updated
    Jan 15, 2024
    Dataset provided by
    American Economic Association
    Authors
    Yoon Joo Jo; Sarah Zubairy
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1963 - Dec 2019
    Area covered
    US States, United States
    Description

    In a New Keynesian model with downward nominal wage rigidity (DNWR), we show that government spending is more effective in stimulating output in a low-inflation recession relative to a high-inflation recession. The government spending multiplier is large when DNWR binds, but the nature of recession matters due to the opposing response of inflation, and consequently for real wages. Using U.S. historical time series data, we provide evidence of larger spending multipliers in low inflation recessions and the importance of the depth of recessions. We also employ cross-sectional data from U.S. states to document supporting evidence on multipliers and our proposed mechanism.

  16. Annual GDP growth for the United States 1930-2022

    • statista.com
    Updated Apr 14, 2021
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    Statista (2021). Annual GDP growth for the United States 1930-2022 [Dataset]. https://www.statista.com/statistics/996758/rea-gdp-growth-united-states-1930-2019/
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    Dataset updated
    Apr 14, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The Covid-19 pandemic saw growth fall by 2.2 percent, compared with an increase of 2.5 percent the year before. The last time the real GDP growth rates fell by a similar level was during the Great Recession in 2009, and the only other time since the Second World War where real GDP fell by more than one percent was in the early 1980s recession. The given records began following the Wall Street Crash in 1929, and GDP growth fluctuated greatly between the Great Depression and the 1950s, before growth became more consistent.

  17. Total employment figures and unemployment rate in the United States...

    • statista.com
    Updated Sep 12, 2025
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    Statista (2025). Total employment figures and unemployment rate in the United States 1980-2025 [Dataset]. https://www.statista.com/statistics/269959/employment-in-the-united-states/
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    Dataset updated
    Sep 12, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

  18. o

    The Intermittent Phillips Curve: Finding a Stable (But Persistence-...

    • openicpsr.org
    Updated Aug 26, 2024
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    Richard Ashley; Randal Verbrugge (2024). The Intermittent Phillips Curve: Finding a Stable (But Persistence- Dependent) Phillips Curve Model Specification [Dataset]. http://doi.org/10.3886/E208705V1
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    Dataset updated
    Aug 26, 2024
    Dataset provided by
    Federal Reserve Bank of Cleveland
    Virginia Tech
    Authors
    Richard Ashley; Randal Verbrugge
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We make substantial progress on understanding the Phillips curve, yielding important monetarypolicy implications. Inflation responds differently to persistent versus moderately persistent (ortransient) fluctuations in the unemployment gap. This persistence-dependent relationship alignswith business-cycle stages, and is consistent with existing theory. Previous work fails to modelthis dependence, thereby finding the numerous “inflation puzzles” – e.g., missinginflation/disinflation – noted in the literature. Our specification eliminates these puzzles; e.g., thePhillips curve has not weakened; inflation’s post-2012 slow upward trudge was predictable. Themodel’s coefficients are stable, and it provides accurate out-of-sample conditional recursiveforecasts through the Great Recession and recovery.Keywords: overheating; recession gap; frequency dependence; NAIRU; Phillips curve.

  19. g

    Oil and the United States Macroeconomy: An Update and a Simple Forecasting...

    • search.gesis.org
    Updated Jul 14, 2021
    + more versions
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    Kliesen, Kevin L. (2021). Oil and the United States Macroeconomy: An Update and a Simple Forecasting Exercise - Archival Version [Dataset]. http://doi.org/10.3886/ICPSR23220
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    Dataset updated
    Jul 14, 2021
    Dataset provided by
    GESIS search
    ICPSR - Interuniversity Consortium for Political and Social Research
    Authors
    Kliesen, Kevin L.
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de447631https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de447631

    Area covered
    United States
    Description

    Abstract (en): Some analysts and economists recently warned that the United States economy faces a much higher risk of recession should the price of oil rise to $100 per barrel or more. In February 2008, spot crude oil prices closed above $100 per barrel for the first time ever, and since then they have climbed even higher. Meanwhile, according to some surveys of economists, it is highly probable that a recession began in the United States in late 2007 or early 2008. Although the findings in this paper are consistent with the view that the United States economy has become much less sensitive to large changes in oil prices, a simple forecasting exercise using Hamilton's model augmented with the first principal component of 85 macroeconomic variables reveals that a permanent increase in the price of crude oil to $150 per barrel by the end of 2008 could have a significant negative effect on the growth rate of real gross domestic product in the short run. Moreover, the model also predicts that such an increase in oil prices would produce much higher overall and core inflation rates in 2009 than most policymakers expect. A zipped package contains a programming syntax file (text format) and a Microsoft Excel file, which contains the data, tables, and corresponding figures used in the article.These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigators if further information is desired.

  20. Consumer Price Index 2022 - West Bank and Gaza

    • pcbs.gov.ps
    Updated May 18, 2023
    + more versions
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    Palestinian Central Bureau of Statistics (2023). Consumer Price Index 2022 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/717
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    Dataset updated
    May 18, 2023
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttps://pcbs.gov/
    Time period covered
    2022
    Area covered
    Gaza Strip, West Bank, Gaza
    Description

    Abstract

    The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

    Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

    Geographic coverage

    Palestine West Bank Gaza Strip Jerusalem

    Analysis unit

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Universe

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

    Sampling deviation

    Not apply

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

    In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

    Cleaning operations

    The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

    At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

    Response rate

    Not apply

    Sampling error estimates

    The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

    Data appraisal

    Other technical procedures to improve data quality: Seasonal adjustment processes and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

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Statista Research Department (2025). Total imports, total exports, and trade balance of the U.S. 1790-1970 [Dataset]. https://www.statista.com/topics/9494/the-great-depression-us/
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Total imports, total exports, and trade balance of the U.S. 1790-1970

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Dataset updated
Apr 10, 2025
Dataset provided by
Statistahttp://statista.com/
Authors
Statista Research Department
Area covered
United States
Description

During the 19th century, the United States generally had a negative trade balance, importing more than it exported, particularly from the British Empire. This changed at the turn of the 20th century, and the U.S. consistently had a positive trade balance between 1896 and 1970. The greatest periods of fluctuation came during the world wars, as well as an observable decline following the Wall Street Crash of 1929.

While inflation rates increased the total value of imports and exports over time, the rate of growth did increase significantly from 1900 onwards. The early 20th century saw the U.S. move away from its traditional isolationist policies (apart from a brief period during the great Depression) and emerge as a global superpower. Following the Second World War, the U.S. used its economic power to maintain its influence across the globe, as it sought to suppress the expansion of communism.

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