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.

Abstract (en): This collection, A Longitudinal Study of Public Response, was conducted to understand the trajectory of risk perception amidst an ongoing economic crisis. A nation-wide panel responded to eight surveys beginning in late September 2008 at the peak of the crisis and concluded in August 2011. At least 600 respondents participated in each survey, with 325 completing all eight surveys. The online survey focused on perceptions of risk (savings, investments, retirement, job), negative emotions toward the financial crisis (sadness, anxiety, fear, anger, worry, stress), confidence in national leaders to manage the crisis (President Obama, Congress, Treasury Secretary, business leaders), and belief in one's ability to realize personal objectives despite the crisis. Latent growth curve modeling was conducted to analyze change in risk perception throughout the crisis. Demographic information includes ethnic origin, sex, age, marital status, income, political affiliation and education. This longitudinal panel study was launched on September 29, 2008, the day the Dow experienced its largest one-day point drop. The first of seven waves of data collection was dedicated almost exclusively to public response to the financial crisis. Further data collection followed on October 8, 2008, November 5, 2008, December 6, 2008, March 21, 2009, June 30, 2009, October 6, 2009, and August 9, 2011. The surveys were spaced closer together in the beginning of the study believing that the most change would occur early in the crisis and, of course, not knowing how long the crisis would last. Collecting the first seven waves of data over a year's period allowed time for the public to respond to different phases of the crisis. A panel of over 800 individuals participated in the study. This ongoing Internet panel was developed by Decision Research through word-of-mouth and Internet recruiting (e.g., paying for Google search words). Nonrespondents (panelists invited to participate but who chose not to) did not differ significantly from respondents in terms of age, gender, or education. Surveys were left open for completion for four to six days, although most panelists responded in the first 24 hours. These online panelists were paid at the rate of $15 per hour with a typical payment of $6 and an incentive if they completed all surveys. Any panelist who appeared to rush through the survey was eliminated and not invited to participate again. N/A ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Presence of Common Scales: Lipkus Numeracy Score, Hierarchy-Egalitarianism Scale, Individualism-Communitarianism Response Rates: Wave 1: 81 percent; Wave 2: 89 percent; Wave 2a:80 percent; Wave 3: 87 percent; Wave 4: 85 percent; Wave 5: 91 percent; Wave 6: 76 percent; Wave 7: 74 percent; Wave 8: 79 percent Smallest Geographic Unit: None Convenience sample of Decision Research web-panel participation located throughout the United States. Funding insitution(s): National Science Foundation (SES-0901036). web-based survey

This statistic shows public evaluation of who was to blame for the economic problems in each country as of 2012. 78 percent of respondents in Spain felt that it was the banks and financial institutions that were most to blame for the current economic problems in their own country as of 2012.

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 paper examines the aftermath of postwar financial crises in advanced countries. We construct a new semiannual series on financial distress in 24 OECD countries for the period 1967-2012. The series is based on assessments of the health of countries' financial systems from a consistent, real-time narrative source, and classifies financial distress on a relatively fine scale. We find that the average decline in output following a financial crisis is statistically significant and persistent, but only moderate in size. More important, we find that the average decline is sensitive to the specification and sample, and that the aftermath of crises is highly variable across major episodes. A simple forecasting exercise suggests that one important driver of the variation is the severity and persistence of financial distress itself. At the same time, we find little evidence of nonlinearities in the relationship between financial distress and the aftermaths of crises.

.xlsx file for the replication of the Paper The Complex Crises Database: 70 years of Macroeconomic Crises. It contains the term frequencies of 20 crises sentiment indexes computed from the IMF country report for the period 1956-2016 for 181 countries. (2021-07-02)

Abstract

This research was conducted in Turkey in June-July 2010 as part of the third round of The Financial Crisis Survey. Data from 364 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Turkey.

Researchers revisited establishments interviewed in Turkey Enterprise Survey 2008. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study was the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors were the primary business sectors of interest. This corresponded to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies were targeted for interviews. Services firms included construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government ownership were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

1152 establishments that participated in Turkey Enterprise Survey 2008 were contacted for The Financial Crisis Survey. The implementing contractor received directions that the final achieved sample should include at least 650 establishments.

Stratified random sampling was used in Turkey Enterprise Survey 2008. Three levels of stratification were implemented: industry, establishment size, and oblast (region).

For industry stratification, the universe was divided into 5 manufacturing industries, 1 services industry -retail -, and two residual sectors. Each manufacturing industry had a target of 160 interviews. The services industry and the two residual sectors had a target of 120 interviews. For the manufacturing industries sample sizes were inflated by about 33% to account for potential non-response cases when requesting sensitive financial data and also because of likely attrition in future surveys that would affect the construction of a panel.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in 5 regions. These regions are Marmara, Aegean, South, Central Anatolia and Black Sea-Eastern.

The Turkey sample contains panel data. The wave 1 panel "Investment Climate Private Enterprise Survey implemented in Turkey" consisted of 1325 establishments interviewed in 2005. A total of 425 establishments have been re-interviewed.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

The source of the sample frame was twofold. Universe estimates were taken from the TOBB database which contains a full list of establishments in manufacturing sectors. TOBB refers to the Union of Chambers and Commodity Exchanges of Turkey. Universe estimates for service sectors were taken from the Statistical Institute of Statistics (SIS) with additional information based on SIC code from the Turkish Studies Institute (TSI). Comparisons were made between estimates in TOBB and SIS to establish that the two sources are comparable and hence can be used side by side.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 43% (2811 out of 6458 establishments).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The following survey instrument is available: - Financial Crisis Survey Questionnaire

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks and callbacks.

Economy and commerce Poverty policy and regulation Data Resource Preview - The Impact of the GLobal Financial and Economic Crisis on Poverty Policy Brief @--> { "fields": [ { "001": "2437_1" }, { "008": "131211 2012 " }, { "100": { "ind1": " ", "subfields": [ { "a": "Tong, Kimsun" } ], "ind2": " " } }, { "245": { "ind1": " ", "subfields": [ { "a": "The Impact of the GLobal Financial and Economic Crisis on Poverty" }, { "b": "Policy Brief" } ], "ind2": " " } }, { "250": { "ind1": " ", "subfields": [ { "a": "No. 6" } ], "ind2": " " } }, { "260": { "ind1": " ", "subfields": [ { "b": "Cambodia Development Research Institute (CDRI)" }, { "a": "Phnom Penh" }, { "c": "2012" } ], "ind2": " " } }, { "300": { "ind1": " ", "subfields": [ { "a": "2 p" } ], "ind2": " " } }, { "653": { "ind1": " ", "subfields": [ { "a": "Poverty" }, { "a": "Economy" }, { "a": "001" } ], "ind2": " " } } ], "leader": "00384nam a0000121ua 124 " }

Background: In light of the coronavirus disease 2019 (COVID-19) pandemic and its large economic consequences, we used a three-layer nested structural model (individual, community, and country), each with a corresponding measure of income, trust, and satisfaction, to assess change in their interrelationships following a global crisis; which, in this study, is the 2008/2009 financial crisis.Methods: With multilevel techniques, we analyzed data from two waves (2006 and 2012) of the European Social Survey (ESS) in 19 countries (weighted N = 73,636) grouped according to their levels of trust.Results: In high trust countries, personal life satisfaction (LS) was not related to personal, community, or national income before or after the crisis. In contrast, in low trust countries, LS was strongly related to all three forms of income, especially after the crisis. In all country groups, personal, social, and political trust moderated their respective effects of income on LS (“the buffer hypothesis”). Political trust moderated the effects of income more strongly in low trust countries. The moderating effect of political trust increased sharply after the crisis. After the crisis, national-level factors (e.g., political trust, national income) increased their importance for LS more than the factors at the local and individual levels. However, the relative importance of all the three forms of income to LS increased after the crisis, to the detriment of trust.Conclusion: Economic crises seem to influence personal LS less in high trust countries compared with low trust countries. Hence, high trust at a national level appears to buffer the negative impact of a financial crisis on personal satisfaction. Overall, the factors at the national level increased their impact during the financial crisis. When facing a global crisis, the actions taken by institutions at the country level may, thus, become even more important than those taken before the crisis.

This data package includes the underlying data files to replicate the data and charts presented in Egypt’s 2023-24 economic crisis: Will this time be different? by Ruchir Agarwal and Adnan Mazarei, PIIE Policy Brief 24-6.

If you use the data, please cite as: Agarwal, Ruchir, and Adnan Mazarei. 2024. Egypt’s 2023-24 economic crisis: Will this time be different?. PIIE Policy Brief 24-6. Washington, DC: Peterson Institute for International Economics.

Women remain underrepresented in cabinets, especially high-prestige, “masculine” portfolios. Still, a growing number of states have appointed women to the finance ministry—a powerful position typically reserved for men. Drawing on the “glass cliff” phenomenon, we examine the relationship between financial crises and women’s ascension to, and survival in, this post. With an original dataset on appointments to finance ministries worldwide (1972-2017), we show that women are more likely to first come to power during a banking crisis. These results also hold for currency and inflation crises, and even when accounting for the political and economic conditions that might otherwise explain this relationship. Subsequent examination of almost 3,000 finance ministers’ tenures shows that once in office, crises shorten men’s (but not women’s) time in the post. Together, these results suggest that women can sometimes seize on crises as opportunities to access traditionally male-dominated positions.

Files allow to reproduce all tables, figures and further data in the article "Macroprudential capital requirements, monetary policy, and financial crises".

Context

This data presented is collected over many years by Carmen Reinhart (with her coauthors Ken Rogoff, Christoph Trebesch, and Vincent Reinhart). These include Banking Crisis dates for more than 21 European countries from 1800-2016, exchange rate crises, stock market crises, sovereign debt growth and default, and many other data series.

Content

The dataset specifically focuses on the Banking, Debt, Financial, Inflation, and Systemic Crises that occurred, from 1800 to 2016, in 13 European countries, including: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Netherlands, Norway, Poland, Portugal, Romania, Russia, Spain, Sweden, Switzerland, United Kingdom.

Acknowledgements

Reinhart, C., Rogoff, K., Trebesch, C. and Reinhart, V. (2019) Global Crises Data by Country. [online] https://www.hbs.edu/behavioral-finance-and-financial-stability/data. Available at: https://www.hbs.edu/behavioral-finance-and-financial-stability/data/Pages/global.aspx [Accessed: 1 September 2020].

Inspiration

Study about the economic factors in European Countries. Carry out various experimental results which can significantly improve the generalization performance for systemic crises using historical financial data of European countries over the past 200 years.

Existing scholarship attributes various political and economic advantages to democratic governance. These advantages may make more democratic countries prone to financial crises. Democracy is characterized by constraints on executive authority, accountability through free and fair elections, protections for civil liberties, and large winning coalitions. These characteristics bring important benefits, but they can also have unintended consequences that increase the likelihood of financial instability and crises. Using data covering the past two centuries, I demonstrate a strong relationship between democracy and financial crisis onset: on average, democracies are about twice as likely to experience a crisis as autocracies. This is an empirical regularity that is robust across a wide range of model specifications and time periods.

This project will explore the impact of the economic recession on cities and households through a systematic comparison of the experiences of two English cities, Bristol and Liverpool.The research will use both quantitative and qualitative approaches. Interviews will be held in both cities with stakeholders from across the public, private and voluntary and community sectors. A social survey of 1000 households will also be conducted in the two cities covering 10 specific household types. A series of in-depth qualitative interviews will then be held with households drawn from the survey and chosen to illustrate the spectrum of experience.In the context of globalisation and the rescaling of cities and states, the research aims to develop our understanding of the relationship between economic crisis, global connectivity and the transnational processes shaping cities and the everyday lives of residents. It will explore the 'capillary-like' impact of the crisis and austerity measures on local economic development, and local labour and housing markets, as well as highlight the intersecting realities of everyday life for households across the life course.The research will document the responses and coping strategies developed across different household types and evaluate the impact and effectiveness of 'anti-recession' strategies and policies.

The classification of finiancial crisis interventions

Source agency: Office for National Statistics

Designation: Supporting material

Language: English

Alternative title: Financial Crisis and Statitical Classification

This dataset is about book series. It has 1 row and is filtered where the books is Global financial crisis : global impact and solutions. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

The Eurobarometer series is a unique cross-national and cross-temporal survey program conducted on behalf of the European Commission. These surveys regularly monitor public opinion in the European Union (EU) member countries and consist of standard modules and special topic modules. The standard modules address attitudes towards European unification, institutions and policies, measurements for general socio-political orientations, as well as respondent and household demographics. The special topic modules address such topics as agriculture, education, natural environment and resources, public health, public safety and crime, and science and technology. This round of Eurobarometer surveys includes the standard modules and covers the following special topics: (1) the financial and economic crisis, (2) the future of the European Union, (3) globalization, and (4) European citizenship. Questions pertain to household financial situation, opinions on performance of the EU economy, reformation of the financial system, national currency and the Euro, public debt, the EU exiting present crisis and preparing for the next decade, and attitudes towards globalization. Other questions address country identification, opinions of European citizenship, the EU achievements for citizens, representation and democracy, the European Citizens' Initiative, and participation of citizens in society. Demographic and other background information collected includes age, gender, nationality, origin of birth (personal and parental), marital status, age when stopped full-time education, occupation, left-right political self-placement, household composition, ownership of a fixed or mobile telephone, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview (select countries).

Do international lenders of last resort create financial instability by generating moral hazard? The evidence is thin and plagued with measurement error. We use the number of American troops hosted by third countries to measure the strength of American commitment to ensuring the countries’ economic health. We test several hypotheses against a dataset covering about sixty-eight countries between 1960 and 2009. Using evidence from fixed-effects and instrumental-variable models, we find that increasing the number of US troops by one standard deviation above the mean raises the probability of a financial crisis in the host country by up to 13 percentage points. We also investigate the channels through which moral hazard materializes. Countries with more US troops conduct more expansionary fiscal and monetary policies, implement riskier financial regulations, and receive more capital, especially from US banks. While many scholars of international relations view the American overseas military presence as a source of stability, we identify an underexplored mechanism by which it generates instability.

Abstract

This research was conducted in Hungary in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 152 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Hungary.

Researchers revisited establishments interviewed in Hungary Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study was the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors were the primary business sectors of interest. This corresponded to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies were targeted for interviews. Services firms included construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government ownership were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

291 establishments that participated in Hungary Enterprise Survey 2009 were contacted for The Financial Crisis Survey. The implementing contractor received directions that the final achieved sample should include at least 150 establishments.

For Hungary Enterprise Survey 2009, the sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in three regions. These regions are Central Hungary, West Hungary and East Hungary.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

For most countries covered in 2008-2009 BEEPS, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for Hungary was the Dun & Bradstreet database, which was considered the most reliable for the country. That frame was sent to the TNS statistical team in London to select the establishments for interviews.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 4.6% (29 out of 630 establishments).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The following survey instrument is available: - Financial Crisis Survey Questionnaire

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks and callbacks.