The Great Depression of the early twentieth century is widely considered the most devastating economic downturn that the developed world has ever seen. Industrial output was severely affected across Europe, and in Germany alone, it fell to just 58 percent of its pre-Depression level by 1932. Other Central European countries, such as Austria and Czechoslovakia, also saw their output fall to just sixty percent of their pre-Depression levels, while output in Western and Northern Europe declined by much less. By 1937/8, almost a decade after the Wall Street Crash, most of these countries saw their industrial output increase above its pre-Depression level. Germany saw its output increase to 132 percent of its 1928 output, as it emerged as Europe's strongest economy shortly before the beginning of the Second World War.

From March to July 1933, US industrial production rose 57 percent. We show that an important source of recovery was the effect of dollar devaluation on farm prices, incomes, and consumption. Devaluation immediately raised traded crop prices, and auto sales grew more rapidly in states and counties most exposed to these price increases. The response was amplified in counties with more severe farm debt burdens. For plausible assumptions about farmers' relative MPC, the incidence of higher farm prices, and the aggregate multiplier, this redistribution to farmers accounted for a substantial portion of spring 1933 growth. This farm channel thus provides an example of how the distributional consequences of macroeconomic policies can have large aggregate effects. That recovery in 1933 benefited from redistribution to farmers suggests an important limitation to the use of 1933 as a guide to the effects of monetary regime changes in other circumstances.

This contains the dataset of the 1936 household consumption survey and 1930 census data used in "Fiscal Policy and Economic Recovery: The Case of the 1936 Veterans' Bonus." The underlying household survey data come from ICPSR study 08908. The Census data come from the IPUMS 5% sample from the 1930 Census. The primary data file is urban_lprob.dta. urban_nodups.dta contains a subset of these data for programming convenience. For further documentation, see the paper, and the data and program files posted on the American Economic Review's website.

Over the course of their first terms in office, no U.S. president in the past 100 years saw as much of a decline in stock prices as Herbert Hoover, and none saw as much of an increase as Franklin D. Roosevelt (FDR) - these were the two presidents in office during the Great Depression. While Hoover is not generally considered to have caused the Wall Street Crash in 1929, less than a year into his term in office, he is viewed as having contributed to its fall, and exacerbating the economic collapse that followed. In contrast, Roosevelt is viewed as overseeing the economic recovery and restoring faith in the stock market played an important role in this.

By the end of Hoover's time in office, stock prices were 82 percent lower than when he entered the White House, whereas prices had risen by 237 percent by the end of Roosevelt's first term. While this is the largest price gain of any president within just one term, it is important to note that stock prices were valued at 317 on the Dow Jones index when Hoover took office, but just 51 when FDR took office four years later - stock prices had peaked in August 1929 at 380 on the Dow Jones index, but the highest they ever reached under FDR was 187, and it was not until late 1954 that they reached pre-Crash levels once more.

During the Great Depression in the United States in 1930s, the federal government's share of relief spending in major cities changed drastically following the inauguration of Franklin D. Roosevelt in 1933. The previous administration of President Herbert Hoover oversaw the beginning of the depression in 1930, however federal spending on relief was virtually non-existent until his final year in office, and the share of overall relief spending was just two percent in 1932.

With Roosevelt's New Deal, the U.S. government established various agencies and programs that provided relief for its citizens. This included the introduction of social security systems, as well as the creation of public works programs which created government jobs in areas such as construction and infrastructure. In later years, economic recovery also allowed for the expansion of these programs into areas such as disability benefits, and per capita relief spending more than doubled from 1933 to 1936.

ABSTRACT By contrasting the Great Depression and the Coronacrisis, we demonstrate that narrative economics (Shiller, 2017) is key in the analysis of economic fluctuations. We note the importance of the populist narrative to understand the economic and health outcomes of the Coronacrisis in Mexico and highlight the role of the predominance of different economic paradigms in economic policy decision-making. We suggest that, just as in 1929, by following orthodox primary fiscal balance sheet policies at the cost of contracting government investment, the Mexican economy will undergo a long and painful recovery process compared to its global peers.

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.

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.

In a survey conducted in September 2020, regarding consumer perception surrounding the economic recovery after coronavirus (COVID-19) in India, 31 percent of the respondents are positive that the economy will bounce back to pre-COVID levels in the next few months. Majority of the respondents disagree that COVID-19 would cause a significant recession or a major economic depression.

How did countries recover from the Great Depression? In this paper, we explore the argument that leaving the gold standard helped by boosting inflationary expectations, lowering real interest rates, and stimulating interest-sensitive expenditures. We do so for a sample of 27 countries, using modern nowcasting methods and a new dataset containing more than 230,000 monthly and quarterly observations for over 1,500 variables. In those cases where the departure from gold happened on well-defined dates, inflationary expectations clearly rose in the wake of departure. IV, diff-in-diff, and synthetic matching techniques suggest that the relationship is causal.

Background: The Improving Access to Psychological Therapies (IAPT) programme launched in 2008 in the United Kingdom has improved access to cost-effective cognitive behavioural therapy (CBT) for treating depression and anxiety. Inspired by this model, a two-year training course was launched in Japan to train therapists to practise CBT. In this study, we analysed the patient data collected from this programme.Methods: We collected observational data from 31 trained therapists who delivered high-intensity face-to-face CBT sessions. A total of 290 patients participated in the study; 241 met the inclusion criteria. Depression and anxiety were assessed using the Japanese versions of the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 questionnaire (GAD-7), respectively and statistical analyses were performed to compare the pre- and post-treatment scores. Reliable improvement and recovery rates were assessed based on established thresholds.Results: Before the treatment, the mean PHQ-9 score was 11.5 (SD = 6.4) and the mean GAD-7 score was 10.0 (SD = 5.2). No significant differences were found between male and female participants. The outcome classification showed that before the treatment, 32.4% of the participants suffered from severe depression (PHQ-9 ≥ 15) and 20.3% from severe anxiety (GAD-7 ≥ 15). The statistical analysis confirmed a significant improvement in depression and anxiety symptoms after the treatment (p < .05): 168 participants (69.7%) showed reliable improvement and 58 participants (35%) showed reliable recovery.Conclusion: The IAPT-adapted CBT model in Japan is feasible despite differences in the healthcare system; however, further consideration is needed to improve the rate of reliable recovery. Future studies should improve implementation strategies, expand the patient database, and evaluate the long-term treatment effects.

An online survey on depression, conducted by a Finnish newspaper. The data consist of responses to open-ended questions about the treatment of depression and recovery from depression. Questions covered, among others, causes of depression, treatment received by the respondents, experiences of drug therapy, future expectations, and recovery process. The dataset is only available in Finnish.

Taylor (2019) details heterogeneity in the effects of the National Industrial Recovery Act (NIRA) across industries and across time. Through first the President’s Reemployment Act (PRA) and then industry-specific “codes of fair competition,” the NIRA raised wages and restricted working hours. In some–but far from all–cases industries also used a NIRA code to collude, raising prices and restricting output. The effect of the NIRA peaked in fall 1933 and winter 1934; thereafter, compliance declined. I review the intellectual history of the NIRA, the implementation of the PRA and the NIRA codes, and Taylor’s econometric evidence on their effects. I end with a discussion of the implications of Taylor’s book for understanding the effect of the NIRA on U.S. recovery from the Great Depression.

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.

What caused the recovery from the British Great Depression? A leading explanation - the “expectations channel” - suggests that a shift in expected inflation lowered real interest rates and stimulated consumption and investment. However, few studies have measured, or tested the economic consequences of, inflation expectations. In this paper, we collect high-frequency information from primary and secondary sources to measure expected inflation in the United Kingdom between the wars. A VAR model suggests that inflation expectations were an important source of the early stages of economic recovery in interwar Britain.

To estimate the extent to which physical capability, depressive symptoms, balanced self-efficacy (BSE), and other risk factors, that are interrelated with stroke, influence the quality of life (QoL) in stroke survivors. A theoretical model based on Wilson and Cleary’s model tested the specific hypotheses: 1) physical capability has an indirect effect on QoL mediated by BSE; 2) physical capability has an indirect effect on QoL by depressive symptoms; 3) stroke risk factors (hypertension/diabetes/gender) moderate the above relationship. Six hundred and seventy stroke survivors were enrolled from ten different hospitals in Yunnan province from 2019 to 2021. Patients’ mental and physical function was assessed using the Brunnstrom recovery stage (BRS), mini-balance evaluation system test (Mini-BEST), Barthel index (BI), Activities-specific Balance Confidence scale (ABC), and Hamilton depression scale (HAM-D). The structural equation model (SEM) was used to test the moderated mediation model in Mplus 8.0 software. The model showed a good fit (RMSEA =  0.075, SRMR =  0.010). BSE significantly mediated the relationship between physical capability and QoL (β =  0.322, p =  0.002). Hypertension was found a significant moderator of all the direct paths from physical capability to QoL through depressive symptoms (В =  0.412, p =  0.015; В =  0.831, p =  0.020, respectively). This study provides a better insight into the relationship between physical capability and QoL via BSE in stroke survivors, which may help establish appropriate treatment for these individuals.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 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.

The global drug free depression treatment demand is anticipated to increase at a moderate CAGR of around 2% to 4% during the forecast period between 2022 and 2032.

Report Attribute	Details
Drug Free Depression Treatment Market Projected Growth Rate (2022 to 2032)	2% to 4% CAGR

Scope of Report

Report Attribute	Details
Growth Rate	CAGR of 2% to 4% from 2022 to 2032
Base Year for Estimation	2021
Historical Data	2015 to 2020
Forecast Period	2022 to 2032
Quantitative Units	Revenue in USD Billion, Volume in Kilotons and CAGR from 2022 to 2032
Report Coverage	Revenue Forecast, Volume Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends and Pricing Analysis
Segments Covered	Treatment Type, Facility Type, Region
Regions Covered	North America; Latin America; Western Europe; Eastern Europe; APEJ; Japan; Middle East and Africa
Key Countries Profiled	USA, Canada, Brazil, Argentina, Germany, UK, France, Spain, Italy, Nordics, BENELUX, Australia & New Zealand, China, India, ASEAN, GCC, South Africa
Key Companies Profiled	Cleveland Clinic; Mayo Clinic; Fortis Healthcare; Assurex Health, Inc.; Great Oaks Recovery Center; McLean Hospital
Customization	Available Upon Request

The Trait-Based Data Archive is a comprehensive repository containing the statistical analyses and findings from a longitudinal study of 139 graduates of the Trait-Based Model of Recovery, as well as an ongoing data collection and analaysis repository for current research efforts. This archive provides detailed insights into the program's impact on mental health outcomes, personality trait development, and participant retention rates.

Key components of the archive include:

Depression and Anxiety Analysis: Statistical evaluations of reductions in depression and anxiety levels, as measured by validated tools such as the PHQ-9 and GAD-7, highlighting the program's effectiveness in addressing co-occurring mental health challenges.

Trait Development Metrics: Pre- and post-intervention data on the development of 10 key personality traits, including resilience, self-awareness, emotional intelligence, and authenticity, with a focus on their role in fostering sustainable recovery and personal growth.

Retention Rate Comparisons: Analysis of retention rates between Trait-Based Model participants (96%) and those in traditional recovery programs (15.5%), emphasizing the program's ability to sustain engagement and commitment.

Control Group Comparisons: Supplementary data from traditional recovery programs, offering a comparative perspective on mental health outcomes and participant progress.

This archive serves as a valuable resource for researchers, practitioners, and policymakers interested in evidence-based, strengths-focused approaches to addiction recovery and mental health improvement. It provides a robust foundation for further exploration of the Trait-Based Model's long-term impacts and its potential applications in diverse behavioral health contexts.

To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern meadow edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). A nor'easter storm moved through the area in early May 2022 producing 59% and 48% of the year's total Gale and Near Gale force winds. After the storm passed, depressions were noticed within the edge treatment sites. To quantify the depression depths a survey of the sediment surface depth was coordinated among all sites in October 2022. Results provide evidence that the edge treatment sites were depressed by 9.4-10.4 cm relative to outside of the treatment plots.