Brazil National Consumer Confidence Index: Expectation: Unemployment: More Than 55 Years data was reported at 55.400 Point in Jun 2019. This records an increase from the previous number of 54.300 Point for Mar 2019. Brazil National Consumer Confidence Index: Expectation: Unemployment: More Than 55 Years data is updated quarterly, averaging 60.200 Point from Mar 2009 (Median) to Jun 2019, with 42 observations. The data reached an all-time high of 73.925 Point in Jun 2015 and a record low of 48.000 Point in Dec 2018. Brazil National Consumer Confidence Index: Expectation: Unemployment: More Than 55 Years data remains active status in CEIC and is reported by National Confederation of Industry. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SJ002: National Consumer Confidence Index: by Age. Diffusion Index On expectation indicators the values above 50 points indicate growth expectancy, while values below 50 points indicate expectancy of fall. Exceptionally the first result of 2019 refers to the month of April/2019 instead of March/2019.

This data set contains the data used in the research project "Cognitive Biases in Consumer Sentiment: the Peak-End Rule and Herding". The following files and items are includedICSdata.xlsx: Index of Consumer Sentiment and its constituents (sheet 1), and PAGO per region (sheet 2); original source University of Michigan, Survey of Consumers, https://data.sca.isr.umich.edu/ALFRED_data: macro economic series related to economic growth, inflation, (un)employment and consumption, including publication date; original source ArchivaL Federal Reserve Economic Data (ALFRED), https://alfred.stlouisfed.org/; for each series a README sheet is included with metadataFREDdata: financial and economic series related to stock, bond, housing markets, interest rates,gasoline prices and regional unemployment rates; each sheet contains the mnemonic of the donwloaded series.MicroData_20220113: demographic information of each respondent in the Survey of Consumers conducted by the University of Michigan; downloaded from University of Michigan, Survey of Consumers, https://data.sca.isr.umich.edu/Prelim_PA.xlsx: the Index of Consumer Sentiment and its constituent series, as reported in the preliminary annoucement by the University of Michigan (prelim), and the series constructed based on the surveys after the preliminary announcements. The prelim series are publicly available via https://data.sca.isr.umich.edu/ . The pa series have been constructed based on interview datas obtains from the University of Michigan. These data are proprietory and cannot be shared freely.DemographicDifferences.xlsx: average differences between the prelim and pa monthly subsample in the demographic statistics available in MicroData_20220113.xlsx. The difference have been constructed based on interview datas obtains from the University of Michigan. These data are proprietory and cannot be shared freely.Methodology: Linear regressions and time-series methods.Findings: We show that two heuristics, the peak-end rule and herding, generate biases in indexes of consumer sentiment. Both affect respondents' assessment of changes in their financial position over the past year. Conform the peak-end rule, their answers relate more to extreme detrimental monthly than to yearly changes in key financial and macro variables. These effects are stronger for more salient variables. As for herding, we document that respondents interviewed in the second round about past financial changes rely too strongly on future expectations from first-round respondents. These effects persist when we account for structural differences in sample composition or for the effect of other predictive variables. Our research shows the presence of both biases outside controlled environments and sheds new light on the relevance of sentiment indexes.

In August 2025, the consumer confidence in Italy stood at 96.2. Index values are calculated by considering eleven subcategories focused on consumer sentiment, such as expectations on the development of domestic unemployment and consumer prices. An index value above 100 indicates a more optimistic outlook of consumers on the economic situation, whereas an index value below 100 indicates a more pessimistic outlook.

This statistic shows the consumer confidence indicator in Flanders, Wallonia and the Brussels Capital Region from January 2018 to December 2025. Every month, a completely different representative sample of ***** people is questioned about the macroeconomic situation in Belgium and their own financial position and consumer behavior. The sample is representative for the geographic, social and demographic differences in Belgium. Macroeconomic questions on unemployment and the Belgian economy, and personal questions about the financial position of the household and the savings of the household are used to calculate the consumer confidence indicator. Overall, the consumer confidence in the Flemish region is higher than that of the Walloon and Brussels Capital region.A consumer confidence indicator characterizes the general opinion of consumers in a defined period and is designed to show how optimistic or pessimistic consumers feel about the financial situation of households and how various factors, such as unemployment or savings expectations, affect their future behavior. Respondents are asked questions in a survey, with both positive and negative answers being possible. The number of positive and negative answers to each of the questions are totaled, leading to the indicator.

Brazil National Consumer Confidence Index: Expectation: Unemployment: Capital data was reported at 58.925 Point in Jun 2019. This records an increase from the previous number of 55.075 Point for Mar 2019. Brazil National Consumer Confidence Index: Expectation: Unemployment: Capital data is updated quarterly, averaging 62.463 Point from Mar 2009 (Median) to Jun 2019, with 42 observations. The data reached an all-time high of 75.000 Point in Jun 2015 and a record low of 52.600 Point in Dec 2018. Brazil National Consumer Confidence Index: Expectation: Unemployment: Capital data remains active status in CEIC and is reported by National Confederation of Industry. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SJ006: National Consumer Confidence Index: by Condition of Municipality. Diffusion Index On expectation indicators the values above 50 points indicate growth expectancy, while values below 50 points indicate expectancy of fall. Exceptionally the first result of 2019 refers to the month of April/2019 instead of March/2019.

Overall, from January 2018 to January 2025, forecasts made by Belgian consumers on the unemployment development for the year to come improved. In January 2025, positive forecasts outweighed negative ones by 32 percentage points. A increase of the balances of this indicator is pointing to a more favorable development. Belgian consumer’s forecasts on unemployment European banks adjust their monetary policies by taking into consideration the consumer confidence indicator. This index provides insight into the consumer's views of the economic situation of their country. In March of 2022, the Belgian consumer confidence indicator had a negative balance, suggesting pessimistic opinions. Appraising the country’s economy entails the assessment of unemployment. Given that the unemployment rate was lately decreasing in Belgium, it can be expected that consumer’s confidence would rise accordingly. The consumer confidence indicator Consumer forecasts on unemployment are only one component of the consumer confidence indicator. Ultimately, the forecasts on the financial situation of households or on the economic situation of the country could explain why the Belgian consumer confidence indicator had a negative balance in 2022.

From January 2018 to January 2025, the consumer confidence indicator in Belgium fluctuated significantly. Unsurprisingly, the concern about the coronavirus (COVID-19) pandemic and the Russia-Ukraine war was reflected in the confidence of consumers. Although the economic consequences are yet to be fully evaluated, in April and August 2020, the consumer confidence indicator was *** percentage points. However, negative answers steadily outweighed positive answers from November 2018 to April 2021. It stood at ** in October of 2023. Consumer confidence during the 2020 sanitary crisis The confidence indicator rests on a monthly survey, thus reflects the current confidence of consumers. In May 2022, Belgian consumers forecast pessimistically the economic situation of Belgium for the year to come. Furthermore, consumers predicted a favorable development of unemployment in 2022. The consumer confidence indicator also evaluates personal attitudes towards personal finance. Early 2020, prior to the confinement, the share of Belgian consumers who viewed their financial situation negatively increased. In May 2022, fewer consumers were optimistic about the future of their finances than in May 2021. Consumption behaviors during the coronavirus pandemic From May 2021 to March 2022, a decreasing share of Belgian consumers notably believed it was the right time to save money. Indeed, in March, consumers believed it was not a good time to make major purchases. Ultimately, confidence is bound to vary alongside with the consumer’s perception of the coronavirus crisis. For instance, in March 2020, sales of certain products such as hand-sanitizers or toilet paper have skyrocketed due to the public’s perception of the pandemic.

The Index of Consumer Confidence is calculated by The Conference Board of Canada using a survey of four attitudinal questions posed to Canadian households. The index measures consumer optimism about the current economic environment and is an indicator of consumer product sales in the near term. The survey questions asked are related to household finances, business conditions, unemployment, inflation, income, government economic policy and whether or not it is a good time to buy or sell a house, automobile and/or major household items. The values presented in this report are annual figures, derived from monthly averages, and have a base year of 2014.

This statistic displays a monthly index of consumer confidence in France from January 2021 to January 2022. Index values are calculated from ** subcategories focused on consumer sentiment, such as expectations on the development of domestic unemployment and consumer prices over the upcoming 12 months. An index value above 100 indicates a more optimistic outlook of consumers on the economic situation than the long-term average; an index value below 100 indicates a more pessimistic outlook. In January 2022, consumer confidence in France had ranged at ** index points.

In July 2025, the index for consumer confidence in China ranged at ** points, up from **** points in the previous month. The index dropped considerably in the first half of 2022 and performed a sideways movement during 2023 and 2024. Consumer confidence Index The consumer confidence index (CCI), also called Index of Consumer Sentiment (ICS) is a commonly used indicator to measure the degree of economic optimism among consumers. Based on information about saving and spending activities of consumers, changes in business climate and future spending behavior are being projected. The CCI plays an important role for investors, retailers, and manufacturers in their decision-making processes. However, measurement of consumer confidence varies strongly from country to country. As consumers need time to react to economic changes, the CCI tends to lag behind other indicators like the consumer price index (CPI) and the producer price index (PPI). Development in China As shown by the graph at hand, confidence among Chinese consumers picked up since mid of 2016. In October 2017, the CCI hit a record value of 127.6 index points and entered into a sideward movement. Owing to a relative stability in GDP growth, a low unemployment rate, and a steady development of disposable household income, Chinese consumers gained more confidence in the state of the national economy. Those factors also contribute to the consumers’ spending power, which was reflected by a larger share of consumption in China’s GDP. After the outbreak of the coronavirus pandemic, consumer confidence dropped quickly in the beginning of 2020, but started to recover in the second half of the year, leading to a v-shaped movement of the index in 2020.

Consumer Confidence Indicator: Unemployment in Finland in 12 Months data was reported at 19.300 % in Jul 2018. This records an increase from the previous number of 18.100 % for Jun 2018. Consumer Confidence Indicator: Unemployment in Finland in 12 Months data is updated monthly, averaging -1.900 % from Oct 1995 (Median) to Jul 2018, with 274 observations. The data reached an all-time high of 27.600 % in Mar 1998 and a record low of -51.100 % in Dec 2008. Consumer Confidence Indicator: Unemployment in Finland in 12 Months data remains active status in CEIC and is reported by Statistics Finland. The data is categorized under Global Database’s Finland – Table FI.H008: Consumer Confidence Indicator.

The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2004 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables. Also explored in this survey, were respondents' types of savings and financial investments, loan use, family income, and retirement planning. The August 2004 survey includes a section exploring how informed respondents perceive themselves to be about certain science and policy issues as well as questions about science and research. Other topics in this series typically include ownership, lease, and use of automobiles, respondents' use of personal computers at home and in the office, and respondents' familiarity with and use of the Internet. Demographic information includes ethnic origin, sex, age, marital status, and education.

An economic indicator is a statistic about an economic activity, and they allow analysis of economic performance and predictions of current and future economic performance. The TX Comptroller’s Key Economic Indicators includes such measures for TX & the US employment and unemployment, consumer confidence, price inflation, housing data, etc.

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The uploaded dataset contains monthly time-series of the index numbers (base 2010) of the Italian current confidence indicator and the Italian future confidence indicator from January 2014 to March 2020. Each time series is composed of 75 values (72 valid data and 3 missing data for the time interval July 2017 – December 2017). The current confidence index measures the judgment of the present economic situation of Italy and families, current opportunity for saving and purchasing durable goods and family financial budget, on the other hand the future confidence index measures the expectation regarding the above-mentioned variables including unemployment. A joint assessment of both indexes can offer a very interesting interpretation referred to the optimistic (current index lower than the future one) or pessimistic (current index greater than the future one) state of the population. The source of these datasets is the official website of Italian Institute of Statistics (http://dati-congiuntura.istat.it/?lang=en&SubSessionId=c419585c-c3e5-4408-9423-14ce999a6dcd).

CSI: Expected Unemployment: Next Yr: More data was reported at 24.000 % in May 2018. This records a decrease from the previous number of 25.000 % for Apr 2018. CSI: Expected Unemployment: Next Yr: More data is updated monthly, averaging 31.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 72.000 % in May 1980 and a record low of 13.000 % in May 1983. CSI: Expected Unemployment: Next Yr: More data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The question was: How about people out of work during the coming 12 months -- do you think there will be more unemployment than now, about the same, or less?

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is the Consumer Services Index a Reliable Indicator of Economic Health?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The twelfth Orange County Annual Survey again focuses on the issue of jobs and the economic outlook. The survey also analyzes the emerging issue of crime in Orange County. Lastly, It examines several topics that have been monitored over time. The sample size is 1,007 Orange County adult residents.

This survey was undertaken to assess consumer sentiment and buying plans, as well as unemployment, travel, long-distance telephone calls, and attitudes toward proposed anti-recession measures. Open-ended questions were asked concerning evaluations and expectations about price changes, employment, recession, and the national business situation. Information was elicited on the number of people then working who had been laid off intermittently in the past year or who were working shorter hours or who had lost their jobs. Questions were also asked about how families whose income had been reduced by unemployment or by shorter hours had managed financially, and what might stimulate business and reduce unemployment. Respondents were also asked about their plans for future travels, travel experiences, and overseas travel preferences, and their reactions to the introduction of jet planes for commercial use. Additional variables probe respondents' telephone usage and the effects of the recession on their use of telephones for long-distance calls. Data are also provided on respondents buying intentions for a house, automobiles, appliances, and other consumer durables, as well as their appraisals of present market conditions for purchasing these items. Demographic variables provide information on age, race, sex, marital status, education, occupation, religion, and family income. A supplementary sample of 122 respondents, consisting of a specially selected Detroit unemployment sample, is available upon request only.

CSI: Government Economic Policy: Good Job data was reported at 28.000 % in May 2018. This records a decrease from the previous number of 30.000 % for Apr 2018. CSI: Government Economic Policy: Good Job data is updated monthly, averaging 19.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 49.000 % in Mar 1999 and a record low of 4.000 % in Dec 2008. CSI: Government Economic Policy: Good Job data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The question was: As to the economic policy of the government -- I mean steps taken to fight inflation or unemployment -- would you say the government is going a good job, only fair, or a poor job?

The statistic shows the gross domestic product (GDP) per capita in Japan from 1987 to 2024, with projections up until 2030. In 2024, the estimated gross domestic product per capita in Japan was around 32,498.15 U.S. dollars. For further information, see Japan's GDP. Japan's economy Japan is the world’s second largest developed economy and a member of the Group of Eight, also known as G8, which is comprised of the eight leading industrialized countries. Due to a weak financial sector, overregulation and a lack of demand, Japan suffered substantially from the early 1990s until 2000, a time referred to as ‘’The Lost Decade’’. Japan’s economy is still slowly recovering from the country’s asset price bubble collapse; however it continues to struggle to retain economic milestones achieved in the 1980s. Japan’s response to the crash was to stimulate the economy, which in turn resulted in extensive amounts of debt that further increased into the 21st century, most notably after the 2008 financial crisis. Despite maintaining a surprisingly low unemployment rate, demand within the country remains inadequate, primarily because Japanese residents spend a rather small fraction of the money they earned from the workplace. Lower demand often has a direct effect on production, with companies seeing not enough profits to continue production at such a high rate. Based on the consumer confidence index, Japanese households found that their quality of life, income growth, employment and propensity to durable goods was below satisfactory standards, perhaps due to these households still experiencing the effects of the 1990s bubble crash.