Michigan Unemployment Rate: 49 years of historical data from 1976 to 2025.

United States Unemployment Rate: Michigan data was reported at 3.800 % in Oct 2018. This records an increase from the previous number of 3.500 % for Sep 2018. United States Unemployment Rate: Michigan data is updated monthly, averaging 7.500 % from Jan 1976 (Median) to Oct 2018, with 514 observations. The data reached an all-time high of 17.300 % in Jan 1983 and a record low of 2.900 % in Apr 2000. United States Unemployment Rate: Michigan data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G057: Unemployment Rate: By State.

United States Unemployment Rate: sa: Michigan data was reported at 4.500 % in Jun 2018. This records a decrease from the previous number of 4.600 % for May 2018. United States Unemployment Rate: sa: Michigan data is updated monthly, averaging 7.300 % from Jan 1976 (Median) to Jun 2018, with 510 observations. The data reached an all-time high of 16.500 % in Dec 1982 and a record low of 3.200 % in Mar 2000. United States Unemployment Rate: sa: Michigan data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G058: Unemployment Rate: By State: Seasonally Adjusted.

Analysis of ‘Problem Resolution Offices’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3c0fc6f2-03c4-4ad9-8968-6e012e4b6f02 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

CSI: Expected Unemployment: Next Yr: Don't Know data was reported at 1.000 % in May 2018. This stayed constant from the previous number of 1.000 % for Apr 2018. CSI: Expected Unemployment: Next Yr: Don't Know data is updated monthly, averaging 1.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 6.000 % in May 1978 and a record low of 0.000 % in Feb 2018. CSI: Expected Unemployment: Next Yr: Don't Know 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?

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE.A spatial representation of the locations of Michigan UIA Problem Resolution Offices (PRO).Data Source: PRO Locations

Problem Resolution Offices - Need Help?The UIA's Problem Resolution Offices (PROs) resolve customer problems and provide access to automated resources.PROs provide:Telephones and computers for the convenience of customers who may not have access to a computer or telephone to file their claim. If you are going to file an unemployment claim at a PRO, please bring: Your Social Security Number, your Driver's License Number or State Identification or your MARVIN PIN (if you have one); along with the names and addresses of employers you have worked for in the past 18 months with your quarterly gross earnings and the last date of employment with each employer. If you are not a U.S. citizen or national, you will need your Alien Registration Number and the expiration date of your work authorization.In-person help for problems with claimsA presence in the community that includes, on request, presentations about unemployment insurance services to employer, business, labor, and community groupsFile at a PRO: If you are going to file an unemployment claim at a PRO, please bring:Your Social Security Number, your Driver's License Number or State Identification or your MARVIN PIN (if you have one)If you are not a U.S. citizen or national, you will need your Alien Registration Number and the expiration date of your work authorization.Names and addresses of employers you have worked for in the past 18 months including quarterly gross earnings and the last date of employment with each.

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.

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.

Blackrock MuniYield Michigan Quality Fund (MIY) Forecast: A Look Ahead

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

United States CSI: Expected Unemployment: Next Yr: Same data was reported at 51.000 % in May 2018. This records an increase from the previous number of 46.000 % for Apr 2018. United States CSI: Expected Unemployment: Next Yr: Same data is updated monthly, averaging 49.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 67.000 % in May 1988 and a record low of 20.000 % in Feb 2009. United States CSI: Expected Unemployment: Next Yr: Same 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?