Smbnh9 Tracking Success Presentation

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SMBNH Tracking Success Presentation: finding, measuring and analyzing economic data online

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Smbnh9 Tracking Success Presentation

  1. 1. SMBNH9: Tracking Success<br />Finding, measuring & analyzing economic data online<br />
  2. 2. Overview<br />Company/personal background<br />Key economic data<br />Easy & free online data sources<br />Basic database, trends, growth<br />Helpful hints<br />
  3. 3. Background<br />CEO of e-forecasting.com<br />Economic research and consulting firm based in Durham, NH<br />Specialize in unique economic data and company demand forecasts<br />Clients/industries: manufacturing, hospitality, government, consulting, academic, media<br />
  4. 4. Data, data, data …<br />With internet and current technology, age of free data is now<br />Issue is knowing where to find it, how to update it, accurately analyzing it<br />
  5. 5. Important Economic Data<br />GDP: measures the value of all goods and services in a country, state, city, industry<br />Employment : measures jobs as gains or losses in the market<br />Production : measures output and levels of productivity or technological change in industries<br />Stocks : measures expectations of future economic activity<br />
  6. 6. Easy steps to find data & build simple spreadsheet<br />Determine the scope and what data will suit your needs<br />Research possible sources and choose most reliable, with high frequency of updates<br />Keep solid record of directions, including link, steps to extract data and release schedule if possible<br />Organize database in system that works for you<br />
  7. 7. Sample file organization<br />Directions<br />Updates<br />Final Data<br />Keep detailed instructions, including link and each step to extract data necessary, include release calendar, keep track of unit of measurement, etc.<br />Enter data updates here, with actual data from source in left columns, then any calculated columns to the right, use color to show which cells are actual, and which are calculations<br />Link cells to updates tab and only show which columns/data you want to look at each month, keep this ‘clean’ meaning only data you want is visible<br />
  8. 8. Easy-ish, free online econ data<br />Bureau of Labor Statistics http://www.bls.gov/<br />Inflation, prices, employment, pay, productivity, regional<br />BEA – Bureau of Economic Analysis http://www.bea.gov/industry/<br />GDP data by industry, state, city, personal income, employment<br />Federal Reserve http://www.federalreserve.gov/<br />Industrial production, interest rates, exchange rates, quantity of money, consumer credit<br />US Census http://www.census.gov/econ/<br />Manufacturing, trade (inventories and sales), monthly sales retail and food, wholesale trade, manufacturers shipments, inventories and orders, housing vacancies, construction spending, new home sales, housing starts/building permits, retail trade<br />IMF – International Monetary Fund http://www.imf.org/external/index.htm<br />Data by country: GDP, consumer prices, producer prices, employment, industrial production, debt, interest rates, share prices, business and consumer confidence, oil prices, exchange rates<br />OECD – Organization of Co-Operation and Economic Development http://www.oecd.org<br />Data by country: agriculture, fisheries, demography, population, development, projections, education, environment, finance, globalization, prices, welfare statistics<br />
  9. 9. Ways to analyze trends<br />Track month over month change: m/m<br />Track year over year change: y/y<br />% change=(new_value/original_value)-1<br />
  10. 10. Ways to analyze trends<br />Make a simple time series of the data to visualize trends, such as the peaks and troughs of the business cycle<br />Long term growth: measures average growth over specified period of time<br />Ex. Average GDP of US is 3.3%, can use this as a baseline to make comparisons<br />
  11. 11. Watch for seasonality!<br />Seasonality in data takes into account trends that happen every year, like gas prices increasing in the summer<br />You need to know if data is <br />seasonally adjusted or actual, especially when comparing with other data<br />Need to compare actual vs actual and seasonal vs seasonal data<br />If you don’t have seasonal data, you need to find a way to make it so, can use program to ID seasonal factors<br />
  12. 12. Helpful Tips<br />Always keep a record of data source, may have to check back, double check values, numbers may be questioned by clients, etc<br />Best to re-arrange data into time series format if possible<br />Check for updates to previous month, quarter, year, data sources continually make revisions, keep your database up to date<br />Run quality tests to make sure data makes sense, even the source can have data wrong, good idea is to make simple graph<br />Carefully note measurement, is data measured in hundreds, dollars, percent?<br />Don’t get discouraged by first-time set up effort, after initial set up, time to update data will be much less and you will have strong data to back up your research and analysis<br />

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