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

1. SMBNH9: Tracking Success Finding, measuring & analyzing economic data online

2. Overview Company/personal background Key economic data Easy & free online data sources Basic database, trends, growth Helpful hints

3. Background CEO of e-forecasting.com Economic research and consulting firm based in Durham, NH Specialize in unique economic data and company demand forecasts Clients/industries: manufacturing, hospitality, government, consulting, academic, media

4. Data, data, data … With internet and current technology, age of free data is now Issue is knowing where to find it, how to update it, accurately analyzing it

5. Important Economic Data GDP: measures the value of all goods and services in a country, state, city, industry Employment : measures jobs as gains or losses in the market Production : measures output and levels of productivity or technological change in industries Stocks : measures expectations of future economic activity

6. Easy steps to find data & build simple spreadsheet Determine the scope and what data will suit your needs Research possible sources and choose most reliable, with high frequency of updates Keep solid record of directions, including link, steps to extract data and release schedule if possible Organize database in system that works for you

7. Sample file organization Directions Updates Final Data Keep detailed instructions, including link and each step to extract data necessary, include release calendar, keep track of unit of measurement, etc. 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 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

8. Easy-ish, free online econ data Bureau of Labor Statistics http://www.bls.gov/ Inflation, prices, employment, pay, productivity, regional BEA – Bureau of Economic Analysis http://www.bea.gov/industry/ GDP data by industry, state, city, personal income, employment Federal Reserve http://www.federalreserve.gov/ Industrial production, interest rates, exchange rates, quantity of money, consumer credit US Census http://www.census.gov/econ/ 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 IMF – International Monetary Fund http://www.imf.org/external/index.htm Data by country: GDP, consumer prices, producer prices, employment, industrial production, debt, interest rates, share prices, business and consumer confidence, oil prices, exchange rates OECD – Organization of Co-Operation and Economic Development http://www.oecd.org Data by country: agriculture, fisheries, demography, population, development, projections, education, environment, finance, globalization, prices, welfare statistics

9. Ways to analyze trends Track month over month change: m/m Track year over year change: y/y % change=(new_value/original_value)-1

10. Ways to analyze trends Make a simple time series of the data to visualize trends, such as the peaks and troughs of the business cycle Long term growth: measures average growth over specified period of time Ex. Average GDP of US is 3.3%, can use this as a baseline to make comparisons

11. Watch for seasonality! Seasonality in data takes into account trends that happen every year, like gas prices increasing in the summer You need to know if data is seasonally adjusted or actual, especially when comparing with other data Need to compare actual vs actual and seasonal vs seasonal data If you don’t have seasonal data, you need to find a way to make it so, can use program to ID seasonal factors

12. Helpful Tips Always keep a record of data source, may have to check back, double check values, numbers may be questioned by clients, etc Best to re-arrange data into time series format if possible Check for updates to previous month, quarter, year, data sources continually make revisions, keep your database up to date Run quality tests to make sure data makes sense, even the source can have data wrong, good idea is to make simple graph Carefully note measurement, is data measured in hundreds, dollars, percent? 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