Information Availability

Not only must an indicator be capable of measurement, but someone has to have measured it.

• Collecting statistics is expensive
• Collecting statistics is time-consuming (it often takes 2 years to compile international statistics)
• Only in rare instances will students want to collect their own statistics

Given the expense and time commitment, ask yourself, "Who would have an interest in collecting this information?"

• Governments? (The US Government is the largest statistics-collecting agency in the world)
• An NGO (e.g. The World Bank)
• An IGO (e.g. The United Nations)
• Non-profit organizations, including professional organizations (for example, the Newspaper Association of America collects statistics on newspaper circulation, pricing, recycling, etc.)
• Corporations (for example, information like "how many hours of television to women over the age of 40 watch?" would be valuable for marketing. If there is a market for corporations, publishers like Dun & Bradstreet or Standard & Poors may have collected the information)
• Media (look for polls, like Gallup)
• Scholars (look for quantitative articles that can lead you to data. Another source for data collected by scholars would be ICPSR)

Problems with Data Availability

• Many countries in the developing world do not collect statistics in as much depth nor as regularly as they are collected in the United States
• Statistics on illegal activities are always flawed and difficult to come by.
  • For example, a rise in drugs confiscated may not show an increase in the drug trade, but may indicate the increased effectiveness of law enforcement.

Advice

• Search for indicators BEFORE committing to a topic
• If the desired indicators are not available, determine whether it is feasible for you to collect and compile the data yourself
• If the data is not available, unless you are writing a dissertation, book, or an article to be published, change topics
  • If you are a student, you are learning HOW to do research and mastering research techniques. Do not commit to gathering massive amounts of statistical data.

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