In my blog last week I mentioned the importance of using data in journalism and using evidence in your argument. While the issue of unsupported arguments needs to be addressed, journalists need to make sure that economic data is used properly and correctly.

In several of my blogs, I’ve talked about issues with variables in data, like the problem with the poverty measurement and unemployment, which can be skewed because of discouraged workers and the labor force participation rate (read my post “Seeing Past the Unemployment Rate”). It is obvious that any side, to prove any issue, will use economic data. As journalists, we need to make sure that the data we use is correct and accurate. Here are some ways to make sure that the data being used in economic articles are beneficial.

Always Pay Attention to the Measurement

Often economic measurements lack an important piece of information. For instance, the exchange rate commonly talked about by the media references the nominal exchange rate, but it is often the real exchange rate that should be referenced. The real exchange rate is the relationship between the domestic country’s goods in terms of the foreign country’s goods. However, the nominal exchange rate is the relationship between the domestic country’s currency and the foreign country’s currency.

Data Used Incorrectly

Data gives the impression that what you’re saying is correct, that it can’t be refuted. I can’t emphasize how wrong that is. Data can be prone to misinterpretation and construed in ways that is not intended, especially if no explanation is given. As an economist or journalist, we must all question the data surrounding us.  A lot of economic data is revised after more information is discovered. This means that journalists should be skeptical of all economic data, no matter where it’s from, be it the government or a private company.

What does the data actually mean?

There may be a reason behind the data that isn’t immediately clear. One big problem with the economy is the multitude of variables that can influence data. This makes it incredibly hard for economists to organize and interpret statistics, and even harder for journalists to explain the issues with data to the audience.

Economic data is changing, statistics are revised, and variables can be missed. As economic journalists we must analyze and decipher the data, but also keep in mind that data isn’t the be-all and end all.

What data have you encountered that has holes in it? What kinds of variables have been missing from data?