Are we measuring the right things for broadband policy?

Remember your first few weeks of learning a language? The teacher would ask – where is the window? And you might answer – mon crayon (my pencil). Sometimes I feel like broadband stats are similar. We ask about broadband use in rural areas – and we get numbers of folks who can, do or won’t access broadband. To be fair, these answers aren’t wrong and they are important but are they the greatest gauge of broadband use in rural areas?

There was a recent article in the Washington Post that demonstrates the point (For minorities, new ‘digital divide’ seen). According to the article…

Latinos and blacks are more likely than the general population to access the Web by cellular phones, and they use their phones more often to do more things.

Unfortunately mobile access does not help when you need to fill out an application online, as the article asserts, but it can keep you up on latest entertainment Tweets. The article also points out the potential problem…

“I don’t know if it’s the right time to celebrate. There are challenges still there,” says Craig Watkins, an associate professor at the University of Texas at Austin and author of “The Young and the Digital.” He adds: “We are much more engaged, but now the questions turn to the quality of that engagement, what are people doing with that access.”

This article caught my eye. Also it sparked a conversation on an E-Democracy list called the Digital Inclusion Network, which included a response from Jeff Smith of CivSource that really struck me. With his permission, I’m including it below.

Firstly, great article – well written, well researched. Beyond touching on some very important issues regarding race and digital access, it articulates the other side of access, which is use.

For me, this article perfectly frames a long-standing problem in public policy: understanding access vs. use and making judgments about those uses.

Following trends in public policy, academic study and government services, most practitioners measure access, delivery speed & delivery accuracy. Usual questions in need of answering are: What percentage of eligible persons have access to this program? How quickly did they receive services and Did the right person(s) get the proper amounts according to his/her eligibility?

A perfect example comes from the Supplemental Nutrition Assistance Program (SNAP), otherwise known as food stamps. For years, government simply made food stamps available to those who were eligible and knew about it. Then a concerted effort was made to increase the amount of people who knew about the program. Metrics being monitored were about access, delivery speed and delivery accuracy. It’s not that these metrics do not make sense, but they’re inadequate to understand efficacy. Until recently, very little has gone into designing a SNAP system that can measure a person’s well-being after having used food stamps. This problem spans many human services programs, but a lot of work is going into better-understanding how aid is used.

Turning to mobile phone access versus use, my own research indicates that access only tells a fraction of the story. In a 2005 study, Leonard Waverman, Fellow at the London Business School and Dean of the Haskayne School of Business at the University of Calgary, found that, “A developing country which had an average of 10 more mobile phones per 100 population between 1996 and 2003 would have enjoyed per capita GDP growth that was 0.59 percent higher than an otherwise identical country.” After updating that study with data spanning to 2008, I found that increasing mobile phones by 10 per 100 people had a far smaller effect on per capita GDP growth (around four times less impact than the 2005 study indicated). This was in line with intuition. Dramatic increases of mobile phone use in the world’s poorest nations (The Gambia saw 0 per 100 in 2000; by 2008, the country had over 70 mobile phones per 100 people) did very little to translate to actual gains in per capita GDP growth i n those nations.

Does this mean that cell phones in poor countries have had no effect on making lives better or enhancing economic growth? No. But it means that simply giving access to technology will yield similarly simplistic results. In fact, a study about fish markets in India is a great example of how cell phones have had significant dividends for communities (users and non-users alike). See study pdf at: http://bit.ly/hhzAue

As more people look to delineate access and use, as Pew and others are trying to do, especially among different socio-economic classes or races, policy questions must try to capture some measures of well-being – not simply access and speed.

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