A map I made just went live at arenewableamerica.org .
This was a relatively small project, but there are two things I’m particularly happy with. One is that it’s the first time I’ve hand-drawn boundaries with enough detail to actually publish – all the convoluted parts of the Grid Campaign layer that don’t correspond to state lines are hand drawn from a reference map:
The other is that it’s the first time in years I’ve been able to work on promoting renewable energy. After leaving a PhD program, my first work outside academia was an internship for a local renewable energy nonprofit, but since then I hadn’t found a way to contribute to this field until this little project showed up. It feels good to circle back to a cause I’ve never stopped caring about.
One of the pleasures of working on FINclusionLab has been getting my work translated into the languages of most of the countries we cover: French, Spanish, and Turkish. By happy coincidence these are also most of the languages that I either speak or am making a serious effort to learn. I am not fluent enough in any of them to do the translating myself, but I can at least understand the translations that I’m applying, and read domestic press coverage when it comes out. It’s not always easy to get key stakeholders to actually use the tools we’re making for them, so it was particularly nice to see Mexico’s national bank trumpeting the release of the financial inclusion dashboards we made:
La CNBV presentó los mapas interactivos para el análisis de la inclusión financiera en México
[Google’s translation is not bad, albeit even wordier than an already government-speak heavy press release]
9 years ago, I was part of a small team that founded what is now Happiness Alliance. Our goal was to get happiness taken seriously as the primary objective of public policy, instead of the status quo in which governments maximise economic indicators without questioning whether they are even good metrics of the economy, never mind why we prioritise the economy above everything else in life. This is not a new idea; in fact I still think Bobby Kennedy said it best in 1968:
…Our Gross National Product, now, is over $800 billion dollars a year, but that Gross National Product – if we judge the United States of America by that – that Gross National Product counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage. It counts special locks for our doors and the jails for the people who break them. It counts the destruction of the redwood and the loss of our natural wonder in chaotic sprawl. It counts napalm and counts nuclear warheads and armored cars for the police to fight the riots in our cities. It counts Whitman’s rifle and Speck’s knife, and the television programs which glorify violence in order to sell toys to our children. Yet the gross national product does not allow for the health of our children, the quality of their education or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages, the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion to our country, it measures everything in short, except that which makes life worthwhile….
And yet, four decades later we still encountered endless skepticism about the whole idea. Those who accepted the premise kept telling us that it was futile because public policy interventions never make a measurable difference to happiness anyway.
Sadly, recent work by the Happiness Alliance (I am no longer involved, but cheer them on from the sidelines) has proven the skeptics wrong in the most negative way possible. We can now clearly see that the grinding awfulness of 2017 was not just in my head or my social circle, but has added up to a measurable decrease in self-reported happiness:
There are a couple of important caveats to understand here:
- This is a “convenience sample”, meaning it has not been weighted to be fully representative of the population –but there’s no reason to expect that 2017’s sample will have new or different biases, having been recruited in the same ways as previous years’.
- We don’t know where every survey taker was, so it’s impossible to compare US-based respondents with those elsewhere –but we do know that the vast majority of respondents are in the US.
It’s not a huge effect size—only 5-6%—but it is highly statistically significant, and when I remember all the people saying we’d never see any changes at all I can’t help but be impressed. And glad that this thing I helped start has had the staying power to be able to look at trends over years.
My biggest project for the past few years has been an ongoing series of workbooks about access to financial services in Africa, Asia & Latin America. I do this work as a subcontractor to an NGO called MIX, whose CEO recently gave an interview concisely explaining why we do this work and what it’s useful for. This paragraph gets to the heart of it:
FINclusion Lab creates single datasets and databases where previously siloes existed. For example, the data – which primarily includes access point location and demand-side data like population density, cellular coverage, poverty rates and the like – is usually found in project documents (PDFs), or separate online locations managed by regulators, or even individual Excel files from financial institutions. Bringing it all together in one place allows users – often regulators, financial institutions or others – to conduct analyses across different types of data including service points (geo-coded data), credit/deposit usage and demographics. It also allows users to visualize the data across geographies and drill down to more specific locales. Because we publish this data in a highly interactive format, users can explore the data based on their specific questions or interests. For example, a user can explore a particular district or type of financial service provider, or pick a reference period to view trends.
I’ve also been working behind the scenes on the infrastructure we use to conduct and share analyses, simplifying the toolchain and making updates & translations easier to apply. This included rebuilding a venerable Tableau template from the ground up, and here’s the first country workbook we’ve published in the new template:
I contributed some small pieces of code to the Fair Voting Systems map that Sightline Institute just published:
And from the context article, I learned of yet another delightful place name:
My coworking space published a nice little blurb about the disaster preparedness site I work on.