Economics & Reason: Reasoned Leaders

“All our knowledge begins with the senses, proceeds then to the understanding, and ends with reason. There is nothing higher than reason.”

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Recently, I sat in on a set of community leadership meetings in a major metro area – one that has a rich collection of community-based non-profits, well resourced municipal government staff and high capacity leadership, and an engaged business community that contributes and supports a range of intermediary organizations that help create vibrant public-private partnerships.

The groups were convened across sectors to consider how to enhance pathways from poverty and to broaden economic mobility. Very quickly, the meeting went the way that many do - the stakeholders agreed on many of the symptoms - too many people stuck, too few legitimate ways for someone to advance from low or moderate incomes, not enough mobility or resilience. There wasn’t great agreement on the causes – some said it was a lack of basic education, others missing advanced and innovative skills, for some it was many of the challenges proximate to work - poorly connected transportation, a lack of childcare, unaffordable housing, or bad healthcare. There didn’t appear to be a clear path to come to agreement – when a bigger issue started to exhibit itself.

Each group was coming to these conversations with a different fact base. In the meeting, three different unemployment rates were cited – and they were quite different. And technically none were wrong.

One was using the metro level estimate from the BLS – that roughly conforms to a release schedule similar to the unemployment rate that is seen in the monthly jobs report. Two other different groups referenced an unemployment rate that were from the American Community Survey – a less timely survey, but one that offers greater granularity – including reports of neighborhood conditions, but sometimes averaged over several years.

The conversation had challenges moving forward - there was confusion about how the number could be different, and some mistrust in the information. How could someone think that the unemployment rate was half as much as someone else? How could a low rate actually speak to the conditions of a community based group that operated in high unemployment communities. No one in the meeting was wrong, but it was hard to come to a shared understanding of the overall conditions.

The group did ultimately come to some agreement, but it was more difficult than it needed to be.

All too often public discourse and strategy building doesn’t ever reach the level of rigor or critical thinking that it needs to.

To explain what I mean by this I will hope too pull on a few things all focused on the development of insights that would help people and communities develop strategies, and hopefully systems, that drove economic growth and pulled more people in to good jobs and family sustaining work.

In my time working in local economic development, in academic research, and in applied research, too often leaders do not engage data, research or analysis from a critical perspective. Often, stakeholders come to conversations ill equipped to engage with information critically — they cannot engage with the research and analysis that people like me have produced because it isn’t in their day to day jobs. This is for two reasons –

• First researchers often create analysis and work that doesn’t hit the mark - too many researchers are deeply studying topics that have little relevance to the real world.
• Second, when they do study policy relevant research, they struggle to make that analysis accessible and connected to the problems and challenges that policymakers, practitioners, and people are struggling with – it ends up too technically sophisticated, too methodological, and too light on real world application.
• Third, is the misalignment between rigorous research methods and the utilization of data on the ground – too often the methods of research that aim to identify causality and develop directional insights matter less to practitioners and policymakers, and findings of this type of research become over specified in practice.

With others, I see a version of a confirmation bias is at play — practitioners and researchers will come to their work or broader conversations equipped with the data points and evidence that help to confirm their world views. They aren’t allowing data to help inform the story and drive the positions that they take. With the world awash in data, increasingly, people can “torture data” until it says what they want it to – using data to confirm a position, rather than use it to better understand the world.

Immanuel Kant thought and wrote quite a bit about reason – considering it the highest form of of knowledge. Kant wrote, “All our knowledge begins with the senses, proceeds then to the understanding, and ends with reason. There is nothing higher than reason.”

My hope is that we can move from reaction to understanding and ultimately build greater reason among workforce developers, educators, economic mobility practitioners, and the researchers that support them.

I am starting to write this with two goals. First, I want to expand the understanding of research and its application to real world uses in policy making and application to practice. Second, I want to create a stronger understanding of the use cases and the types of research that would be most helpful to expanding economic opportunity. I’ll lean on new insights as well as the two decades of experience I have working as an academic and applied researcher, a local economic development practitioner, and as a researcher at the Federal Reserve in macroeconomic policymaking settings.

Song That Kept Me Working This Week

A weekly featured song that kept me working! Many are about work.

“Green Rocky Road” by Spirit Family Reunion

Green Rocky Road is a modern adaptation of a folk song – the lyrics don’t make a ton of sense. It is generally from the era and style of songs like “Skip to My Lou” - rhyming words and short phrases that make up a simple folk song. So not deep meaning.

But, it is a wonderful version the “folk process.” To pull on the “shared understanding of data” discussion from above, imagine the folk process as a collection of iterations and better understandings of a piece of music.

Pete Seeger described the folk process as learning and adapting and changing commonly used songs or older songs to make them to one’s use and style. I love the idea of the folk process – it takes common knowledge and shared experience, but then allows for the adaptation – and improvement of that knowledge for an individual’s taste and context.

As I think about all of the three groups trying to understand the labor market, I wish that instead of some of the stutter steps they had, they understood they had a set of common ingredients that they could adapt to their individual efforts. And these common ingredients help to create common ground across groups. Green Rocky Road has prominent recordings by Van Morrison, Dave Von Ronk, and Oscar Isaac. Same ingredients, same construction, completely different utilization and application by Spirit Family Reunion.

We can all sing from the same songbook – in our own style and to meet the diverse needs of the groups that we serve – but it starts with some shared knowledge.

Maybe this is a stretched metaphor, but the song kept me working this week.

Data of the Moment

Keeping on the theme of shared understanding, the data of the moment is actually a lack of data. Because of the federal shutdown, initially there was to be no October jobs report from the Bureau of Labor Statistics because of the Federal shutdown. The September report was released about a month and a half late, and showed better topline signs of hiring than the months preceding. There were signs of weakness though - 20,000 jobs lost in professional services and a slight increase in the unemployment rate in September.

Mid-December brought a combined jobs report for October and November. The report presents data for the month of November (though the release was delayed by a week and a half, and the surveys may have been fielded at somewhat non-comparable times). The report does eventually describe changes from September to November and suggests significant job loss in October (attributable to federal government job loss from layoffs and deferred separations that happened in October).

What do you do when there is limited data or breaks in a time series? First start by understanding what you do not know specifically – in this case of missing monthly data reports, statistical weighting methods are used to impute the portion of change that happened in October. Next, understand your use case. Depending on the work that you do, the limited immediate data on the month of October may or may not be material. Investors utilizing macroeconomic investment strategies may be one of the most affected – up to the moment data is essential for managing strategic investments. For researchers, they must acknowledge and understand that the measurement of change over that period is different than it was other months. For service providers or practitioners, the frequency of change may not be a material to their work – or they may be identifying trends that lead data through interactions with clients or the people that they serve. (More on the use of leading qualitative and quantitative data in the future…).

Understanding what data tells us, how its collection changes and how that informs what you are doing is critical to making it advance your work. Too often we aren’t keeping ourselves grounded and focused on what we learn from data and how to use or produce it.

Thanks everyone for reading. Have a great new year. More soon.

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