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Economic Data-Classes To Pay Attention To During The COVID-19 Pandemic

There are plenty of individuals and organizations compiling data on the spread of the disease and the healthcare response, but less so on the economic side -- especially when it comes to real-time data, i.e., not waiting for monthly government statistics or quarterly financial statements.

Based on the data we've seen and the data science we've done here at Quandl, plus our conversations with clients in the finance industry, I would say there are 5 categories of data (and the related questions they answer) that are the most interesting and important right now:

1. Supply Chain:

Disruptions and shortages, logistical issues, inventory buildup or depletion etc. Global commerce is tightly coupled and highly optimized, is the system sufficiently resilient to this kind of shock? We're monitoring a bunch of supply chain and logistics datasets to answer this,

2. Small Business Performance:

Obviously getting hammered now with closures, lost revenue. Small biz is the driver of local economies and employment; will government relief reach them in time? Can firms survive weeks to months of shutdown? Can they reopen easily afterwards? We've got a few small business datasets that track payroll, revenue, closures, payments etc that we're watching for these answers.

3. Employment:

Unprecedented numbers right now, driven by entire sectors going into recession (travel, hospitality, entertainment), hourly worker layoffs, loss of income for small business, freelancers, gig workers, self-employed, contractors and so on. We're monitoring hours worked and hiring patterns, both pictures are pretty bleak.

4. Consumption:

Clearly some headline categories (hotels, airlines, restaurants, concerts) are being decimated but what about spillover into other categories of consumption? Discretionary spending is down (a lot), does that stay the case or will we see a snap-back of pent-up demand? We're watching a wide range of data here -- everything from e-commerce transactions to airline bookings to new car sales to social media sentiment and confidence.

5. Credit:

This is the wild card. If employment falls, consumption falls, businesses close -- sooner or later people and firms are going to fall behind on debt payments (and there's a lot of debt / leverage in the economy right now). The Fed and Treasury are trying hard to head this off; will they succeed? Or will lenders get burned and/or pull back? If credit dries up, that transforms the small business shock into a more general financial shock. Conversely, if government intervention is effective at bridging short-term liquidity needs, we could see a tremendous amount of catchup growth in Q3-Q4. So we're watching different credit and payments metrics as an early indicator here.

So, lots of different currents pulling the economy in different directions, which makes it hard to identify a top 3 or even a top 10, but I do think the category-focused approach has merit. We're getting a huge amount of client demand for data that offers any sort of insight into these themes, as you can imagine. It's also a very rapidly-evolving situation: the data that's most relevant today could be old news by next week (literally! the news changes so fast!) so we're working to stay on top of that. Interesting times to be sure!


Abraham Thomas is the cofounder and chief data officer of Quandl, a company he and cofounder Tammer Kamel created with the goal of making it easy for anyone to find and use high-quality data effectively in their professional decision making. Previously, Abraham was a portfolio manager and head of US bond trading at Simplex Asset Management, a multi-billion-dollar hedge fund group with offices in Tokyo, Hong Kong, and Princeton. He holds a degree from IIT Bombay.

You can access Abraham’s COVID-19 Economic Impact analysis to learn more about how data is illuminating our current economic environment.

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