Fog of uncertainty
The most important number over the last few days for any country in the world is the number of COVID-19 cases. This number determines everything in our daily lives.
To go out and shop, consumers check the news for the number of COVID-19 cases to gauge the risk of infection.
Businesses gauge the risk of reopening their stores with this number. If the number is too high, they postpone reopening, and if it low enough they reopen.
The number of COVID-19 cases in the past few days is an incredibly important number, and like many important pieces of information it can be analyzed using economics.
Positive externalities
Imagine you started a company to provide data on COVID-19 numbers in a place which does not have them. Every single day, you go to the labs testing for COVID-19 and ask them their numbers. At the end of the day you collate it, put it in an excel file, and charge people for it.
But it is hard to keep this number a secret. If you send it to one person, they can note down the number and forward it to everyone they know. Then, everyone knows the number and benefits from it. But you, our poor COVID-19 data collection entrepreneur doesn’t benefit from everyone’s knowledge of the number.
They know it, but you don’t make any money off their knowledge which you worked so hard to get. A third party - someone unrelated to this transaction - benefits from your work of collating data, running around to different labs and asking for numbers.
This is what is called a positive externality. A third party benefits from a transaction between two people.
Everyone can get it - and its not the virus
You cannot easily exclude people from knowing the number of cases. As shown above, the number can go around and its not easy to stop other people from knowing it.
But there is another interesting aspect of it. Unlike other economic goods like cars or pencils, one person using this good (information) doesn’t make any of the others worse off. If you know that there were 188 people who had tested positive for COVID-19, that doesn’t stop me from knowing it.
So, while being non-excludable, data on COVID-19 is also non-rivalrous. If one person uses it there is no harm to the others who use it.
Data is a public good
So, COVID-19 data meets all the criterion for being a public good. It is non-excludable and non-rivalrous. There is a free rider problem and this is usually solved by governments taxing their population and spending money from this to pay for COVID-19 data collection.
Just like COVID-19 data, many other forms of data are public goods. Economic statistics are public goods because they meet the same criterion of non-rivality and non-excludability as COVID-19 data.
Steering through the fog
We live under a fog of uncertainty today. We don’t really know the actual risk of COVID-19 in different places, and we do not have a good idea of the economy’s changing picture day by day.
Now that we know that data is a public good, there are many places where governments can do better. Two specific places are of high importance. They are high frequency economic data and public health data.
High frequency economic data
Most economic data is released quarterly or annually. Numbers like GDP and unemployment come out once a quarter or once a year in many places. Only in the United States, Canada and the UK jobs data is released every month. But during COVID-19 it was clear that even one month was too far apart to get data.
While yesterday’s jobs report in the US showed positive signs of a recovery, this was largely overshadowed by several states closing their economies due to a second wave of the coronavirus. While there are other indicators of jobs like unemployment filings, they are of low quality and do not accurately reflect the situation on the ground.
For developing countries however, monthly data on jobs would be a god send. Several developing countries such as India, Indonesia and Malaysia do not have reliable economic data. What does exist is plagued by data quality concerns.
Public Health data
One of the major concerns felt by people daily is the risk of infection when going out for daily activities such as exercising and shopping. This can be reduced if governments (or charities) collected and gave data about hospital capacity with regards to ventilators, ICUs and bed capacity. Along with that, data on recorded transmission of the virus would be extremely helpful in determining the risk of COVID-19 transmission for the general public.
To use an example of going on a taxi, people do not know if going in a taxi would expose them to COVID-19, and so they do not go on the taxi to avoid the risk hurting both the people who are scared and the taxi drivers whose incomes are reduced.
This could be reduced if information on transmission of the virus, along with an index of how risky certain activities are would be published by governments who already have the data on transmission.
To conclude, data is a public good and should be treated as such. We’d all be much richer and better off if this data was provided to the public