Public discourse is rife with arguments backed by economic research, and the phrases "economists claim" and "economic studies show" are commonplace. What tools do economists use to validate their claims and what are the limits of these tools?
The field of economics is most often categorized by subject of study (education economics, health economics, labor economics, and more), but that’s just one way to differentiate between types of economic study. Today, I want to discuss different types of economic research. Economic research can be broken down based on different research approaches: theoretical, empirical, and quantitative (and others that I won’t expand on in this post). Each approach has advantages and limitations, which I’ll describe using the example of universal basic income, which I covered in my previous post.
All economic research uses economic models, which are simplified descriptions of the phenomenon the economist is researching. A good model needs to omit confounding details in order to enable the economist to analyze the situation, while still including enough important details to be realistic. And still, the model’s predictions will always reflect the researcher’s working assumptions. One good example of a model is a geographic map. A map isn’t an exact description of the area it describes. Instead, it leaves out unnecessary detail while including enough information to help us get where we need to go.
Let’s return to the three types of economic research. We’ll start by expanding on theoretical research. In this approach, the economist describes reality using a mathematical model, which is often a collection of equations. This approach doesn’t require much more than paper and a pencil. The results of these models are straightforward and general, which is the main advantage of this approach to economic research. A theoretical approach can yield interesting qualitative insights in many fields, such as determining under which conditions the free market approach might lead to market failure. However, a theoretical approach isn’t appropriate for quantitative analysis. Our subject at hand, universal basic income, may have a positive effect on the economy because it provides social security to the unemployed, as well as a negative effect through the disincentive it presents to finding work. In this case, we need more than theory in order to determine if the advantages outweigh the disadvantages.
So what do we do when we want to study reality using data? That’s where empirical research comes in. This approach has skyrocketed in recent decades due to developments in the field and the creation of enormous databases. Advanced analysis methods allow us to differentiate between causation and statistical correlation - for example, the positive correlation that exists between the scope of an area’s police force and the amount of crime in that area doesn’t mean that police cause crime. Empirical research can not only determine causation, it can even quantify how exactly a policy affects various factors. But even the most advanced methods of analysis are only as useful as the databases they’re analyzing. Universal basic income as we define it - meaningful income for everyone for an unlimited period of time - is very expensive. Because no country has ever undertaken a project on the scale of universal basic income, there’s no existing data that can be analyzed to study the effects of such a project.
What does exist is data from various basic income experiments that were limited in scope and timeframe. These fascinating experiments show that in general, giving people (primarily poor or unemployed people) money improves their well-being. This result doesn’t surprise me, as I generally don’t believe that poor people use money unwisely. However, these experiments can’t teach us whether distributing funds without distinguishing between rich and poor, or for an unlimited timeframe,
would be good policy. I should note that in developing countries with very high poverty rates and very low cost of living, I believe that such a program could be funded by rich countries.
The third research approach that I’ll address is the quantitative method, which is the method I use in my own research. Like theoretical research, this approach begins with a mathematical model of reality. But instead of a mathematical solution like a theoretical model would have, a quantitative model is solved through computer simulations that allow us to consider various programs. In the case of universal basic income, our model allows us to study how people would respond to stipends of various sizes over time. The main advantage of this approach is that the computer allows us to simulate reality with lots of detail. The disadvantage is that the results vary based on the numbers we feed into the simulation.
As a pluralist, I don’t consider there to be a hierarchy between the various approaches to research. On the contrary, different approaches can complement each other and lead to richer understandings. In my next post, I’ll describe the research my colleagues and I have conducted on the topic of universal basic income.