In 2006, Greg Mankiw published an essay in the Journal of Economic Perspectives titled "The Macroeconomist as Scientist and Engineer." I really liked reading through this paper then and the more I think about it, the more I think Greg has struck a fundamental chord here. The distinction he makes resonates extremely strongly with me and my own experience with my field and how I view my own work. In this post, I would like to discuss Greg's essay, and give some thoughts on why I think this distinction is essential, why it is healthy to make it and why, historically, economists seem to not have paid sufficient attention to it.
Greg starts his paper by ackowledging how much economists want to pose as scientists:
Economists like to strike the pose of a scientist. I know, because I often do it myself. When I teach undergraduates, I very consciously describe the field of economics as a science, so no student will start the course thinking that he or she is embarking on some squishy academic endeavor. Our colleagues in the physics department across campus may find it amusing that we view them as close cousins, but we are quick to remind anyone who will listen that economists formulate theories with mathematical precision, collect huge data sets on individual and aggregate behavior, and exploit the most sophisticated statistical techniques to reach empirical judgments that are free of bias and ideology (or so we like to think).
I love Greg's writing, full of humour and self-deprecation. He mocks economists for posing as scientists, but immediately includes himself in the lot, so that the blow is not so strong. We even empathize. But self-derision aside, I think that economists have a right to pose as scientists. Economists are scientists because they want to understand how men behave, make decisions and interact with each other and with their envitonment. Economists, along with sociologists, and psychologists (and maybe anthropologists), are part of behavioral social science, in my opinion.
Then Greg goes on describing now why economists are also engineers.
Having recently spent two years in Washington as an economic adviser at a time when the U.S. economy was struggling to pull out of a recession, I am reminded that the subfield of macroeconomics was born not as a science but more as a type of engineering. God put macroeconomists on earth not to propose and test elegant theories but to solve practical problems. The problems He gave us, moreover, were not modest in dimension. The problem that gave birth to our field—the Great Depression of the 1930s— was an economic downturn of unprecedented scale, including incomes so depressed and unemployment so widespread that it is no exaggeration to say that the viability of the capitalist system was called into question.
Again, Greg is both fun and efficient. But he is also to the point. Economists are engineers because they deal with pressing social issues: how Central Banks should set the interest rate? How to forecast and respond to crises? How to decrease unemployment? I would add that this is not limited to macroeconomists. In microeconomics, we also have pressing policy questions to solve: How to set taxes? How to organize the education system? How to curb pollution? How to best organize markets?
Greg goes on with the aim of his essay.
This essay offers a brief history of macroeconomics, together with an evaluation of what we have learned. My premise is that the field has evolved through the efforts of two types of macroeconomists—those who understand the field as a type of engineering and those who would like it to be more of a science. Engineers are, first and foremost, problem solvers. By contrast, the goal of scientists is to understand how the world works.
I think Greg is really on to something big here. I think this distinction between scientists and engineers is key. To me, it has been summarized extremely efficiently by a famous quote by Neil Armstrong: "Science is about what is and Engineering is about what can be."
To Greg, the history of macroeconomics has started as an engineering venture that has slowly drifted into a more scientific ground.
The research emphasis of macroeconomists has varied over time between these two motives. While the early macroeconomists were engineers trying to solve practical problems, the macroeconomists of the past several decades have been more interested in developing analytic tools and establishing theoretical principles. These tools and principles, however, have been slow to find their way into applications. As the field of macroeconomics has evolved, one recurrent theme is the interaction—sometimes productive and sometimes not—between the scientists and the engineers. The substantial disconnect between the science and engineering of macroeconomics should be a humbling fact for all of us working in the field.
Science has very often started with a strong applied question, before drifting away into more abstract areas. Think of the theory of optimal transportation that started with Monge - as a way to displace rocks from a quareer to a hole in the ground - has developped to an abstract and very general modern theory.
Though I understand it, I disagree with Greg's last comment. It might seem humbling that the most recent theories do not find their way into applications, but I think it is rather healthy and the sign of a maturing science. In the other sciences, scientists are always extremely cautious when discussing the potential applications of a major fundamental scientific breakthrough. The discovery of how a virus operates does not immediately pave the way for a vaccine. Decades of research are needed. First, the scientific result has to be reproduced a sufficient number of times so that we know it is correct. Second, a feasible way to exploit this result has to be found and its efficiency evaluted. This is the work of what I call engineers, in that case doctors. It would be crazy to try to use the last scientific theory/hypothesis as a workhorse for policy purposes. Which engineer uses string theory today?
My feeling is that hard-pressed by politicians to find anwers to policy questions, economists have always made useful simplifying assumptions about human behavior. At some point, these assumptions seemed to be shaky, or some of the conclusions did not seem to rigorously be drawn from them. Then economists entered a phase of rigorous mathematisation and axiomatisation, which is the first leg of any science, the theoretical one. This has produced amazing theoretical results. But until recently, economists did not make a lot of use of the other leg of any science: the empirical leg. Empirical validation is something different, a way to tell what's wrong, it is a way to discriminate between all the theoretically sound theories we have that make different empirical predictions. We are in the middle of an empirical revolution in economics (some have called it the credibility revolution). Economics is slowly starting to use data to discriminate between competing theories. In the process, I think it would be extremely useful to distinguish between the use scientists and engineers make of the data. For most of its existence, economics have used the data with mainly one aim in mind: estimate the values of theoretical parameters that theory did not provide. This is extremely important and we have made a lot of progress in this direction. Extremely beautiful theories have been developed, but this is not what I have in mind when I think about how engineering and science use data.
Engineers use the empirical data to check whether their devices work whereas scientists use to data to refute theories.
In the following posts of this series, I will examine some of my favorite results in economics that use data in a engineering or a scientific fashion. I will also try to give a sense of what empirical economics and econometrics have achieved up to now, and why they have mostly focused on the limited goal of estimating theoretical parameters.
As a conclusion to this post, I would like to quote the last part of Greg's introduction to his essay:
To avoid any confusion, I should say at the outset that the story I tell is not one of good guys and bad guys. Neither scientists nor engineers have a claim to greater virtue. The story is also not one of deep thinkers and simple-minded plumbers. Science professors are typically no better at solving engineering problems than engineering professors are at solving scientific problems. In both fields, cutting-edge problems are hard problems, as well as intellectually challenging ones. Just as the world needs both scientists and engineers, it needs macroeconomists of both mindsets. But I believe that the discipline would advance more smoothly and fruitfully if macroeconomists always kept in mind that their field has a dual role.