Economists have a useful benchmark and so can you!
Why do we spend so much time on competitive models?
Welcome to another edition of Economic Forces. I am Josh Hendrickson. You might remember me as the guy that you muted on Twitter or the person you have to tolerate in order to read Brian’s posts. In any event, we are having fun with the newsletter and we hope that you enjoy it, share it, and subscribe.
Last week Brian defended supply and demand as a useful tool, even for labor markets (*audible gasp*). This week, I am also going to defend models of competitive markets but from a different perspective: as a vital benchmark.
Why do we spend so much time talking about competitive markets? When students sign up to take their first microeconomics course, they will typically spend a good portion of that semester on the perfectly competitive model and applications thereof. When graduate students show up for their Ph.D. macro courses, the first business cycle model that they learn is the Real Business Cycle (RBC) model. This model is a dynamic, stochastic general equilibrium model with competitive markets. It seems that whether you are starting out as an undergraduate or a graduate student, competitive markets are inescapable.
There is no doubt that some students and scholars think that this is overkill or unnecessary. In fact, it has become routine for people to complain that economics courses need to be more “realistic” or “data-driven” (who gets to decide what is realistic is rarely addressed, nor is the fact that there are often disagreements about what the data tell us). Recent research on the minimum wage has led people to argue that any discussion of labor markets in introductory classes should be based on monopsony models rather than competitive models. Otherwise, we risk teaching students the “wrong” things about labor market policy. (Brian’s previous post already addressed this point from a different perspective.)
I disagree with this growing sentiment that there is something wrong with what we teach. One of the most important questions that economists ask is: “compared to what?”
Economists are fundamentally preoccupied – and rightfully so – with counterfactuals. If you ask me to tell you the effect of a tax on capital, my first question should be to ask, “compared to what?” Do you want me to tell you the effect of a tax on capital in comparison to a world with no taxes? To a world with income taxes? To a world with consumption taxes? I need some benchmark for comparison.
If we start our Principles of Microeconomics course with a discussion of monopolies, it is true that we can get a sense of how firms make decisions when they have market power. Maybe it is more “realistic” to start with market power. However, how do we teach students who have never taken an economics course in their lives about the deadweight loss of monopoly? This deadweight loss is the value of trade that was lost due to the monopoly, but what does it mean that this trade is lost? A loss relative to what? Well, a loss relative to competitive markets in which all gains from trade are exhausted in equilibrium.
The value of the competitive model is its use as a benchmark. A proper discussion of the competitive model provides a rich understanding of how prices coordinate the behavior of buyers and sellers to get resources where they are valued most, despite the fact that both buyers and sellers are only concerned with their own objectives and constraints. The model also illustrates what economists mean by “gains from trade” and facilitates a corresponding discussion of efficiency.
With this model as a benchmark, one can then contrast this benchmark with a world of externalities, taxes, price controls, a monopoly, and countless other examples. However, these effects are all relative to the competitive model. It is also useful to note that this competitive model benchmark provides a lot of insights even when its assumptions are not technically satisfied.
In macroeconomics, the RBC model is subject to many of the same criticisms. Critics argue that the model is not useful for describing actual business cycles. Why should we spend so much time teaching graduate students about a model that implies that business cycles are efficient responses to random changes in tastes and technology and that does not seem to fit the data? After all, most of these graduate students have already learned about deviations from competitive markets. Why do we still treat them the same way as introductory students?
Again, the answer is that the RBC model serves as a benchmark. There are a lot of conjectures about the causes and propagation of business cycles in the literature. How can we judge the validity of these claims? Of course, we can go out and do empirical work, but many hypotheses are common across multiple business cycle theories. If two theories produce observationally equivalent predictions, how can we resolve this?
To sort this out, it helps to write down a formal model in which the similarities and differences with other models can be explicitly understood. This model outlines the mechanisms through which business cycles propagate. Furthermore, to judge whether such propagation mechanisms are important, it is necessary to have something with which the implications can be compared. The RBC model has served as this point of comparison. Since the RBC model has competitive and complete markets, the inefficiency of business cycles can be measured by using the RBC as a benchmark. In addition, if your model does not add much insight relative to the RBC model, how valuable can it be?
Economists use models to help us understand something about the real world. Our objective is to gain some intuition from the models. But large-scale models, while they might fit the data better, are not equipped to provide this intuition. There are too many moving parts. Thus, isolating the propagation mechanism that the researcher thinks is important and incorporating it into the RBC model can provide some of this insight and intuition. With that intuition established, the researcher can proceed to the larger-scale, or more “realistic” model.
The competitive model and the RBC model are just two examples of benchmarks. There are countless other examples. Ricardian Equivalence holds that governments should be indifferent between generating revenue from taxes or new debt issuances. This is a benchmark. The Modigliani-Miller Theorem states that the value of the firm does not depend on whether it is financing with debt or equity. Again, this is a benchmark. Regardless of what one thinks about the empirical validity of these claims, they provide useful benchmarks in the sense that they give us an understanding of when these claims are true and how to test them. By providing a benchmark for comparison, they help us to better understand the world.
With all that being said, a world without “frictions” is not always the correct counterfactual. In fact, in a number of my subsequent posts, I will argue that researchers too often rely on competitive markets as the relevant counterfactual when it comes to political economy. As a result, they tend to overestimate either the costs or the benefits of some proposed policy.
Nonetheless, this distinction highlights an important point. The proper counterfactual for a researcher is not necessarily the proper counterfactual for the classroom. In the classroom, the competitive model is often the most useful because it provides both powerful insights and a useful foil. A mastery of the competitive model is the foundation for learning to “think like an economist.”
I want to add an anecdote to this discussion. Last week, I had a long discussion with an economist about how graduate students (and undergrads!) dismiss benchmark models too quickly and instead go to complex models with too many parameters, too many equations, and have no idea what is going on or how the model is actually solved (because the computer does it). I think this is true to some extent. If you solve an RBC model with tax and productivity shocks and calibrate it correctly, you'll get practically the same elasticity of investment with respect to taxation as you would with a far more complex model which may as well be written in Sumerian for all the good it does in terms of understanding and communication. Compared to the more complex model, there is clearer understanding of the processes at work, which in turn leaves one more able to think and communicate about possible shortcomings. Sure, there tradeoffs, but the benchmark models get short shrift.
I agree that the RBC model can serve as a useful benchmark. However I agree with Caballero (2010) who outlines that one failure of macroeconomists to identify the GFC was our desire to build models with "one-deviation at a time". Which I think as a first pass is a fine way to go about building models, as you say we understand the propogation of a shock through a new mechanism when it is only one deviation from a model we understand. In the real world however we need a model with a large number of deviations from the RBC model (all the bells and whistles). If we discount these larger models as not parsimonious enough then as policy makers we are really stuck with a suite of models that in a few different dimensions are only one deviation away from the RBC model.
Ultimately then we are leaving it up to the judgement of the policymaker to weigh up the evidence of a range of simple models that deviate from the RBC model in order to set policy, a process that has a complicated model implicit in the policymakers brain and is therefore even less parsimonious than a full bells and whistles DSGE! With these large scale DSGE models the RBC becomes a less useful counterfactual for analysing shock propagation mechanisms.
Great post and am loving the blog!