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Our minds are so good at imagining things that once mine had begun to think about the end of my run, reaching the end of my run—and therefore the end of my pain—was all I could think about. The idea that my pain was about to end became so enticing that my ability to withstand it dramatically declined.
Of course, the amount of pain I was feeling at that moment was no worse than the amount I'd felt the moment before. What changed was my ability to handle it. Why? Because when my mind started to visualize the end of the run, it shifted from managing the pain my body was feeling to preparing for it to end. And in preparing for it to end, its ability to resist the influence of that pain rapidly fell apart.
I think this sequence occurs often in other areas of life as well. From the moment we embark on any endeavor numerous reasons immediately present themselves that push us to quit (e.g., fear of failure, fear of success, laziness, failing to believe in ourselves, etc.). One way of thinking about why we don't quit is that other, more powerful motivations to keep going command our attention more (e.g., the desire to improve our level of fitness or reduce our level of fatness). The idea to quit remains present in our minds as long as reasons to quit exist, but the likelihood that we will quit only increases when we start to pay attention to them.
We don't end up quitting because we find ourselves facing too many obstacles or obstacles that are too strong. We end up quitting because we're too weak. I firmly believe, however, the inflection point at which we can no longer avoid paying attention to the idea of quitting—that is, the point at which our strength fails us—can be changed. We can become stronger by challenging our weakness even if at first we don't succeed. Increasing resilience, both mental and physical, is an arduous process that's rarely linear. That is, it's a process filled with stops and starts, periods of progress and periods of regression.
I quit running before I finished my route many mornings at first. But the benefit of the effort I made in running up to the point I quit weren't nullified by my quitting. Those efforts strengthened me enough over time that eventually I became capable of meeting my goal consistently, i.e., reached my previous level of fitness. But only because I didn't allow my quitting on any one day to stop me from going back out the next.
This same principle applies any time we make to break new ground in any arena. The key to success is simply to keep coming back for more—even if you quit short of your goal several times over—until you find yourself strong enough not to give in when your body or your mind are telling you to. Just because you do quit—even a hundred times in a row—the experiences you have up until the various points at which you do are the very things that develop the resilience you need to win in the end. What if you need to fail a hundred times to gain the ability to succeed on the 101st?
The risk of becoming grounded in self-defeating thoughts when you're defeated by yourself (i.e., you choose to give up), we should note, is far greater than when you're defeated by something else . It may very well be psychologically easier to get yourself to try again in the latter case than in the former because in the former you're far more likely to buy into a narrative that defines you as a quitter and therefore undeserving of success.
But this is a false narrative. Even if you failed because you chose to give up, you can still try again. You must constantly remind yourself that having tried at all has increased your chances of ignoring the voices in your head urging you to quit the next time. Always remember, the key to victory is strength, and the key to developing strength is trying again, no matter what the reason you failed before.
If you enjoyed this post, please feel free to visit Dr. Lickerman's home page, Happiness in this World.
In three recent posts (here, here, and here), I have argued that macroeconomics is deeply flawed and not a science. Or at least not scientific in the conventional sense of the word. Let me try to make my claims a little more precise and react to some of the comments. Just because economics isn’t like physics doesn’t mean it’s useless. So I will also try to talk about what it is useful for.
Hayek condemned scientism–the use of the tools of science to give a field such as economics the aura of science without it’s predictive or descriptive power. He didn’t just say this was a waste of time, he said it was dangerous because it led to a false sense of precision and understanding. The way I understand this (and I agree with Hayek) is that the tools of physics–advanced dynamic equations that treat the economy as a planetary body or even a group of planets interacting, is not just wrong, but deeply misleading.
Was Hayek right about this? I think so, but the defenders of the mathematical approach to either macroeconomics (Bob Lucas, say) or microeconomics (the game theorists, for example, pick your favorites) would argue otherwise, saying either that we haven’t quite mastered the full set of equations but will eventually, or that we are close enough now and sometimes, the unexpected comes along and we have to modify our models. I would also include John Taylor in this camp, as someone who argues that the recent macroeconomic downturn can be explained by a failure to follow the Taylor Rule.
I have a lot of respect for many of the practitioners of the theoretical art. But I think the burden of proof is on them, not on the skeptics, to show that our understanding of the macroeconomy is anything akin to our understanding of the solar system or a similar system that physics understands. I would also include in this camp, Austrians who tout versions of Hayek’s or Mises’s models of the business cycle as the “right” answer to the boom and bust cycle. I have learned a lot from Austrian business cycle theory, from John Taylor’s writings on monetary policy, and from Robert Lucas. They are not wrong. But they are not right either in my opinion.
All of these models enhance my understanding of the complex system called an economy, but none have a unified, consistent model that can explain the movements of macroeconomic aggregates. They also are unable to convince people in the other camps nor is it clear that any data or empirical test would lead to ideological or methodological conversions. This is not comforting for those who claim any sort of scientific mantle for macroeconomics.
I think the later Hayek would agree with me and that is how I read his Nobel Prize lecture. It is also how I read Bruce Caldwell’s take on Hayek’s business cycle work in the 1930′s that culminated in The Pure Theory of Capital and his failure to respond directly to Keynes’s magnum opus, The General Theory. I think Hayek thought he was going to outdo Keynes and produce a better theory of the business cycle, one that was more consistent, more general, and one grounded in individual decision-making. What he did may have been better than Keynes’s so-called, general theory, but I don’t think Hayek found it very satisfying and rather than continuing to improve it, he abandoned macroeconomic theory for a long time and turned to other issues. (Next week’s EconTalk with Bruce Caldwell touches on these issues.)
So have the moderns improved on the Keynes and Hayek models of the 1930s? Perhaps, but that’s a very modest standard. My claim is that seventy years of macroeconomic theorizing has led to a better understanding of many macroeconomic phenomena. But it has not yielded a general theory that can explain the causes of macroeconomic problems or the likely success of proposed solutions.
I will say it again in a simpler way. There are a lot of things we understand today that we didn’t understand in the 1930′s. But there are still many things we don’t understand. Will we ever close that gap? One view would argue that it is simply a matter of time and data accumulation. When major downturns are infrequent, they are going to be hard to explain because we have very few data points. The second view, which is the Hayekian view, is that the system is simply too complex to model with too many unobservable variables to allow systematic understanding. Thus we reach scientism–we are fooled into thinking that we are making progress when in fact we are misleading ourselves.
Another way to say it is that modeling economic behavior using the tools of the physical sciences in hopes of attaining the holy grail of a full-blown, accurate, model that can track the ups and downs of a complex modern economy is not just a fool’s quest, but a dangerous one.
I have often said that economics, to the extent it is a science, is like biology rather than physics. Let me try to make that clearer. By biology, I do not mean the study of the human cell, which we have made a great deal of progress understanding though there is more to learn. I am thinking of biology in the sense of an ecosystem where competition and emergent order create a complex interaction of organisms and their environment. That sounds a lot like economics and of course it is. But we would never ask of biologists what the public and media ask of economists. We do not expect a biologist to forecast how many squirrels will be alive in ten years if we increase the number of trees in the United States by 20%. A biologist would laugh at you. But that is what people ask of economists all the time. Economists should be honest and say that the tasks they are often asked to do are outside the scope of economics as we know it and perhaps outside the scope of economics as it will ever be known.
Is economics a science because it is like Darwinian biology? Darwinian biology is very different from the physical sciences. Like economics it is a very useful way to organize your thinking about complex phenomena. But it is not a predictive or very precise science or whatever you want to call it. Before seeing any direct fossil evidence, no biologist can tell you how long the giraffe’s neck was ten million years ago. They cannot make accurate backcasts of any precision such as the year that the forerunner of the giraffe began to lengthen its neck through natural selection. It cannot model why the giraffe’s neck isn’t longer. Darwinism, like much of economics, exploits tautological reasoning. If the fossil record is incomplete or shows no change or vast periods or the pace of change is inconsistent with the fossil record, the theory is not discarded but modified with the concept of punctuated equilibrium. Is punctuated equilibrium true? There is no real way of knowing. It is our best hypothesis given very limited data. Is it a science? Sure. But it is a science that is unlike physics. That’s OK. It is still a very useful way of organizing one’s thinking about evolution. And the “imperfection” of biology is fine unless you really want to know when the elephant got his trunk. Then you are in unscientific territory. It doesn’t matter whether our understanding of natural selection is imperfect or that we simply don’t have enough fossil data. Biologists understand the limits of their field.
So the fact that economists did not foresee the Great Recession with any precision and have failed to model accurately the recovery does not mean that economics or even macroeconomics is worthless. My claim is simply that we should recognize the limits of reason in analyzing complex systems with millions of decision-makers, numerous feedback loops, institutional features (synthetic CDOs, the repo market, the willingness of the Fed to bail out bondholders) that are difficult to model in tandem with the outcomes we care about. Finally, there are important variables that we cannot observe directly such as expectations, anxiety, confidence, overconfidence and so on.
So what is economics good for? It’s good for organizing your thinking. It helps you know where to look for causal elements even if we cannot measure their precise contribution or how to relative weights of factors that pull in opposite directions. Economics helps us understand the relationship between the money supply and a general rise in the price level, between inflationary expectations and nominal interest rates, between expectations of the future and the willingness to invest, between policies that reduce prudence and a rise in imprudent investing. These are all things we understand better than we did 100 years ago partly because we have thought about them a lot, partly because of correlations in the data that we might view as sufficiently close to natural experiments, partly from armchair reasoning and partly from theoretical models of varying degrees of complexity.
We can’t measure any of these relationships with great precision, but we understand something and sometimes a lot about the direction that things are likely to go if something changes but nothing else does. Those are useful but modest gains in understanding. But they do not reach the level of what the media expects economists to be able to explain such as predicting the net impact of NAFTA on the US economy and the well-being of Americans, or how many jobs were created by the stimulus package of 2009. Unfortunately, economists do answer these questions with numerical precision as if they were physical scientists. My argument is that such answers are scientism and intellectually bankrupt.
Perhaps most importantly, economics can often remind us of the full range of effects of a particular policy, what Bastiat called the seen and the unseen. This is very valuable. Is it science? I don’t care. It’s a very powerful way of organizing your thinking about what happens when something changes in a complex system. Economics inevitably makes you aware of unintended or what might better be described as non-obvious consequences of a particular change.
Finally, economics is good for generating humility and preventing hubris. Remember the Hayek quote:
-->The curious task of economics is to illustrate to men how little they really know about what they imagine they can design.
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