King's argument has both a broad conceptual message for the study of macroeconomics, which is that it is literally impossible to demonstrate with statistics that a certain macroeconomic model is "true." After all, drawing statistical conclusions requires a decent sample size. But to get a sample size of, say, 20 or 30 recessions in a given economy would take a long time--perhaps several centuries--and it is not plausible that any macroeconomic model remains "true" over that length of time. As King puts it (footnotes omitted):
"Let me give a simple example. It relates to my own experience when, as deputy governor of the Bank of England, I was asked to give evidence before the House of Commons Select Committee on Education and Employment on whether Britain should join the European Monetary Union. I was asked how we might know when the business cycle in the U.K. had converged with that on the Continent. I responded that given the typical length of the business cycle, and the need to have a minimum of 20 or 30 observations before one could draw statistically significant conclusions, it would be 200 years or more before we would know. And of course it would be absurd to claim that the stochastic process generating the relevant shocks had been stationary since the beginning of the Industrial Revolution. There was no basis for pretending that we could construct a probability distribution. As I concluded, `You will never be at a point where you can be confident that the cycles have genuinely converged; it is always going to be a matter of judgment.'"In the current economic context, King takes aim at the macroeconomic perspective which argues that we had a pretty good model of the macroeconomy for the decades leading up to the Great Recession, but the model has broken down since then. The dashed line in the figure shows a trendline for growth of GDP per capita from 1960-2016. For the US economy, you can project that trendline backward to 1900: as I noted a few years ago, long-run US economic growth had a remarkable consistency from the late 19th century up through about 2010. However, the divergence from this long-run path in the aftermath of the Great Recession is quite noticeable. The trendline for the United Kingdom data doesn't project backward as well, but it does show a similar divergence from that trend in recent years.
Looking at the economy as represented in this figure, one might plausibly argue that the macroeconomy can be modeled by a fairly steady long-run trend, with some up-and-down fluctuations of recessions and recoveries around that trend. However, King suggests that this appearance is misleading. Instead, the world economy saw a dramatic shift starting in the mid-1990s that has continued since then, which can be seen in the pattern of real interest rates over time. King says:
"From around the time when China and the members of the former Soviet Union entered the world trading system, long-term real interest rates have steadily declined to reach their present level of around zero. Such a fall over a long period is unprecedented. ... [M]uch effort has been invested in the attempt to explain why the "natural" real rate of interest has fallen to zero or negative levels. But there is nothing natural about a negative real rate of interest. It is simpler to see Figure 3 as a disequilibrium phenomenon that cannot persist indefinitely."
In King's view, the world economy is still adjusting to this shift, which has a number of components. High savings rates in China and Germany have helped to drive down real interest rates. Moreover, we have moved into a world economy where some countries have seemingly perpetual trade surpluses while others have seemingly perpetual trade deficits. King writes:
"Both the U.S. and U.K. had substantial current account deficits, amounting in aggregate to around $600 billion, and China and Germany had correspondingly large current account surpluses. All four economies need to move back to a balanced growth path. But far too little attention has been paid to the problems involved in doing that. With unemployment at low levels, the key problem with slower-than-expected growth is not insufficient aggregate demand but a long period away from the balanced path, reflecting the fact that relative prices are away from their steady-state levels. The result is that the shortfall of GDP per head relative to the pre-crisis trend path was over 15 percent in both the U.S. and U.K. at the end of last year. Policies which focus only on reducing the real interest rate miss the point; all the relevant relative prices need to change, too."In short, King is offering an alternative diagnosis of our current slow-growth woes. In his view, the slow growth, it's not due to lingering hangover from the high debt burdens that preceded the Great Recession, nor is it due to a decline in technological opportunities, or to a shortfall in investment related to "secular stagnation." Instead, King argues that what needs to happen is a shift in global prices in the sectors of tradeable and nontradeable goods.
I'm adding King's explanation to my list of mental possibilities for what forces are underlying the slow productivity growth in the US economy. But in addition, it's worth adding a dose of King-size skepticism about economists who arrive at any macroeconomic situation with a given model fixed in their minds, rather than trying to figure out which model is most likely to apply in a given case. King notes:
"Imagine that you had a problem in your kitchen, and summoned a plumber. You would hope that he might arrive with a large box of tools, examine carefully the nature of the problem, and select the appropriate tool to deal with it. Now imagine that when the plumber arrived, he said that he was a professional economist but did plumbing in his spare time. He arrived with just a single tool. And he looked around the kitchen for a problem to which he could apply that one tool. You might think he should stick to economics. But when dealing with economic problems, you should also hope that he had a box of tools from which it was possible to choose the relevant one. And there are times when there is no good model to explain what we see. The proposition that `it takes a model to beat a model' is rather peculiar. Why does it not take a fact to beat a model? And although models can be helpful, why do we always have to have one? After the financial crisis, a degree of doubt and skepticism about many models would be appropriate."