Wednesday, October 13, 2021

My take on this year's Nobel.

Vivek Dehejia

2021 Nobel in Economics

The anticipation in advance of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel — to give the prize its full title — is always palpable for academic economists, especially for those of us who’ve had the privilege of working with a future Laureate as doctoral students. To add to the sense of occasion, the Economics prize, by coincidence, happens to fall on Thanksgiving Day in Canada, a major national holiday. This year’s prize was awarded to David Card (one-half share) and to Joshua Angrist and Guido Imbens (one quarter-share each), for their pathbreaking work in allowing us make credible causal claims when analyzing data.

In a sense, this year’s prize is the flip side of the 2019 prize, awarded to Michael Kremer, Indian-born Abhijit Banerjee, and Esther Duflo. That trio won, in good measure, for their work in popularizing “randomized controlled trials” (RCTs), long a staple in the natural sciences, in the realm of economics research. RCTs allow us to make causal claims by randomly assigning subjects to a “control” and a “treatment” group — the randomness ensuring that any difference between the two groups can plausibly be attributed to the treatment, rather than any unobserved differences; the theory being that such differences should average out when subjects are randomized.

But, RCTs have some major limitations, which your columnist has argued in detail in these pages (“The experimental turn in economics”, 30 January 2016). A key problem is “external validity” — can a finding in one context be replicated in another, very different, one? Equally importantly, because creating an RCT is not always feasible, nor even ethical, in many situations, such an approach simply cannot address some of the “big” questions in economics, which perforce require that we analyze raw, non-randomized data, but find some way to tease out causality, if it is present.

Recall at the outset that observing a statistical correlation between two variables in the data is not, in itself, evidence of a causal relationship. Take an example close to home. During the pandemic, my classes switched on-line, with a pre-recorded two-hour lecture followed by a “live” one-hour Q&A session. Attendance at the latter was highly recommended, but not mandatory. Uniformly, I observed that students who attended, and participated activity, in the discussion session performed better on the course. But is this because my discussion session allowed them to perform better? Flattering as that would be for any professor, it is equally plausible that those who were anyway going to do well chose to participate — what we call “reverse causality”. Or, perhaps there were unobserved differences between those who participated and those who did not — say, access to high quality internet and the time to read, study, and discuss rather than struggling with poor internet, work, and school — which could plausibly explain the correlation instead? In other words, does non-random selection, rather than causality, matter in this case?

Economics is filled with such situations, where a correlation in the data entices us to draw a causal inference — which may be treacherous to do, in the absence of randomization, which, as noted, is impossible to achieve in most real world situations. The genius of David Card, working with the late Alan Krueger, was to find a clever solution, which was to look at a real world situation presenting as close to a natural experiment as the real world gives us — in this case, two contiguous US states which were otherwise similar, and which shared a common labour market and general macroeconomic conditions, but one of which increased the minimum wage whilst the other did not. (Interested readers may find a detailed exposition in fine write-ups on this year’s prize by economist Alex Tabarok in the Marginal Revolution blog and Tim Harford in the Financial Times .) By computing the “differences in differences” before and after the change and across the two jurisdictions allowed them to infer that any differential impact on unemployment was very likely driven by the policy change, not any unobserved differences.

In a similar vein, research by Angrist and Imbens, again with Krueger, in a series of papers, studied important questions such as whether increased schooling increases earnings, an obvious situation where any assumption of a unidirectional causal link may be problematic. (For instance, brighter students may study more and also earn higher incomes, both because of higher intrinsic ability.) In one seminal paper, Angrist and Krueger asked whether compulsory schooling could increase wages, and found a brilliant technique for randomization: given the oddities of the US school system, students born in late December would be one class behind those born in early January, and laws in some states allowed students to drop out at 16. The upshot is that there would be at least some students otherwise almost identical who got a year more of schooling for a purely random reason, and, these students, did indeed earn higher wages, making a causal claim tenable. (Again, check Tabarok and Harford for more details.)

The beauty of these contributions is that they were not founded on a complex and technical mathematical or statistical result that would be undecipherable to the layman, but on a simple and profound intuition of how randomization may be found even in our messy and non-random world, thus making causal inference tenable. Three cheers!

Vivek Dehejia is associate professor of economics and philosophy, Carleton University, Ottawa, Canada.

Monday, October 4, 2021

My latest column asks whether Evergrande's woes mean this is a Schandenfreude moment for China critics.

Is this the Schadenfreude moment for China sceptics?

Vivek Dehejia

The woes of Chinese property development firm, Evergrande, heavily indebted to both domestic and foreign lenders and on the verge of collapse, has engendered a Schadenfreude moment amongst China sceptics: but is it premature? After the crisis broke out, some proclaimed that the imminent failure of Evergrande might just be China’s “Lehman moment”, referring to the 2008 bankruptcy of the New York investment bank, Lehman Brothers, which was the opening salvo in the global financial crisis. Yet, global financial markets settled after a day or two of turmoil, as investors bet that that the Chinese state, which still heavily regulates the economy, will restructure the debt-laden firm in a manner that forestalls any potential international contagion. The critics might just have to wait before popping the Schadenfreude champagne corks.

Yet, even absent contagion, the Evergrande saga is but the tip of the iceberg of an overheated and indebted property sector which potentially threatens the edifice of the larger Chinese economy and, therefore, indirectly the global economy, too. In a fascinating long read, British-born historian, Niall Ferguson, makes just such a case (“Evergrande's Fall Shows How Xi Has Created a China Crisis”, Bloomberg Opinion, 26 September ).

As Ferguson observes, Evergrande is emblematic of a China which has developed in the past decade with an economic development paradigm premised on “urbanization on steroids”. For all of the skyscrapers, both commercial and residential, that dot the landscape of Chinese cities, large and even small, many of these remain empty and their property developers unable to sell enough units to pay off the debt incurred in putting up the buildings to begin with.

In other words, the property sector in China, larger even than in the US on the eve of the collapse of Lehman, is a ticking time bomb that could have significant macroeconomic consequences beyond the property and financial sectors through the impact on Chinese households, who are heavily invested in a property market that has been in bubble territory for some time. Citing research by Harvard economics professor, Kenneth Rogoff, and his co-author, Yuanchen Yang of Beijing’s Tsinghua University, Ferguson notes that housing wealth accounts for a whopping 78 percent of total assets in China, much higher than the 35 percent share in the United States, for instance. The upshot is that consumer spending in China is, per Rogoff-Yang, “significantly more sensitive to a decline in housing prices” than in the US. The impacts of a more generalized collapse in the property market in China could be large and consequential for the global economy.

For those with a long enough memory, none of these recent developments should come as a surprise. As long ago as 2004, economist James Dean and I argued, and as I summarized for Mint readers much later (“Will the elephant overshadow the dragon?”, Economics Express, 5 March 2015 ), that the Chinese model is characterized by the glaring contradiction between ever-increasing economic freedoms and an authoritarian political dispensation. What is more, the economic development paradigm of the Chinese Communist authorities was focussed on an infrastructure-driven, “build and they will come” model, in sharp contrast to, say, the Indian model, in which the supply of new infrastructure is driven by the demand for it, rather than the reverse.

The consequence, as Dean and I argued in 2004, was a Chinese development success story that was something of a house of cards, and built upon excessive investment, including in housing — what the Austrian school of economics would call “malinvestment”. Chinese growth statistics would, therefore, in an important sense be inflated: after all, if the economy grows rapidly because of a stock of property and infrastructure that ultimately will never be put to use, and which leads to the accumulation of large debts, such rapid growth may be unsustainable and, in a certain sense, illusory.

Up until now, China sceptics, including your columnist, have been confounded by the reality that successive generations of the Chinese leadership have shown a remarkable ability to continue to refresh and reinvent their model — both economic and political — thus ensuring that growth rates remain high and that the spectre of social chaos and unrest remains at bay. Every Chinese leader since Deng Xiaoping and his pioneering reforms of the late 1970s have managed to maintain the unwritten but all-important bargain with the populace: “we will give the you the opportunity to get rich, and the price is that you must stay out of politics”. But perhaps, just perhaps, the chickens may finally have come home to roost on the watch of authoritarian strongman, Xi Jinping — what, writing in 2015, I had reckoned might be an “implosion” in the Chinese economy or  a “belated and disorderly democratization” of the society.

What might make this time different is that, in the past few years, Xi has begun to rewrite the unwritten social compact, and increase government and party control over the economy, and reign in what he clearly believes is an excessively free and insufficiently regulated market economy, undoing the premise of Deng’s reforms. He has also been, first quietly, now overtly, building a cult of personality to match that around Mao. If the economy, and the public mood, sour, Xi may end up ruing these choices.

Vivek Dehejia is associate professor of economics and philosophy at Carleton University in Ottawa, Canada.