Category Archives: uncertainty

23/7/20: Globalization and Populism: A Recent Study

I recently came across a fascinating paper by Dani Rodrik, an economist always worth reading. The paper, titled "Why Does Globalization Fuel Populism? Economics, Culture, and the Rise of Right-wing Populism" (NBER Working Paper No. 27526, July 2020) argues that "there is compelling evidence that globalization shocks, often working through culture and identity, have played an important role in driving up support for populist movements, particularly of the right-wing kind."

Rodrik carries out "an empirical analysis of the 2016 presidential election in the U.S. to show globalization-related attitudinal variables were important correlates of the switch to Trump."

  • "Trump voters were more likely to be white, older, and college-educated. 
  • "...they were significantly more hostile to racial equality and perceived themselves to be of higher social class. 
  • "The estimated coefficient on racial attitudes is particularly large: a one-point increase in the index of racial hostility – which theoretically ranges from 1 to 5 – is associated with a 0.28 percentage point increase in the probability of voting for Trump (Table below, column 1). 
  • "By contrast, economic insecurity does not seem to be associated with a propensity to vote for Trump.

"The finding that Trump voters thought of themselves as belonging to upper social classes ... largely reflects the role played by party identification in shaping voting preferences. When we control for Republican party identification (cols. 2 and 6), the estimated coefficient for social class drops sharply and ceases to be statistically significant."

"Note, however, that racial hostility remains significant, although its estimated coefficient becomes smaller (cols. 2 and 6)."

The other columns in the table above examine attitudes towards globalization (columns 2-5).

  • "All three of our measures enter statistically significantly: 
  • "Trump voters disliked trade agreements and immigration; 
  • "They were also against bank regulation (presumably in line with the general anti-regulation views of (cols. 2-5) the Republican party). 
  • "These indictors remain significant in the kitchen-sink version where they are all entered together (col. 6)."

"In none of these regressions does economic insecurity (financial worries) enter significantly. This
changes when we move from Trump voters in general to switchers from Obama to Trump (cols. 7-12). ... financial worries now becomes statistically significant, and switchers do not identify with the upper social classes. "

"Switchers are similar to Trump voters insofar as they too dislike trade agreements and immigration
(cols. 9-11). But they are dissimilar in that they view regulation of banks favorably. Hence switchers
appear to be against all aspects of globalization – trade, immigration, finance. the regression."

Rodrik postulates "a conceptual framework to clarify the various channels through which globalization can stimulate populism" on both "the demand and supply sides of politics". He also lists "the different causal pathways that link globalization shocks to political outcomes". 

Rodrik identifies "four mechanisms in particular, two each on the demand and supply sides:

  • (a) a direct effect from economic dislocation to demands for anti-elite, redistributive policies; 
  • (b) an indirect demand-side effect, through the amplification of cultural and identity divisions; 
  • (c) a supply-side effect through political candidates adopting more populist platforms in response to economic shocks; and 
  • (d) another supply-side effect through political candidates adopting platforms that deliberately inflame cultural and identity tensions in order to shift voters’ attention away from economic issues."

The full paper, accessible at is choke full of other insights and is absolutely worth reading.

30/4/20: No, Healthcare Systems are Not Lean Startups, Mr. Musk

A tweet from @elonmusk yesterday has prompted a brief response from myself:

For two reasons, as follows, it is worth elaborating on my argument a little more:

  1. I have seen similar sentiment toward authorities' over-providing healthcare system capacity in other countries as well, including, for example in Ireland, where the public has raised some concerns with the State contracting private hospitals for surplus capacity; and
  2. Quite a few people have engaged with my response to Musk.
So here are some more thoughts on the subject:

'Lean startups' is an idea that goes hand-in-hand with the notion that a startup needs some organic growth runway. In other words, it needs to ‘nail’ parts of its business model first, before ‘scaling’ the model up. ‘Nailing’ bit is done using highly scarce resources pre-extensive funding (which is a ‘scaling’ phase). It makes perfect sense for a start up, imo, for a startup.

But in the ‘nailing’ stage, when financial resources are scarce, the startup enterprise has another resource is relies upon to execute on a ‘lean’ strategy: time. Why? Because a ‘lean’ startup is a smaller undertaking than a scaling startup. As a result, failure at that stage carries lower costs. In other words, you can be ‘lean’ because you are allowed to fail, because if you do fail in that stage of development, you can re-group and re-launch. You can afford to be reactive to news flows and changes in your environment, which means you do not need to over-provide resources in being predictive or pro-active. Your startup can survive on lean funding.

As you scale startup, you accumulate resources (investment and retained earnings) forward. In other words, you are securing your organization by over-providing capacity. Why? Because failure is more expensive for a scaling startup than for a 'lean' early stage startup. The notion of retained and untilized cash is no longer the idea of waste, but, rather a prudential cushion. Tesla, Mr. Musk's company, carries cash reserves and lines of credit that it is NOT using at the moment in time precisely because not doing so risks smaller shocks to the company immediately escalating into existential shocks. And a failure of Tesla has larger impact than a failure of small 'lean' startup. In other words, Mr. Musk does not run a 'lean startup' for a good reason. Now, in a public health emergency with rapid rates of evolution and high degree of forecast uncertainty, you cannot be reactive. You must allocate resources to be pro-active, or anticipatory. In doing so, you do not have a choice, but to over-supply resources. You cannot be ‘lean’, because the potential (and highly probable) impact of any resource under-provision is a public health threat spinning out of control into a public health emergency and a systemic shock. ‘Lean’ startup methods work, when you are dealing with risk and uncertainty in a de-coupled systems with a limited degree of complexity involved and the range of shocks impact limited by the size of the organization/system being shocked. Public health emergence are the exact opposite of such a environment: we are dealing with severe uncertainty (as opposed to risk) with hugely substantial impacts of these shocks (think thousands of lives here, vs few million dollars in investment in an early stage start up failure). We are also dealing with severe extent of complexity. High speed of evolution of threats and shocks, uncertain and potentially ambiguous pathways for shocks propagation, and highly complex shock contagion pathways that go beyond the already hard-to-model disease contagion pathways. So a proper response to a pandemic, like the one we are witnessing today, is to use an extremely precautionary principle in providing resources and imposing controls. This means: (1) over-providing resources before they become needed (which, by definition, means having excess capacity ex-post shock realization); (2) over-imposing controls to create breaks on shock contagion (which, by definition, means doing too-much-tightening in social and economic environment), (3) doing (1) and (2) earlier in the threat evolution process rather than later (which means overpaying severely for spare capacity and controls, including - by design - at the time when these costs may appear irrational). And (4), relying on the worst-case-scenario parameterization of adverse impact in your probabilistic and forecasting analysis and planning. This basis for a public health threat means that responses to public health threat are the exact opposite to a ‘lean’ start up environment. In fact they are not comparable to the ‘scaling up’ start up environment either. A system that has a huge surplus capacity left in it, not utilized, in a case of a start up is equivalent to waste. Such system’s leadership should be penalized. A system that has a huge surplus capacity left un-utilized, in a case of a pandemic is equivalent to the best possible practice in prudential management of the public health threat. Such system’s leadership should be applauded.

And even more so in the case of COVID pandemic. Mr. Musk implies something being wrong with California secured hospital beds capacity running at more than double the rate of COVID patients arrivals. That's the great news, folks. COVID pandemic carries infection detection rates that double the population of infected individuals every 3-30 days, depending on the stage of contagion evolution. Earlier on, doubling times are closer to 3 days, later on, they are closer to 30 days. But, utilization of hospital beds follows an even more complex dynamic, because in addition to the arrival rates of new patients, you also need to account for the duration of hospital stay for patients arriving at different times in the pandemic. Let's be generous to sceptics, like Mr. Musk, and assume that duration-of-stay adjusted arrivals of new patients into the hospitals has a doubling time of the mid-point of 3-30 days or, close to two weeks. If California Government did NOT secure massively excessive capacity for COVID patients in advance of their arrival, the system would not have been able to add new capacity amidst the pandemic on time to match the doubling of new cases arrivals. This would have meant that some patients would be able to access beds only later in the disease progression period, arriving to hospital beds later in time, with more severe impact from the disease and in the need of longer stays and more aggressive interventions. The result would have been even faster doubling rate in the demand for hospital beds with a lag of few days. You can see how the system shortages would escalate out of control.

Running tight supply chains in a pandemic is the exact opposite to what has to be done. Running supply capacity at more than double the rate of realized demand is exactly what needs to be done. We do not cut corners on basic safety equipment. Boeing did, with 737-Max, and we know where they should be because of this. We most certainly should not treat public health pandemic as the basis for cutting surplus safety capacity in the system.

21/1/20: Investor Fear and Uncertainty in Cryptocurrencies

Our paper on behavioral biases in cryptocurrencies trading is now published by the Journal of Behavioral and Experimental Finance volume 25, 2020:

We cover investor sentiment effects on pricing processes of 10 largest (by market capitalization) crypto-currencies, showing direct but non-linear impact of herding and anchoring biases in investor behavior. We also show that these biases are themselves anchored to the specific trends/direction of price movements. Our results provide direct links between investors' sentiment toward:

  1. Overall risky assets investment markets,
  2. Cryptocurrencies investment markets, and
  3. Macroeconomic conditions,
and market price dynamics for crypto-assets. We also show direct evidence that both markets uncertainty and investor fear sentiment drive price processes for crypto-assets.