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Ben Snaith

How to revive the world economy - A recession is unlikely but not impossible | Finance ... - 0 views

www.economist.com/...is-unlikely-but-not-impossible

Coronavirus Economics

shared by Ben Snaith on 23 Apr 20 - No Cached
  • One way the virus hurts the economy is by disrupting the supply of labour, goods and services. People fall ill. Schools close, forcing parents to stay at home. Quarantines might force workplaces to shut entirely. This is accompanied by sizeable demand effects. Some are unavoidable: sick people go out less and buy fewer goods. Public-health measures, too, restrict economic activity. Putting more money into consumers’ hands will do little to offset this drag, unlike your garden-variety downturn. Activity will resume only once the outbreak runs its course.
Ben Snaith

Graphing the Pandemic Economy by Michael Spence & Chen Long - Project Syndicate - 0 views

www.project-syndicate.org/...l-spence-and-chen-long-2020-06

Data Coronavirus Mobility Economics

shared by Ben Snaith on 03 Jun 20 - No Cached
  • To be sure, mobility is only one indicator of economic contraction. Risk avoidance by individuals, companies, and other institutions also could play a role in depressing economic activity, even in the absence of mandated lockdowns. But as a variable that captures the state of economic activity, mobility has several major advantages.
  • First, it is one of the few big-data metrics that both captures current activities and is available in more than 130 economies on a daily basis. Second, it is an endogenous variable, in the sense that it reflects both the impact of lockdowns and people’s choices, which often are motivated by risk aversion. And, third, it appears to capture a substantial portion of GDP variation across economies and over time.
Ben Snaith

Britons want quality of life indicators to take priority over economy | Society | The G... - 0 views

www.theguardian.com/...ority-over-economy-coronavirus

Data Coronavirus Economics Health

shared by Ben Snaith on 11 May 20 - No Cached
  • A YouGov poll has found eight out of 10 people would prefer the government to prioritise health and wellbeing over economic growth during the coronavirus crisis, and six in 10 would still want the government to pursue health and wellbeing ahead of growth after the pandemic has subsided, though nearly a third would prioritise the economy instead at that point.
  • The focus on GDP means economic growth can take place at the expense of the environment, and people’s quality of life, without any of the resulting damages ever being taken into account, the report argues. That in turn encourages ministers and officials to seek ways of raising the GDP figures, even if rising nominal growth is accompanied by environmental degradation, worsening health, poor educational attainment and increasing poverty.
Ben Snaith

Coronavirus Recession Will Be Difficult to Fight - The Atlantic - 0 views

www.theatlantic.com/...607657

Coronavirus Economics

shared by Ben Snaith on 23 Apr 20 - No Cached
  • A downturn stemming from an epidemic is an unusual one. And it might prove unusually difficult for policy makers to fight, in the United States and abroad.For one, the coronavirus epidemic has come with extraordinary, intense uncertainty. Officials are not sure how many cases there are and how deadly the virus is. Businesses and households are uncertain of how long the danger will last and what measures governments might take to counter it. People are afraid, as the market panic demonstrates, and it may take months for that fear to abate.
  • judiciously targeted bailouts are really the only way I can think of to keep businesses and people from going bankrupt given the absence of pandemic insurance.”
  • Harvard’s Jason Furman has suggested that Congress send every adult American $1,000 and every child $500
Ben Snaith

How will Coronavirus affect jobs in different parts of the country? | Centre for Cities - 0 views

www.centreforcities.org/...different-parts-of-the-country

Coronavirus Regions Statistics Jobs Cities

shared by Ben Snaith on 23 Apr 20 - No Cached
  • Self-employed people in the North and Midlands are more likely to be in insecure, lower-paid roles at high risk from economic shocks
  • Cities in the Greater South East are more likely to be able to shift to working from home
  • The jobs that could be more easily done from home – such as consultants or finance – are concentrated in cities in the Greater South East (see the figure below). Assuming some sectors could completely shift to home working if necessary, up to one in two workers in London could shift to working from home. Meanwhile in Reading, Aldershot and Edinburgh over 40 per cent of workers could too.
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  • On the other hand, less than 20 per cent of all workers in Barnsley, Burnley and Stoke could work from home, suggesting the economies of many northern cities are likely to be hardest hit by a complete lockdown.
Ben Snaith

Virus lays bare the frailty of the social contract | Financial Times - 0 views

www.ft.com/...9a-74dd-11ea-95fe-fcd274e920ca

Coronavirus Economics Government

shared by Ben Snaith on 23 Apr 20 - No Cached
  • Governments will have to accept a more active role in the economy. They must see public services as investments rather than liabilities, and look for ways to make labour markets less insecure. Redistribution will again be on the agenda; the privileges of the elderly and wealthy in question. Policies until recently considered eccentric, such as basic income and wealth taxes, will have to be in the mix.
Ben Snaith

Did city centres get a 'Super Saturday' bounce? | Centre for Cities - 1 views

www.centreforcities.org/...es-get-a-super-saturday-bounce

Mobility Data Coronavirus Economics

shared by Ben Snaith on 31 Jul 20 - No Cached
  • There are three key things to note in this: Looking between late-February and mid-March, we see that the drop-off in footfall happened earlier and was much sharper in London than the other cities. Looking between early-April and mid-June, we see that the small and the medium-sized cities experienced less of a decline than London and the other large cities, and they also started to recover from this earlier. Looking between mid-June (when non-essential retail reopened) and Saturday 4 July, we see that while the trajectory is upwards everywhere, the small and the medium-sized cities have seen a much sharper climb back up towards normal.
  • There are three things potentially playing into this: City centres of large cities tend to have less residential and industrial space and are often concentrations of office jobs, which have been and still are being done from home. This limits how many workers are in the city centre compared to before.  Larger cities, especially London are more reliant on public transport than their smaller counterparts. With public transport still limited in both capacity and use for public health reasons, it is now harder for people to travel into the centres of these cities. Due to their size, larger cities have more options for going to the pub or shopping beyond the centre and it may be that this has further reduced footfall in the city centre.
  • This and our other analysis on the topic suggests that we are unlikely to see large-scale changes in footfall and a ‘return to the normal’ in the city centres of the largest cities until office workers are welcome to and do return. 
Ben Snaith

Mobile phone data for informing public health actions across the COVID-19 pandemic life... - 0 views

advances.sciencemag.org/...eabc0764

Coronavirus Data Mobility

shared by Ben Snaith on 08 Jun 20 - No Cached
  • Decision-making and evaluation or such interventions during all stages of the pandemic life cycle require specific, reliable, and timely data not only about infections but also about human behavior, especially mobility and physical copresence. We argue that mobile phone data, when used properly and carefully, represents a critical arsenal of tools for supporting public health actions across early-, middle-, and late-stage phases of the COVID-19 pandemic.
  • Seminal work on human mobility has shown that aggregate and (pseudo-)anonymized mobile phone data can assist the modeling of the geographical spread of epidemics (7–11).
  • Although ad hoc mechanisms leveraging mobile phone data can be effectively (but not easily) developed at the local or national level, regional or even global collaborations seem to be much more difficult given the number of actors, the range of interests and priorities, the variety of legislations concerned, and the need to protect civil liberties. The global scale and spread of the COVID-19 pandemic highlight the need for a more harmonized or coordinated approach.
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  • Government and public health authorities broadly raise questions in at least four critical areas of inquiries for which the use of mobile phone data is relevant. First, situational awareness questions seek to develop an understanding of the dynamic environment of the pandemic. Mobile phone data can provide access to previously unavailable population estimates and mobility information to enable stakeholders across sectors better understand COVID-19 trends and geographic distribution. Second, cause-and-effect questions seek to help identify the key mechanisms and consequences of implementing different measures to contain the spread of COVID-19. They aim to establish which variables make a difference for a problem and whether further issues might be caused. Third, predictive analysis seeks to identify the likelihood of future outcomes and could, for example, leverage real-time population counts and mobility data to enable predictive capabilities and allow stakeholders to assess future risks, needs, and opportunities. Finally, impact assessments aim to determine which, whether, and how various interventions affect the spread of COVID-19 and require data to identify the obstacles hampering the achievement of certain objectives or the success of particular interventions.
  • During the acceleration phase, when community transmission reaches exponential levels, the focus is on interventions for containment, which typically involve social contact and mobility restrictions. At this stage, aggregated mobile phone data are valuable to assess the efficacy of implemented policies through the monitoring of mobility between and within affected municipalities. Mobility information also contributes to the building of more accurate epidemiological models that can explain and anticipate the spread of the disease, as shown for H1N1 flu outbreaks (29). These models, in turn, can inform the mobilization of resources (e.g., respirators and intensive care units).
  • Continued situational monitoring will be important as the COVID-19 pandemic is expected to come in waves (4, 31). Near real-time data on mobility and hotspots will be important to understand how lifting and reestablishing various measures translate into behavior, especially to find the optimal combination of measures at the right time (e.g., general mobility restrictions, school closures, and banning of large gatherings), and to balance these restrictions with aspects of economic vitality.
  • After the pandemic has subsided, mobile data will be helpful for post hoc analysis of the impact of different interventions on the progression of the disease and cost-benefit analysis of mobility restrictions. During this phase, digital contact-tracing technologies might be deployed, such as the Korean smartphone app Corona 100m (32) and the Singaporean smartphone app TraceTogether (33), that aim at minimizing the spread of a disease as mobility restrictions are lifted.
  • Origin-destination (OD) matrices are especially useful in the first epidemiological phases, where the focus is to assess the mobility of the population. The number of people moving between two different areas daily can be computed from the mobile network data, and it can be considered a proxy of human mobility.
  • Amount of time spent at home, at work, or other locations are estimates of the individual percentage of time spent at home/work/other locations (e.g., public parks, malls, and shops), which can be useful to assess the local compliance with countermeasures adopted by governments. The home and work locations need to be computed in a period of time before the deployment of mobility restrictions measures.
  • The use of mobile phone data for tackling the COVID-19 pandemic has gained attention but remains relatively scarce.
  • First, governments and public authorities frequently are unaware and/or lack a “digital mindset” and capacity needed for both for processing information that often is complex and requires multidisciplinary expertise (e.g., mixing location and health data and specialized modeling) and for establishing the necessary interdisciplinary teams and collaborations. Many government units are understaffed and sometimes also lack technological equipment.
  • Second, despite substantial efforts, access to data remains a challenge. Most companies, including mobile network operators, tend to be very reluctant to make data available—even aggregated and anonymized—to researchers and/or governments. Apart from data protection issues, such data are also seen and used as commercial assets, thus limiting the potential use for humanitarian goals if there are no sustainable models to support operational systems. One should also be aware that not all mobile network operators in the world are equal in terms of data maturity. Some are actively sharing data as a business, while others have hardly started to collect and use data.
  • Third, the use of mobile phone data raises legitimate public concerns about privacy, data protection, and civil liberties.
  • Control of the pandemic requires control of people—including their mobility and other behaviors. A key concern is that the pandemic is used to create and legitimize surveillance tools used by government and technology companies that are likely to persist beyond the emergency. Such tools and enhanced access to data may be used for purposes such as law enforcement by the government or hypertargeting by the private sector. Such an increase in government and industry power and the absence of checks and balance is harmful in any democratic state. The consequences may be even more devastating in less democratic states that routinely target and oppress minorities, vulnerable groups, and other populations of concern.
  • Fourth, researchers and technologists frequently fail to articulate their findings in clear, actionable terms that respond to practical political and technical questions. Researchers and domain experts tend to define the scope and direction of analytical problems from their perspective and not necessarily from the perspective of governments’ needs. Critical decisions have to be taken, while key results are often published in scientific journals and in jargon that are not easily accessible to outsiders, including government workers and policy makers.
  • Last, there is little political will and resources invested to support preparedness for immediate and rapid action. On country levels, there are too few latent and standing mixed teams, composed of (i) representatives of governments and public authorities, (ii) mobile network operators and technology companies, and (iii) different topic experts (virologists, epidemiologists, and data analysts); and there are no procedures and protocols predefined. None of these challenges are insurmountable, but they require a clear call for action.
  • To effectively build the best, most up-to-date, relevant, and actionable knowledge, we call on governments, mobile network operators, and technology companies (e.g. Google, Facebook, and Apple), and researchers to form mixed teams.
  • For later stages of the pandemic, and for the future, stakeholders should aim for a minimum level of “preparedness” for immediate and rapid action.
Ben Snaith

Wall Street Mines Apple and Google Mobility Data to Spot Revival - 0 views

www.bloombergquint.com/...-mobility-data-to-spot-revival

Mobility Data Economics Coronavirus

shared by Ben Snaith on 11 Jun 20 - No Cached
  • LGIM’s asset allocation team takes Apple users’ requests for travel directions and adjusts them for weekly seasonality before projecting the data onto estimates for gross domestic product. So far, their analysis shows that the U.S. economy is holding up better than other regions and is gradually reopening, while there are signs of improvement in southern Europe as countries like Italy relax their movement restrictions.
  • In addition to LGIM, Societe Generale SA and Deutsche Bank AG are among those tracking mobility data. SocGen quant strategists led by Andrew Lapthorne said in a note on Monday that the data has helped them see that despite the easing of lockdowns in major economies, activity continues to be weak.
  • Over at Deutsche Bank, strategists are using Google data to monitor any pick-up in activity in various New York communities.
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  • Torsten Slok, chief economist at Deutsche Bank Securities, said the analysts are beginning to see early signs of a turnaround in daily and weekly indicators of New York City subway usage, but those improvements are more modest than the pick-up in activity at parks, grocery stores and pharmacies.
Ben Snaith

City-wide data in London: pandemic response & recovery (Part 1) - 0 views

medium.com/...e-recovery-part-1-13c25efbac43

Coronavirus Data Cities London Local-Government

shared by Ben Snaith on 22 Jun 20 - No Cached
  • The crisis more than ever demonstrated there is a very clear need for data in real time (or as near to real time) as possible to help inform decisions. It showed that problems-to-be-solved can’t be solved by the data one organisation holds alone: inevitably joining-up data from other sources is required. It also told us that without greater data collaboration our routes to creative, scalable solutions will remain limited.
  • The UK’s unusually fragmented approach to public sector data means often we talk more about how data is not shared or is not available than how it is more seamlessly used to understand common needs or meet shared objectives.
  • For example, City Hall is using aggregated data from Vodafone, O2 and Mastercard payments to add to our view of the observance of lockdown restrictions and add our understanding of the health of local economies.
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  • Work (known as ‘Project Odysseus’) with the Turing Institute, London First and Microsoft UK repurposes our ongoing work on air quality forecasting to assess the ‘busy-ness’ of areas of the city, also allowing insight into restrictions and economic recovery.
Ben Snaith

The problem of modelling: Public policy and the coronavirus - 0 views

www.the-tls.co.uk/...olicy-coronavirus-paul-collier

Public-Policy Models Coronavirus

shared by Ben Snaith on 05 Jun 20 - No Cached
  • The current epidemic is a classic application of what economists call “radical uncertainty” (most recently explored by John Kay and Mervyn King in their brilliant book of that title, which came out last month): in a world that has inevitably become too complex to be adequately captured in models, a world of both “known unknowns” and “unknown unknowns”, the most sensible response to the question “what should we do?” is “I don’t know”. At the onset of this crisis, we could not put probabilities on which forms of social distancing would best limit its spread because we’d never done it before. We didn’t know how people would alter their behaviour in response to the appeal to “save the NHS”. We didn’t even know whether reducing the spread was desirable: perhaps fewer deaths now would come at the cost of more next winter. And these were just the known unknowns. With a disruption as big as this, unknown unknowns are also lurking. We have no experience of the material and economic repercussions from shutdowns of this nature and their aftermath in a modern economy, and no meaningful way of assigning probabilities; nor of how people’s behaviour will evolve.
  • What the modellers should have said, right from the beginning, was that it was vital to establish two fundamental parameters: the incidence and the rate of contagion, both of which require mass testing, and without which mortality rates are impossible to decipher and hence sensible policy impossible to implement. It is frankly astounding that four months into this new virus such tests are only now being instigated.
  • . Shifting responsibilities down the system not only enables rapid scale-up, it has a further huge advantage: the power of decision is closer to the coalface of practitioner experience. We learn not just from accumulating and analysing codifiable knowledge – the domain of the expert. We learn by doing, or by trying to do things that we can’t do and that force us to experiment. A decentralized system learns from a litany of failed experiments running in parallel, and so it learns fast: teams copy other teams that have hit on something that works well enough to get the job done.
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  • The political herd immunity to which governments are prone is that it is much safer to fail with a policy that others are following than to fail with a distinctive policy, even if, ex ante, the chances of failure are higher with the former.
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