Paper by Shomik Jain, Davide Proserpio, Giovanni Quattrone, and Daniele Quercia: “There is a rumbling debate over the impact of gentrification: presumed gentrifiers have been the target of protests and attacks in some cities, while they have been welcome as generators of new jobs and taxes in others. Census data fails to measure neighborhood change in real-time since it is usually updated every ten years. This work shows that Airbnb data can be used to quantify and track neighborhood changes. Specifically, we consider both structured data (e.g. number of listings, number of reviews, listing information) and unstructured data (e.g. user-generated reviews processed with natural language processing and machine learning algorithms) for three major cities, New York City (US), Los Angeles (US), and Greater London (UK). We find that Airbnb data (especially its unstructured part) appears to nowcast neighborhood gentrification, measured as changes in housing affordability and demographics. Overall, our results suggest that user-generated data from online platforms can be used to create socioeconomic indices to complement traditional measures that are less granular, not in real-time, and more costly to obtain….(More)”.
Mission Economy: A Moonshot Guide to Changing Capitalism
Book by Mariana Mazzucato: “Even before the Covid-19 pandemic in 2020, capitalism was stuck. It had no answers to a host of problems, including disease, inequality, the digital divide and, perhaps most blatantly, the environmental crisis. Taking her inspiration from the ‘moonshot’ programmes which successfully co-ordinated public and private sectors on a massive scale, Mariana Mazzucato calls for the same level of boldness and experimentation to be applied to the biggest problems of our time. We must, she argues, rethink the capacities and role of government within the economy and society, and above all recover a sense of public purpose. Mission Economy, whose ideas are already being adopted around the world, offers a way out of our impasse to a more optimistic future….(More)”.
Connected Devices – an Unfair Competition Law Approach to Data Access Rights of Users
Paper by Josef Drexl: “On the European level, promoting the free flow of data and access to data has moved to the forefront of the policy goals concerning the digital economy. A particular aspect of this economy is the advent of connected devices that are increasingly deployed and used in the context of the Internet of Things (IoT). As regards these devices, the Commission has identified the particular problem that the manufacturers may try to remain in control of the data and refuse data access to third parties, thereby impeding the development of innovative business models in secondary data-related markets. To address this issue, this paper discusses potential legislation on data access rights of the users of connected devices. The paper conceives refusals of the device manufacturers to grant access to data vis-à-vis users as a form of unfair trading practice and therefore recommends embedding data access rights of users in the context of the European law against unfair competition. Such access rights would be complementary to other access regimes, including sector-specific data access rights of competitors in secondary markets as well as access rights available under contract and competition law. Against the backdrop of ongoing debates to reform contract and competition law for the purpose of enhancing data access, the paper seeks to draw attention to a so far not explored unfair competition law approach….(More)”.
People understand statistics better than politicians think
Sarah O’Connor at the Financial Times: “In 2015 I took my reporter’s notebook to Liverpool because statistics suggested it was enjoying a jobs boom. The unemployment gap between the northern English city and the national average had shrunk to the smallest in a decade. When I mentioned that fact to people I met, I might as well have said the grass was pink.
“It’s certainly not our experience, I would say I’ve never seen poverty at this level,” was the response from the director of the local Citizens Advice Bureau. A woman who ran a small cake business said: “My cynical side thinks straight away they’ve probably got zero-hours contracts somewhere — [they] are a great way of cooking the books.”
I thought of that trip when I read a newly published study that uses an in-depth survey and focus groups to delve into the British public’s understanding of economics. The headline findings are bleak. Large parts of the public have misperceptions about how economic concepts such as the unemployment rate are measured and they are “sceptical and cynical” about data.
One obvious response would be to blame inadequate education and worry that economic ignorance allows people to be duped by demagogues such as Nigel Farage in the UK and Donald Trump in the US.
Economic literacy classes in schools would certainly be a good idea, especially since most of those surveyed were “deeply interested” in the economy and regretted not understanding the details. But there’s more to this story. The public live and breathe the economy every day. If their first response to a statistic such as the unemployment rate is to say “that doesn’t feel right” (a common response in the focus groups) then perhaps it’s the economists who are missing something….(More)”.
OECD Digital Economy Outlook
OECD: “…we released the third and latest edition of the OECD Digital Economy Outlook, our comprehensive analysis of emerging trends, opportunities and challenges in the digital economy….
Below are four key findings from this year’s Outlook. Find out more in our full publication and watch our virtual launch event here.
- Widespread connectivity has allowed many to adapt to the crisis
Our report finds that connectivity has continued to improve over time. Mobile broadband subscriptions nearly tripled between 2009 and June 2019, rising from 32 to nearly 113 subscriptions per 100 inhabitants, while average mobile data usage quadrupled over the course of four years, reaching 4.6 GB in 2018. Although fibre connections have increased at a slower rate, by June 2019 they accounted for 27% of all fixed broadband connections in the OECD and no less than 50% in nine OECD countries.
- But there are still significant divides in access, use and skills…
- Governments are increasingly putting the digital transformation front and centre
By mid-2020, 34 OECD countries had put in place a national digital strategy co-ordinated at the highest levels of government, and they are devoting more attention to emerging digital technologies such as AI, blockchain and 5G infrastructure. By mid-2020, 60 countries had established a national AI strategy, and several OECD countries – Australia, Austria, Colombia, France, Germany, Korea, Spain, the United Kingdom and the United States – have issued national 5G strategies. Several countries – Australia, People’s Republic of China, Germany, India and Switzerland – have issued a blockchain strategy, while others (France and Italy) are currently developing one.
- But more needs to be done to ensure an inclusive digital transformation…(More)”.
Geospatial Data Market Study
Study by Frontier Economics: “Frontier Economics was commissioned by the Geospatial Commission to carry out a detailed economic study of the size, features and characteristics of the UK geospatial data market. The Geospatial Commission was established within the Cabinet Office in 2018, as an independent, expert committee responsible for setting the UK’s Geospatial Strategy and coordinating public sector geospatial activity. The Geospatial Commission’s aim is to unlock the significant economic, social and environmental opportunities offered by location data. The UK’s Geospatial Strategy (2020) sets out how the UK can unlock the full power of location data and take advantage of the significant economic, social and environmental opportunities offered by location data….
Like many other forms of data, the value of geospatial data is not limited to the data creator or data user. Value from using geospatial data can be subdivided into several different categories, based on who the value accrues to:
Direct use value: where value accrues to users of geospatial data. This could include government using geospatial data to better manage public assets like roadways.
Indirect use value: where value is also derived by indirect beneficiaries who interact with direct users. This could include users of the public assets who benefit from better public service provision.
Spillover use value: value that accrues to others who are not a direct data user or indirect beneficiary. This could, for example, include lower levels of emissions due to improvement management of the road network by government. The benefits of lower emissions are felt by all of society even those who do not use the road network.
As the value from geospatial data does not always accrue to the direct user of the data, there is a risk of underinvestment in geospatial technology and services. Our £6 billion estimate of turnover for a subset of geospatial firms in 2018 does not take account of these wider economic benefits that “spill over” across the UK economy, and generate additional value. As such, the value that geospatial data delivers is likely to be significantly higher than we have estimated and is therefore an area for potential future investment….(More)”.
Public value and platform governance
UCL Institute for Innovation and Public Purpose (IIPP) Working Paper: “The market size and strength of the major digital platform companies has invited international concern about how such firms should best be regulated to serve the interests of wider society, with a particular emphasis on the need for new anti-trust legislation. Using a normative innovation systems approach, this paper investigates how current anti-trust models may insufficiently address the value-extracting features of existing data-intensive and platform-oriented industry behaviour and business models. To do so, we employ the concept of economic rents to investigate how digital platforms create and extract value. Two forms of rent are elaborated: ‘network monopoly rents’ and ‘algorithmic rents’. By identifying such rents more precisely, policymakers and researchers can better direct regulatory investigations, as well as broader industrial and innovation policy approaches, to shape the features of platform-driven digital markets…(More)”.
The forecasting fallacy
Essay by Alex Murrell: “Marketers are prone to a prediction.
You’ll find them in the annual tirade of trend decks. In the PowerPoint projections of self-proclaimed prophets. In the feeds of forecasters and futurists. They crop up on every conference stage. They make their mark on every marketing magazine. And they work their way into every white paper.
To understand the extent of our forecasting fascination, I analysed the websites of three management consultancies looking for predictions with time frames ranging from 2025 to 2050. Whilst one prediction may be published multiple times, the size of the numbers still shocked me. Deloitte’s site makes 6904 predictions. McKinsey & Company make 4296. And Boston Consulting Group, 3679.
In total, these three companies’ websites include just shy of 15,000 predictions stretching out over the next 30 years.
But it doesn’t stop there.
My analysis finished in the year 2050 not because the predictions came to an end but because my enthusiasm did.
Search the sites and you’ll find forecasts stretching all the way to the year 2100. We’re still finding our feet in this century but some, it seems, already understand the next.
I believe the vast majority of these to be not forecasts but fantasies. Snake oil dressed up as science. Fiction masquerading as fact.
This article assesses how predictions have performed in five fields. It argues that poor projections have propagated throughout our society and proliferated throughout our industry. It argues that our fixation with forecasts is fundamentally flawed.
So instead of focussing on the future, let’s take a moment to look at the predictions of the past. Let’s see how our projections panned out….
Viewed through the lens of Tetlock, it becomes clear that the 15,000 predictions with which I began this article are not forecasts but fantasies.
The projections look precise. They sound scientific. But these forecasts are nothing more than delusions with decimal places. Snake oil dressed up as statistics. Fiction masquerading as fact. They provide a feeling of certainty but they deliver anything but.
In his 1998 book The Fortune Sellers, the business writer William A. Sherden quantified our consensual hallucination:
“Each year the prediction industry showers us with $200 billion in (mostly erroneous) information. The forecasting track records for all types of experts are universally poor, whether we consider scientifically oriented professionals, such as economists, demographers, meteorologists, and seismologists, or psychic and astrological forecasters whose names are household words.”
The comparison between professional predictors and fortune tellers is apt.
From tarot cards to tea leaves, palmistry to pyromancy, clear visions of cloudy futures have always been sold to susceptible audiences.
Today, marketers are one such audience.
It’s time we opened our eyes….(More)”.
Using behavioral insights to make the most of emergency social protection cash transfers
Article by Laura Rawlings, Jessica Jean-Francois and Catherine MacLeod: “In response to the COVID-19 pandemic, countries across the globe have been adapting social assistance policies to support their populations. In fact, since March 2020, 139 countries and territories have planned, implemented, or adapted cash transfers to support their citizens. Cash transfers specifically make up about half of the social protection programs implemented to address the pandemic. Now more than ever, it’s crucial that such programs are designed to maximize impacts. Behavioral insights can be mobilized as a cost-effective way to help beneficiaries make the most out of the available support. The World Bank and ideas42 partnership on behavioral designs for cash transfer programs is helping countries achieve this goal.
Cash transfers are a key response instrument in the social protection toolkit—and for good reason. Cash transfers have been shown to generate a wide variety of positive benefits, from helping families invest in their children to promoting gender equality. However, we know from our previous work that in order to make the most out of cash transfers, recipients of any program (already facing challenging circumstances that compete for their attention) must undertake complex decisions and actions with their cash. These challenges are only magnified by the global pandemic. COVID-19 has wrought increased uncertainty around future employment and income, which makes calculations and planning to use cash transfer benefits all the more complex.
To help practitioners design programs that account for the complex thought processes and potential barriers recipients face, we mapped out their journey to effectively spend emergency social protection cash transfers. We also created simple, actionable guidance for program designers to put to use in maximizing their programs to help recipients use their cash transfer benefit to most effectively support families and reduce mid- to long-term financial volatility.
For example, the first step is helping recipients understand what the transfer is for. For recipients who have not yet been impacted by financial instability, or indeed have never encountered a cash transfer before, such funds might seem like a gift or bonus, and recipients may spend it accordingly. Providing clear, simple framing or labelling the transfer may signal to recipients that they should use the cash not only for immediate needs, but also in ways that can help them protect investments in their family members’ human capital and jumpstart their livelihood after the crisis wanes….(More)”.
The economics of Business to Government data sharing
Paper by Bertin Martens and Nestor Duch Brown: “Data and information are fundamental pieces for effective evidence-based policy making and provision of public services. In recent years, some private firms have been collecting large amounts of data, which, were they available to governments, could greatly improve their capacity to take better policy decisions and to increase social welfare. Business-to-Government (B2G) data sharing can result in substantial benefits for society. It can save costs to governments by allowing them to benefit from the use of data collected by businesses without having to collect the same data again. Moreover, it can support the production of new and innovative outputs based on the shared data by different users. Finally, the data available to government may give only an incomplete or even biased picture, while aggregating complementary datasets shared by different parties (including businesses) may result in improved policies with strong social welfare benefits.
The examples assembled by the High Level Expert Group on B2G data sharing show that most of the current B2G data transactions remain one-off experimental pilot projects that do not seem to be sustainable over time. Overall, the volume of B2G operations still seems to be relatively small and clearly sub-optimal from a social welfare perspective. The market does not seem to scale compared to the economic potential for welfare gains in society. There are likely to be significant potential economic benefits from additional B2G data sharing operations. These could be enabled by measures that would seek to improve their governance conditions to contribute to increase the overall number of transactions. To design such measures, it is important to understand the nature of the current barriers for B2G data sharing operations. In this paper, we focus on the more important barriers from an economic perspective: (a) monopolistic data markets, (b) high transaction costs and perceived risks in data sharing and (c) a lack of incentives for private firms to contribute to the production of public benefits. The following reflections are mainly conceptual, since there is currently little quantitative empirical evidence on the different aspects of B2G transactions.
- Monopolistic data markets. Some firms -like big tech companies for instance- may be in a privileged position as the exclusive providers of the type of data that a public body seeks to access. This position enables the firms to charge a high price for the data beyond a reasonable rate of return on costs. While a monopolistic market is still a functioning market, the resulting price may lead to some governments not being able or willing to purchase the data and therefore may cause social welfare losses. Nonetheless, monopolistic pricing may still be justified from an innovation perspective: it strengthens incentives to invest in more and better data collection systems and thereby increases the supply of data in the long run. In some cases, the data seller may be in a position to price-discriminate between commercial buyers and a public body, charging a lower price to the latter since the data would not be used for commercial purposes.
- High transaction costs and perceived risks. An important barrier for data sharing comes from the ex-ante costs related to finding a suitable data sharing partner, negotiating a contractual arrangement, re-formatting and cleaning the data, among others. Potentially interested public bodies may not be aware of available datasets or may not be in a position to handle them or understand their advantages and disadvantages. There may also be ex-post risks related to uncertainties in the quality and/or usefulness of the data, the technical implementation of the data sharing deal, ensuring compliance with the agreed conditions, the risk of data leaks to unauthorized third-parties and exposure of personal and confidential data.
- Lack of incentives. Firms may be reluctant to share data with governments because it might have a negative impact on them. This could be due to suspicions that the data delivered might be used to implement market regulations and to enforce competition rules that could negatively affect firms’ profits. Moreover, if firms share data with government under preferential conditions, they may have difficulties justifying the foregone profit to shareholders, since the benefits generated by better policies or public services fuelled by the private data will occur to society as a whole and are often difficult to express in monetary terms. Finally, firms might be afraid of entering into a competitive disadvantage if they provide data to public bodies – perhaps under preferential conditions – and their competitors do not.
Several mechanisms could be designed to solve the barriers that may be holding back B2G data sharing initiatives. One would be to provide stronger incentives for the data supplier firm to engage in this type of transactions. These incentives can be direct, i.e., monetary, or indirect, i.e., reputational (e.g. as part of corporate social responsibility programmes). Another way would be to ascertain the data transfer by making the transaction mandatory, with a fair cost compensation. An intermediate way would be based on solutions that seek to facilitate voluntary B2G operations without mandating them, for example by reducing the transaction costs and perceived risks for the provider data supplier, e.g. by setting up trusted data intermediary platforms, or appropriate contractual provisions. A possible EU governance framework for B2G data sharing operations could cover these options….(More)”.