Technology & Innovation

The outlook series: behind the data—10 things that will matter in 2023

January 05, 2023


Behind the data: 10 things that will matter in 2023

January 05, 2023

Multiple contributor piece

This piece has been produced leveraging expertise from across our policy and insights team.

For full details of contributors please see bottom of the page.

Behind the data: 10 things that will matter in 2023

The Advanced Analytics team at Economist Impact answers important global questions by applying economic and data-science techniques. We analyse a range of issues, including trade, remote work, food security and scope-3 emissions. We love data. It can provide insights that confirm or challenge our preconceptions, empowering us to understand the world better.

Here’s a summary of what is currently on our minds:

The pace of innovation is slowing

We conducted a large-scale linguistic analysis of 60 years of academic papers using natural-language processing techniques. Text analysis of patent data can help us to understand where the weight of scientific attention is focused; as well as its overall trajectory. In some key areas such as  clean energy, the data suggests attention is shifting  from innovation to commercialisation. We’re currently benefiting from previous waves of innovation, through cheaper and more usable products including EVs and solar panels. The next wave of clean-energy innovation is essential, but where will it come from?

Seeing (AI) history in a new light

Our linguistic analysis found that several key concepts underpinning today’s most promising AI applications were developed in a period known as the  “AI winter”—the late 1980s to the early 1990s.This includes neural networks and deep learning, which both underpin the internet’s latest obsession, the ChatGPT tool—something we’ve recently dedicated a significant amount of time to beta testing. May this also serve as a reminder that there can be huge lags between innovation and usable tools—the first “artificial neuron” was developed back in 1943.

The quantum computing age is arriving, and up to $21 trillion in economic gains are up for grabs

We used GTAP, a computable general equilibrium model, to estimate the potential economic impact of quantum computing—a nascent technology that can power complex modeling tasks to discover new materials, forecast weather, and design life-saving drugs. Our scenario analysis  suggests that by 2035 the global economy could benefit by between $3 trillion and $21 trillion. This huge range of potential outcomes— equivalent to about 40 years of US GDP growth—reflects both the uncertainties involved in modeling a nascent technology, as well as the significance of the different sets of supports, enablers, and constraints that we model under different scenarios.

China’s highway network is more efficient than Germany’s

We developed a  new geospatial measure  of travel times between cities. Traditional measures of infrastructure connectivity rely on metrics such as the length of highways per thousand square kilometer. However, these measures often omit crucial information such as how easy it is to get from place to place. We applied our new model to the APAC region with a few international benchmarks, and learned that after two decades of large-scale infrastructure investment, China now boasts a highway network that surpasses Germany’s. That said, across the APAC region more broadly, it’s clear that there are significant gaps in highway networks and cross-border road connectivity that would be supportive of trade—particularly for landlocked countries and those with significant industrial activity in non-coastal areas, such as Laos, Cambodia and Bangladesh.

Half of US residents live within a five-minute drive of an electric-vehicle charging station

EV uptake remains slow in many countries including the US, where they account for less than 1% of registered vehicles. Efforts to prompt consumers to switch face multiple challenges, including the availability of charging infrastructure: both a challenge of fact and of perception–people are less likely to consider an EV if they think there’s limited charging infrastructure. To determine the facts, we ran an experiment using geospatial methods, and discovered that charging availability was better than we expected. Californians are best catered for with 67% of people living within five minutes of a charging station—compared with just 1% in the worst-served state, West Virginia. This coming year, we’ll be looking to add a socioeconomic dimension to the mix, to explore the equity of access.

Can an online movement spur better childcare infrastructure?

For an upcoming study, we’ve been looking at public awareness and engagement on childcare across 20 countries through the lens of social-media monitoring. Much of the conversation and community is built around information sharing. But there’s a strong streak of activism as well, with twice as many people engaged and vocal in countries that have lagging infrastructure compared with those with stronger childcare support.

Better support for caregivers could create a new New York

Putting aside childcare, aging populations in many economies is fueling a growing need for caregivers. In the US nearly 48 million people are family caregivers, which affects their work arrangements and prospects. Our impact modeling suggests that helping caregivers aged 50-plus to stay in the workforce could add $1.7 trillion to US GDP—equivalent to the size of New York state’s total economy.

The very real cost of lost focus in the workplace

A couple of years ago we found that distraction in the workplace costs businesses over $390 billion per year—costing the economy a potential $1.2 trillion. While meetings take a lot of the blame, we found that smaller distractions are the biggest culprits. These include instant messages, continual flicking tabs to check emails or the latest headlines, colleagues dropping by for a chat. Perhaps this is unsurprising given what we understand about the “attention costs” of context switching. We’re about to revisit and update this work, and we’re curious what the data will tell us several years after the onset of covid. Has the new normal helped or harmed the perennial challenge of focus in the workplace? What are organizations doing that’s working?

In online privacy we…maybe do trust?

This year, trust in online privacy declined in Europe and the US while improving in APAC. It’s clearly an issue on people’s minds. So, in our recent survey, we were surprised to find no correlation between self-reported levels of trust in online service providers and specific actions by users to protect themselves. It’s always interesting when people’s stated preferences diverge from their revealed preferences. This makes us want to learn more.

Our regular reminder that we need to check our assumptions at the gate:

In some recent consulting work, we were surprised to find that outlet malls in China attract more higher-income consumers than full-priced malls located in downtown areas. This was until we considered how outlet malls typically require private cars to reach. Another reminder that data can be  critical to challenging  our assumptions, enabling  us to better understand the world—and the opportunities in it.

Samantha Grenville

Global Lead, Advanced Analytics – Policy and Insights

Samantha leads Economist Impact’s Advanced Analytics practice, developing innovative, data-driven methodologies that generate evidence-based insights to inform internal strategy and external engagement for governments, international institutions, corporations, foundations and NGOs around the world.

Sam is an experienced economist who has spent over fifteen years advising senior executives and policymakers, and leading bespoke research programs that deploy economic techniques and data analytics across a wide range of issue areas. A seasoned speaker, she regularly briefs the international business and policymaking community as well as the media. Sam’s work has been reported in multiple outlets including the Financial Times, New York Times, Bloomberg, Market Insider, Forbes, and Foreign Policy.

Sam joined The Economist Group in 2013 as part of The Economist Intelligence Unit’s public policy consulting practice. Prior to that, she covered financial services policy and regulation at Eurasia Group and worked in corporate finance and M&A at Goldman Sachs.

Sam holds a Master’s in International Economic Policy from Columbia’s School of International and Public Affairs, and a Bachelor of Commerce (Economics and Finance) / Bachelor of Laws from Sydney University.

Alexander van Kemenade

Principal, Economist Impact’s Asia practice

Alex van Kemenade is a Principal in Economist Impact’s Asia practice. He leads the China office as well as the company’s economics and data science work in the region, specialising in applying data-driven analysis to generate insights and solutions to critical policy and strategy challenges.

Alex’s public sector work includes advising governments and international organisations on issues spanning macroeconomics, trade, infrastructure, demographics and digital economy. His private sector area of expertise is in business intelligence, forecasting, strategy and analytics, covering sectors including retail, automotive, consumer-packaged goods and ICT manufacturing. He pioneered the use of geospatial analysis in Economist Impact’s work.

Previously, Alex led The Economist Intelligence Unit’s China macroeconomics research team. His work has been featured in the Financial Times and CNN and he has appeared as a commentator on BBC, Sky News and ABC. He holds an MSc in Economics from the London School of Economics and Political Science and speaks fluent Mandarin.

Shivangi Jain
Manager and economist, Policy and insights 
Shivangi is a manager and economist at Economist Impact. She holds a master’s and bachelor’s degree in Economics from the London School of Economics and Political Science. Shivangi leads research programmes for governments, nonprofits and private sector organisations seeking evidence-based research and analysis. The focus of her work is on building custom impact assessment models for quantitative analysis, using a range of techniques including econometric modelling, general equilibrium modelling and cost-benefit analysis amongst others. Shivangi works across a broad range of industries and research areas including economic policy, social development, trade and competitiveness, sustainable growth, healthcare, productivity and others.

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