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Do our beliefs about future technology affect the economy?

New technologies, such as 5G telecommunications, self-driving vehicles and mRNA-based drugs and vaccines, have the potential to shape our future. Anticipation of their impact may already be affecting the economy today.

Over the past year, there has been a surge in the use and development of new technologies, as well as new applications for existing ones. For example, online conferencing tools have become part of many people’s everyday lives and progress in mRNA research through vaccine development promises treatment of diseases beyond Covid-19.

Just as the internet and smartphones have revolutionised how we live and work over the past decade, many expect that new technologies – including electric self-driving vehicles, blockchain and artificial intelligence – will do the same in the near future.

On an almost daily basis, we learn about imminent technological advances that give rise to expectations of higher future wealth and better quality of life. One would think that we would have to wait for these new technologies to become available for them to start affecting our lives. But recent research shows that behaviour can change, simply in anticipation of future technological advances.

These ‘news shocks’ about technology affect the economy now and may account for about 50% of the fluctuations in GDP. As such, our expectations about future technologies may be a very important factor contributing to booms and recessions (the business cycle). Could this help to explain the rapid recovery during the Covid-19 crisis?

How can news about future technologies affect the economy?

Promising and potentially life-changing news about future technologies is everywhere. Of course, the feeling of optimism about a brighter and more advanced future is nothing new – it has been repeated across generations.

In the past, news about the establishment of networks for railways, electricity and telecommunications, as well as the widespread introduction of computers all fuelled similar positive expectations. As with today’s technological advances, these all promised to make everyday life easier, save time and money, and offer new business opportunities.

Indeed, technological advances are the main drivers of long-term productivity growth in an economy. As such, the anticipation of new technologies offers hope of future growth in GDP and economy-wide productivity (Beaudry and Portier, 2006).

How then can news about future technological progress affect the economy now? Consider the following scenario: on news of a substantial future pay rise, one might well celebrate the success with a nice meal at a restaurant or the purchase of that long-wanted but far too expensive bike. Typically, people celebrate and consume in anticipation of the pay rise as soon as the good news arrives, rather than waiting for the higher pay actually to appear in their bank account.

Projecting this example onto the whole economy in the context of news about future technologies, something similar happens. Expectations about future technological advances are associated with higher wealth in the future, which makes us feel wealthier in the present. As in the above example about a future pay rise, this leads to higher spending, and hence a rise in GDP, even before the new technologies become available.

How can we measure the effect of productivity news shocks?

The idea that shifts in expectations and beliefs about future technology can be powerful enough to drive booms and trigger recessions has been recognised by economists for over a hundred years (Pigou, 1927).

While the idea itself is persuasive, actually measuring the effects of shifts in expectations about productivity is not straightforward. Over the past 20 years, advances have been made, but have led to conflicting results. Some studies find evidence that changes in expectations about future technologies, which economists have termed news shocks, account for a sizable share in the fluctuations of GDP (Schmitt-Grohe and Uribe, 2012; Görtz and Tsoukalas, 2017). While others come to quite the opposite conclusion (Forni et al, 2013).

Different ways to determine the effects of productivity news shocks have been suggested over the years, including both direct and indirect measurement approaches.

The former directly determines the effects of expectations from data about the level of productivity. But calculating the economy-wide level of productivity is notoriously difficult and prone to a certain degree of measurement error, which could affect the results on the economic effects of news shocks. In recent years, the construction of productivity measures has improved and methodologies have been developed to minimise the distortionary effects of any remaining measurement error (Fernald, 2014; Kurmann and Sims, 2021; Office for National Statistics, 2021).

Indirect approaches have also been considered to measure the effects of news shocks. Movements in stock markets, which arguably respond strongly to information about the future, are used to learn about how expectations drive business cycles (Beaudry and Portier, 2006). The link between expectations and stock prices is highly topical and has been discussed in an earlier Economics Observatory article. Recent studies also suggest using firms’ patent filings as a proxy for news about future technologies (Cascaldi-Garcia and Vukotic, 2020; Bluwstein et al, 2020).

The success of these indirect approaches crucially hinges on whether variables, such as stock prices and patent filings, are adequate representations of expectations about future technology and whether they contain sufficient information to be representative of the entire economy.

Since there are many ways to measure news shocks, do they have consistent implications?

Common to all these studies is that they aim to determine the average effects of news shocks over many decades and multiple business cycles (periods of both economic growth and recession). Not only do they use very different methodological approaches, but it is difficult to make a detailed comparison of the findings, particularly because they consider different time spans.

We therefore need a more holistic approach that applies both direct and indirect methods to the same data. A recent study conducts this comparison using a variety of direct and indirect methods over almost 40 years of data for the United States (Görtz et al, 2021). It shows that news about future technological advances does consistently trigger a strong boom in the economy.

Further, it highlights that shifts in beliefs are a powerful force behind business cycle fluctuations. They are found to account for, on average, about 50% of the fluctuations in GDP. This is in line with other research, which also documents that anticipated news productivity shocks tend to be somewhat more important for business cycle fluctuations than unanticipated shocks to productivity, (for example the unexpected malfunctioning of a machine) (Levchenko and Pandalai-Nayar, 2020; Görtz et al, 2021).

More recent studies add a new layer of scrutiny by investigating how firms change the level of goods they stock for sale in response to technology news shocks (Crouzet and Oh, 2016; Görtz et al, 2020; Görtz et al, 2021).

These inventories provide a new litmus test to establish the relevance of expectations in driving business cycles for two reasons. First, inventories are believed to respond strongly to news, because accumulating and holding stock is costly and requires firms to forward plan.

Second, inventories are one of the key variables behind business cycle fluctuations, in the sense that reductions in the level of goods in stock account for a substantial share of the decline in GDP during recessions. For example, the reduction in inventory investment during the global financial crisis of 2007-09 accounted for a third of the decline of GDP during this recession (Shibayama and Chadha, 2014).

For these two reasons, examining inventories is likely to increase understanding about the relevance of shifts in expectations for business cycle fluctuations.

Economists are in wide agreement that inventory stock increases during booms and declines during recessions. This so-called ‘pro-cyclical behaviour’ of inventories is widely documented (for example Lubik and Teo, 2012). As a result, some argue that news shocks can only be a relevant driving force behind booms and recessions if they cause inventories to follow this pattern (Crouzet and Oh, 2016).

The response of inventories to news shocks is therefore seen as a strong litmus test for the importance of news shocks. One study finds that in response to positive news about future technology – measured using a variety of direct and indirect approaches – inventory stock rises, alongside increases in GDP, investment, consumption and hours worked (Görtz, Gunn and Lubik, 2021). This finding provides strong evidence for the powerful force of news about productivity in driving business cycles.

Understanding the role of news shocks and the resulting changes in expectations for business cycle fluctuations is important for policy-makers, for example as they aim to limit the current Covid-19 recession.

As discussed, the shift in expectations due to news about higher future productivity boosts GDP in the present. This is independent of whether the expectations retrospectively turn out to be overly optimistic, overly pessimistic or fully accurate. Realising that past expectations have been inaccurate may again result in an adjustment of our economic decision-making and future expectations.

Recent advances have been made in understanding the importance of news shocks about future technological advances for booms and busts. But further insight into other dimensions of how individuals, firms and governments adjust their expectations in light of news shocks and how this affects the economy is still needed.

It is too early to pin down all the economic forces at play during the Covid-19 recession. Yet the recent studies discussed above support the notion that a severe recession may have been dampened and the fast recovery after the economy’s crash may have been partly fuelled by our response to positive news about the potential of future technologies.

Where can I find out more?

  • Overview article about news shock driven business cycles.
  • Evidence on the effects of productivity news shocks on inflation and consumer confidence.
  • Information on the international transmission of technology news shocks.

Who are experts on this question?

Author: Christoph Görtz
Photo by LinkedIn Sales Solutions on Unsplash
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