Economics in Information Technology. Хрестоматия для студентов бакалавров направлений «Бизнес-информатика», «Прикладная информатика»

been stagnant in the U.S. over the decade, despite rising productivity,” while only 28 percent disagreed. Similarly, a

2015 study by the International Monetary Fund concluded that technological progress is a major factor in the increase of inequality over the past decades.

The bottom line is that while automation is eliminating many jobs in the economy that were once done by people, there is no sign that the introduction of technologies in recent years is creating an equal number of well-paying jobs to compensate for those losses. A 2014 Oxford study found that the number of U.S. workers shifting into new industries has been strikingly small: in 2010, only 0.5 percent of the labor force was employed in industries that did not exist in 2000.

The discussion about humans, machines and work tends to be a discussion about some undetermined point in the far future. But it is time to face reality. The future is now.

Students need IT skills to compete in the new economy

https://theconversation.com (June 8, 2018)

By 2026, employment in computer and information technology occupations is projected to grow 13 percent over what it was in 2016. Jobs in these fields will require skills in cloud computing, big data collection and storage, information security and more.

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As I argue in a paper in the Journal of Monetary Economics with Giovanni Gallipoli, these information technology – or IT – skills are increasingly required if you want a job with upward mobility and autonomy.

A new “IT intensity” index that I developed illustrates this trend. Using data from the Bureau of Labor Statistics that measures tasks and skills across occupations, the index gauges how much occupations deal with information technology. I developed this IT intensity index as a labor economist who studies macroeconomic trends, policy and their interaction with individuals and labor markets.

While the index is far from perfect, it allows us to distinguish between jobs that require more interaction with computers, whether it’s software engineering or coding.

Increase in IT jobs

Using our IT intensity index, together with data tables from the Occupation Employment Statistics program, I found that IT intensive occupations grew by 19.5 percent between 2004 and 2017, while less IT intensive occupations only grew by 2.4 percent. That’s more than eight times as large of a growth rate over the past decade.

And yet, companies routinely complain about not being able to find enough workers. While the skills gap for digital and

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technical tasks is large, some researchers argue it is largest for cybersecurity.

There is also concern about unmet demand for coordination and communication skills.

The fact that so many prospective job candidates lack these skills might help explain the decline in labor force participation and stagnation of median hourly wages over the past few decades.

On the other hand, new research suggests that the economic benefits of technological advancements – such as the development of artificial intelligence – do not always show up right away in national measurements of productivity growth. The research blames “implementation lags” in technology as a likely culprit.

New models in higher education

Educational institutions can help turn things around by equipping individuals with IT skills. Technology is changing at an increasing rate and a four-year degree may not give students the skills they need to remain competitive until retirement. Students today must become lifelong learners. To do that, universities need to provide their services to enough students to make an impact and focus on teaching relevant and tangible skills, particularly around data analysis, that are in increased demand. Several universities stand out as leaders in this regard.

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The standouts include Arizona State University and Georgia State University, which rank first and fourth, respectively, as the most innovative universities in the United States, according to U.S. News. These schools are actively using big data to help improve the delivery and scale of their services to improve student success rates.

For example, GSU is using data analytics to help predict how at-risk students might do in certain courses. This enables better advising, which in turn helps improve completion rates. GSU has boosted its graduation rate to 54 percent in 2017 – up from 32 percent in 2003.

Benefits of completion

What does a college degree have to do with equipping students with IT skills? Using my measure of IT jobs, together with data from the American Community Survey between 2005 and 2016, I find that workers with a college degree are 36 percentage points more likely to work an IT job, controlling for other demographic factors, such as age, race and gender. Even if a student does not major in computer science, universities provide an environment to cultivate the skills needed to excel in IT jobs, which demand other interpersonal and noncognitive skills. For instance, other research suggests that students who double major in STEM and liberal arts tend to earn 10 percent higher annual salaries than their counterparts who double major in just one broad field.

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ASU is another example of a university that has significantly boosted the number of students it educates. Specifically, ASU enrolled nearly more than 98,000 students in 2016 – significantly more than the 73,000 it enrolled in 2012 – while simultaneously rising in international rankings.

One of the things that ASU does particularly well is provide students with real-world experience. For example, ASU’s Edson Student Entrepreneur Initiative provides students with funding, mentoring and office space to co-found a startup.

Encouraging students to engage with real-world problems not only directly cultivates their problem-solving skills, but also indirectly exposes them to the limitless possibilities of IT. Access to technology can help a startup to stay competitive. The same holds true for students.

Regulation and competition in the digital economy

https://www.cairn-int.info (February, 2016)

Because of increasing productivity, the digital economy has a natural tendency to market concentration (referred to as

“natural” monopolies). Existing regulation measures

(concerning ownership of capital, prices, behavioural obligations, etc.) are in part ill-adapted to the digital economy’s dominant companies, which derive their effectiveness from the implementation of network effects by raising barriers of entry to their markets, in particular:

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Vertical (“silo systems”) and horizontal (bundling) integration in closed ecosystems designed to keep the maximum of users. Apple constitutes an emblematic example of this strategy: initially positioned on the computers, MP3 players and smartphones market, Apple progressively integrated itself by creating a contents platform (iTunes) and a software applications store (App Store), which constitute the only sources of supply for users of its products;

The development of multi-sided business models (“platforms”), which generate indirect network effects that it is difficult for new entrants to reproduce (see the example of Google, text box).

Although the traditional tools of competition law are effectively adapted to fighting against the abuse of dominant positions, diagnosis of abuse of this kind is made more complex by the presence of network externalities.

Monitoring closed ecosystems

Companies can collect data on a mass scale thanks to regular and systematic monitoring of software application users’ activities. In certain cases, this data makes it possible to create more value on a different side of the platform: the capacity to collect data on Internet users’ searches thus enables Google to gain better knowledge of their centres of interest and make them targeted commercial offers through its advertising clients. In other cases, it enables improvement and personalisation of

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offers, thereby making it possible to reduce the cost of acquiring new customers and securing their loyalty (Netflix, Apple). Cost savings are reinforced by further savings arising from ancillary businesses (for example, the supply of cartography and hotel reservation services within the same mobile apps environment).

These closed ecosystems, within which users adopt a product and are then obliged to only purchase terminals, software applications and content associated with it, pose sensitive issues of competition. They can be beneficial to consumers: competition tends to be more intense between closed ecosystems than between composite systems. However, the fact of being “locked-in” to a given technological choice may pose problems of competition when switching costs are high and consumers purchase numerous products that are not transferable from one system to another. In this case, the act of choosing one technology restricts consumers’ subsequent choices and may make them vulnerable in relation to the company operating the ecosystem. Above all, switching costs reduce the intensity of competition: once established in a given environment, consumers need to be made a significantly better offer (from the point of view of prices or characteristics other than price) in order to consent to change system. The portability solutions adopted in banking and telephony constitute an interesting possible approach for addressing this problem with regard to digital activities.

Regulating indirect network effects

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Direct and/or indirect network effects benefit users: they give rise to a dynamic of growth and promote the development of standards. However, the resulting dominant positions may also prevent new actors from entering the market, since they have to put particularly attractive offers together in order to challenge the “established base” of the companies already present. For example, the more numerous the hotels referenced on a hotel reservations platform, the more useful it is to consumers, quite apart from its specific qualities and ergonomics. A competing platform therefore has to offer considerable improvement of the service provided, in order to enter the market in the face of established large-scale actors. This problem is reinforced in sectors dominated by single-homing, in which clients tend to use a single platform. 

In order to rapidly reach a critical mass by means of network effects, a condition for the success of a new platform, various different strategies may be put in place. One such strategy is the provision of services free of charge: hotel room reservation services are free for individuals, but hotels are charged on the other side; Google distributes the Android operating system to smartphone manufacturers free of charge so as to reach a critical scale and attract software application developers, it then charges end-users for some of these applications. Determining whether these strategies are anti-competitive is a sensitive issue. The usual tests concerning predatory practices, which are aimed at determining whether a dominant company is charging prices lower than the variable cost of its product, in order to oust competitors incapable of withstanding these types of aggressive pricing strategies, are as such difficult to apply to multi-sided

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models. In most cases, the absence of any charge on one side of the platform is aimed at giving rise to network effects, rather than driving competitor companies out of the market. Where indirect network effects are present, subsidising one side of the market constitutes an optimal practice, when the latter exercises an externality of attraction on the other side, or is characterised by greater elasticity of demand.

The presence of exclusivity agreements on two-sided markets provides another example of strategies that may prove to be pro or anti-competitive, depending on the particular set-up. Paradoxically, when platforms attach certain actors exclusively to themselves on one side of the market, they promote differentiation of services, which prevents excessive concentration. For example, exclusive referencing of certain hotels on certain reservation platforms could enable the maintenance of several competing platforms on the market, rather than concentration in favour of a single platform. However, everything depends upon the dosage: an excessive number of exclusivity agreements, entered into by a dominant platform, may also prevent new actors from entering the market and expanding. 

Competition law provides the necessary tools for understanding anti-competitive practices that may be implemented by digital companies. Its concepts are transverse and sufficiently powerful to identify abusive behaviours. Its means of financial penalties are applicable. Behavioural and structural measures likely to correct situations of interference with competition can

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be designed in a pertinent manner. Admittedly, it may prove necessary to adapt certain tests to the digital economy’s specific characteristics. For example, in order to analyse whether services provided “free of charge” are anti-competitive in character, the “predatory pricing tests” that are usually implemented need to be revised, so as to take the two-sided character of these platforms’ activities into account. However, this does not call the pertinence of the concept of predatory pricing into question, nor the customary need for competition regulators to set out an appropriate anti-competition theory of harm, explaining the strategy followed by the company and the effects its upon competition.

On the other hand, the customary –legal and economic– competence to be found within competition regulators does not necessarily provide the most suitable means of examining whether the results of Internet searches displayed by search engines are biased or whether data collected on users is being used for the purposes of anti-competitive strategies. Equipping competition authorities with the required technical skills, for example in the field of data processing and analysis, would enable them to extend their analyses more easily to all fields of the digital economy.

The data question

The collection of data on individuals’ behaviours and centres of interest improves the quality of services provided. Better targeting of commercial offers on the basis of the preferences

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