IMPLICATIONS OF THE DIGITAL ECONOMY ON POLICY-MAKING

1. Introduction

The growth and pace of technological advancement have fundamentally transformed our everyday lives, inadvertently impacting society and the economy as a whole. The Fourth Industrial Revolution (4IR) has seen a range of technologies integrating the physical, digital and biological platforms through innovations once thought impossible. New technologies such as nanotechnology, supercomputing and artificial intelligence (AI) have brought about a myriad of benefits. Concurrently, many are also concerned of the massive disruptions inflicted upon our current state of being by the speed, scale and force at which technology is advancing. Schwab (2017), for instance, questions the readiness of organizations and effectiveness of governments’ measures and regulations in dealing with constantly changing technologies. He also discusses the challenges and opportunities faced by the jobs market with the rise in automation. While digitalization and automation could improve one’s quality of work through greater efficiency, there are also concerns that they may worsen inequality. Low-skilled workers who are not equipped to adapt to the fast-changing environment may lose out to those who have acquired future-proof skills. Another risk highlighted by Schwab (2017) is that in a more hyper-connected world without physical and geographical limitations, there will be heightened cyber security concerns.

In sum, digitalization has become both an enabler and disruptor, giving rise to both opportunities and challenges to all levels of society. Policymakers, in particular, are burdened with the responsibility of formulating policies that ensure the maximum benefits of digitalization can be reaped without compromising people’s welfare and interests.

This topic has become ever more relevant with the outbreak of COVID-19 in 2020 which, according to D’mello (2020), further catapulted the digitalization process and transformation by at least five years ahead as economies and people are forced to adapt and go online wherever possible to reduce the spread of virus whilst continuing to function.

There is currently no single agreed definition of the digital economy, as it is a concept that is constantly evolving with the emergence of new trends and technologies. For the purpose of this paper, we shall define it as an economy being transformed by digitalization, which encompasses a wide range of applications of information technology in business processes and products (International Monetary Fund [IMF], 2018).

This paper analyzes various literature studies to draw insights on issues that policymakers need to be mindful of in the digital age. The paper is divided into five sections starting with a background, followed by an examination of the impacts of digitalization on the economy, the financial sector and central banking, implications to policy-making and to regional and domestic economies. The final section will draw some conclusions and recommendations with suggestions for further research.

2. Impacts of Digitalization on the Economy

Digitalization impacts the economy at several levels. On the production side of the economy, digital transformation enables the automation of business operations, yielding operational efficiencies. Besides transaction costs, digitalization has lowered many other costs in the economy such as search, replication, transportation, tracking and verification costs (Goldfarb and Tucker, 2017). Digitalization has also enabled access to new markets, spawned many new businesses and ways of doing business whilst providing significant scope for profit shifting across international borders away from the origination of economic activity and value creation by multinational enterprises (MNEs). On the latter, the Organisation of Economic Co-operation and Development (OECD) is particularly concerned with the gaps in the international tax system that have led to a significant loss in corporate tax revenues. In a July 2021 statement under the OECD/G20 Base Erosion and Profit Shifting Project (BEPS), 130 countries and jurisdictions have agreed to a two-pillar solution to address the tax challenges resulting from the digitalization of the economy where the minimum global tax rate applicable to large MNEs will be at least 15%.¹

At the national level, through online platforms, households are increasingly engaging in intermediation services (Bean, 2017 cited in IMF, 2018), blurring the divide between pure consumption and participative production. All of these activities have significant implications on employment and entrepreneurship.

Digitalization has also helped governments improve the delivery of public services through better communication and interaction with the public via electronic means. By designing more user-oriented applications, some e-government initiatives can leverage self-management by individuals, to improve the efficiency of services and to allow more effective monitoring. The uptake of such initiatives has helped government entities to continue serving the public while observing health guidelines during the COVID-19 outbreak. Additionally, despite some challenges (Vidal-Alaball et al., 2020), the pandemic also led to faster adoption of telemedicine (Mann et al., 2020) as the first line of defense to protect health workers attending to patients. In Brunei Darussalam, the COVID-19 situation has been managed with clear government guidance and strong support from businesses and general public in adhering to health guidelines and policies, especially in adopting the BruHealth² app, a health management application with a self-assessment tool, information-sharing and contact-tracing technology. The features of the BruHealth app have been expanded to include the users’ online personal medical records, and a tool to schedule consultations and appointments.

Aside from health, digitalization has also helped to facilitate the provision of education online or via e-learning when education institutions had to be shut down to mitigate the spread of the COVID-19 virus. However, this has brought on a myriad of new challenges as having to deliver classes online for a long period of time is not necessarily ideal nor effective without the synergy of face-to-face class interactions while also making it difficult to properly assess students. Additionally, not everyone has access to internet and the necessary devices, which raises the issue of a widening digital divide and inequality in many countries. Segments of the society who do not have access to technology will be left out — not just in terms of education but in other aspects across the board.

Take financial services for instance. Digitalization has been instrumental in bridging some gaps between high-income and low-income groups in some economies by facilitating access to financial services, thereby improving what is called “digital financial inclusion” — a term defined by The Consultative Group to Assist the Poor (CGAP, 2015) as digital access to and use of formal financial services by the excluded and underserved population. If not addressed, the digital divide may bring negative spillovers to the socio-economy such as greater social inequality between the rich and the poor; and between the young and the old in some countries. By making financial services more accessible and affordable to customers, besides poverty reduction and economic growth (Pazarbasioglu et al., 2020) at the macro level, it can also be a sustainable move for financial service providers as they can serve a wider customer base.

To fully reap the benefits of digital financial services besides having the appropriate infrastructure and access, we need to have digital trust and digital literacy amongst the population. Their absence may give rise to reduced welfare and compromised consumer protection issues.

2.1. Measurement of the impact of digitalization on GDP and productivity

Gross Domestic Product (GDP) often serves as a gauge of the economy’s overall size and health. It is a measure of production, specifically market and near-market production valued at market prices (IMF, 2018). Policymakers, government officials, businesses, economists and the public alike rely on GDP and related statistics to help assess the economic performance. Policymakers for instance refer to GDP, alongside other key statistics, when contemplating decisions on interest rates, spending, tax and trade policies, amongst others. Therefore, sound measurement of GDP is crucial for policy-making.

However, the changes that new technologies and innovations have rapidly inflicted upon the nature of work and production in recent years have led many to question the accuracy of official statistics such as GDP in measuring the economic performance of today. As ubiquitous digitalization is in the economy, there are increasing concerns that its impact on the economy is largely absent from the said official statistics. Such concerns stem from the intriguing mismatch between technological advancement and productivity. The advent of new digital innovations and technologies was expected to lead to rapid productivity growth. However, productivity growth — which can be measured by either labor productivity or total factor productivity depending on factors such as the time period under study, the quality and comparability of the capital stock data and the growth model assumed (Sargent and Rodriguez, 2000) — does not seem to have improved in tandem with advancements in technology. Labor productivity has been dismal since the early 2000s (see Fig. 1), while total factor productivity has not changed much since the 1990s, other than the dip around Global Financial Crisis (see Fig. 2). This issue is often referred to as the “productivity paradox” or “productivity puzzle”, which has led some researchers to question the effectiveness of new technologies in fostering productivity and economic growth. Others argue that it is our limited understanding of the full impact of such technologies which hinders our ability to reap the maximum benefits that they supposedly provide and as such, we are unable to measure and account for them completely in official statistics. This can be particularly concerning for policymakers as the mismeasurement or incomplete measurement of GDP could have negative implications on policy decisions that rely on such data.

A study by the OECD (Ahmad and Schreyer, 2016) highlights a number of factors likely to have caused difficulties in the measurement of output in a digital economy. They include (i) the growth of new forms of intermediation of peer-to-peer services (which blur production boundaries as consumers can now become producers through services like Uber and Airbnb); (ii) the delineation of dual-use consumer durables and investment in the sharing economy (there is no clear guidance on when consumer durables such as motor vehicles should or should not be included as investment in GDP when they are used for both personal and also in production via the abovementioned Uber platform, for instance); (iii) the availability of free and subsidized consumer products such as the Google search engine and Wikipedia and open-source software like Linux; (iv) the vague transactions through cross-border e-commerce, especially for activities such as streaming and downloading; and (v) the cross-border flows of knowledge-based assets and intellectual property.

Measurement of the digital economy has indeed become more complex with the increasingly globalized production and the rise of a new form of financial services offered by FinTech (such as Paypal, Monzo, Revolut) and TechFin companies (the likes of Google, Amazon, Apple, Alipay offering financial products and services). The availability of improved products has also posed further challenges as quality change can affect inflation via price statistics, which may have implications for monetary policy for economies facing deflationary pressures while undergoing rapid digital transformations (IMF, 2018).

Brynjolfsson et al. (2019) point out that the proliferation of new and often free information and entertainment services like Wikipedia, Youtube, Facebook and Instagram has generated welfare improvements which are not well captured in existing national accounts. What is offered on such platforms can be digitally replicated, redistributed and made available at near-zero costs with prices that are not easily observable and therefore priced at zero in the standard national accounts.

Brynjolfsson et al. (2019) create a new metric called GDP-B to capture the benefits associated with new types of products brought about by digitalization and a new framework to measure the welfare change and real GDP growth in the presence of new and free goods in the economy. They used incentive compatible choice experiments to estimate the valuations of Facebook and smartphone cameras and found that the welfare gains from Facebook alone translated to about US$16 billion annually for the period 2013–2017. This alone would have added between 0.05 and 0.11 percentage points to GDP-B growth per year in the United States during the period.

As for household consumption, if this were to include total consumer surplus derived from these free digital products including search engines, email and online messaging, it would go up by around 30% in the United States (Brynjolfsson et al., 2017). However, IMF (2018) suggests the inclusion of the total welfare of households from digital products may exaggerate the scale of potential under-measurement of GDP.

Further, Ahmad and Schreyer (2016) argue that GDP is a measure of production and not welfare and consumer surplus. Stiglitz et al. (2009) and several other researchers have suggested some alternative measurement of well-being, and not just the economy.

For policy-making, Ahmad and Ribarsky (2018) lay out the conceptualized framework for measuring the digital economy. They propose a satellite account that recognizes the multi-dimensional aspects as well as policy needs of the digital economy. This satellite account for the digital economy characterizes firms, what they produce and how they sell, within current international accounting standards. They also provide some recommendations to refine the classification system.

Considering the full debate on GDP and its adequacy as a measure of output today, Ahmad and Schreyer (2016) conclude that on balance, even though it is clear that practical measurement remains a challenge in many areas, the accounting framework used for GDP seems to be up to the challenges posed by digitalization. Some even argue that certain activities are better captured by GDP now than in the past, for instance the intermediation of peer-to-peer services like dwelling and rental services facilitated by sites such as Booking.com and Airbnb. Their “output” can be observed from their balance sheets and income statements, compared to off-the-book rentals by households in the past. Nevertheless, a key observation of this discussion is that the underlying activities are not new. What is new is the rapid pace and bigger scale at which these economic activities are taking place as a result of digitalization. This may further complicate compilation methods and classification systems in the official statistics. To this end, OECD (2014) propose some indicators that can inform policy-making and also share action plans to further advance the measurement framework for the digital economy where both stakeholders and stakeholders can work together to address the measurement challenges.

2.1.1. Impacts of digitalization and rise of automation to the labor market

Digitalization has affected the labor market but the feedback loop between new technology, jobs and skills can be complex. Technological progress has ambiguous effects on employment in general. Technology can complement workers (labor-augmenting technology) or substitute for them (labor-saving technology or automation). When such progress takes the form of product replacement, firms producing the old product go out of business, but labor demand may increase due to additional demand from firms producing the new product. In labor-replacing automation, technological change leads firms to adopt more capital-intensive technologies and to substitute labor for capital. However, various compensation mechanisms (such as price-productivity effects, scale-productivity effects, additional demand in other sectors of the economy) can counterbalance this type of reduction in labor demand.

While having few effects on the level of employment, technology strongly affects its composition (World Trade Report, 2017). This is because technological change has different effects on different workers, depending on, for example, their skills and the tasks they perform. The current technological change tends to be skills-based, whereby it increases the relative demand for skills, but it is also routine-based, in the sense that it actually decreases demand for routine tasks. Therefore, skilled workers performing non-routine tasks tend to benefit from technological change, while the latter bias can be disruptive for workers employed in routine tasks. The Future of Jobs Report by the World Economic Forum (2018) provides a good reference as it lists out many of the new roles and types of jobs that will be created, those that remain relevant as they are now and also those that will be made redundant in the future. Country-specific study by EY Singapore (2019) highlighted the challenges in the financial services industry. Adoption of data analytics and automation require a shift to more cross-functional teams and though human expertise is still required, the nature of roles will evolve and converge for some.

These changes bring about significant challenges for policymakers. Meeting the needs of an increasingly skills-based economy whilst ensuring the lesser-skilled can remain as part of the workforce is challenging. This requires labor policies to focus on training and reskilling workers, ensuring their adaptability in an economy going through rapid digital transformation.

As described in previous sections, the digital economy is also characterized by the rise of new forms of intermediation, service provision and consumption. These include new online platforms that better enable the sharing economy by facilitating peer-to-peer transactions (such as Airbnb and Uber) and new activities (such as crowdsourcing) in addition to promoting the rise of free media services, funded by advertising and the use of Big Data³ (Ahmad and Schreyer, 2016). These have brought about changes to people’s working arrangements, evident in the growing category of the just-in-time workers, the occasional self-employed and independent workers.

However, this raises the question of how sustainable it is for one to be a gig or on-demand worker. Gig workers are paid on piece-by-piece basis and often face irregular working hours. As such, they tend not to have job security and are subject to irregular earnings and fewer benefits compared to full-time employment. On the other hand, gig workers may enjoy greater autonomy and flexibility compared to the typically rigid work environment of full-time office workers.

Policymakers in some countries began to recognize the emergence of a new category of workers who are neither contractors nor employees. The risk lies in the fact that there is a rapidly expanding group of workers subject to irregular work patterns and unstable incomes with little wage protection and benefits. New forms of social and employment contracts may need to be created to cater to the changing labor market and workforce. Certain jurisdictions have taken steps to address this issue. For example, in 2018, New York City voted to enact a first-of-its-kind pay floor for Uber drivers who, as independent contractors, are not protected by federal or state minimum-wage laws (Griswold, 2018).

Finally, measurement remains an issue for policymakers. In order to have a detailed analysis for appropriate policy decisions, more data and information are needed to capture these trends. For example, the Online Labor Index (OLI) is the first economic indicator equivalent to conventional labor statistics but was developed to measure, on a real-time basis, the online labor markets across countries and occupations in the gig economy (Kässi and Lehdonvirta, 2018).

The above are just a few of the many issues faced by labor economists and policymakers on the subject. Further research is certainly required for better policies to address these transformations to society and the labor market in the digital age.

3. Impacts of Digitalization on the Financial Sector and Central Banking

Finance is seen as one of the industries most vulnerable to disruption by digitalization. This section provides a broad overview of how digitalization affects the financial sector and central banking. While it is premature to speak of disruption to traditional concepts of central banking, it is worth considering if the changes to money, financial market players and payment systems will have significant repercussions for the operations of central banks and their ability to deliver their core mandates such as monetary and financial stability. In most financial sectors, banks play a dominant role. It is getting more challenging for banks which have been slow to adapt to the changing needs of customers, while facing stiffer competition, as well as increasing regulatory and compliance burden. Bohmayr et al. (2019) summarizes the current challenges they face in Fig. 3.

In particular, cost-cutting exercises have become more evident, especially with the rising costs of compliance after the Global Financial Crisis. Regulators have clamped down on financial institutions to ensure compliance with a variety of regulations ranging from capital requirements, corporate governance, disclosure requirements including for anti-money laundering and counter-terrorist financing (AML/CFT) purposes, consumer protection issues and market conduct. In recent years, many well-known banks (HSBC Bank, BNP Paribas, Deutsche Bank, Commonwealth Bank of Australia, Danske Bank, Swedbank, just to name a few) were fined heavily, severely denting their financial positions.

The continuous survival of the banking industry will depend on how fast it can adapt and evolve with technological advancements that have fundamentally changed the financial landscape. The three key trends to watch closely that may break up a bank are the following: (i) the rise of FinTech and TechFin companies⁴; (ii) the rise of mobile-only “neobanks”⁵; and (iii) digital currencies for retail market issued by central banks that may displace the financial intermediation function of the banks. All these trends can potentially affect the financial stability of the economy.

FinTech is an upcoming player in the market that can compete with the banking industry under three possible scenarios (Lautenschläger, 2017 cited in Japparova and Rupeika-Apoga, 2017). First, banks might team up with FinTech in a smaller market. In the second scenario, an efficient and well-run FinTech firm might pose a greater threat by breaking up the value chain of the banking industry in a bigger market with fierce competition and fewer barriers for these firms. Finally, the third scenario could be where FinTech is taken over by big tech companies to become TechFin which could deeply transform the banking industry.

With the rise of FinTech and TechFin, while policymakers are keen to develop a progressive financial sector, at the same time they have to balance regulation and innovation while maintaining the core objective of financial stability. FinTech and TechFin are hybrid organizations that offer financial services and interact with consumers directly. Further regulatory gray areas or loopholes will emerge as the institutions evolve. The rise of FinTech and TechFin has blurred the lines and traditional definitions of a bank or financial intermediary, and it has become even more important that regulations are more activity-based rather than entity-based. This calls for more collaboration with regulators across different sectors including technology regulators to safeguard financial stability and consumers’ interests. Carbó-Valverde (2017) also suggested having a level playing field between banks and non-bank providers besides imposing adequate oversight and control over them.

Central banks are also keeping up with these new developments and incorporating changes to their regulations as appropriate. Several central banks have granted virtual banking licences including the Hong Kong Monetary Authority. Regionally, at the point of writing, the Monetary Authority of Singapore has awarded four digital bank licences in December 2020 (Ang, 2020) including non-bank players while Bank Negara Malaysia may issue up to five digital bank licences by the first quarter of 2022 (Bank Negara Malaysia, 2021). This would place even greater competition in the already tight market for small economies. Virtual neobanks operating under substantially lower overheads could draw depositors away from traditional banks, which can lead to some challenges for banks to manage their balance sheets. Banks need to hold some portion in reserves and lend the rest out to generate revenue. Therefore, losing deposits can create a potential mismatch of assets and liabilities on traditional banks’ balance sheets. If neobanks are efficient and provide good services for customers to transact, traditional banks can also lose income derived from transactional fees including service fees. As long as the neobanks are well capitalized and well managed, coupled with effective oversight by the regulators, the risk of their failure leading to systemic risk in the financial sector may be limited.

The development of digital currency is another recent phenomenon of digitalization. Though these new forms of currencies do not necessarily fulfill all the characteristics of money, with wider use they can lead to some disruptions in the financial sector. Bech and Garratt (2017) classify money based on several criteria: (1) issuer (central bank or other); (2) form (electronic or physical); (3) accessibility (universal or limited); and (4) transfer mechanism (centralized or peer-to-peer). They regarded central bank-issued digital currencies or CBDCs as electronic forms of central bank money that may be exchanged peer-to-peer in a decentralized manner.

Given the limited adoption of digital currencies and the crashes of unregulated privately issued cryptocurrencies and various scams in 2018, there is a growing interest in CBDCs. CBDCs have wider implications on the economy and the financial sector given their potential of generating greater uptake by the general public and the market since they are backed by a trusted issuer. Thus, CBDCs are potentially a new form of digital central bank money that can be distinguished from reserves or settlement balances held by commercial banks at the central bank. There are two main types of CBDCs — retail/general purpose and wholesale. Retail CBDCs would be universally accessible and directly available to the public whilst wholesale CBDCs would only be available to financial institutions for settlements of payments and securities.

In general, central banks hold conflicting views on the issuance of CBDCs — some see them as necessary and inevitable while others remain skeptical. A retail CBDC in particular would act as a replacement for physical currency issued by the central bank and depends on the model adopted, this could potentially diminish the role of intermediaries such as banks which would have broader implications to the financial sector. From the consumer’s perspective, a widely accepted digital currency such as CBDC can facilitate less expensive and yet more efficient options for making retail payments for person-to-person, e-commerce and cross-border transactions for consumers and merchants alike.

However, several studies, most notably the one by the Bank for International Settlements (BIS, 2018) highlighted that despite better efficiency and traceability of payment transactions, the introduction of retail CBDCs requires careful consideration. A retail CBDC can crowd out the banks as households, institutions and the market in general may shift retail deposits towards the central bank leading to potential financial stability risk with weaker banks at risk of facing bank runs and stronger banks losing a low cost and stable source of funding.

On the other hand, wholesale CBDCs combined with the use of distributed ledger technology (DLT) could enhance settlement efficiency for transactions involving securities and it has the potential to address long-standing challenges such as cost and efficiency in transactions and also payment system operational resilience. However, the degree of DLT and blockchain technology research and experimentation vary greatly among central banks, and so do their motivations. Nonetheless, BIS (2018) concludes that combining the issuance of wholesale CBDCs utilizing DLT does not seem to offer clear advantages over existing payment infrastructures which are quite well developed to serve current market needs.

However, the announcement of digital currency Libra (now known as Diem) by Facebook back in 2019 has prompted even more central banks to put more effort in research, experimentation or development of CBDCs, especially into retail CBDC (Auer et al., 2020). The most advanced retail CBDC project is that by the People’s Bank of China where Digital Currency Electronic Payment (DC/EP) has been rolled out to 10 regions in China at its pilot stage and will also be made available for foreign visitors, including the 2022 Winter Olympics as a trial (Tang, 2021). China has embraced technological innovations in its digitalized economy as an important driver of high-quality economic development and sees the issuance of e-CNY can meet public’s demand for digital cash supported by a safe and efficient retail payment infrastructure (Working Group on e-CNY Research and Development of the People’s Bank of China, 2021). Introduction of e-CNY into the market of digital payments services currently dominated by Alipay and WeChat Pay will not only add diversity but will also change the market dynamics with further implications (Bloomberg News, 2021).

4. Implications to Policy-Making and Issues to Consider

To map the scale of the impact of digital transformations on the economy, we will need the right data and mechanisms to track the changes in outputs, especially the uncaptured statistics in traditional classifications, cross-border transactions, emerging and declining occupations, evolving skills, the prevalence of gig and sharing economy and more. In the market alone, there are about 2.5 quintillion⁶ bytes of data being created every day with the growth of the Internet of Things (IoT). Data are often coined as the new oil and it is not surprising to observe the prevalent race by companies and institutions to capture as much data as possible nearly everywhere, databases are often sold as we can see tracking cookies linked to many websites and unauthorized parties. Policymakers may feel the control of the wealth of data by private sector players is undesirable and can affect consumers in terms of privacy, their rights if exploited.

Harnessing the power of data to produce meaningful analysis that aids policy-making and business decisions is becoming more important than ever. Data itself has no intrinsic value and it is being acquired continuously and in abundance. It can also be stored easily, with the availability of massive data storage devices and electronic means. The true value creation lies within the processing and organization of such data to draw meaningful insights to help with decision-making, to solve a specific problem and more. The process of turning data into something useful does require resources where costs will be incurred. Data specialists spend a large amount of time sieving through data from various sources, cleansing and restructuring them into usable formats. These carefully prepared data also need to be further verified and validated wherever possible before these data can be used in models, algorithms and business intelligence tools for analysis. Both the quality of data and analysis are crucial to allow policymakers to make sound and informed decisions.

Data flows indeed underpin the delivery of products and services in the digital economy where buyers and sellers exchange information for trade to take place. Personal data such as location and preference are collected to deliver personalized products, to improve consumer experience and to produce relevant content in targeted advertisements. The process of data gathering does come with its own issues — whether there was authorization and consent for the data to be collected, particularly personal data, and if there were adequate measures in place to safeguard the data from theft and leakage. With digitalization increasingly being embraced by governments, financial institutions and private firms, data security and data privacy are crucial to think about.

There have been many reported cases of cyberattacks around the world targeting personal and sensitive information that happened at both national and institutional levels. Consumers are also wary of possible theft of their funds via cyber means if the integrity of a bank’s financial transaction data is compromised. Central banks are concerned with their own cyber resilience too, not only in relation to the risks of financial loss but also reputational damage as they have to maintain public trust. Cyberattacks could also occur outside national borders and are often unpredictable. It is therefore not surprising that more and more governments are adopting laws and regulations on data protection.

APEC (2017) reported that 13 out of 21 economies have comprehensive data protection laws in place, with different definitions of personal data and sensitive information. Several APEC economies also have regulations in place to restrict cross-border data flow with varying degrees; from stringent measures that completely prohibit the exportation of data in any circumstances, to allowing some cross-border flows of data under certain conditions such as consumers’ consent. While some policies allow data to be sent for offshore processing, others require the storage and processing of data to be done locally, leading to the establishment of local data centers to store data that are deemed sensitive by the respective economy (APEC, 2017). So far, the European Union’s General Data Protection Regulation⁷ (GDPR) put into effect since May 2018 is the toughest data privacy and security law, which is applicable to any organization in the world that collects data from EU residents.

Such policy measures can incur large compliance costs. Costs to establish data centers can be an entry barrier for companies to operate in domestic economies, especially if they already have data centers elsewhere. Restrictions on cross-border data flow can also lead to lost efficiencies where better and varied data from other economies cannot be gathered to improve analysis and outcomes. Small and medium enterprises can also be limited to utilize local cloud operators instead of tapping into better resources by other service providers if cross-border data restrictions are in place. Establishing a local data center may appear to serve national security objectives, but one has to be mindful that it is not the locality of where the data are hosted that matters. It is the cyber security and encryption technology that prevent theft and data hacks that matter, since national boundaries do not deter cyber criminals who can reside anywhere in the world to attack.

Digitalization challenges existing policies in a myriad of other areas. As a result, silos are disintegrating, and hard borders are becoming less relevant. This means that stronger co-operation and collaboration are critical, as well as a reconsideration about how policy is developed and implemented. In particular, a flexible, forward-looking and integrated policy framework is essential to ensure a coherent and whole-of-government approach to fully realize the potential of digital transformation and address its challenges.

The OECD is developing an integrated policy framework under its Going Digital project.⁸ This includes seven building blocks — access, use, innovation, trust, jobs, society and market openness — that are supported by quantitative indicators and practical policy guidance. The Going Digital integrated policy framework brings together the policies that governments must consider in order to shape a common digital future that improves lives and boosts economic growth and well-being.

To catch up, not only do governments in developing economies need an integrated policy response to digital transformation, they must also seize the opportunity to go digital themselves. Many governments and administrations are currently exploring the possibilities, testing the potential and evaluating the effectiveness of using digital technologies for improving policy design, implementation and enforcement. Governments can use digital technologies to improve efficiency and targeting; enable innovative policy design and rigorous impact evaluation, and expand citizen and stakeholder engagement. Some of the initiatives to reduce red tape and paperwork include the implementation of National Digital Identity (NDI) systems to allow digital identification of individuals and businesses in their interactions with the governments in a more convenient and secured manner. Financial institutions can also leverage paperless Know Your Customers (e-KYC) or biometric ID approach to improve efficiency and processes for customers.

To measure the impact of digitalization on the economy, several issues need to be addressed. These include the conceptual boundaries of GDP; the prices of new and improved digital products; and unrecorded digital sector output (IMF, 2018). The digital sector is more narrowly defined as the segment that covers the core activities of digitalization, ICT goods and services, online platforms and platform-enabled activities such as the sharing economy. Although the digital sector accounts for less than 10% of most economies in terms of value added, income or employment (IMF, 2018), it is expected to grow in importance.

Indeed, there are methodological challenges and also data availability issues due to budget constraints for data collection. However, without accurate measurement, we are unable to fully understand the impact of new technologies, new goods and services on the economy in terms of productivity, growth and welfare. Nonetheless, Ahmad and Schreyer (2016) suggest that current measures remain adequate to capture the digital economy. Regardless, statisticians and authorities should continue to monitor the progress of digitalization and to review current compilation methods to ensure the impact of digitalization on the economy is sufficiently captured.

5. Implications of Digitalization to Regional and Domestic Economies

According to the 2018 e-Conomy SEA report jointly produced by Google and Temasek of Singapore, Southeast Asia is the world’s fastest growing region in terms of digital economy (Google and Temasek, 2018). The 2016 and 2017 reports foresaw a US$200 billion digital economy in the region by 2025, but after seeing the region’s digital economy hit an inflection point in 2018, the forecast is now expected to be closer to US$240 billion by 2025. Southeast Asia’s digital economy is powered by the most engaged mobile internet users in the world, and as such industries like e-commerce, online media, online travel and ride-hailing grew at an unprecedented rate. Investors have taken notice and are pouring record amounts of funds into the region. FinTech investments in Southeast Asia increased by more than 30% in 2018 to nearly US$6 billion. Located in the same region, Brunei Darussalam needs to prepare itself both in terms of infrastructure and environment to capitalize from the regional growth.

In relation to its small population of 453,600⁹ (as of 2020), Brunei Darussalam has the advantage of being tech savvy with high mobile and internet penetration with active social media users¹⁰ (Fig. 4). There is great potential to drive digitalization in the economy with close coordination in policies and initiatives to ensure Brunei Darussalam can fully benefit from technological advancements.

Brunei Darussalam has set up the Digital Economy Council¹¹ (DEC) and, in June 2020, unveiled the Digital Economy Masterplan 2025,¹² which outlines strategies for Brunei Darussalam to become a “Smart Nation”. One of the key challenges identified is the need to bring down the cost of accessing technology further to provide incentives for more uptake and widespread utilization of digital technologies. Nonetheless, there has been some progress towards building a Digital Government as several ministries and departments have turned to the delivery of a range of e-services via the use of a “one-stop-shop” government portal called E-Darussalam.¹³ This has improved efficiency in some ways. In addition, for a small nation like Brunei Darussalam which already has 4G in place, it is not impossible to be an early adopter of 5G technology, or even be the first in the region. This will require close collaboration of government agencies, telecommunications companies (telcos) and industry partners in Brunei Darussalam to realize its vision of becoming a future smart nation.¹⁴

In terms of gross value added (GVA) contribution to domestic economy, the financial sector is the second largest service sector after the government services/public administration in the non-oil and gas sector in Brunei Darussalam. In 2020, it contributed about 5.5% to the economy.¹⁵ The financial sector mainly consists of banking, insurance and capital markets with the banking industry being the dominant player. In a small market, the banking industry is facing more challenges than before and it needs to keep up or risk getting left behind and fail to survive in the digital age.

If the banking industry can adapt quickly to leverage the power of digitalization while managing customers’ expectations to deliver quality services, it can retain existing customers’ loyalty, acquire new customers and generate more revenue. As customers migrate to digital channels, this would allow data and information to be gathered more readily. As discussed in the literature (many cited in Japparova and Rupeika-Apoga, 2017), with the use of digital technology and data gathered, financial institutions are able to target their customers better and deliver customized or personalized products and services. Through good customer relationship management, financial institutions can gain customers’ trust and loyalty and also benefit from repeated purchases of products and services. They may even gain further referrals from satisfied customers.

The financial institutions will have to invest in good cyber security safeguards to protect customers’ data and information to maintain trust. To address data privacy and security concerns, policymakers also need to review current legislative framework and amend where necessary to ensure that regulations are balanced and well-implemented without limiting the potential benefits of digitalization.

Brunei Darussalam is also experiencing the rise of gig economy, partly driven by the high level of youth unemployment. Gig workers work informally and enjoy a flexible work schedule but this can come with a cost in a competitive marketplace. Unless an individual offers something unique in skills/goods/services, he may lose his client base quickly should he choose to not work for an extended period of time. Clients are becoming less patient and can easily find substitutes from online searches. Therefore, gig workers may soon find themselves “trapped” and need to work constantly with thin margins as the digital economy has given more bargaining power to the consumers over the producers.

In the case of Brunei Darussalam, there are many micro businesses that prefer to operate from home and leverage free or low-cost advertising avenues such as Facebook and Instagram to promote their businesses. However, there is so much information on social media that it becomes a challenge to maintain visibility and gain customers’ attention. This avenue of advertising may not be sustainable to allow them to expand fast. These informal businesses operate in a less stringent business environment with little overhead costs and compliance. It remains unclear how profitable and sustainable they are in providing more stable self-employment or employment of workers. Unless data and information are gathered on these businesses, there remain limitations on what policymakers can do to increase their value-add to the economy.

As for employment, to future proof the workforce, it is never too early for the government to consider the needs of the future industry as well as the market. They need to assess the existing education and vocational training systems to ensure they remain capable of producing individuals with the relevant skillsets. This will help minimize the impact of technology unemployment in the foreseeable future.

6. Concluding Remarks and Recommendations

All levels of society, businesses, institutions and governments must embrace and adapt to this inevitable digital revolution. To fully reap the benefits of digitalization, one has to be able to manage the associated costs and negative externalities to the best of one’s abilities by having cyber resilience measures in place, appropriate regulations and enforcement, as well as monitoring and surveillance to keep potential risks in check. Nonetheless, there are many issues relating to the digital economy that need to be better understood.

The rapid growth of digitalization has brought to light some weaknesses in the GDP compilation method, particularly in the digital sector and of digital transactions which may affect the quality and relevance of GDP data for economic surveillance. In the classification of digital activities, coverage can be further improved to include digital platforms, digital products and services, and also digital transactions. For better measurement, the classifications need to be refined so as to improve data collection to determine the GDP production boundary as household non-market production has been made possible with greater access to digitalization leading to welfare gains which are not currently captured in GDP.

Businesses need to review their business models and processes in order to leverage their customer base and technology enabling delivery of goods and services in a highly competitive environment. Intangible capital including data has become increasingly important — especially in the value creation process and one needs to consider the treatment of data as an asset or product.

The population has to be digitally literate as financial literacy alone will not be sufficient to safeguard their financial well-being. Policymakers can leverage digital technologies to raise awareness through various channels to educate the public and also improve efficiencies in their processes. Policies can be devised to safeguard consumers’ interests in terms of data protection while giving individuals the freedom of choice in sharing data by consent without the loss of efficiency.

Policymakers cannot do it all alone, they need to engage the private sector and other stakeholders to work together. Steps must be taken to ensure the country is ready to handle digitalization that can affect all walks of life; protect the vulnerable; close loopholes that may be taken advantage of; ensure financial stability is not compromised; ensure the labor force stays relevant in the digital economy; ensure the education system remains relevant; measure the economy better and balance legislation with innovation.

In the fast-changing world fueled by the 4IR, key changes to leadership are also inevitable. Organizations should do away with the practice of working in silos and in a compartmentalized working space and enable more synergy and close cooperation within their institutions. Leaders need to collaborate and appreciate diverse networks across many disciplines and to develop a shared understanding of the issues at hand. For effective policy-making, more collective thinking and wisdom are needed for problem solving to ensure holistic and flexible solutions can be delivered.

Disclaimer

The views expressed in this paper are those of the author(s) and do not necessarily represent the views of Brunei Darussalam Central Bank (BDCB), the Board of Directors, or BDCB Management.

Notes