How broadband, digitization and ICT regulation impact the global economy

Global econometric modelling

November 2020

Acknowledgements

This report has been prepared by the International Telecommunication Union (ITU), led by the ITU Telecommunication Development Bureau (BDT), Digital Knowledge Hub Department (DKH), Regulatory and Market Environment Division (RME). It is based on regional findings from research prepared for the ITU global study on the economic contribution of broadband, digitization and ICT regulation published in 2018. Each of the regional studies is available here: https://www.itu.int/en/ITU-D/Regulatory-Market/Pages/Economic-Contribution.aspx..

This study is based on extensive compilation and analysis of statistical data from national and international sources and on data from the ITU ICT Regulatory Tracker and the Digital Ecosystem Development Index, developed with funding from CAF (Corporación Andina de Fomento) Development Bank for Latin America.

Raul Katz (Ph.D., Management Science and Political Science, Massachusetts Institute of Technology) is lead author. Dr Katz is currently Director of Business Strategy Research at the Columbia Institute for Tele-Information, and President of Telecom Advisory Services, LLC (www.teleadvs.com). Before founding Telecom Advisory Services, he worked for 20 years at Booz Allen Hamilton, where he was the Head of the Telecommunications Practice in North and Latin America and member of its Leadership Team.

Further important contributions were provided by Fernando Callorda (BA, MA, Economics, Universidad de San Andrés-Argentina). Mr Callorda is a project manager with Telecom Advisory Services, LLC, an Assistant Professor at the Universidad de San Andrés and a researcher at the National Network of Public Universities. Before joining Telecom Advisory Services, he was a consultant with Deloitte and staff analyst in the Argentina Congress.

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Please consider the environment before printing this report.

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Some rights reserved. This work is licensed to the public through a Creative Commons Attribution-Non-Commercial-Share Alike 3.0 IGO license (CC BY-NC-SA 3.0 IGO).

Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited. In any use of this work, there should be no suggestion that ITU endorse any specific organization, products or services. The unauthorized use of the ITU names or logos is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: “This translation was not created by the International Telecommunication Union (ITU). ITU is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition”. For more information, please visit https://creativecommons.org/licenses/by-nc-sa/3.0/igo/

Foreword

As the global economy reels from the shock of COVID-19, decisions taken now that impact economic recovery and growth will be of the utmost importance for the decade ahead. For those of us in the global ICT community and for those in other industries charged with making strategic infrastructure decisions in the years ahead – government policy-makers, regulators, influencers, operators and service providers – this expert report is especially valuable at this time. Its findings are clear and its recommendations are specific, concrete and practical.

The analysis looks at how fixed and mobile broadband as well as digital transformation impact the economy, globally and at regional levels. It also reports on how our institutions and our regulatory approach affect the development of the global digital ecosystem. It is based on the ITU global study on the economic contribution of broadband, digitization and ICT regulation (2018), and related regional econometric modelling studies – each of which adds a rich and detailed regional dimension. The data set that lies at the heart of this work is world class – global, up-to-date and robust.

Our work in building ICT policy, infrastructure and services that deliver inclusive and sustainable growth for people worldwide is of special importance at this time. This ITU expert report lays down important markers for us as we help reinvent and recast the shape of post-COVID-19 economies worldwide – we hope its findings will be useful to a wide readership.

Doreen Bogdan-Martin
Director, ITU Telecommunication Development Bureau

Table of Contents

Foreword

List of tables and figures

Executive summary: How broadband and digitization impact the global economy

1 Fixed broadband and its impact on the economy

1.1 Impact of fixed broadband at global and regional levels

1.2 What the modelling showed globally and by region

2. Mobile broadband and its impact on the economy

2.1 Impact of mobile broadband at global and regional levels

2.2 What the modelling showed globally and by region

2.3 Fixed vs. mobile broadband – economic impact by level of development

3 The economic impact of digitization

3.1 An index to measure the development of digital ecosystems: 8 pillars, 64 indicators

3.2 Digitization correlates with economic development

3.3 Digitization – on par with mobile broadband in boosting economies

4 Policy and regulation drive development of digitization

Annex A: Review of the related research literature

Annex B: Countries analysed for economic impact of fixed and mobile broadband

Annex C: Data sources for models testing the economic impact of fixed and mobile broadband

Annex D: Indicators included in the Digital Ecosystem Development Index and data sources

Annex E: Econometric methodology

Acronyms

Bibliography

List of tables and figures

Tables

Table 1: Econometric model equations

Table 2: Regional GDP growth impact of an increase in 10% of broadband penetration (in per cent)

Table A.1: Structure of original digitization index

Table A.2: ICT Regulatory Tracker and CAF Digital Ecosystem Development Index pillars￼

Figures

￼Figure 1: Global sample: GDP growth impact of an increase in 10% of fixed broadband penetration (in per cent)

Figure 2: Regional GDP growth impact of an increase in 10% of fixed broadband penetration (in per cent)

Figure 3: Economic contribution – fixed versus mobile broadband

Figure 4: Global sample: growth impact of an increase in 10% of mobile broadband penetration (in per cent)

Figure 5: Regional GDP growth impact of an increase in 10% of mobile broadband penetration (in per cent)

Figure 6: GDP growth impact of an increase in 10% of broadband penetration (in per cent)

Figure 7: Eight pillars of the Digital Ecosystem Development Index

Figure 8: The Index – 64 indicators grouped under eight pillars

Figure 9: Comparative development of the digital ecosystem (2018)

Figure 10: Correlation between GDP per capita and Digital Ecosystem Development Index, 2015

Figure 11: Impact on GDP of 1% increase in independent variable, 2004-2015

Figure 12: Impact on GDP of 10% increase in digitization, 2004-2015

Figure 13: Regression model indices

Figure 14: Impact of the 10% of the lagged ITU ICT Regulatory Tracker on the Digital Ecosystem Development Index

Figure A.1: Conceptual framework for the impact of broadband on economic output over the diffusion process

Figure A.2: Studies measuring the GDP impact on broadband speeds (impact of 1% increase in speed on GDP) (%)

Figure A.3: Comparative development of the digital ecosystem (2018)￼

Executive summary: How broadband and digitization impact the global economy

This study uses econometric modelling to examine two major components of great importance to all those concerned with investment decisions in ICT and the digital ecosystem over the coming decade. The modelling is built on data from 139 countries between 2007 and 2018 – an up-to-date data set that is robust, high-quality and global in scope.

The first component examined is how broadband and digitization impact the economy. The second is how institutional and regulatory maturity impact the growth of the digital ecosystem.

Four major findings

Our evidence points to four major findings that are of great import in informing governments, policy-makers, regulators and operators as they formulate general infrastructure and ICT investment decisions in the years ahead. The findings are:

1. Developing countries should implement policies to maximize mobile broadband[1] adoption, as the main digital technology contributing to economic development and addressing the digital divide.

2. Developed countries should adopt policies which favour fixed broadband penetration as a key contributor to their economic growth.

3. Beyond broadband, all countries should aim to increase the development of digitization, which encompasses not only infrastructure deployment but its usage to foster the digital transformation of industries and improve consumer wellbeing.

4. Regulatory and institutional maturity in the ICT arena do indeed make a significant difference – and are important in driving the growth of digitization.

The study confirms that the economic impact of fixed broadband is guided by a return to scale effect: economic impact grows with penetration. The economic benefit of mobile broadband depicts a saturation effect: its economic contribution declines with penetration.

Developing countries: Accelerate development of mobile broadband

Developing countries should accelerate the development of mobile broadband to maximize economic impact. Penetration of mobile broadband in OECD countries is at 74 per cent in terms of unique subscribers – but comparable figures for the Africa region are 31 per cent, for Latin America 57 per cent and for the Asia-Pacific region 52 per cent.[2] Since the economic impact of mobile broadband is higher in developing countries, such countries should maximize its adoption.

Six concrete steps for developing country governments to consider:

• Policy and regulation. Encourage policy and regulatory measures that facilitate infrastructure deployment in rural and isolated areas: these include the sharing of infrastructure, interconnectivity, and effective use of spectrum.

• Emerging technologies. Promote the use of emerging technologies to address the need for affordable digital infrastructure and services.

• Incentives and collaboration. Promote deployment of mobile broadband infrastructure in remote and rural areas through incentives that are attractive to private sector operators. Stimulate collaboration between private sector firms within your digital ecosystem.

• Affordable pricing. Focus on mobile broadband affordability of non-adopters: implement government initiatives that drive affordable pricing for your most vulnerable populations.

• Content of importance and relevance to your citizens. Complement economic-focused efforts by promoting the development of local Internet content and languages.

• Skill up your non-adopters. Focus on building the digital skills of non-adopters to address digital illiteracy.

Developed countries: Focus on technologies that boost digitization of production

Developed countries should focus on technologies that accelerate the digitization of production: these include ultra-broadband wireline (FTTx and DOCSIS 3.1) and 5G – critical infrastructure technologies that enhance digitization of production, which will in turn boost economic impact. OECD countries have reached 5G coverage of 39 per cent[3] while FTTx household penetration is at 21 per cent.[4]

Seven concrete steps for developed countries to consider:

• Grow infrastructure and demand. Promote commercial and investment cases that combine the benefits of telecommunications infrastructure with other enabling technologies (e.g. AI, AR/VR) to grow infrastructure and ICT demand from enterprises.

• Use regulatory sandboxes enabling enterprises to test emerging technologies and use cases free of regulation.

• Spectrum allocation and new services. Launch 5G pilot projects to obtain feedback and to support design of future spectrum allocations – at the same time stimulating the adoption of new services.

• Balance new technologies with re-skilling. Recognize that advanced technologies can eliminate jobs. As you move to the digital transformation of production, ensure digital skills requirements are identified and retraining taken into account.

• Flexibility in regulation. Keep enough flexibility on regulatory rules and procedures (for example the use of spectrum) to foster innovation and new technologies.

• Long-term policies. Recognize that building infrastructure is a multi-year process that needs to be underpinned by long-term policies for predictability and regulatory certainty.

• Balance consumer protection with commercial returns. Recognize that competition models need to protect consumers, while ensuring adequate returns are available to commercial players making the investment.

Addressing all countries: Make regulation and ICT policy work for the economy

This report clearly demonstrates that broadband technologies on one hand, and effective ICT regulation on the other, undoubtedly help grow national economies and the prosperity of the people.

All countries should leverage regulatory frameworks and institutions in accelerating digitization – forging sound ICT policy that maximizes economic impact within a simplified institutional architecture.

Three specific policy approaches are recommended:

• Incorporate the economic impact of digitization in your assessment of policies. Policy-makers and regulatory agencies in all countries should integrate advanced socio-economic impact analysis into their policy development. Often, ICT policy-making takes only the engineering perspective into account. This task is best accomplished through close collaboration and partnership with academia and research institutions.

• Be collaborative and quick. Adopt a collaborative approach involving policy-makers, regulators and private operators. Build policy and regulation on principles of simplification and speed.

• Consult and be transparent. Allow for intense public participation and consultation with civil society as you build regulation. Give stakeholders the most transparent information.

Three focus areas

This report uses global econometric analysis – based on robust, reliable data – to measure the impact of broadband (fixed and mobile) and digital transformation on the economy as a whole. It also examines how institutional and regulatory variables impact the development of the digital ecosystem at global level.

The study builds on previous ITU-published studies – using econometric modelling – that looked at how broadband, digitization and ICT regulation[5] contribute to the economy at the global and regional levels.

The study is built on three key analyses:

1. How fixed and mobile broadband are impacting the economy: Economic models, designed to explore how broadband contributed to the economy, have been developed primarily in the first decade of the 21st century. Are they still valid? This study brings fresh scrutiny to bear. On the basis of large data sets, the report relies on long historical series and asks whether the economic boost of broadband increases with penetration – the so-called return to scale effect[6]- or is broadband’s economic impact undergoing a “saturation effect” therefore yielding diminishing returns. Importantly, the analysis asks what the key differences are in how fixed and mobile broadband play in an economy, according to its level of development.

2. How digitization contributes to the economy: It is important to note that “digitization” is much broader in scope than broadband. It encompasses digital services infrastructure, connectivity, digital transformation both of households and production, the development of digital industries, and the availability of digital factors in production. So, what is the impact of digitization on GDP and productivity when compared to broadband? This report presents analysis of this question region by region.

3. How policy and regulatory frameworks affect market growth in digital services and applications: How exactly do regulation and institutions impact the development of the digital economy – the transformation of the techno-economic environment and socio-institutional operations through digital communications and applications. Given that growth of digitization is driven largely by the private sector, just how important are policy and regulatory variables in growing the digital economy?

1 Fixed broadband and its impact on the economy

Developed countries with high penetration of fixed broadband realize larger benefit from the technology than developing nations. The impact is driven by a “return to scale”:

1 when fixed broadband penetration is low, economic impact is minimal; but

2 when fixed broadband infrastructure reaches a critical level of development, typical of developed countries, it starts to have a significant impact on the economy.[7]

1.1 Impact of fixed broadband at global and regional levels

Data for 139 countries between 2010 and 2017 (in some cases between 2007 and 2018, and for others between 2011 and 2017) were examined. In each case, identical econometric structural models used the following four equations[8]:

Table 1: Econometric model equations

Aggregate production function

GDP per capitait = a_1(Capitalit)+a_2(Educationit)+a_3(Broadband_Penetrationit)+ eit (1)

Demand function

Broadband_Penetrationit=b_1(Rural_population)it)+b_2(Broadband_Price)it+b_3(GDPper capita)it+b_4(HHI)it+eit (2)

Supply function

Broadband_Revenueit=c_1(Broadband_Price)it+c_2(GDP per capita)it+c_3(HHI Fixed broadband)it+ eit (3)

Output function

ΔBroadband_Penetrationit = d_1(Fixed_Broadband_Revenueit )+ ɛ4it (4)

• In order to test the current economic impact of telecommunication technology, two models were constructed (one for fixed broadband and another one for mobile broadband) and specified for two cross-sectional samples of countries. This methodology would allow the three hypotheses explained above to be tested while controlling for endogeneity effects.[9] The review of related relevant research literature is available on Annex A as well as, the complete methodology applied is described in Annex E.

• The econometric model was first run for all countries and then for distinct groups of countries according to their level of development:

◦ Countries with GDP per capita higher than USD 22 000 (50 countries)

◦ Countries with GDP per capita between USD 12 000 and USD 22 000 (26 countries)

◦ Countries with GDP per capita lower than USD 12 000 (63 countries)

• The economic impact of fixed broadband by region was also measured (the list of countries analysed for the economic impact of fixed and mobile broadband is available in Annex B):

◦ Africa region (34 countries)

◦ Americas region (18 countries)

◦ Arab States region (14 countries)

◦ Asia-Pacific region (18 countries)

◦ Commonwealth of Independent States region (8 countries)

◦ Europe region (38 countries)

Confirmed – globally, fixed broadband impact is higher in more developed countries

The econometric models run for the global sample confirm the “return to scale” effect: fixed broadband economic impact tends to increase with economic development (see Figure 1).

Figure 1: Global sample: GDP growth impact of an increase in 10% of fixed broadband penetration (in per cent)[10]

Note: The impact on countries with GDP under USD 12 000 per capita is not statistically significant.

Source: ITU[11]

1.2 What the modelling showed globally and by region

Figure 2: Regional GDP growth impact of an increase in 10% of fixed broadband penetration (in per cent)

Source: ITU

Econometric modelling was applied to all the world’s regions, assuming an increase of 10 per cent in fixed broadband penetration to calculate increase (or not) in GDP per capita, the models suggested the following results:

• Africa region: most countries would see no increase.

• Americas region: countries across this region (North America and for Latin America and the Caribbean) would enjoy an increase of 1.88 per cent. Latin America and the Caribbean only would enjoy an increase of 1.57 per cent.

• Arab States region: countries would enjoy an increase in 0.71 per cent.

• Asia-Pacific region: the entire region would enjoy an increase of 1.63 per cent while mid- and low-income countries in the region would see no increase.

• Commonwealth of Independent States (CIS) region: the region would enjoy an increase in 0.63 per cent in GDP per capita.

• Europe region: the results suggest that an increase of 10 per cent in fixed broadband penetration in high-income Europe region countries would yield an increase in 2.94 per cent in GDP per capita. If only low-income Europe region countries are included in the model, the impact is statistically not significant.

2. Mobile broadband and its impact on the economy

The economic contribution of mobile broadband is greater in countries and regions with lower levels of economic development and lower relative mobile penetration. The impact of mobile broadband is driven by a “saturation” or “diminishing returns” effect.

In economics, “diminishing returns” is the decrease in the marginal (incremental) output of a production process as the amount of a single factor of production is incrementally increased, while the amounts of all other factors of production stay constant. In this case, we apply the concept to explain that the economic impact of mobile broadband decreases with penetration. The concept of “saturation” is applied to explain that, after a certain point in the diffusion process, no matter how much mobile broadband is adopted, no tangible economic effect will be registered.

2.1 Impact of mobile broadband at global and regional levels

The corollary is that the economic impact of mobile broadband diminishes in countries and regions with higher levels of penetration and development.

How is this explained? A number of factors are at play:

• Early broadband adopters (such as large enterprises and government services) gain most from mobile broadband, while late adopters (such as small and medium enterprises) will gain less.

• Incremental infrastructure deployment will not yield proportional gains where critical levels of telecommunication/ICT infrastructure and usage have already been attained.

• The national economic impact is at its maximum when telecommunications/ICT infrastructure investment has reached critical mass. Beyond that point, economic impact slows down, reflecting “diminishing returns”.

• In countries with low fixed broadband penetration (i.e. low GDP per capita), mobile broadband is the technology with high economic impact – the “substitution effect”.

Figure 3: Economic contribution – fixed versus mobile broadband

Source: ITU

The economic impact of mobile broadband declines as penetration levels increase

In economic terms, the impact of mobile broadband tends to decline with penetration. Governments should not however stand down policies aimed at stimulating its adoption: mobile broadband in many countries is the single most important technology that provides citizens and consumers with access to the Internet, thereby providing enormous social value.

This study measured the economic impact of mobile broadband both at the global level and by region to test the “diminishing returns” effect, looking at data for 139 countries between 2010 and 2017 (in some cases through 2018).

• Econometric structural models (composed of four equations specified similar to the case of fixed broadband) tested the economic impact of mobile broadband:

◦ The global analysis relied on 3 858 observations between 2010 and 2017. For the regional analysis, a total of 4 061 observations between 2010 and 2018 were utilized.

◦ Models included country, year, and fixed effects.

• The econometric model was first run for all countries and then for distinct groups of countries according to their level of development:

◦ Countries with GDP per capita higher than USD 22K (50 countries).

◦ Countries with GDP per capita between USD 12K and USD 22K (26 countries).

◦ Countries with GDP per capita lower than USD 12K (63 countries).

• The economic impact of mobile broadband was also measured by region:

◦ Africa region (34 countries)

◦ Americas region (18 countries)

◦ Arab States region (14 countries)

◦ Asia-Pacific region (18 countries)

◦ Commonwealth of Independent States region (8 countries)

◦ Europe region (38 countries)

2.2 What the modelling showed globally and by region

Globally, mobile broadband economic contribution is higher than fixed broadband, although impact decreases with economic development

Figure 4: Global sample: growth impact of an increase in 10% of mobile broadband penetration (in per cent)

Source: ITU

Regional analysis: developing economies benefit more from mobile broadband

Figure 5: Regional GDP growth impact of an increase in 10% of mobile broadband penetration (in per cent)

Source: ITU

The econometric modelling was applied to all the world’s regions, assuming an increase of 10 per cent in mobile broadband penetration to calculate increase (or not) in GDP per capita, the models suggested the following:

• Africa region: the majority of countries would enjoy an increase of 2.46 per cent.

• Americas region: North America, Latin America and Caribbean would enjoy an increase of 1.16 per cent in GDP per capita. Latin America and the Caribbean countries would enjoy an increase of 1.73 per cent.

• Arab States region would enjoy an increase in 1.82 per cent in GDP per capita.

• Asia and Pacific region countries overall would enjoy an increase of 0.51 per cent. Mid- and low-income countries only would enjoy an increase of 2.44 per cent.

• Commonwealth of Independent States region would enjoy an increase of 1.25 per cent.

• Europe region countries overall would enjoy an increase of 2.1 per cent. When low-income Europe region countries were included, the increase would be 2.0 – most regional economic impact is concentrated in countries with GDP per capita lower than USD 20 000.

2.3 Fixed vs. mobile broadband – economic impact by level of development

Using structural models for the global sample, our analysis of 139 countries confirms the following:

• Fixed broadband (data between 2010 – 2017): its contribution is greater in developed countries, with high penetration of fixed broadband, reflecting the “return to scale” effect.

• Mobile broadband (data from 2010 – 2018): its economic dividend is greater in countries and regions with lower levels of economic development and lower relative mobile penetration reflecting the “diminishing returns” effect. This contribution diminishes in countries and regions with higher levels of penetration and development.

Figure 6: GDP growth impact of an increase in 10% of broadband penetration (in per cent)

Source: ITU

Regional analyses confirm both effects and are summarized in Table 2.

Table 2: Regional GDP growth impact of an increase in 10% of broadband penetration (in per cent)

Fixed broadband impact

Mobile broadband impact

Africa

Impact in Africa is as low as that estimated for the global sample of low-income countries – not statistically significant.

Impact in Africa is a 2.46% increase - higher than that estimated for low-income countries in the global sample at 1.98%.

Asia-Pacific

Overall region: 1.63% increase and comparable to high-income country global figure of 1.4% because of weight of high-income economies in the region. Zero impact in both low-income groups of countries.

Low and medium-income countries enjoy 2.44% increase, higher than overall region’s total of 0.51%.

Europe

Impact is higher in high-income countries at 2.94% increase than that of Europe’s low-income countries (0.07%, although not significant). Higher too than high-income countries in the global sample (1.4%).

Impact is not significant for high-income countries while low-income countries would enjoy a 2.0% increase – this is statistically significant.

Arab States

Impact is 0.71% increase – higher than the global sample of medium-income countries at 0.58% but lower than high-income countries at 1.40%.

Impact is a 1.82% increase – lower than that of low-income countries at 1.90% but positive and statistically significant relative to high-income countries.

The Americas

Impact is higher for the Americas (which includes the United States and Canada) at 1.88% increase than in Latin America and Caribbean at 1.57% increase.

Impact is a 1.73% increase in Latin America and the Caribbean – higher than in the Americas (which includes the United States and Canada) at 1.16% increase.

Commonwealth of Independent States (CIS)

Impact is 0.63% increase – somewhat higher than global sample of medium-income countries at 0.58% but lower than high-income countries at 1.40%.

Impact is a 1.25% increase – which is lower than global sample of low-income countries at 2% but is positive and statistically significant relative to high-income countries.

Source: ITU

3 The economic impact of digitization

Digitization is the transformation of the techno-economic environment and socio-institutional operations through digital communications and applications.

Digitization, as a social process, refers to the transformation of the techno-economic environment and socio-institutional operations through digital communications and applications. Unlike other technological innovations, digitization builds on the evolution of network access technologies (mobile or fixed broadband networks), semiconductor technologies (computers/laptops, wireless devices/tablets), software engineering (increased functionality of operating systems) and the spillover effects resulting from their use (common platforms for application development, electronic delivery of government services, electronic commerce, social networks, and availability of online information in fora, blogs and portals). In order to measure the economic impact of digitization it is necessary to develop metrics that determine a country’s level of digital eco-system development.

These Digitization metrics quantify:

• the cumulative effect of adoption and usage of multiple information and communication technologies across individual users and enterprises;

• the development of digital industries;

• the factors of production of the digital economy;

• the level of competitive intensity.

3.1 An index to measure the development of digital ecosystems: 8 pillars, 64 indicators

As the digital ecosystem landscape becomes increasingly complex, an index that reflected a wider range of domains and indicators was built.[12] The Digital Ecosystem Development Index was used to measure the level of regional digitization, as well as to understand the progress achieved so far and the nature of the challenges ahead.

This index is a composite metric that quantitatively assesses the eight pillars that make up the digital economy (Figure 7). The index breaks these down into 64 indicators as set out in Figure 8. The list of Indicators included in the Digital Ecosystem Development Index and data sources are available in Annex D.

Figure 7: Eight pillars of the Digital Ecosystem Development Index

Note: Links are drawn only for relatively strong causal relationships.

Source: CAF

Figure 8: The Index – 64 indicators grouped under eight pillars

Note: Numbers in bold above each pillar indicate total number of indicators for that pillar (some examples are included below each box), while the numbers in brackets represent the relative weight of the pillar for calculation of the Index. For a full list of indicators see Annex D.

Source: CAF

The analysis of the economic impact of policy and regulatory framework on the growth of markets for digital service relies also on the ITU ICT Regulatory Tracker[13] as the independent variable to test its impact on the CAF Digital Ecosystem Development Index. For this purpose, two models were developed to test the correlation between the ICT Regulatory Tracker and CAF Digital Ecosystem Development Index. The underlying premise is that higher regulatory performance is directly related to the development of the digital economy (the methodology is available in Annex E).

As expected, advanced economies depict a higher digitization index, Figure 9 compares the results of the Development Index of the Digital Ecosystem in seven defined regions. As explained above, the index is a composite metric that quantitatively assesses the eight pillars that make up the digital economy in each of the regions. The results highlight that the lowest value is the Africa region (34.18) and the highest are Europe and North America (75.43).

Figure 9: Comparative development of the digital ecosystem (2018)

Source: ITU

3.2 Digitization correlates with economic development

Figure 10: Correlation between GDP per capita and Digital Ecosystem Development Index, 2015

Source: ITU

This study tested three hypotheses in regard to how digitization impacts the economy:

1. Its impact is higher than standalone information technologies.

2. Impact increases at higher development stages.

3. There is a positive impact on productivity.

The econometric models are built on data for 73 countries between 2004 and 2015:

• Africa region (4 countries)

• Americas region (24 countries)

• Arab States region (3 countries)

• Asia-Pacific region (9 countries)

• Europe region (24 countries)

• Commonwealth of Independent States region (9)

The endogenous growth model tests the impact on GDP growth and is based on the Cobb-Douglas production function:

Log (GDPit)=a_1log (Fixed capital formationit)+a_2log (Labour forceit)+a_3log (digitization indexit)+a_4log (previous year GDP) εit

The model to test the impact of digitization on productivity:

Log (Productivity it) =a_1log (Growth of digitization it) +a_2log (digitization index it) +εit

3.3 Digitization – on par with mobile broadband in boosting economies

On a global scale, digitization has a larger economic contribution than fixed broadband, on a par with that of mobile broadband.

Figure 11: Impact on GDP of 1% increase in independent variable, 2004-2015

Source: ITU

Digitization boosts advanced economies

The impact of digitization on advanced economies is higher than in emerging countries, confirming the “return to scale” effect (see Figure 12).

Figure 12: Impact on GDP of 10% increase in digitization, 2004-2015

Source: ITU

Digitization boosts productivity

Digitization boosts labour productivity – 10 per cent digitization yields an increase of 2.62 per cent. Ten per cent increase yields an increase of 2.28 per cent in total factor productivity.

4 Policy and regulation drive development of digitization

Institutional and regulatory factors drive the development of digitization in addition to endogenous variables. An acceleration in the digital ecosystem development is seen following changes to policy and institutions that influence deployment and adoption of digital technologies. There is a notable time lag between change and effect.

How was the impact of policy and regulation on digitization measured? This was based on a multivariate regression model that included two indices as set out in Figure 13:

Figure 13: Regression model indices

Source: ITU

The regional results (presented in Figure 14) show the impact of the 10% of the lagged ITU ICT Regulatory Tracker on the Digital Ecosystem Development Index in the world and in the six ITU regions of the world.

Figure 14: Impact of the 10% of the lagged ITU ICT Regulatory Tracker on the Digital Ecosystem Development Index

Source: ITU

Regional results confirm the importance of regulation and policy

All regional results confirm the importance of regulation and policy on the development of digitization.

There are three simultaneously occurring mechanisms that drive this effect:

1 Changes in policy and regulations as well as at an institutional level drive increased public ICT investment, which in turn improves network reliability, connectivity, and affordability.

2 Institutional change facilitates more effective public policy which in turn can drive the development of a national digital agenda, such as a broadband plan and the creation of legislative consensus.

3 Institutional changes signal the importance of ICT and digital development to the private sector and in response, the private sector (operators, service providers and other Internet players) increases investment and commercial activities. In this way, public initiative such as institutional change functions as a multiplier of ICT development.

Annex A: Review of the related research literature

A review of the research literature on the economic contribution of telecommunications and digital technologies, as well as the impact of the policy variable on the development of telecommunications and digitization has been prepared and published in each of the regional econometric studies.[14] Whenever applicable, the literature was reviewed both in terms of global results and by region in order to ascertain the level of progress of research in each region of the world. The review set the stage for defining the theoretical frameworks that guided this study.

A.1. The economic contribution of fixed and mobile broadband

Studies on the economic impact of telecommunications have been produced for the past two decades confirming, to a large extent, that wireline and wireless telephony, as well as fixed and mobile broadband have an impact on economic growth and, in some cases, on employment and productivity (Hardy, 1980; Karner and Onyeji, 2007; Jensen, 2007; Katz et al., 2008; Katz, 2011; Katz et al., 2009; Katz et al., 2012, Arvin and Pradhan, 2014). Along these lines, a critical issue of the evolving research on network externalities of telecommunications is the impact pattern telecommunications penetration levels may have on output and employment. For example, is there a linear relationship between broadband adoption and economic growth, whereby higher penetration yields larger impact? Or, are we in the presence of more complex non-linear causal effects, such as “increasing returns to scale” and/or “diminishing returns” due to saturation? Along those lines, is it possible to identify a particular effect of increasing returns linked to broadband speed?

The following section summarizes first, the historical evolution of econometric modelling studies of broadband economic contribution. Following this, it examines specific results from studies that have evaluated contribution patterns such as identifying potential returns to scale or diminishing returns effects. More specifically, it focuses on the particular research domain of return to speed. Finally, it examines econometric research conducted within specific geographic regions.

A.1.1. Historical evolution of econometric modelling of broadband economic contribution

Broadband technology is a contributor to economic growth at several levels. First, the deployment of broadband technology across business enterprises improves productivity by facilitating the adoption of more efficient business processes (e.g., marketing, inventory optimization, and streamlining of supply chains). Second, extensive deployment of broadband accelerates innovation by introducing new consumer applications and services (e.g., new forms of commerce and financial intermediation). Third, broadband leads to a more efficient functional deployment of enterprises by maximizing their reach to labour pools, access to raw materials, and consumers (e.g., outsourcing of services, virtual call centres).

Quantitative research aimed at generating statistical evidence regarding the economic impact of broadband is recent. The review of the research indicates that there are multiple approaches to estimate the economic impact of broadband, ranging from highly sophisticated econometric techniques to qualitative micro-level case studies.

A.1.2. The “return to scale” or “critical mass” effect

Research on the causal link between broadband penetration and economic output indicates the existence of a non-linear relationship between the two (following an inverted U shape). At low levels of broadband penetration, the impact of broadband on the economy is minimal because the impact of telecommunications infrastructure on economic output is only maximized once the infrastructure reaches a critical mass point, generally associated with levels of penetration of developed countries.

According to the evidence generated by this body of theory, the impact of telecommunications networks on economic output is maximized once the infrastructure reaches critical mass generally associated with high levels of penetration.

The implication of this evidence for developing countries is quite significant. Unless emerging economies do not strive to dramatically increase their penetration of broadband, the economic impact of the technology will be quite limited.

A.1.3. The saturation and “diminishing returns” effect

At the other end of the diffusion process, some authors have pointed out a potential “saturation” effect. They have found that, beyond a certain adoption level, the contribution of a telecommunications technology to the economy tends to diminish. For example, Atkinson et al. (2009) point out, albeit without quantitative evidence, that network externalities decline with the build out of networks and the maturation of technology over time. There is evidence that supports this argument. It has been demonstrated in diffusion theory that early technology adopters are generally those who can elicit the higher returns of a given innovation. Conversely, network externalities would tend to diminish over time because those effects would not be as strong for late adopters. Along those lines, Gillett et al. (2006) argued that the relation between broadband penetration and economic impact should not be linear “because broadband will be adopted (…) first by those who get the greatest benefit (while) late adopters (…) will realize a lesser benefit” (p. 10).

To test the saturation hypothesis, Czernich et al. (2009)[15] added dummy variables to account for 10 per cent and 20 per cent broadband penetration to their models explaining broadband contribution to OECD economies. They found that 10 per cent broadband penetration has a significant impact on GDP per capita: between 0.9 and 1.5 percentage points. However, the transition from 10 per cent to 20 per cent yielded non-significant results. This led the authors to postulate that broadband saturation and diminishing returns occurs at the 20 per cent point. Gillett et al. (2006), presented above, also included saturation as an independent variable and found that it was negatively related to the increase in economic growth (notwithstanding the possible influence of network effects). In an implicit confirmation of this postulate, Qiang et al. (2009) found that economic impact of a 1 per cent increase in broadband is higher in low and middle-income economies and lower in high-income economies.[16] Similarly, in their study of the impact of broadband in Kentucky, Shideler et al. (2007) found that economic impact is highest around the mean level of broadband saturation at the county level. Again, this was due to diminishing returns to scale. According to this last study, a critical amount of broadband infrastructure may be needed to sizably increase employment, but once a community is completely built out, additional broadband infrastructure will not further contribute to employment growth. In the case of mobile telephony, Gruber and Koutroumpis (2011) show as well, that mobile telephony’s effects on GDP growth correlate with wireless penetration growth up until penetration rates reach 60 per cent, at which point effects tend to subside.

One should be very careful, however, in interpreting the evidence of “diminishing returns”. The saturation evidence still needs to be carefully tested particularly in terms of what is the point beyond which the economic impact tends to diminish. Furthermore, even if there were to be found confirming evidence of saturation with regard to contribution to GDP or employment creation, that would not put into question the need to achieve universal broadband in terms of the other social benefits it yields to end users.

With both points of view in mind – need to achieve critical mass and diminishing returns –, it would appear that the strength of the relationship between telecommunications and economic growth is highest once the technology has achieved a certain critical mass but before it reaches saturation (see Figure A.1).

Figure A.1: Conceptual framework for the impact of broadband on economic output over the diffusion process

Source: ITU

Theoretically, it would appear that there is a non-linear (or inverted U shape) relationship between broadband penetration and output. At low levels of broadband penetration, we believe the impact of broadband on the economy is minimal due to the need to reach “critical mass”. According to this theory, the impact of telecommunications infrastructure on the economic output is maximized once the infrastructure reaches a critical mass point generally associated with levels of penetration of developed countries. Beyond that point, economic impact tends to slow down, depicting “diminishing returns”. As a cautionary point, the literature has evidenced an important dispersion in the level of penetration that would indicate a saturation point when economic impact tends to diminish: it ranges between 20 per cent and 60 per cent.

A.1.4. The “return to speed” effect

Beyond research the aggregate economic contribution of broadband, studies have recently started focusing on the so-called “return to speed”. Research on the contribution of broadband speed to economic growth generally concludes that faster Internet access has a positive impact on GDP growth. Two types of effects explain this causal relationship. First, faster broadband contributes to an improvement of productivity resulting from the adoption of more efficient business processes. For example, improved marketing of excess inventories and optimization of the supply chain are two of the effects that might be generated. Second, faster connectivity yields an acceleration of the rate of introduction of new products, services, and the launch of innovative business models.

An early study that assessed the impact of broadband speed on GDP (Rohman, Bohlin, 2012) looked at 33 OECD countries and concluded that a 100 per cent increase (or doubling) of speed yields a 0.3 per cent increase in GDP with a sample mean of 8.3 Mbit/s. Following on this study, Kongaut and Bohlin (2014) used a similar approach, but differentiated between high and low-income OECD countries and determined that an increase in broadband speed of 1 per cent yields an increase in GDP per capita of 0.09 per cent for low income countries and 0.06 per cent for high income countries.

Two studies completed in 2018 provided additional evidence of broadband speed impact on GDP. Briglauer and Gugler (2018) looked at data for 27 EU Member States between 2003 and 2015. In this case, 1 per cent increase in basic broadband adoption was found to increase GDP by about 0.015 per cent, while 1 per cent increase in ultra-fast broadband adoption led to an incremental increase of 0.004-0.005 per cent of GDP. In another iteration, Carew et al. (2018) concluded that a 1 per cent increase in speed equates to a 0.0197 per cent in real GDP. Therefore, a doubling of speed (100 per cent increase) yields 1.97 per cent increase in GDP. A recent study by Katz and Callorda (2019) based on an extensive dataset of 159 countries found that the impact on GDP of fixed broadband download speeds under 10 Mbit/s is non-existent, while once the average speed is in a range between 10 and 40 Mbit/s, the effect on GDP is positive and statistically significant. The effect on GDP is even greater for download speeds in excess of 40 Mbit/s. The results of this study are in the range of what was estimated by Briglauer and Gugler (2018) for the EU ultrabroadband impact, while the difference with Carew et al. (2018) is likely because, since broadband adoption is not included as independent variable for control purposes, the effect of speed subsumes broadband penetration.

Figure A.2: Studies measuring the GDP impact on broadband speeds (impact of 1% increase in speed on GDP) (%)

Source: ITU

As indicated in Figure A.2, while all studies conclude that broadband speed has an impact on GDP, the range of contribution varies. Some of the difference is explained by methodologies used. For example, Carew et al. (2018) did not include broadband adoption as an independent variable which means that the effect of speed subsumes broadband penetration. In other cases, the difference can be explained by the timing of the data used.

Can a saturation effect attached to broadband penetration and GDP be extended to broadband speed? Koutroumpis (2018) argues that a country that has reached the saturation point in speed may experience additional GDP growth although this would not be attributed to the network anymore but to new products and services enabled by the network.

A.1.4.1. Broadband speed and household income

While broadband speed has been consistently found to have a positive effect on economic growth, the evidence of a positive contribution of Internet speed to household income is less conclusive. Rhoman and Bohlin (2013) concluded that there are positive benefits from broadband speed on income, though they are not linear and continuous, but nonlinear and stepwise. Furthermore, the authors found that the impact for lower speed is greater in BRIC countries and for higher speeds it is greater in OECD countries. On the other hand, Ford (2018) analysed data of US and found no economic payoff from a 15 Mbit/s speed difference.

A.1.4.2. Broadband speed and enterprise productivity

The contribution of broadband speed to enterprise productivity has been studied in terms of its efficiency enhancement and productivity levels. In a study of Irish firms, Haller et al. (2019) found significant productivity gains from broadband availability in two services sectors: information and communication services and administrative and support service activities. The effects measured for these two sectors were large, equivalent to about a third of the typical variation in productivity. Smaller effects were found in other sectors. These results suggest the benefits of broadband for productivity depend heavily upon sectoral and firm characteristics rather than representing a homogeneous effect. Cariolle et al. (2018) study firms in 62 countries, using World Bank data, and detected a large impact of broadband speed on a firm’s average annual sales and sales per worker.

A.1.4.3. Broadband speed and job creation

Research on the impact of broadband speed on employment, which takes place through the contribution to firm relocation and start-up incubation, is fairly conclusive. With the exception of one study, all research has been focused on the United States. Whitacre et al. (2014) looked at local level data of non-metropolitan United States counties between 2001 and 2010 and identified a positive impact of broadband speed on unemployment reduction. In particular, rural areas with fast broadband tend to attract more creative class workers. Bai (2016) studied United States counties between 2011 and 2014 and found that while broadband has a positive impact on employment, ultra-fast broadband has less incremental effects. Lobo et al. (2019) studied the counties within the US state of Tennessee and found that unemployment rates are about 0.26 percentage points lower in counties with high speed broadband compared to counties with low speed service. Coinciding with Whitacre et al. (2014), this study found that better quality broadband has a disproportionately greater effect in rural areas.

The only study conducted outside the United States was done by Hasbi (2017), analysing panel data on 36 000 municipalities in France between 2010 and 2015, the author found that deployment of high-speed broadband (> 30 Mbit/s) increases company relocation and start-up development in those areas in the non-agricultural sector. These two effects yield a positive contribution to reduction of unemployment.

A.1.4.4. Broadband speed and consumer surplus

Consumer surplus is defined as the amount that consumers benefit from purchasing a product for a price that is less than what they would be willing to pay. Broadband consumer surplus, typically assessed against dial up or pricing differences, indicates a high willingness to pay for speed. Most studies of consumer surplus derived from faster speed are based on surveys or focus groups where consumers stipulate the amount they would be willing to pay for a service such as broadband (Savage et al. (2004); Greenstein and McDewitt (2011); Liu et al. (2018)).

Finally, other studies on consumer surplus focus the assessment of how consumers react to variations in price according to their data usage.

A.2. Regional studies of the economic impact of broadband

While some of the research reviewed above focused on specific geographies, it was pertinent to reevaluate it in light of progress that has occurred in each region of the world to ascertain what has taken place in terms of econometric modelling at the regional level. As mentioned above, the full description of this research is available on each regional econometric study.

A.3. The economic impact of digitization

The study of a country or region stage of development in the adoption of Information and Communication Technologies has been progressing over the last twenty years. While the original focus was to assess the deployment and adoption of telecommunications and information technology infrastructure (broadband, mobile telephony, computers), research has been gradually expanding its focus to include dimensions such as the use of digital technologies (electronic commerce, electronic government, social networks) as well as the development of industries within the full digital value chain (Internet platforms, Collaborative Internet Services, etc.).

This new perspective has led to the emergence of the concept of digitization. This chapter focuses first on providing a definition of digitization. Given that this phenomenon is comprised of multiple technology trends, its measurement requires the development of composite indices. The efforts in this domain are being reviewed in the second section. Once measurement of digitization was established, the estimation of its economic impact was conducted.

A.3.1. What is digitization?

Digitization per se, is the process of converting analogue information to a digital format. Digitization, as a social process, refers to the transformation of the techno-economic environment and socio-institutional operations through digital communications and applications.[17] Unlike other technological innovations, digitization builds on the evolution of network access technologies (mobile or fixed broadband networks), semiconductor technologies (computers/laptops, wireless devices/tablets), software engineering (increased functionality of operating systems) and the spillover effects resulting from their use (common platforms for application development, electronic delivery of government services, electronic commerce, social networks, and availability of online information in fora, blogs and portals). In order to measure the economic impact of digitization it is necessary to develop composite metrics that allow us to determine a country’s level of digital eco-system development.

Digitization metrics aim to quantify the cumulative effect of adoption and usage of information and communication technologies. While most of the research literature measuring the social and economic impact of ICT focuses on discrete technology platforms, the holistic adoption and usage of information technology results in enhanced effects that go beyond the contribution of specific platforms. Furthermore, to achieve a significant impact, digitization has to be widely adopted in the economic and social fabric of a given country. As such, they have to be widely utilized by individuals, economic enterprises and societies, embedded in processes of delivery of goods and services (e.g. eCommerce), and relied upon to deliver public services (e.g. eHealth, eGovernment).

A.3.2. Measurement of digitization

The study of a country or region stage of development in the adoption of Information and Communication Technologies has been progressing over the last twenty years. While the original focus was to assess the deployment and adoption of telecommunications and information technology infrastructure (broadband, mobile telephony, computers), research has been gradually expanding its focus to include dimensions such as the use of digital technologies (electronic commerce, electronic government, social networks) as well as the development of industries within the full digital value chain (Internet platforms, collaborative Internet services, etc.). In this process, a number of indices have been developed along the way, including the International Telecommunications Union’s ICT Development Index, the World Bank’s Knowledge Economy Index, the World Economic Forum Network Readiness Index, and the Inter-American Development Bank’s Broadband Development Index. However, most of the indices developed so far tend to either address a particular aspect of the digital ecosystem, such as broadband penetration, or include a limited number of indicators.

The first index of digitization developed[18] was based on six components (see Table A.1).

Table A.1: Structure of original digitization index

Components

Subcomponents

Sub-Subcomponents

Affordability

Residential fixed line cost adjusted for GDP per capita

Residential fixed line tariff adjusted for GDP per capita

Residential fixed line connection fee adjusted for GDP per capita

Mobile cellular cost adjusted for GDP per capita

Mobile cellular prepaid tariff adjusted for GDP/capita

Mobile cellular prepaid connection fee adjusted for GDP per capita

Fixed broadband Internet access cost adjusted for GDP per capita

Infrastructure Reliability

Investment per telecom subscriber (mobile, broadband and fixed)

Mobile investment per telecom subscriber

Broadband investment per telecom subscriber

Fixed line investment per telecom subscriber

Network Access

Network Penetration

Fixed Broadband penetration

Mobile Phone penetration

Coverage, Infrastructure and Investment

Mobile cellular network coverage

PC population penetration

3G Penetration

Capacity

International Internet bandwidth (kbit/s/user)

% Broadband connections higher than 2 Mbit/s

Usage

Internet retail volume

E-government usage

% Individuals using the internet

Data as % of wireless ARPU

Dominant Social Network Unique Visitors per month Per Capita

SMS Usage

Human Capital

% Engineers in labour force

% Skilled labour

Source: Katz and Koutroumpis, 2013a

The increasing complexity of the digital eco-system required constructing an index that reflected a larger number of domains and indicators. The index for measuring the development of a digital ecosystem, constructed with support of CAF Development Bank for Latin America,[19] is a composite metric for quantitatively assessing the eight pillars comprising the digital economy.

According to this conceptual structure, the digital ecosystem is defined as a set of interconnected components (or pillars) operating within a socio-economic context. For example, the development of the infrastructure of digital services provides individuals, businesses and public organizations access to digital content and services. It also supplies interconnectivity to players within the digital value chain (e.g. developers of digital content, Internet platforms, etc.) so they can deliver a value proposition to users. Digital connectivity measures the adoption of terminals (computers, smartphones) and services (broadband, wireless telephony) in order to allow individuals and organizations to gain access to networks. Network access enables the use of digital products and services, which is defined as digitization. This term is used to measure not only the use of digital services by individual consumers (household digitization) but also its assimilation by enterprises (digitization of production). The demand of digital products and services by individual consumers, enterprises and governments is met by the offer supplied by digital industries (which comprise Internet platforms, media companies, telecommunications operators and equipment manufacturers, among others). These firms can be located within the country where demand is located or, enabled by virtual business models, can be based beyond its frontiers. In order for digital industries to operate within the country, they require conventional factors of production ranging from human to investment capital. Finally, for digital industries to generate static and dynamic consumer benefits, they need to operate within a sustainable competitive environment, and receive the appropriate incentives and controls embodied in a regulatory framework and public policies.

Given that the digital ecosystem embodies a complex interaction among its eight components, the measurement of its development requires the creation of an index composed of eight pillars, each of which is a composite sub-index based on multiple indicators. In total, the Digital Ecosystem Development Index is based on 64 indicators (see image relating to the measurement of digitization conducted by an index composed of 64 indicators grouped in eight pillars and shown above in Figure 8).

This index has been used to measure the development of regions of the world (see Figure A.3), as well to understand the progress achieved so far and the nature of the challenges facing ahead.

Figure A.3: Comparative development of the digital ecosystem (2018)

Note: Countries included in each region are those with GDP per capita higher than USD 5 000 and a population of 5 000 000 or more, which include Australia, China, India, Japan, Malaysia, New Zealand, Republic of Korea, Singapore, and Thailand for the Asia Pacific region, Canada and United States for North America, Cote d’Ivoire, Egypt, Kenya and South Africa for Africa, Azerbaijan, Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Kazakhstan, Latvia, Poland, Romania, Russian Federation, Slovakia, Slovenia, and Turkey for Eastern Europe, Austria, Belgium, Denmark, Finland, Germany, Greece, Iceland, Ireland, Italy, Luxemburg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and United Kingdom for Western Europe, Israel, Lebanon Saudi Arabia and United Arab Emirates for Middle East and North Africa, and Argentina, Barbados, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay, and Venezuela for Latin America and the Caribbean.

Source: Authors

The Index facilitates the estimation of digitization economic impact.

A.3.3. Economic impact of digitization

The original index, discussed above, was used to test the impact of digitization on economic growth. For this purpose, we used an endogenous growth model that links Gross Domestic Product to the Fixed Stock of Capital, Labor Force and the Digitization Index as a proxy of technology progress. This model for economic output stems from the simple Cobb-Douglas form:

Y = A(t)K1-bLb

where

A(t) represents the level of technology progress (in our case the Digitization Index),

K corresponds to the fixed capital formation, and

L to the labour force.

By converting all terms to logarithms, the coefficients were estimated through an econometric model.

log(GDPit) = a_1log(kit) + a_2log(Lit) + a_3log(Dit) + ɛit

The Digitization Index was found to have a positive and significant effect at the 5 per cent level indicating a strong effect on economic output. A ten-point increase in the Digitization Index had approximately a 3 per cent impact on GDP for the period 2004-2010 resulting on an annualized effect of 0.50 per cent.[20]

The Digital Ecosystem Development Index was run for 73 countries for the period 2004-2015, which resulted in 803 observations, and included fixed effects by country (Katz and Callorda, 2018). According to the model, an increase of 1 per cent in the Digital Ecosystem Development Index results in a 0.13 per cent growth in GDP per capita. This means, for example, that an increase in the Digital Ecosystem Development Index from 50 to 51 will yield an increase of per capita GDP of 0.26 per cent (accounting both for direct and indirect effects on output).

The model was also run for OECD and non-OECD countries to test for a “return to scale” effect. The results indicate that the impact of the digital ecosystem on more advanced economies is higher than emerging countries. Thus, an increase of 1 per cent in the Digital Ecosystem Development Index yields an increase of 0.14 per cent in per capita GDP for OECD countries, while the impact of a similar change in non-OECD countries will be 0.10 per cent. In other words, the higher the economic development, the stronger the contribution of the digital ecosystem on economic growth.

A.4. The impact of policy on digitization

While very limited research has been conducted so far in terms of measuring the impact of policy on the development of digitization, substantial work has been done regarding the impact of public policies on the development of specific technologies. The policy variables that affect digitization and ICT sector performance have multiple dimensions, ranging from the regulatory to the institutional ones, both being either specific or not to the sector. In general terms, variables can be grouped in three categories: 1) the institutional framework, 2) the regulatory framework, and 3) non-sector specific policies which can have a spillover effect on the ICT sector.

The institutional framework variables comprise the factors such as the type of governmental entities that are in charge of developing digital policy or regulating the ICT sector and the providers of service. For example, the variables included in this cluster comprise the overall policy environment (e.g. existence of Cabinet-level position centralizing all digital policy matters (telecommunications, content, computing), the scope and scale of a telecommunications national regulatory authority, its enforcement powers, and independence, the existence of an overarching ICT national planning process, and the scope of government participation in the digital sector.

The regulatory framework cluster comprises all the variables related to specific policies and regulatory approaches. They include market entry regulation (e.g. vertical separation, local loop unbundling, rights of way, numbering scheme, spectrum management), price regulation (interconnection, mobile termination rates, weighted average cost of capital, retail pricing), investment incentive regulation (e.g. asymmetry), the regulatory process (e.g. market analysis ex-ante), and the application of regulation (e.g. technological neutrality, operational conditions, compliance monitoring).

Finally, non-sector specific policies that can have an impact on the performance of the sector comprise variables such as direct foreign investment restrictions affecting market entry and capital structure, other trade restrictions affecting services supply, proactive long term government planning, and regulation of audiovisual content affecting convergence (e.g. restrictions of telecommunications carriers regarding content distribution). In particular, policies that promote and facilitate the adoption of ICT by late adopters (socio-economic disenfranchised and small and medium enterprises), such as digital literacy programmes and equipment subsidization, play an extremely important role in fostering the emergence of a high-performance sector.

Annex B: Countries analysed for economic impact of fixed and mobile broadband

• Argentina

• Haiti

• Australia

• Honduras

• Austria

• Hong Kong, China

• Azerbaijan

• Hungary

• Barbados

• Iceland

• Belarus

• India

• Belgium

• Ireland

• Bolivia

• Israel

• Brazil

• Italy

• Bulgaria

• Jamaica

• Canada

• Japan

• Chile

• Kazakhstan

• China

• Kenya

• Colombia

• Republic of Korea

• Costa Rica

• Latvia

• Côte d’Ivoire

• Lebanon

• Cuba

• Luxembourg

• Czech Republic

• Malaysia

• Denmark

• Mexico

• Dominican Republic

• Netherlands

• Ecuador

• New Zealand

• Egypt

• Nicaragua

• El Salvador

• Norway

• Estonia

• Panama

• Finland

• Paraguay

• France

• Peru

• Germany

• Poland

• Greece

• Portugal

• Guatemala

• Romania

• Russian Federation

• Thailand

• Saudi Arabia

• Trinidad and Tobago

• Singapore

• Turkey

• Slovakia

• United Arab Emirates

• Slovenia

• United Kingdom

• South Africa

• United States of America

• Spain

• Uruguay

• Sweden

• Venezuela

• Switzerland

Annex C: Data sources for models testing the economic impact of fixed and mobile broadband

Indicator

Source

GDP per Capita (PPP)

IMF

Fixed Broadband Subscriber Penetration

ITU - OVUM

Capital - Gross Capital Formation (% of GDP)

World Bank

Education- School Enrolment, tertiary (% gross)

World Bank

Fixed Telephone Subscribers

ITU

Rural Population (% of total population)

World Bank

Fixed Broadband Price

ITU

HHI Fixed Broadband

OVUM

Fixed Broadband Revenue

ITU - OVUM

Mobile Broadband Unique Subscribers Penetration

GSMA

Mobile Unique Subscribers Penetration

GSMA

Mobile Broadband Price//ARPU

ITU - GSMA

HHI Mobile Broadband

GSMA

Mobile Broadband Revenue

GSMA

Annex D: Indicators included in the Digital Ecosystem Development Index and data sources

Pillar

Sub-pillar

Indicator

Source

Infrastructure

Investment

Telecommunications investment per capita in current prices – five-year average (USD PPP)

World Bank; ITU

Infrastructure

Quality of service

Average fixed broadband download speed (Mbit/s)

Akamai

Infrastructure

Quality of service

Average mobile broadband download speed (Average Mbit/s)

Akamai

Infrastructure

Quality of service

Fixed broadband connections with download speed higher than 4 Mbit/s (percentage)

Akamai

Infrastructure

Quality of service

Fixed broadband connections with download speed higher than 10 Mbit/s (percentage)

Akamai

Infrastructure

Quality of service

Fixed broadband connections with download speed higher than 15 Mbit/s (percentage)

Akamai

Infrastructure

Quality of service

Fibre optic broadband connections as a percentage of total fixed broadband connections

ITU; FTTH; OECD

Infrastructure

Quality of service

International broadband bandwidth per Internet user (bit/s)

ITU

Infrastructure

Coverage

Fixed broadband coverage (% of households)

Eurostat, CAF Ideal; OECD

Infrastructure

Coverage

2G coverage

ITU

Infrastructure

Coverage

3G coverage

ITU

Infrastructure

Coverage

4G coverage

ITU

Infrastructure

Service infrastructure

IXPs per 1 000 000 population

Packet Clearing House; UNCTAD

Infrastructure

Service infrastructure

Number of secure servers (per 1 000 000 population)

World Bank

Infrastructure

Service infrastructure

Number of satellites (per 1 000 000 population)

N2yo.com

Connectivity

Affordability

Monthly fixed broadband subscription as percentage of GDP per capita

ITU

Connectivity

Affordability

Monthly mobile broadband smartphone subscription (500 MB cap, prepaid) as percentage of GDP per capita

ITU

Connectivity

Affordability

Monthly mobile broadband PC subscription (1 GB cap, postpaid) as percentage of GDP per capita

ITU

Connectivity

Affordability

Monthly pay TV subscription as percentage of GDP per capita

Business Bureau; CAF; PwC; TAS

Connectivity

Penetration

Fixed broadband penetration (connections per 100 households)

ITU

Connectivity

Penetration

Mobile broadband penetration (connections per 100 population)

ITU

Connectivity

Penetration

Unique mobile broadband users (per 100 population)

GSMA

Connectivity

Penetration

Pay TV penetration (connections per 100 households)

Business Bureau; CAF; PwC; TAS; ITU; Convergencia

Connectivity

Ownership

Penetration of computers (% of households)

ITU

Connectivity

Ownership

Smartphone users (per 100 population)

GSMA

Connectivity

Ownership

Percentage of population with access to electric energy

World Bank

Household digitization

Internet use

Percentage of population using the Internet

ITU

Household digitization

Internet use

Penetration of dominant social network (users per 100 population)

OWLOO

Household digitization

Internet use

Mobile data ARPU as percentage of total ARPU

GSMA

Household digitization

E-government

E-government index

UN

Household digitization

E-commerce

Internet commerce as percentage of total retail commerce

Euromonitor

Household digitization

Telemedicine

National health policy (binary variables)

WHO

Household digitization

OTTs

Video on demand penetration (per cent households)

PwC

Digitization of production

Digital infrastructure

Per cent enterprises with Internet access

UNCTADstat; TAS; Eurostats

Digitization of production

Digital supply chain

Per cent enterprises using Internet for electronic banking

UNCTADstat; TAS; Eurostats

Digitization of production

Digital supply chain

Per cent enterprises using Internet for purchasing inputs

UNCTADstat; TAS; Eurostats

Digitization of production

Digital distribution

Per cent enterprises that sell products over the Internet

UNCTADstat; TAS; Eurostats

Digitization of production

Digital processing

Per cent workforce using the Internet

UNCTADstat; TAS; Eurostats

Digitization of production

Digital processing

Per cent workforce using computers

UNCTADstat; TAS; Eurostats

Competitive intensity

Competition level

HHI fixed broadband

Convergencia; Regulators; TAS

Competitive intensity

Competition level

HHI mobile broadband

GSMA; Regulators

Competitive intensity

Competition level

HHI pay TV

Convergencia; Dataxis; Ofcom; TAS; Regulatory agencies

Competitive intensity

Competition level

HHI mobile telephony

GSMA; Regulatory agencies

Digital industries

Exports

High technology exports (USD per capita in current prices)

World Bank

Digital industries

Exports

ICT services exports (USD per capita in current prices)

World Bank

Digital industries

Weight of digital industries

Digital ecosystem sales as a percentage of GDP

PwC; TAS; ITU

Digital industries

Weight of digital industries

Telecommunications operators revenues per capita (USD in current prices)

ITU

Digital industries

Weight of digital industries

Computer software spending (per cent of GDP)

INSEAD

Digital industries

IoT

M2M connections (per 100 population)

ITU; OECD

Digital industries

Content production

Wikipedia pages edited per month (per million population between 15 and 69 years old)

INSEAD

Factors of digital production

Human capital

Education years expectancy (years)

World Bank; UNESCO

Factors of digital production

Human capital

Tertiary school enrollment (per cent population)

World Bank; UNESCO

Factors of digital production

Schools

Per cent educational establishments with Internet access

UNESCO; CEPAL

Factors of digital production

Schools

Computers per students ratio

UNESCO; CEPAL

Factors of digital production

Innovation

USPTO patents per country (per 1, 000 000 population)

USPTO

Factors of digital production

Innovation

Intellectual property revenues (USD per capita PPA in current prices)

World Bank

Factors of digital production

Investment in innovation

R&D spending (per cent of GDP)

World Bank; UNESCO

Factors of digital production

Economic development

GDP per capita (USD current prices)

IMF

Factors of digital production

Economic development

Electric energy consumption (kWh per capita)

World Bank

Institutional and regulatory

Cybersecurity and piracy

Per cent of non-licensed installed software

BSA, The Software Alliance

Institutional and regulatory

Cybersecurity and piracy

Commercial value of non-licensed software (as per cent of GDP)

BSA, The Software Alliance

Institutional and regulatory

Government role

Per cent of regulatory agency attributions based on ITU Regulatory Tracker

ITU; TAS

Institutional and regulatory

Government role

Per cent of regulatory agency functions based on ITU Regulatory Tracker

ITU; TAS

-

-

Population

World Bank

-

-

Exchange rate PPP

IMF

-

-

Number of households

ITU

-

-

GDP per capita for first quintile (USD in current prices)

IMF; World Bank

Annex E: Econometric methodology

Economic contribution of fixed and mobile broadband

The state-of-the-art econometric models currently in use consist of four equations: an aggregate production function modelling the economy and, subsequently, three functions: demand, supply and output.[21] In the case of mobile telecommunications, for example, the last three functions model the mobile market operation and, controlling for the reverse effects, the actual impact of the infrastructure, as follows:

• In the production function, GDP is linked to the fixed stock of capital, labour and the mobile infrastructure proxied by mobile penetration.

• The demand function links mobile penetration to the average consumption propensity of individuals proxied by GDP per capita, the price of a mobile service proxied by ARPU (average revenue per user), the per cent rural population, and the level of competitive intensity in the mobile market measured by the HHI (Herfindahl Hirschman) index.

• The supply function links aggregate mobile revenues to mobile price levels proxied by ARPU, the industry concentration index of the mobile market (HHI), and GDP per capita.

• The output equation links annual change in mobile penetration to mobile revenues, used as a proxy of the capital invested in a country in the same year. The econometric specification of the model is:

Aggregate Production function: (1)

GDPit = a_1Kit + a_2Lit + a_3Mob_Penit + eit

Demand function: (2)

Mob_Penit = b_1Ruralit + b_2Mob_Priceit + b_3GDPCit + b_4HHIit + eit

Supply function: (3)

Mob_Revit = c_1MobPrit + c_2GDPCit + c_3HHIit +

Output function: (4)

ΔMob _Penit = d_1Mob_Revit + ɛ4it

In order to test the current economic impact of telecommunication technology, two models were constructed (one for fixed broadband and another one for mobile broadband) and specified for two cross-sectional samples of countries. This methodology would allow the three hypotheses explained above to be tested while controlling for endogeneity effects.[22]

Economic impact of digitization

The study of a country or region stage of development in the adoption of ICTs (information and communication technologies) has been progressing over the last 20 years. While the original focus was to assess the deployment and adoption of telecommunication and information technology infrastructure (broadband, mobile telephony, computers), research has been gradually expanding its focus to include dimensions such as the use of digital technologies (electronic commerce, electronic government, social networks) as well as the development of industries within the full digital value chain (Internet platforms, collaborative Internet services, etc.). In this process, a number of indices have been developed along the way, including the International Telecommunication Union ICT Development Index, the World Bank Knowledge Economy Index, the World Economic Forum Network Readiness Index, and the Inter-American Development Bank Broadband Development Index. However, most of the indices developed so far tend to either address a particular aspect of the digital ecosystem, such as broadband penetration, or include a limited number of indicators.

For the application of this methodology an endogenous growth model was used, which links GDP to the fixed stock of capital, labour force, and the digitization index as a proxy of technology progress. This model for economic output stems from the simple Cobb-Douglas form:

Y = A(t) K1-b Lb

where

A(t) represents the level of technology progress (in our case the digitization index),

K corresponds to the fixed capital formation, and

L to the labour force.

By converting all terms to logarithms, the coefficients can be estimated through an econometric model.

log(GDPit) = a_1log(kit) + a_2log(Lit) + a_3log(Dit) + ɛit

Since the development of the original digitization index, a number of changes occurred within this phenomenon, adding complexity that was not accounted for in the original index. For example, the development of the infrastructure of digital services provides individuals, businesses and public organizations access to digital content and services. It also supplies interconnectivity to players within the digital value chain (e.g. developers of digital content, Internet platforms, etc.) so they can deliver a value proposition to users.[23] Digital connectivity measures the adoption of terminals (computers, smartphones) and services (broadband, wireless telephony) in order to allow individuals and organizations to gain access to networks. Network access enables the use of digital products and services, which is defined as digitization. This term is used to measure not only the use of digital services by individual consumers (household digitization) but also its assimilation by enterprises (digitization of production).

The demand of digital products and services by individual consumers, enterprises and governments is met by the offer supplied by digital industries (which comprise Internet platforms, media companies, telecommunication operators, and equipment manufacturers, among others). These firms can be located within the country where demand is located or enabled by virtual business models, can be based beyond its frontiers. In order to develop digital industries within a country, they require conventional factors of production ranging from human to investment capital.

Finally, for digital industries to generate static and dynamic consumer benefits, they need to operate within a sustainable competitive environment, and receive the appropriate incentives and controls embodied in a regulatory framework and public policies. As a result, the digital ecosystem could be defined as a set of interconnected components (or pillars) operating within a socio-economic context.

In order to assess the existence and strength of the causal link between digital ecosystem development and economic development, an endogenous growth model based on the Cobb-Douglas production function was specified linking the stock of fixed capital, labour force, and the CAF Digital Ecosystem Development Index. The model also controls for GDP per capita for previous year to account for inertia effects:

Y (t)= A (t) K (t)1-b L (t)b

By converting all equation terms to logarithms, the level of impact of each independent variable of the growth of the digital ecosystem was estimated:

log (GDPit) = a_1log (Kit) + a_2log (Lit) + a_3log (Ait) + εit

Where:

K(t) measures the level of fixed capital formation

L(t) measures labour force

A(t) measures the CAF Digital Ecosystem Development Index

In this model, since both the dependent and independent variables are indices, the analysis is essentially correlational. In that sense, from a policy standpoint, if regulation improves in a given country, the digital ecosystem is expected to grow as well. The reverse causality hurdle is partly addressed by measuring how the rate of change in the ICT Regulatory Tracker affects the rate of development of the digital ecosystem.

Economic impact of policy and regulatory framework on the growth of markets for digital service

As explained in Section 3 of the main report, the analysis of the economic impact of policy and regulatory framework on the growth of markets for digital service relies on the ITU ICT Regulatory Tracker as the independent variable to test its impact on the CAF Digital Ecosystem Development Index. For this purpose, two models were developed initially: the first tests the correlation between the ICT Regulatory Tracker and the CAF Digital Ecosystem Development Index. The underlying premise is that higher regulatory performance is directly related to the development of the digital economy:

Dig.Indexit = ᵦ_1Reg.Indexit + Year F.E. + Country F.E. + eit

Beyond measuring the correlation between both variables, a model with lagged variables was developed. In this case, the specified model is as follows:

Dig.Indexit = ᵦ_1Reg.Indexit + ᵦ_2Reg.Indexit-1 + Year F.E. + Country F.E. + eit

Finally, the variables were converted to logarithms to test causality of change in values of both indices:

In (Dig.Indexit) = ᵦ_1In (Dig.Indexit) + ᵦ_2In (Dig.Indexit-1) + Year F.E. + Country F.E. + eit

Furthermore, one cannot detect in this analysis a component of the ICT Regulatory Tracker that has higher importance than the rest when correlated with the CAF Digital Ecosystem Development Index and its pillars. It is clear that growth in the ICT Regulatory Tracker components go in tandem with an improvement in all pillars of the Digital Ecosystem. A second set of regressions showed that the regulatory regime component of the ICT Regulatory Tracker appears to be the main path of impact of the CAF Digital Ecosystem Development Index.

Table A.2: ICT Regulatory Tracker and CAF Digital Ecosystem Development Index pillars

ICT Regulatory Tracker

ICT Regulatory Tracker (w/o Competition component)

Regulatory authority component

Regulatory mandate component

Regulatory regime component

Competition framework

CAF Digital Ecosystem Development Index

Infrastructure of Digital Services

Connectivity of Digital Services

Household digitization

Digitization of production

Digital Competitive Intensity

Development of Digital Industries

Digital factors of production

Acronyms

AI

Artificial Intelligence

AR

Augmented Reality

APRU

Average Revenue Per User

BDT

Telecommunication Development Bureau

BRIC

Brazil, Russia, India and China (ITU)

CAF

Corporación Andina de Fomento

CEPAL

Commission économique pour l'Amérique latine et les Caraïbes

CIS

Commonwealth of Independent States

FTTH

Fibre to the Home

FTTx

Fibre to the x

GDP

Gross Domestic Product

HHI

Herfindahl Hirschman Index

ICT

Information and Communication Technology

IMF

International Monetary Fund

IoT

Internet of Things

ITU

International Telecommunication Union

M2M

Machine-to-Machine

OECD

Organisation for Economic Co-operation and Development

OTT

Over-the-top

PPP

Public-Private Partnership

R&D

Research and Development

RME

Regulatory and Market Environment Division

SMS

Short Message Service

USPTO

United States Patent and Trademark Office

UNCTAD

United Nations Conference on Trade and Development

UNESCO

United Nations Educational, Scientific and Cultural Organization

VR

Virtual Reality

WHO

World Health Organization

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[1] Based on the ITU Manual for measuring ICT access and use by households and individuals, 2020 edition, mobile broadband network refers at least 3G (e.g. UMTS) via a handset and Fixed broadband network refers to technologies at advertised download speeds of at least 256 kbit/s, such as DSL, cable modem, high speed leased lines, fibre-to-the-home/building, powerline and other fixed broadband.

[2] Source: Prorated GSMA Intelligence figures for 2020.

[3] Source: Prorated GSMA intelligence 5G coverage for 2020.

[4] Source: Prorated IDATE FTTx penetration for 2019.

[5] ITU’s The economic contribution of broadband, digitization and ICT regulation and the Regional Econometric Modelling Reports are available at: https://www.itu.int/en/ITU-D/Regulatory-Market/Pages/Economic-Contribution.aspx.

[6] Generally, the returns to scale effect refers to a reduction in unit cost as the scale of production increases over time, when inputs such as physical capital usage are variable. The ITU Broadband Series Impact of Broadband on the Economy, 2012 (https://www.itu.int/pub/D-PREF-BB.RPT2-2012) states that according to the returns to scale theory, the economic impact of broadband increases exponentially with the penetration of the technology.

[7] This was already detected in early studies conducted with 2007 OECD data (see Czernich et al., 2009).

[8] As explained by Roller and Waverman (2001): “This approach uses all the exogenous variable in the system of equations (i.e., those that we can reasonably assume are not determined by the other variables in the system, such as the amount of labour and the amount of total capital) as ‘instruments’ for the endogenous variables (output, the level of penetration, and the prices). Instrumenting the endogenous variables essentially involves isolating that component of the given endogenous variable that is explained by the exogenous variables in the system (‘the instruments’) and then using this component as a regressor.”

[9] As explained by Roller and Waverman, “This approach uses all the exogenous variable in the system of equations (i.e. those that can reasonably be assumed are not determined by the other variables in the system, such as the amount of labour and the amount of total capital) as ‘instruments’ for the endogenous variables (output, the level of penetration, and the prices). Instrumenting the endogenous variables essentially involves isolating that component of the given endogenous variable that is explained by the exogenous variables in the system (‘the instruments’) and then using this component as a regressor.”

[10] Detailed results of econometric models are included in Annex E.

[11] See: https://www.itu.int/en/ITU-D/Regulatory-Market/Pages/Economic-Contribution.aspx.

[12] The Index for Development of the Digital Ecosystem was developed under funding from CAF Development Bank of Latin America.

[13] The ITU ICT Regulatory Tracker is available at www.itu.int/net4/itu-d/irt/#/tracker-by-country/regulatory-tracker/2019.

[14] The Regional Econometric Studies are available at: https://www.itu.int/en/ITU-D/Regulatory-Market/Pages/Economic-Contribution.aspx.

[15] Op. cit. above.

[16] Op. cit. above.

[17] See Katz and Koutroumpis, 2013a.

[18] Katz and Koutroumpis, 2013a; Katz et al., 2013b, Katz et al., 2014.

[19] Katz and Callorda, 2018.

[20] This was used as a base case of an “average” country whose Digitization Index increased by 10 points.

[21] Originally developed by Roller and Waverman (2001) and implemented by Koutroumpis (2009), Katz and Koutroumpis (2012a; 2012b), and Katz and Callorda (2014; 2016; 2018).

[22] As explained by Roller and Waverman, “This approach uses all the exogenous variable in the system of equations (i.e. those that can reasonably be assumed are not determined by the other variables in the system, such as the amount of labour and the amount of total capital) as ‘instruments’ for the endogenous variables (output, the level of penetration, and the prices). Instrumenting the endogenous variables essentially involves isolating that component of the given endogenous variable that is explained by the exogenous variables in the system (‘the instruments’) and then using this component as a regressor.”

[23] Telecommunications services provide value insofar that they allow consumer access to the Internet.