New Frontiers in Economic Research1
Governor Mr Ahmed Munawar, Maldives Monetary Authority (MMA), Dr
Mahamood Shougee, Chancellor of the Maldives National University, Mr
Ahmed Imad, Deputy Governor, MMA, other senior colleagues of the
MMA, distinguished presenters and panelists and participants, ladies and
gentlemen, good morning to all of you.
It is an honour for me to be invited to give the keynote address at this two-
day Annual Research Conference of the MMA that is aptly themed:
Advancing Economic Research: Policy and Innovation for a Sustainable
Future. The impressive line-up of papers to be presented in the
conference will shine light on to this topical theme. In my address today, I
wish to focus on some new frontiers in economic research and their
relevance for policy making globally, but with a focus on the Global South.
Economic inquiry is characterised as the spirit of exploration in a continual
quest to understand the invisible hand that transforms livelihoods, shapes
societies, and defines humanity's aspirations. In that sense, economists
have always been cartographers of unyielding trade-offs and impossible
trinities in their profession of studying mankind in the ordinary business of
life, as Alfred Marshall famously defined economics. The lives of
economists are complicated by the fact that underneath their feet, the
ground is always shifting and reshaping economic constructs, information
stocks and flows, and available tools. Today, we stand on the cusp of an
era being redefined as much by the boundless possibilities of technology
and innovation as the risks of climate change and deglobalisation. For
the economics profession, therefore, as the Greek philosopher Heraclitus
remarked, "Change is the only constant."
Our research has to adapt not only to today's tectonic shifts but also to
new frontiers to be traversed tomorrow. Against this backdrop and in the
interest of time, I will focus on four emerging areas of research that, I
believe, will redefine human behaviour and hence economic research.
I. Redefining Technology Shocks in Economic Models
The rapid spread of digitalisation has been transformative, reshaping the
way we live and work, the interactions between economic agents,
production processes and market structures. Digitalisation can be
regarded as a long-term technology shock impacting economic growth,
productivity, labour markets, older technologies and inflation. It is
estimated that the global digital economy already accounts for more than
15 per cent of global GDP.2 Generative artificial intelligence (Gen-AI)
alone is projected to boost global GDP by $7-10 trillion over the next three
years.3 To capture these evolving dynamics, empirical research
methodologies must evolve to be able to understand and assess the
underlying relationships and implications.
Despite the potential of digital technologies to drive productivity through
efficiency, growth has consistently fallen short of expectations. This has
given rise to antithetical scenarios of slow innovation diffusion.4 Recent
studies have deepened the debate, highlighting the uncertainty around
AI's impact on productivity and economic growth.5 This productivity puzzle
could be pointing to research gaps in growth decomposition models as
well as in the received wisdom in explaining sectoral productivity shifts
and the distributional effects of technology shocks across regions and
income groups.
Digitalisation's long-term impact on employment appears benign so far,
but its disruptive effects on labour markets have drawn considerable
2
United Nations. (2023). Opening Session of Global Development Initiative Digital
Cooperation Forum.
3
JP Morgan. (2024). Is Generative AI a Game Changer?
4
Brynjolfsson, E., and McAfee, A. (2014). The Second Machine Age: Work, Progress,
and Prosperity in a Time of Brilliant Technologies. WW Norton & Company; Haldane,
A. (2017). Productivity Puzzles. Speech at the London School of Economics;
Summers, L. H. (2013). Speech at the IMF 14th Annual Research Conference in Honor
of Stanley Fisher. International Monetary Fund, 8
5
Goldman Sachs. (2024). Gen AI: Too Much Spend, Too Little Benefit Report.
attention.6 Population ageing may further accelerate adoption of digital
technologies. With AI set to affect 40 per cent of global jobs, education,
retraining and social safety nets will be crucial.7 Within central banks too,
recruitment and retention of FinTech talent are becoming major
challenges, with 64 per cent struggling to recruit and 68 per cent facing
retention issues.8 The ambit of research need to expand to examine
digitalisation-driven labour reallocation, job-matching efficiency, new
vistas of job creation such as in data science, and digitalisation's role in
boosting female workforce participation through remote-friendly jobs.
Digitalisation's impact on economic variables relevant to monetary policy
requires close monitoring, particularly its effect on inflation due to
differences between online and offline prices, potentially steepening the
Phillips curve, and hence, warranting a reassessment of traditional
inflation models.9 Research interest is being drawn to examining how
financial innovations like digital payments, FinTech, central bank digital
currencies (CBDCs) and AI can reshape monetary policy transmission
and affect financial stability. Dynamic methods and big data analytics like
web-scraping, text mining, large language techniques and machine
learning frameworks (e.g., tree-based models and neural networks)10 are
becoming vital for macro-financial analysis and monetary policy tech.
II. Climate Change and Macroeconomic Stability
Climate change is manifesting itself at an alarming scale and pace
globally. It is affecting growth and price stability through supply shocks
such as food and energy shortages and through a decline in productive
capacity. Recurrent climate-related shocks are leading to inflation
volatility, un-anchoring inflation expectations. Demand shocks also arise
due to the loss of wealth of firms and households on account of frequent
natural disasters, with attendant financial stability risks. Physical and
transition risks can affect the balance sheets of financial institutions and
banks, limiting the flow of credit to the real economy. In fact, transition
risks can operate through multiple channels, exacerbating traditional risks
in all categories, including credit, market, liquidity, operational and
reputational risks for banks and financial institutions. Mitigation and green
transition policies such as carbon pricing can also affect price stability,
potentially precipitating large and long-lasting movements in relative
prices and shifts in trend inflation. Depreciation pressures on currencies
of countries frequently affected by climate disasters can also cause
financial instability, higher import costs and negative terms of trade.
The range of policy options available to mitigate climate risks require
dedicated research, especially in the context of the complex, non-linear
ways in which climate, the real economy, financial systems and markets
interact and affect each other. Improved inter-disciplinary macroeconomic
modelling is becoming crucial for understanding directions of causality
and feedbacks.
III. Globalisation and the Natural Rate of Interest
Monetary policy making has evolved in line with structural changes in the
economy and the financial system. Inflation targeting (IT) - the longest
surviving modern monetary policy framework - is no exception. This could
be attributed to the 'rule-based' principle built into the framework
alongside elements of "flexibility" that have evolved in practice. It has been
argued while the application of a core set of "scientific principles" has
expanded significantly in practice, there remains, and will likely always
remain, elements of art in the conduct of monetary policy11.
One principle followed by central banks in setting policy rates is the natural
rate of interest - popularly known as R-star. It is a theoretical benchmark
for monetary policy, reflecting the real interest rate that supports the
economy at full employment while keeping inflation low and stable. This
concept of R-star or the natural rate dates back to 189812 and currently
forms an integral element of modern macroeconomic frameworks. It is
argued in a seminal work that "a central bank should seek to close the
gaps between actual economic conditions and the economy's potential for
output and employment (y-star and u-star, respectively) as well as the gap
between the actual real interest rate and the natural rate (R-star), all at
the same time to obtain an optimal outcome".13 The problem is that R-star
or any of the other stars in that formulation are fundamentally
unobservable. Formal efforts to estimate the value of R-star14 have been
refined over the years in terms of estimation approaches as well as by
accounting for structural changes and country-specific features.
It is widely believed that historically, R-star has declined, especially in
advanced economies, due to factors like aging populations, lower
productivity growth, and excess global savings. More recently, however,
the view gaining ground is that post-pandemic dynamics - in particular,
overlapping shocks - have reversed some of these trends. This is
observed, for instance, in the real time measure of R-star released by the
New York Fed on its website15. A better understanding of the reasons
behind the post-pandemic reversal and this recent disconnect from history
will be useful for monetary policy setting in an uncertain future.
Global economic conditions add complexity to an accurate assessment of
R-star. Advanced economies face sluggish growth amidst changing
labour market dynamics, stubborn services inflation, and fiscal policy
uncertainties, all of which could be imparting upsides to R-star. Emerging
and developing economies may be experiencing upward pressure on their
R-stars due to stronger economic activity and investment as well as
productivity differentials. They, however, face challenges from geo-
economic fragmentation and geo-political uncertainty as well as global
supply chain disruptions and financial market volatility. Central banks
across the globe are therefore, reassessing how these global factors
could be driving shifts in R-star to ensure that monetary policy remains
effective in an interconnected world.
IV. Consumption Patterns and their Economic Impact
The rapid progress in information and communication technology (ICT) is
contributing significantly to shortening the 'space-time flow' of circulation
of capital - allowing it to move faster and grow larger.16 The growing
usage of digital financial platforms and tools is also shaping the behaviour
of households in multifarious ways.
First, with the proliferation of digital products and social media platforms,
there has been a marked shift from in-person shopping to online shopping.
E-commerce is growing rapidly, with online sales accounting for a
significant portion of retail sales in many countries. The pandemic gave a
distinct push to online shopping, which has sustained its growth
momentum even in the post-pandemic period. In 2023, e-commerce
accounted for over 19 per cent of retail sales worldwide. Forecasts
indicate that by 2027, the online segment will make up close to a quarter
of total global retail sales.17 The global annual retail e-commerce sales
growth is projected to reach 9 per cent in 2024 from 6 per cent in 2022.18
This rise of e-commerce has also led to a shift in favour of digital goods
and services.19 To illustrate, the global number of users of video streaming
services has increased from 0.6 billion in 2017 to 1.4 billion in 2024, with
a similar uptrend seen for music streaming and digital news services.20
Secondly, the proliferation of digital consumption has also been
accompanied by a shift in saving and investment decisions such as online
brokerage accounts, robo-advisors, investment apps and the like, as they
are easier, faster and more informed. Digitalisation has also influenced
borrowing patterns of households, with greater and easier access to
fintech companies for digital loans, and by reducing information
asymmetries through a wide range of sources, including tax returns,
electronic toll collection, and bill payments.21
At the same time, these newer technologies pose challenges for monetary
and regulatory policy formulation. First, the shift from traditional modes of
savings can affect the transmission of monetary policy impulses to the real
economy.22 Second, central banks need to be vigilant about the
possibilities of debt escalation and risk build-up at the household level.23
Third, there is evidence to suggest that the buy-now-pay-later and credit
card-based spending can facilitate immediate consumption, especially for
younger generations and lower their savings.24 Fourth, there can be
concerns of mis-selling of financial services to households due to poor
digital financial literacy.25
These shifts in consumer behaviour may require central banks and
policymakers to transition from traditional macroeconomic models to
agent-based modelling, integration of behavioural economics,
nowcasting, policy simulations and advanced liquidity stress tests. They
also need to equip themselves with cutting-edge computational tools like
machine learning and big data analytics to examine the real-time, high-
frequency data received from digital platforms.
V. Conclusion
As we journey towards new frontiers of economic research, I am reminded
of the words of John Maynard Keynes: "The difficulty lies not so much in
developing new ideas as in escaping from old ones".
Economic research is like exploring a dense forest: each new finding
clears a path, but also reveals deeper mysteries. As we prepare, like the
starship Enterprise, in the famous sci-fi television series Star Trek, to
boldly go where no man has gone before, I am reminded of the words of
T.S. Eliot: 'Only those who will risk going too far can possibly find out how
far one can go'. In recent years, economic research is increasingly being
equipped with multi-disciplinary frameworks, forward-looking and
computationally intensive analytical tools, and high dimensional data. So
let us venture into the unknown with a commitment to redefine what is
possible, to make the complex comprehensible, and to transform our
understanding of the forces that shape human experience.
Thank you.