How Data Helps Digital Nomads Thrive in Asia and the Pacific

A review of geographically granular or subnational data on socioeconomic indicators, such as employment rate, gross domestic product (GDP), and prices, can help provide a better understanding of the growing trend of digital nomadism.

Access to geographically granular data, which breaks down economic indicators by region or province, enables digital nomads to make informed decisions about where to live or work.

Geographically disaggregated employment statistics are particularly valuable for digital nomads, many of whom take on multiple jobs across various industries. By providing insights into local labor markets, these statistics identify regions with strong economic activity and diverse job opportunities. This enables digital nomads to strategically choose locations where freelance, contract, or remote work is more accessible—supporting both their professional growth and financial stability. On the other hand, data on economic activity and prices allow for a better understanding of how affordable different locations within an economy are and where availability of economic opportunities are higher.

Beyond the general understanding of digital nomadism, compiling cross-economy geographically granular data on various socioeconomic indicators in one database is essential for enhanced policymaking and comparative analysis.

Data helps local governments assess the level of attractiveness for digital nomads and make informed decisions accordingly. It can assist in tailored interventions, address unique local challenges more effectively, and ensure efficient resource allocation. It facilitates the comparison of socioeconomic conditions across different geographic areas and economies, helping identify best practices and successful policy programs.

Geographically granular data also enables continuous monitoring and evaluation of progress, revealing disparities that might be hidden in aggregated national data and allowing for precise interventions to reduce inequality.

Recognizing the advantages of having easy access to geographically granular data, ADB’s Key Indicators for Asia and the Pacific 2024 started piloting compilation of geographically granular data on labor, GDP, and prices in select economies with diverse socioeconomic conditions.

From resource-driven economies like Indonesia and Kazakhstan, to small island nations like Micronesia, to urbanizing economies such as Thailand and Philippines, to a developed economy like Australia, and a young nation like Timor-Leste, the granular data pilot initiative provides a valuable platform to examine region-specific data in order to design interventions that can address each economy’s unique developmental challenges.

For digital nomads seeking their next destination, navigating through an ocean of economic variables is no easy task. Local economic conditions, cost of living, and employment opportunities vary widely—even within the same economy.

Subnational data offers a much-needed perspective on these differences, empowering nomads to make informed decisions that align with their professional needs and lifestyle preferences. ADB's Key Indicators for Asia and the Pacific 2024 builds on this need by presenting geographically disaggregated data on labor, GDP, and prices across diverse economies. This data unveils regional disparities and factors that influence the economic competitiveness and livability of various locations. These insights are indispensable for both digital nomads and policymakers.

Economic attractiveness 
Economies, such as Indonesia, Malaysia, Philippines, and Thailand, show significant disparities in GDP per capital across different regions. Capital cities and key economic hubs—such as DKI Jakarta in Indonesia, Kuala Lumpur in Malaysia, National Capital Region in the Philippines, and Rayong in Thailand—exhibit GDP per capita levels approximately eight to 13 times higher than those of other provinces or regions within their respective economies, indicating that economic growth remains highly concentrated in a few urban and industrial centers.

Figure 1. 10-Year Average GDP Per Capita by Region in Indonesia (2014–2023)

Jakarta leads regional GDP per capita in Indonesia, with stark disparities evident across regions.

Note: y-axis: Indonesian Rupiah (Rp '000); x-axis: Region

Figure 2. 10-Year Average GDP Per Capita by Region in Malaysia (2013–2022)

Kuala Lumpur tops Malaysia's regional GDP per capita, highlighting urban–rural divide.

Note: y-axis: Malaysian Ringgit (RM); x-axis: Region

Figure 3. 10-Year Average GDP Per Capita by Region in the Philippines (2014–2023)

NCR exhibits highest regional GDP per capita in the Philippines, underlining pronounced interregional economic disparities. 

Note: y-axis: Philippine Peso (PHP); x-axis: Region

Figure 4. 10-Year Average GDP Per Capita by Province in Thailand (2013–2022)

Rayong and Bangkok lead in GDP per capita among Thailand’s provinces, reflecting persistent economic concentration in key economic hubs.

Note: y-axis: Thai Baht (B); x-axis: Province

Affordability
While high GDP may attract digital nomads due to economic opportunities, affordability is equally vital. Economies with low consumer price index (CPI) growth offer more cost-effective living conditions.

Figure 5. Regional CPI Trends in the Philippines: Comparing 2014 and 2023

The Philippine's regional CPI trends highlight varied inflationary pressures, with significant increases observed across most regions between 2014 and 2023.

Figure 6. Regional CPI Trends in Malaysia: Comparing 2014 and 2023

Malaysia's regional CPI trends highlight a general decline in inflation rates, indicating enhanced affordability in most areas between 2014 and 2023.

Employment dynamics
Using the Theil index^[1], 2000–2023 data on select developing member economies—Thailand, Philippines, Indonesia, and Malaysia—reveals key patterns of uneven economic development, highlighting the ongoing challenges of regional inequality.

Figure 7. Trends in Regional Economic Inequality: Theil Index of GDP (2000–2023)

Theil index computed from data in ADB’s Key Indicators for Asia and the Pacific 2024, a pilot compilation of geographically granular data on labor, GDP, and prices in select economies.

In Thailand, the index underscores significant disparities among 77 provinces, with economic activity disproportionately concentrated in urban centers such as Bangkok. The capital’s overwhelming contribution to the GDP compared to rural provinces emphasizes the need for more balanced regional development. While industrial and tourism hubs continue to attract investment and generate employment, rural areas struggle with higher unemployment and underemployment rates. For example, Bangkok’s unemployment rate (3.1%) is lower than in many rural provinces, while its GDP per capita (634,108 THB) exceeds that of rural areas like Yasothon (72,523 THB).

Similarly, economic growth in the Philippines has largely been centered around Metro Manila, Cavite-Laguna-Batangas-Rizal-Quezon, and Central Luzon, leaving behind other regions, particularly Mindanao. The uneven distribution of resources mirrors employment disparities, with rural areas facing higher unemployment rates and fewer economic opportunities.

In Indonesia, the economy's unique archipelagic geography presents its own set of challenges for achieving equitable growth. Local level data reveals sharp disparities between urban regions such as Jakarta, Java, and Bali, and the more remote islands. Consumer price index for Jakarta (119.251) outpaces many other regions, indicating a higher cost of living in the capital city.

In Malaysia, the divide between urban and rural states is also evident in the Theil Index. Economic dominance is concentrated in urban areas, such as Kuala Lumpur and Selangor, which lead in terms of GDP and employment opportunities. Meanwhile, rural states Sabah and Sarawak continue to lag—struggling with lower incomes and limited job prospects.

The growing inequality underscores the need for targeted interventions to bridge the urban–rural divide and promote balanced growth across the economy. These disparities highlight the importance of subnational data in understanding local economic conditions.

For digital nomads, granular data provides invaluable insights into the economic conditions of various areas, empowering them to make more informed choices about their destinations that are aligned with their lifestyle preferences and professional goals.

By comparing living costs, job market conditions, and economic growth across regions, nomads can identify locations that offer the best value for their budget without sacrificing quality of life or career opportunities. For example, they might discover that secondary cities in Thailand or Malaysia offer a lower cost of living compared to capital cities, while still providing robust digital infrastructure and vibrant expat communities.

The implications of this data extend beyond the nomad community into policymakers in Asia and the Pacific. The stark economic disparities highlighted by the Key Indicators for Asia and the Pacific 2024 initiative underscore the need for targeted development strategies. Regions with high unemployment rates, such as Sabah in Malaysia (7.5%), may require focused job creation initiatives. Conversely, high-growth areas, such as Central Sulawesi in Indonesia (11.91% GDP growth), might inform infrastructure and investment decisions.

The Key Indicators for Asia and the Pacific 2024 pilot initiative marks a significant step toward understanding and harnessing the potential of geographically disaggregated data in Asia and the Pacific. Policymakers can use this information to develop targeted strategies that can attract global talent and foster economic growth across all regions.

As the world becomes more interconnected, the ability to make data-driven decisions will be crucial role in shaping economic policies, guiding individual decisions, and fostering a more equitable distribution of opportunities across the region.

^[1] The Theil index is a robust measure of inequality that helps capture how economic growth and resources are distributed across different subnational areas within an economy.

Asian Development Bank. 2024. Key Indicators for Asia and the Pacific 2024: Data for Climate Action. 

K. Chen. 2024. 66 Countries with Digital Nomad Visas—and How to Apply to the Top Programs. Condé Nast Traveler. 6 November.

World Tourism Organization. 2023. UNWTO Brief: Digital Nomad Visas.