Yusuf Mansur

For decades, economic development was judged primarily through a narrow set of indicators, most notably gross domestic product (GDP), income per capita, and unemployment rates. While these measures remain important, they no longer tell the whole story. Over the past three decades, economists and policymakers have come to recognize that development is about far more than economic output. It is equally about improving people's quality of life, expanding opportunities, enhancing public services, and ensuring that the benefits of growth are broadly shared.

The intellectual foundations of local development measurement can be traced back to the emergence of regional science during the 1950s under the leadership of American economist Walter Isard, widely regarded as the founding father of the discipline. In 1954, the Regional Science Association was established, bringing together economists, geographers, urban planners, and statisticians to develop analytical tools capable of measuring disparities not only between countries but also among cities, regions, and local communities.

The concept evolved significantly in the decades that followed. Nobel laureate Amartya Sen transformed the understanding of development by arguing that it should be measured by people's capabilities and freedoms rather than income alone. Later, the Stiglitz-Sen-Fitoussi Commission helped shift the international policy debate toward what became known as the "Beyond GDP" agenda. The Commission argued that economic progress should be assessed through a broader lens encompassing quality of life, sustainability, inequality, human capital, environmental conditions, and trust in public institutions—not merely the value of goods and services produced.

Today, international organizations have adopted a multidimensional approach to measuring local development. These indicators generally fall into five broad categories: The first consists of traditional economic indicators, including GDP per capita, unemployment, poverty, investment, labor productivity, business creation, exports, and wage levels. The second covers social indicators, such as educational attainment, life expectancy, healthcare quality, gender equality, public safety, and housing conditions. These measures form the backbone of the United Nations' Human Development Index. A third category focuses on infrastructure, assessing the quality of roads, access to electricity and clean water, sanitation, public transportation, and digital connectivity. The fourth evaluates environmental sustainability, including air quality, waste management, carbon emissions, water efficiency, and the availability of green spaces.

Yet perhaps the most remarkable transformation has come from the rise of big data, satellite imagery, and artificial intelligence, which have introduced entirely new ways of measuring economic activity and local prosperity.

Among the most influential innovations is the use of nighttime satellite imagery. Satellites operated by NASA and the U.S. National Oceanic and Atmospheric Administration capture images of the Earth's surface after dark, allowing researchers to measure the intensity of artificial lighting. Institutions such as the World Bank and the International Monetary Fund increasingly use these data as a proxy for local economic activity, particularly in countries or regions where reliable official statistics are scarce. Numerous studies have shown that brighter nighttime lights are strongly associated with higher levels of income, employment, urban development, education, and access to public services.

Nighttime lights have become especially valuable in conflict-affected countries such as Syria, Yemen, and Sudan, where conventional economic statistics are often unavailable or unreliable. They have even been used to monitor economic activity in North Korea, offering researchers rare insights into regional development patterns that would otherwise remain invisible.

But satellite lights represent only one element of a rapidly expanding toolkit. International institutions increasingly use electricity consumption as a high-frequency indicator of economic activity, since industrial production, commercial activity, and household consumption all influence electricity demand.

Mobile phone data have become another valuable resource, helping analysts measure population movements, tourism flows, commuting patterns, and post-disaster recovery.

Likewise, electronic payment systems and credit card transactions provide near real-time information about household spending, consumer confidence, and commercial activity.

Artificial intelligence has also opened entirely new frontiers. By analyzing satellite images of buildings, roads, and urban expansion, AI algorithms can estimate housing quality, identify informal settlements, and even predict poverty levels in areas where household surveys are unavailable.

The World Bank has also developed measures based on travel time to essential services, assessing how long it takes residents to reach schools, hospitals, markets, or major roads. Accessibility, after all, is an essential component of development.

Other unconventional indicators are equally revealing. Satellite-based vegetation indices help monitor agricultural productivity and food security. Property prices provide insights into the attractiveness and competitiveness of cities. Hotel occupancy rates measure tourism performance. Broadband internet speed reflects digital readiness. Even municipal solid waste generation has been used in several advanced economies as a proxy for economic activity and consumption.

What do these developments mean for Jordan? They present an opportunity to move beyond traditional statistics and establish a Smart Local Development Index capable of measuring the performance of governorates, districts, and municipalities regularly. Such an index could integrate conventional economic and social statistics with modern data sources, including satellite imagery, electricity consumption, digital payments, mobile phone mobility, and artificial intelligence.

The benefits would extend well beyond statistical reporting; instead of allocating development spending based primarily on historical patterns or administrative considerations, policymakers could identify the areas most in need of investment, evaluate the impact of infrastructure projects, compare regional performance objectively, and link development budgets to measurable outcomes.

Around the world, the measurement of development is moving beyond GDP toward a richer understanding of prosperity—one that incorporates quality of life, opportunity, sustainability, and spatial inclusion. Advances in remote sensing, big data, and artificial intelligence are making it possible to monitor local development with unprecedented precision and frequency.

For Jordan, embracing this transformation would not simply represent an improvement in statistical methodology. It would provide a strategic decision-making tool capable of directing investment where it is needed most, narrowing regional disparities, improving policy evaluation, and supporting a more inclusive and sustainable model of economic development. In an era where data increasingly shape public policy, the countries that measure development more intelligently will also be the ones best positioned to manage it more effectively.


The writer is a Former Jordanian Minister of State for Economic Affairs