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Innovation, industrial dynamics and regional inequalities

Boschma, Ron; Pardy, Martina; Petralia, Sergio - In: Handbook of industrial development, (pp. 151-164). 2023

Persistent link: https://www.econbiz.de/10014329246

Urban economics in a historical perspective: recovering data with machine learning

Combes, Pierre-Philippe; Gobillon, Laurent; Zylberberg, … - 2021

A recent literature has used a historical perspective to better understand fundamental questions of urban economics. However, a wide range of historical documents of exceptional quality remain underutilised: their use has been hampered by their original format or by the massive amount of...

Persistent link: https://www.econbiz.de/10012519104

Predicting provincial gross domestic product using satellite data and machine learning methods : a case study of Thailand

Puttanapong, Nattapong; Nutchapon Prasertsoong; Wichaya … - In: Asian development review : studies of Asian and pacific … 40 (2023) 2, pp. 39-85

This study introduced a new approach for monitoring regional development by applying satellite data with machine … system of regional development. …

Persistent link: https://www.econbiz.de/10014426256

Predicting Urban Growth with Machine Learning

Buechler, Simon; Niu, Dongxiao; Kinsella Thompson, Anne - 2021

Using machine learning (ML) models, we predict the population growth for the next two, ﬁve, and ten years for American and Chinese urban areas. To this end, we construct a rich city-level data set encompassing information on transportation, output, amenities, and human capital. The ML models...

Persistent link: https://www.econbiz.de/10013241488

Deep Learning, Deep Change? Mapping the Development of the Artificial Intelligence General Purpose Technology

Klinger, Joel - 2018

and national and regional competitiveness. In spite of this, the geography of their development and diffusion has not … new fields where it has generated an impact, we describe changes in its geography. Our analysis shows China's rise in AI … rankings and relative decline in several European countries. We also find that initial volatility in the geography of DL has …

Persistent link: https://www.econbiz.de/10012912827

Assessing spatiotemporal differences in shrimp ponds using remote sensing data and machine learning algorithms

Kumar Bellam, Pavan; Gumma, Murali Krishna; Panjala, Pranay - 2023

Shrimp farming and exporting is the main income source for the southern coastal districts of the Mekong delta. Monitoring these shrimp ponds is helpful in identifying losses incurred due to natural calamities like floods, sources of water pollution by chemicals used in shrimp farming, and...

Persistent link: https://www.econbiz.de/10014251077

Is distance from innovation a barrier to the adoption of Artificial Intelligence?

Hunt, Jennifer; Cockburn, Iain; Bessen, James - 2024

Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone...

Persistent link: https://www.econbiz.de/10015074505

Why East Asian students perform better in mathematics than their peers : An investigation using a machine learning approach

Lee, Hanol; Lee, Jong-Wha - 2021

Using a machine learning approach, we attempt to identify the school-, student-, and country-related factors that predict East Asian students’ higher PISA mathematics scores compared to their international peers. We identify student- and school-related factors, such as metacognition–assess...

Persistent link: https://www.econbiz.de/10013217422

How Does AI Improve Human Decision-Making? Evidence from the AI-Powered Go Program

Choi, Sukwoong; Kim, Namil; Kim, Junsik; Kang, Hyo - 2021

How does artificial intelligence (AI) improve human decision-making? Answering this question is challenging because it is difficult to assess the quality of each decision and to disentangle AI’s influence on decisions. We study professional Go games, which provide a unique opportunity to...

Persistent link: https://www.econbiz.de/10013217857

Applying Artificial Intelligence on Satellite Imagery to Compile Granular Poverty Statistics

Hofer, Martin; Sako, Tomas; Martinez, Jr., Arturo; … - 2021

The spatial granularity of poverty statistics can have a significant impact on the efficiency of targeting resources meant to improve the living conditions of the poor. However, achieving granularity typically requires increasing the sample sizes of surveys on household income and expenditure or...

Persistent link: https://www.econbiz.de/10013241473

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