Meklēšanas opcijas
Sākums Medijiem Noderīga informācija Pētījumi un publikācijas Statistika Monetārā politika Euro Maksājumi un tirgi Karjera
Ierosinājumi
Šķirošanas kritērijs
Latviešu valodas versija nav pieejama

Simon Ben Arous

31 January 2024
WORKING PAPER SERIES - No. 2900
Details
Abstract
This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck’s law) and machine learning to detect the heat produced by cement plants in activity. This allows us to monitor in real-time whether a cement plant is working. Using this information on around 500 plants, we construct a satellite-based index tracking activity. We show that using this satellite index outperforms benchmark models and alternative indicators for nowcasting the production of the cement industry as well as the activity in the construction sector. Comparing across methods, we find neural networks yields significantly more accurate predictions as they allow to exploit the granularity of our daily and plant-level data. Overall, we show that combining satellite images and machine learning allows to track economic activity accurately.
JEL Code
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
E23 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Production
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications

Mūsu interneta vietnē izmantotas sīkdatnes

Mēs izmantojam funkcionālās sīkdatnes, lai saglabātu lietotāju izvēles, analītikas sīkdatnes, lai uzlabotu tīmekļa vietnes sniegumu, un trešo pušu sīkdatnes, ko nosaka trešo pušu pakalpojumi, kas integrēti interneta vietnē.

Jūs varat tās pieņemt vai noraidīt. Lai iegūtu plašāku informāciju vai pārskatītu mūsu izmanto sīkdatņu un serveru žurnālu izvēli, aicinām jūs iepazīties ar tālāk sniegto informāciju.

Lasiet mūsu privātuma paziņojumu

Uzziniet vairāk par sīkdatņu izmantošanu