Digging in to Premise, and mentioned in a recent notable.

https://www.huffingtonpost.com/jon-hartley/the-success-of-monitoring_b_6875126.html

It’s rare to find academic economists in the Ivory Tower creating new technologies that generate waves of interest jointly from policymakers, Wall Street and Silicon Valley. Roberto Rigobon and Alberto Cavallo, two professors at the MIT Sloan School of Management, make an exception. Since 2006, the tandem academic team have been working diligently on “The Billion Prices Project“ (BPP), an initiative that gathers price data by scraping information from online retailers around the globe. The high-frequency price data from the internet is then aggregated to measure inflation on a daily basis, helping government officials, economists and investors learn macroeconomic trends in real time.

Using online prices, the BPP daily inflation indices cover more than 70 countries and use daily price fluctuations of over five million items sold in over 300 online retailers. Since inception, the BPP U.S. inflation index has moved reasonably closely with the U.S. Consumer Price Index (CPI), an inflation index published by the Bureau of Labor Statistics which tracks monthly data on the prices paid by urban consumers for a representative basket of goods. The CPI’s annual percentage change is used as one of the canonical measures of inflation alongside the PCE published by the Bureau of Economic Analysis that often runs 0.5% lower than annual change in CPI and is often used by the Fed in its inflation forecasting. As one of the most widely tracked macroeconomic indicators, the CPI is published monthly at a lag and doesn’t give policymakers and economists the same timeliness associated that real-time price indices like the BPP series can provide.

>>5607361

Premise, a start-up data company based in San Francisco, takes a different approach to measuring inflation using new technology. They focus on aggregating and collecting price data from iPhone snapshots of price tags taken by paid individuals that are scattered across a wide variety of countries (some of which have underdeveloped national statistics).

>>5607367

Alberto Cavallo, MIT Sloan School of Management professor and co-founder of the BPP also spoke about how Big Data allows for the “ability to measure things we could not measure before” citing how data collected from new sources like satellite imagery can help measure economic trends. He agreed with commissioner Groshen in saying that the BLS and BPP data were “complementary”.

They're tracking us with phones and satellites guys…

>>5607377

https://www.earth.com/news/map-living-conditions-global-poverty/

Satellites could help the United Nations (UN) achieve its Sustainable Development Goals by providing a clearer picture of living conditions across the world at the household level.

It can be difficult to measure global poverty levels and economic conditions especially in developing nations where population growth is expected to increase rapidly in the coming years.

But if the UN is to stay on schedule with its development agenda which aims to improve quality of life and sustainability worldwide, tracking living and economic conditions is critical. That’s why researchers from Aarhus University in Denmark have turned to satellite data.

A new study published in the journal Proceedings of the National Academy of Sciences shows that freely available satellite imagery can be used to map economic living conditions at the household level in developing nations where this information has not been readily available.

>>5607388

“The use of satellite images makes it much, much cheaper to keep track of how far we are in reaching the UN’s goals for sustainable development. If conventional assessments of the households’ economic conditions were used, the cost would be more than 250 billion dollars,” said Gary R. Watmough, a lead member of the research team.

SENSES TINGLING

>>5607397

When U.N. member states unanimously adopted the 2030 Agenda in 2015, the narrative around global development embraced a new paradigm of sustainability and inclusion—of planetary stewardship alongside economic progress, and inclusive distribution of income. This comprehensive agenda—merging social, economic and environmental dimensions of sustainability—is not supported by current modes of data collection and data analysis, so the report of the High-Level Panel on the post-2015 development agenda called for a “data revolution” to empower people through access to information.

https://www.brookings.edu/research/using-big-data-and-artificial-intelligence-to-accelerate-global-development/

FUCK!

>>5607411

Earth Observations (EO) provide finely tuned and near-real-time data on global terrain. These data are becoming widely available to public and private actors through platforms like the Global EO System of Systems (GEOSS). A coalition of 105 governments and 127 participating organizations, known as the Group on Earth Observations (GEO), is working to ensure that EO are accessible and interoperable.[6] There is increasing recognition that these data can be used to support the 2030 Agenda for Sustainable Development.

>>5607415

Mobile phone data can also be used to infer socioeconomic characteristics in a geographically disaggregated way. Cell phones are ubiquitous in developed and emerging economies. Call Detail Records (CDRs), which are stored and secured by Mobile Network Operators (MNOs) provide data on: (i) mobility, (ii) social interactions, and (iii) consumption and expenditure patterns (from the degree to which airtime is pre-paid). Joshua Blumenstock et al. (2015) used anonymized metadata from Rwanda’s largest cell phone network in combination with follow-up surveys to examine the extent to which mobile phone data can be used to estimate socioeconomic characteristics, and map a country-level wealth profile.[13] When aggregated at a district level, Blumenstock et al. found that mobile phone data estimations were comparable to predictions using ground data collected by the Kigali Demographic and Health Survey (DHS). More granularly, historical records of an individual’s mobile phone use can accurately predict socioeconomic characteristics. Vanessa Frias-Martinez et al. determined that cell records can also be used to approximate costly and infrequent census information.[14] They propose a new tool, CenCell, which uses behavioral patterns collected from CDRs to classify socioeconomic levels, with classification accuracy rates of up to 70 percent.

AGENDA 2030

AGENDA 2030

DIG

DIG