CREDIT SCORING | PLACE PREMIUMS | HOUSING PROPOSALS
Big data's effect on the credit-scoring industry
A lengthy 2016 article from the Yale Journal of Law and Technology delves into credit-scoring then suggests a new legislative framework.
Since 2008, lenders have only intensified their use of big-data profiling techniques. With increased use of smartphones, social media, and electronic means of payment, every consumer leaves behind a digital trail of data that companies—including lenders and credit scorers—are eagerly scooping up and analyzing as a means to better predict consumer behavior. The credit-scoring industry has experienced a recent explosion of start-ups that take an 'all data is credit data' approach that combines conventional credit information with thousands of data points mined from consumers' offline and online activities. Many companies also use complex algorithms to detect patterns and signals within a vast sea of information about consumers' daily lives. Forecasting credit risk on the basis of a consumer's retail preferences is just the tip of the iceberg; many alternative credit-assessment tools now claim to analyze everything from consumer browsing habits and social media activities to geolocation data.
Tallying the gains of migration
We recently linked to a paper by LANT PRITCHETT that challenged development orthodoxy by pointing out that the income gains for the subjects of best practice direct development interventions are about 40 times smaller than those from allowing the same people to work in a rich country like the United States.
Link, again, to that paper.
That argument was built upon previous scholarship that attempted to put rigorous numbers to the obvious intuition that migration is beneficial for those drawn to wealthy countries by labor markets. From a 2016 paper by Pritchett and co-authors MICHAEL CLEMENS and CLAUDIO MONTENEGRO:
"We use migrant selection theory and evidence to place lower bounds on the ad valorem equivalent of labor mobility barriers to the United States, with unique nationally-representative microdata on both US immigrant workers and workers in their 42 home countries. The average price equivalent of migration barriers in this setting, for low-skill males, is greater than $13,700 per worker per year."