Category: Data Source

Who benefits from Uber surge pricing?

In the last decade, new technologies have led to a boom in dynamic pricing. I analyze the most salient example, surge pricing in ride hailing. Using data from Uber in Houston, I build an empirical model of spatial equilibrium to measure the welfare effects of surge pricing. My model is composed of demand, supply, and a matching technology, and it allows for temporal and spatial heterogeneity, as well as randomness in supply and demand. I find that, relative to a counterfactual with uniform pricing, surge pricing increases total welfare by 3.66% of gross revenue. Only riders benefit: rider surplus increases by 6.52% of gross revenue, whereas driver surplus and Uber’s short-run profits decrease by 1.63% and 1.18% of gross revenue, respectively.

That is from a new job market paper by Juan Camilo Castillo of Stanford University.  At the link his other papers are interesting too.

The Long-Term Effects of California’s 2004 Paid Family Leave Act on Women’s Careers

It is not obviously a winner policy, at least not from the point of view of boosting women’s labor market opportunities.  In fact it seems to harm them:

This paper uses IRS tax data to evaluate the short- and long-term effects of California’s 2004 Paid Family Leave Act (PFLA) on women’s careers. Our research design exploits the increased availability of paid leave for women giving birth in the third quarter of 2004 (just after PFLA was implemented). These mothers were 18 percentage points more likely to use paid leave but otherwise identical to multiple comparison groups in pre-birth demographic, marital, and work characteristics. We find little evidence that PFLA increased women’s employment, wage earnings, or attachment to employers. For new mothers, taking up PFLA reduced employment by 7 percent and lowered annual wages by 8 percent six to ten years after giving birth. Overall, PFLA tended to reduce the number of children born and, by decreasing mothers’ time at work, increase time spent with children.

That is from a new NBER working paper by Martha J. Bailey, Tanya S. Byker, Elena Patel, and Shanthi Ramnath.  And are you wondering why the number of children falls as a response?  Because the mother ends up staying home with them?  Or do mothers invest more in child quality, thereby lower quantity, as in a Becker model?  In any case a good question.

The Mexican drug war and its intensification

Event study estimates suggest that cartel presence increases substantially after 2010 in municipalities well suited to grow opium poppy. Homicide rates increase along with the number of active cartels per municipality, with higher increases when a second, third, fourth and fifth cartel become active in the territory. These results suggest that some of the increase in violence that Mexico experienced in the last fifteen years could be attribute to criminal groups fighting for market shares of heroin and not only to changes in government enforcement.

That is from a recent job market paper by Fernanda Sobrino of Princeton University.

Facts about YouTube

From a new and very important paper by Kevin Munger and Joseph Phillips from Penn State:

The most extreme branches of the AIN (the Alt-Right and Alt-Lite) have been in decline since mid-2017.

However, the Alt-Right’s remaining audience is more engaged than any other audience, in terms of likes and comments per view on their videos.

The bulk of the growth in terms of both video production and viewership over the past two years has come from the entry of mainstream conservatives into the YouTube marketplace.

…despite considerable energy, Ribeiro et al. (2019) fail to demonstrate that the algorithm has a noteworthy effect on the audience for Alt-Right content.  A random walk algorithm beginning at an Alt-Lite video and taking 5 steps randomly selecting one of the ten recommended videos will only be recommended a video from the Alt-Right approximately one out every 1,700 trips.  For a random walker beginning at a “control” video from the mainstream media, the probability is so small that it is difficult to see on the graph, but it is certainly no more common than one out of every 10,000 trips.

That authors suggest (p.24) that if anything the data suggest deradicalization as a more plausible baseline hypothesis.

Of course this is not the final word, but in the meantime so much of what you are reading about YouTube would appear to be wrong or at least off-base.

Who tips on Uber?

Men tip 12 percent more if their driver is a woman, but that’s entirely because they give more money to the youngest female drivers. The premium men pay to women behind the wheel shrinks as the women get older. By the time the drivers are age 65, it has virtually vanished. Women also tip other women more, but they don’t significantly change their tips based on the driver’s age.

Tips are highest between 3 a.m. and 5 a.m., and not surprisingly:

Tips are highest in small cities and the middle of the country. Riders in California and the Northeast weren’t great tippers.

Here is much more from Andrew van Dam at The Washington Post.

Academic vita fraud?

recent study of 180 academic curricula vitae found that 56 percent that claimed to have at least one publication contained at least one unverifiable or inaccurate publication, and it suggests that CV falsification could be much more common than scholars committed to professional integrity might hope. The study is small — the 56 percent reflects only 79 CVs, of 141 that claimed to have at least one publication. The researchers behind the study make no presumption as to whether the errors were intentional.

Here is further information from Megan Zahneis.

Ranking states by their degree of regulation

Now Mercatus has completed an analysis of state-level regulation. State RegData 1.0 analyzes the administrative codes of 46 states plus the District of Columbia, and the results are informative. The average state has 131,000 restrictive terms and about 9 million words in its code, which would require roughly twelve work weeks to read at a normal reading pace.

But there is huge variation. The least regulated state is South Dakota, with about 44,000 regulatory restrictions, while the most regulated state is California, with 395,000. All told, the least regulated states are South Dakota, Alaska, Montana, Idaho, and North Dakota, while the most regulated states are California, New York, Illinois, Ohio, and Texas.

Unfortunately, we weren’t able to include Vermont, New Jersey, Arkansas, and Hawaii. Arkansas is the easiest to explain: It has no administrative code, at least not yet. Its state agencies produce regulations, but until this year no one had ever bothered to compile them in one place. Fortunately — perhaps partly in response to RegData — legislation was passed this year to create an official Code of Arkansas Rules by January 2023, so Arkansas’s regulatory landscape will eventually come to light.

That is from James Broughel and Patrick A. McLaughlin, there is more at the link.

Facebook and privacy

Oops, this blog post isn’t about Facebook at all!  Here goes:

Records and interviews show that colleges are building vast repositories of data on prospective students — scanning test scores, Zip codes, high school transcripts, academic interests, Web browsing histories, ethnic backgrounds and household incomes for clues about which students would make the best candidates for admission. At many schools, this data is used to give students a score from 1 to 100, which determines how much attention colleges pay them in the recruiting process.

Admissions consulting companies charge schools tens of thousands of dollars a year to collect and analyze the data of millions of students. In emails reviewed by The Post, employees of Louisville-based Capture Higher Ed urged school administrators to hand over all data they felt comfortable sharing.

“We love data, so the more the merrier,” one of Capture’s consultants wrote in a 2017 email to the admissions director at UW-Stout.

The more the merrier!  And did you know that The New York Times will sell subscriber data about you?

Here is the full article, via the excellent Samir Varma.

The economic effects of private equity buyouts

We examine thousands of U.S. private equity (PE) buyouts from 1980 to 2013, a period that saw huge swings in credit market tightness and GDP growth. Our results show striking, systematic differences in the real-side effects of PE buyouts, depending on buyout type and external conditions. Employment at target firms shrinks 13% over two years in buyouts of publicly listed firms but expands 13% in buyouts of privately held firms, both relative to contemporaneous outcomes at control firms. Labor productivity rises 8% at targets over two years post buyout (again, relative to controls), with large gains for both public-to-private and private-to-private buyouts. Target productivity gains are larger yet for deals executed amidst tight credit conditions. A post-buyout widening of credit spreads or slowdown in GDP growth lowers employment growth at targets and sharply curtails productivity gains in public-to-private and divisional buyouts. Average earnings per worker fall by 1.7% at target firms after buyouts, largely erasing a pre-buyout wage premium relative to controls. Wage effects are also heterogeneous. In these and other respects, the economic effects of private equity vary greatly by buyout type and with external conditions.

That is from a new paper by Steven J. Davis, John Haltiwanger, Kyle Handley, Josh Lerner, Ben Lipsius, and Javier Miranda.  Via John Chamberlain.

California state taxes are too high and that is a problem

Among top-bracket California taxpayers, outward migration and behavioral responses by stayers together eroded 45.2% of the windfall tax revenues from the reform.

That is from a new NBER working paper by Joshua Rauh and Ryan J. Shyux.  Here is the full abstract:

Drawing on the universe of California income tax filings and the variation imposed by a 2012 tax increase of up to 3 percentage points for high-income households, we present new findings about the effects of personal income taxation on household location choice and pre-tax income. First, over and above baseline rates of taxpayer departure from California, an additional 0.8% of the California residential tax filing base whose 2012 income would have been in the new top tax bracket moved out from full-year residency of California in 2013, mostly to states with zero income tax. Second, to identify the impact of the California tax policy shift on the pre-tax earnings of high-income California residents, we use as a control group high-earning out-of-state taxpayers who persistently file as California non-residents. Using a differences-in-differences strategy paired with propensity score matching, we estimate an intensive margin elasticity of 2013 income with respect to the marginal net-of-tax rate of 2.5 to 3.3. Among top-bracket California taxpayers, outward migration and behavioral responses by stayers together eroded 45.2% of the windfall tax revenues from the reform.

You can file this one under Arthur Laffer: “these days definitely underrated.”

The real China shock came to Mexico

Mexican manufacturing job loss induced by competition with China increases cocaine trafficking and violence, particularly in municipalities with transnational criminal organizations. When it becomes more lucrative to traffic drugs because changes in local labor markets lower the opportunity cost of criminal employment, criminal organizations plausibly fight to gain control. The evidence supports a Becker-style model in which the elasticity between legitimate and criminal employment is particularly high where criminal organizations lower illicit job search costs, where the drug trade implies higher pecuniary returns to violent crime, and where unemployment disproportionately affects low-skilled men.

That is from a recent paper by Melissa Dell, Benjamin Feigenberg, Kensuke Teshima, forthcoming in AER: Insights.

Does walkability boost economic mobility?

Intergenerational upward economic mobility—the opportunity for children from poorer households to pull themselves up the economic ladder in adulthood—is a hallmark of a just society. In the United States, there are large regional differences in upward social mobility. The present research examined why it is easier to get ahead in some cities and harder in others. We identified the “walkability” of a city, how easy it is to get things done without a car, as a key factor in determining the upward social mobility of its residents. We 1st identified the relationship between walkability and upward mobility using tax data from approximately 10 million Americans born between 1980 and 1982. We found that this relationship is linked to both economic and psychological factors. Using data from the American Community Survey from over 3.66 million Americans, we showed that residents of walkable cities are less reliant on car ownership for employment and wages, significantly reducing 1 barrier to upward mobility. Additionally, in 2 studies, including 1 preregistered study (1,827 Americans; 1,466 Koreans), we found that people living in more walkable neighborhoods felt a greater sense of belonging to their communities, which is associated with actual changes in individual social class.

Here is the paper by Oishi, S., Koo, M., & Buttrick, N. R., via Anecdotal.

The Wage Penalty to Undocumented Immigration

This paper examines the determinants of the wage penalty experienced by undocumented workers, defined as the wage gap between observationally equivalent legal and undocumented immigrants. Using recently developed methods that impute undocumented status for foreign-born persons sampled in microdata surveys, the study documents a number of empirical findings. Although the unadjusted gap in the log hourly wage between the average undocumented and legal immigrant is very large (over 35%), almost all of this gap disappears once the calculation adjusts for differences in observable socioeconomic characteristics. The wage penalty to undocumented immigration for men was only about 4% in 2016. Nevertheless, there is sizable variation in the wage penalty over the life cycle, across demographic groups, across different legal environments, and across labor markets. The flat age-earnings profiles of undocumented immigrants, created partly by slower occupational mobility, implies a sizable increase in the wage penalty over the life cycle; the wage penalty falls when legal restrictions on the employment of undocumented immigrants are relaxed (as with DACA) and rises when restrictions are tightened (as with E-Verify); and the wage penalty responds to increases in the number of undocumented workers in the labor market, with the wage penalty being higher in those states with larger undocumented populations.

By George Borjas and Hugh Cassidy, via the excellent Kevin Lewis.