On my reading list: Selected papers

Some collected readings for my list. 


Julian Reiss. The Methodology of Positive Economics: Reflections on the Milton Friedman Legacy, ed. Uskali Mäki. Cambridge: Cambridge University Press,  Link.

Pablo D. Fajgelbaum, Pinelopi K. Goldberg, Patrick J. Kennedy and Amit K. Khandelwal. The Return to Protectionism. Link.

Gilbert Cette, Lorraine Koehl, Thomas Philippon. Labor Shares in Some Advanced Economies. Link.

Grace Weishi Gu, Eswar Prasad. New Evidence on Cyclical Variation in Labor Costs in the U.S. Link.

Robert J. Gordon. Friedman and Phelps on the Phillips Curve Viewed from a Half Century's Perspective. Link. 

Andrew B. Hall, Jesse Yoder. Does Homeownership Influence Political Behavior? Evidence from Administrative Data. Link.

Anna Maria Mayda, Giovanni Peri, Walter Steingress. The Political Impact of Immigration: Evidence from the United States. Link.

Patrick Bajari, Victor Chernozhukov, Ali Hortaçsu, Junichi Suzuki. The Impact of Big Data on Firm Performance: An Empirical Investigation. Link. 

Jared Walczak, Tax Trends at the Dawn of 2020. Tax Foundation. Link.

David Neumark, Peter Shirley. The Long-Run Effects of the Earned Income Tax Credit on Women's Earnings. Link.

David Autor, David Dorn, Lawrence F. Katz, Christina Patterson, John Van Reenen. Concentrating on the Fall of the Labor Share. Link.

David Autor, David Dorn, Lawrence F. Katz, Christina Patterson, John Van Reenen. The Fall of the Labor Share and the Rise of Superstar Firms. Link.

Murray Rothbard. Robert Nozick and the Immaculate Conception of the State. Link.

Austan Goolsbee. Public Policy in an AI Economy. NBER. Link. 

Dani Rodrik. What Do Trade Agreements Really Do? Link. 

"The estimates suggest that the shift to Internet sales substantially increased both seller profits and consumer surplus."

The finding from a new NBER working paper by Glenn Ellison and Sara Fisher Ellison titled, "Match Quality, Search, and the Internet Market for Used Book."

Abstract:

This paper examines the effect of the Internet on markets in which match-quality is important, including an analysis of the market for used books.  A model in which sellers of unusual objects wait for high-value buyers to arrive brings out match quality and competition effects through which improved search technologies may increase both price dispersion and social welfare.  A reduced-form empirical analysis finds support for a number of more nuanced predictions of the model in the context of the used book market, exploiting both cross-sectional differences across books and time-series differences in the wake of Amazon's acquisition and incorporation of a large used book marketplace.  The paper develops a framework for structural estimation of a model based on the theory.  The estimates suggest that the shift to Internet sales substantially increased both seller profits and consumer surplus.

When it comes to business data, is Yelp as good as the U.S. Census?

From the paper titled, "Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity," by Edward L. Glaeser, Hyunjin Kim and Michael Luca

Here's the abstract from NBER.

Abstract:

Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of local economic activity at the local level.  However, these statistics typically appear only after multi-year lags, and the public-facing versions are aggregated to the county or ZIP code level. In contrast, crowdsourced data from online platforms such as Yelp are often contemporaneous and geographically finer than official government statistics.  In this paper, we present evidence that Yelp data can complement government surveys by measuring economic activity in close to real time, at a granular level, and at almost any geographic scale.  Changes in the number of businesses and restaurants reviewed on Yelp can predict changes in the number of overall establishments and restaurants in County Business Patterns.  An algorithm using contemporaneous and lagged Yelp data can explain 29.2 percent of the residual variance after accounting for lagged CBP data, in a testing sample not used to generate the algorithm.  The algorithm is more accurate for denser, wealthier, and more educated ZIP codes.

The rise of the machines. What does it mean?

A new working paper from the National Bureau of Economic Research by Erik Brynjolfsson, Daniel Rock, Chad Syverson. Abstract:  

We live in an age of paradox.  Systems using artificial intelligence match or surpass human-level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices.  Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans.  We describe four potential explanations for this clash of expectations and statistics:  false hopes, mismeasurement, redistribution, and implementation lags.  While a case can be made for each, we argue that lags have likely been the biggest contributor to the paradox.  The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely.  More importantly, like other general purpose technologies, their full effects won't be realized until waves of complementary innovations are developed and implemented.  The required adjustment costs, organizational changes, and new skills can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, going forward, national statistics could fail to measure the full benefits of the new technologies and some may even have the wrong sign.

When pot laws are not the same across states, can we expect seepage?

In their new working paper, Benjamin Hansen, Keaton Miller, Caroline Weber ask "How Extensive is Inter-State Diversion of Recreational Marijuana?" Only a small amount they say. 

Abstract:

Despite federal prohibition, recreational marijuana is available to 21% of the United States population.  A chief concern among policy makers across multiple levels of government and political parties is inter-state diversion of marijuana from states with legal markets to others.  We measure this diversion with a natural experiment.  Oregon opened a recreational market on October 1, 2015, next to an existing market in Washington, which opened on July 8, 2014.  Using comprehensive administrative data on the universe of Washington sales, we find Washington retailers along the Oregon border experienced a 41% decline in sales immediately following Oregon's market opening.  Retailers along Washington's borders with Idaho and Canada experienced no such decline.  The decline occurred equally across weekdays and weekends, and was largest among the largest transaction sizes, suggesting diversion, not drug tourism, was to blame. Our estimates suggest that 11.9% of the marijuana sold in Washington was diverted out of the state before Oregon legalized and
7.5% remains diverted today.

A gated copy of the research paper can be found here. 

Economist Dani Rodrik: Populism should not be a surprise

The new Dani Rodrik paper: Populism and the Economics of Globalization

Populism may seem like it has come out of nowhere, but it has been on the rise for a while. I argue that economic history and economic theory both provide ample grounds for anticipating that advanced stages of economic globalization would produce a political backlash. While the backlash may have been predictable, the specific form it took was less so. I distinguish between left-wing and right-wing variants of populism, which differ with respect to the societal cleavages that populist politicians highlight. The first has been predominant in Latin America, and the second in Europe. I argue that these different reactions are related to the relative salience of different types of globalization shocks.

Can the observations of building permit activity explain the stock mr

From a new NBER working paper

Stock volatility during the Great Depression was two to three times
higher than any other period in American financial history.  The period has been labelled a "volatility puzzle" because scholars have been unable to provide a convincing explanation for the dramatic rise in stock volatility (Schwert, 1989).  We investigate the volatility puzzle during the period 1928-1938 using a new series of building permits, a forward-looking measure of economic activity.  Our results suggest that the largest stock volatility spike in American history can be predicted by an increase in the volatility of building permit growth. Markets appear to have factored in a forthcoming economic disaster.

What would building permit activity tell us today?