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Monetary Policy, Redistribution, and Risk Premia
Rohan Kekre, University of Chicago and NBER
Moritz Lenel, Princeton University
Francesco Bianchi, Duke University and NBER

Kekre and Lenel study the transmission of monetary policy through risk premia in a heterogeneous agent New Keynesian environment. Heterogeneity in households' marginal propensity to take risk (MPR) summarizes differences in portfolio choice on the margin. An unexpected reduction in the nominal interest rate redistributes to households with high MPRs, lowering risk premia and amplifying the stimulus to the real economy. Quantitatively, this mechanism rationalizes the role of news about future excess returns in driving the stock market response to monetary policy shocks.


This paper was distributed as Working Paper 28869, where an updated version may be available.

Immigration, Innovation, and Growth
Konrad B. Burchardi, IIES, Stockholm University
Thomas Chaney, Sciences Po
Tarek Alexander Hassan, Boston University and NBER
Lisa Tarquinio, University of Western Ontario
Stephen J. Terry, Boston University and NBER
Michael Peters, Yale University and NBER

Building upon endogenous growth theory, Burchardi, Chaney, Hassan, Tarquinio, and Terry show a causal impact of immigration on innovation and dynamism in US counties. In order to identify the causal impact of immigration, they use 130 years of detailed data on migrations from foreign countries to US counties to isolate quasi-random variation in the ancestry composition of US counties that results purely from the interaction of two forces: (i) changes over time in the relative attractiveness of different destinations within the US to the average migrant arriving at the time and (ii) the staggered timing of arrival of migrants from different origin countries. The researchers then use this plausibly exogenous variation in ancestry composition to predict the total number of migrants flowing into each US county in recent decades. They show four main results. First, immigration has a positive impact on innovation, measured by patenting of local firms. Second, immigration has a positive impact on measures of local dynamism, as endogenous growth theory predicts. Third, the positive impact of immigration on innovation percolates over space, but spatial spillovers quickly die with distance. Fourth, the impact of immigration on innovation is stronger for more educated migrants.


This paper was distributed as Working Paper 27075, where an updated version may be available.

Firm Wages in a Frictional Labor Market
Leena Rudanko, Federal Reserve Bank of Philadelphia
Christopher K. Huckfeldt, Cornell University

Rudanko studies a labor market with directed search, where multi-worker firms follow a firm wage policy: They pay equally productive workers the same. The policy reduces wages, due to the influence of firms' existing workers on their wage setting problem, increasing the profitability of hiring. It also introduces a time-inconsistency into the dynamic firm problem, because firms face a less elastic labor supply in the short run. To consider outcomes when firms reoptimize each period, Rudanko studies Markov perfect equilibria, proposing a tractable solution approach based on standard Euler equations. In two applications, they first show that firm wages dampen wage variation over the business cycle, amplifying that in unemployment, with quantitatively significant effects. Second, they show that firm wage firms may find it profitable to fix wages for a period of time, and that an equilibrium with fixed wages can be good for worker welfare, despite added volatility in the labor market.

Anatomy of Lifetime Earnings Inequality: Heterogeneity in Job Ladder Risk vs. Human Capital
Fatih Karahan, Federal Reserve Bank of New York
Serdar Ozkan, University of Toronto
Jae Song, Social Security Administration
Richard Rogerson, Princeton University and NBER

Karahan, Ozkan, and Song study the determinants of lifetime earnings (LE) inequality in the US using administrative balanced panel data between the ages of 25 and 55 by focusing on the roles of job ladder dynamics and on-the-job learning. The researchers first document that lower LE workers change jobs more often, mainly driven by higher non-employment risk. Second, average annual earnings growth for job stayers is surprisingly similar at around 2% in the bottom two thirds of the LE distribution, whereas for job switchers it rises almost linearly from zero at the bottom to around 4% at the 90th percentile. Third, top LE workers enjoy high earnings growth regardless of job switching. To interpret these facts, the researchers estimate a life-cycle job ladder model with on-the-job learning featuring ex-ante heterogeneity in learning ability as well as in job ladder risk — job loss, job finding, and contact rates. The researchers find that learning ability is Pareto distributed and explains almost all earnings growth heterogeneity above the median LE — the main driver of LE inequality. As for below the median LE, they find that 80% of lifetime earnings growth differences would vanish if workers had the same ex-ante job ladder risk. The researchers validate this large ex-ante heterogeneity in job-ladder risk with direct evidence from survey data.

Top Wealth in the United States: New Estimates and Implications for Taxing the Rich
Matthew Smith, Department of the Treasury
Owen M. Zidar, Princeton University and NBER
Eric Zwick, University of Chicago and NBER
Ellen McGrattan, University of Minnesota and NBER

Smith, Zidar, and Zwick use administrative tax data to estimate top wealth in the United States. They build on the capitalization approach in Saez and Zucman (2016) while accounting for heterogeneity within asset classes when mapping income flows to wealth. The approach reduces bias in wealth estimates because wealth and rates of return are correlated. Overall, wealth is very concentrated: the top 1% holds as much wealth as the bottom 90%. However, the "P90-99" class holds more wealth than either group after accounting for heterogeneity. Relative to a top 0.1% wealth share of more than 20% under equal returns, the researchers estimate a top 0.1% wealth share of [15%] and find that the rise since 1980 in top wealth shares falls by [half]. Top portfolios depend less on fixed income and public equity, depend more on private equity and housing, and more closely match the composition reported in the SCF and estate tax returns. The researchers' adjustments reduce mechanical revenue estimates from a wealth tax and top capital income shares in distributional national accounts, which depend on well-measured estimates of top wealth. Though the capitalization approach has advantages over other methods of estimating top wealth, the researchers emphasize that considerable uncertainty remains inherent to the approach by showing the sensitivity of estimates to different assumptions.

How EU Markets Became More Competitive Than US Markets: A Study of Institutional Drift
Germán Gutiérrez, New York University
Thomas Philippon, New York University and NBER
Nicolas Crouzet, Northwestern University

Many European markets today appear more competitive than their American counterparts. Gutiérrez and Philippon document this surprising reversal of history and propose an explanation. Their model of political support predicts that a supranational regulator enforces free markets beyond the preferences of any individual country. The researchers find that European institutions are indeed more independent and enforce competition more strongly than any individual country ever did. Countries with ex-ante weaker institutions benefit more from the delegation of competition policy to the EU level. The model also explains why political and lobbying expenditures have increased more in America than in Europe.


This paper was distributed as Working Paper 24700, where an updated version may be available.


Divya Bhagia, Boston College
Carter Bryson, Boston College
Nicolas Caramp, University of California at Davis
Eva Carceles-Poveda, Stony Brook University
Gastón Chaumont, University of Rochester
Fernando Cirelli, New York University
William L. Gamber, New York University
Elisa Giannone, Pennsylvania State University
Sebastian Graves, New York University
Alexey Khazanov, Boston College
Eunmi Ko, Rochester Institute of Technology
Jonathan McCarthy, Federal Reserve Bank of New York
Indrajit Mitra, Federal Reserve Bank of Atlanta
Abdoulaye Ndiaye, New York University
Kristoffer Nimark, Cornell University
Jonathan Payne, Princeton University
Tom Phelan, Federal Reserve Bank of Cleveland
Roxane Spitznagel, Yale University
Daniel Stackman, New York University
Joshua Weiss, New York University
Liukun Wu, Princeton University
Fangyuan Yi, Princeton University

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