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Emmanuel Saez


Emmanuel Saez (born 1972) is a French-American economist specializing in , , and . A of at the , where he also directs the Stone Center on Wealth and Income Inequality, Saez has utilized historical tax records to quantify trends in top income shares, revealing sharp increases in concentration among the highest earners since the .
Saez's seminal collaborations, particularly with , produced long-term series on that have shaped global discussions on economic disparity, emphasizing pre-tax market incomes derived from IRS data. His empirical approach highlights how reductions in top marginal tax rates correlated with rising , informing arguments for more progressive taxation, including rates as high as 70-90% on top brackets to optimize revenue without deterring effort, based on elasticity estimates. Saez holds dual , earned a B.A. from in 1994, advanced degrees in Paris, and a Ph.D. from in 1999, before teaching at Harvard and joining in 2002. Among his accolades are the 2009 for contributions under age 40, the 2010 MacArthur Fellowship, election to the in 2023, and the Wihuri International Prize in 2023. Recent works, such as co-authored analyses with on billionaire taxation and U.S. updates, extend his focus to wealth concentration and policy reforms like wealth taxes, though these have sparked debates over measurement conventions—such as excluding government transfers—and potential overemphasis on gross incomes versus post-tax distributions. Saez's research underscores causal links between tax structures and inequality dynamics, privileging data-driven insights amid broader academic tendencies toward interpretive biases in inequality narratives.

Early Life and Education

Early Life

Emmanuel Saez was born on November 26, 1972, in . He spent his childhood in . Saez holds dual citizenship in and the .

Academic Education

Emmanuel Saez earned a B.A. in Mathematics from the in in 1994. The is a prestigious grande known for advanced studies in sciences and humanities, where Saez trained as an agrégé, a competitive qualification for teaching and research in . In 1996, Saez obtained an M.D. in Economics from (Department and Laboratory of Applied and Theoretical Economics) in , a research institution affiliated with leading French academic bodies including the and École des Hautes Études en Sciences Sociales. Saez completed his Ph.D. in Economics at the () in 1999, under the supervision of faculty specializing in . His doctoral dissertation, which earned the National Tax Association's dissertation prize in 1999, focused on taxation and labor supply responses.

Academic Career

Early Positions

Following his PhD in economics from the in 1999, Saez joined as Assistant Professor of Economics, holding the position from July 1999 to June 2002. During this period, his research began focusing on empirical analysis of taxation and , including early papers on optimal income taxation and behavioral responses to tax changes. In the overlapping academic year from July 2001 to June 2002, Saez served as Visiting Assistant Professor of Economics at the University of California, Berkeley, which facilitated his transition to the institution. This visiting role allowed him to engage with Berkeley's economics faculty while completing his commitments at Harvard.

Berkeley Tenure and Leadership Roles

Saez joined the University of California, Berkeley, as a visiting assistant professor of economics from July 2001 to June 2002, overlapping with his assistant professorship at Harvard University. He transitioned to a tenure-track assistant professor position at Berkeley from July 2002 to June 2003. In July 2003, Saez was promoted to associate professor of economics, a rank that typically includes tenure at Berkeley, reflecting recognition of his early contributions to public economics and inequality research. He advanced to full professor in July 2005 and currently holds the Chancellor's Professorship of Tax Policy and Public Finance. In leadership roles, Saez directed the Berkeley Center for Equitable Growth from July 2010 to June 2023, overseeing research on , taxation, and policy interventions. Since July 2023, he has served as director of the James M. and Cathleen D. Stone Center on Wealth and at , focusing on empirical analysis of distribution and redistribution mechanisms. These positions have positioned him to influence interdisciplinary initiatives at the institution, integrating with data-driven .

Research Areas

Income and Wealth Inequality Measurement

Emmanuel Saez's research on primarily utilizes administrative data from individual returns to construct historical series of top shares in the United States. Collaborating with , Saez developed a methodology that defines as comprehensive pre-tax fiscal , encompassing wages, , and realized gains, adjusted for missing variables and underreporting using totals. This approach addresses limitations in household surveys, which often underrepresent top incomes due to top-coding and non-response among high earners. Key findings indicate that the top 1% share rose from approximately 10% in 1980 to 20.2% in 2021, with the top 0.1% share increasing from 3.6% to 8.5% over the same period. Saez extended this framework through the Distributional National Accounts (DINA), co-developed with Piketty and , which reconciles tax data with survey and accounts information to estimate the full distribution of since 1913. The DINA method allocates all components of —such as corporate profits and transfers—across ranks, revealing that the bottom 50% captured only 12.5% of by 2014, down from 20% in 1980, while the top 1% share reached 20%. Recent extensions include real-time inequality tracking using quarterly tax data for provisional estimates, enabling timely analysis of distributional impacts from events like the . For wealth inequality, lacking direct administrative wealth data, Saez and Zucman (2016) employed an income capitalization method, estimating household by dividing reported asset income from tax returns by imputed rates of return derived from aggregate balance sheets. This technique assumes that high- individuals earn supernormal returns on their assets, allowing backward estimation of wealth stocks from flows. Their shows the top 1% wealth share fluctuating between 22% and 28% from 1913 to the 1970s before surging to 32% by 1989 and stabilizing around 35% through 2020, with the top 10% holding 70-75% of total . Updates incorporating revised assumptions on rates of return have refined these estimates, confirming persistent high concentration at the top.

Optimal Taxation and Public Economics

Emmanuel Saez has made significant contributions to optimal taxation theory by deriving formulas for top marginal tax rates using empirical elasticities of , emphasizing that optimal rates depend on behavioral responses such as labor supply, , and compensation bargaining. In a paper, Saez developed simple elasticity-based formulas for optimal schedules, showing that the revenue-maximizing top tax rate is given by \tau = \frac{1}{1 + a e}, where a is the Pareto parameter of the tail and e is the elasticity of with respect to the net-of-tax rate; he argued that low estimated elasticities for top earners (around 0.25-0.5) imply optimal rates exceeding 70%. This approach builds on Mirrlees' framework but incorporates microempirical evidence to challenge favoring flat or low top rates. Collaborating with Peter Diamond, Saez extended this in a 2011 analysis, estimating a revenue-maximizing combined federal, state, and local top marginal rate of 73% under plausible elasticity assumptions, asserting that such rates enhance efficiency by reducing and at the top without substantial if top incomes are highly elastic to pre-tax shares rather than hours worked. Their model highlights that optimal progressivity increases with the social value of redistribution and decreases with stronger Pareto tails in income distributions, supported by U.S. historical data showing limited labor supply responses among top earners. Saez's 2013 work further refines this by modeling three elasticities—labor supply (small for executives), avoidance (shifted to capital or offshore), and compensation rents (where high taxes curb excessive pay)—concluding that optimal top rates remain high (around 50-70%) even accounting for these channels, based on econometric estimates from tax reforms. In broader , Saez's research addresses optimal labor income taxation across the distribution, including subsidies (negative marginal rates) at the bottom to boost participation among low-skill workers, as derived in his contributions to the 2013 Handbook of , where he integrates bunching methods and quasi-experimental evidence from tax changes to estimate elasticities. He has also analyzed tax expenditures, proposing in a 2004 model that optimal treatment involves taxing contributions to favored activities at rates reflecting their social value, balancing private incentives with public goods provision. These frameworks prioritize causal identification from policy variations, such as EITC expansions and capital gains realizations, to inform progressive reforms while acknowledging that long-run elasticities may exceed short-run ones, though Saez maintains empirical support for high top rates given observed low responsiveness.

Behavioral Responses to Policy

Saez's research on behavioral responses to policy emphasizes empirical measurement of how changes influence reported incomes, capturing a broad range of reactions including labor supply adjustments, occupational shifts, , and evasion. Central to this work is the elasticity of (ETI), defined as the percentage change in divided by the percentage change in the net-of- (1 minus the marginal ). In a comprehensive review with Joel Slemrod and Seth Giertz, Saez analyzed from multiple U.S. reforms, estimating an overall ETI of approximately 0.4 for the general population, with higher values (around 0.5-0.7) for top earners. This aggregate figure includes both real behavioral changes, such as reduced work effort, and optimization strategies like shifting or deductions, though Saez notes that real responses—excluding avoidance—are significantly lower, often near zero in short-run estimates. Early contributions include a 2000 study with Jon Gruber using 1979-1990 U.S. tax data, which found an ETI of about 0.4 overall but stressed that the elasticity for broad income measures (excluding narrow tax preferences) was much smaller, implying limited distortion to underlying economic activity from rate hikes. Saez argued that policymakers should prioritize total ETI for revenue forecasting while distinguishing real versus avoidance effects for efficiency assessments, as avoidance responses do not necessarily reduce societal output. For high-income groups, analyses of historical U.S. data from 1960-2000 revealed pronounced responses only among the top 1%, where taxable income elasticities exceeded 0.5 during tax cuts, but with evidence of reversion during subsequent increases, suggesting partial offsetting via enforcement or norms. Saez applied these methods to evaluate specific reforms, such as the 2013 U.S. increase raising the top marginal rate from 35% to 39.6% plus a 3.8% net income . Using IRS data through 2014, he documented modest short-term declines in top reported incomes—about 1-2% for the top 1%—yielding an implied ETI below 0.2, with no significant acceleration in avoidance like charitable deductions or realizations. This low response aligned with prior estimates, indicating that high earners did not substantially alter behavior immediately post-reform, though Saez cautioned that longer horizons might reveal delayed effects. Extending to international contexts, collaborative work on Sweden's examined avoidance via asset reclassification or , estimating a net-of-tax elasticity of 0.14-0.3, which informed debates on taxation's feasibility by quantifying evasion risks without crippling . These findings underpin Saez's policy-oriented models, where low real ETI values support progressive taxation with minimal efficiency costs; for instance, he derived optimal top tax rates exceeding 70% under conservative elasticity assumptions, arguing that behavioral responses are often overstated in opposition to hikes. Critics, including supply-side economists, contend that Saez's estimates underweight long-run real responses like deterrence, but his approaches control for such confounders using quasi-experimental variation from rate discontinuities. Overall, Saez's emphasis on administrative data over surveys enhances reliability, revealing that policy responses are heterogeneous by income level and reform design, with avoidance dominating short-term adjustments.

Awards and Recognition

John Bates Clark Medal

In 2009, Emmanuel Saez received the from the , an award given annually since 2009 (biennially prior) to an American economist under age 40 for significant contributions to economic thought and knowledge. At the time, Saez was 36 years old and a at the . The Association's citation highlighted Saez's definitive contributions to , particularly in bridging theoretical models with empirical analysis to inform policy. His work revitalized optimal theory by connecting abstract policy prescriptions to observable parameters, such as behavioral elasticities, and addressed real-world applications including marginal rates and transfer programs. Saez advanced the measurement of and inequality through innovative datasets, including a seminal collaboration with reconstructing U.S. top shares from 1913 to 1998, revealing a U-shaped with rising concentration at the top in recent decades. He also quantified taxpayers' responses to changes, such as the elasticity of , and examined factors influencing participation in savings plans using quasi-experimental methods. These achievements, detailed in a profile by B. Douglas Bernheim in the Journal of Economic Perspectives, underscored Saez's role in enhancing understanding of taxation's effects on labor supply, savings, and investment, while shaping debates on inequality and . The medal positioned Saez among elite economists, joining prior UC recipients like Jorgenson (1971) and (1975).

MacArthur Fellowship

In 2010, Emmanuel Saez was named a MacArthur Fellow by the John D. and Catherine T. MacArthur Foundation as part of its class of , with the announcement made on September 28. The fellowship provides recipients with $500,000 disbursed over five years without any stipulations or reporting requirements, designed to support unrestricted creative and intellectual pursuits. At age 37, Saez was recognized for his innovative approaches to , particularly his integration of empirical , behavioral experiments, and theoretical frameworks to examine how tax policies influence and taxpayer behavior. The foundation cited Saez's documentation of historical trends in U.S. , including a U-shaped pattern of concentration among top earners over the twentieth century, which highlighted rising disparities linked to policy shifts. His research also quantified elasticities of in response to marginal changes, informing debates on design and revenue maximization under behavioral constraints. Experimental contributions included evidence that simplified participation incentives—such as automatic enrollment with options—significantly increase savings rates, challenging traditional assumptions about individual in financial decisions. Saez's selection underscored the fellowship's emphasis on interdisciplinary impact, bridging with empirical measurement and experimentation at a time when his prior work, including collaborations on top income shares using tax data, had gained prominence following his 2009 . As the E. Morris Cox Professor of at the , he exemplified the program's focus on early-career scholars demonstrating exceptional originality in addressing societal challenges like .

Policy Influence

Contributions to Tax Policy Debates

Saez has advanced discussions through empirical analyses of behavioral responses to marginal tax rates, particularly emphasizing low elasticities among top earners. In collaboration with , he estimated in 2013 that the revenue-maximizing combined federal, state, and local top marginal rate stands at approximately 73%, based on historical data showing limited disincentives to labor supply and earnings at high tax levels post-World War II. This finding challenges supply-side arguments for low top rates, positing that optimal rates could exceed current levels without substantial economic distortion if avoidance channels are addressed. Extending this framework, Saez co-authored a 2013 model incorporating three elasticities—labor supply, , and compensation —demonstrating that top rates could reach 50-70% or higher under realistic parameters derived from U.S. data, where top incomes respond more to avoidance than effort reduction. These results, grounded in administrative records, have informed debates on reversing cuts, arguing that higher rates enhance and without the predicted collapse in high-end earnings observed under lower rates. Critics, however, contend that such models undervalue long-term incentives for and , potentially overstating feasible rates given of greater elasticity in entrepreneurial activity. Saez's joint work with on wealth taxation has shaped progressive reform proposals, including scoring Elizabeth Warren's 2019 plan for a 2% annual on fortunes over $50 million, projecting $2.75 trillion in revenue over a decade to fund social programs without significant . Their 2019 book The Triumph of Injustice documents how effective rates on the top 400 earners fell to 23% by 2018—below middle-class levels—due to deductions and offshore evasion, advocating annual wealth taxes and billionaire minimum taxes to restore progressivity. This analysis, leveraging IRS data, counters claims of inherent system progressivity by highlighting pre-tax income concentration and avoidance, though detractors argue it overlooks savings reductions and administrative burdens. In broader debates, Saez has underscored tax policy's role in inequality trends, co-authoring with a 2007 study showing U.S. federal taxes were most progressive in the 1950s-1970s under 70-90% top rates, correlating with compressed income shares, and less so post-1980 cuts amid rising top incomes. His 2012 Journal of Economic Perspectives piece synthesizes theory to support earnings-based progressivity, rejecting flat taxes as inefficient for redistribution given empirical Pareto tail distributions of high incomes. These contributions have influenced Democratic platforms, yet remain contested in academic circles for potentially underweighting dynamic growth effects, as evidenced by simulations showing lower optimal rates when broader general impacts are modeled.

Advocacy for Progressive Taxation

Saez has argued that optimal tax theory supports highly progressive income taxation, particularly at the top end, to maximize social welfare by balancing revenue needs with limited behavioral distortions from high earners. In collaboration with , he derived formulas for the optimal top marginal tax rate, given by T = \frac{1}{1 + a e}, where a reflects the social marginal value of income for top earners (often modeled via the Pareto parameter of the ) and e is the elasticity of with respect to the net-of-tax rate. Empirical estimates of e around 0.2–0.4 for top earners imply optimal rates of 70–80% on incomes above approximately $500,000 (in 2011 dollars), combining federal, state, and local taxes, as these rates minimize efficiency losses while enabling redistribution. This advocacy rests on evidence that top incomes exhibit low responsiveness to tax changes, with elasticities primarily driven by avoidance rather than reductions in effort or hours worked. Saez's of historical U.S. data shows that pre-1980s high top rates (often exceeding 70%) did not substantially deter high , and post-2013 tax increases temporarily depressed top shares without long-term harm to growth. He recommends phasing in high marginal rates on labor for top brackets, complemented by subsidies for lower incomes, rejecting flat or low top rates as inefficient for addressing concentrated at the apex. Extending this to wealth, Saez co-authored with proposals for a progressive annual targeting extreme concentrations, with a moderate schedule of 3% on net above $1 billion and a more aggressive 10% rate at that threshold. Such a , applied since 1982, could have halved the share of the top 400 U.S. families by 2018, generating $100–200 billion annually in revenue for public goods while curbing dynastic accumulation. Feasibility is supported by administrative precedents in and U.S. estate mechanisms, with arguments emphasizing that 's immobility reduces evasion risks compared to income. In public discourse, Saez has advocated raising average effective tax rates on top earners to around 60%, aligning with historical norms before the , to counteract rising pretax inequality driven by rents and rather than . These positions inform policy debates, positing that taxation enhances without the deadweight losses assumed in supply-side critiques, provided elasticities remain empirically grounded.

Methodological Debates and Criticisms

Critiques of Inequality Data Methods

Critics have argued that Saez's methods for estimating top income shares, primarily derived from IRS tax return data, overestimate inequality by failing to adequately adjust for underreporting, tax avoidance, and changes in tax compliance over time. For instance, Saez's series often extrapolates top incomes using Pareto based on observed tax data, but this approach assumes stable reporting behavior, which critics contend ignores shifts induced by changes, such as the that encouraged income realization. Economists Gerald Auten and David Splinter, analyzing comprehensive tax data including adjustments for evasion and non-filers, estimate that the top 1% income share rose from about 10% in 1980 to 14% by 2014, substantially less than the 20+ percentage points implied by Saez's unadjusted figures. Their methodology incorporates corrections for undercounted lower-income filers and pass-through business income reallocation, revealing that Saez's reliance on gross tax units without such adjustments inflates concentration at the top. Another key critique centers on Saez's predominant use of pre-tax, pre-transfer income definitions, which exclude the equalizing effects of government taxes and benefits that have expanded significantly since the . Saez acknowledges post-tax variants but emphasizes pre-tax shares in much of his public work, arguing they better capture market outcomes; however, researchers note this omits how progressive taxation and programs like Social Security and have redistributed up to 20-30% of national income, flattening post-tax distributions. For example, when transfers are included, the bottom quintile's income growth appears robust, contrasting Saez's focus on stagnant middle-class pre-tax gains. Critics like Scott Winship contend this selective framing misleads by prioritizing fiscal incidence over comprehensive household resources, potentially exaggerating perceived stagnation. Historical estimates in Saez's datasets have drawn scrutiny for data imputation errors and inconsistent sourcing, particularly pre-1940s, where sparse tax records lead to unreliable extrapolations. Phillip Magness has documented how Saez and coauthor mishandle the denominator for total —often derived from —by double-counting corporate retentions or excluding untaxed labor income, artificially boosting top shares by 2-5 percentage points in early 20th-century figures. Post-1980s, similar issues arise from unadjusted surges in realized capital gains during low-tax periods, which Saez treats as ordinary income spikes without normalizing for behavioral responses. These methodological choices, while innovative for capturing high-end dynamics, contrast with survey-based measures like the , which show milder trends when harmonized across datasets.

Responses and Counterarguments

Saez, along with Thomas Piketty and Gabriel Zucman, has defended their methodology for estimating top income shares by emphasizing the consistency of tax data with national accounts and critiquing alternative imputations for underreported income as implausible. In response to Auten and Splinter's (2023) adjustments, which allocate the majority of underreported income to the bottom 90% and result in minimal changes to top 1% shares (from 9% in 1960 to about 10% in 2019), Piketty, Saez, and Zucman (2024) argue that such allocations contradict IRS audit data showing higher underreporting rates among high-income taxpayers, particularly through mechanisms like offshore accounts and pass-through businesses. They contend that assuming over 70% of missing income accrues to lower earners ignores evidence from randomized audits, where noncompliance rates exceed 20% for the top 1% versus under 5% for the bottom 50%. Regarding the distribution of tax-exempt income, such as retirement savings, Saez and Zucman (2020) previously highlighted inconsistencies in Auten and Splinter's (2019) earlier estimates, noting that their apportionment of and balances fails to align with administrative data from the and , which indicate disproportionate holdings by top earners. Piketty, Saez, and Zucman (2024) reiterate that proper imputation, drawing from flow-of-funds data, supports their finding of rising top shares, with the top 1% capturing 15% of after-tax national income by 2019 under post-tax adjustments prorated by shares. This approach, they assert, better reflects fiscal incidence than alternatives that underweight transfers to the poor or exemptions benefiting the wealthy. In earlier rebuttals, such as to Reynolds (2006), Saez and Piketty (2006) addressed claims of methodological overstatement by clarifying that their pre-tax income definitions exclude certain fiscal residuals but capture realized capital gains and entrepreneurial income comprehensively via , yielding trends corroborated by independent sources like undercounts for top earners. Saez maintains that critiques often stem from differing unit-of-observation choices (e.g., tax units versus households) or incomplete integration of administrative , but their series' upward revisions for recent years—driven by updated IRS statistics—reinforce the core trend of increasing concentration since the . Despite ongoing disputes, Saez's framework has influenced distributions, which partially adopt -based imputations for proprietor income.

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