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January 6, 2022

The Effect of Monetary and Fiscal Policy on Inequality

How does accounting for households’ heterogeneityand in particular inequality in income and wealth—change our approach to macroeconomics? What are the effects of monetary and fiscal policy on inequality, and what did we learn in this regard from the COVID-19 pandemic? What are the implications of inequality for the transmission of monetary policy, and its ability to stabilize the economy? These are some of the questions that were debated at a recent symposium on “Heterogeneity in Macroeconomics: Implications for Policy” organized by the new Applied Macroeconomics and Econometrics Center (AMEC) of the New York Fed on November 12.

The Symposium

The Symposium brought together a distinguished panel of researchers from academia and policy institutions—some of whom have written foundational works in the growing literature on heterogeneity in macroeconomicsfor an open and lively discussion on these topics. The conversation featured four sessions, two in the morning and two in the afternoon, which are outlined in the agenda (including links to all the presentations). A recording of the proceedings is also available on the Symposium website.

The morning sessions, which we cover in this post, explored the effects of monetary and fiscal policy on inequality. The afternoon sessions, covered in tomorrow’s post, examined the effect of inequality on the transmission of monetary and fiscal policy, and the normative lessons of this literature for monetary policy. This discussion was timely given the relevance of these topics in current policy debates, both in the United States and around the world. In the U.S., for example, the active debates on the macroeconomic impact of redistributive fiscal policy (see this Liberty Street Economics post on “excess savings”) and of the Federal Reserve’s new flexible average inflation targeting framework are in fact very much centered on questions of redistribution and of the uneven effects of policy on wages and unemployment.

Inequality, Fiscal Policy, and the COVID-19 Recession

The first session focused on understanding how recessions affect economic inequality, the policy tools that can mitigate these effects, and whether the COVID-19 experience taught us something new about the efficacy of these tools in providing support to those who need it.

Claudia Sahm of Stay-at-Home Macro (SAHM) Consulting and the Jain Family Institute discussed whether the fiscal policies that were employed in response to COVID-19 helped to mitigate economic hardship for those that were particularly marginalized by the epidemic. She argued that the answer was a resounding yes, but that, even with that help, the hardship was still greater for some, such as low-wage workers and people in minority groups. While the U.S. government’s COVID response could be described as going “big, … broad, and … fast,” there remains, Sahm said, room for improvement.

In particular, Sahm noted that the stimulus checks, which were sent out fairly rapidly and to nearly everyone excluding those in the top 20 percent of the income distribution, supported families with less income pre-COVID relatively more—therefore, this form of fiscal policy did help to mitigate some rise in inequality. Nonetheless, inequality was still present in many dimensions, none more so than in the death rate from COVID-19, where minorities suffered to a much greater extent, she said. The inequities can further be seen in the labor market, where the recovery in employment is thus far less complete for people of color. For example, as of October 2021, the employment rates for Blacks and Hispanics were 3 percentage points below their pre-COVID levels, while the employment rate for whites was 2 percentage points below its pre-COVID level. Sahm also noted that much of the inequality is structural, pre-dating COVID. In this sense, fiscal policies during the pandemic were fighting an uphill battle; so while they were partially successful, inequities remained.

Finally, Sahm gave several policy prescriptions for the future. First, she argued that we need to improve our existing automatic stabilizers such as the unemployment insurance (UI) system, which had difficulty reaching even those that were eligible. Second, she advocated introducing new automatic stabilizers like stimulus checks, with disbursement tied to economic indicators rather than reliant on the political process.

Peter Ganong of the University of Chicago focused on the UI system during the pandemic, noting that while there were other support programs (economic impact payments and the paycheck protection program, for example), UI was arguably the most able to target those in need.

Ganong noted that the COVID recession featured an unprecedented expansion of UI. First, there was an introduction of sizeable UI supplements, and second, eligibility was expanded. In terms of the supplements, Ganong pointed out that, while the stated goal of the legislators was to replace 100 percent of lost income, relative to that goal, legislators overshot, providing many with more than a 100 percent replacement rate. The UI supplements were therefore very progressive in that the replacement rate for those at the lower end of the (pre-displacement) income distribution was above 100 percent, while for those at the higher end of the distribution the replacement rate was less than 100 percent.

What were the effects of these payments on spending and job-finding rates for recipients? Using data from JPMorgan Chase Institute and the parent bank’s customers, Ganong showed that that the UI supplements increased spending and reduced the job-finding rate among recipients. The spending effects were much larger than previous estimates for the spending effects of UI, while the job-finding effects were six times smaller. In this sense, the supplements were largely a success, but the analysis helps underscore the fact that there are still issues that UI cannot fix, including the duration dependence in unemployment—that is, the fact that those who are unemployed longer have lower job-finding rates.

New York Fed President and CEO John Williams opened the discussion. His first question focused on the purpose of the stimulus checks in the COVID recession relative to prior recessions: was the focus on measuring the marginal propensity to consume (MPC) out of the checks misplaced, given that their intended purpose was primarily relief rather than a way to stimulate aggregate demand?

Sahm noted that, even during the COVID episode, stimulus checks both provided relief and stimulated consumption. She noted that those at the bottom 20 percent of the income distribution use 80 percent of their spending on necessities. Relatedly, Ganong noted that the MPC is still a relevant number because it measures both actual consumption out of the checks, as well as the need to consume out of the check, that is, those who have high MPCs are those who have a high marginal utility of consumption.

Williams also asked about the current degree of excess savings in the economy, noting that we do not know how it is distributed across households, and how the panelists viewed the propensity to consume out of that wealth over the next few months. Ganong pointed out that data from JPMorgan Chase account holders through July 2021 showed that the liquid asset balances for those in the bottom income quartile are up by 70 percent relative to their pre-pandemic levels, indicating that indeed even those at the bottom were able to save some of the transfers they received. Sahm said it is unlikely that these savings will deliver large consumption booms in the future since the MPC out of wealth is small, though she admitted that this issue is still an open question.

Finally, an audience member asked about other policy interventions such as those in Europe, and how they compare to those that were in the United States. For example, furlough policies and wage subsidies for those on furlough were much more heavily used in Europe relative to the United States. Would those have been a better solution relative to UI and stimulus checks? Sahm agreed that the so-called German model may be a better one, since it prevents individuals from entering long-term unemployment. Ganong had noted that entering long-term unemployment has the negative feature of duration dependence, that is, the longer the unemployment, the harder it is to find employment. In this regard, furlough programs would be able to prevent this experience.

How Does Monetary Policy Impact Inequality?

The second session focused on the impact of accommodative fiscal and especially monetary policy on the distribution of income and wealth. It asked whether running the economy “hot” for an extended time reduces inequality and improves outcomes disproportionally for disadvantaged groups or for low-income households, and about the effects of unconventional monetary policy (in particular, quantitative easing, or QE) on inequality.

Gianluca Violante from Princeton University addressed both questions from the perspective of quantitative Heterogeneous Agent New Keynesian (also known as HANK) models, which take into account distributional issues as well as the fact that households are not perfectly able to share risk with one another. Violante pointed out that the effects of QE on inequality are ambiguous. While on the one hand QE tends to increase the value of assets, thereby increasing inequality as assets are mostly held by rich people, it also lowers the cost of long-term borrowing, such as mortgages, favoring the middle class. Most important perhaps, unconventional policy is often the only option left to central banks to fight recessions when interest rates hit the zero lower bound. And recessions represent a “double whammy” for low income, less educated, and more disadvantaged households, as he argues in a paper with Heathcote and Perri.

In recessions, low-skilled workers are disproportionately likely to experience unemployment, which further reduces skills. In the presence of skill-biased technological change (that is, a change that works against low-skilled workers), a low-skilled individual may give up searching for a job, leading to an increase in non-participation and to a persistent gap in earnings relative to high-skilled workers. Violante then discussed ongoing work with Felipe Alves where they build on this literature to argue that policies such as average inflation targeting—which involve running the economy hot during expansions to compensate for the lower inflation during recessions—may have beneficial effects on the income distribution. This is because workers who lost their jobs in the recession get hired back during booms, in spite of having lost skills, and manage to regain some of those skills while being employed—a development that can result in persistently higher earnings for low-income households.

Stephanie Aaronson of the Brookings Institution then discussed what the notion of a hot economy entails. She highlighted how little agreement there is in the profession regarding this concept, especially given the uncertainty surrounding the measurement of the natural rate of unemployment, u*. She then pointed out that for more marginalized groups, such as Blacks and Hispanics, both the level of unemployment and its cyclicality are higher, suggesting that these workers benefit more from a tighter labor market. Borrowing from her work with Barnes and Edelberg and Daly, Wascher, and Wilcox, Aaronson showed that a hot economy (as measured by the unemployment rate being lower than u*) does help to reduce the unemployment gap between Black and Hispanic men and women with respect to their white counterparts. This finding does not apply to all disadvantaged groups, however, such as men with less than a college degree. In terms of income inequality, the effects of running the economy hot are even less clear, she added. This is partly because the composition of income across cohorts differs: high-income households receive a substantial fraction of their earnings from financial and business incomes, which tend to be very procyclical, while low-income households are more reliant on transfer income, which is mostly countercyclical.

Finally, Aaronson touched on inflation, which is a potential implication of running the economy hot, as the U.S. economy is currently witnessing. She emphasized that inflation has important redistributive consequences, both because low-income households tend to be borrowers and because recent research argues that their consumption basket may be more sensitive to inflation than that of higher-income households. In terms of implications for monetary policy, Aaronson concluded that stabilizing fluctuations in economic activity, and in particular avoiding recessions, ought to be a primary goal of policy given that recessions tend to disproportionally hurt marginalized groups—a message very much in accordance with Violante’s conclusions.

After the presentations, Williams opened the discussion by asking how we tell apart the cycle and the trend in analyzing inequality, especially because the phases of the business cycle have become longer over time. Aaronson replied that indeed distinguishing between the cyclical and structural sources of inequality is critical, as monetary policy may have limited efficacy against the latter, which should be the purview of fiscal policy. Violante agreed that there is solid evidence that technological changes and globalization are the main sources of the increase in inequality over the past decades, and these sources have little to do with monetary policy. However, as mentioned above, there are subtle interactions between the cycle and the trend where stabilization policies can play an important role. Another participant’s question further pushed on this point and asked Aaronson to what extent macro conditions interact with structural sources of inequality—for instance, employers may find it costlier to discriminate when the labor market is tight. Aaronson concurred and thought that this interaction was most likely one of the mechanisms behind the effect of a hot economy on unemployment gaps between Black and Hispanic and white workers, which she discussed earlier.

After the morning sessions, Williams gave a few remarks on the importance of heterogeneity for monetary policy analysis. Anticipating some of the discussion of the afternoon sessions, he highlighted the extent to which heterogeneity across sectors and households has been essential in analyzing the dynamics of the macroeconomy during the COVID-19 pandemic—especially the behavior of labor force participation, quits, and inflation. He mentioned that appreciating the correlation between health, job loss, lack of financial security, and access to credit is key to understanding the events since 2020, especially for communities of color and low-income households, and for deciding what needs to be done in terms of policy. Williams emphasized that the Fed explicitly recognizes heterogeneity in its reference to broad and inclusive employment goals. A discussion followed Williams’ remarks during which a number of issues were raised, such as the possible long-term effects of monetary policy, the definition of maximum employment in the Fed’s mandate, the heterogeneous costs of inflation and climate change, and the political economy of central banking.

The bottom line from the morning sessions was that both fiscal and monetary policy have meaningful effects on inequality. In light of this evidence, how should policy be conducted? This question was the topic of the afternoon sessions, discussed in the forthcoming companion post.

Marco Del Negro is a vice president in the Federal Reserve Bank of New York’s Research and Statistics Group.

Keshav Dogra is a senior economist in the Bank’s Research and Statistics Group.

Laura Pilossoph is a senior economist in the Bank’s Research and Statistics Group.

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

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