Can Government Demand Stimulate Private Investment? Evidence from U.S. Federal Procurement
Shafik Hebous & Tom Zimmermann
Journal of Monetary Economics, forthcoming
Demand shocks lower firm financing premiums by increasing the present value of cash-flow, thereby easing firm financing constraints. We study the effects of unanticipated federal spending shocks on firm investment in the United States using a novel panel dataset that combines federal procurement contracts with key financial firm-level information. Consistent with the financial accelerator model, our results suggest that 1 dollar of federal purchases increases capital investment of financially constrained firms by 10 to 13 cents over a horizon of 4 quarters, but has no effect on investment of unconstrained firms.
The Young, the Old, and the Government: Demographics and Fiscal Multipliers
Henrique Basso & Omar Rachedi
American Economic Journal: Macroeconomics, forthcoming
We document that government spending multipliers depend on the population age structure. Using the variation in military spending and birth rates across U.S. states, we show that the local fiscal multiplier is 1.5 and increases with the population share of young people, implying multipliers of 1.1-1.9 in the inter-quartile range. A parsimonious life-cycle open-economy New Keynesian model with credit market imperfections and age-specific differences in labor supply and demand explains 87% of the relationship between local multipliers and demographics. The model implies that the U.S. population aging between 1980 and 2015 caused a 38% drop in national government spending multipliers.
Designing, not Checking, for Policy Robustness: An Example with Optimal Taxation
Benjamin Lockwood, Afras Sial & Matthew Weinzierl
NBER Working Paper, November 2020
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness — for the purposes of policymaking and evaluation — is to design policy that takes these ranges into account. We modify the standard optimal income tax model to include the policymaker’s subjective uncertainty over parameter values, and we characterize robust optimal policy as that which maximizes expected social welfare. After calibrating uncertainty over the elasticity of taxable income from past empirical work and novel survey data on economists’ beliefs, we compare the implied robust optimal marginal tax rates to the alternative benchmark policy based on the best point estimates of relevant parameters. Our results suggest that robust optimal marginal tax rates are typically more progressive than in benchmark analyses, raising top marginal tax rates by between 5 and 7 percentage points, and generating modest expected welfare gains.
Better Statistics, Better Economic Policies?
Johannes Binswanger & Manuel Oechslin
European Economic Review, forthcoming
More and more economic transactions leave a “digital footprint”. This trend opens unprecedented opportunities for improving economic statistics and underpins demands to give statistical agencies far-reaching access to private-sector data. We analyze the consequences of better economic statistics in a political-agency framework that includes fundamental uncertainty about the impact of potentially welfare-enhancing reforms. We demonstrate that improvements in economic statistics can inhibit — rather than stimulate — reform attempts. With better statistics, the government is less likely to receive the “benefit of the doubt” if the numbers suggest its past reforms are failing. Reforms therefore come with a higher risk of electoral losses, implying that the government has stronger incentives to preserve the status quo. We identify political environments that are particularly vulnerable to this mechanism and contribute to the debate on private-sector data access.
The impact of COVID-19 on attitudes toward poverty and inequality
Dylan Wiwad et al.
Journal of Experimental Social Psychology, forthcoming
The novel Coronavirus that spread around the world in early 2020 triggered a global pandemic and economic downturn that affected nearly everyone. Yet the crisis had a disproportionate impact on the poor and revealed how easily working-class individuals' financial security can be destabilised by factors beyond personal control. In a pre-registered longitudinal study of Americans (N = 233) spanning April 2019 to May 2020, we tested whether the pandemic altered beliefs about the extent to which poverty is caused by external forces and internal dispositions and support for economic inequality. Over this timespan, participants revealed a shift in their attributions for poverty, reporting that poverty is more strongly impacted by external-situational causes and less by internal-dispositional causes. However, we did not detect an overall mean-level change in opposition to inequality or support for government intervention. Instead, only for those who most strongly recognized the negative impact of COVID-19 did changes in poverty attributions translate to decreased support for inequality, and increased support for government intervention to help the poor.
Alex Rees-Jones & Dmitry Taubinsky
Review of Economic Studies, October 2020, Pages 2399–2438
What mental models do individuals use to approximate their tax schedule? Using incentivized forecasts of the U.S. Federal income tax schedule, we estimate the prevalence of the “schmeduling” heuristics for constructing mental representations of nonlinear incentive schemes. We find evidence of widespread reliance on the “ironing” heuristic, which linearizes the tax schedule using one’s average tax rate. In our preferred specification, 43% of the population irons. We find no evidence of reliance on the “spotlighting” heuristic, which linearizes the tax schedule using one’s marginal tax rate. We show that the presence of ironing rationalizes a number of empirical patterns in individuals’ perceptions of tax liability across the income distribution. Furthermore, while our empirical framework accommodates a rich class of other misperceptions, we find that a simple model including only ironers and correct forecasters accurately predicts average underestimation of marginal tax rates. We replicate our finding of prevalent ironing, and a lack of other systematic misperceptions, in a controlled experiment that studies real-stakes decisions across exogenously varied tax schedules. To illustrate the policy relevance of the ironing heuristic, we show that it augments the benefits of progressive taxation in a standard model of earnings choice. We quantify these benefits in a calibrated model of the U.S. tax system.
In the Nick of Time: Performance-Based Compensation and Proactive Responses to the Tax Cuts and Jobs Act
Jon Durrant, James Jianxin Gong & Jennifer Howard
Journal of Management Accounting Research, forthcoming
The Tax Cuts and Jobs Act of 2017 (TCJA) introduced two major changes that may influence the structure of executive compensation: (1) reducing corporate tax rates from 35 to 21 percent and (2) eliminating the performance-based pay exception in Section 162(m). These changes provide incentives to maximize deductible compensation expense in 2017, before the TCJA goes into effect. Therefore, we predict performance-based compensation to increase more in 2017 relative to prior years. Consistent with our expectation, we find that the increase in CEO bonus and stock option compensation is significantly greater in 2017. Our difference-in-difference results are consistent with the tax rate reduction driving the bonus increase and the repeal of the performance-based exception leading to the increase in CEO stock options. The TCJA also changed the definition of covered employees to include the CFO. We find weak evidence for abnormal increases in CFO performance-based compensation. Additional analyses indicate firms facing stronger tax incentives drive our results. Overall, our findings suggest that firms’ responded to the TCJA in the period before it was effective.
Non‐linear effects of government spending shocks in the US. Evidence from state‐level data
Haroon Mumtaz & Laura Sunder‐Plassmann
Journal of Applied Econometrics, forthcoming
This paper uses state‐level data to estimate the effect of government spending shocks during expansions and recessions. By employing a mixed‐frequency framework, we are able to include a long span of annual state‐level government spending data in our non‐linear quarterly panel VAR model. We find evidence that for the average state the fiscal multiplier is larger during recessions. However, there is substantial heterogeneity across the cross‐section. The degree of non‐linearity in the effect of spending shocks is larger in states that are subject to a higher degree of financial frictions. In contrast states with a prevalence of manufacturing, mining and agricultural industries tend to have multipliers that are more similar across business cycle phases.
The federal-private wage differential: How has it evolved?
Sun-Ki Choi & John Garen
Applied Economics, forthcoming
This paper is the first to document and analyse the variation of the federal-private pay differential over time. We estimate the evolution of the federal-private pay differential from 1995 to 2017 using Current Population Survey data, enabling us to examine the current pay gap and how it has changed. To do so, wage regressions are estimated by year and used to calculate the yearly federal-private wage differential. To deal with unobserved heterogeneity, we adopt control function methods. We also estimate the probability of receiving employer-provided health insurance and a pension plan each year for each sector. The findings imply that the federal pay differential is invariably positive, but has varied substantially. We examine the reasons for this variation and find that the most robust result is the positive effect of federal spending as a share of GDP, implying that a 1 percentage point increase in federal spending as a share of GDP raises the federal pay differential by 1.3 to 1.75 percentage points.