Bargaining Power and Aggregate Fluctuations (with Jesus Fernandez-Villaverde and Pablo Guerron-Quintana)
(supersedes "Political Distribution Risk and Aggregate Fluctuations")
We argue that social and political risk causes significant aggregate fluctuations by changing bargaining power. To that end, we document significant changes in the capital share after large political events, such as political realignments, modifications in collective bargaining rules, or the end of dictatorships, in a sample of developed and emerging economies. These policy changes are associated with significant fluctuations in output. Using a Bayesian proxy-VAR estimated with U.S. data, we show how distribution shocks cause movements in output and unemployment. To quantify the importance of these political shocks for the U.S. as a whole, we extend an otherwise standard neoclassical growth model. We model political shocks as exogenous changes in the bargaining power of workers in a labor market with search and matching. We calibrate the model to the U.S. corporate non-.financial business sector and we back out the evolution of the bargaining power of workers over time using a new methodological approach, the partial .filter. We show how the estimated shocks agree with the historical narrative evidence. We document that bargaining shocks account for 28% of aggregate fluctuations and have a welfare cost of 2.4% in consumption units.
Partisan Politics in Fiscal Unions: Evidence from U.S. States (with Jerry Carlino, Bob Inman, and Nick Zarra; in progress)
States have become increasingly important agents of fiscal policy in the U.S. Motivated by the large literature that finds increases in partisanship among policymakers, we analyze how partisanship affects state fiscal policy and what the macroeconomic effects are. Using data from close elections, we find strong partisanship effects in the spending propensity of federal transfers, the so-called fly-paper effect: Republican governors spend less of federal funds and, instead, cut distortionary taxes. Transfers are an important vehicle of federal policies, with a share of 40\% in the 2009 ARRA stimulus bill, and subsequent funding of the 2014 Medicaid expansion. We provide causal evidence that the spending pass-through of federal transfers by state governments varies between Republican and Democratic governors, using a regression-discontinuity design. To analyze the macroeconomic effects of this partisan behavior, we calibrate a New Keynesian model of Republican and Democratic states in a fiscal union, drawing from the estimated pass-through distribution. The model delivers aggregate transfer multipliers that are significantly different by partisan preferences. Further, the transfer multiplier varies over time by the partisan affiliation of governors. We find empirical support for the structural model's partisan predictions using local-projection methods.
Philadelphia Fed Working Paper, Slides.
Alternative Strategies: How Do They Work? How Might They Help? (with Jonas Arias, Martin Bodenstein, Hess Chung, and Andrea Raffo)
Several structural developments in the U.S. economy—including lower neutral interest rates and a flatter Phillips curve—have challenged the ability of the current monetary policy framework to deliver on the Federal Open Market Committee’s (FOMC) dual-mandate goals. This paper explores whether makeup strategies, in which policymakers seek to stabilize average inflation around the inflation target over some horizon, could strengthen the FOMC’s ability to fulfill its dual mandate. The quantitative analysis discussed here suggests that credible makeup strategies may provide some moderate stabilization gains. The practical implementation of these strategies, however, faces a number of challenges that would have to be surmounted for the full benefit of these strategies to be realized.
Identification And Inference With Ranking Restrictions (with Pooyan Amir-Ahmadi)
Quantitative Economics (forthcoming)
We propose ranking restrictions on impulse-responses to sharpen set identification with sign restrictions in Bayesian vector autoregressions (VARs) and develop tools for inference with tight restrictions. Ranking restrictions come from micro data on heterogeneous industries in VARs, bounds on elasticities, or restrictions on dynamics. We characterize analytically when ranking restrictions sharpen the identified set in small VARs, including for variables not subject to ranking restrictions. Our tools for inference are of independent interest: (1) A simple algorithm testing whether the identified set is nonempty, (2) a fully Bayesian algorithm that directly samples from the identified set, and (3) a prior-robust algorithm to sample the posterior bounds of the identified set. Using our tools, we analyze productivity news shocks. Both heterogeneity and slope restrictions, but not sign restrictions alone, imply that news shocks raise output temporarily, but significantly. With ranking restrictions the output contribution of news shocks drops by 20-40pp.
The Role of Startups for Local Labor Markets (with Jerry Carlino)
Journal of Applied Econometrics (2020)
There are substantial differences in startup activity across U.S. local labor markets. We study the causes and consequences of these differences. Startup productivity shocks are found to drive much of these cross-city differences in startup activity. Examples of such shocks include breakthroughs in biotech that spurred startup formation in San Diego and Philadelphia. Overall, these shocks explain half of the forecast error variance of startup job creation, accounting for 40% of population growth and long-run changes in employment. Shocks to barriers to firm entry have economy-wide effects similar to those of startup productivity shocks but operate largely through the number of startups, rather than their size. We use a novel spatial panel VAR, identifying shocks using shift-share external instruments.
Quantitative Economics (2020)
Structural DSGE models are used for analyzing both policy and the sources of business cycles. Conclusions based on full structural models are, however, potentially affected by misspecification. A competing method is to use partially identified SVARs based on narrative shocks. This paper asks whether both approaches agree. Specifically, I use narrative data in a DSGE-SVAR that partially identify policy shocks in the VAR and assess the fit of the DSGE model relative to this narrative benchmark. In developing this narrative DSGE-SVAR, I develop a tractable Bayesian approach to proxy VARs and show that such an approach is valid for models with a certain class of Taylor rules. Estimating a DSGE-SVAR based on a standard DSGE model with fiscal rules and narrative data, I find that the DSGE model identification is at odds with the narrative information as measured by the marginal likelihood. I trace this discrepancy to differences in impulse responses, identified historical shocks, and policy rules. The results indicate monetary accommodation of fiscal shocks.
Journal of Monetary Economics (2019)
New businesses are important for job creation and have contributed more than proportionally to the recent economic fluctuations. Given the risk exposure of entrepreneurs, this paper asks whether changing risk can explain the dynamics of new businesses. It makes two contributions. First, it provides a tractable, quantitative framework for analyzing business creation when entrants are exposed to idiosyncratic risk. Second, it provides conditions under which data on the size distribution of new businesses and their exit rates identifies entrepreneurial risk. According to the structural estimates, fluctuations in such risk explain around 40% of the employment fluctuations at new U.S. businesses.
Paper, web appendix.
Accounting for the Sources of Macroeconomic Tail Risks (with Enghin Atalay and Zhenting Wang)
Economics Letters (2018)
Using a multi-industry real business cycle model, we empirically investigate the microeconomic origins of aggregate tail risks. Our model, estimated using industry-level data from 1972 to 2016, indicates that industry-specific shocks account for most of the third and fourth moments of GDP growth.
Fiscal Stimulus and Distortionary Taxation (with Harald Uhlig)
Review of Economic Dynamics (2015)
We quantify the fiscal multipliers in response to the American Recovery and Reinvestment Act (ARRA) of 2009. We extend the benchmark Smets-Wouters (Smets and Wouters, 2007) New Keynesian model, allowing for credit-constrained households, the zero lower bound, government capital and distortionary taxation. The posterior yields modestly positive short-run multipliers around 0.52 and modestly negative long-run multipliers around -0.42. The multiplier is sensitive to the fraction of transfers given to credit-constrained households, the duration of the zero lower bound and the capital. The stimulus results in negative welfare effects for unconstrained agents. The constrained agents gain, if they discount the future substantially.
(Philadelphia Fed Economic Insights)
Mainstream economics views business cycles as driven by random shocks, making it hard to predict downturns. I discuss theories linking shocks and business cycles and give examples of identified shocks.
(Philadelphia Fed Economic Insights)
New businesses are major job generators, so disappointing trends in firm formation have raised concern. I discuss why at least some of the worry might be misplaced.
Financing Fiscal Stimulus (with Harald Uhlig)
VOX column summarizing research on fiscal stimulus.