Heterogeneity and the Effects of Aggregation on Wage Growth
Robert Rich and Joseph Tracy
Abstract: This paper focuses on the implications of alternative methods of aggregating individual wage data for the behavior of economy-wide wage growth. The analysis is motivated by evidence of significant heterogeneity in individual wage growth and its cyclicality. Because of this heterogeneity, the choice of aggregation will affect the properties of economy-wide wage growth measures. To assess the importance of this consideration, we provide a decomposition of wage growth into aggregation effects and composition effects and use the decomposition to compare growth in an average wage—specifically average hourly earnings—to a measure of average wage growth from the Survey of Income and Program Participation. We find that aggregation effects largely account for average hourly earnings growth being persistently lower and less cyclical than average wage growth over the period 1990-2015, with these effects reflecting a disproportionate weighting of high-earning workers. The analysis also indicates that composition effects now play a more limited role in the cyclicality of wage growth compared to results reported in previous studies for earlier time periods.
Flexible Average Inflation Targeting: How Much Is U.S. Monetary Policy Changing?
Jarod Coulter, Roberto Duncan and Enrique Martínez-García
Abstract: One major outcome of the Federal Reserve’s 2019–20 framework review was the adoption of a Flexible Average Inflation Targeting (FAIT) strategy in August 2020. Using synthetic control methods, we document that U.S. inflation rose post-FAIT considerably more than predicted had the strategy not changed (an average of 1.18 percentage points during 2020:M8-2022:M2). To explore the extent to which targeting average inflation delayed the Fed’s response and contributed to post-FAIT inflation, we adopt a version of the open-economy New Keynesian model in Martínez-García (2021) and document the economic consequences of adopting alternative measures of average inflation as policy objectives. We document three additional major findings using this general equilibrium setup: First, depending on how far back and how much weight is assigned to past inflation misses, the policy outcomes under FAIT are similar to those under the pre-FAIT regime. Secondly, we find that the implementation of FAIT can have large effects over short periods of time as it tends to delay action. However, over longer periods of time—such as the 1984:Q1-2019:Q4 pre-FAIT period—its effects wash out and appear negligible. Finally, we find that different average inflation measures explain an average of 0.5 percentage points per quarter of the post-FAIT inflation surge, indicating that targeting average inflation by itself can only explain part of the inflation spike since August 2020.
Demographic Transition, Industrial Policies and Chinese Economic Growth
Michael Dotsey, Wenli Li and Fang Yang
Abstract: We build a unified framework to quantitatively examine the demographic transition and industrial policies in contributing to China’s economic growth between 1976 and 2015. We find that the demographic transition and industrial policy changes by themselves account for a large fraction of the rise in household and corporate savings relative to total output and the rise in the country’s per capita output growth. Importantly, their interactions also lead to a sizable fraction of the increases in savings since the late 1980s and reduce growth after 2010. A novel and important factor that drives these dynamics is endogenous human capital accumulation, which depresses household savings between 1985 and 2010 but leads to substantial gains in per capita output growth after 2005.
The Effects of Audit Partners on Financial Reporting: Evidence from U.S. Bank Holding Companies
Gauri Bhat, Hemang Desai, W. Scott Frame, Christoffer Koch and Erik J. Mayer
Abstract: This paper uses confidential data on audit engagement partner names from regulatory filings of bank holding companies (BHC) to investigate whether partners display individual style that affects the financial reporting of the BHCs. We focus on loan loss provisioning. We construct an audit partner-BHC matched panel data set that enables us to track different partners across different BHCs over time. We employ two empirical approaches to investigate partner style. The first approach tests whether partner fixed effects are statistically significant in loan loss provisioning models. The second approach tests whether a partner’s history of loan loss provisioning predicts future practices for the same partner. Our empirical evidence does not support systematic differences in loan loss provisioning across audit engagement partners, suggesting that the audit firm’s standards and quality control constrain personal partner style.
A Robust Test for Weak Instruments with Multiple Endogenous Regressors
Daniel J. Lewis and Karel Mertens
Abstract: We extend the popular bias-based test of Stock and Yogo (2005) for instrument strength in linear instrumental variables regressions with multiple endogenous regressors to be robust to heteroskedasticity and autocorrelation. Equivalently, we extend the robust test of Montiel Olea and Pflueger (2013) for one endogenous regressor to the general case with multiple endogenous regressors. We describe a simple procedure for applied researchers to conduct our generalized first-stage test of instrument strength and provide efficient and easy-to-use Matlab code for its implementation. We demonstrate our testing procedures by considering the estimation of the state-dependent effects of fiscal policy as in Ramey and Zubairy (2018).
The Impact of Minority Representation at Mortgage Lenders
W. Scott Frame, Ruidi Huang, Erik J. Mayer and Adi Sunderam
Abstract: We study links between the labor market for loan officers and access to mortgage credit. Using novel data matching the (near) universe of mortgage applications to loan officers, we find that minorities are significantly underrepresented among loan officers. Minority borrowers are less likely to complete mortgage applications, have completed applications approved, and to ultimately take-up a loan. These disparities are significantly reduced when minority borrowers work with minority loan officers. Minority borrowers working with minority loan officers also have lower default rates. Our results suggest that minority underrepresentation among loan officers has adverse effects on minority borrowers’ access to credit.
The Global Financial Cycle and Capital Flows During the COVID-19 Pandemic
J. Scott Davis and Andrei Zlate
Abstract: We estimate the heterogeneous effect of the global financial cycle on exchange rates and cross-border capital flows during the COVID-19 pandemic, using weekly exchange rate and portfolio flow data for a panel of 48 advanced and emerging market economies. We begin by estimating the global financial cycle at a weekly frequency with data through 2021 and observe the two standard deviation fall in our global financial cycle index over a period of four weeks in March 2020. We then estimate the country-specific sensitivities of exchange rates and capital flows to fluctuations in the global financial cycle. We show how during the pandemic crisis, high-frequency COVID-19 fundamentals like infection and vaccination rates—which differed in timing and intensity across our sample countries—were just as important as traditional, slow-moving macroeconomic fundamentals, such as the net external asset position and the current account balance, in explaining the cross-country heterogeneity in exchange rates and capital flows.
How Do Mortgage Rate Resets Affect Consumer Spending and Debt Repayment? Evidence from Canadian Consumers
Katya Kartashova and Xiaoqing Zhou
Abstract: One of the most important channels through which monetary policy affects the real economy is changes in mortgage rates. This paper studies the effects of mortgage rate changes resulting from monetary policy shifts on homeowners’ spending, debt repayment and defaults. The Canadian institutional setting facilitates the design of identification strategies for causal inference, since the vast majority of mortgages in the country experience predetermined, periodic and automatic contract renewals with the mortgage rate reset based on the prevailing market rate. This allows us to exploit quasi-random variation in the timing of the rate reset and present causal evidence for both rate declines and increases, with the help of detailed, representative consumer credit panel data. We find asymmetric effects of rate changes on spending, debt repayment and defaults. Our results can be rationalized by the conventional cash-flow effect in conjunction with changes in consumer expectations about future interest rates upon the reset. Given the pervasiveness of Canadian-type mortgages in many other OECD countries, our findings have broader implications for the transmission of monetary policy to the household sector.
When Do State-Dependent Local Projections Work?
Sílvia Gonçalves, Ana María Herrera, Lutz Kilian and Elena Pesavento
Abstract: Many empirical studies estimate impulse response functions that depend on the state of the economy. Most of these studies rely on a variant of the local projection (LP) approach to estimate the state-dependent impulse response functions. Despite its widespread application, the asymptotic validity of the LP approach to estimating state-dependent impulse responses has not been established to date. We formally derive this result for a structural state-dependent vector autoregressive process. The model only requires the structural shock of interest to be identified. A sufficient condition for the consistency of the state-dependent LP estimator of the response function is that the first- and second-order conditional moments of the structural shocks are independent of current and future states, given the information available at the time the shock is realized. This rules out models in which the state of the economy is a function of current or future realizations of the outcome variable of interest, as is often the case in applied work. Even when the state is a function of past values of this variable only, consistency may hold only at short horizons.
Dynamic Identification Using System Projections and Instrumental Variables
Daniel J. Lewis and Karel Mertens
Abstract: We propose System Projections with Instrumental Variables (SP-IV) to estimate dynamic structural relationships. SP-IV replaces lag sequences of instruments in traditional IV with lead sequences of endogenous variables. SP-IV allows the inclusion of controls to weaken exogeneity requirements, can be more efficient than IV with lags, and allows identification over many time horizons without creating many-weak-instruments problems. SP-IV also enables the estimation of structural relationships across impulse responses obtained from local projections or vector autoregressions. We provide a bias-based test for instrument strength, and inference procedures under strong and weak identification. SP-IV outperforms competing estimators of the Phillips Curve parameters in simulations. We estimate the Phillips Curve implied by the main business cycle shock of Angeletos et al. (2020), and find evidence for forward-looking behavior. The data is consistent with weak but also relatively strong cyclical connections between inflation and unemployment.
FinTech Lending, Social Networks and the Transmission of Monetary Policy
Abstract: One of the main channels through which monetary policy stimulus affects the real economy is mortgage borrowing. This channel, however, is weakened by frictions in the mortgage market. The rapid growth of financial technology-based (FinTech) lending tends to ease these frictions, given the higher quality services provided under this new lending model. This paper establishes that the role of FinTech lending in the monetary policy transmission is further amplified by consumers’ social networks. I provide empirical evidence for this network effect using county-level data and novel identification strategies. A 1 pp increase in the FinTech market share in a county’s socially connected markets raises the county’s FinTech market share by 0.23-0.26 pps. Moreover, I find that in counties where FinTech market penetration is high, the pass-through of market interest rates to borrowers is more complete. To quantify the role of FinTech lending and its network propagation in the transmission of monetary policy shocks, I build a multi-region heterogeneous-agent model with social learning that embodies key features of FinTech lending. The model shows that the responses of consumption and refinancing to a monetary stimulus are 13% higher in the presence of FinTech lending. Almost half of this improvement is accounted for by FinTech propagation through social networks.
Endogenous Option Pricing
Andrea Gamba and Alessio Saretto
Abstract: We show that a structural model of firm decisions can produce very flexible implied volatility surfaces: upward and downward sloping, u-shaped. A calibrated version of the model is able to match many unconditional financial characteristics of the average option-able stock, and can help explain how, contrary to simple economic intuition, more valuable growth and contraction options are associated with a more negatively sloped implied volatility curve (i.e., a more negatively skewed implied distribution).
Revisiting the Great Ratios Hypothesis
Alexander Chudik, M. Hashem Pesaran and Ron P. Smith
Abstract: The idea that certain economic variables are roughly constant in the long run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth, arbitrage or solvency, the empirical literature has tended to find little evidence for them. We argue that this outcome could be due to episodic failure of cointegration, possible two-way causality between the variables in the ratios and cross-country error dependence due to latent factors. We propose a new system pooled mean group estimator (SPMG) to deal with these features. Using this new panel estimator and a dataset spanning almost one and a half centuries and 17 countries, we find support for five out of the seven great ratios that we consider. Extensive Monte Carlo experiments also show that the SPMG estimator with bootstrapped confidence intervals stands out as the only estimator with satisfactory small sample properties.
The Matching Function and Nonlinear Business Cycles
Joshua Bernstein, Alexander W. Richter and Nathaniel A. Throckmorton
Abstract: The Cobb-Douglas matching function is ubiquitous in search and matching models, even though it imposes a constant matching elasticity that is unlikely to hold empirically. Using a general constant returns to scale matching function, this paper first derives analytical conditions that determine how the cyclicality of the matching elasticity amplifies or dampens the nonlinear dynamics of the job finding and unemployment rates. It then demonstrates that these effects are quantitatively significant and driven by plausible variation in the matching elasticity.
Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe (Revised July 2022)
Alexander Chudik, M. Hashem Pesaran and Alessandro Rebucci
Abstract: This paper provides estimates of COVID-19 transmission rates and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government-mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicates that the diversity of outcomes that we document may have resulted from the non-linear interaction of mandated and voluntary social distancing and the economic incentives that governments provided to support isolation. The importance of these factors declined over time, with vaccine uptake driving heterogeneity in country experiences in 2021. Our approach also allows us to identify the basic reproduction number, R0, which is precisely estimated around 5, which is much larger than the values in the range of 2.4 – 3.9 assumed in the extant literature.
On the Distributional Effects of International Tariffs
Daniel Carroll and Sewon Hur
Abstract: We provide a quantitative analysis of the distributional effects of the 2018 increase in tariffs by the U.S. and its major trading partners. We build a trade model with incomplete asset markets and households that are heterogeneous in their age, income, wealth and labor skill. When tariff revenues are used to reduce labor and capital income taxes and increase transfers, the average welfare loss from the trade war is equivalent to a permanent 0.1 percent reduction in consumption. Much larger welfare losses are concentrated among retirees and low-wealth and low-income workers, while only wealthy households experience a welfare gain.