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Journal ArticleDOI

Government Spending Multipliers in Good Times and in Bad: Evidence from U.S. Historical Data

05 Dec 2017-Journal of Political Economy (University of Chicago PressChicago, IL)-Vol. 126, Iss: 2, pp 850-901
TL;DR: The authors investigated whether U.S. government spending multipliers differ according to two potentially important features of the economy: (1) the amount of slack and (2) whether interest rates are near the zero lower bound.
Abstract: This paper investigates whether U.S. government spending multipliers differ according to two potentially important features of the economy: (1) the amount of slack and (2) whether interest rates are near the zero lower bound. We shed light on these questions by analyzing new quarterly historical U.S. data covering multiple large wars and deep recessions. We estimate a state-dependent model in which impulse responses and multipliers depend on the average dynamics of the economy in each state. We find no evidence that multipliers differ by the amount of slack in the economy. These results are robust to many alternative specifications. The results are less clear for the zero lower bound. For the entire sample, there is no evidence of elevated multipliers near the zero lower bound. When World War II is excluded, some point estimates suggest higher multipliers during the zero lower bound state, but they are not statistically different from the normal state. Our results imply that, contrary to recent conjecture, government spending multipliers were not necessarily higher than average during the Great Recession.

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Citations
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Book ChapterDOI
TL;DR: This article reviewed and synthesized our current understanding of the shocks that drive economic fluctuations and concluded that we are much closer to understanding the shocks in economic fluctuations than we were 20 years ago.
Abstract: This chapter reviews and synthesizes our current understanding of the shocks that drive economic fluctuations. The chapter begins with an illustration of the problem of identifying macroeconomic shocks, followed by an overview of the many recent innovations for identifying shocks. It then reviews in detail three main types of shocks: monetary, fiscal, and technology. After surveying the literature, each section presents new estimates that compare and synthesize key parts of the literature. The penultimate section briefly summarizes a few additional shocks. The final section analyzes the extent to which the leading shock candidates can explain fluctuations in output and hours. It concludes that we are much closer to understanding the shocks that drive economic fluctuations than we were 20 years ago.

738 citations


Cites background from "Government Spending Multipliers in ..."

  • ...Auerbach and Gorodnichenko (2013) and Ramey and Zubairy (2014) discuss this application and how it relates to another leading method, smooth transition VARs....

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Journal ArticleDOI
TL;DR: In this article, the authors focus on the costs of public debt when safe interest rates are low and develop four main arguments for public debt rollovers, including the existence of multiple equilibria where investors believe debt to be risky and, by requiring a risk premium, increase the fiscal burden and make debt effectively more risky.
Abstract: This lecture focuses on the costs of public debt when safe interest rates are low. I develop four main arguments. First, I show that the current US situation, in which safe interest rates are expected to remain below growth rates for a long time, is more the historical norm than the exception. If the future is like the past, this implies that debt rollovers, that is the issuance of debt without a later increase in taxes, may well be feasible. Put bluntly, public debt may have no fiscal cost. Second, even in the absence of fiscal costs, public debt reduces capital accumulation, and may therefore have welfare costs. I show that welfare costs may be smaller than typically assumed. The reason is that the safe rate is the risk-adjusted rate of return to capital. If it is lower than the growth rate, it indicates that the risk-adjusted rate of return to capital is in fact low. The average risky rate however also plays a role. I show how both the average risky rate and the average safe rate determine welfare outcomes. Third, I look at the evidence on the average risky rate, i.e., the average marginal product of capital. While the measured rate of earnings has been and is still quite high, the evidence from asset markets suggests that the marginal product of capital may be lower, with the difference reflecting either mismeasurement of capital or rents. This matters for debt: the lower the marginal product, the lower the welfare cost of debt. Fourth, I discuss a number of arguments against high public debt, and in particular the existence of multiple equilibria where investors believe debt to be risky and, by requiring a risk premium, increase the fiscal burden and make debt effectively more risky. This is a very relevant argument, but it does not have straightforward implications for the appropriate level of debt. My purpose in the lecture is not to argue for more public debt, especially in the current political environment. It is to have a richer discussion of the costs of debt and of fiscal policy than is currently the case.

437 citations


Cites background from "Government Spending Multipliers in ..."

  • ...…see, for example, Mertens (2018) on tax multipliers, Miyamoto et al (2018) on the multipliers under the zero lower bound in Japan, and the debate between Auerbach and Gorodnichenko (2012) and Ramey and Zubairy (2018) 39I examined the evidence for or against hysteresis in Blanchard (2018)....

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Journal ArticleDOI
TL;DR: In this article, the effects of uncertainty shocks on unemployment dynamics were investigated by estimating non-linear smooth transition models with post-WWII US data, and the relevance of such uncertainty shocks was found to be much larger than that predicted by standard linear VARs in terms of magnitude of the reaction of the unemployment rate to such shocks, and contribution to the variance of the prediction errors of unemployment at business cycle frequencies.

362 citations


Additional excerpts

  • ...Ramey and Zubairy (2014) criticize Auerbach and Gorodnichenko s (2012) computation of the macroeconomic IRFs to a positive scal spending shock....

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Journal ArticleDOI
TL;DR: This article found that an increase in the household debt to GDP ratio predicts lower subsequent GDP growth and higher unemployment in an unbalanced panel of 30 countries from 1960 to 2012, and uncover a global household debt cycle that partly predicts the severity of the global growth slowdown after 2007.
Abstract: An increase in the household debt to GDP ratio predicts lower subsequent GDP growth and higher unemployment in an unbalanced panel of 30 countries from 1960 to 2012. Low mortgage spreads are associated with an increase in the household debt to GDP ratio and a decline in subsequent GDP growth, highlighting the importance of credit supply shocks. Economic forecasters systematically over-predict GDP growth at the end of household debt booms, suggesting an important role of flawed expectations formation. The negative relation between the change in household debt to GDP and subsequent output growth is stronger for countries with less flexible exchange rate regimes and those closer to the zero lower bound on nominal interest rates. We also uncover a global household debt cycle that partly predicts the severity of the global growth slowdown after 2007. Countries with a household debt cycle more correlated with the global household debt cycle experience a sharper decline in growth after an increase in domestic household debt.

355 citations

Journal ArticleDOI
01 Apr 2022
TL;DR: In this paper , a news-based measure of adverse geopolitical events and associated risks is presented, and the adverse consequences of the GPR index are driven by both the threat and the realization of adverse political events.
Abstract: We present a news-based measure of adverse geopolitical events and associated risks. The geopolitical risk (GPR) index spikes around the two world wars, at the beginning of the Korean War, during the Cuban Missile Crisis, and after 9/11. Higher geopolitical risk foreshadows lower investment and employment and is associated with higher disaster probability and larger downside risks. The adverse consequences of the GPR index are driven by both the threat and the realization of adverse geopolitical events. We complement our aggregate measures with industry- and firm-level indicators of geopolitical risk. Investment drops more in industries that are exposed to aggregate geopolitical risk. Higher firm-level geopolitical risk is associated with lower firm-level investment. (JEL C43, E32, F51, F52, G31, H56, N40)

302 citations

References
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ReportDOI
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Abstract: This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

18,117 citations

Journal ArticleDOI
TL;DR: In this article, the parameters of an autoregression are viewed as the outcome of a discrete-state Markov process, and an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter is presented.
Abstract: This paper proposes a very tractable approach to modeling changes in regime. The parameters of an autoregression are viewed as the outcome of a discrete-state Markov process. For example, the mean growth rate of a nonstationary series may be subject to occasional, discrete shifts. The econometrician is presumed not to observe these shifts directly, but instead must draw probabilistic inference about whether and when they may have occurred based on the observed behavior of the series. The paper presents an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter

9,189 citations

ReportDOI
TL;DR: In this paper, the authors developed asymptotic distribution theory for instrumental variable regression when the partial correlation between the instruments and a single included endogenous variable is weak, here modeled as local to zero.
Abstract: This paper develops asymptotic distribution theory for instrumental variable regression when the partial correlation between the instruments and a single included endogenous variable is weak, here modeled as local to zero. Asymptotic representations are provided for various instrumental variable statistics, including the two-stage least squares (TSLS) and limited information maximum- likelihood (LIML) estimators and their t-statistics. The asymptotic distributions are found to provide good approximations to sampling distributions with just 20 observations per instrument. Even in large samples, TSLS can be badly biased, but LIML is, in many cases, approximately median unbiased. The theory suggests concrete quantitative guidelines for applied work. These guidelines help to interpret Angrist and Krueger's (1991) estimates of the returns to education: whereas TSLS estimates with many instruments approach the OLS estimate of 6%, the more reliable LIML and TSLS estimates with fewer instruments fall between 8% and 10%, with a typical confidence interval of (6%, 14%).

5,249 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a unified approach to impulse response analysis which can be used for both linear and nonlinear multivariate models and demonstrate the use of these measures for a nonlinear bivariate model of US output and the unemployment rate.

3,821 citations


Additional excerpts

  • ...Koop et al. (1996))....

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Journal ArticleDOI
TL;DR: The authors presented conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large.
Abstract: Many panel data sets encountered in macroeconomics, international economics, regional science, and finance are characterized by cross-sectional or “spatial” dependence. Standard techniques that fail to account for this dependence will result in inconsistently estimated standard errors. In this paper we present conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large. We illustrate the relevance of this approach using Monte Carlo simulations and a number of empirical examples.

3,763 citations