We study the impact of uncertainty shocks using a disaggregated model featuring US state-level unemployment, and uncertainty measured using state-level Google search data. Importantly, the model captures spillovers across states and identifies substantial differences in peak responses and time dynamics. Moreover, the importance of national factors in propagating the effect of uncertainty is also heterogeneous across states, but less relevant than state-level factors. These heterogeneous effects are related to state-specific industry compositions and fiscal positions. In addition, we highlight the usefulness of disaggregated data in models of uncertainty and economic activity for the USA, based on the superior ability of the disaggregate model to predict aggregate uncertainty and unemployment.

We document that the employment effects of financial aid to US states during the Great Recession were strongly unevenly distributed across sectors, the construction sector being the main beneficiary. State fiscal relief not only preserved a substantial number of jobs but it also fostered employment most strongly in the sectors hit hardest by the recession. Exploiting across-state differences, we conclude that the sectoral employment effects of state fiscal relief reflect the typical spending patterns of state and local governments, who usually spend large shares of their discretionary expenditures on construction.

This paper revisits the canonical assumption of nonconvex capital adjustment costs in lumpy investment models as in Khan and Thomas [(2008) Econometrica 76(2), 395–436], which are assumed to follow a uniform distribution from zero to an upper bound, without distinguishing between the mean and the variance of the distribution. Unlike the usual claim that the upper bound stands for the size (represented by the mean) of a nonconvex cost, I show that in order to generate an empirically consistent interest elasticity of aggregate investment, both a sizable mean and a sizable variance are necessary. The mean governs the importance of the extensive margin in aggregate investment dynamics, while the variance governs how sensitive the extensive margin is to changes in the real interest rate. As a result, both the mean and the variance are quantitatively important for aggregate investment dynamics.

This paper investigates the impact of the introduction of inflation-linked bonds, which incur transaction costs when traded, on the monetary economy with sunspots. This paper shows that there always exists a certain range of positive transaction costs, where both monetary and bond markets are active. This implies that on top of governments, profit-seeking financial entrepreneurs also have the incentive to issue these bonds. This paper also displays how financial innovation on the indexed bond can be Kaldor improving, even if not necessarily Pareto improving. This finding indicates that together with lump-sum tax policies, the government can attain consensus among consumers on bond issuance.

This study investigates the time-varying effects of international uncertainty shocks. I use a global vector autoregressive model with drifting coefficients and factor stochastic volatility in the errors to model the G7 economies jointly. The measure of uncertainty is constructed by estimating a time-varying scalar driving the innovation variances of the latent factors, which is also included in the conditional mean of the process. To achieve regularization, I use Bayesian techniques for estimation, and rely on hierarchical global–local priors to shrink the high-dimensional multivariate system towards sparsity. I compare the obtained econometric measure of uncertainty to alternative indices and discuss commonalities and differences. Moreover, I find that international uncertainty may differ substantially compared to identically constructed domestic measures. Structural inference points towards pronounced real and financial effects of uncertainty shocks in all considered economies. These effects are subject to heterogeneities over time and the cross-section, providing empirical evidence in favor of using the flexible econometric framework introduced in this study.

We explore how tax evasion by firms affects the growth- and welfare-maximizing rates of corporate income tax (CIT) in an endogenous growth model with productive public service. We show that the negative effect of CIT on growth is mitigated in the presence of tax evasion. This increases the benefit of raising the CIT rate for public service provision. Thus, in contrast to Barro [(1990) Journal of Political Economy 98, 103–125], the optimal tax rate is higher than the output elasticity of public service. Through numerical exercises, we demonstrate that the role of tax evasion by firms is quantitatively significant.

Expectations are among the main driving forces for economic dynamics. Therefore, managing expectations has become a primary objective for monetary policy seeking to stabilize the business cycle. In this paper, we study whether central banks can manage private-sector expectations by means of publishing one-period ahead inflation projections in a New Keynesian learning-to-forecast experiment. Subjects in the experiment observe these projections along with the historic development of the economy and subsequently submit their own one-period ahead inflation forecasts. In this context, we find that the central bank can significantly manage private-sector expectations and that this management strongly supports monetary policy in stabilizing the economy. Moreover, published central bank inflation projections drastically reduce the probability of a deflationary spiral after strong negative shocks to the economy.

Nonlinear co-integration is studied for score-driven models, using a new multivariate dynamic conditional score/generalized autoregressive score model. The model is named t-QVARMA (quasi-vector autoregressive moving average model), which is a location model for the multivariate t-distribution. In t-QVARMA, I(0) and co-integrated I(1) components of the dependent variables are included. For t-QVARMA, the conditions of the maximum likelihood estimator and impulse response functions (IRFs) are presented. A limiting special case of t-QVARMA, named Gaussian-QVARMA, is a Gaussian-VARMA specification with I(0) and I(1) components. As an empirical application, the US real gross domestic product growth, US inflation rate, and effective federal funds rate are studied for the period of 1954 Q3 to 2020 Q2. Statistical performance and predictive accuracy of t-QVARMA are superior to those of Gaussian-VAR. Estimates of the short-run IRF, long-run IRF, and total IRF impacts for the US data are reported.

We estimate the relationship between GDP per capita growth and the growth rate of the national saving rate using a panel of 130 countries over the period 1960–2017. We find that GDP per capita growth increases (decreases) the growth rate of the national saving rate in poor countries (rich countries), and a higher credit-to-GDP ratio decreases the national saving rate as well as the income elasticity of the national saving rate. We develop a model with a credit constraint to explain the growth-saving relationship by the saving behavior of entrepreneurs at both the intensive and extensive margins. We further present supporting evidence for our theoretical findings by utilizing cross-country time series data of the number of new businesses registered and the corporate saving rate.

We present a new methodology that uses professional forecasts to estimate the effects of fiscal policy. We use short-term forecasts to better identify exogenous shocks to government spending by controlling for anticipatory information already in the public domain. We use longer-term forecasts to net out expectations from the future path of other variables, which improves accuracy and efficiency by focusing on more precise measures of the impact of shocks. We show that this improves the statistical fit relative to both local projection methods and vector autoregression-based analyses that do not control for the entire future path of expectations.

The monetary authority’s choice of operating procedure has significant implications for the role of monetary aggregates and interest rate policy on the business cycle. Using a dynamic general equilibrium model, we show that the type of endogenous monetary regime, together with the interaction between money supply and demand, does well to capture the actual behavior of a monetary economy—the USA. The results suggest that the evolution toward a stricter interest rate-targeting regime renders central bank balance sheet expansions ineffective. In the context of the 2007–2009 Great Recession, a more flexible interest rate-targeting regime would have led to a significant monetary expansion and more rapid economic recovery in the USA.

The Survey of Consumer Finances (SCF) indicates that, unlike subprime borrowers, prime borrowers are more likely to own investment homes during recessions than during recoveries. Drawing on this empirical fact, we present and estimate a dynamic stochastic general equilibrium (DSGE) model that distinguishes between borrowers through their credit access. We find that the relative ease of credit access among borrowers explains the divergence in investment homeownership seen in the data. This divergence is amplified when subprime borrowers are subject to lax credit conditions prior to a financial shock or when the nominal interest rate is constrained at the zero lower bound (ZLB). An expansionary monetary policy helps bridge this gap across borrowers.

Japan’s so-called Lost Decade of the 1990s presents a unique case study of an economy with a recent severe and prolonged recession, with large changes in the labor market and fiscal policy as the main policy available to the government. Japanese unemployment rate surged from 2.1% in 1991 to 5.4% in 2002. Meanwhile, the Japanese economy experienced a rise in government expenditures, while taxes remained fairly stable. This paper quantitatively evaluates the impact of these changes in fiscal policies on labor market variables, in particular the unemployment rate, during the 1990s. We build, calibrate, and simulate a dynamic general equilibrium model with search frictions in the labor market, a productive government sector, heterogenous government spendings, and different categories of taxes. Our model is able to reproduce the paths of the main labor market variables, and the counterfactual experiments show that the changes that took place in the different spending components affected the unemployment rate heterogeneously, although overall they kept unemployment lower than it could have been. We also find that had the government also implemented countercyclical tax policies, unemployment would not have risen as much as it did by 2002.

When some steps of a complex, multi-step task are automated, the demand for human work in the remaining complementary sub-tasks goes up. In contrast, when the task is fully automated, the demand for human work declines. Upon aggregation to the macroeconomic scale, partial automatability of complex tasks creates a bottleneck of development, where further growth is constrained by the scarcity of essential human work. This bottleneck is removed once the tasks become fully automatable. Theoretical analysis using a two-level nested constant elasticity of substitution production function specification demonstrates that the shift from partial to full automation generates a non-convexity: humans and machines switch from complementary to substitutable, and the share of output accruing to human workers switches from an upward to a downward trend. This process has implications for inequality, the risk of technological unemployment, and the likelihood of a secular stagnation.

Multiple equilibria arise in standard New Keynesian models when the nominal interest rate is set according to the Taylor rule and constrained by a zero lower bound (ZLB). One of these equilibria is deflationary and referred to as an expectations-driven liquidity trap (ELT) as it arises because of the de-anchoring of inflation expectations. This study demonstrates that a simple tax rule responding to inflation can prevent a liquidity trap from arising without increasing government spending or debt. We analytically investigate the necessary and sufficient conditions to prevent an ELT and show that both the frequency and persistence of ELT episodes affect the extent to which the tax rule must respond to inflation. In brief, the higher the frequency or the longer the persistence of the ELT, the greater the response of the tax rate must be.

This paper argues that output can respond to public education spending in a delayed and persistent manner through human capital accumulation. We refer to this as a “time-release” response, reflecting that the output response grows as students exposed to increased expenditures sequentially enter the labor market. We first develop and calibrate a stochastic overlapping generations model to formalize the propagation of spending shocks over a long time horizon. We then empirically explore this time-release aspect of shocks to government education expenditures on output using US state-level data for the period 1963–2016 and a panel structural vector autoregression methodology. Consistent with the model, our empirical results show that the dynamic response of output to shocks to government education expenditures is positive, significant, and long-lasting.

We estimate the effects of government spending shocks during prolonged episodes of low interest rates, which we consider as proxy for the effective lower bound (ELB). Using a panel VAR model for 17 advanced countries, we find that both the government consumption and investment multipliers are significantly higher, and exceed unity, when interest rates are persistently low. Distinguishing between construction- and equipment-related government investments, we find that only the former raises output by significantly more when the ELB binds. This result can be explained by existing New Keynesian models featuring time-to-build constraints on government investment.

This paper offers a framework for measuring global growth and inflation, built on standard index number theory, national accounts principles, and the concepts and methods for international macro-economic comparisons. Our approach provides a sound basis for purchasing power parity (PPP)- and exchange rate (XR)-based global growth and inflation measures. The Sato–Vartia index number system advocated here offers very similar results to a Fisher system but has the added advantage of allowing a complete decomposition with PPP or XR effects. For illustrative purposes, we present estimates of global growth and inflation for 141 countries over the years 2005 and 2011. The contribution of movements in XRs and PPPs to global inflation are presented. The aggregation properties of the method are also discussed.

Fixed search costs, that is, costs that do not vary with search duration, can amplify the cyclical volatility of the labor market. To assess the size of fixed costs, we analyze the relation between search costs and search duration using German establishment data. An instrumental variable estimation shows no relation between search duration and search costs. We conclude that search costs are mainly fixed costs. Furthermore, we show that a search and matching model, calibrated for Germany with fixed costs close to 75%, can generate labor market volatility that is consistent with the data.

The literature on international business cycles has employed dynamic factor models (DFMs) to disentangle global from group-specific and national factors in countries’ macroeconomic aggregates. Therefore, the countries have simply been classified ex ante as belonging to the same region or the same level of development. This paper estimates a DFM for a sample of 106 countries and three variables (output, consumption, investment) over the period 1960–2014, in which the countries are classified according to the outcome of a cluster analysis. By comparing the results with those obtained by the previous grouping approaches, we show substantial deviations in the importance of global and group-specific factors. Remarkably, when the groups are defined properly, the “global business cycle” accounts for only a very small fraction of macroeconomic fluctuations, most evidently in the industrialized world. The group-specific factors, on the other hand, play a much greater role for national business cycles than previously thought—also in the pre-globalization period.