This paper demonstrates that, in a large class of linear-quadratic models with rational expectations, losses due to time-inconsistency problems can be avoided, as the commitment solution can be implemented by a policy-maker who acts under discretion. We focus on two approaches. First, we show that a non-Markovian, reputational equilibrium that implements the commitment solution always exists. Second, we show how delegation to a policy-maker with an additional objective for the policy instrument can be used to implement the commitment solution via a standard discretionary Markov equilibrium. Implementation is facilitated by the fact that the commitment outcome can be attained irrespective of the weight that the policy-maker assigns to the additional target. Using the standard new Keynesian model as an example, we study the dynamics of the economy under optimal additional output targets as well as optimal interest-rate targets for central banks.

This paper analyzes how idiosyncratic risk, measured by the variance of firm-level idiosyncratic shocks, affects long-run growth when bankruptcy costs are present. These costs are incurred by creditors during the bankruptcy procedure of failing firms. In an endogenous growth model with bankruptcy costs where firms privately observe the outcome of idiosyncratic shocks, an increase in idiosyncratic risk reduces long-run growth. This happens because, when bankruptcy costs are present, higher idiosyncratic risk enlarges the wedge between the rental rate of capital and its marginal product, thereby slowing down capital accumulation. This growth-reducing effect of idiosyncratic risk is stronger when bankruptcy costs are higher. Empirical support for these propositions is provided in a growth regression that exploits cross-country variations in the dispersion of firms’ real sales growth as a proxy for idiosyncratic risk along with recovery rates as a measure that proxies the inverse of bankruptcy costs.

Using monthly headline inflation data covering 184 countries for the period between January 1971 and December 2020, this paper investigates the role of standard gravity variables on inflation convergence across country pairs. The convergence analysis by unit root tests is based on ten-year rolling windows to control for potential structural changes over time, whereas the corresponding results are connected to the standard gravity variables in the preceding year to investigate the drivers of inflation convergence and its speed. Regarding the existence of inflation convergence, empirical results show that having a common currency, a free trade agreement, proximity, a common border, or a colonial relationship between countries increases the probability of inflation convergence. Regarding the speed of inflation convergence, the very same gravity variables are shown to reduce the half-life of convergence. In both cases, the effects of having a common currency are shown to dominate those of other gravity variables.

What determines the strength of the relationship between money growth and inflation? A large literature suggests that it has weakened since the 1980s, without a definitive explanation of the cause. I explore how population age structure explains changes in the pass through of money growth rates to inflation. I show that the quantity theory of money holds over long time horizons, with sizable estimates of the impact of money growth on inflation in the short to medium term. Various measures of population age structure have significant impact on the strength of this relationship. These demographics account for an increase in the transmission of money growth to prices in the 1970s and a weakening throughout the great moderation. The baby boomer cohort, now in the age groups around retirement, may exert upward pressure on this money transmission to prices at present, with ambiguous implications in the future as low fertility and rising longevity persist.

We use a labor search model with heterogenous households and firms to study the efficacy of a wage subsidy during a pandemic, relative to enhancing unemployment benefits. A large proportion of the economy is forced to shut down, and firms in that sector choose whether to lay off workers or keep them on payroll. A wage subsidy encourages firms to keep workers on payroll, which speeds up labor market recovery after the pandemic ends. However, a wage subsidy can be costlier than enhancing unemployment benefits. If the shutdown is long or profit margins are low, then a wage subsidy is preferable and vice versa. The optimal mixture of policies includes a wage subsidy that covers 90$\%$ of the first $200/week of earnings and expands unemployment benefits to cover all salary up to $275/week. Low-income workers, as well as those in less productive jobs, benefit the most from a wage subsidy.

I develop a dynamic model of consumption variety in status goods by introducing a realistic aspect that is new in the existing literature—that a good will not carry status appeal unless it is advertised. As advertisements will divert resources from new product research, growth in new products will be reduced. However, status-good advertisements also enhance distinctiveness of a good and increase a firm’s profit. This will motivate more researches. With the two effects offsetting each other, the original market bias in a standard product-development model—insufficient research due to a general knowledge spillover—cannot be overcome. While introducing advertising into models of this kind does not reverse the original welfare implication of suboptimal growth, this makes available a new and better intervention option—taxing advertisements. This tax is superior to consumption tax, the conventional solution to inefficient status competition, as consumption tax is found to be ineffective in the present model. It is also superior to research subsidies, the conventional solution to suboptimal growth, as subsidies must be financed and is not a self-sufficient policy.

This paper applies the common stochastic trends representation approach to the time series of total factor productivity (TFP) and the relative price of investment (RPI) to investigate the modeling of neutral technology (NT) and investment-specific technology (IST) and its econometric ramifications on the analysis of general equilibrium model. The permanent and transitory movements in both series are estimated efficiently via Markov chain Monte Carlo methods using band matrix algorithms. The results indicate that TFP and the RPI are, each, well represented by a differenced first-order autoregressive process. In addition, their time series share a common trend component that we interpret as reflecting changes in general purpose technology. These results are consistent with studies that suggest that (1) the traditional view of assuming that NT and IST follow independent processes is not supported by the features of the time series and (2) improper specification of secular trends may distort estimation and inference. Notably, the findings provide some guidance to minimize the effect of idiosyncratic and common trend misspecifications on the analysis of impulse dynamics and propagation mechanisms in macroeconomic models.

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.