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.

Since at least the mid-2000s, many advanced economies have experienced low productivity growth. This development is often related to declining productivity gains at the technology frontier, which is largely determined by the US. We challenge this explanation by studying the effects of US technology shocks on productivity levels in advanced economies. We find positive but small spillovers of US technology shocks. For many countries, the elasticity of their productivity with respect to a 1% increase in the US technology level is significantly lower than 1. Thus, the recent US productivity slowdown must have had a limited effect on productivity developments in advanced economies. Nevertheless, after 5 years, the degree of productivity spillovers varies across countries. Therefore, we analyze the role of institutions in shaping these results. Our findings suggest that isolated institutional characteristics are not able to explain the observed various spillover degrees.

Carbon pricing aims to shift the risk-adjusted returns on investment in favor of green technologies vis-‘a-vis fossil investment, relying on efficient capital markets to redirect investment accordingly. Capital markets with financial frictions can distort this transmission of climate policy. This study analyses the impact of emission taxes on mitigation and low-carbon investment in the presence of financial frictions. We develop a two-sector environmental dynamic stochastic general equilibrium model calibrated to the Euro Area, to simulate an economic transition in line with the EU climate targets. Financial frictions dampen the response of the economy to the carbon tax such that the emissions target will be missed by 11 percentage points. Moreover, the adverse effects of financial frictions increase when climate policy is delayed. We further identify a volume and a risk effect that drive the impact of a financial wealth shock and an uncertainty shock on emission intensity.

There is no consensus on the existence of welfare gains from international monetary policy cooperation. This study adds to the debate by providing a new open macroeconomics model with incomplete exchange rate pass-through. We find that, from a global perspective, the welfare gains from international monetary policy cooperation arise with incomplete exchange rate pass-through. Furthermore, the country’s incentive for cooperation increases with its degree of exchange rate pass-through. Cooperation benefits small countries with high pass-through; however, it is disadvantageous to large countries with low pass-through. In addition, when there is in the absence of cooperation, fixed exchange rate regime is preferred for a country suffering from monetary uncertainty, particularly for small economies with high exchange rate pass-through.

I examine how money and trend inflation shaped US macroeconomic dynamics during the Great Inflation. I develop a business cycle model with positive trend inflation where money is allowed (but not required) to play a role in determining the equilibrium values of inflation and output through non-separable utility, adjustment costs for holding real balances, and the monetary policy reaction function. The Taylor principle changes in this environment. Targeting money guarantees price determinacy even with trend inflation, but these results are sensitive to the inclusion of non-separability and portfolio adjustment costs. The framework is combined with Greenbook data that detect the role of money in the policy reaction function. The response to money was likely not sufficiently strong to complement the reaction to inflation and counteract the high trend inflation observed during the pre-Volcker period, which most likely led to price indeterminacy.

This study detects a structural break in international consumer price index (CPI) inflation comovement. We estimate the dynamic common factor models with unknown breakpoints of cross-country inflation rates and global price index of all commodities. We identify two global factors from the models: a commodity global factor and a noncommodity global factor. The former is a common factor between national inflation rates and commodity price index growth; the latter is a common factor among national inflation rates. The estimation of 29 countries’ quarterly CPI inflation data from 2001:Q1 to 2018:Q2 shows a one-time break in cross-country inflation dynamics in 2008:Q4. Thereafter, the importance of global factors in explaining the national inflation rates is remarkably increased. Furthermore, the increased global inflation synchronization is mainly driven by the larger role of the noncommodity global factor rather than that of the commodity global factor.

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.

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.

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.

In the presence of frictions, the existing literature shows that currency substitution is detrimental for domestic aggregate stability. This paper singles out the role of currency substitution and shows that diversified currency holdings operate as an automatic stabilizer that mitigates belief-driven cyclical fluctuations in Farmer’s (1997) indeterminate monetary economy. When the foreign inflation rate is lower than the domestic inflation rate, the model’s steady state always displays saddle-path stability. Hence, equilibrium indeterminacy originally present in the domestic country is entirely removed in the presence of diversified currency holdings. When the foreign inflation rate is higher than the domestic inflation rate, then depending on the degrees of currency substitution and relative risk aversion, indeterminacy is either impossible or the requisite level of the foreign inflation rate for indeterminacy is too high to square with data. The stabilizing effect of diversified currency holdings on domestic aggregate stability is robust to whether domestic and foreign currencies display as Edgeworth substitutes or complements, or are additively separable in the household’s preferences.

We use a time-varying parameter dynamic factor model with stochastic volatility estimated using Bayesian methods to disentangle the relative importance of the common component in Federal Housing Finance Agency house price movements from state-specific shocks, over the quarterly period of 1975Q2 to 2017Q4. We find that the contribution of the national factor in explaining fluctuations in house prices is critical. We then use a Bayesian change-point vector autoregressive model that allows for different regimes throughout the sample period, to study the impact of aggregate supply, aggregate demand, (conventional) monetary policy, and term-spread shocks, identified based on sign restrictions on the national component of house price movements. While monetary policy and other shocks are found to be quite dominant early on, we find evidence that the national factor has been detached from the identified macroeconomic shocks since 2014, thus suggesting that a “national bubble” might be brewing again in the US housing market.

We measure how taking into account air quality affects relative welfare levels and welfare convergence across countries. We use the equivalent variation framework by Jones and Klenow [(2016) American Economic Review 106(9), 2426–2457.] which takes into account consumption, life expectancy, inequality, and leisure and extend it with respect to environmental quality in form of air pollution. Our results show that omitting environmental aspects from welfare accounting might lead to both a substantial over- or understatement of actual relative welfare and welfare developments for different (groups of) countries.

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.

This paper estimates a model using Bayesian methods and data from the USA (1990Q1–2019Q2) to explore how the financial sector contributes to business cycles through banks’ asset channel and the quality of capital adequacy constraint. The paper shows that the contribution of financial and non-financial shocks varied before, during, and after the 2008 financial crisis; housing demand and asset price shocks are the main contributors, and the credit shocks are the most persistent. In addition, the paper presents the application of macroprudential tools, along with their impact on the economy in general, and on welfare in particular. The findings illustrate that the tools which control household borrowing ability, such as loan-to-value or debt-to-income ratios, do not impact welfare significantly. However, the impact of policies on the leveraged sector is substantial. The paper proposes macroprudential policies that allow policy-makers to stabilize the economy without changing welfare. Such policies, however, should be timely, targeted, and temporary; otherwise, they may cause disruptions.

This paper quantitatively examines the macroeconomic effects of size-dependent financial frictions on capital misallocation and aggregate total factor productivity. Based on panel data from China’s manufacturing sector, I find that among non-state-owned enterprises, (i) the dispersion of the marginal product of capital is large and persistent and (ii) large firms tend to have higher leverage, and lower mean and dispersion of the marginal product of capital than their small counterparts. This paper analyzes a dynamic stochastic general equilibrium model with heterogeneous agents and size-dependent financial frictions. By calibrating the model to a Chinese firm-level dataset, I show that in addition to matching the aforementioned stylized facts, the economy with a size-dependent borrowing constraint is able to reproduce the observed negative correlation between firm size and the marginal product of capital, as well as generate quantitatively modest TFP loss. Furthermore, ignoring firms’ size-dependent financing patterns may lead to an overstatement of TFP loss due to financial frictions.

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.

In the USA, the linkages between the housing market, the credit market, and the real sector have been striking in the past decades. To explain these linkages, I develop a small-scale dynamic stochastic general equilibrium (DSGE) model in which agents update non-rational beliefs about future house price growth, in accord with recent survey data evidence. Both standard productivity shocks and shocks in the credit sector generate endogenously persistent booms in house prices. Long-lasting excess volatility in house prices, in turn, affects the financial sector and propagates to the real sector. This amplification and propagation mechanism improves the ability of the model to explain empirical puzzles in the US housing market and to explain the macro-financial linkages during 1985−2019. The learning model can also replicate the predictability of forecast errors evidenced in recent survey data.

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.

This paper quantitatively examines the macroeconomic and welfare effects of macroprudential policies in open economies. We develop a small open economy dynamic stochastic general equilibrium (DSGE) model, where banks choose their funding sources (domestic vs. foreign deposits) and are subject to financial constraints. Our model predicts that banks reduce leverage in response to a macroprudential policy tightening, but increasingly rely on foreign funding. This endogenous shifts of funding composition significantly undermine the stabilizing effect and welfare gains of macroprudential policies. Our results also suggest macroprudential policies are less effective in financially more open economies, and optimal policy should take capital flows into consideration. Finally, we find empirical support for the model predictions in a group of developing and emerging economies.

This study introduces automation into a Schumpeterian growth model to explore the effects of R&D and automation subsidies. R&D subsidy increases innovation and growth but decreases the share of automated industries and the degree of capital intensity in the aggregate production function. Automation subsidy has the opposite effects on these macroeconomic variables. Calibrating the model to US data, we find that raising R&D subsidy increases the welfare of high-skill workers but decreases the welfare of low-skill workers and capital owners, whereas increasing automation subsidy increases the welfare of high-skill workers and capital owners but decreases the welfare of low-skill workers. Therefore, whether the government should subsidize innovation or automation depends on how it evaluates the welfare gains and losses of different agents in the economy.