Revolving credit is the prime determinant of short-run household liquidity and comoves positively with product variety and negatively with unemployment. I develop a theory of feedback between revolving credit and product development and examine its ability to explain labor market volatility. Extending the Mortensen–Pissarides model with an endogenous borrowing constraint and free entry of monopolistically competitive firms reproduces stylized facts in the data and amplifies both productivity and financial shocks through mutual causality. Higher debt limits encourage firm entry and raise product variety (the entry channel), and greater variety makes default more costly and thereby raises the equilibrium debt level (the consumption value channel). Though productivity shocks are sufficient to generate higher volatility, financial shocks are essential in approximating the time series patterns of unemployment, vacancies, and revolving credit in the data, and reproduce the rise in unemployment during the Great Recession.

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.

We study the implications of changes in the mix of taxes, public spending, and public finance in the Eurozone. In so doing, we build a general equilibrium OLG model that naturally incorporates all the main categories of public spending and taxes. We focus on the medium- and long-run implications of permanent reforms in the actual policy mix. When we depart from 2008, the best way out of the recession would be an increase in public spending on education and health and in turn cuts in distorting taxes including social security contributions. When we depart from the year 2017, which features a higher inherited public debt, public debt consolidation becomes the superior reform to the extent that the focus is on the medium and long run.

This paper studies the evolution of China’s exchange rate policy using real options theory. With intervention costs and ongoing uncertainty, intervention involves the exercise of an option. Increased uncertainty increases the value of this option. This “wait and see” effect leads the Central Bank to widen its intervention band. However, increased volatility also produces larger fluctuations in welfare, which creates a “fear of floating.” This induces the Central Bank to set a tighter band. To study this trade-off, our paper incorporates stochastic volatility into a new Keynesian target zone model and then calibrates it to data from China. We find that increased uncertainty leads to a tighter intervention band, both in the data and in the model. Hence, in China, “fear of floating” appears to dominate the “wait and see” effect.

We introduce business-to-business (B2B) relationships into an otherwise standard model to revisit two aspects of price dynamics in a unified analysis. On one side, the pass-through of cost shocks to prices is empirically incomplete. On the other side, the literature contains conjectures that long-term relationships may reduce the allocative role of price changes. After a partial equilibrium analysis of these aspects, we consider the general equilibrium effects. The formation of B2B relationships implies that the trade of intermediate goods depends on search, bargaining, and the adjustment along the intensive margin as opposed to the extensive margin. We find that, when this adjustment is costly, retailers have a relatively high bargaining power, and mismatch shocks are possible, the model can account for the second moments of the US producer price index and other variables. In this case, although its allocative role is low, the intermediate goods price affects the allocation of goods through the search externalities and is sufficiently volatile. The analysis includes several sensitivity tests and comparisons.

This research empirically establishes and interprets the hypothesis that the relationship between population aging and inventive activity is hump-shaped. We estimate a reduced form, hump-shaped relationship in a panel of 33 OECD countries over the period 1960–2012, as well as in a panel of 248 NUTS 2 regions in Europe over the period 2001–2012. The increasing part of the hump may be associated with various channels including the acknowledgement that population aging requires inventive activity to guarantee current and future standards of living, or the observation that older educated workers are more innovative than their young peers. The decreasing part may reflect the tendency of aging societies to lose dynamism and the willingness to take risks.

We provide a new way of deriving a number of dynamic unobserved factors from a set of variables. We show how standard principal components may be expressed in state space form and estimated using the Kalman filter. To illustrate our procedure, we perform two exercises. First, we use it to estimate a measure of the current account imbalances among northern and southern euro area countries that developed during the period leading up to the outbreak of the euro area crisis, before looking at adjustment in the post-crisis period. Second, we show how these dynamic factors can improve forecasting of the euro exchange rate.

This paper establishes new stylized facts about labor market dynamics in developing economies, which are distinct from those in advanced economies, and then proposes a simple model to explain them. We first show that the response of hours worked and employment to a technology shock—identified by a structural VAR model with either short-run or long-run restrictions—is substantially smaller in developing economies. We then present compelling empirical evidence that several structural factors related to the relevance of subsistence consumption across countries can jointly account for the relative volatility of employment to output and that of consumption to output. We argue that a standard real business cycle (RBC) model augmented with subsistence consumption can explain the several salient features of business cycle fluctuations in developing economies, especially their distinct labor market dynamics under technology shocks.

The learning-from-experience model of Malmendier and Nagel [(2016) Quarterly Journal of Economics 131, 53–87] successfully reproduces the heterogeneity in inflation expectations across age groups. However, inflation expectations presumably depend on not only age and experience but also inflation regime. Therefore, this paper proposes an extended learning-from-experience model, in which expectation formation depends on inflation regime. Estimating the model with US data, I find that when inflation is higher and more volatile, households place more weight on recent data when making private forecasts. Moreover, in this regime, households rely more heavily on private forecasts than on public information.

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.

Unemployment insurance schemes typically include eligibility conditions comprising the employment history prior to becoming unemployed, an aspect largely neglected in the literature. We develop an analytically tractable matching model including such contingencies. Unemployed determine reservation durations for jobs to be acceptable, and stronger employment histories increase reservation durations. This creates a stratification among unemployed; unemployed with short employment histories accept short-term jobs, while those with a strong employment history aims for jobs with a longer duration. A trade-off arises between the employment level and the matching quality in terms of job duration; a stronger reward to employment histories reduces employment, but improves match quality (more long-term jobs). Numerical simulations show that the distribution between short- and long-term jobs is significantly affected by history dependencies in benefits levels and duration. The optimal utilitarian policy is shown to include contingencies based on employment histories of the unemployed.

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.

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.

We develop a dynamic general equilibrium growth model, where households purchase final goods on cash or credit and have different capital and money endowments, to investigate whether inflation affects trends in income and consumption inequality. We show that, under a strong substitutability between cash and credit goods, inflation has a negative relationship with income inequality, but a U-shaped relationship with consumption inequality. The divergence between income and consumption inequality explains several recent empirical observations. This result has important policy implications, as consumption inequality better reflects the welfare distribution whereas income inequality fails to capture consumption disparities resulting from different consumption and asset distributions across households. In the growth model with heterogeneous households, there is a mixed relationship between growth and income inequality, confirming the existence of the Kuznets curve. The inflation-driven asset reallocation might also produce a Mundell–Tobin effect, enhancing growth.

This study investigates if the reaction function of the Federal Reserve switches between two distinct policy rules. Using a time-varying transition probability framework, we also determine if forward-looking macroeconomic or financial covariates signal an impending monetary regime switch. We find that US monetary policy is best described by a Markov-switching model with two regime processes, one of which controls for heteroskedasticity in the shocks to the policy rule. We find that the Fed switches between an aggressive regime with a relatively high weight on inflation and a dovish regime that is less responsive to inflationary pressures. We find that an increase in private forecasters’ expectations of an impending recession signals a switch from the more aggressive policy regime to the less aggressive regime. A recovery in equity returns signals a return back to the more aggressive regime.

The development of artificial intelligence (AI) does influence human jobs but not necessarily in a negative way. Although labor force participation rates and firms’ job vacancies for human labor decline, the unemployment rate may be lower than that in an economy without AI. In an economy with heterogeneously skilled workers, the invention of AI usually has a negative effect on the skilled labor market but a positive effect on the unskilled labor market. The overall unemployment rate may decline as AI develops.

This paper studies the government spending multiplier in the presence of the cost channel of the nominal interest rate. I find that the spending multiplier of normal times declines markedly when this channel is introduced. The rise in government spending leads to a rise in the nominal interest rate and, with the cost channel, to a rise in the marginal cost and inflation. In turn, this leads to a bigger rise in the nominal interest rate and the expected real interest rate, hence a lower multiplier, than in a model that abstracts from the cost channel. On the other hand, in a liquidity trap, the cost channel makes the spending multiplier larger. Therefore, by ignoring the cost channel, the spending multiplier is overestimated in normal times and underestimated during liquidity trap episodes. Since liquidity traps are rare, however, the spending multiplier is mostly lower than in previous estimates.

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.

This paper uses Bayesian methods to estimate a small-scale New Keynesian model with heterogeneous expectations (HE). Agents form expectations via Euler equation adaptive learning (AL) and differ by the model they use to forecast. Type A agents use a correctly specified model, while type B and type C agents use misspecified models. Quarterly US data from the pre-Great Moderation and Great Moderation periods are used to jointly estimate the degree of agent heterogeneity, the AL parameters, and the deep model parameters. Results show that the data exhibit significant expectational heterogeneity, and that the HE model fits the data better than a model with homogeneous agent AL.

Drawing on the empirical evidence that heterogeneity in inflation expectations is persistent and endogenously time-varying, we embed two inflation forecasting strategies—one based on costly ex ante perfect foresight, and the second based on costless ex ante extrapolative trend-following—in a macrodynamic model. Drawing also on the empirical evidence that inflation forecast errors may have to exceed some threshold before agents abandon their previously selected forecasting strategy, we describe agents as switching between forecasting strategies according to evolutionarily satisficing learning. Convergence to a long-run equilibrium consistent with output growth, unemployment and inflation at their natural levels may be achieved even if heterogeneity in inflation forecasting strategies (with predominance of the extrapolative foresight strategy) is an attractor of an evolutionarily satisficing dynamic perturbed by mutant agents. Thus, in keeping with the empirical evidence, heterogeneity in strategies to form inflation expectations (with prevalence of bounded rationality) can be a stable long-run equilibrium.