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.

Bénabou [(2002) Econometrica 70, 481–517.] demonstrated how progressive redistribution mitigates unequal opportunity for education to promote growth. We ask how effective that policy is when it affects the average quality of education. So, we add a learning externality in his model of human capital accumulation. It captures how knowledge diffusion through global channels—such as a national educational curriculum—influences children’s learning outcomes and, hence, growth. Whether inequality is a curse or a blessing for economic growth depends on how efficiently an economy designs these channels and to what extent they influence children’s education. The greater this efficiency, the lower is the optimal progressiveness of income redistribution for maximizing the long-run output growth rate. Interestingly, if poorly designed global channels exert greater influence in education, the optimal progressivity may increase. Our quantitative analysis reveals new implications for redistributive policies, including a surprisingly low optimal progressivity (approximately 6–7%) for the calibrated US economy.

The unorthodox estimation procedure, which Phillips (1958) adopted in his original paper, is examined using the Haar wavelet filter. The application of the Haar wavelet transform to Phillips’ original data shows that Phillips’ six pairs of mean coordinates display a striking similarity with the Haar scaling coefficients that represent averages with a period greater than 16 years. This is consistent with Desai’s (1975) intuition on the interpretation of the Phillips Curve. We show that the choice of sorting observations by ascending values of the unemployment rate is crucial for reaching the goal of estimating the eye-catching nonlinear hyperbolic shape of the wage–unemployment relationship that would be otherwise linear. Interestingly, the Haar filter can account not only for the facts characterizing the Phillips’ relationship up to the early 1960s but also for two important facts mostly debated among policymakers: the downward shift of the Phillips Curve and its flattening over time.

We assess the impact of fiscal and monetary policy shocks on US survey-based consumer expectations within states of low and high public debt. Following an unexpected increase in government spending, consumption intentions rise in the low-debt state and fall in the high-debt state. Overall, such a shock has adverse effects on expectations in high-debt states. Similarly, contractionary monetary policy shocks induce pessimistic expectations in the high-debt state but not in the low-debt state. The estimated responses suggest that higher public debt fuels considerations regarding its repayment, giving rise to state dependencies in the updating of expectations in response to both fiscal and monetary policy shocks.

This paper examines correlation and dependence structures between money and the level of economic activity in the USA in the context of a Markov-switching copula vector error correction model. We use the error correction model to focus on the short-run dynamics between money and output while accounting for their long-run equilibrium relationship. We use the Markov regime-switching model to account for instabilities in the relationship between money and output, and also consider different copula models with different dependence structures to investigate (upper and lower) tail dependence.

We use nonparametric and parametric demand analysis to empirically estimate a credit card-augmented monetary asset demand system, based on the Minflex Laurent flexible functional form, and a sample period that includes the 2007–2009 global financial crisis and the COVID-19 pandemic. We also use multivariate copulae in an attempt to capture various patterns of dependence structures. In doing so, we relax the joint normality assumption of the errors of the demand system and estimate the model without having to delete one equation as is usually the practice. We show that the Minflex Laurent copula-based demand system produces a higher income elasticity for credit card transaction services and higher Morishima elasticities between credit card transaction services and monetary assets compared to the traditional estimation of the Minflex Laurent demand system. We also show that credit cards are substitutes for monetary assets and that there is lower tail dependence between the demand for credit card transaction services and transaction balances.

This study empirically examines whether shock size matters for the US monetary policy effects. Using a nonlinear local projection method, I find that large monetary policy shocks are less powerful than smaller monetary policy shocks, with the information effect being the potential source of the observed asymmetry in monetary policy efficacy.

This paper examines the effect of a tariff on long-run growth and welfare in a two-country innovation-led growth model. We show that although raising the home country’s tariff reduces the growth and GDP of the foreign country, it will backfire by depressing R&D and growth of the home country. The Nash equilibrium tariffs can be positive, and they are larger when the government expenditure is more beneficial to private production and/or when the productivity of innovation is higher. The presence of positive Nash equilibrium tariffs provides a theoretical explanation for why countries have incentives to implement a tariff policy regardless of its negative effect on growth. Finally, the Nash equilibrium tariffs are higher than the globally optimal tariffs, that is, the levels that maximize the joint welfare of both countries.