Research

Does the effect of monetary policy depend on the prevailing level of inflation? In order to answer this question, we construct a parsimonious nonlinear time series model that allows for inflation regimes. We find that the effects of monetary policy are markedly different when year-over-year inflation exceeds 5.5 percent. Below this threshold, changes in monetary policy have a short-lived effect on prices, but no effect on the unemployment rate, giving a potential explanation for the recent “soft-landing” in the United States. Above this threshold, the effects of monetary policy surprises on both inflation and unemployment can be larger and longer-lasting.

What are the effects of fiscal shocks on the economy, and do they change over time? This is a long standing question in macroeconomic analysis, but we show that recent advances in data collection at very disaggregated and high frequency levels can help us answer it. This paper makes two main contributions to the literature. The first contribution is the construction of a new dataset of county-level government spending shocks in US data, available at several frequencies, including monthly, quarterly, and yearly frequencies at the most disaggregated county-level data, as well as daily frequencies at the aggregate national level. The second contribution is to shed light on the time-varying effects of fiscal policy shocks at a very disaggregated level by leveraging on the richness of the new data set. We find that the COVID-19 pandemic was associated with unprecedented challenges in the ability of governments to stimulate the economy: economic variables significantly respond to government spending shocks before and after the pandemic, while there are no significant responses during the pandemic. The fiscal stimulus that occurred before the pandemic had persistent effects over time, suggesting that the economic slowdown during those years could have been even more severe without it.

Central to macroeconomic analysis is the study of the propagation of structural shocks, normally performed via the estimation of IRFs. Such an investigation often employs one of two popular empirical tools: VARs or LPs. Despite the apparent differences between such approaches, recent studies have shown that both estimate the same impulse responses in population. However, this result has been proven exclusively for linear models. Given this result in linear models, a natural question that arises is: does the equivalence also hold for the estimation of the thresholds in their regime-dependent counterparts? To answer it, we employ the joint threshold estimator for a TVAR proposed by Gargiulo (2026). Then, we show how such estimator can be employed within a regime-dependent LP framework and provide an analytical comparison between the two models’ threshold estimates. We find conditions for the equivalence of the estimates.

This paper presents MEGAIReF, a medium-scale estimated dynamic stochastic general equilibrium (DSGE) model for the Spanish economy. The model describes a small open economy with heterogeneous households —Ricardian and Hand-to-Mouth— nominal rigidities in price and wage setting, and real rigidities such as monopolistic competition, investment adjustment costs, and a frictional labor market giving rise to unemployment dynamics. It also incorporates a banking sector with financial intermediation frictions, generating a financial accelerator mechanism. In addition, MEGAIReF features a comprehensive fiscal block encompassing multiple expenditure categories —public consumption, public investment, and public employment— as well as a detailed specification of revenue instruments, including taxes on consumption, labor income, and personal and corporate income. All fiscal instruments respond endogenously to macroeconomic conditions through a set of estimated fiscal rules. The model is estimated with Bayesian methods using data for Spain and the Euro area.