Working Papers

  • "Quantitative Analysis of Climate Heterogeneity via an Unconditional Quantile Vector Error Correction Model"
    • Abstract This paper introduces a time-series methodology to quantify heterogeneity in the dynamics of the unconditional temperature distribution and its association with climate drivers. By recognizing that temperature unconditional quantiles represent temperatures at different locations—or seasons—, I establish an equivalence between a structural One-Dimensional Energy Balance Model (1D-EBM) and a statistical reduced-form Vector Error Correction Model (VECM) for a range of distributional characteristics of temperature—mean and quantiles—and total radiative forcing, including radiative forcing from anthropogenic greenhouse gases (GHGs). The VECM is estimated employing time-series methods agnostic about the type of trends (stochastic or deterministic) in climate data, and is utilized to produce the following outcomes of practical interest for economic analyses: i) estimation of long-run responses of temperature distribution to changes in GHGs, ii) long-term temperature density forecasts, iii) conditional projections of temperature distribution under different scenarios of future GHGs emissions, iv) extraction of the common-trending component behind the existing warming trend, and v) identification of distributional climate shocks and impulse-response analysis. An empirical study using station-level temperature records (1880–2021) reveals strong climate heterogeneity at global, hemispheric, and continental (Europe) scales, with important potential implications for damage analysis and integrated assessment modeling. A deeper understanding of global warming dynamics is crucial for informing more efficient adaptation and mitigation policies.

  • "Becoming Green: Decomposing the Macroeconomic Effects of Green Technology News Shocks", with Oscar Jaulín
    Abstract This paper studies the macroeconomic effects of news about future technological advancements in the green sector. Utilizing the economic value of green patents granted to publicly listed companies in the U.S., we identify green technology news shocks via a convenient and meaningful rotation of the innovations from a Bayesian Vector Autorregresion Model (BVAR). These shocks are decomposed into two orthogonal components: i) a common technological component shared by both green and non-green innovation, that reproduces response patterns similar to those expected from a technology news shock with long-run impacts on productivity; and ii) an idiosyncratic component to green innovation inducing inflationary pressures and stock price reductions. The responses to the idiosyncratic component suggest the existence of a green transition news mechanism related to expectations of more rigorous carbon policies or stricter environmental standards in the future. The focus on green innovation deepens our understanding about the effect of technology-specific news shocks and provides information of practical importance for macroeconomic and environmental policies.

  • "High-frequency Density Nowcasts of State-Level Carbon Dioxide (CO2) Emissions in the U.S.", with Ignacio Garrón
    Abstract Accurate tracking of anthropogenic carbon dioxide (CO2) emissions is crucial for shaping climate policies and meeting global decarbonization targets. However, energy consumption and emissions data are released annually and with substantial publication lags, hindering timely decision-making. This paper introduces a panel nowcasting framework to produce higher-frequency predictions of the state-level growth rate of per-capita energy consumption and CO2 emissions in the United States (U.S.). Our approach employs a panel mixed-data sampling (MIDAS) model to predict per-capita energy consumption growth, considering quarterly personal income, monthly electricity consumption, and the weekly economic conditions index as predictors. A bridge equation linking per-capita CO2 emissions growth with the nowcasts of energy consumption is estimated using panel quantile regression methods. A pseudo out-of-sample study (2009-2018), simulating the real-time data release calendar, confirms the improved accuracy of our nowcasts with respect to a historical benchmark. Our results suggest that by leveraging the availability of higher-frequency indicators, we not only enhance predictive accuracy for per-capita energy consumption growth but also provide more reliable estimates of the distribution of CO2 emissions growth.

  • "Here Comes the Rain: Weather Shocks and Economic Outcomes in Ecuador", with Gustavo Canavire and Alejandro Puerta
    Abstract This paper examines the heterogeneous effect of precipitation shocks on poverty status in Ecuador. Using gridded monthly precipitation data from 2007 to 2021, we define measures for the excess and deficit in precipitation levels at the parish geographical level. Weather data are merged with household socioeconomic information derived from the National Survey of Employment, Unemployment, and Underemployment (ENEMDU). Our empirical findings reveal that both excess and deficit in precipitation significantly affect poverty status, with considerable heterogeneity across economic sectors. Variations in the Standardized Precipitation Index, whether positive or negative, lead to an increased probability of poverty among workers in the primary sector. In contrast, we find poverty-reducing effects in the secondary and tertiary sectors, with their magnitude being shaped by formality status, urban/rural location, and self-employment status. The analysis identifies per-capita household income and labor earnings as key transmission channels, with precipitation shocks having redistributive effects on labor income in the tertiary sector, while amplifying inequality in the primary sector.

    Publications

  • "On the Effects of Wildfires on Poverty in Bolivia", (2025) with Gustavo Canavire and Alejandro Puerta
    Journal of Development Economics, 175: 103494. doi.org/10.1016/j.jdeveco.2025.103494

  • "Trends in Temperature Data: Micro-foundations of Their Nature", (2024) with Lola Gadea and Jesús Gonzalo
    Economics Letters, 244: 111992. doi: 10.1016/j.econlet.2024.111992
    Replication files

  • "Which Crisis Support Fiscal Measures Worked During the Covid-19 Shock in Europe?", (2024) with Evi Pappa and Eugenia Vella
    SERIEs Journal of the Spanish Economics Association, 15: 327-348. doi: 10.1007/s13209-023-00288-w
    Replication files

  • "Heterogeneous Predictive Association of CO2 with Global Warming", (2023) with Liang Chen, Juan J. Dolado, and Jesús Gonzalo
    Economica, 90(360): 1397-1421. doi: 10.1111/ecca.12491

    • Work in Progress

  • Macroeconomic Effects of Temperature Distributional Shocks (with Lola Gadea and Jesús Gonzalo)
    • Abstract This paper introduces a methodology to examine the macroeconomic impacts of temperature distributional shocks, that is, shocks to the average and quantiles of the temperature process. Distributional shocks are defined as persistent deviations from the long-run trend in the global and local temperature characteristics and are obtained using the Hamilton (2018) filter. Since these shocks are correlated, we employ a factor model to extract the sources of common variation. Our empirical analysis at the global, United States, and Euro Area levels consistently detects three uncorrelated factor shocks, each with significant macroeconomic implications. The first factor, capturing a general distributional effect, leads to persistent declines in output and total factor productivity, aligning with existing studies that treat average temperature as a suf ficient statistic for climate change. The key contribution of this paper to the literature is to uncover two additional factors that do not correlate with the average temperature, but instead influence different parts of the distribution in particular ways. These factors induce additional macroeconomic impacts that have not been documented in previous literature. For instance, the third factor—which affects the lower and the upper extremes of the global or local temperature distributions in the same direction—reduces output and productivity, particularly in the Euro Area. Our findings underscore the usefulness of analyzing the effects of shocks to the full temperature distribution and carry important implications for estimating the social cost of carbon and assessing climate-related economic risks.

  • Macroeconomic Outcomes at Risk and the Time-Varying Effect of Climate Shocks (with Ignacio Garrón and Oscar Jaulín)