Catalina Martínez Hernández
Economics
- Division
Prices & Costs
- Current Position
-
Economist
- Fields of interest
-
Macroeconomics and Monetary Economics,Mathematical and Quantitative Methods
- Education
- 2015-2021
PhD in Economics, Freie Universität Berlin, Germany
- 2013-2015
MA in Economics, Universität Konstanz, Germany
- 2007-2012
Licenciatura en Economía, Universidad de Guanajuato, Mexico
- Professional experience
- 2023-
Economist, Prices and Costs Division, Directorate General Economics, European Central Bank
- 2023
Economist Graduate Programme Participant - Monetary Policy Research Division, Directorate General Research, European Central Bank
- 2021-2023
Economist Graduate Programme Participant - Forecasting and Policy Modelling Division, Directorate General Economics, European Central Bank
- 2018-2021
Research Associate, Freie Universität Berlin
- 2019-2020
PhD Trainee, Supply Side, Labour and Surveillance Division, Directorate General Economics, European Central Bank
- 2019
CSWEP Summer Research Fellow, Research Department, Federal Reserve Bank of Dallas
- 21 March 2024
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2024Details
- Abstract
- This box looks at errors in Eurosystem and ECB staff inflation projections over the post-pandemic period, updating and extending earlier analysis published in 2022 and 2023. Projection errors have come down considerably since the end of 2022 and now stand close to pre-pandemic levels. The low predictability of energy commodity prices (which surprised markets on the downside in 2023) explains a significant share of the recent errors in HICP inflation projections. The remaining errors are likely to stem from non-standard transmission of the exceptional shocks to commodity prices and global supply chains – which, together with demand shocks, explain a large share of the post-pandemic dynamics of HICP inflation excluding food and energy (HICPX), including in 2023. Eurosystem and ECB staff continue to refine their forecasting toolkits, providing additional analysis that informs projections in times of high uncertainty.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 19 March 2024
- RESEARCH BULLETIN - No. 117Details
- Abstract
- The pandemic's disruption of global supply chains and the spike in natural gas prices following Russia’s invasion of Ukraine were significant drivers of surging inflation. Traditional inflation models often ignore such supply-side shocks, even though they can have a significant and persistent impact on core inflation in the euro area (as measured by rates of change in the Harmonised Index of Consumer Prices excluding the energy and food components). In response, we propose a new model that takes these and other factors into account, particularly as future inflation dynamics could be shaped by the impact of geopolitical tensions on supply chains and the role of gas in the green transition.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models
- 16 November 2023
- WORKING PAPER SERIES - No. 2875Details
- Abstract
- We propose a framework to identify a rich set of structural drivers of inflation in order to understand the role of the multiple and concomitant sources of the post-pandemic inflation surge. We specify a medium-sized structural Bayesian VAR on a comprehensive set of variables for the euro area economy. We analyse in particular various types of supply shocks, some of which were not considered relevant before the pandemic, notably global supply chain shocks and gas price shocks. The residuals of the VAR are assumed to admit a factor structure and the shocks are identified via zero and sign restrictions on factor loadings. The framework can deal with ragged-edge data and extreme observations. Shocks linked to global supply chains and to gas prices have exhibited a much larger influence than in the past. Overall, supply shocks can explain the bulk of the post-pandemic inflation surge, also for core inflation. Being able to gauge the impact of such shocks is useful for policy making. We show that a counterfactual core inflation measure net of energy and global supply chain shocks has been more stable after the pandemic.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
- 10 October 2023
- RESEARCH BULLETIN - No. 111Details
- Abstract
- Climate change has implications for price stability and the work of central banks. It may increase the volatility and heterogeneity of inflation, and hotter summers may lead to more frequent and persistent upward pressures on food and services inflation. Our empirical study provides evidence for the four largest euro area economies and outlines the relationship between temperature and inflation.
- JEL Code
- Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 25 September 2023
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 6, 2023Details
- Abstract
- The strong rebound in the labour force is a notable development in the euro area labour market and supported the resilient employment growth in recent quarters. In particular, over the last year and a half the main source of employment growth has been the strong inflow of people joining the labour force rather than a fall in the number of unemployed. This box provides an overview of recent euro area labour force developments, using data from Eurostat and the ECB Consumer Expectations Survey. It also analyses the drivers of the euro area labour force using a mixed-frequency Bayesian VAR to disentangle the push and pull factors behind the labour force dynamics.
- JEL Code
- E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
J21 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Force and Employment, Size, and Structure
- 22 March 2023
- WORKING PAPER SERIES - No. 2798Details
- Abstract
- This paper assesses the impact of weather shocks on inflation components in the four largest euro area economies. We combine high-frequency weather data with monthly data on inflation and output growth within a set of Bayesian Vector Autore-gressions which explicitly considers the seasonal dependence of the shock. Results suggest the presence of significant country asymmetries and seasonal responses of inflation to temperature shocks, mainly via food, energy, and service prices. An increase in monthly mean temperatures has inflationary effects in summer and au-tumn, with a stronger response in warmer euro area countries. An increase in temperature variability has significant upward impacts on inflation rates over and above the impacts of changes in means.
- JEL Code
- Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 8 October 2021
- WORKING PAPER SERIES - No. 2601Details
- Abstract
- We introduce a Bayesian Mixed-Frequency VAR model for the aggregate euro area labour market that features a structural identification via sign restrictions. The purpose of this paper is twofold: we aim at (i) providing reliable and timely forecasts of key labour market variables and (ii) enhancing the economic interpretation of the main movements in the labour market. We find satisfactory results in terms of forecasting, especially when looking at quarterly variables, such as employment growth and the job finding rate. Furthermore, we look into the shocks that drove the labour market and macroeconomic dynamics from 2002 to early 2020, with a first insight also on the COVID-19 recession. While domestic and foreign demand shocks were the main drivers during the Global Financial Crisis, aggregate supply conditions and labour supply factors reflecting the degree of lockdown-related restrictions have been important drivers of key labour market variables during the pandemic.
- JEL Code
- J6 : Labor and Demographic Economics→Mobility, Unemployment, Vacancies, and Immigrant Workers
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
- 2024
- European Economic Review
- 2023
- Oxford Bulletin of Economics and Statistics
- 2014
- PLoS ONE