This research project characterizes the dynamic behavior of the sectoral structure throughout the growth process. First, it analyzes how the breakdown of the services sector into homogeneous categories in terms of productivity growth determines the relative contribution of the determinants of the evolution of the sector composition. Second, the factorial bias of technical progress and its contribution to the change in the sectoral structure are studied. Third, the importance of the dynamics of consumer decisions on the use of time for the sectoral composition of employment and production is analyzed. Finally, the relationship between demographic dynamics and sectoral composition is characterized.

To study the efficacy of the public policy response to the COVID-19 pandemic, we develop a model of the rich interactions between epidemiology and socioeconomic choices. Preferences feature a “fear of death” that lead individuals to reduce their social activity and work time in the face of the pandemic. The aggregate effect of these reductions is to slow the spread of the coronavirus. We calibrate the model, including public policies, to developments in Ontario in spring 2020. The model fits the epidemiological data quite well, including the second wave starting in late 2020. We find that socioeconomic interventions work well in the short term, resulting in a rapid drop off in new cases. The long run, however, is governed chiefly by health developments. Welfare cost calculations point to synergies between the health and socioeconomic measures.

Our aim is to contribute in our understanding of the processes of technical innovation and capital accumulation in the global economy. Technology interacts with the investment decisions taken by households, firms and governments over the accumulation of physical and human capital, and the management of natural resources and the labor force. This interaction occurs in a global market economy opened to international flows of production factors. In order to advance in our understanding of the aforementioned processes we aim to build theoretical model economies that incorporate their key features and we will test them with econometric tools. We aim to build model economies of i) sustainable growth, ii) inequality, poverty and growth, iii) adoption of technologies and vintage capital iv) energy use and nonrenewable resources, v) international trade and finance vi) fiscal policy, debt and sustainable growth, vii) decentralized trading. The results obtained will help us to propose policy recommendations, for the governance of the global economy as well as Spain and the European Union.

This project investigates the interconnection between, first, energy efficiency innovation, economic development and economic growth; second, between inequality of opportunity, social network, human capital and economic growth; third, between infant health, poverty and weather shocks.

The overarching goal of this project is to study the potential causes behind the dismal performances of many European countries, and to propose policy implications in order to achieve a more resilient and integrated Euro area. The project focuses on two aspects of economic and financial divergence in the euro area. In the first part, by means of recent developments in econometric modelling, we analyze the dynamic interactions between the sovereign yield curves of member countries, and study how monetary, uncertainty and liquidity shocks are transmitted to the interest rates and term premia of member countries. In the second part of the project we study the effect of financial shocks on the process of income and productivity convergence/divergence in a currency union composed by countries with heterogeneous market structures. To this end, we develop a Dynamic Stochastic General Equilibrium (DSGE) New Keynesian model for a currency union. The main innovation is the introduction, in a unified framework, of three key ingredients: 1) Search and matching frictions and sticky wages in the labor market; 2) imperfect competition and sticky prices in the product market; 3) endogenous productivity through R&D investment and intangible capital accumulation in the innovation sector

The goal of this project is to dig deeper on how financial constraints and the process of globalization affect and are affected by productivity and other important macroeconomic factors. To achieve this goal, it concentrates on two main topics for four years. The first one deals with the effects of financial constraints on fiscal policy, the sustainability of the pension system, the provision of electricity infrastructure and its impact on productivity, the demand for education, misallocation, and the firm’s informality. The second part focuses on the relationship of globalization with the labor-market, innovation, natural resources, and product quality.

A project on in a network with more than 25 researchers at 10 different Economics Departments and Research Institutions in Spain. Excellent Research Programme of Grants 2020-2022.

It is a broad project in which we analyze how structural change affects economic growth study the relationship between uses of time and sectoral composition and study how the composition of the agricultural sector affects productivity.

The adoption of new technologies is an important engine of economic growth. This research project focuses on quantitatively assessing the effects of adopting a wide set of new technologies. This assessment is separately contextualized for poor and rich countries. We aim to determine the role of technology adoption as both a sources of both growth (such as productivity and factor accumulation) and a potential source of inequality (such as the potential increase in risk associated to technology adoption and its coping strategies). Welfare assessments will be provided.

This project develops around two main hypotheses. First, agents can learn from financial markets to predict macroeconomic outcomes. At the same time learning dynamics can feedback into both the macroeconomy and financial markets. This research project introduces the term structure of interest rates, which is observed in real-time, in an estimated medium-scale dynamic stochastic general equilibrium model with adaptive learning expectations. Second, real-time data can be an important source of inflation bias. This project introduces a simple model where a central banker might be forced to react quickly to real-time data as a result of short-term pressure coming from other policy makers, economic pundits or public opinion even when the policy maker knows that revised data provide a more accurately measure of the performance of the actual economy.