I am an Assistant Professor in the School of Economics and a member of the Centre for Finance, Credit and Macroeconomics (CFCM) and the Centre for Research on Globalisation and Economic Policy (GEP) at the University of Nottingham.
In my research, I develop cutting-edge theoretical frameworks disciplined by micro and aggregate data to study Macroeconomic issues. My main areas of interest are growth, development, structural change, and human capital.
I received my Ph.D. in Economics from Washington University in St. Louis in 2020.
PhD in Economics, 2020
Washington University in St Louis
We develop a continuous time stochastic growth model that is suitable for studying the impact of natural disasters on the short run and long run growth rate of an economy. We find that the growth effects of a natural disaster depend in complicated ways on the details of expected foreign disaster aid and the existence of catastrophe insurance markets. We show that aid can have an influence on investments in prevention and mitigation activities and can delay the recovery from a natural disaster strike.
Using a broad panel of advanced economies we document that increases in GDP per capita are associated with a systematic shift in the composition of value added to sectors that are intensive in high-skill labor, a process we label as skill-biased structural change. It follows that further development in these economies leads to an increase in the relative demand for skilled labor. We develop a quantitative two-sector model of this process as a laboratory to assess the sources of the rise of the skill premium in the US and a set of ten other advanced economies, over the period 1977 to 2005. For the US, we find that the sector-specific skill neutral component of technical change accounts for 18-24% of the overall increase of the skill premium due to technical change, and that the mechanism through which this component of technical change affects the skill premium is via skill biased structural change.
I study how the productivity of skilled and unskilled labor varies with development. Using harmonized, occupational labor market outcomes for a broad set of countries across the development spectrum, I document that employment in high-skill occupations, or jobs that are relatively more intensive in non-routine cognitive tasks, grows with development. In addition, the income of workers in high-skill occupations falls relative to earnings in low-skill occupations as countries grow richer. To understand the forces driving these findings, I develop a stylized model of the labor market across development. In the model, labor productivity is determined endogenously as a result of the selection of heterogeneous workers into occupations and education. I use a quantitative version of the model to decompose the observed decline in relative labor income between less-developed countries and the US into a component embedded in technologies, or relative skilled labor efficiency, and a fraction due to workers' characteristics, or relative skilled labor quality. I find that relative quality explains 25 percent of the decline in relative labor income, with the remaining fraction due to relative efficiency. In less-developed countries, the relatively few skilled workers are the most productive in performing high-skill jobs, which reduces the magnitude of skill-biased technological progress needed to rationalize the cross-country data by one half when compared to a world where labor quality is purely determined by educational attainment.