Research

This paper investigates the dynamic causal effects of monetary policy on carbon emissions in the United States through a Structural Vector Autoregression (SVAR) model. I find that, contrary to conventional wisdom, a contractionary monetary policy shock leads to a significant increase in total carbon emissions from energy consumption, even as economic activity declines. The impact is sizeable, as a 25-basis-point tightening leads to a rise in emissions of about one percent. This countercyclical response is driven by contrasting sectoral dynamics: whereas emissions from the industrial sector decline, as expected, emissions from non-industrial sectors rise significantly in the short run. A detailed analysis reveals that the channels of monetary policy transmission vary in strength and relevance across sectors and help explain these heterogeneous responses: while the conventional aggregate demand channel plays a central role in the response of industrial sector emissions, the evidence suggests a more significant role of commodity price and energy reallocation channels for the transmission of shocks to non-industrial sectors.

Awards: Best Paper presented by a Junior Researcher at the 2nd edition of the UEA ECO Time Series Workshop

We study how manufacturing establishments in India respond to flood risk. Using establishment-level data merged with geo-coded flood records and regional economic indicators, we estimate how firms adjust production and investment decisions following flood events, conditional on historical exposure. We document that investment is more resilient in districts with greater historical flood exposure, consistent with forward-looking adaptation behavior. To rationalize these findings, we develop a dynamic spatial model of firm dynamics featuring location-specific flood risk and firm-level adaptation through investment in a distinct type of capital—flood-preventing capital—which mitigates damages from flooding. To overcome the curse of dimensionality inherent in solving this class of models under aggregate uncertainty, we implement Deep Learning techniques. We use the model to assess the aggregate economic costs of floods and to quantify the effectiveness of private adaptation mechanisms, finding that our proposed framework successfully replicates the empirical patterns observed in the data.

In 2008 two Ponzi schemes, DMG and DRFE, were shut down by the Colombian government. Using matched administrative data for a sample of almost a quarter of a million of their investors, we analyze the household risk factors associated with three main outcomes: the probability of investing, the likelihood of making a profit, and the size of financial gains or losses relative to deposits. We find that education, age, and household wealth are positively associated with these outcomes, though effects are often non-linear and vary across margins. Geographical location is also important: individuals residing in the regions of origin of the schemes were substantially more likely to invest, profit, and achieve higher returns, suggesting a role for timing and access in driving outcomes. While higher education, which has been shown to be highly correlated with measures of financial literacy, improves outcomes, even the most educated groups suffered substantial losses on average. Our findings contribute to the literature on household finance, financial education, and financial literacy, and have implications for the design and targeting of financial education programs, particularly in settings with weak regulatory oversight and limited financial literacy.

Political momentum towards Africa-wide free trade has been intensifying. In March 2018, over 40 countries signed the African Continental Free Trade Area (AfCFTA) agreement. Once fully implemented, the AfCFTA is expected to cover all 55 African countries, with a combined GDP of about US$2.2 trillion. This SDN takes stock of recent trade developments in Sub-Saharan Africa and assesses the potential benefits and costs of the AfCFTA, as well as challenges to its successful implementation. In addition to increased trade flows both in existing and new products, the AfCFTA has the potential to generate substantial economic benefits for African countries. These benefits include higher income arising from increased efficiency and productivity from improved resource allocation, higher cross-border investment flows, and technology transfers. Besides lowering import tariffs, to ensure these benefits, African countries will need reduce other trade barriers by making more efficient their customs procedures, reducing their wide infrastructure gaps, and improving their business climates. At the same time, policy measures should be taken to mitigate the differential impact of trade liberalization on certain groups as resources are reallocated in the economy and activities migrate to locations with comparatively lower costs.

Media coverage: Brookings, Afrobarometer 

A trade gravity model is used to calculate the bilateral export potential of Southern Cone countries (Argentina, Brazil, Chile, Paraguay, and Uruguay) and identify patterns of weak performance across destinations and productive sectors. After controlling for key trade fundamentals and country and time effects, we find that exports to large advanced economies like the United States and the European Union fall short of expected levels. Potential trade with the rest of Latin America shows a high degree of heterogeneity across sectors and countries. Exports within the Southern Cone are generally above the predicted value, but there is still space for higher flows, particularly regarding Chile-MERCOSUR relations.