From Products to Capabilities: Constructing a Genotypic Product Space

Economic development is a path-dependent process in which countries accumulate capabilities that allow them to move into more complex products and industries. Inspired by a theory of capabilities that explains which countries produce which products, these diversification dynamics have been studied in great detail in the literature on economic complexity analysis. However, so far, these capabilities have remained latent and inference is drawn from product spaces that reflect economic outcomes: which products are often exported in tandem. Borrowing a metaphor from biology, such analysis remains phenotypic in nature. In this paper we develop a methodology that allows economic complexity analysis to use capabilities directly. To do so, we interpret the capability requirements of industries as a genetic code that shows how capabilities map onto products. We apply this framework to construct a genotypic product space and to infer countries’ capability bases. These constructs can be used to determine which capabilities a country would still need to acquire if it were to diversify into a given industry. We show that this information is not just valuable in predicting future diversification paths and to advance our understanding of economic development, but also to design more concrete policy interventions that go beyond targeting products by identifying the underlying capability requirements. 

Export-led Growth

In this paper, I argue that a focus on exports, both at the intensive margin (where existing products increase their volume), but especially at the extensive margin (where new products start being exported), can help countries figure out what policies to adopt in order to achieve sustained growth. I present five stylised facts about growth and its trends in the decades that followed the Washington Consensus. 

Women Seeking Jobs with Limited Information: Evidence from Iraq

Do women apply more for jobs when they know the hiring probability of female job seekers directly from employers? I implemented a randomized control trial and a double-incentivized resume rating to elicit the preferences of employers and job seekers for candidates and vacancies in Iraq. The treatment reveals the job offer rate for women, calculated using the employers’ selection of women divided by the total number of female candidates. After revealing the treatment, the women applied for jobs by three more percentage points than the men in the control group. This paper highlights the value of revealing employers’ preferences to improve the match between female candidates and employers when women underestimate the chances of finding a job. 

On the Design of Effective Sanctions: The Case of Bans on Exports to Russia

We build on Baqaee and Farhi (2019, 2021) and derive a theoretically-grounded criterion that allows targeting bans on exports to a sanctioned country at the level of ∼5000 6-digit HS products. The criterion implies that the costs to the sanctioned country are highly convex in the market share of the sanctioning parties. Hence, there are large benefits from coordinating export bans among a broad coalition of countries. Applying our results to Russia reveals that sanctions imposed by the EU and the US in response to Russia’s invasion of Ukraine are not systematically related to our arguments once we condition on Russia’s total imports of a product from participating countries. We discuss drivers of these differences, and then provide a quantitative evaluation of the export bans to show that (i) they are very effective with the welfare loss typically ∼100 times larger for Russia than for the sanctioners; (ii) improved coordination of the sanctions and targeting sanctions based on our criterion allows to increase the costs to Russia by about 80% with little to no extra cost to the sanctioners; and (iii) there is scope for increasing the cost to Russia further by expanding the set of sanctioned products.

Pandemic-era Inflation Drivers and Global Spillovers

We estimate a multi-country multi-sector New Keynesian model to quantify the drivers of domestic inflation during 2020–2023 in several countries, including the United States. The model matches observed inflation together with sector-level prices and wages. We further measure the relative importance of different types of shocks on inflation across countries over time. The key mechanism, the international transmission of demand, supply and energy shocks through global linkages helps us to match the behavior of the USD/Euro exchange rate. The quantification exercise yields four key findings. First, negative supply shocks to factors of production, labor and intermediate inputs, initially sparked inflation in 2020–2021. Global supply chains and complementarities in production played an amplification role in this initial phase. Second, positive aggregate demand shocks, due to stimulative policies, widened demand-supply imbalances, amplifying inflation further during 2021–2022. Third, the reallocation of consumption between goods and service sectors, a relative sector-level demand shock, played a role in transmitting these imbalances across countries through the global trade and production network. Fourth, global energy shocks have differential impacts on the US relative to other countries’ inflation rates. Further, complementarities between energy and other inputs to production play a particularly important role in the quantitative impact of these shocks on inflation.

COVID-19 and emerging markets: A SIR model, demand shocks and capital flows

We quantify the macroeconomic effects of COVID-19 for a small open economy. We use a two-country framework combined with a sectoral SIR model to estimate the effects of collapses in foreign demand and supply. The small open economy (country one) suffers from domestic demand and supply shocks due to its own pandemic. In addition, there are external shocks coming from the rest of the world (country two). Aggregate exports of the small open economy decline when foreign demand goes down, and aggregate imports suffer from lockdowns in the rest of the world. We calibrate the model to Turkey. Our results show that the optimal policy, which yields the lowest output loss and saves the maximum number of lives, for the small open economy, is an early and globally coordinated full lockdown of 39 days.

Pretending to be the Law: Violence to Reduce the COVID-19 Outbreak

Did the COVID-19 pandemic create an opportunity to earn population control through illegal violence? We argue that criminal groups in Colombia portray as de facto police by using mass killings to reduce the COVID-19 outbreak. They used massacres as a threat to enforce social distance measures in places they considered worth decreasing mobility. Our results from an Augmented Synthetic Control Method model estimated that commuting to parks fell 20% more in areas with massacres than in places without mass killings. In addition, we do not find a decline in mobility to workplaces and COVID-19 deaths after the first mass killing. These findings are congruent with the hypothesis that illegal armed groups used fear to enforce mobility restrictions without hurting economic activities and their sources of revenue. However, violence slightly impacted the virus’ spread. Treated areas had a decline of 35 cases per 100,000 inhabitants four months after the first massacre.

Economic Costs of Friend-shoring

The nature of international trade has changed significantly since the early 1990s: the liberalisation of cross-border transactions, advances in information and communication technology, reductions in transport costs, and innovations in logistics have given firms greater incentives to break up the production process and locate its various stages across many countries. As a result, global supply chains have become very common, accounting for around a half of global trade in 2020 (World Bank 2020).

The prevalence of global value chains has been underpinned by the well-functioning international trade rule enshrined in the General Agreement on Tariffs and Trade (GATT) and later the WTO, as well as regional agreements. However, geopolitical tensions and disruptions to global value chains – ranging from cyber-threats, the US-China trade war (Fajgelbaum et al. 2022), and the Russian invasion of Ukraine to systemic issues such as the Covid-19 pandemic and the climate crisis – have led policymakers to re-evaluate their approach to globalisation. Many countries are considering ‘friend-shoring’ – trading primarily with countries sharing similar values (such as democratic institutions or maintaining peace) – as a way of minimising exposure to weaponisation of trade and securing access to critical inputs, particularly those required for green transition (Arjona et al. 2023, Attinasi et al. 2023).

In contrast to optimisation under free trade, friend-shoring – by imposing constraints – is likely to be less efficient. But how high is the price that needs to be paid for the alleged insurance benefits brought about by friend-shoring? To shed some light on this question, this chapter assesses the economic costs of friend-shoring, with a focus on broadly defined emerging Europe and European neighbourhood economies. We make three main points. First, we show that, in the medium run, friend-shoring is bad for most economies and generally leads to real output losses globally. Second, only countries that manage to remain non-aligned may see real output gains, but these gains are much smaller than the losses incurred by other countries and not guaranteed. Third, economic costs of friend-shoring are higher than the economic costs of sanctions imposed on Russia after its invasion of Ukraine.

Gravity with History: On Incumbency Effects in International Trade

We introduce incumbency effects into a tractable dynamic model of international trade. The framework nests the canonical Melitz (2003)-Chaney (2008) model as a special case. The key novelty is that fixed costs of market access decrease with tenure. As a consequence, there is less market exit and entry in response to a shock. We derive a gravity equation and show that, ceteris paribus, countries that liberalized their trade relationship earlier trade more today. We provide supporting evidence for the underlying mechanism and derive an augmented ACR formula (Arkolakis et al., 2012) for the gains from trade that accounts for incumbency effects. A quantitative analysis suggests that our mechanism can explain up to 25% of countries’ home shares and that the gains from trade are, on average, 10% larger when accounting for incumbency effects. The analysis further reveals novel distributional effects of trade that benefit real wages but reduce profits.

Eight Decades of Changes in Occupational Tasks, Computerization and the Gender Pay Gap

We build a new longitudinal dataset of job tasks and technologies by transforming the U.S. Dictionary of Occupational Titles (DOT, 1939 -1991) and four books documenting occupational use of tools and technologies in the 1940s, into a database akin to, and comparable with its digital successor, the O*NET (1998 -today). After creating a single occupational classification stretching between 1939 and 2019, we connect all DOT waves and the decennial O*NET databases into a single dataset, and we connect these with the U.S. Decennial Census data at the level of 585 occupational groups. We use the new dataset to study how technology changed the gender pay gap in the United States since the 1940s. We find that computerization had two counteracting effects on the pay gap -it simultaneously reduced it by attracting more women into better-paying occupations, and increased it through higher returns to computer use among men. The first effect closed the pay gap by 3.3 pp, but the second increased it by 5.8 pp, leading to a net widening of the pay gap.