Muhammed Yildirim

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.

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.

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.

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.

Geo-political tensions and disruptions to global value chains have led policymakers to reevaluate their approach to globalisation. Many countries are considering regionalisation and friend-shoring – trading primarily with countries sharing similar values – as a way of minimising exposure to weaponisation of trade and securing access to critical inputs. If followed through, this process has the potential to reverse global economic integration of recent decades. This paper estimates the economic costs of friend-shoring using a quantitative model incorporating inter-country inter-industry linkages. The results suggest that friend-shoring may lead to real GDP losses of up to 4.6% of global GDP. Thus, although friend-shoring may provide insurance against extreme disruptions and increase the security of supply of vital inputs, it would come at a significant cost.

We analyze the effects of bans on exports at the level of 5,000 products and show how our results can inform economic sanctions against Russia after its invasion of Ukraine. We begin with characterizing export restrictions imposed by the EU and the US until mid May 2022. We then propose a theoretically-grounded criterion for targeting export bans at the 6-digit HS level. Our results show that the cost to Russia are highly convex in the market share of the sanctioning parties, i.e., there are large benefits from coordinating export bans among a broad coalition of countries. Applying our results to Russia, we find that sanctions imposed by the EU and the US are not systematically related to our arguments once we condition on Russia’s total imports of a product from participating countries. Quantitative evaluations of the export bans show (i) that 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 60% with little to no extra cost to the sanctioners. (iii) There is scope for increasing the cost to Russia further by expanding the set of sanctioned products.

Wall Street Journal: Sanctions Against Russia Could Be Better, These Harvard Economists Say

Video summary: How can sanctions against Russia be more effective?

We study the impact of the Covid-19 pandemic on Euro Area inflation and how it compares to the experiences of other countries, such as the United States, over the two-year period 2020-21. Our model-based calibration exercises deliver four key results: 1) Compositional effects – the switch from services to goods consumption – are amplified through global input-output linkages, affecting both trade and inflation. 2) Inflation can be higher under sector-specific labor shortages relative to a scenario with no such supply shocks. 3) Foreign shocks and global supply chain bottlenecks played an outsized role relative to domestic aggregate demand shocks in explaining Euro Area inflation over 2020-21. 4) International trade did not respond to changes in GDP as strongly as it did during the 2008-09 crisis despite strong demand for goods. These lower trade elasticities in part reflect supply chain bottlenecks. These four results imply that policies aimed at stimulating aggregate demand would not have produced as high an inflation as the one observed in the data without the negative sectoral supply shocks.

Assignment models in trade predict that countries with higher productivity levels are assortatively matched to industries that make better use of these higher levels. Here, we assume that the driver of productivity differences is the differential distribution of factors among countries. Utilizing such a structure, we define and estimate the average factor level (AFL) for countries and products using only the information about the production patterns. Interestingly, our estimates coincide with the complexity variables of (Hidalgo and Hausmann, 2009), providing an underlying economic rationale. We show that AFL is highly correlated with country-level characteristics and predictive of future economic growth.

COVID-19 pandemic had a devastating effect on both lives and livelihoods in 2020. The arrival of effective vaccines can be a major game changer. However, vaccines are in short supply as of early 2021 and most of them are reserved for the advanced economies. We show that the global GDP loss of not inoculating all the countries, relative to a counterfactual of global vaccinations, is higher than the cost of manufacturing and distributing vaccines globally. We use an economic-epidemiological framework that combines a SIR model with international production and trade networks. Based on this framework, we estimate the costs for 65 countries and 35 sectors. Our estimates suggest that up to 49 percent of the global economic costs of the pandemic in 2021 are borne by the advanced economies even if they achieve universal vaccination in their own countries.

Cities and countries undergo constant structural transformation. Industries need many inputs, such as regulations, infrastructure or productive knowledge, which we call capabilities. And locations are successful in hosting industries insofar as the capabilities that they can provide. We propose a capabilities-based production model and an empirical strategy to measure the Sophistication of a product and the Production Ability of a location. We apply our framework to international trade data and employment data in the United States, recovering measures of Production Ability for countries and cities, and the Sophistication of products and industries. We show that both country- and city-level measures have a strong correlation with income and economic growth at different time horizons. Product Sophistication is positively correlated with indicators of human capital and wages. Our model-based estimations predict product appearances and disappearances through the extensive margin.

Venezuela has seen an unprecedented exodus of people in recent months. In response to a dramatic economic downturn in which inflation is soaring, oil production tanking, and a humanitarian catastrophe unfolding, many Venezuelans are seeking refuge in neighboring countries. However, the lack of official numbers on emigration from the Venezuelan government, and receiving countries largely refusing to acknowledge a refugee status for affected people, it has been difficult to quantify the magnitude of this crisis. In this note we document how we use data from the social media service Twitter to measure the emigration of people from Venezuela. Using a simple statistical model that allows us to correct for a sampling bias in the data, we estimate that up to 2,9 million Venezuelans have left the country in the past year.

The comparative advantage of a location shapes its industrial structure. Current theoretical models based on this principle do not take a stance on how comparative advantages in different industries or locations are related with each other, or what such patterns of relatedness might imply about the underlying process that governs the evolution of comparative advantage. We build a simple Ricardian-inspired model and show this hidden information on inter-industry and inter-location relatedness can be captured by simple correlations between the observed patterns of industries across locations or locations across industries. Using the information from related industries or related locations, we calculate the implied comparative advantage and show that this measure explains much of the location’s current industrial structure. We give evidence that these patterns are present in a wide variety of contexts, namely the export of goods (internationally) and the employment, payroll and number of establishments across the industries of subnational regions (in the US, Chile and India). The deviations between the observed and implied comparative advantage measures tend to be highly predictive of future industry growth, especially at horizons of a decade or more; this explanatory power holds at both the intensive as well as the extensive margin. These results suggest that a component of the long-term evolution of comparative advantage is already implied in today’s patterns of production.