Working Papers
2024
October 11, 2024
Reported Social Unrest Index: September 2024 Update
Description: This is the third update of the reported Social Unrest Index (Barrett et al. 2022), describing the evolution of social unrest worldwide since June 2023. It shows that the global incidence of unrest has stayed broadly stable in the last year. However, the global distribution has not been even, with a concentration of major events in Europe and sub-Saharan Africa and, to a lesser extent, in the Western Hemisphere.
October 11, 2024
What Can Artificial Intelligence Do for Stagnant Productivity in Latin America and the Caribbean?
Description: Since 1980, income levels in Latin America and the Caribbean (LAC) have shown no convergence with those in the US, in stark contrast to emerging Asia and emerging Europe, which have seen rapid convergence. A key factor contributing to this divergence has been sluggish productivity growth in LAC. Low productivity growth has been broad-based across industries and firms in the formal sector, with limited diffusion of technology being an important contributing factor. Digital technologies and artificial intelligence (AI) hold significant potential to enhance productivity in the formal sector, foster its expansion, reduce informality, and facilitate LAC’s convergence with advanced economies. However, there is a risk that the region will fall behind advanced countries and frontier emerging markets in AI adoption. To capitalize on the benefits of AI, policies should aim to facilitate technological diffusion and job transition.
October 4, 2024
Global Shocks Unfolding: Lessons from Fragile and Conflict-affected States
Description: This paper investigates the consequences of global shocks on a sample of low- and lower-middle-income countries with a particular focus on fragile and conflict-affected states (FCS). FCS are a group of countries that display institutional weakness and/or are negatively affected by active conflict, thereby facing challenges in macroeconomic policy management. Examining different global shocks associated with commodity prices, external demand, and financing conditions, this paper establishes that FCS economies are more vulnerable to these shocks compared to non-FCS peers. The higher sensitivity of FCS economies is mainly driven by procyclical fiscal responses, aggravated by the lack of effective spending controls and timely access to financial sources. External financing serves as a source of stability, partially mitigating the adverse impact of global shocks. This paper contributes to a better understanding of how conditions of fragility, which are on the rise in many parts of the world today, can amplify the effects of negative exogenous shocks. Its results highlight the diverse nature of underlying sources of vulnerabilities, spanning from fiscal and external buffers to institutional quality and economic structure, with lessons applicable to a broader set of countries. Efficient and timely external financial support from external partners, including international financial institutions, should help countries’ counter-cyclical responses to mitigate adverse shocks and achieve macroeconomic stability.
October 4, 2024
The Economics of Decarbonizing Electricity Production
Description: Electricity production is the sector with the largest share of global emissions and there are many options for decarbonizing it. Identifying the lowest cost option for achieving decarbonization (and full reliability) is a complex optimization problem at the intersection of economics and engineering. Key determinants are the cost of individual technologies, the geographical potential, the complementarities between energy sources and supporting infrastructure like electricity grids and energy storage. This paper reviews the literature on the subject and draws high-level conclusions from the abundance of specialized analyses. It finds that energy-economy models have strongly changed projections of the optimal electricity mix in recent years. While the models differ in detail, models project that the share of renewable energy, mostly solar and wind power, increases steadily in a “below 2°C” scenario and becomes the dominant source of energy by 2050. An electricity system based on solar and wind power can use flexibility options as a complement instead of baseload energy. Models vary by the degree to which renewable energy is supported by carbon capture and storage, bioenergy, and nuclear energy.
October 4, 2024
Measuring Soft Power: A New Global Index
Description: Soft power is difficult to measure directly, and existing indicators—mostly subjective and not always transparent—fail to take into account the multidimensional nature of soft power. In this paper, we introduce a new comprehensive Global Soft Power Index (GSPI) composed of six dimensions for a broad sample of countries over a long span of time. The proposed framework allows for comparisons not only at the “headline” level of the GSPI, but also at the level of the sub-indices, which in turn helps identify and study how countries differ at a granular level of soft power. In a final step of the analysis, we present a possible macro-financial application to investigate the relationship between soft power and exchange rates. The results indicate that some dimensions of the GSPI play an important role in explaining exchange rate volatility. Overall, the composite GSPI presented in this paper provides a systematic approach to measure soft power along its multiple dimensions. By capturing the matrix of soft power characteristics, the GSPI offers significant advantages in comparative analysis of soft power across countries and over time.
September 27, 2024
Migration into the EU: Stocktaking of Recent Developments and Macroeconomic Implications
Description: Against the backdrop of the war in Ukraine, immigration into the European Union (EU) reached a historical high in 2022 and stayed significantly above pre-pandemic levels in 2023. The recent migration has helped accommodate strong labor demand, with around two-thirds of jobs created between 2019 and 2023 filled by non-EU citizens, while unemployment of EU citizens remained at historical lows. Ukrainian refugees also appear to have been absorbed into the labor market faster than previous waves of refugees in many countries. The stronger-than-expected net migration over 2020-23 into the euro area (of around 2 million workers) is estimated to push up potential output by around 0.5 percent by 2030—slightly less than half the euro area’s annual potential GDP growth at that time—even if immigrants are assumed to be 20 percent less productive than natives. This highlights the important role immigration can play in attenuating the effects of the Europe’s challenging demographic outlook. On the flipside, the large inflow had initial fiscal costs and likely led to some congestion of local public services such as schooling. Policy efforts should thus seek to continue to integrate migrants into the labor force while making sure that the supply of public services and amenities (including at the local level) keeps up with the population increase.
September 27, 2024
An Updated Action-based Dataset of Fiscal Consolidation
Description: This paper presents a dataset of fiscal consolidation for 17 OECD economies during 1978-2020 and 14 economies in Latin America and the Caribbean during 1989-2020. We focus on discretionary changes in taxes and government spending primarily motivated by a desire to reduce the budget deficit and not by a response to prospective economic conditions. To identify the motivation and budgetary impact of the fiscal policy changes, we examine contemporaneous policy documents, including central bank reports, Convergence Programmes and Stability Programmes submitted by the authorities to the European Commission, and IMF and OECD reports. The resulting series can be used to estimate the macroeconomic effects of fiscal consolidation.
September 27, 2024
The Economic Impact of Fiscal Policy Uncertainty: Evidence from a New Cross-Country Database
Description: Fiscal policy uncertainty (FPU)—ambiguity in government spending and tax plans, as well as in public debt valuation—is widely regarded as a source of economic and financial disruptions. However, assessing its impact has so far been limited to a few large economies. In this paper, we construct a novel database of news-based fiscal policy uncertainty for 189 countries. Importantly, we track fiscal uncertainty events that generate global attention that we refer to as the “global fiscal policy uncertainty." This uncertainty has contractionary effects, reducing industrial production in both advanced and emerging market economies, with impacts greater than country-specific fiscal policy uncertainty. Additionally, global fiscal policy uncertainty raises sovereign borrowing costs and generates synchronous movements in the global financial variables, even after accounting for US monetary policy shocks.
September 27, 2024
Transfers, Excess Savings, and Large Fiscal Multipliers
Description: This paper seeks to show that a New Keynesian model can produce highly persistent and large output responses to fiscal transfers and excess wealth, in line with recent empirical literature. The introduction of myopia to households to allow realistic degrees of dissaving from wealth and accumulated transfers, alongside more standard Keynesian features, achieves this goal. Model IRFs closely match the high fiscal multipliers from the tax stimulus SVAR literature, and also have important inflationary consequences. An application of this model to the COVID era, where transfer payments in the United States supported an accumulation of ``excess savings", results in inflation rising by over 1 percentage point for several years as well as a persistent increase in output over the same horizon. Finally, under the same framework and calibration, it is found that high debt and a weak fiscal rule can dull the transmission of monetary policy due to the wealth effect from higher interest payments.
September 27, 2024
Mending the Crystal Ball: Enhanced Inflation Forecasts with Machine Learning
Description: Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting performance by incorporating a wider range of variables, allowing for non-linear relationships, and focusing on out-of-sample performance. In this paper, we apply machine learning (ML) models to forecast near-term core inflation in Japan post-pandemic. Japan is a challenging case, because inflation had been muted until 2022 and has now risen to a level not seen in four decades. Four machine learning models are applied to a large set of predictors alongside two benchmark models. For 2023, the two penalized regression models systematically outperform the benchmark models, with LASSO providing the most accurate forecast. Useful predictors of inflation post-2022 include household inflation expectations, inbound tourism, exchange rates, and the output gap.