Middle East and Central Asia > Qatar

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International Monetary Fund. Middle East and Central Asia Dept.
Growth normalization after the 2022 FIFA World Cup continued with signs of activities strengthening more recently. Fiscal and external surpluses softened mainly due to lower hydrocarbon prices. Banks are healthy but pockets of vulnerabilities remain. Reform momentum has strengthened, guided by the Third National Development Strategy (NDS3).
Yueling Huang
This paper empirically investigates the impact of Artificial Intelligence (AI) on employment. Exploiting variation in AI adoption across US commuting zones using a shift-share approach, I find that during 2010-2021, commuting zones with higher AI adoption have experienced a stronger decline in the employment-to-population ratio. Moreover, this negative employment effect is primarily borne by the manufacturing and lowskill services sectors, middle-skill workers, non-STEM occupations, and individuals at the two ends of the age distribution. The adverse impact is also more pronounced on men than women.
Naomi-Rose Alexander
,
Longji Li
,
Jorge Mondragon
,
Sahar Priano
, and
Marina Mendes Tavares
This study examines the green transition's effects on labor markets using a task-based framework to identify jobs with tasks that contribute, or with the potential to contribute, to the green transition. Analyzing data from Brazil, Colombia, South Africa, the United Kingdom, and the United States, we find that the proportion of workers in green jobs is similar across AEs and EMs, albeit with distinct occupational patterns: AE green job holders typically have higher education levels, whereas in EMs, they tend to have lower education levels. Despite these disparities, the distribution of green jobs across genders is similar across countries, with men occupying over two-thirds of these positions. Furthermore, green jobs are characterized by a wage premium and a narrower gender pay gap. Our research further studies the implications of AI for the expansion of green employment opportunities. This research advances our understanding of the interplay between green jobs, gender equity, and AI and provides valuable insights for promoting a more inclusive green transition.
Sophia Chen
,
Ryu Matsuura
,
Flavien Moreau
, and
Joana Pereira
Prioritizing populations most in need of social assistance is an important policy decision. In the Eastern Caribbean, social assistance targeting is constrained by limited data and the need for rapid support in times of large economic and natural disaster shocks. We leverage recent advances in machine learning and satellite imagery processing to propose an implementable strategy in the face of these constraints. We show that local well-being can be predicted with high accuracy in the Eastern Caribbean region using satellite data and that such predictions can be used to improve targeting by reducing aggregation bias, better allocating resources across areas, and proxying for information difficult to verify.
Chandana Kularatne
,
Ken Miyajima
, and
Dirk V Muir
Qatar’s state-led, hydrocarbon intensive growth model has delivered rapid growth and substantial improvements in living standards over the past several decades. Guided by the National Vision 2030, an economic transformation is underway toward a more dynamic, diversified, knowledge-based, sustainable, and private sector-led growth model. As Qatar is finalizing its Third National Development Strategy to make the final leap toward Vision 2030, this paper aims to identify key structural reforms needed, quantify their potential impact on the economy, and shed light on the design of a comprehensive reform agenda ahead. The paper finds that labor market reforms could bring substantial benefits, particularly reforms related to increasing the share of skilled foreign workers. Certain reforms to further improve the business environment, such as improving access to finance, could also have large growth impact. A comprehensive, well-integrated, and properly sequenced reform package to exploit complementarities across reforms could boost Qatar’s potential growth significantly.
Aliona Cebotari
,
Enrique Chueca-Montuenga
,
Yoro Diallo
,
Yunsheng Ma
,
Rima A Turk
,
Weining Xin
, and
Harold Zavarce
The paper explores the drivers of political fragility by focusing on coups d’état as symptomatic of such fragility. It uses event studies to identify factors that exhibit significantly different dynamics in the runup to coups, and machine learning to identify these stressors and more structural determinants of fragility—as well as their nonlinear interactions—that create an environment propitious to coups. The paper finds that the destabilization of a country’s economic, political or security environment—such as low growth, high inflation, weak external positions, political instability and conflict—set the stage for a higher likelihood of coups, with overlapping stressors amplifying each other. These stressors are more likely to lead to breakdowns in political systems when demographic pressures and underlying structural weaknesses (especially poverty, exclusion, and weak governance) are present or when policies are weaker, through complex interactions. Conversely, strengthened fundamentals and macropolicies have higher returns in structurally fragile environments in terms of staving off political breakdowns, suggesting that continued engagement by multilateral institutions and donors in fragile situations is likely to yield particularly high dividends. The model performs well in predicting coups out of sample, having predicted a high probability of most 2020-23 coups, including in the Sahel region.
International Monetary Fund. Middle East and Central Asia Dept.
This Selected Issues paper aims to identify key reforms to accelerate Qatar’s economic transformation, estimate their impact, and shed light on the design of a comprehensive reform agenda. This paper starts by taking stock of Qatar’s progress in key reforms so far, identifying areas for further improvement, proposing structural reform measures, estimating the impact of key proposed reforms, and providing principles on the prioritization and sequencing of reforms. Qatar’s state-led, hydrocarbon intensive growth model has delivered rapid growth and substantial improvements in living standards over the past several decades. Guided by the National Vision 2030, an economic transformation is underway toward a more dynamic, diversified, knowledge-based, sustainable, and private sector-led growth model. The paper finds that labor market reforms could bring substantial benefits, particularly reforms related to increasing the share of skilled foreign workers. Certain reforms to further improve the business environment, such as improving access to finance, could also have large growth impact. A comprehensive, well-integrated, and properly sequenced reform package to exploit complementarities across reforms could boost Qatar’s potential growth significantly.
International Monetary Fund. Middle East and Central Asia Dept.
The 2023 Article IV Consultation highlights that Qatar’s decade-long efforts to diversify the economy culminated into the successful hosting of the 2022 FIFA World Cup. Banks are well capitalized, liquid, and profitable, with the capital adequacy ratio and return on equity at 19 and 14.6 percent, respectively, in the second quarter of 2023. Banks’ nonresident deposits fell by more than one-third from the recent peak, partially replaced by higher public sector domestic deposits, reducing vulnerabilities amid tight global financial conditions. Structural reforms continue to progress, including to enhance protection and mobility of expatriate labor, improve the business environment, promote public–private partnerships, and further attract private investment through the residency program and broadened foreign ownership provisions. The pension scheme has been expanded to more Qataris in the private sector to promote private sector employment. If downside risks materialize, Qatar has strong policy buffers to mitigate the negative impact. On the upside, accelerated reform efforts guided by Third National Development Strategy could further promote diversification and boost potential growth.
Tohid Atashbar
In this study we introduce and apply a set of machine learning and artificial intelligence techniques to analyze multi-dimensional fragility-related data. Our analysis of the fragility data collected by the OECD for its States of Fragility index showed that the use of such techniques could provide further insights into the non-linear relationships and diverse drivers of state fragility, highlighting the importance of a nuanced and context-specific approach to understanding and addressing this multi-aspect issue. We also applied the methodology used in this paper to South Sudan, one of the most fragile countries in the world to analyze the dynamics behind the different aspects of fragility over time. The results could be used to improve the Fund’s country engagement strategy (CES) and efforts at the country.
Katharina Bergant
,
Miss Anke Weber
, and
Andrea Medici
Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United States over the last four decades. Employing a price index that appears appropriate for low income households, we show that poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our results are threefold. First, we identify the poor as more likely to be minorities, without a college education, never married, and living in the Midwest. Second, the importance of some factors, such as race and ethnicity, for determining poverty has declined over the last decades but they remain significant. Third, we find that social and economic factors can only partially capture the likelihood of being poor, pointing to the possibility that random factors (“bad luck”) could play a significant role.