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Middle East and Central Asia > Qatar

You are looking at 1 - 10 of 17 items for :

  • Type: Journal Issue x
  • Data Collection and Data Estimation Methodology; Computer Programs: Other x
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Cover IMF Working Papers
Reinforcement Learning from Experience Feedback: Application to Economic Policy
Tohid Atashbar
Learning from the past is critical for shaping the future, especially when it comes to economic policymaking. Building upon the current methods in the application of Reinforcement Learning (RL) to the large language models (LLMs), this paper introduces Reinforcement Learning from Experience Feedback (RLXF), a procedure that tunes LLMs based on lessons from past experiences. RLXF integrates historical experiences into LLM training in two key ways - by training reward models on historical data, and by using that knowledge to fine-tune the LLMs. As a case study, we applied RLXF to tune an LLM using the IMF's MONA database to generate historically-grounded policy suggestions. The results demonstrate RLXF's potential to equip generative AI with a nuanced perspective informed by previous experiences. Overall, it seems RLXF could enable more informed applications of LLMs for economic policy, but this approach is not without the potential risks and limitations of relying heavily on historical data, as it may perpetuate biases and outdated assumptions.
Keywords:
LLMs; GAI; RLHF; RLAIF; RLXF; experience feedback; RL model; applying RLXF; Reinforcement Learning from AI feedback; Reinforcement Learning method; Artificial intelligence; Economic classification
Cover IMF Staff Country Reports
Qatar: 2023 Article IV Consultation-Press Release; and Staff Report
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.
Keywords:
LNG production expansion; money market rate; financial asset; IMF staff calculation; labor market dynamics; policy buffer; Fiscal stance; Anti-money laundering and combating the financing of terrorism (AML/CFT); Public sector; Global; Middle East; North Africa; East Africa
Cover IMF Working Papers
How Nations Become Fragile: An AI-Augmented Bird’s-Eye View (with a Case Study of South Sudan)
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.
Keywords:
Fragile and Conflict-Affected States; Fragility Trap; Fragility Syndrome; Machine Learning; Artificial Intelligence; AI technique; fragility data; Bird's-Eye View; artificial intelligence technique; aggregate fragility; Artificial intelligence and machine learning; Global; Middle East; North Africa; South Asia; Sub-Saharan Africa
Cover IMF Working Papers
Deep Reinforcement Learning: Emerging Trends in Macroeconomics and Future Prospects
Tohid Atashbar
and
Rui Aruhan Shi
The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how deep reinforcement learning can be used to study a variety of economic problems, including optimal policy-making, game theory, and bounded rationality. In this paper, after a theoretical introduction to deep reinforcement learning and various DRL algorithms, we provide an overview of the literature on deep reinforcement learning in economics, with a focus on the main applications of deep reinforcement learning in macromodeling. Then, we analyze the potentials and limitations of deep reinforcement learning in macroeconomics and identify a number of issues that need to be addressed in order for deep reinforcement learning to be more widely used in macro modeling.
Keywords:
Reinforcement learning; Deep reinforcement learning; Artificial intelligence, RL; DRL; Learning algorithms; Macro modeling; RL algorithm overview; trust region policy optimization; DRL algorithm; decision process; RL algorithm; Machine learning; Artificial intelligence; Debt relief; General equilibrium models; Global
Cover IMF Staff Country Reports
Qatar: 2022 Article IV Consultation-Press Release; and Staff Report
International Monetary Fund. Middle East and Central Asia Dept.
Swift and decisive policy response to the Covid-19 pandemic has helped to mitigate the health and economic impact of the crisis. Fast vaccination rollout has also strengthened the economy’s resilience to new pandemic waves, paving the way for a speedy recovery. As the economy rebounds, a gradual exit from pandemic support measures is underway.
Keywords:
hydrocarbon price; CPI data; money market rate; financial asset; headline inflation; IMF's transparency policy; COVID-19; External sector statistics; Foreign assets; Global; Middle East; North Africa; East Africa
Cover IMF Working Papers
UnFEAR: Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification
Mr. Jorge A Chan-Lau
We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses unsupervised representation learning and a novel mode contrastive autoencoder to group episodes into time-invariant non-overlapping clusters, each of which could be identified with a different regime. The likelihood that a country may experience an econmic crisis could be set equal to its cluster crisis frequency. Moreover, unFEAR could serve as a first step towards developing cluster-specific crisis prediction models tailored to each crisis regime.
Keywords:
clustering; unsupervised feature extraction; autoencoder; deep learning; biased label problem; crisis prediction; WP; crisis frequency; crisis observation; crisis risk; crisis data points; machine learning; Early warning systems; Global
Cover IMF Staff Country Reports
Qatar: 2019 Article IV Consultation-Press Release; Staff Report
International Monetary Fund. Middle East and Central Asia Dept.
This 2019 Article IV Consultation discusses that stronger real gross domestic product (GDP) growth is envisaged in the near term, with a recovery in hydrocarbon output. Medium-term growth will be buoyed by increased gas production and non-hydrocarbon growth. Expenditure consolidation would help to sustain fiscal and external surpluses. Ample liquidity will enable credit growth to support non-hydrocarbon GDP. Trade and geopolitical tensions could undermine investor confidence and weaken fiscal and external positions. The policy priorities are fiscal consolidation, strengthened fiscal policy frameworks, enhanced resiliency of the financial sector, financial inclusion, and a diversified economy. The financial sector remains sound, underpinned by strong profitability and capital. Strengthening the regulatory and supervisory frameworks would help to bolster financial stability. Attention to women’s empowerment by introducing legislation emphasizing equality in remuneration and avoiding gender-based discrimination would support inclusive growth.
Keywords:
ISCR; CR; Qatar; GDP; IMF staff estimate; central bank; economy; hydrocarbon price; headline inflation; financial asset; Qatar's economy; QCB website; Oil prices; Fiscal stance; Global; Middle East; North Africa; East Africa
Cover IMF Staff Country Reports
Indonesia: Technical Assistance Report – Residential Property Price Statistics Capacity Development Mission
International Monetary Fund. Statistics Dept.
Technical Assistance Report – Residential Property Price Statistics Capacity Development Mission
Keywords:
ISCR; CR; price index; residential property price index; commercial property price index; mortgage data; rent price index; sales-price indexes; bank Indonesia CPPI; big data project; Price indexes; Land prices; Big data; Real estate prices; Real sector statistics
Cover IMF Staff Country Reports
Qatar: 2018 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for Qatar
International Monetary Fund. Middle East and Central Asia Dept.
This 2018 Article IV Consultation highlights that Qatar’s growth performance remains resilient. The direct economic and financial impact of the diplomatic rift between Qatar and some countries in the region has been manageable. Nonhydrocarbon real GDP growth is estimated to have moderated to about 4 percent in 2017 owing to on-going fiscal consolidation and the effect of the diplomatic rift. Headline inflation remains subdued, primarily owing to lower rental prices. The near-term growth outlook is broadly positive. Overall, GDP growth of 2.6 percent is projected for 2018. Inflation is expected to peak at 3.9 percent in 2018 before easing to 2.2 percent in the medium term. The underlying fiscal position continues to improve.
Keywords:
ISCR; CR; GDP; near-term growth outlook; GDDS summary table II data coverage; growth; Non-hydrocarbon real GDP growth; private sector engagement; growth performance; real estate price index; liquidity profile; hydrocarbon price; Commercial banks; Credit; Fiscal stance; Global; Middle East; North Africa; East Africa
Cover Staff Discussion Notes
Big Data: Potential, Challenges and Statistical Implications
Cornelia Hammer
,
Ms. Diane C Kostroch
, and
Mr. Gabriel Quiros-Romero
Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.
Keywords:
SDN; big data data source; strategy action plan; innovation challenge; big data application; big data classification; big data project; IMF big data; private sector; project inventory; Big Data; Macroeconomic and Financial Statistics; Official Statistics; Data Quality; Surveillance; statistics big data strategy action plan; big data data analysis; big data network; big data revolution; big data use; Social networks; Financial statistics; Global