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Middle East and Central Asia > Qatar

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Cover Policy Papers
Gulf Cooperation Council: Pursuing Visions Amid Geopolitical Turbulence: Economic Prospects and Policy Challenges for the GCC Countries
International Monetary Fund. Middle East and Central Asia Dept.
The Gulf Cooperation Council countries have successfully weathered recent turbulence in the Middle East, and their economic prospects remain favorable. Nonhydrocarbon activity has been strong amid reform implementation, although overall growth has decelerated due to cuts in oil production. The growth outlook is positive, as the envisaged easing of oil production cuts and natural gas expansion spur the recovery in the hydrocarbon sector, while the nonhydrocarbon economy continues to expand. External buffers remain comfortable despite current account balances having narrowed. Risks around the outlook are broadly balanced in the near term. More challenging medium-term risks, especially in the context of geoeconomic fragmentation and climate change, call for action on policy priorities to continue to strengthen the private sector and to diversify the economy.
Keywords:
economic diversification; financial stability; fiscal sustainability; GCC; productivity improvements; regional integration; GCC country; policy priority; B. GCC; GCC well; GCC public sector balance sheet; Labor markets; Fiscal rules; Total factor productivity; Global; Middle East; Middle East and Central Asia
Cover IMF Working Papers
Industrial Policies for Innovation: A Cost-Benefit Framework
Daniel Garcia-Macia
and
Alexandre Sollaci
When and how should governments use industrial policy to direct innovation to specific sectors? This paper develops a framework to analyze the costs and benefits of industrial policies for innovation. The framework is based on a model of endogenous innovation with a sectoral network of knowledge spillovers (Liu and Ma 2023), extended to capture implementation frictions and alternative policy goals. Simulations show that implementing sector-specific fiscal support is only preferable to sector-neutral support under restrictive conditions—when externalities are well measured (e.g., greenhouse gas emissions), domestic knowledge spillovers of targeted sectors are high (typically in larger economies), and administrative capacity is strong (including to avoid misallocation to politically connected sectors). If any of these conditions are not fully met, welfare impacts of industrial policy quickly become negative. The optimal allocation of support entails greater subsidies to greener sectors, but other factors such as cross-sector knowledge spillovers matter. For a sample of technologically advanced economies, existing industrial policies seem to be directing innovation to broadly the right sectors, but to an excessive degree in most economies, including China and the United States.
Keywords:
Industrial policy; innovation; knowledge spillovers; climate policy; AI; implementation friction; knowledge spillover; economy openness; R&D allocation; welfare impact; policy goal; Spillovers; Artificial intelligence; Global
Cover IMF Staff Country Reports
Singapore: Selected Issues
International Monetary Fund. Asia and Pacific Dept
This Selected Issues paper estimates the exchange pass-through to inflation in Singapore with a particular focus on the role of labor market conditions. The paper first finds a strong exchange rate pass-through to inflation in Singapore, after accounting for the potential endogeneity of changes in the exchange rate. Further, it uncovers that labor market tightness dampens exchange rate pass-through and therefore could weaken monetary policy transmission. Overall, the results suggest that monetary policy should be more vigilant under a tight labor market condition. Under tight market conditions, the pass-through is found to be severely weakened and more so for the service components of the consumer price index basket. Overall, our findings suggest that the exchange rate-based monetary policy serves Singapore well, but it would need to be more vigilant when the labor market is tight. The paper then draws policy implications for taming inflation under tight labor market conditions. Further, policies designed to ease structural labor market tightness could help support monetary policy to ensure price stability in Singapore. This is consistent with a recent study on the US that suggests that dealing with the inflationary pressures originating from a tight labor market would require policy actions that bring labor demand and supply into a better balance.
Keywords:
AI exposure; IMF China growth projection; China growth shock; growth slowdown; growth shock; Artificial intelligence; Exchange rate pass-through; Inflation; Labor markets; Spillovers; Global; Southeast Asia; Asia and Pacific
Cover IMF Staff Country Reports
Peru: Selected Issues
International Monetary Fund. Western Hemisphere Dept.
The Selected Issues paper focuses on productivity and growth in Peru. Firms have maintained smaller sizes to avoid the application of a profit-sharing legislation, which has resulted in lower productivity. After a decade of high economic growth averaging over 6 percent per year, potential growth has been falling since 2014. A much slower pace of investment and human has driven the decline capital accumulation, but most notably, a decline in total factor productivity growth. In line with the macroeconomic trends, firm-level productivity has worsened, and the decline has been broad-based across the economy. Special corporate tax regimes and labor legislations and regulations have created barriers to productivity growth. To raise productivity, policies will need to focus on reforming regulations that impose excessive costs to formalizing or growing a business. Down the line, introducing greater labor market flexibility would ensure that workers could transition to productive sectors of the economy and reduce labor informality.
Keywords:
El Niño shock; building RESILIENCE; B. Measuring productivity; B. artificial intelligence; total factor productivity growth; labor force complementarity; Climate change; Natural disasters; Productivity; Potential output; Artificial intelligence; Global; Caribbean
Cover Selected Issues Papers
2022 FIFA World Cup: Economic Impact on Qatar and Regional Spillovers
Aidyn Bibolov
,
Ken Miyajima
,
Sidra Rehman
, and
Tongfang Yuan
Qatar hosted the 2022 FIFA World Cup (WC) successfully and took the opportunity to further develop its non-hydrocarbon economy. Near-term contributions to Qatar’s economy, from visitors’ spending and WC-related broadcasting revenue, of up to 1 percent of GDP was comparable to cross-country experiences. The event generated positive regional economic spillovers as a sizeable share of spectators stayed in and commuted from neighboring GCC countries. Longer-term contributions were significant—the large investment in general infrastructure ahead of the WC drove much of the non-hydrocarbon sector’s growth in the past decade. The high-quality infrastructure and global visibility brought by the WC should be leveraged to further promote diversification and achieve the National Vision 2030.
Keywords:
Economic diversification; economic transformation; Qatar; structural reform; FIFA World Cup; broadcasting revenue; Qatar's economy; WC spectator; World Cup broadcasting right; Public investment spending; Capital spending; Production growth; Spillovers; Tourism; Global; Asia and Pacific
Cover IMF Working Papers
Mining the Gap: Extracting Firms’ Inflation Expectations From Earnings Calls
Silvia Albrizio
,
Allan Dizioli
, and
Pedro Vitale Simon
Using a novel approach involving natural language processing (NLP) algorithms, we construct a new cross-country index of firms' inflation expectations from earnings call transcripts. Our index has a high correlation with existing survey-based measures of firms' inflation expectations, it is robust to external validation tests and is built using a new method that outperforms other NLP algorithms. In an application of our index to United States, we uncover some facts related to firm's inflation expectations. We show that higher expected inflation translates into future inflation. Going into the firms level dimension of our index, we show departures from a rational framework in firms' inflation expectations and that firms' attention to the central enhances monetary policy effectiveness.
Keywords:
rms' inflation expectations; Firms' earnings calls transcripts; Natural Language processing; GPT3.5; Monetary policy; inflation expectation; expectation index; monetary policy effectiveness; firms attention; expectations disagreement; Inflation; Artificial intelligence; Wages; Futures; Consumer price indexes; Global
Cover IMF Working Papers
AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC model
Tohid Atashbar
and
Rui Aruhan Shi
This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, one of which is deterministic without the technological shock and the other is stochastic. The objective of the deterministic environment is to compare the learning agent's behavior to a deterministic steady-state scenario. We demonstrate that in both deterministic and stochastic scenarios, the agent's choices are close to their optimal value. We also present cases of unstable learning behaviours. This AI-macro model may be enhanced in future research by adding additional variables or sectors to the model or by incorporating different DRL algorithms.
Keywords:
Reinforcement learning; Deep reinforcement learning; Artificial intelligence; RL; DRL; Learning algorithms; Macro modeling; RBC; Real business cycles; DDPG; Deep deterministic policy gradient; Actor-critic algorithms; RBC model; AI-macroeconomic simulator; AI experiment; learning algorithm; Machine learning; Rational expectations; Debt relief; Global
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 Working Papers
Structural Reforms and Economic Growth: A Machine Learning Approach
Mr. Anil Ari
,
Gabor Pula
, and
Liyang Sun
The qualitative and granular nature of most structural indicators and the variety in data sources poses difficulties for consistent cross-country assessments and empirical analysis. We overcome these issues by using a machine learning approach (the partial least squares method) to combine a broad set of cross-country structural indicators into a small number of synthetic scores which correspond to key structural areas, and which are suitable for consistent quantitative comparisons across countries and time. With this newly constructed dataset of synthetic structural scores in 126 countries between 2000-2019, we establish stylized facts about structural gaps and reforms, and analyze the impact of reforms targeting different structural areas on economic growth. Our findings suggest that structural reforms in the area of product, labor and financial markets as well as the legal system have a significant impact on economic growth in a 5-year horizon, with one standard deviation improvement in one of these reform areas raising cumulative 5-year growth by 2 to 6 percent. We also find synergies between different structural areas, in particular between product and labor market reforms.
Keywords:
Structural reforms; institutions; economic growth; C. PLS estimation procedure; machine learning approach; Gabor pula; Liyang sun; labor market composite; Business environment; Labor markets; Machine learning; Labor market reforms; Global
Cover IMF Working Papers
Shocks to Inflation Expectations
Mr. Philip Barrett
and
Jonathan J. Adams
The consensus among central bankers is that higher inflation expectations can drive up inflation today, requiring tighter policy. We assess this by devising a novel method for identifying shocks to inflation expectations, estimating a semi-structural VAR where an expectation shock is identified as that which causes measured expectations to diverge from rationality. Using data for the United States, we find that a positive inflation expectations shock is deflationary and contractionary: inflation, output, and interest rates all fall. These results are inconsistent with the standard New Keynesian model, which predicts inflation and interest rate hikes. We discuss possible resolutions to this new puzzle.
Keywords:
Inflation; Sentiments; Expectations; Monetary Policy; inflation expectation; interest rate hike; sentiment shock; forecasted inflation; expectations multiplier; inflation impulse; Inflation; Neoclassical theory; Rational expectations; Vector autoregression; Machine learning