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Western Hemisphere > Argentina

You are looking at 1 - 6 of 6 items for :

  • Type: Journal Issue x
  • Technological Change: Choices and Consequences; Diffusion Processes x
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Cover IMF Working Papers
Predicting IMF-Supported Programs: A Machine Learning Approach
Tsendsuren Batsuuri
,
Shan He
,
Ruofei Hu
,
Jonathan Leslie
, and
Flora Lutz
This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF-supported arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financing arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical.
Keywords:
Early warning systems; IMF Lending; Machine Learning; IMF arrangement; ML model; machine learning approach; state-of-the-art machine learning; machine learning model; Emergency assistance; Data processing; Global financial crisis of 2008-2009; Global
Cover IMF Working Papers
Will the AI Revolution Cause a Great Divergence?
Cristian Alonso
,
Mr. Andrew Berg
,
Siddharth Kothari
,
Mr. Chris Papageorgiou
, and
Sidra Rehman
This paper considers the implications for developing countries of a new wave of technological change that substitutes pervasively for labor. It makes simple and plausible assumptions: the AI revolution can be modeled as an increase in productivity of a distinct type of capital that substitutes closely with labor; and the only fundamental difference between the advanced and developing country is the level of TFP. This set-up is minimalist, but the resulting conclusions are powerful: improvements in the productivity of “robots” drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. In addition, capital—if internationally mobile—is pulled “uphill”, resulting in a transitional GDP decline in the developing country. In an extended model where robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently for the country relatively well-endowed in unskilled labor.
Keywords:
WP; production function; financial asset; Automation; robots; divergence; development; technological change; advanced economy; labor share; unskilled labor; developing economy; robot productivity; robot share; Robotics; Unskilled labor; Labor share; Skilled labor; Global; parameter e; unskilled-labor-saving technology
Cover IMF Research Perspectives
IMF Research Perspectives: Spring-Summer 2020
IMF Research Perspectives Spring-Summer 2020
Keywords:
IRB; worker; view IMF research; MARTINEZ PERIA interview
Cover Finance & Development
Finance & Development, September 2018
International Monetary Fund. Communications Department
Finance and Development
Keywords:
FD; F&D; economy; IMF's Asia; government; coin; anti-corruption office
Cover Finance & Development
Finance & Development, September 2018
International Monetary Fund. Communications Department
This paper discusses that from shifting demographics to climate change, Southeast Asia confronts a host of challenges. Summoning them will require both resilience and flexibility. Advances in artificial intelligence, including robotics, together with innovations such as 3-D printing and new composite materials, will transform manufacturing processes, making them less labor-intensive while creating opportunities for new products. This will enable new ways of making things and change the drivers of competitiveness. There will be indirect effects as well. For example, aircraft manufacturers, taking advantage of new composite materials such as carbon fibers, have developed a class of superlong-haul aircraft that could bring more tourists to Southeast Asia as relatively cheap point-to-point travel options emerge. The region should still enjoy synergies from globalization and other modes of economic integration, but the form and shape of such integration could change. For Southeast Asia, the next couple of decades could prove exhilarating in terms of the opportunities presented by technology and global growth, but also tumultuous because of the continuing risks, such as those posed by an unreformed and unstable international financial architecture. There clearly is much hard work to be done. Policymakers still have not gotten everything right, but they are heading in the right direction.
Keywords:
FD; F&D; economy; IMF's Asia; government; coin; anti-corruption office; shrinking world trade of the Great Depression; policy recommendation; coin design; remittance trap; Gender diversity; Climate change; Women; Southeast Asia; Global; Asia and Pacific; Sub-Saharan Africa; Mekong
Cover IMF Working Papers
Terms-of-Trade Cycles and External Adjustment
Gustavo Adler
,
Mr. Nicolas E Magud
, and
Alejandro M. Werner
We study the process of external adjustment to large terms-of-trade level shifts—identified with a Markov-switching approach—for a large set of countries during the period 1960–2015. We find that adjustment to these shocks is relatively fast. Current accounts experience, on average, a contemporaneous variation of only about ½ of the magnitude of the price shock—indicating a significant volume offset—and a full adjustment within 3–4 years. Dynamics are largely symmetric for terms-of-trade booms and busts, as well as for advanced and emerging market economies. External adjustment is driven primarily by offsetting shifts in domestic demand, as opposed to variations in output (also reflected in the response of import rather than export volumes), indicating a strong income channel at play. Exchange rate flexibility appears to have played an important buffering role during booms, but less so during busts; while international reserve holdings have been a key tool for smoothing the adjustment process.
Keywords:
WP; commodity exporter; current account balance; exchange rate regime; terms of trade; external adjustment; current account; commodity importer; imports volume; current account response; current account dynamics; commodity price swing; Technology transfer; Exchange rate arrangements; Adjustment process; Exchange rate flexibility; Global