What is he best known for?
The fields of study he is best known for:
- Macroeconomics
- Finance
- Microeconomics
Emmanuel Farhi spends much of his time researching Monetary economics, Exchange rate, Interest rate, Risk premium and Monetary policy.
His research integrates issues of Capital and Investment in his study of Monetary economics.
The concepts of his Exchange rate study are interwoven with issues in Outcome, Econometrics and Foreign direct investment.
Emmanuel Farhi has included themes like Conventional wisdom, Global imbalances and Portfolio in his Outcome study.
His work carried out in the field of Risk premium brings together such families of science as Currency and Interest rate parity.
His Monetary policy study combines topics from a wide range of disciplines, such as Market liquidity and Externality.
His most cited work include:
- An Equilibrium Model of "Global Imbalances" and Low Interest Rates (745 citations)
- Collective Moral Hazard, Maturity Mismatch, and Systemic Bailouts † (565 citations)
- An Equilibrium Model of Global Imbalances and Low Interest Rates (310 citations)
What are the main themes of his work throughout his whole career to date?
Emmanuel Farhi mainly investigates Monetary economics, Interest rate, Econometrics, Market liquidity and Currency.
His studies deal with areas such as Asset and Debt as well as Monetary economics.
His work deals with themes such as Risk premium, Stylized fact, Investment, Exchange rate and Global imbalances, which intersect with Interest rate.
His studies in Exchange rate integrate themes in fields like Outcome and Foreign direct investment.
His Foreign direct investment study integrates concerns from other disciplines, such as Conventional wisdom and Portfolio.
His Econometrics study combines topics in areas such as Productivity, Production, Welfare and General equilibrium theory.
He most often published in these fields:
- Monetary economics (64.77%)
- Interest rate (32.58%)
- Econometrics (28.79%)
What were the highlights of his more recent work (between 2019-2021)?
- Monetary economics (64.77%)
- Supply shock (5.68%)
- Allocative efficiency (9.47%)
In recent papers he was focusing on the following fields of study:
Emmanuel Farhi focuses on Monetary economics, Supply shock, Allocative efficiency, Returns to scale and Production.
His Monetary economics research is multidisciplinary, incorporating perspectives in Government spending and Capital market.
His study looks at the intersection of Government spending and topics like Current account with Market liquidity.
The various areas that Emmanuel Farhi examines in his Allocative efficiency study include Total factor productivity, Core and Welfare.
As part of one scientific family, he deals mainly with the area of Total factor productivity, narrowing it down to issues related to the Phillips curve, and often Interest rate.
While the research belongs to areas of Production, he spends his time largely on the problem of Consumption, intersecting his research to questions surrounding Shock, Incomplete markets and Wage.
Between 2019 and 2021, his most popular works were:
- Optimal Taxation with Behavioral Agents (41 citations)
- Productivity and Misallocation in General Equilibrium (31 citations)
- Supply and Demand in Disaggregated Keynesian Economies with an Application to the Covid-19 Crisis (21 citations)
In his most recent research, the most cited papers focused on:
- Macroeconomics
- Finance
- Inflation
His primary areas of study are Supply shock, Monetary economics, Shock, Production and Supply chain.
The Supply shock study combines topics in areas such as Supply and demand, Deflation, Recession and Unemployment.
His research in Monetary economics intersects with topics in Government spending and Capital market.
His biological study spans a wide range of topics, including Total factor productivity, Econometrics, Allocative efficiency and General equilibrium theory.
His Final demand study, which is part of a larger body of work in Production, is frequently linked to Nonlinear system, bridging the gap between disciplines.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
