What is he best known for?
The fields of study he is best known for:
- Statistics
- Inflation
- Macroeconomics
His primary scientific interests are in Econometrics, Rational expectations, Inflation, Monetary policy and Mathematical economics.
His Econometrics research is multidisciplinary, incorporating elements of Maximum likelihood and Economic model.
His research integrates issues of Quasi-maximum likelihood, Time series, Endogeneity, Microeconomics and Hyperinflation in his study of Rational expectations.
His Inflation study frequently draws connections between adjacent fields such as Unemployment.
His work carried out in the field of Monetary policy brings together such families of science as Volatility, Natural rate of unemployment and Bayesian probability.
His Mathematical economics study combines topics from a wide range of disciplines, such as Private information retrieval, Neoclassical economics, Money supply, Debt and Least squares.
His most cited work include:
- "Rational" Expectations, the Optimal Monetary Instrument, and the Optimal Money Supply Rule (1608 citations)
- Some Unpleasant Monetarist Arithmetic (1438 citations)
- Recursive Macroeconomic Theory (1294 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Econometrics, Rational expectations, Mathematical economics, Inflation and Unemployment.
His Econometrics research integrates issues from Consumption, Decision rule and Expected utility hypothesis.
His Rational expectations research includes themes of Value and Microeconomics.
His work in Inflation addresses issues such as Monetary policy, which are connected to fields such as Prior probability.
The various areas that Thomas J. Sargent examines in his Unemployment study include Matching, Welfare state, Labour economics and General equilibrium theory.
His research in Labour economics focuses on subjects like Government, which are connected to Debt.
He most often published in these fields:
- Econometrics (32.16%)
- Rational expectations (20.56%)
- Mathematical economics (16.52%)
What were the highlights of his more recent work (between 2010-2021)?
- Econometrics (32.16%)
- Business cycle (4.75%)
- Unemployment (19.51%)
In recent papers he was focusing on the following fields of study:
Thomas J. Sargent mostly deals with Econometrics, Business cycle, Unemployment, Keynesian economics and Ambiguity.
His Econometrics study also includes
- Baseline that connect with fields like Kullback–Leibler divergence,
- Probability distribution that connect with fields like Parametric model.
His Business cycle study incorporates themes from Incomplete markets, Microeconomics and Welfare.
His Unemployment research incorporates elements of Productivity, Depreciation and Overlapping generations model, Labour economics.
His study in Inflation is interdisciplinary in nature, drawing from both Rational expectations, Government budget and Debt.
His Monetary policy study is concerned with the field of Macroeconomics as a whole.
Between 2010 and 2021, his most popular works were:
- Two Illustrations of the Quantity Theory of Money: Breakdowns and Revivals (74 citations)
- Recursive Models of Dynamic Linear Economies (63 citations)
- Interest rate risk and other determinants of post-WWII US government Debt/GDP dynamics (51 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- World War II
- Inflation
His primary areas of investigation include Econometrics, Government, Business cycle, Unemployment and Keynesian economics.
His Econometrics research includes elements of Prior probability, Applied mathematics, Entropy, Likelihood function and Hidden Markov model.
His Business cycle research is multidisciplinary, incorporating perspectives in Systematic risk, Robustness, Microeconomics and Welfare.
The Unemployment study combines topics in areas such as Matching, Human capital, Depreciation, Labour economics and Productivity.
His Keynesian economics study combines topics in areas such as Instability and Macroeconomics.
His biological study spans a wide range of topics, including Omitted-variable bias and Short run.
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