What is he best known for?
The fields of study he is best known for:
- Statistics
- Econometrics
- Normal distribution
Jeremy Smith focuses on Econometrics, Statistics, Cohort, Monte Carlo method and Mathematics education.
His work in the fields of Econometrics, such as Autoregressive model, intersects with other areas such as Aggregate.
His work on Mean squared error, Consensus forecast and Multilevel model as part of general Statistics study is frequently linked to Individual level and Competing risks, bridging the gap between disciplines.
His research investigates the connection between Mean squared error and topics such as Error variance that intersect with problems in Unemployment.
His studies deal with areas such as Forecast error, Empirical research and SETAR as well as Monte Carlo method.
His Mathematics education research integrates issues from Preparedness, Ceteris paribus and Full-time.
His most cited work include:
- SEASONALITY AND THE ORDER OF INTEGRATION FOR CONSUMPTION (233 citations)
- Determinants of Degree Performance in UK Universities: A Statistical Analysis of the 1993 Student Cohort (224 citations)
- Dropping out of university: A statistical analysis of the probability of withdrawal for UK university students (191 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Econometrics, Statistics, Monte Carlo method, Higher education and Demographic economics.
His Autoregressive model study, which is part of a larger body of work in Econometrics, is frequently linked to Unit, bridging the gap between disciplines.
In the field of Statistics, his study on Unit root, Goodness of fit and Mean squared error overlaps with subjects such as Unit.
His Monte Carlo method study incorporates themes from Statistic, KPSS test and Kurtosis.
His biological study spans a wide range of topics, including Earnings, Hourly wage, Cohort study and Cohort.
Jeremy Smith has researched Cohort in several fields, including Preparedness and Mathematics education, Academic year.
He most often published in these fields:
- Econometrics (44.13%)
- Statistics (29.05%)
- Monte Carlo method (21.79%)
What were the highlights of his more recent work (between 2007-2018)?
- Econometrics (44.13%)
- Monte Carlo method (21.79%)
- Unit root (8.94%)
In recent papers he was focusing on the following fields of study:
Jeremy Smith spends much of his time researching Econometrics, Monte Carlo method, Unit root, Statistics and Demographic economics.
His work on Panel data is typically connected to Unit as part of general Econometrics study, connecting several disciplines of science.
His work deals with themes such as Forecast error and Empirical research, which intersect with Monte Carlo method.
His study on KPSS test, Integration testing and Seasonality is often connected to Unit and Null as part of broader study in Statistics.
The concepts of his Demographic economics study are interwoven with issues in Higher education, Labour economics and Sample.
His work in Higher education addresses issues such as Earnings, which are connected to fields such as Economic growth.
Between 2007 and 2018, his most popular works were:
- SEASONALITY AND THE ORDER OF INTEGRATION FOR CONSUMPTION (233 citations)
- A Simple Explanation of the Forecast Combination Puzzle (177 citations)
- Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters (106 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Econometrics
- Normal distribution
His scientific interests lie mostly in Econometrics, Inflation, Statistics, Monte Carlo method and Discount points.
Panel data is the focus of his Econometrics research.
His Inflation research incorporates themes from Monetary policy and Independence.
In general Statistics, his work in Null hypothesis is often linked to Variable, Surface, Lag and Order linking many areas of study.
His Monte Carlo method study combines topics from a wide range of disciplines, such as Forecast error, Quantile, Empirical research and Test statistic.
His Discount points research incorporates elements of Individual heterogeneity, Survey data collection, Macroeconomics and Consensus forecast.
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