What is he best known for?
The fields of study he is best known for:
- Statistics
- Econometrics
- Capitalism
Raymond J.G.M. Florax focuses on Econometrics, Spatial econometrics, Statistics, Spatial dependence and Spatial analysis.
His work on Autoregressive model as part of his general Econometrics study is frequently connected to Estimation, thereby bridging the divide between different branches of science.
His studies in Autoregressive model integrate themes in fields like Space and Contrast.
His research investigates the connection with Spatial econometrics and areas like Econometric model which intersect with concerns in Discrete choice and Demographic economics.
His Autocorrelation and Regression analysis study in the realm of Statistics interacts with subjects such as Odds, Publication bias and Rate of convergence.
His studies deal with areas such as Monte Carlo method, Linear regression and Probit as well as Spatial dependence.
His most cited work include:
- Simple diagnostic tests for spatial dependence (1180 citations)
- The Empirics of Wetland Valuation: A Comprehensive Summary and a Meta-Analysis of the Literature (480 citations)
- Price and Income Elasticities of Residential Water Demand: A Meta-Analysis (478 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Econometrics, Spatial econometrics, Economic geography, Estimator and Statistics.
The concepts of his Econometrics study are interwoven with issues in Spatial analysis, Regression analysis, Empirical research and Spatial dependence.
The various areas that he examines in his Spatial econometrics study include Econometric model, Autoregressive model and Variables.
His Economic geography study also includes fields such as
- Urbanization that intertwine with fields like Per capita income,
- Gravity model of trade most often made with reference to Space.
His Estimator research includes elements of Yield, Sample size determination, Monte Carlo method and Autocorrelation.
His work on Linear regression as part of general Statistics study is frequently connected to Random effects model, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
He most often published in these fields:
- Econometrics (57.27%)
- Spatial econometrics (34.30%)
- Economic geography (27.33%)
What were the highlights of his more recent work (between 2013-2021)?
- Economic geography (27.33%)
- Econometrics (57.27%)
- Spatial econometrics (34.30%)
In recent papers he was focusing on the following fields of study:
Raymond J.G.M. Florax spends much of his time researching Economic geography, Econometrics, Spatial econometrics, Agricultural economics and Monte Carlo method.
Raymond J.G.M. Florax has researched Economic geography in several fields, including Elevation and Per capita income.
His work on Panel data as part of general Econometrics research is frequently linked to Function, thereby connecting diverse disciplines of science.
His Spatial econometrics research integrates issues from Parametric statistics, Autoregressive model and Variables.
His research in Monte Carlo method intersects with topics in Estimator, Spatial analysis, Regression and Autocorrelation.
His Statistics study incorporates themes from Agricultural productivity and Yield.
Between 2013 and 2021, his most popular works were:
- How Does Population Density Influence Agricultural Intensification and Productivity (52 citations)
- Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction ☆ (36 citations)
- Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction ☆ (36 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Capitalism
- Microeconomics
The scientist’s investigation covers issues in Econometrics, Spatial econometrics, Estimator, Productivity and Monte Carlo method.
His Econometrics research includes themes of Spillover effect and Spatial dependence.
His study on Spatial econometrics is mostly dedicated to connecting different topics, such as Regime switching.
His Estimator study contributes to a more complete understanding of Statistics.
The Statistics study combines topics in areas such as Agricultural productivity and Yield.
His biological study spans a wide range of topics, including Outcome, Spatial analysis, Regression and Autocorrelation.
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