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Branch of econometrics
Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation
Bayesian_econometrics
descriptions of redirect targets Bayesian cognitive science Bayesian econometrics – Branch of econometrics Bayesian efficiency – Analog of Pareto efficiency
List of things named after Thomas Bayes
List_of_things_named_after_Thomas_Bayes
American econometrician and statistician (1933–2026)
editor of Statistica Sinica. He contributed greatly to the field of Bayesian econometrics. Tiao was born in London while both his parents were studying at
George_C._Tiao
Statistical estimation method
In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs
Bayesian vector autoregression
Bayesian_vector_autoregression
Method of statistical inference
Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a method of statistical inference in which Bayes' theorem is used to calculate a probability
Bayesian_inference
Empirical statistical testing of economic theories
consistency. Applied econometrics uses theoretical econometrics and real-world data for assessing economic theories, developing econometric models, analysing
Econometrics
American economist and statistician
the fields of Bayesian probability and econometrics. Zellner contributed pioneering work in the field of Bayesian analysis and econometric modeling. Zellner
Arnold_Zellner
German economist
His research interests are in macroeconomics, financial markets, Bayesian econometrics, and in particular at the intersection of these three. Major fields
Harald_Uhlig
Belgian economist (1929–2022)
Drèze's work on Bayesian Econometrics (see also [61]) and expounds complementarities between economic theory, decision theory, econometrics and mathematical
Jacques_Drèze
Interpretation of probability
Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or
Bayesian_probability
Method of statistical analysis
Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables
Bayesian_linear_regression
Ratio of competing statistical models
Gary (2003). "Model Comparison: The Savage–Dickey Density Ratio". Bayesian Econometrics. Somerset: John Wiley & Sons. pp. 69–71. ISBN 0-470-84567-8. Wagenmakers
Bayes_factor
Austrian academic statistician
applied statistics and econometrics at the Vienna University of Economics and Business. She is known for her research in Bayesian analysis. In 2020 she
Sylvia_Frühwirth-Schnatter
Conditional probability used in Bayesian statistics
(2004). An Introduction to Modern Bayesian Econometrics. Oxford: Blackwell. ISBN 1-4051-1720-6. Lee, Peter M. (2004). Bayesian Statistics : An Introduction
Posterior_probability
Statistical technique used for feature selection
Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal
Bayesian structural time series
Bayesian_structural_time_series
French econometrician
Toulouse School of Economics. He is known for his research on Bayesian inference, econometrics of stochastic processes, causality, frontier estimation, and
Jean-Pierre_Florens
American economist (1938–2022)
British-American Bayesian econometrician. He was the Herbert H. Goldberger Professor Emeritus at Brown University and a fellow of the Econometric Society from
Tony_Lancaster
Probability distribution
applications in various fields, including econometrics, Bayesian statistics, and life testing. In econometrics, the (α, θ) parameterization is common for
Gamma_distribution
theorem Bayesian – disambiguation Bayesian average Bayesian brain Bayesian econometrics Bayesian experimental design Bayesian game Bayesian inference
List_of_statistics_articles
Statistical property of collections of time series data
"Chapter 17: Bayesian Approaches to Cointegration". In Mills, T.C.; Patterson, K. (eds.). Handbook of Econometrics Vol.1 Econometric Theory. Palgrave
Cointegration
Econometric analysis of financial risk
The econometrics of risk is a specialized field within econometrics that focuses on the quantitative modelling and statistical analysis of risk in various
Econometrics_of_risk
Criterion for model selection
In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among
Bayesian information criterion
Bayesian_information_criterion
Bayesian approach to multivariate linear regression
In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted
Bayesian multivariate linear regression
Bayesian_multivariate_linear_regression
Statistical software package
datasets natively, using the fdause and fdasave commands. Some other econometric applications, including gretl, can directly import Stata file formats
Stata
Analytical expression in statistics
). Bayesian and Likelihood Methods in Statistics and Econometrics. Elsevier. pp. 473–488. ISBN 0-444-88376-2. MacKay, David J. C. (1992). "Bayesian Interpolation"
Laplace's_approximation
Concept in Bayesian statistics
In Bayesian statistics, a credible interval is an interval used to characterize a probability distribution. It is defined such that an unobserved parameter
Credible_interval
American statistician (born 1941)
University. Kadane is one of the early proponents of Bayesian statistics, particularly the subjective Bayesian philosophy. Kadane was born in Washington, DC
Joseph_Born_Kadane
design of experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in
History_of_statistics
Econometrics book
Mostly Harmless Econometrics: An Empiricist's Companion is an econometrics book written by two labour economists Joshua Angrist and Jörn-Steffen Pischke
Mostly_Harmless_Econometrics
Concept in statistics
2139/ssrn.2983919 Kmenta, Jan (1986). "Latent Variables". Elements of Econometrics (Second ed.). New York: Macmillan. pp. 581–587. ISBN 978-0-02-365070-3
Latent and observable variables
Latent_and_observable_variables
American econometrician and macroeconomist (1942–2026)
Sims published numerous important papers in his areas of research: econometrics and macroeconomic theory and policy. Among other things, he was one of
Christopher_A._Sims
Regularization technique for ill-posed problems
variables are highly correlated. It has been used in many fields including econometrics, chemistry, and engineering. It is a widely used method of regularization
Ridge_regression
Function related to statistics and probability theory
§ Interpretation Zellner, Arnold (1971). An Introduction to Bayesian Inference in Econometrics. New York: Wiley. pp. 13–14. ISBN 0-471-98165-6. Billingsley
Likelihood_function
Statistician and econometrician
Professor of Econometrics and Statistics at the Olin Business School at Washington University in St. Louis. His work is primarily in Bayesian statistics
Siddhartha_Chib
Dutch economist (1946–2025)
Professor Emeritus at the Econometric Institute of the Erasmus University Rotterdam, known for his contributions in the field of Bayesian analysis. Van Dijk
Herman_K._van_Dijk
Type of probability distribution used in statistics
Decision Techniques: Essays in Honor of Bruno de Finetti. Studies in Bayesian Econometrics and Statistics. Vol. 6. New York: Elsevier. pp. 233–243. ISBN 978-0-444-87712-3
G-prior
Linear dependency situation in a regression model
Theoretical Econometrics. Blackwell. pp. 256–278. doi:10.1002/9780470996249.ch13. ISBN 978-0-631-21254-6. Johnston, John (1972). Econometric Methods (Second ed
Multicollinearity
Family of multivariate continuous probability distributions
to exponential family | Introduction to Bayesian Econometrics. Denison, David G. T.; et al. (2002). Bayesian Methods for Nonlinear Classification and
Normal-inverse-gamma distribution
Normal-inverse-gamma_distribution
Belgian-American economist (born 1943)
primarily in the field of econometrics. His interests are auctions, computational methods, collusions, Bayesian methods and econometric modeling. He has been
Jean-François_Richard
Method of estimating the parameters of a statistical model, given observations
Statistics and Econometrics Models. Cambridge University Press. p. 161. ISBN 0-521-40551-3. Kane, Edward J. (1968). Economic Statistics and Econometrics. New York
Maximum_likelihood_estimation
American academic (1924–2016)
and Harvard Kennedy School at Harvard University. He was an influential Bayesian decision theorist and pioneer in the field of decision analysis, with works
Howard_Raiffa
American economist
most of the emerging areas of econometrics. His 1983 book titled Limited Dependent and Qualitative Variables in Econometrics is now regarded as a classic
G._S._Maddala
Distribution of an uncertain quantity
Distributions to Represent 'Knowing Little'". An Introduction to Bayesian Inference in Econometrics. New York: John Wiley & Sons. pp. 41–53. ISBN 0-471-98165-6
Prior_probability
Statistician
Veronika Ročková (born 1985) is a Bayesian statistician. Born in Czechoslovakia, and educated in the Czech Republic, Belgium, and the Netherlands, she
Veronika_Ročková
alternative to IBM SPSS Statistics with additional option for Bayesian methods JMulTi – For econometric analysis, specialised in univariate and multivariate time
List_of_statistical_software
Econometric term
In econometrics and statistics, a structural break is an unexpected change over time in the parameters of regression models, which can lead to huge forecasting
Structural_break
Class of statistical tests
and Practice of Econometrics (Second ed.). Wiley. pp. 890–892. ISBN 978-0-471-08277-4. Gujarati, Damodar N. (2002). Basic Econometrics (Fourth ed.). McGraw
Normality_test
Computational method in Bayesian statistics
Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior
Approximate Bayesian computation
Approximate_Bayesian_computation
Bayesian variable selection technique in statistics
distribution). Bayesian model averaging Bayesian structural time series Lasso Varian, Hal R. (2014). "Big Data: New Tricks for Econometrics". Journal of
Spike-and-slab_regression
Process of using data analysis for predicting population data from sample data
inference need have a Bayesian interpretation. Analyses which are not formally Bayesian can be (logically) incoherent; a feature of Bayesian procedures which
Statistical_inference
Mathematical decision rule
utility function. An alternative way of formulating an estimator within Bayesian statistics is maximum a posteriori estimation. Suppose an unknown parameter
Bayes_estimator
Belgian research university
programming and econometrics, initially minor fields, also developed and became important research areas at CORE. Thus, Bayesian econometrics can be considered
Center for Operations Research and Econometrics
Center_for_Operations_Research_and_Econometrics
Economic model of personal preferences
developed by Luce and Plackett. The Plackett-Luce model was applied in econometrics, for example, to analyze automobile prices in market equilibrium. It
Random_utility_model
Mathematical framework for identifying causal effects
Bareinboim, Elias. "Causal Inference and Data Fusion in Econometrics" (PDF). The Econometrics Journal. Retrieved 2025-04-15. Bottou, Léon (2013). "Counterfactual
Do-calculus
Economist
Econometrics, and the Econometric Theory. Yu's research concentrates on stochastic volatility models, continuous-time models, Bayesian econometrics,
Jun_Yu
Spanish engineer and statistician
articles in time series analysis, multivariate methods, Bayesian Statistics and Econometrics that have received more than 10,000 references. He is fellow
Daniel_Peña_(engineer)
Type of statistical model
on the right displays Bayesian research cycle using Bayesian nonlinear mixed-effects model. A research cycle using the Bayesian nonlinear mixed-effects
Multilevel_model
American statistician
pp. 237–245. ISBN 981-02-3060-5. "DeGroot Prize". bayesian.org. International Society for Bayesian Analysis. 2005. Archived from the original on 2001-02-19
Morris_H._DeGroot
Concept in statistics
meanings in different branches of statistics. In statistics, especially in Bayesian statistics, the kernel of a probability density function (pdf) or probability
Kernel_(statistics)
French economist (born 1969)
(2014). "Accurate Methods for Approximate Bayesian Computation Filtering". Journal of Financial Econometrics. 13 (4): 798–838. doi:10.1093/jjfinec/nbu019
Laurent-Emmanuel_Calvet
Computing Applied Econometrics and International Development Econometric Reviews Econometric Theory Econometrica Journal of Applied Econometrics Journal of Business
List_of_statistics_journals
Indian-born statistician (born c. 1934)
foundations of econometrics, Swamy and Peter von zur Muehlen published a paper, reprinted in a volume on the foundations of probability, econometrics, and economic
P._A._V._B._Swamy
Mathematical relation assigning a probability event to a cost
is mapped to a monetary loss. Leonard J. Savage argued that using non-Bayesian methods such as minimax, the loss function should be based on the idea
Loss_function
Australian statistician
Gael Margaret Martin FASSA is an Australian Bayesian econometrician, known for her work in simulation-based inference and time series analysis of non-Gaussian
Gael_M._Martin
Analog of Pareto efficiency for situations with incomplete information
Postlewaite, A. (1993) Bayesian Implementation. Pg. 13-14. ISBN 3-7186-5314-1 Baltagi, Badi Hani. (2001) A Companion to Theoretical Econometrics. Blackwell Publishing
Bayesian_efficiency
Statistical property
in Econometrics. New York: Oxford University Press. pp. 547–582. ISBN 978-0-19-506011-9. Dougherty, Christopher (2011). Introduction to Econometrics. New
Homoscedasticity and heteroscedasticity
Homoscedasticity_and_heteroscedasticity
Economics and Business, where he also taught as a researcher focusing on econometrics and financial modeling. His public service career has been characterized
Athanasios_Petralias
Dutch-American econometrician
Dutch-American economist whose research concerns econometrics and statistics. He holds the Applied Econometrics Professorship in Economics at the Stanford Graduate
Guido_Imbens
Indian-American mathematician (1920–2023)
recognise Dr. Rao's own contributions to econometrics and acknowledge his major role in the development of econometric research in India." Estimation theory
C._R._Rao
American economist
Robert F. Stambaugh is an American economist, who specializes in econometrics and finance. Stambaugh received a PhD in finance from the University of Chicago
Robert_F._Stambaugh
Concept in statistical mathematics
In econometrics, the seemingly unrelated regressions (SUR) or seemingly unrelated regression equations (SURE) model, proposed by Arnold Zellner in (1962)
Seemingly unrelated regressions
Seemingly_unrelated_regressions
Experimental design framework
Bayesian experimental design provides a general probability-theoretical framework from which other theories on experimental design can be derived. It is
Bayesian_experimental_design
Time series statistical test
package urca function ur.df Gretl Matlab the Econometrics Toolbox function adfTest the Spatial Econometrics toolbox (free) SAS PROC ARIMA Stata command
Augmented_Dickey–Fuller_test
British statistician (born 1963)
a professor of econometrics and statistics at the University of Chicago Booth School of Business. His works are primarily in Bayesian statistics, Markov
Nicholas_Polson
Principle in Bayesian statistics
300117. Clarke, B. (2006). "Information optimality and Bayesian modelling". Journal of Econometrics. 138 (2): 405–429. doi:10.1016/j.jeconom.2006.05.003
Principle_of_maximum_entropy
Time series model
In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance
Autoregressive conditional heteroskedasticity
Autoregressive_conditional_heteroskedasticity
Calculation of complex statistical distributions
methods (especially Gibbs sampling) for complex statistical (particularly Bayesian) problems, spurred by increasing computational power and software like
Markov_chain_Monte_Carlo
Mathematical concept
{\displaystyle {\boldsymbol {\beta }}} and is therefore equivalent to Bayesian linear regression. Regularized least squares: the elements of β {\displaystyle
Constrained_least_squares
Estimator for quality of a statistical model
and Bayesian inference. AIC, though, can be used to do statistical inference without relying on either the frequentist paradigm or the Bayesian paradigm:
Akaike_information_criterion
American/Australian economist (born 1961)
popular econometrics software packages, including SAS, Stata, GAUSSX, Matlab and R-Cran-Bayesm, and is a standard topic in graduate econometrics texts.
Michael_Keane_(economist)
Statistical modeling method
In statistics and econometrics, a distributed lag model is a model for time series data in which a regression equation is used to predict current values
Distributed_lag
Generalized method of moments estimator in econometrics
In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator used to estimate dynamic models of panel data. It was proposed
Arellano–Bond_estimator
Introduced the Laplace transform, exponential families, and conjugate priors in Bayesian statistics. Pioneering asymptotic statistics, proved an early version of
List of publications in statistics
List_of_publications_in_statistics
Finnish statistician (1911–1983)
"An Interview with Timo Teräsvirta". Studies in Nonlinear Dynamics & Econometrics. 22 (5). doi:10.1515/snde-2018-0021. S2CID 158569911. Torvalds, Linus;
Leo_Törnqvist
Reciprocal of the statistical variance
error). One particular use of the precision matrix is in the context of Bayesian analysis of the multivariate normal distribution: for example, Bernardo
Precision_(statistics)
Theorem related to ordinary least squares
(1970). An Introduction to Econometrics. New York: W. W. Norton. p. 275. ISBN 0-393-09931-8. Hayashi, Fumio (2000). Econometrics. Princeton University Press
Gauss–Markov_theorem
Russian American statistician and economist
Restrictions, Partial Identification and Inference on Sets Laplacian and Bayesian Inference, Quantiles and Multivariate Quantiles, Endogeneity, and Extremes
Victor_Chernozhukov
American economist
in economics at Harvard and PhD from UC Berkeley. He specializes in econometrics and regulation, with applications in energy, environmental studies, telecommunications
Kenneth_E._Train
Unbiased statistical estimator minimizing variance
X_{n})\mid T)\,} is the MVUE for g ( θ ) . {\displaystyle g(\theta ).} A Bayesian analog is a Bayes estimator, particularly with minimum mean square error
Minimum-variance unbiased estimator
Minimum-variance_unbiased_estimator
Type of statistical inference
and type II errors. As a point of reference, the complement to this in Bayesian statistics is the minimum Bayes risk criterion. Because of the reliance
Frequentist_inference
Dutch economist (born 1934)
and emeritus Professor of Econometrics at the Erasmus Universiteit Rotterdam. His research interests centered on econometric methods and their applications
Teun_Kloek
Study of collection and analysis of data
government, and business. Business statistics applies statistical methods in econometrics, auditing and production and operations, including services improvement
Statistics
American statistician and mathematician
fundamental concept of monotone likelihood ratio families. Bayesian Inference: Rubin was a lifelong Bayesian statistician who took the theory and axioms of Leonard
Herman_Rubin
Statistical property
theory terms. But the results of a Bayesian approach can differ from the sampling theory approach even if the Bayesian tries to adopt an "uninformative"
Bias_of_an_estimator
Statistical test
and Lagrange Multiplier Tests in Econometrics". In Intriligator, M. D.; Griliches, Z. (eds.). Handbook of Econometrics. Vol. II. Elsevier. pp. 796–801
Wald_test
American statistician
was Bayesian Optimal Designs for Approximate Normality, which received the Savage Award for outstanding dissertation in Bayesian econometrics and statistics
Merlise_A._Clyde
Categorization of data using statistics
computations were developed, approximations for Bayesian clustering rules were devised. Some Bayesian procedures involve the calculation of group-membership
Statistical_classification
Probability distribution
^{2},\nu )} it generalizes the normal distribution and also arises in the Bayesian analysis of data from a normal family as a compound distribution when marginalizing
Student's_t-distribution
Indian-American statistician
India) is an Indian-American statistician best known for his work on Bayesian methodologies. He is currently the Board of Trustees Distinguished Professor
Dipak_K._Dey
Probabilistic model
models are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning. Generally, probabilistic graphical models
Graphical_model
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
Girl/Female
Arabic, Muslim
To Walk with Pride
Boy/Male
Muslim
Girl/Female
Muslim
To walk with pride
Boy/Male
Indian
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS
BAYESIAN ECONOMETRICS