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The Bayesian approach to monopoly regulation after 40 years
This paper surveys the monopoly regulation literature with the Bayesian approach. The literature builds on Baron and Myerson’s seminal 1982 paper,...
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Forecasting House Prices through Credit Conditions: A Bayesian Approach
As housing development and housing market policies involve many long-term decisions, improving house price predictions could benefit the functioning...
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Bayesian spatial panel models: a flexible Kronecker error component approach
We introduce a class of spatial panel data models with correlated error components that can simultaneously handle cross-sectional and temporal...
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Is unemployment hysteretic or structural? A Bayesian model selection approach
This document estimates an unobserved components model to examine the connection between the business cycle and the natural unemployment rate in...
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Stock price index analysis of four OPEC members: a Bayesian approach
This study examines the relationship between macroeconomic variables and stock price indices of four prominent OPEC oil-exporting members. Bayesian...
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Which financial inclusion indicators and dimensions matter for income inequality? A Bayesian model averaging approach
This paper employs Bayesian model averaging (BMA) and uses posterior inclusion probability (PIP) values to evaluate which financial inclusion...
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Behavioral welfare economics and risk preferences: a Bayesian approach
We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed...
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Two-tiered stochastic frontier models: a Bayesian perspective
Bayesian methods have been well-studied in single-tiered stochastic frontier literature, but as of yet have not been proposed in a two-tiered...
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Oil price shocks and China’s consumer and entrepreneur sentiment: a Bayesian structural VAR approach
This paper studies the effect of oil price shocks on China’s consumer and entrepreneur sentiment using a novel Bayesian inference structural vector...
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Spatio-Temporal Instrumental Variables Regression with Missing Data: A Bayesian Approach
This paper proposes an extension of the Bayesian instrumental variables regression which allows spatial and temporal correlation among observations....
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A Bayesian Time-Varying Coefficient Model for Cobb–Douglas Production Function
This paper proposes a Bayesian varying coefficient model to estimate parameters exhibiting time-dependence in the Cobb–Douglas (CD) production...
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Regression Analysis Using Asymmetric Losses: A Bayesian Approach
Symmetric loss functions are sometimes inappropriate in Economics prediction problems. Asymmetric loss functions can then be applied where errors of...
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Ambiguity and partial Bayesian updating
Models of updating a set of priors either do not allow a decision maker to make inference about her priors (full bayesian updating or FB) or require...
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Regional Integration and Decoupling in the Asia Pacific: A Bayesian Panel VAR Approach
Policymakers have been debating for over a decade whether Asia is decoupling from the USA. Increasingly, deepening regional integration is cited as a...
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An inquiry into the drivers of an entrepreneurial economy: A Bayesian clustering approach
Understanding the worldwide drivers of qualified entrepreneurship is a key issue in economic policy design. To help policy decisions exert their...
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Bayesian spatio-temporal modeling of real estate launch prices
In this study, we utilize Bayesian methods to construct a comprehensive spatio-temporal model for real estate launch prices in the city of São Paulo....
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Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches
We compare the effectiveness of Classical, Bayesian, and Machine Learning (ML) methods for predicting the presence of a unit root in univariate...
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Macroeconomic Modelling and Bayesian Methods
This paper discusses the evolution of macroeconomic modelling. In particular, it focuses on Bayesian methods and provides some applications of the...
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Bayesian spatial econometrics: a software architecture
Bayesian approaches play an important role in the development of new spatial econometric methods, but are uncommon in applied work. This is partly...
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Bayesian Local Likelihood Estimation of Time-Varying DSGE Models: Allowing for Indeterminacy
This paper modifies and employs a Bayesian Local Likelihood approach to estimate time-varying parameters of a New Keynesian model and assess such...
