Results 21 to 30 of about 63,609 (288)

Interregional Effects of Innovations in Russia: Analysis from the Bayesian Perspective [PDF]

open access: yesProstranstvennaâ Èkonomika
This study analyzes the interregional effects of innovation in Russia. The hypothesis of the presence of interregional effects is tested by combining the methods of spatial econometrics and Bayesian approach.
Dmitrii Sergeevich Tereshchenko
doaj   +1 more source

Estimating the exchange rate pass through on the price of Manufacturing sub-sectors in Iran with a Bayesian approach [PDF]

open access: yesسیاست‌گذاری اقتصادی
Purpose: It is commonly known that the exchange rate is one of the most important macroeconomic variables whose changes strongly influence a country's balance of payments and international competitiveness. Exchange rate fluctuations affect the production
Hassan Heydari, Sahar Bashiri
doaj   +1 more source

Bayesian nonparametric sparse VAR models [PDF]

open access: yes, 2018
High dimensional vector autoregressive (VAR) models require a large number of parameters to be estimated and may suffer of inferential problems. We propose a new Bayesian nonparametric (BNP) Lasso prior (BNP-Lasso) for high-dimensional VAR models that ...
Billio, Monica   +2 more
core   +3 more sources

Semiparametric Bayesian inference in multiple equation models [PDF]

open access: yes, 2005
This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components.
Koop, Gary   +2 more
core   +1 more source

Topics in bayesian econometrics [PDF]

open access: yes, 2021
Η παρούσα διπλωματική διατριβή αποτελείται από τέσσερα δοκίμια εφαρμογής της Μπεϋζιανής οικονομετρίας στα οικονομικά. Το πρώτο δοκίμιο, προτείνει μια νέα μέθοδο επαγωγής για τα Δυναμικά Στοχαστικά Μοντέλα Γενικής Ισορροπίας, χρησιμοποιώντας μια Μπεϋζιανή ήμι-παραμετρική προσέγγιση. Η μέθοδος θεωρεί ένα σύνολο από συνθήκες ροπής οι οποίες εμπεριέχουν μη
openaire   +1 more source

Machine Learning Econometrics: Bayesian Algorithms and Methods [PDF]

open access: yesSSRN Electronic Journal, 2020
Bayesian inference in economics is primarily perceived as a methodology for cases where the data are short, that is, not informative enough in order to be able to obtain reliable econometric estimates of quantities of interest. In these cases, prior beliefs, such as the experience of the decision-maker or results from economic theory, can be explicitly
Korobilis, Dimitris, Pettenuzzo, Davide
openaire   +3 more sources

An Overview of Economics and Econometrics Related R Packages

open access: yesStats
This study provides a systematic overview of 207 econometrics-related R packages identified through CRAN and the Econometrics Task View. Using descriptive and inferential statistics and text mining to compute the word frequency and association among ...
Despina Michelaki   +2 more
doaj   +1 more source

Bayesian long-run prediction in time series models [PDF]

open access: yes, 1992
This paper considers Bayesian long-run prediction in time series models. We allow time series to exhibit stationary or non-stationary behavior and show how differences between prior structures which have little effect on posterior inferences can have a ...
Koop, Gary   +2 more
core   +7 more sources

Examining the Impact of Row Planting on Labor Use for Sustainable Food Production Among Maize Farmers in Rural Ghana

open access: yesAgribusiness, EarlyView.
ABSTRACT Smallholder farmers are reverting to traditional production methods due to the high opportunity costs and unintended consequences of new technologies. This study focuses on row planting technology, which is labor‐intensive and slow without mechanized operations.
Emmanuel Tetteh Jumpah   +4 more
wiley   +1 more source

Bayesian Nonparametric Calibration and Combination of Predictive Distributions [PDF]

open access: yes, 2015
We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work
Bassetti, Federico   +2 more
core   +4 more sources

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