Bayesian Model Averaging And Endogeneity Under Model Uncertainty PDF Download
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Author | : Theo S. Eicher |
Publisher | : |
Total Pages | : 0 |
Release | : 2012 |
Genre | : |
ISBN | : |
Download Bayesian Model Averaging and Endogeneity Under Model Uncertainty Book in PDF, ePub and Kindle
Recent approaches to development accounting reflect substantial model uncertainty at both the instrument and the development determinant level. Bayesian Model Averaging (BMA) has been proven useful in resolving model uncertainty in economics, and we extend BMA to formally account for model uncertainty in the presence of endogeneity. The new methodology is shown to be highly efficient and to reduce many instrument bias; in a simulation study we found that IVBMA estimates reduced mean squared error by 60% over standard IV estimates. We also introduce Bayesian over and under-identification tests that are based on model averaged predictive p-values. This approach is shown to mitigate the reduction in power these tests experience as dimension increases. In a simulation study where the exogeneity of the instrument is compromised we show that the classical Sargan test has a power of 0.2% while our Bayesian over-identification test has a power of 98% at detecting the violation of the exogeneity assumption. An application of our method to a prominent development accounting approach leads to new insights regarding the primacy of institutions. Using identical data and robustness specifications we find support not only for institutions, but also for geography and integration, once both model uncertainty and endogeneity have been jointly addressed.
Author | : Alin Mirestean |
Publisher | : International Monetary Fund |
Total Pages | : 48 |
Release | : 2009-04 |
Genre | : Business & Economics |
ISBN | : |
Download Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods Book in PDF, ePub and Kindle
Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation results suggest that asymptotically our methodology performs well both in Bayesian model selection and averaging. In particular, LIBMA recovers the data generating process very well, with high posterior inclusion probabilities for all the relevant regressors, and parameter estimates very close to the true values. These findings suggest that our methodology is well suited for inference in dynamic panel data models with short time periods in the presence of endogenous regressors under model uncertainty.
Author | : Huigang Chen |
Publisher | : International Monetary Fund |
Total Pages | : 47 |
Release | : 2011-10-01 |
Genre | : Business & Economics |
ISBN | : 1463921306 |
Download Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model Book in PDF, ePub and Kindle
This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation results suggest that asymptotically our methodology performs well both in Bayesian model averaging and selection. In particular, LIBMA recovers the data generating process well, with high posterior inclusion probabilities for all the relevant regressors, and parameter estimates very close to their true values. These findings suggest that our methodology is well suited for inference in short dynamic panel data models with endogenous regressors in the context of model uncertainty. We illustrate the use of LIBMA in an application to the estimation of a dynamic gravity model for bilateral trade.
Author | : Mr.Charalambos G. Tsangarides |
Publisher | : INTERNATIONAL MONETARY FUND |
Total Pages | : 21 |
Release | : 2004-04-01 |
Genre | : Business & Economics |
ISBN | : 9781451849028 |
Download A Bayesian Approach to Model Uncertainty Book in PDF, ePub and Kindle
This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it simultaneously addresses the biases associated with endogenous and omitted variables by incorporating a panel data systems Generalized Method of Moments estimator. Practical applications of the developed methodology are discussed, including testing for the robustness of explanatory variables in the analyses of the determinants of economic growth and poverty.
Author | : Anne Miloschewski |
Publisher | : |
Total Pages | : |
Release | : 2019 |
Genre | : |
ISBN | : |
Download Bayesian Treatment of Model Uncertainty Under Endogeneity Book in PDF, ePub and Kindle
Author | : |
Publisher | : Cuvillier Verlag |
Total Pages | : 182 |
Release | : 2006-04-24 |
Genre | : Science |
ISBN | : 3736918445 |
Download Estimating and Correcting the Effects of Model Selection Uncertainty Book in PDF, ePub and Kindle
Most applied statistical analyses are carried out under model uncertainty, meaning that the model which generated the observations is unknown, and so the data are first used to select one of a set of plausible models by means of some selection criterion. Generally the data are then used to make inferences about some quantity of interest, ignoring model selection uncertainty, i.e. the fact that the selection step was carried out using the same data, and despite the known fact that this leads to invalid inferences. This thesis investigates several issues relating to this problem from both the Bayesian and the frequentist points of view, and offers new suggestions for dealing with it. We examine Bayesian model averaging (BMA) and point out that its frequentist performance is not always well-defined because, in some cases, it is unclear whether BMA methodology is truly Bayesian. We illustrate the point with a “fully Bayesian model averaging" that is applicable when the quantity of interest is parametric.
Author | : |
Publisher | : |
Total Pages | : 38 |
Release | : 2006 |
Genre | : |
ISBN | : |
Download Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes Book in PDF, ePub and Kindle
Author | : Eduardo Ley |
Publisher | : |
Total Pages | : 32 |
Release | : 2007 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression Book in PDF, ePub and Kindle
This paper examines the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. The paper analyzes the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors, and predictive performance. The analysis illustrates these issues in the context of cross-country growth regressions using three datasets with 41 to 67 potential drivers of growth and 72 to 93 observations. The results favor particular prior structures for use in this and related contexts.
Author | : Francesco Ravazzolo |
Publisher | : |
Total Pages | : 43 |
Release | : 2010 |
Genre | : |
ISBN | : |
Download Bayesian Model Averaging in the Presence of Structural Breaks Book in PDF, ePub and Kindle
This paper develops a return forecasting methodology that allows for instability in the relationship between stock returns and predictor variables, for model uncertainty, and for parameter estimation uncertainty. The predictive regression specification that is put forward allows for occasional structural breaks of random magnitude in the regression parameters, and for uncertainty about the inclusion of forecasting variables, and about the parameter values by employing Bayesian Model Averaging. The implications of these three sources of uncertainty, and their relative importance, are investigated from an active investment management perspective. It is found that the economic value of incorporating all three sources of uncertainty is considerable. A typical in vestor would be willing to pay up to several hundreds of basis points annually to switch from a passive buy-and-hold strategy to an active strategy based on a return forecasting model that allows for model and parameter uncertainty as well as structural breaks in the regression parameters.
Author | : Roberto Leon-Gonzalez |
Publisher | : |
Total Pages | : |
Release | : 2015 |
Genre | : |
ISBN | : |
Download Endogeneity and Panel Data in Growth Regressions Book in PDF, ePub and Kindle