نتایج جستجو برای: bayesian estimation jel classification e22
تعداد نتایج: 816103 فیلتر نتایج به سال:
This paper presents an analytically tractable continuous-time general equilibrium model with investment irreversibility and fixed adjustment costs. In the model, there is a continuum of firms that are subject to idiosyncratic shocks to capital. Although the presence of investment frictions lowers consumer welfare, it may raise or reduce the long-run average capital stock, depending on the degre...
Using a recursive empirical model of the real interest rate, GDP growth and the primary government deficit in the United States, I solve for the ergodic distribution of the debt/GDP ratio. If such a distribution exists, the government is satisfying its intertemporal budget constraint. One key finding is that historical fiscal policy would bring the current high-debt ratio back to its normal lev...
The factors behind the increase in the relative wages of skilled workers in developing countries are still not well understood. The authors use data from Peru to analyze the determinants of withinindustry share of skilled workers. They use a translog cost function for gross output and are therefore able to incorporate the effects of materials, both domestic and imported, in addition to capital....
We assess the impact of the Sarbanes-Oxley Act of 2002 on corporate investment in an investment Euler equation framework, where a dummy for the passage of the Act is allowed to affect the rate at which managers discount future investment payoffs. Using generalized method of moments estimators, we find that the rate U.S. firm managers apply to discount investment projects rises significantly aft...
A recently proposed Bayesian modeling framework for classification facilitates both the analysis and optimization of error estimation performance. The Bayesian error estimator is then defined to have optimal mean-square error performance, but in many situations closed-form representations are unavailable and approximations may not be feasible. To address this, we present a method to optimally c...
In the context of an autoregressive panel data model with fixed effect, we examine the relationship between consistent parameter estimation and consistent model selection. Consistency in parameter estimation is achieved by using the tansformation of the fixed effect proposed by Lancaster (2002). We find that such transformation does not necessarily lead to consistent estimation of the autoregre...
Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...
There are different types of classification methods for classifying the certain data. All the time the value of the variables is not certain and they may belong to the interval that is called uncertain data. In recent years, by assuming the distribution of the uncertain data is normal, there are several estimation for the mean and variance of this distribution. In this paper, we co...
background often, there is no access to sufficient sample size to estimate the prevalence using the method of direct estimator in all areas. the aim of this study was to compare small area’s bayesian method and direct method in estimating the prevalence of steatosis in obese and overweight children. materials and methods: in this cross-sectional study, was conducted on 150 overweight and obese ...
We provide a characterization of virtual Bayesian implementation in pure strategies for environments satisfying no-total-indifference. A social choice function in such environments is virtually Bayesian implementable if and only if it satisfies incentive compatibility and a condition we term virtual monotonicity. The latter is weaker than Bayesian monotonicity known to be necessary for Bayesian...
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