Global ETD Search
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Showing 1 to 14 of 14 for “"Monte Carlo experiment"”.
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The Hausman test, and some alternatives, with heteroskedastic data
… them as a system. We examine these options in a Monte Carlo experiment. We conclude that in both these cases the preferred test is based on an artificial regression, perhaps using a robust covariance matrix estimator if heteroskedasticity is suspected. If instruments are weak (not highly …
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Finite sample properties of the maximum likelihood estimator in continuous time models
… both a fixed and a random initial value. A Monte Carlo study suggests that the performance of the formulae is reasonably good. Analytical bias expressions are then used in the second chapter to compute bias corrected estimators. This chapter also explores other methods for bias reduction …
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Essays in Nonparametric Econometrics
… via standard linear programming methods. A Monte Carlo experiment shows that the proposed estimator is competitive with the standard linear-programming estimator for moderately large sample sizes. The second chapter presents an improvement on existing recursive regression methods for pricing …
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A comparison of three prediction based methods of choosing the ridge regression parameter k
… and leverage. This was completed by using a Monte Carlo experiment.
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Sources of Fluctuations in Emerging Markets: DSGE Estimation with Mixed Frequency Data
… frequency strategy. In Chapter II, I perform a Monte Carlo experiment for a representative emerging economy to assess the relative merits of the mixed frequency strategy. Strikingly, estimations based on short quarterly series exhibit large upward bias for the contribution of permanent …
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Unstable Consumer Learning Models: Structural Estimation and Experimental Examination
… in two essays.</p><p>The first essay uses two experiments to examine how consumers learn when product quality is stable or changing. By collecting repeated measures of expectation data and experiences, more information enables estimation to discriminate between stable and unstable learning. The …
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Three essays on bias, bias reduction and estimation in autoregressive time series models
… series by use of the bias function. A simple Monte Carlo experiment provides evidence that the three estimators outperform OLS in terms of their bias reduction capabilities. Given the derived discontinuity of the bias function around the vicinity of unity, the second essay proposes an optimal …
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Three Essays in Applied Microeconometrics
… that is has well-behaved finite properties in a Monte Carlo experiment. An empirical example is also provided. Chapter 2 proposes a novel estimation strategy that accounts for asynchronous fieldwork, often found in multi-country surveys. The resulting biases are substantial and this is likely to …
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Choice modeling with observed and unobserved information search
… considered in decision-making. A preliminary Monte Carlo experiment is conducted to validate model identification and estimation.
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Essays on the Bayesian inequality restricted estimation
… estimation has gained ground after Markov Chain Monte Carlo process made it possible to sample from exact posterior distributions. This research aims at contributing to the ongoing debate about the relative virtues of the Frequentist and Bayesian theories by concentrating on the qualitative …
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Three essays in macroeconomic forecasting using Bayesian model selection
… variable selection method is assessed in a small Monte Carlo experiment, and in forecasting four short macroeconmic series for the UK using time-varying parameters vector autoregressions (TVP-VARs). I find that restricted models consistently improve upon their unrestricted counterparts in …
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Three essays in microeconometric methods and applications
… has a specific focus on econometric methods. A Monte Carlo experiment is used to investigate the extent to with the Poisson RE estimator is likely to produce results similar to ones obtained using the Poisson FE estimator when the random effects assumption is violated. The first order conditions …
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Model Selection, Uniform Inference and Nonparametric Regression
… the need for duplicate theories. An extensive Monte Carlo experiment corroborates the theoretical results by showing that the non-asymptotic bound becomes arbitrarily small as the sample size diverges. The second chapter returns to more classical statistics and econometrics by studying the …
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Monte Carlo Examination of Static and Dynamic Student t Regression Models
… operational form is then examined in a series of Monte Carlo experiments. The model is judged based on its usefulness for estimation and testing and its ability to model the heteroskedastic conditional variance. It is also compared with the traditional Normal Linear Regression Model. Subsequently …