24,360 research outputs found
A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey
Full text linkImportant empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.
A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey
Full text linkImportant empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.
Theory and inference for a Markov switching Garch model.
Full text linkWe develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity and existence of moments of the process. Because of path dependence, maximum likelihood estimation is not feasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We illustrate the model on SP500 daily returns.GARCH, Markov-switching, Bayesian inference.
Predicting the author of Twitter posts with Markov chain analysis
Full text linkGiven a set of text with known authors, is it possible to take new text, not knowing who wrote it, and correctly identify the author? One way to do this is to analyze the text using Markov chains. This research project will first attempt to answer this question using books available in the public domain. Using what is learned from trying to identify authors of books, the primary goal of this project is to identify the best way to guess the author of a post on the social media network Twitter using Markov chains
Report on Meteorological Research March 1, 1935 (m-1)
No full textThe object of the report was to elucidate in detail the various features of the research program in meteorology being carried on at the Daniel Guggenheim Airship Institute in Akron, Ohio. Mr. L. J. Fangman, of the U.S. Weather Bureau, was collaborating with the author in carrying out work such as a study of autographic records of the various meteorological elements during frontal passages with a view to the possible prediction of the intensity of the accompanying disturbance as it may affect the operation of aircraft and a study of atmospheric gustiness with a view to finding the dependence between frequency end amplitude of velocity fluctuations and the vertical temperature and velocity gradients
Robust Markov Decision Processes
Full text linkMarkov decision processes (MDPs) are powerful tools for decision making in uncertain dynamic environments. However, the solutions of MDPs are of limited practical use due to their sensitivity to distributional model parameters, which are typically unknown and have to be estimated by the decision maker. To counter the detrimental effects of estimation errors, we consider robust MDPs that offer probabilistic guarantees in view of the unknown parameters. To this end, we assume that an observation history of the MDP is available. Based on this history, we derive a confidence region that contains the unknown parameters with a pre-specified probability 1-ß. Afterwards, we determine a policy that attains the highest worst-case performance over this confidence region. By construction, this policy achieves or exceeds its worst-case performance with a confidence of at least 1 - ß. Our method involves the solution of tractable conic programs of moderate size.
Understanding Markov-Switching Rational Expectations Models
Full text linkWe develop a set of necessary and sufficient conditions for equilibria to be determinate in a class of forward-looking Markov-switching rational expectations models and we develop an algorithm to check these conditions in practice. We use three examples, based on the new-Keynesian model of monetary policy, to illustrate our technique. Our work connects applied econometric models of Markov-switching with forward looking rational expectations models and allows an applied researcher to construct the likelihood function for models in this class over a parameter space that includes a determinate region and an indeterminate region.
Realised and Optimal Monetary Policy Rules in an Estimated Markov-Switching DSGE Model of the United Kingdom
Full text linkThis paper conducts a systematic investigation of parameter instability in a small open economy DSGE model of the UK economy over the past thirty-five years. Using Bayesian analysis, we find a number of Markov-switching versions of the model provide a better fit for the UK data than a model with time-invariant parameters. The Markov-switching DSGE model that has two independent Markov-chains - one governing the shifts in UK monetary policy and nominal price rigidity and one governing the standard deviations of shocks - is selected as the best fitting model. The preferred model is then used to evaluate and design monetary policy. For the latter, we use the Markov-Jump-Linear-Quadratic (MJLQ) model, as it incorporates abrupt changes in structural parameters into derivations of the optimal and arbitrary policy rules. It also reveals the entire forecasting distribution of the targeted variables. To our knowledge, this is the first paper that attempts to evaluate and design UK monetary policy based on an estimated open economy Markov-switching DSGE model.DSGE models; Markov-switching; Bayesian analysis
(Fourth) Report on Meteorological Activities at the DGAI (8-1-36)(Weather Bureau Copy)
No full textThis report is on the investigations of frontal phenomena at the Daniel Guggenheim Airship Institute in Akron, Ohio from January 1, 1935 through August 1, 1936. The investigation was carried out with the cooperation of the U.S. Bureau of Aeronautics, the U.S. Weather Bureau, the California Institute of Technology, and the Guggenheim Airship Institute. Mr. R.C. Robinson of the Weather Bureau cooperated with the author in carrying out the investigation. The object of the investigation was to determine the intensity of the atmospheric disturbances (i.e. rapidity of wind shift and gustiness) accompanying the passage of cold fronts, along with a study of the characteristics of the air masses involved and other features which might affect the intensity of the disturbance. The report treated thirty cold fronts which passed the station during 1935 to 1936
Archives and Images as Repositories of Time, Language, and Forms from the Past: A Conversation with Daniel Eisenberg
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