Profile-based Maximum Penalised Likelihood Trajectory Estimation from Space-borne LOS Measurements
In: Defence science journal: a journal devotet to science & technology in defence, Band 66, Heft 3, S. 278-286
ISSN: 0011-748X
In: Defence science journal: a journal devotet to science & technology in defence, Band 66, Heft 3, S. 278-286
ISSN: 0011-748X
In: Themes in modern econometrics
Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn.
In: A Stata Press publication
The second edition of this book contains several new recipes illustrating how do-files, ado-files, and Mata functions can be used to solve programming problems. Several recipes have also been updated to reflect new features in Stata added between versions 10 and 14. The discussion of maximum-likelihood function evaluators has been significantly expanded in this edition. The new topics covered in this edition include factor variables and operatores; use of margins, marginsplot, and suest; Mata-based likelihood function evaluators; and associative arrays. (Preface)
In: Journal of political economy, Band 92, Heft 5, S. 841-851
ISSN: 0022-3808
THIS PAPER DEVELOPS A FINITE-HORIZON DYNAMIC STOCHASTIC MODEL OF DISCRETE CHOICE WITH RESPECT TO LIFE-CYCLE FERTILITY WITHIN AN ENVIRONMENT WHERE INFANT SURVIVAL IS UNCERTAIN. THE MODEL YIELDS IMPLICATIONS FOR THE NUMBER, TIMING, AND SPACING OF CHILDREN. A TRACTABLE ESTIMATION METHOD IS DEVELOPED FOR THE LINEAR CONSTRAINT-QUADRATIC UTILITY CASE THAT IS INTIMATELY TIED TO THE DYNAMIC OPTIMIZATION PROBLEM, AND THE METHOD IS APPLIED TO MALAYSIAN HOUSEHOLD DATA. ESTIMATION IS BASED ON INTEGRATING THE NUMERICAL SOLUTION OF THE DYNAMIC PROGRAMMING MODEL OF BEHAVIOR WITH A MAXIMUM LIKELIHOOD PROCEDURE.
In: Social science quarterly, Band 67, Heft 2, S. 353-364
ISSN: 0038-4941
An examination of the determinants of the award & receipt of child support payments for ever-married mothers (N = 2,416) based on the Mar/Apr 1979 Match File of the Current Population Survey. Previous studies are improved on by using a large nationally representative data set & nonlinear maximum likelihood estimation techniques. The results show that SE characteristics associated with the needs of the custodial mother tend to be more important as a determinant of the award of child support than its receipt, while characteristics associated with the ability or desire of the absent father to pay support are important in both its receipt & award. 4 Tables, 10 References. HA
In: Statistische Diskussionsbeiträge Nr. 24
This paper tries to apply common methods to estimate unbiased coefficients for the return to schooling in Germany for the year 2004. Based on the simple Mincer-type wage equation, the return to schooling is around 9.5% per year. There is no sheepskin effect. As expected the return in the private sector is higher than in the public sector. Females have a higher return than males, but there are no differences between East and West Germans. An Instrumental Variables and a 3-Stage-Least-Squares approach give very high returns. For correcting the sample selection, the Heckman Two Step Procedure and the Heckman Maximum Likelihood Approach are used. For both methods, the coefficients are very similar, but higher than without correcting for it.
In: Public choice, Band 51, Heft 1, S. 71-80
ISSN: 0048-5829
R. G. Niemi ("Majority Decision Making with Partial Unidimensionality," American Political Science Review, 1969, 63, 488-497), in an important but neglected paper, found that when orderings were drawn from a simulation based on the impartial culture, the greater the proportion of voter orderings that were single-peaked (a condition he called partial single-peakedness), the more likely there was to be a transitive group ordering. In addition, the likelihood of transitivity increased with group size. However, Niemi's simulation was restricted to the case of three alternatives, & he provided no theoretical explanation for the results of his simulation. This is provided here in terms of a model based on the idea of net preferences, & Niemi's results are extended for the general case of any finite number of alternatives, for electorates that are large relative to the number of alternatives being considered. In addition to providing a rationale for Niemi's simulation results, the ideas of net preferences & opposite preferences have a wide range of potential applications. 23 References. HA
In: CESifo working paper series 4725
In: Empirical and theoretical models
This paper explores the properties of pre-test strategies in estimating a linear Cliff-Ord-type spatial model when the researcher is unsure about the nature of the spatial dependence. More specifically, the paper explores the finite sample properties of the pre-test estimators introduced in Florax et al. (2003), which are based on Lagrange Multiplier (LM) tests, within the context of a Monte Carlo study. The performance of those estimators is compared with that of the maximum likelihood (ML) estimator of the encompassing model. We find that, even in a very simple setting, the bias of the estimates generated by pre-testing strategies can be very large and the empirical size of tests can differ substantially from the nominal size. This is in contrast to the ML estimator. However, if the true data generating process corresponds to the spatial error or lag model the issues arising with the pre-test estimators seem to be lessened.
In: The journal of modern African studies: a quarterly survey of politics, economics & related topics in contemporary Africa, Band 37, Heft 4, S. 597-619
ISSN: 0022-278X
World Affairs Online
In: Political behavior, Band 18, Heft 4, S. 393-412
ISSN: 0190-9320
In: Methodology in the social sciences
"The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website includes datasets and analysis examples from the book, up-to-date software information, and other resources. Subject areas/Key words: advanced quantitative methods, management, survey, longitudinal, structural equation modeling, handling, how to handle, incomplete, multivariate, social research, behavioral sciences, statistical techniques, textbooks, seminars, doctoral courses, multiple imputation, models, MCAR, MNAR, Bayesian Audience: Researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science."--
This book has grown out of half a century of experience of teaching undergraduate econometrics at the Econometric Institute in Rotterdam. It combines a solid exposition of econometric methods with the application-oriented approach that is characteristic of the Rotterdam tradition in econometrics. Covering basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, generalized method of moments), this books explains their practical applications in modern business and economics and provides examples of these. Much attention is paid to the creative process of model building, with due attention for diagnostic testing and model improvement. The last part of the book is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). In addition, data sets and (for instructors) full solutions of all exercises are available to readers. The book provides a thorough training in modern applications of econometrics to practical questions in business and economics. It is guided by a spirit of practical learning, and provides a wealth of examples and practical exercises based on a wide variety of data sets drawn from business and micro, macro, and international economics. The book will be suitable for introductory applied econometrics courses at undergraduate level up to more advanced courses at the graduate level.
In: Journal of peace research, Band 39, Heft 4, S. 395-416
ISSN: 0022-3433
World Affairs Online