Ebooks Maximum Entropy Econometrics: Robust Estimation with Limited Data: 16 (Financial Economics and Quantitative Analysis Series)

Description Maximum Entropy Econometrics: Robust Estimation with Limited Data: 16 (Financial Economics and Quantitative Analysis Series)

In the theory and practice of econometrics the model, the methodand the data are all interdependent links in informationrecovery-estimation and inference. Seldom, however, are theeconomic and statistical models correctly specified, the datacomplete or capable of being replicated, the estimation rulesoptimal and the inferences free of distortion. Faced with theseproblems, Maximum Entropy Economeirics provides a new basis forlearning from economic and statistical models that may benon-regular in the sense that they are ill-posed or underdeterminedand the data are partial or incomplete. By extending the maximumentropy formalisms used in the physical sciences, the authorspresent a new set of generalized entropy techniques designed torecover information about economic systems. The authors compare thegeneralized entropy techniques with the performance of the relevanttraditional methods of information recovery and clearly demonstratetheories with applications including * Pure inverse problems that include first order Markov processes,and input-output, multisectoral or SAM models to * Inverse problems with noise that include statistical modelssubject to ill-conditioning, non-normal errors, heteroskedasticity,autocorrelation, censored, multinomial and simultaneous responsedata, as well as model selection and non-stationary and dynamiccontrol problems Maximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical sciences.

Maximum Entropy Econometrics: Robust Estimation with Limited Data: 16 (Financial Economics and Quantitative Analysis Series) PDF ePub

Maximum Entropy Econometrics: Robust Estimation with ~ He has published in economics, econometrics, statistics, mathematics, physics and philosophy journals. His books include Maximum Entropy Econometrics: Robust Estimation with Limited Data (coauthored with Judge and Miller) and Information and Entropy Econometrics - A Review and Synthesis.

Maximum entropy econometrics : robust estimation with ~ book Maximum entropy econometrics : robust estimation with limited data Amos Golan, George Garrett Judge, Douglas Miller Published in 1996 in Chichester England] New York by Wiley

Entropy / Free Full-Text / The Role of Entropy in the ~ The aim of this paper is to examine the role of thermodynamics, and in particular, entropy, for the development of economics within the last 150 years. The use of entropy has not only led to a significant increase in economic knowledge, but also to the emergence of such scientific disciplines as econophysics, complexity economics and quantum economics.

2013 Stata Conference New Orleans / Stata ~ Abstracts for the Stata Conference in New Orleans on July 18-19, 2013. The Stata Conference is enjoyable and rewarding for Stata users at all levels and from all disciplines.

Sequential Downscaling Methods for Estimation from ~ Abstract. Global change processes raise new estimation problems challenging the conventional statistical methods. These methods are based on the ability to obtain observations from unknown true probability distributions, whereas the new problems require recovering information from only partially observable or even unobservable variables.

Uses of entropy and divergence measures for evaluating ~ For the applications in econometrics, see the recent surveys by Maasoumi (1993) and Ullah (1996) and the book by Golan et al. (1996). However, it is clear from these works that in many areas of econometric research the usefulness of divergence measures has not been explored fully.

Livestock production planning under environmental risks ~ In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorrelated or even negatively correlated contingencies.

(PDF) A boundary analysis of ICT firms on Thailand Stock ~ Golan, A., Judge, G. and Miller, D. (1996) Maximum Entropy Econometrics: Robust . estimate time series data like financial data because it . robust estimation with limited data.

Fisher information and equilibrium distributions in ~ Fisher information provides the basis for a comprehensive alternative approach to the calculation of the equilibrium distributions of physics , , .This suggests that Fisher information may be useful for deriving these properties in emerging subfields of physics and it is the purpose of this Letter to report that Fisher information can indeed be so used in econophysics.

Interval Estimation: An Information Theoretic Approach ~ Maximum entropy econometrics: robust . The method is based on the procedure of maximal entropy, but is not limited to the estimation of . Diday added a new dimension to data analysis with his .

Econometrics I - New York University ~ Data Structures Observation mechanisms Passive, nonexperimental (the usual) Randomly assigned experiment (wishful) Active, experimental (occasional) The ‘natural experiment’ (occasional, limited) Data types Cross section Pure time series Panel – Longitudinal data – NLS Country macro data – Penn W.T.

Portfolio Selection with Robust Estimation / Operations ~ Parameter-free robust optimization for the maximum-Sharpe portfolio problem. European Journal of Operational Research. . Advances in Data Analysis and Classification, Vol. 5, . Efficient and Robust Estimation for Financial Returns: An Approach Based on q-Entropy.

Information and Entropy Econometrics--Editor's View ~ Since the maximum entropy procedure is constrained both by theory and data, this procedure is greatly helpful for economics in which theories are abound but relevant data are often limited.

Foundations for Automated Trading — Its the Information ~ Part of the Lecture Notes in Computer Science book series (LNCS, volume 3588) . Miller, D.: Maximum Entropy Econometrics: Robust Estimation with Limited Data. In: Financial Economics and Quantitative Analysis. John Wiley and Sons, Inc., .

Info-metrics - Wikipedia ~ Info-metrics is an interdisciplinary approach to scientific modeling, inference and efficient information processing.It is the science of modeling, reasoning, and drawing inferences under conditions of noisy and limited information. From the point of view of the sciences, this framework is at the intersection of information theory, statistical methods of inference, applied mathematics .

Information and Entropy Econometrics — A Review and ~ This maximum entropy estimation problem, subject to moment constraints, also known as the principle of maximum entropy, is applicable to large classes of problems in natural and social sciences .

Analysis of indoor PM2.5 exposure in Asian countries using ~ Highlights We analyzed Indoor PM 2.5 exposure for individual cohorts in 15 Asian countries. Time use surveys conducted in individual countries were used for our study. China has the highest estimate for average exposure concentration. Children and unemployed women between the ages of 35 and 64 are most highly exposed. Exposure concentration is greatly affected by people's use of time indoors.

Managing inventory systems of slow-moving items ~ In the numerical analysis, we examine three exemplary sets of industry time series with the characteristics summarized in Table 1. In general, the time series cover a broad range of fractions of zero-demand events (0.21–0.73) and also include higher levels of demand variation (SCVs up to 1.05).

Social accounting matrix: A new estimation methodology ~ If data are available, any of the above blocks can be further disaggregated depending on the objective of the analysis. The SAM is considered an extension of the traditional Input–Output (I/O) model proposed by Leontief, which also consists of a transaction matrix and records, in quantitative terms, the exchange flows of an economic system in a specific place, for a specific period.

(PDF) Updating and Estimating a Social Accounting Matrix ~ The cross-entropy method is recognized in adjusting and balancing SUT and IOT as it allows a wide range of prior information of various nature to be used efficiently in estimation (Canning & Wang .

Anil K. Bera - Wikipedia ~ Bera, Anil K. and Premaratne, G. (2005). 'A Test for Symmetry with Leptokurtic Financial Data'. Journal of Financial Econometrics, pp. 169–187. Bera, Anil K. and Park, S. (2004). Financial Data Analysis Using Maximum Entropy Approach, Proceedings of the International Statistical Conference, pp. 89–105. Bera, Anil K (2003).

Econometric analysis / Greene, William H / download ~ Econometric analysis Greene , William H Econometric Analysis serves as a bridge between an introduction to the field of econometrics and the professional literature for social scientists and other professionals in the field of social sciences, focusing on applied econometrics and theoretical background.

Entropy / Free Full-Text / Bayesian Estimation of ~ We propose a robust method to simultaneously localize multiple objects in cardiac computed tomography angiography (CTA) images. The relative prior distributions of the multiple objects in the three-dimensional (3D) space can be obtained through integrating the geometric morphological relationship of each target object to some reference objects. In cardiac CTA images, the cross-sections of .