Social and Behavioral Sciences Commons^™

Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans

Lonnie K. Stevans

The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …

Obtaining Critical Values For Test Of Markov Regime Switching, Douglas G. Steigerwald, Valerie Bostwick

Douglas G. Steigerwald

For Markov regime-switching models, testing for the possible presence of more than one regime requires the use of a non-standard test statistic. Carter and Steigerwald (forthcoming, Journal of Econometric Methods) derive in detail the analytic steps needed to implement the test ofMarkov regime-switching proposed by Cho and White (2007, Econometrica). We summarize the implementation steps and address the computational issues that arise. A new command to compute regime-switching critical values, rscv, is introduced and presented in the context of empirical research.

Disparities In Globalization Of The World Economies, Sudhanshu K. Mishra, Binod Kumar

Sudhanshu K Mishra

This paper constructs composite indices of globalization of 131 countries spread over the five continents and classified into World-I, World-II and World-III countries. KOF, the Business Cycle Research Institute in the Swiss Federal Institute of Technology, Zurich is the source of data used in this study. The Composite Indices of Globalization have been computed by Pena’s method, which attributes the most desirable properties to the indices so constructed. On the basis of these indices, the paper investigates into the trends of globalization and disparities in globalization for a period of 11 years (1999-2009). Disparities have been obtained as the Gini’s …

Regional Specialization: Measurement & Application, Zheng Lu

Zheng Lu (Chinese: 路征)

Various measure methods for regional specialization and evolution of China's regional specialization are introduced in this presentation.

Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter

Russell T Warne

This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson’s r (47.8%), χ2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach’s alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.

Construction Of Pena’S Dp2-Based Ordinal Synthetic Indicator When Partial Indicators Are Rank Scores, Sudhanshu K. Mishra

Sudhanshu K Mishra

The present study devises a computational scheme (and develops a FORTRAN 77 computer program) that may be appropriate to construct Pena’s DP2 (ordinal) synthetic indicator (Z) from the partial indicators (X) all of which are ordinal (ranking scores). An attempt has also been made to empirically apply the method (and the computer program) to obtain an ordinal synthetic indicator from a given ordinal data set.

Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne

Russell T Warne

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.

An Introduction To Item Response Theory For Health Behavior Researchers, Russell Warne

Russell T Warne

OBJECTIVE:

To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior.

METHOD:

Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n=1343 adolescents).

RESULTS:

An IRT 2PL model can produce viable substance use scores that differentiate different levels of substance use, resulting in improved precision and specificity at the respondent level.

CONCLUSION:

IRT is a viable option for health researchers who want to produce high-quality scores for unidimensional constructs. The results from our example-although not …

Testing For Regime Swtiching: A Comment, Douglas Steigerwald, Andrew Carter

Douglas G. Steigerwald

An autoregressive model with Markov-regime switching is analyzed that reflects on the properties of the quasi-likelihood ratio test developed by Cho and White (2007). For such a model, we show that consistency of the quasi-maximum likelihood estimator for the population parameter values, on which consistency of the test is based, does not hold. We describe a condition that ensures consistency of the estimator and discuss the consistency of the test in the absence of consistency of the estimator.

Positive Trait Item Response Models, Joseph F. Lucke

Joseph Lucke

A new item response model is proposed for which the trait is positive. Three such models, the loglogistic, the log-normal, and the Weibull, are presented along with their item information curves. The data of seven addiction items from the DSM-IV from a study on alcohol addiction is analyzed by these three models using Bayesian Markov chain Monte Carlo methods. The item characteristic curves and item information curves are presented for all three models. The person scores for four item response patterns are presented for the log-logistic model.

Excel Calculator For Assignment/Article "Compound Interest And The Power Of Saving", Richard H. Serlin

Richard H. Serlin

No abstract provided.

Syllabus Of Intermediate Macroeconomics (Master's Course), Reza Moosavi Mohseni Dr.

Reza Moosavi Mohseni

No abstract provided.