Abstract:
The theme of unit roots in macroeconomic time series have received a great amount of attention in terms of theoretical and applied research over the last three decades. Since the seminal work by Nelson and Plosser (1982), testing for the presence of a unit root in the time series data has become a topic of great concern. This issue gained further momentum with Perron’s 1989 paper which emphasized the importance of structural breaks when testing for unit root processes.This paper reviews the available literature on unit root tests taking into account possible structural breaks. An important distinction between testing for breaks when the break date is known or exogenous and when the break date is endogenously determined is explained. We also describe tests for both single and multiple breaks. Additionally, the paper provides a survey of the empirical studies and an application in order for readers to be able to grasp the underlying problems that time series with structural breaks arecurrently facing.

Abstract:
Background and objectives There is no doubt that the dramatic worldwide increase in obesity prevalence is due to changes in environmental factors. However, twin studies suggest that genetic differences are responsible for the major part of the variation in body mass index (BMI) and other measures of body fatness within populations. Several recent studies suggest that the genetic effects on adiposity may be stronger when combined with presumed risk factors for obesity. We tested the hypothesis that a higher prevalence of obesity and overweight and a higher BMI mean is associated with a larger genetic variation in BMI. Methods The data consisted of self-reported height and weight from two Danish twin surveys in 1994 and 2002. A total of 15,017 monozygotic and dizygotic twin pairs were divided into subgroups by year of birth (from 1931 through 1982) and sex. The genetic and environmental variance components of BMI were calculated for each subgroup using the classical twin design. Likewise, the prevalence of obesity, prevalence of overweight and the mean of the BMI distribution was calculated for each subgroup and tested as explanatory variables in a random effects meta-regression model with the square root of the additive genetic variance (equal to the standard deviation) as the dependent variable. Results The size of additive genetic variation was positively and significantly associated with obesity prevalence (p = 0.001) and the mean of the BMI distribution (p = 0.015). The association with prevalence of overweight was positive but not statistically significant (p = 0.177). Conclusion The results suggest that the genetic variation in BMI increases as the prevalence of obesity, prevalence of overweight and the BMI mean increases. The findings suggest that the genes related to body fatness are expressed more aggressively under the influence of an obesity-promoting environment.

Abstract:
This paper investigates the stationary characteristics of computed real interest rates with nominal interest rates and inflation for 22 OECD countries. Using quarterly data over the 2000 – 2010 period, LM unit root test is employed which endogenously determines up to two structural breaks in level and trend. The empirical findings suggest a combination of stationary and nonstationary results for real interest rates, nominal interest rates and inflation. Besides, the internal stationarity or nonstationary interactions of real and nominal interest rates are investigated by inflation. The results indicate that stationary nominal interest rates and inflation cause stationary real interest rates. At the same time nonstationary nominal interest rates and inflation could cause a stationary or nonstationary real interest rate with respect to cointegration. Stationary nominal interest rate and nonstationary real interest rate cause to nonstationary real interest rate while nonstationary nominal interest rate and stationary inflation could cause stationary or nonstationary real interest rate.

Abstract:
In the last years, many studies have analyzed the stationarity of reel exchange rates which gives important knowledge about economic stability of countries. The panel unit root tests which include both pooled and individual unit root tests are used frequently to analyze the stationarity of real exchange rates. Generally, structural breaks issue have taken place in macroeconomic time series for some years. If unit root tests are used without taking account these structural breaks, stationarity hypothesis can be rejected mistakenly. In this study, panel unit root tests with and without structural breaks were used to analyze the validity of Purchasing Power Parity hypothesis in 25 OECD countries. According to the results, while in panel unit root tests with no break, PPP theory is valid for only 10 countries; it is valid for all countries in panel unit root tests with structural breaks.

Abstract:
This paper extends the method of regressing production and sales variables on a set of seasonal dummy variables and a linear trend for empirical tests on the production smoothing hypothesis of inventory investment. Unit root testing procedures form the basis for constructing the bootstrap confidence intervals for the ratio of the variance of production to the variance of sales. Models used to test for a unit root when there are structural breaks in the linear time trend are converted to equations comprising deterministic and stochastic components. A limiting distribution of the test statistic is derived. Bootstrap resampling is conducted over deterministic parts of the converted equations to construct confidence intervals for the relative variance ratio for G7 countries. Primary findings for these countries are production-counter smoothing phenomena.

Abstract:
The random walk is used as a model expressing equitableness and the effectiveness of various finance phenomena. Random walk is included in unit root process which is a class of nonstationary processes. Due to its nonstationarity, the least squares estimator (LSE) of random walk does not satisfy asymptotic normality. However, it is well known that the sequence of partial sum processes of random walk weakly converges to standard Brownian motion. This result is so-called functional central limit theorem (FCLT). We can derive the limiting distribution of LSE of unit root process from the FCLT result. The FCLT result has been extended to unit root process with locally stationary process (LSP) innovation. This model includes different two types of nonstationarity. Since the LSP innovation has time-varying spectral structure, it is suitable for describing the empirical financial time series data. Here we will derive the limiting distributions of LSE of unit root, near unit root and general integrated processes with LSP innovation. Testing problem between unit root and near unit root will be also discussed. Furthermore, we will suggest two kind of extensions for LSE, which include various famous estimators as special cases. 1. Introduction Since the random walk is a martingale sequence, the best predictor of the next term becomes the value of this term. In this sense, the random walk is used as a model expressing equitableness and the effectiveness of various finance phenomena in economics. Furthermore, because the random walk is a unit root process, taking the difference of the random walk, we can recover the independent sequence. However, the information of the original sequence will be lost by taking the difference when it does not include a unit root. Therefore, the testing of the existence of unit root in the original sequence becomes important. In this section, we review the fundamental asymptotic results for unit root processes. Let be i.i.d. random variables, where , and define the partial sum which is the so-called random walk process. Random walk corresponds to the first-order autoregressive (AR(1)) model with unit coefficient. Therefore, random walk is included in unit root (I(1)) processes which is a class of nonstationary processes. Let be the space of all real-valued continuous functions defined on . For random walk process, we construct the sequence of the processes of the partial sum in as It is well known that the partial sum process converge weakly to a standard Brownian motion on , namely, where denotes the distribution law of the

Abstract:
This paper presents a System Dynamics perspective to establish a causal model to demonstrate how organizations can achieve an increased market standing by leveraging Knowledge Management (KM) as a tool for Innovation. The study is grounded in the various models that are discussed in the literature and the model is developed from research surrounding this theory. It can be concluded that, the key to achieve an increased market standing in a dynamic environment arises from consistent innovation by companies that come out with newer and better products and services. New product development stems from a robust Knowledge Management system. This paper very strongly recommends KM initiative in innovating new products and services using a causal approach and designs a framework to use KM as a strategic tool. It also emphasizes on the interaction between KM and its influence on Innovation through a feedback loop system using System Dynamics.

Abstract:
Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

Abstract:
This paper aims to investigate the unemployment hysteresis hypothesis, in which the endogenously determined break points are incorporated, by using annual data of actual urban unemployment rates during 1978-2009 in China. We treat the break date as unknown and utilize recursive, rolling and sequential tests to determine the endogenous structural breaks which are caused by external shocks. Our empirical findings show that three structural breaks existed in the time series of China’s actual urban unemployment rates and we can not reject the unit-root hypothesis, which is consistent with the hysteresis hypothesis of unemployment. Key words: Structural breaks; Unemployment hysteresis; External shocks

Abstract:
It is widely accepted that supersonic, magnetised turbulence plays a fundamental role for star formation in molecular clouds. It produces the initial dense gas seeds out of which new stars can form. However, the exact relation between gas compression, turbulent Mach number, and magnetic field strength is still poorly understood. Here, we introduce and test an analytical prediction for the relation between the density variance and the root-mean-square Mach number in supersonic, isothermal, magnetised turbulent flows. We approximate the density and velocity structure of the interstellar medium as a superposition of shock waves. We obtain the density contrast considering the momentum equation for a single magnetised shock and extrapolate this result to the entire cloud. Depending on the field geometry, we then make three different assumptions based on observational and theoretical constraints: B independent of density, B proportional to the root square of the density and B proportional to the density. We test the analytically derived density variance--Mach number relation with numerical simulations, and find that for B proportional to the root square of the density, the variance in the logarithmic density contrast, $\sigma_{\ln \rho/\rho_0}^2=\ln[1+b^2\mathscr{M}^2\beta_0/(\beta_0+1)]$, fits very well to simulated data with turbulent forcing parameter b=0.4, when the gas is super-Alfv\'enic. However, this result breaks down when the turbulence becomes trans-Alfv\'enic or sub-Alfv\'enic, because in this regime the turbulence becomes highly anisotropic. Our density variance--Mach number relations simplify to the purely hydrodynamic relation as the ratio of thermal to magnetic pressure $\beta_0$ approaches infinite.