Is inflation persistent? Evidence from a time-varying unit root model

2021 ◽  
pp. 101577
Author(s):  
Neluka Devpura ◽  
Susan Sunila Sharma ◽  
P.K.G. Harischandra ◽  
Lasitha Pathberiya
Keyword(s):  
Unit Root ◽  
Time Varying ◽  
Root Model

scholarly journals Lie-Algebraic Approach for Pricing Zero-Coupon Bonds in Single-Factor Interest Rate Models

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
C. F. Lo
Keyword(s):  
Interest Rate ◽  
Algebraic Approach ◽  
Dynamical Symmetry ◽  
Bond Pricing ◽  
Model Parameters ◽  
Time Varying ◽  
Single Factor ◽  
Bond Price ◽  
Interest Rate Models ◽  
Root Model

The Lie-algebraic approach has been applied to solve the bond pricing problem in single-factor interest rate models. Four of the popular single-factor models, namely, the Vasicek model, Cox-Ingersoll-Ross model, double square-root model, and Ahn-Gao model, are investigated. By exploiting the dynamical symmetry of their bond pricing equations, analytical closed-form pricing formulae can be derived in a straightfoward manner. Time-varying model parameters could also be incorporated into the derivation of the bond price formulae, and this has the added advantage of allowing yield curves to be fitted. Furthermore, the Lie-algebraic approach can be easily extended to formulate new analytically tractable single-factor interest rate models.

LSTUR regression theory and the instability of the sample correlation coefficient between financial return indices

2020 ◽  
Author(s):  
Tim Ginker ◽  
Offer Lieberman
Keyword(s):  
Correlation Coefficient ◽  
Unit Root ◽  
Asymptotic Theory ◽  
Financial Return ◽  
Spurious Regression ◽  
Root Model ◽  
Sampling Window ◽  
Sample Correlation ◽  
Underlying Processes ◽  
Regression Theory

Summary It is well known that the sample correlation coefficient between many financial return indices exhibits substantial variation on any reasonable sampling window. This stylised fact contradicts a unit root model for the underlying processes in levels, as the statistic converges in probability to a constant under this modeling scheme. In this paper, we establish asymptotic theory for regression in local stochastic unit root (LSTUR) variables. An empirical application reveals that the new theory explains very well the instability, in both sign and scale, of the sample correlation coefficient between gold, oil, and stock return price indices. In addition, we establish spurious regression theory for LSTUR variables, which generalises the results known hitherto, as well as a theory for balanced regression in this setting.

Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances

2014 ◽  
Vol 35 (5) ◽  
pp. 751-781 ◽  
Author(s):  
Matei Demetrescu ◽  
Christoph Hanck
Keyword(s):  
Unit Root ◽  
Robust Inference ◽  
Time Varying ◽  
Near Unit Root

scholarly journals A multivariate stochastic unit root model with an application to derivative pricing

2017 ◽  
Vol 196 (1) ◽  
pp. 99-110 ◽  
Author(s):  
Offer Lieberman ◽  
Peter C.B. Phillips
Keyword(s):  
Unit Root ◽  
Derivative Pricing ◽  
Root Model

Panel Unit-root Tests for Heteroskedastic Panels

2018 ◽  
Vol 18 (1) ◽  
pp. 184-196 ◽  
Author(s):  
Helmut Herwartz ◽  
Simone Maxand ◽  
Fabian H. C. Raters ◽  
Yabibal M. Walle
Keyword(s):  
Unit Root ◽  
Serial Correlation ◽  
Unit Root Tests ◽  
Order Selection ◽  
Time Varying ◽  
Development Research ◽  
Computational Statistics ◽  
Panel Unit Root Tests ◽  
Panel Unit Root ◽  
European Governance

In this article, we describe the command xtpurt, which implements the heteroskedasticity-robust panel unit-root tests suggested in Herwartz and Siedenburg (2008, Computational Statistics and Data Analysis 53: 137–150), Demetrescu and Hanck (2012a, Economics Letters 117: 10–13), and, recently, Herwartz, Maxand, and Walle (2017, Center for European, Governance and Economic Development Research Discussion Papers 314). While the former two tests are robust to time-varying volatility when the data contain only an intercept, the latter test is unique because it is asymptotically pivotal for trending heteroskedastic panels. Moreover, xtpurt incorporates lag-order selection, prewhitening, and detrending procedures to account for serial correlation and trending data.

REGIME-SWITCHING AUTOREGRESSIVE COEFFICIENTS AND THE ASYMPTOTICS FOR UNIT ROOT TESTS

2008 ◽  
Vol 24 (4) ◽  
pp. 1137-1148
Author(s):  
Giuseppe Cavaliere ◽  
Iliyan Georgiev
Keyword(s):  
Sample Size ◽  
Unit Root ◽  
Regime Switching ◽  
Asymptotic Theory ◽  
Unit Roots ◽  
Stationary Regime ◽  
Unit Root Tests ◽  
Asymptotic Results ◽  
Switching Models ◽  
Root Model

Most of the asymptotic results for Markov regime-switching models with possible unit roots are based on specifications implying that the number of regime switches grows to infinity as the sample size increases. Conversely, in this note we derive some new asymptotic results for the case of Markov regime switches that are infrequent in the sense that their number is bounded in probability, even asymptotically. This is achieved by (inversely) relating the probability of regime switching to the sample size. The proposed asymptotic theory is applied to a well-known stochastic unit root model, where the dynamics of the observed variable switches between a unit root regime and a stationary regime.

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