nep-ets New Economics Papers
on Econometric Time Series
Issue of 2018‒05‒28
ten papers chosen by
Jaqueson K. Galimberti
KOF Swiss Economic Institute

  1. Asymptotic Theory for Near Integrated Process Driven by Tempered Linear Process By Farzad Sabzikar; Qiying Wang; Peter C.B. Phillips
  2. Testing for cointegration with threshold adjustment in the presence of structural breaks By Schweikert, Karsten
  3. Specification tests for non-Gaussian maximum likelihood estimators By Gabriele Fiorentini; Enrique Sentana
  4. Non-parametric Estimation of GARCH (2, 2) Volatility model: A new Algorithm By Cassim, Lucius
  5. Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model By Audrone Virbickaite; Hedibert F. Lopes; Maria Concepción Ausín; Pedro Galeano
  6. Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations By Baumeister, Christiane; Hamilton, James
  7. Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach By Susana Martins; Cristina Amado
  8. Some Empirical Evidence on Models of the Fisher Relation: Post-Data Comparison By KIM, Jae-Young; PARK, Woong Yong
  9. Robust analysis of convergence in per capita GDP in BRICS economies By Andrew Phiri
  10. A time series model of interest rates with the effective lower bound By Benjamin K Johannsen; Elmar Mertens

  1. By: Farzad Sabzikar (Dept. of Statistics, Iowa State University); Qiying Wang (University of Sydney); Peter C.B. Phillips (Cowles Foundation, Yale University)
    Abstract: This paper develops an asymptotic theory for near-integrated random processes and some associated regressions when the errors are tempered linear processes. Tempered processes are stationary time series that have a semi-long memory property in the sense that the autocovariogram of the process resembles that of a long memory model for moderate lags but eventually diminishes exponentially fast according to the presence of a decay factor governed by a tempering parameter. When the tempering parameter is sample size dependent, the resulting class of processes admits a wide range of behavior that includes both long memory, semi-long memory, and short memory processes. The paper develops asymptotic theory for such processes and associated regression statistics thereby extending earlier ?ndings that fall within certain subclasses of processes involving near-integrated time series. The limit results relate to tempered fractional processes that include tempered fractional Brownian motion and tempered fractional di?usions. The theory is extended to provide the limiting distribution for autoregressions with such tempered near-integrated time series, thereby enabling analysis of the limit properties of statistics of particular interest in econometrics, such as unit root tests, under more general conditions than existing theory. Some extensions of the theory to the multivariate case are reported.
    Keywords: Asymptotics, Fractional Brownian motion, Long memory, Near Integration, Tempered processes
    JEL: C22 C23
    Date: 2018–05
    URL: http://d.repec.org/n?u=RePEc:cwl:cwldpp:2131&r=ets
  2. By: Schweikert, Karsten
    Abstract: In this paper, we develop new threshold cointegration tests with SETAR and MTAR adjustment allowing for the presence of structural breaks in the equilibrium equation. We propose a simple procedure to simultaneously estimate the previously unknown breakpoint and test the null hypothesis of no cointegration. Thereby, we extend the well-known residual-based cointegration test with regime shift introduced by Gregory and Hansen (1996a) to include forms of nonlinear adjustment. We derive the asymptotic distribution of the test statistics and demonstrate the finite-sample performance of the tests in a series of Monte Carlo experiments. We find a substantial decrease of power of the conventional threshold cointegration tests caused by a shift in the slope coefficient of the equilibrium equation. The proposed tests perform superior in these situations. An application to the 'rockets and feathers' hypothesis of price adjustment in the US gasoline market provides empirical support for this methodology.
    Keywords: cointegration,threshold autoregression,structural breaks,SETAR,MTAR,asymmetric price transmission
    JEL: C12 C32 C34 Q41
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:zbw:hohdps:072018&r=ets
  3. By: Gabriele Fiorentini (Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze); Enrique Sentana (CEMFI, Madrid)
    Abstract: We propose generalised DWH specification tests which simultaneously compare three or more likelihood-based estimators of conditional mean and variance parameters in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for GARCH models and in many empirically relevant macro and finance applications involving Vars and multivariate regressions. To design powerful and reliable tests, we determine the rank deficiencies of the differences between the estimators' asymptotic covariance matrices under the null of correct specification, and take into account that some parameters remain consistently estimated under the alternative of distributional misspecification. Finally, we provide finite sample results through Monte Carlo simulations.
    Keywords: Durbin-Wu-Hausman Tests, Partial Adaptivity, Semiparametric Estimators, Singular Covariance Matrices.
    JEL: C12 C14 C22 C32 C52
    Date: 2018–05
    URL: http://d.repec.org/n?u=RePEc:fir:econom:wp2018_05&r=ets
  4. By: Cassim, Lucius
    Abstract: The main objective of this paper is to provide an estimation approach for non-parametric GARCH (2, 2) volatility model. Specifically the paper, by combining the aspects of multivariate adaptive regression splines(MARS) model estimation algorithm proposed by Chung (2012) and an algorithm proposed by Buhlman and McNeil(200), develops an algorithm for non-parametrically estimating GARCH (2,2) volatility model. Just like the MARS algorithm, the algorithm that is developed in this paper takes a logarithmic transformation as a preliminary analysis to examine a nonparametric volatility model. The algorithm however differs from the MARS algorithm by assuming that the innovations are i.d.d. The algorithm developed follows similar steps to that of Buhlman and McNeil (200) but starts by semi parametric estimation of the GARCH model and not parametric while relaxing the dependency assumption of the innovations to avoid exposing the estimation procedure to risk of inconsistency in the event of misspecification errors.
    Keywords: GARCH (2,2), MARS, Algorithm, Parametric, Semi parametric, Nonparametric
    JEL: C1 C14 C4
    Date: 2018–05–18
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:86861&r=ets
  5. By: Audrone Virbickaite (Universitat de les Illes Balears); Hedibert F. Lopes (Insper Institute of Education and Research); Maria Concepción Ausín (Universidad Carlos III de Madrid); Pedro Galeano (Universidad Carlos III de Madrid)
    Abstract: This paper designs a Sequential Monte Carlo (SMC) algorithm for estimation of Bayesian semi-parametric Stochastic Volatility model for financial data. In particular, it makes use of one of the most recent particle filters called Particle Learning (PL). SMC methods are especially well suited for state-space models and can be seen as a cost-efficient alternative to MCMC, since they allow for online type inference. The posterior distributions are updated as new data is observed, which is prohibitively costly using MCMC. Also, PL allows for consistent online model comparison using sequential predictive log Bayes factors. A simulated data is used in order to compare the posterior outputs for the PL and MCMC schemes, which are shown to be almost identical. Finally, a short real data application is included.
    Keywords: Bayes factor; Dirichlet Process Mixture; MCMC; Sequential Monte Carlo.
    JEL: C58 C11 C14
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:ubi:deawps:88&r=ets
  6. By: Baumeister, Christiane; Hamilton, James
    Abstract: Reporting point estimates and error bands for structural vector autoregressions that are only set identified is a very common practice. However, unless the researcher is persuaded on the basis of prior information that some parameter values are more plausible than others, this common practice has no formal justification. When the role and reliability of prior information is defended, Bayesian posterior probabilities can be used to form an inference that incorporates doubts about the identifying assumptions. We illustrate how prior information can be used about both structural coefficients and the impacts of shocks, and propose a new distribution, which we call the asymmetric t distribution, for incorporating prior beliefs about the signs of equilibrium impacts in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks were not the major driver of output, inflation, or interest rates during the Great Moderation.
    Keywords: historical decompositions; impulse-response functions; informative priors; Model uncertainty; monetary policy; set identification; structural vector autoregressions
    JEL: C11 C32 E52
    Date: 2018–05
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:12911&r=ets
  7. By: Susana Martins (University of Minho and NIPE); Cristina Amado (University of Minho and NIPE, CREATES and Aarhus University)
    Abstract: In this paper, we investigate the timing and extent of sovereign debt contagion across nine Eurozone countries using daily returns on 10-year government bonds from 2007 until 2017. The novelty lies in modelling bond return correlations using a multivariate GARCH model with a multiplicative decomposition of the variance and time-varying conditional correlations. The model introduces flexibility by allowing the individual unconditional variances to be time-dependent and the correlations to change smoothly between two extreme states according to time and observable financial variables. The main results provide no evidence of asymmetric response of comovements to negative shocks, as opposed to the size of innovations from the periphery which is expected to affect the dynamics of correlations. Our findings further indicate the presence of long-run contagion effects across peripheral countries following the more acute phase of the sovereign crisis. Interestingly, periods of high turbulence in the European stock market do not seem to drive financial contagion.
    Keywords: Financial contagion; European sovereign debt crisis; Multivariate GARCH model; Dynamic correlations; Multiplicative decomposition of volatility
    JEL: C32 C58 G01 G15
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:nip:nipewp:08/2018&r=ets
  8. By: KIM, Jae-Young; PARK, Woong Yong
    Abstract: The Fisher relation, describing a one-for-one relation between the nominal interest rate and the expected inflation, underlies many important results in economics and finance. Although it is a conceptually simple relation, the Fisher relation has more or less complicated with mixed results. There are several alternative models proposed in the empirical literature for the Fisher relation that have different implications. We evaluate those alternative models for the Fisher relation based on a post-data model determination method. Our results for data from the U.S. Japan and Korea show that models with both regimes/periods, a regime with nonstationary fluctuations and the other with stationary fluctuations, fit data best for the Fisher relation.
    Keywords: Fisher relation, nonlinear behavior, post-data model determination
    JEL: C1 C22 C5
    Date: 2018–04
    URL: http://d.repec.org/n?u=RePEc:hit:hiasdp:hias-e-68&r=ets
  9. By: Andrew Phiri (Department of Economics, Nelson Mandela University)
    Abstract: Whilst the issue of whether or not per capita GDP adheres to the convergence theory continues to draw increasing attention within the academic paradigm, with very little consensus having been reached in the literature thus far. Our study contributes to the literature by examining the stationarity of per capita GDP for BRICS countries using annual data collected between 1971 and 2015. Considering that our sample covers a period underlying a number of crisis and structural breaks within and amongst the BRICS countries, we rely on a robust nonlinear unit root testing procedure which captures a series of unobserved structural breaks. Our results confirm on Brazil and China being the only two BRICS economies who present the most convincing evidence of per capita GDP converging back to it’s natural equilibrium after an economic shock, whilst Russia and South Africa provide less convincing evidence of convergence dynamics in the time series and India having the weakest convergence properties.
    Keywords: Per capita GDP, Convergence, unit root tests, nonlinearities, structural breaks, BRICS Emerging economies
    JEL: C12 C13 C21 C22 C51 C52 O47
    Date: 2018–05
    URL: http://d.repec.org/n?u=RePEc:mnd:wpaper:1822&r=ets
  10. By: Benjamin K Johannsen; Elmar Mertens
    Abstract: Modeling nominal interest rates requires their effective lower bound (ELB) to be taken into account. We propose a flexible time series approach that includes a "shadow rate" - a notional rate identical to the actual nominal rate except when the ELB binds. We apply this approach to a trend-cycle decomposition of interest rates and macroeconomic variables that generates competitive interest-rate forecasts. Our estimates of the real-rate trend have edged down somewhat in recent decades, but not significantly so. We identify monetary policy shocks from shadow-rate surprises and find that they were particularly effective at stimulating economic activity during the ELB period.
    Keywords: shadow rate, effective lower bound, trend real rate, monetary policy shocks, bayesian time series
    JEL: C32 C34 C53 E43 E47
    Date: 2018–04
    URL: http://d.repec.org/n?u=RePEc:bis:biswps:715&r=ets

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