Finite Critical Values Research Articles

A New Change-Point Rank Tests

A new rank-based test statistics are proposed for the problem of a possible change in the distribution of independent observations. We extend the two-sample test statistic of Damico (2004) to the change point setup. The finite sample critical values of the proposed tests is estimated. We also conduct a Monte Carlo simulation to compare the powers of the new tests with their competitors. Using the Nile data of Cobb (1978), we demonstrate the applicability of the new tests.

Bank–Laine functions, the Liouville transformation and the Eremenko–Lyubich class

The Bank–Laine conjecture concerning the oscillation of solutions of second order homogeneous linear differential equations has recently been disproved by Bergweiler and Eremenko. It is shown here, however, that the conjecture is true if the set of finite critical and asymptotic values of the coefficient function is bounded. It is also shown that if E is a Bank–Laine function of finite order with infinitely many zeros, all real and positive, then its zeros must have exponent of convergence at least 3/2, and an example is constructed via quasiconformal surgery to demonstrate that this result is sharp.

Inference and Specification Testing in Threshold Regression with Endogeneity

We propose three new methods of inference for the threshold point in endogenous threshold regression and two specification tests designed to assess the presence of endogeneity and threshold effects without necessarily relying on instrumentation of the covariates. The first inferential method is a parametric two-stage least squares method and is suitable when instruments are available. The second and third methods are based on smoothing the objective function of the integrated difference kernel estimator in different ways and these methods do not require instrumentation. All three methods are applicable irrespective of endogeneity of the threshold variable. The two specification tests are constructed using a score-type principle. The threshold effect test extends conventional parametric structural change tests to the nonparametric case. A wild bootstrap procedure is suggested to deliver finite sample critical values for both tests. Simulations show good finite sample performance of these procedures and the methods provide flexibility in testing and inference for practitioners working with threshold models.

A (negative) replication of ‘The relationship between energy consumption, energy prices, and economic growth: Time series evidence from Asian developing countries’ (Energy Economics, 2000)

This paper replicates Asafu-Adjaye (2000) which employs unit root and cointegration tests together with error correction models to investigate the relationships between energy consumption and income for four energy-dependent Asian developing countries using data from 1971 through 1995. This paper finds not only that the results cannot be replicated, but that the results are not robust to alternative estimation procedures that include the simulation of finite sample critical values and the extension to panel unit root, stationarity and cointegration tests which are necessary to improve upon the power properties of the short time series employed by Asafu-Adjaye (2000). The results from the extension of the analysis to more modern time series techniques disprove the original paper's results, with panel cointegration tests finding that the trivariate system (income, energy consumption, and prices) does not follow a long run relationship for India, Indonesia, Thailand, and the Philippines.

How Many Zolotarëv Fractions are There?

Known properties of Chebyshev polynomials are the following: they have simple critical points with only two (finite) critical values. Those properties uniquely determine the named polynomials modulo affine transformations of dependent and independent variables. A similar property of Zolotarev fractions: simple critical points and only four critical values generates already many classes of rational functions modulo projective transformations of their dependent and independent variables. They are listed in this note.

Rtadf: Testing for Bubbles with EViews

This paper presents Rtadf (right-tail augmented Dickey-Fuller), an EViews add-in that facilitates the performance of time series based tests that help detect and date-stamp asset price bubbles. The detection strategy is based on a right-tail variation of the standard augmented Dickey-Fuller (ADF) test where the alternative hypothesis is of a mildly explosive process. Rejection of the null in each of these tests may serve as empirical evidence for an asset price bubble. The add-in implements four types of tests: standard ADF, rolling window ADF, supremum ADF (SADF; Phillips, Wu, and Yu 2011) and generalized SADF (GSADF; Phillips, Shi, and Yu 2015). It calculates the test statistics for each of the above four tests, simulates the corresponding exact finite sample critical values and p values via Monte Carlo methods, under the assumption of Gaussian innovations, and produces a graphical display of the date stamping procedure.

Herman’s Condition and Siegel Disks of Bi-Critical Polynomials

We extend a theorem of Herman from the case of unicritical polynomials to the case of polynomials with two finite critical values. This theorem states that Siegel disks of such polynomials, under a diophantine condition (called Herman's condition) on the rotation number, must have a critical point on their boundaries.

Threshold Regression with Endogeneity

This paper studies estimation and specification testing in threshold regression with endogeneity. Three key results differ from those in regular models. First, both the threshold point and the threshold effect parameters are shown to be identified without the need for instrumentation. Second, in partially linear threshold models, both parametric and nonparametric components rely on the same data, which prima facie suggests identification failure. But, as shown here, the discontinuity structure of the threshold itself supplies identifying information for the parametric coefficients without the need for extra randomness in the regressors. Third, instrumentation plays different roles in the estimation of the system parameters, delivering identification for the structural coefficients in the usual way, but raising convergence rates for the threshold effect parameters and improving efficiency for the threshold point. Specification tests are developed to test for the presence of endogeneity and threshold effects without relying on instrumentation of the covariates. The threshold effect test extends conventional parametric structural change tests to the nonparametric case. A wild bootstrap procedure is suggested to deliver finite sample critical values for both tests. Simulation studies corroborate the theory and the asymptotics. An empirical application is conducted to explore the effects of 401(k) retirement programs on savings, illustrating the relevance of threshold models in treatment effects evaluation in the presence of endogeneity.

LM tests of spatial dependence based on bootstrap critical values

To test the existence of spatial dependence in an econometric model, a convenient test is the Lagrange Multiplier (LM) test. However, evidence shows that, in finite samples, the LM test referring to asymptotic critical values may suffer from the problems of size distortion and low power, which become worse with a denser spatial weight matrix. In this paper, residual-based bootstrap methods are introduced for asymptotically refined approximations to the finite sample critical values of the LM statistics. Conditions for their validity are clearly laid out and formal justifications are given in general, and in detail under several popular spatial LM tests using Edgeworth expansions. Monte Carlo results show that when the conditions are not fully met, bootstrap may lead to unstable critical values that change significantly with the alternative, whereas when all conditions are met, bootstrap critical values are very stable, approximate much better the finite sample critical values than those based on asymptotics, and lead to significantly improved size and power. The methods are further demonstrated using more general spatial LM tests, in connection with local misspecification and unknown heteroskedasticity.

Large N phase transitions in supersymmetric Chern-Simons theory with massive matter

We study three-dimensional {\cal N}=2 U(N) Chern-Simons theory on S^3 coupled to 2N_f chiral multiplets deformed by mass terms. The partition function localizes to a matrix integral, which can be exactly computed in the large N limit. In a specific decompactification limit, the theory exhibits quantum (third-order) phase transitions at finite critical values of the coupling. The theory presents three phases when 0 < N_f < N and two phases when N_f\geq N. The vacuum expectation value of the supersymmetric circular Wilson loop has a discontinuity in the first derivative.

Unit root testing with stationary covariates and a structural break in the trend function

The issue of testing for a unit root allowing for a structural break in the trend function is considered. The focus is on the construction of more powerful tests using the information in relevant multi‐variate data sets. The proposed test adopts the generalized least squares detrending approach and uses correlated stationary covariates to improve power. As it is standard in the literature, the break date is treated as unknown. Asymptotic distributions are derived, and a set of asymptotic and finite sample critical values are tabulated. Asymptotic local power functions show that power gains can be large. Finite sample results show that the test exhibits small‐size distortions and power that can be far beyond what is achievable by univariate tests.

Long-term asset tail risks in developed and emerging markets

A power law typically governs the tail decay of financial returns but the constancy of the so-called tail index which dictates the tail decay remains relatively unexplored. We study the finite sample properties of some recently proposed endogenous tests for structural change in the tail index. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans developed and emerging financial asset returns. Somewhat surprisingly, emerging stock market tails are not more inclined to structural change than their developed counterparts. Emerging currency tails, on the contrary, do exhibit structural shifts in contrast to developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds.

Recursive adjustment, unit root tests and structural breaks

In this paper, we introduce unit root tests for time series with a potential structural break computed from test regressions in which the deterministic components have been recursively adjusted. We present finite sample critical values as well as Monte Carlo results on the size and power performance of the new procedures, and compare these with other available tests in the literature, such as OLS and quasi‐differenced based tests (see, for instance, Perron, (1997)Perron and Rodriguez, (2003) and Carrion‐i‐Silvestre et al. (2009)). The small sample behaviour of the tests is evaluated in a known and an unknown break date context allowing for negligible and non‐negligible initial conditions. In the unknown break date case, two break date estimation procedures are considered, one based on the minimum unit root t‐statistic and the other based on the minimum sum of squared residuals obtained from a regression on a set of deterministic variables. The size and power performance of the recursive adjustment based procedure in the unknown break date case is encouraging. A further result of this paper relates to the aditional finite sample evidence on the performance of quasi‐differenced unit root tests, complementing the results in Perron and Rodriguez (2003).

On the Hausdorff dimension of the escaping set of certain meromorphic functions

The escaping set I(f) of a transcendental meromorphic function f consists of all points which tend to infinity under iteration. The Eremenko-Lyubich class B consists of all transcendental meromorphic functions for which the set of finite critical and asymptotic values of f is bounded. It is shown that if f is in B and of finite order of growth, if infinity is not an asymptotic value of f and if the multiplicities of the poles of f are uniformly bounded, then the Hausdorff dimension of I(f) is strictly smaller than 2. In fact, we give a sharp bound for the Hausdorff dimension of I(f) in terms of the order of f and the bound for the multiplicities of the poles. If f satisfies the above hypotheses but is of infinite order, then the area of I(f) is zero. This result does not hold without a restriction on the multiplicities of the poles.

Long-Term Asset Tail Risk in Developed and Emerging Markets

The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for structural change in α. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans a wide variety of long-term developed and emerging financial asset returns. Somewhat surprisingly, the tail behavior of emerging stock markets is not more strongly inclined to structural change than their developed counterparts. Emerging currencies, on the contrary, are more prone to shifts in the tail behavior than developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks or in assessing the (changing) propensity to financial crises can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds. However, our break results also indicate it is advisable to use shorter estimation windows when applying EVT methods to emerging currency portfolios.

On the asymptotic distribution of a simple unit root test for trending and breaking series

In this paper, we derive the asymptotic distribution of Popp's (2008) innovational outlier unit root test for trending series with a break. The results of Zivot and Andrews (1992) are applied to provide the limiting results of these new test statistics. We tabulate their asymptotic and finite sample critical values, and illustrate the use of the new statistics with an application to the unemployment rate series for 23 OECD countries.

Lag Length Selection in DF-GLS Unit Root Tests

We reinvestigate the empirical problem of lag length selection in unit root tests when using the augmented Dickey–Fuller test based on GLS-detrending. We extend the Ng and Perron (1995) work on this issue by applying the finite sample critical values calculated using the formulae proposed by Cheung and Lai (1995). Unlike Ng and Perron (2001) we find through simulation studies that the method of selecting lag length using the sequential t-test in the ADF regression of GLS-detrended series performs the best in most cases.

A bivariate fractionally cointegrated relationship in the context of cyclical structures

This paper deals with the analysis of cointegration in a bivariate system. However, we depart from the classic concept of cointegration in two aspects. First, we permit fractional degrees of integration in both the parent series and in their linear combination. Second, instead of assuming that the pole or singularity in the spectrum takes places at the zero frequency, we consider the case where the singularity occurs at a frequency λ in the interval (0, π]. We use a procedure that follows the same lines as the two-step testing strategy of R.F. Engle, and C.W.J. Granger, [Cointegration and error correction model. Representation, estimation and testing, Econometrica 55 (1987), pp. 251–276]. Thus, we test first the order of integration in the individual series, which are specified in terms of the Gegenbauer polynomials. Then, if the two series share the same degree of integration at a given frequency, we test the null hypothesis of no cointegration against the alternative of fractional cyclical cointegration, by testing the order of integration on the estimated residuals from the cointegrating regression. Finite sample critical values are obtained, and the power properties of the test are examined. An empirical application is also carried out at the end of the article.

Critical values for the augmented efficient Wald test for fractional unit roots

This paper presents response surface estimates of finite sample critical values of the Efficient Wald test for Fractional Unit Roots of Lobato and Velasco (Econometrica 75:575–590, 2007) in the presence of deterministic components. Lag-adjusted critical values of the augmented versions of the tests illustrate that as in the context of traditional unit root and stationarity tests, incorporating adjustments for serial correlation affects the finite sample distributions of the test statistics.

Extended complex error correction models for seasonal cointegration

In this paper, we extend the complex error correction model (ECM) of [Cubadda, G. (2001). Complex reduced rank models for seasonally cointegrated time series. Oxford Bulletin of Economics and Statistics, 63, 497–511] to models with two types of deterministic terms: (i) restricted seasonal dummies and constant; (ii) restricted seasonal dummies and unrestricted constant. These types of deterministic terms are most frequently adopted in the analysis of seasonal cointegration by many practitioners and researchers, because the other type–where all seasonal dummies and constant terms are unrestricted–may yield oscillating trends. We obtain the limiting distribution of the likelihood ratio (LR) test for the seasonal cointegrating (CI) rank in the extended models. We also provide asymptotic and finite critical values for the test.