22 results for Phillips, Peter

Infrastructure Investment: Supporting Better Decisions Report
Phillips, Peter; Ellis, Murray; Boshier, John (2010)
Authored Books
University of Canterbury LibraryThe research detailed in this publication has developed an agenda for reform that is designed to enhance decisionmaking on infrastructure investments. It is apparent from the collective wisdom of the interviews with leading decisionmakers, a survey of infrastructure businesses, the case studies, literature analysis and experience of the study team members that the quality of decisionmaking practice on infrastructure investments is quite varied. This study has identified remedies in approach and method, in use both here and overseas, which can address these deficiencies, at least in part. Some aspects of the required reforms can be implemented simply through information and training. Others require some investigation and demonstration. None the methods are so technically demanding to be ultimately beyond competent analysts (although some are currently operating at a modest level). All require the adoption of rigorous and more standardised process by decisionmakers and analysts alike.
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Infrastructure Investment: Supporting Better Decisions Summary
Phillips, Peter; Ellis, Murray; Boshier, John (2010)
Discussion / Working Papers
University of Canterbury LibrarySummary of Report: The research detailed in this publication has developed an agenda for reform that is designed to enhance decisionmaking on infrastructure investments. It is apparent from the collective wisdom of the interviews with leading decisionmakers, a survey of infrastructure businesses, the case studies, literature analysis and experience of the study team members that the quality of decisionmaking practice on infrastructure investments is quite varied. This study has identified remedies in approach and method, in use both here and overseas, which can address these deficiencies, at least in part. Some aspects of the required reforms can be implemented simply through information and training. Others require some investigation and demonstration. None the methods are so technically demanding to be ultimately beyond competent analysts (although some are currently operating at a modest level). All require the adoption of rigorous and more standardised process by decisionmakers and analysts alike.
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Discrete Fourier Transforms of Fractional Processes August
Phillips, Peter (1999)
Working or discussion paper
The University of Auckland LibraryDiscrete Fourier transforms (dft's) of fractional processes are studied and a exact representation of the dft is given in terms of the component data. The new representation gives the frequency domain form of the model for a fractional process, and is particularly useful in analyzing the asymptotic behavior of the dft and periodogram in the nonstationary case when the memory parameter d > 1/2. Various asymptotic approximations are suggested. It is shown that smoothed periodogram spectral estimates remain consistent for frequencies away from the origin in the nonstationary case provided the memory parameter d < 1. When d = 1, the spectral estimates are inconsistent and converge weakly to random variates. Applications of the theory to log periodogram regression and local Whittle estimation of the memory parameter are discussed and some modified versions of these procedures are suggested.
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The Elusive Empirical Shadow of Growth Convergence
Phillips, Peter; Sul, Donggyu (2003)
Working or discussion paper
The University of Auckland LibraryTwo groups of applied econometricians have figured prominently in empirical studies of growth convergence. In terms of a popular caricature, one group believes it has found a black hat of convergence (evidence for growth convergence) in the dark room of economic growth, even though the hat may not exist (the task may be futile). A second group believes it has found a black coat of divergence (evidence against growth convergence) even though this object also may not exist (empirical reality, including the nature of growth divergence, is ever more complex than the models used to characterize it). The present paper seeks to light a candle to see whether there is a hat, a coat or another object of identifiable clothing in the room of regional and multicountry economic growth. After our examination, we find that the candle power of applied econometrics is too low to clearly distinguish a black hat in the huge dark room of economic growth. However, in our theory model, we find an important new role for heterogeneity over time and across economies in the transitional dynamics of economic growth; and, in our empirical work, these transitional dynamics reveal an elusive shadow of the conditional convergence hat in both US regional and intercountry OECD growth patterns.
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Prewhitening Bias in HAC Estimation
Sul, Donggyu; Phillips, Peter; Choi, ChiYoung (2003)
Working or discussion paper
The University of Auckland LibraryLater version now published as a Journal Article: Oxford Bulletin of Economics & Statistics 67 (4), 517546. doi: 10.1111/j.14680084.2005.00130.x HAC estimation commonly involves the use of prewhitening filters based on simple autoregressive models. In such applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recoloring filter, leading to HAC variance estimates that can be badly biased. The present paper provides an analysis of these issues using asymptotic expansions and simulations. The approach we recommend involves the use of recursive demeaning procedures that mitigate the effects of small sample autoregressive bias. Moreover, a commonlyused restriction rule on the prewhitening estimates (that first order autoregressive coefficient estimates, or largest eigenvalues, greater than 0.97 be replaced by 0.97) adversely interferes with the power of unit root and KPSS tests. We provide a new boundary condition rule that improves the size and power properties of these tests. Some illustrations are given of the effects of these adjustments on the size and power of KPSS testing. Using prewhitened HAC estimates and the new boundary condition rule, the KPSS test is consistent, in contrast to KPSS testing that uses conventional prewhitened HAC estimates (Lee, 1996).
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Jacknifing Bond Option Prices
Yu, Jun; Phillips, Peter (2002)
Working or discussion paper
The University of Auckland LibraryIn continuous time specifications, the prices of interest rate derivative securities depend crucially on the mean reversion parameter of the associated interest rate diffusion equation. This parameter is well known to be subject to estimation bias when standard methods like maximum likelihood (ML) are used. The estimation bias can be substantial even in very large samples and it translates into a bias in pricing bond options and other derivative securities that is important in practical work. The present paper proposes a very general method of bias reduction for pricing bond options that is based on Quenouille's (1956) jackknife. We show how the method can be applied directly to the options price itself as well as the coefficients in continuous time models. The method is implemented and evaluated here in the Cox, Ingersoll and Ross (1985) model, although it has much wider applicability. A Monte Carlo study shows that the proposed procedure achieves substantial bias reductions in pricing bond options with only mild increases in variance that do not compromise the overall gains in mean squared error. Our findings indicate that bias correction in estimation of the drift can be more important in pricing bond options than correct specification of the diffusion. Thus, even if ML or approximate ML can be used to estimate more complicated models, it still appears to be of equal or greater importance to correct for the effects on pricing bond options of bias in the estimation of the drift. An empirical application to U.S. interest rates highlights the differences between bond and option prices implied by the jackknife procedure and those implied by the standard approach. These differences are large and suggest that bias reduction in pricing options is important in practical applications.
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Dynamic Panel Estimation and Homogenity Testing Under Cross Section Dependence
Phillips, Peter; Sul, Donggyu (2002)
Working or discussion paper
The University of Auckland LibraryNow published as a Journal Article in The Econometrics Journal Volume 6 Issue 1 Page 217  June 2003 doi:10.1111/1368423X.00108 This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a panel approach to median unbiased estimation that takes account of cross section dependence. The new estimators given here considerably reduce the effects of bias and gain precision from estimating cross section error correlation. The paper also develops an asymptotic theory for tests of coefficient homogeneity under cross section dependence, and proposes a modified Hausman test to test for the presence of homogeneous unit roots. An orthogonalization procedure is developed to remove cross section dependence and permit the use of conventional and meta unit root tests with panel data. Some simulations investigating the finite sample performance of the estimation and test procedures are reported.
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Forecasting New Zealand's Real GDP
Schiff, Aaron; Phillips, Peter (2000)
Working or discussion paper
The University of Auckland LibraryRecent time series methods are applied to the problem of forecasting New Zealand_s real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz (1978) BIC and the PhillipsPloberger (1996) PIC criteria. The forecasts generated by the data determined AR models and an international VAR model are found to be competitive with forecasts from fixed format models and forecasts produced by the NZIER. Two illustrations of the methodology in conditional forecasting settings are performed with the VAR models. The first provides conditional predictions of New Zealand_s real GDP when there is a future recession in the United States. The second gives conditional predictions of New Zealand_s real GDP under a variety of profiles that allow for tightening in monetary conditions by the Reserve Bank.
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New Unit Root Asymptotics in the Presence of Deterministic Trends
Phillips, Peter (1998)
Working or discussion paper
The University of Auckland LibraryRecent work by the author (1998) has shown that stochastic trends can be validly represented in empirical regressions in terms of deterministic functions of time. These representations offer an alternative mechanism for modelling stochastic trends. It is shown here that the alternate representations affect the asymptotics of all commonly used unit root tests in the presence of trends. In particular, the critical values of unit root tests diverge when the number of deterministic regressors K + rn as the sample size n + w. In such circumstances, use of conventional critical values based on fixed K will lead to rejection of the null of a unit root in favour of trend stationarity with probability one when the null is true. The results can be interpreted as saying that serious attempts to model trends by deterministic functions will always be successful and that these functions can validly represent stochastically trending data even when lagged variables are present in the regressor set, thereby undermining conventional unit root tests.
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Exact Gaussian Estimation of Continuous Time Models of The Term Structure of Interest Rates Rankings of Economics Departments in New Zealand
Phillips, Peter; Yu, Jun (2000)
Working or discussion paper
The University of Auckland LibraryThis paper proposes an exact Gaussian estimator for nonlinear continuous time models of the term structure of interest rates. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite sample performance of the proposed procedure offers an improvement over the discrete approximation method proposed by Nowman (1997). An empirical application to U.S. and British interest rates is given.
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Bias in Dynamic Panel Estimation with Fixed Effects, Incidental Trends and Cross Section Dependence
Phillips, Peter; Sul, Donggyu (2003)
Working or discussion paper
The University of Auckland LibraryExplicit asymptotic bias formulae are given for dynamic panel regression estimators as the cross section sample size N 8. The results extend earlier work by Nickell (1981) in several directions that are relevant for practical work, including models with unit roots, deterministic trends, predetermined and exogenous regressors, and errors that may be cross sectionally dependent. The asymptotic bias is found to be so large when incidental linear trends are fitted and the time series sample size is small that it changes the sign of the autoregressive coefficient. Another finding of interest is that, when there is cross section error dependence, the probability limit of the dynamic panel regression estimator is a random variable rather than a constant, which helps to explain the substantial variability observed in dynamic panel estimates when there is cross section dependence even in situations where N is very large.
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Inference in NearSingular Regression
Phillips, Peter (2016)
Conference item
The University of Auckland LibraryThis paper considers stationary regression models with nearcollinear regressors. Limit theory is developed for regression estimates and test statistics in cases where the signal matrix is nearly singular in finite samples and is asymptotically degenerate. Examples include models that involve evaporating trends in the regressors that arise in conditions such as growth convergence. Structural equation models are also considered and limit theory is derived for the corresponding instrumental variable (IV) estimator, Wald test statistic, and overidentification test when the regressors are endogenous. It is shown that nearsingular designs of the type considered here are not completely fatal to least squares inference, but do inevitably involve size distortion except in special Gaussian cases. In the endogenous case, IV estimation is inconsistent and both the block Wald test and Sargan overidentification test are conservative, biasing these tests in favor of the null.
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Estimating smooth structural change in cointegration models
Phillips, Peter; Li, D; Gao, J (201701)
Journal article
The University of Auckland LibraryThis paper studies nonlinear cointegration models in which the structural coefficients may evolve smoothly over time, and considers timevarying coefficient functions estimated by nonparametric kernel methods. It is shown that the usual asymptotic methods of kernel estimation completely break down in this setting when the functional coefficients are multivariate. The reason for this breakdown is a kernelinduced degeneracy in the weighted signal matrix associated with the nonstationary regressors, a new phenomenon in the kernel regression literature. Some new techniques are developed to address the degeneracy and resolve the asymptotics, using a pathdependent local coordinate transformation to reorient coordinates and accommodate the degeneracy. The resulting asymptotic theory is fundamentally different from the existing kernel literature, giving two different limit distributions with different convergence rates in the different directions of the (functional) parameter space. Both rates are faster than the usual rootnh rate for nonlinear models with smoothly changing coefficients and local stationarity. In addition, local linear methods are used to reduce asymptotic bias and a fully modified kernel regression method is proposed to deal with the general endogenous nonstationary regressor case, which facilitates inference on the time varying functions. The finite sample properties of the methods and limit theory are explored in simulations. A brief empirical application to macroeconomic data shows that a linear cointegrating regression is rejected but finds support for alternative polynomial approximations for the timevarying coefficients in the regression.
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Identifying Latent Structures in Panel Data
Su, L; Shi, Z; Phillips, Peter (201611)
Journal article
The University of Auckland LibraryThis paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered???penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier???Lasso (C???Lasso) that serves to shrink individual coefficients to the unknown group???specific coefficients. C???Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C???Lasso also achieves the oracle property so that group???specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C???Lasso is preserved in some special cases. Simulations demonstrate good finite???sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.
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Hot Property in New Zealand: Empirical Evidence of Housing Bubbles in the Metropolitan Centres
GreenawayMcGrevy, Ryan; Phillips, Peter (20150420)
Report
The University of Auckland LibraryUsing recently developed statistical methods for testing and dating exhuberant behavior in asset prices we document evidence of episodic bubbles in the New Zealand property market over the past two decades. The results show clear evidence of a broadbased New Zealand housing bubble that began in 2003 and collapsed over mid 2007 to early 2008 with the onset of the worldwide recession and the ??nancial crisis. New methods of analyzing market contagion are also developed and are used to examine spillovers from the Auckland property market to the other metropolitan centres. Evidence from the latest data reveals that the greater Auckland metropolitan area is currently experiencing a new property bubble that began in 2013. But there is no evidence yet of any contagion e??ect of this bubble on the other centres, in contrast to the earlier bubble over 20032008 for which there is evidence of transmission of the housing bubble from Auckland to the other centres. One of our primary conclusions is that the expensive nature of New Zealand real estate relative to potential earnings in rents is partly due to the sustained market exuberance that produced the broad based bubble in house prices during the last decade and that has continued through the most recent bubble experienced in the Auckland region since 2013.
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A multivariate stochastic unit root model with an application to derivative pricing
Lieberman, O; Phillips, Peter (201701)
Journal article
The University of Auckland LibraryThis paper extends recent findings of Lieberman and Phillips (2014) on stochastic unit root (STUR) models to a multivariate case including asymptotic theory for estimation of the model???s parameters. The extensions are useful for applications of STUR modeling and because they lead to a generalization of the Black???Scholes formula for derivative pricing. In place of the standard assumption that the price process follows a geometric Brownian motion, we derive a new form of the Black???Scholes equation that allows for a multivariate time varying coefficient element in the price equation. The corresponding formula for the value of a Europeantype call option is obtained and shown to extend the existing option price formula in a manner that embodies the effect of a stochastic departure from a unit root. An empirical application reveals that the new model substantially reduces the average percentage pricing error of the Black???Scholes and Heston???s (1993) stochastic volatility (with zero volatility risk premium) pricing schemes in most moneynessmaturity categories considered.
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Hot property in New Zealand: Empirical evidence of housing bubbles in the metropolitan centres
GreenawayMcGrevy, Ryan; Phillips, Peter (2016)
Journal article
The University of Auckland LibraryUsing recently developed statistical methods for testing and dating exuberant behaviour in asset prices we document evidence of episodic bubbles in the New Zealand property market over the past two decades. The results show clear evidence of a broadbased New Zealand housing bubble that began in 2003 and collapsed over mid2007 to early 2008 with the onset of the worldwide recession and the financial crisis. New methods of analysing market contagion are also developed and are used to examine spillovers from the Auckland property market to the other metropolitan centres. Evidence from the latest data reveals that the greater Auckland metropolitan area is currently experiencing a new property bubble that began in 2013. But there is no evidence yet of any contagion effect of this bubble on the other centres, in contrast to the earlier bubble over 2003???2008 for which there is evidence of transmission of the housing bubble from Auckland to the other centres. One of our primary conclusions is that the expensive nature of New Zealand real estate relative to potential earnings in rents is partly due to the sustained market exuberance that produced the broadbased bubble in house prices during the last decade and that has continued through the most recent bubble experienced in the Auckland region since 2013.
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Limit Theory for Moderate Deviations from Unity
Phillips, Peter; Magdalinos, T (2007)
Journal article
The University of Auckland LibraryAn asymptotic theory is given for autoregressive time series with a root of the form ??n=1+c/kn, which represents moderate deviations from unity when (kn)n???N is a deterministic sequence increasing to infinity at a rate slower than n, so that kn=o(n) as n??????. For c0, the serial correlation coefficient is shown to have a convergence rate and a Cauchy limit distribution without assuming Gaussian errors, so an invariance principle applies when ??n>1. This result links moderate deviation asymptotics to earlier results on the explosive autoregression proved under Gaussian errors for kn=1, where the convergence rate of the serial correlation coefficient is (1+c)n and no invariance principle applies.
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Structural Nonparametric Cointegrating Regression
Wang, Q; Phillips, Peter (2009)
Journal article
The University of Auckland LibraryNonparametric estimation of a structural cointegrating regression model is studied. As in the standard linear cointegrating regression model, the regressor and the dependent variable are jointly dependent and contemporaneously correlated. In nonparametric estimation problems, joint dependence is known to be a major complication that affects identification, induces bias in conventional kernel estimates, and frequently leads to illposed inverse problems. In functional cointegrating regressions where the regressor is an integrated or nearintegrated time series, it is shown here that inverse and illposed inverse problems do not arise. Instead, simple nonparametric kernel estimation of a structural nonparametric cointegrating regression is consistent and the limit distribution theory is mixed normal, giving straightforward asymptotics that are useable in practical work. It is further shown that use of augmented regression, as is common in linear cointegration modeling to address endogeneity, does not lead to bias reduction in nonparametric regression, but there is an asymptotic gain in variance reduction. The results provide a convenient basis for inference in structural nonparametric regression with nonstationary time series when there is a single integrated or nearintegrated regressor. The methods may be applied to a range of empirical models where functional estimation of cointegrating relations is required.
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Dating the Timeline of Financial Bubbles during the Subprime Crisis
Phillips, Peter (201111)
Journal article
The University of Auckland LibraryA new recursive regression methodology is introduced to analyze the bubble characteristics of various financial time series during the subprime crisis. The methods modify a technique proposed in Phillips, Wu, and Yu (2011) and provide a technology for identifying bubble behavior with consistent dating of their origination and collapse. The tests serve as an early warning diagnostic of bubble activity and a new procedure is introduced for testing bubble migration across markets. Three relevant financial series are investigated, including a financial asset price (a house price index), a commodity price (the crude oil price), and one bond price (the spread between Baa and Aaa). Statistically significant bubble characteristics are found in all of these series. The empirical estimates of the origination and collapse dates suggest a migration mechanism among the financial variables. A bubble emerged in the real estate market in February 2002. After the subprime crisis erupted in 2007, the phenomenon migrated selectively into the commodity market and the bond market, creating bubbles which subsequently burst at the end of 2008, just as the effects on the real economy and economic growth became manifest. Our empirical estimates of the origination and collapse dates and tests of migration across markets match well with the general dateline of the crisis put forward in the recent study by Caballero, Farhi, and Gourinchas (2008a).
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