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Full-Text Articles in Social and Behavioral Sciences
High-Dimensional Iv Cointegration Estimation And Inference, Peter C. B. Phillips, Igor L. Kheifets
High-Dimensional Iv Cointegration Estimation And Inference, Peter C. B. Phillips, Igor L. Kheifets
Research Collection School Of Economics
A semiparametric triangular systems approach shows how multicointegrating linkages occur naturally in an I(1) cointegrated regression model when the long run error variance matrix in the system is singular. Under such singularity, cointegrated I(1) systems embody a multicointegrated structure that makes them useful in many empirical settings. Earlier work shows that such systems may be analyzed and estimated without appealing to the associated I(2) system but with suboptimal convergence rates and potential asymptotic bias. The present paper develops a robust approach to estimation and inference of such systems using high dimensional IV methods that have appealing asymptotic properties like those …
Fully Modified Least Squares Cointegrating Parameter Estimation In Multicointegrated Systems, Igor L. Kheifets, Peter C. B. Phillips
Fully Modified Least Squares Cointegrating Parameter Estimation In Multicointegrated Systems, Igor L. Kheifets, Peter C. B. Phillips
Research Collection School Of Economics
Multicointegration is traditionally defined as a particular long run relationship among variables in a parametric vector autoregressive model that introduces additional cointegrating links between these variables and partial sums of the equilibrium errors. This paper departs from the parametric model, using a semiparametric formulation that reveals the explicit role that singularity of the long run conditional covariance matrix plays in determining multicointegration. The semiparametric framework has the advantage that short run dynamics do not need to be modeled and estimation by standard techniques such as fully modified least squares (FM-OLS) on the original system is straightforward. The paper derives FM-OLS …
Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression, Degui Li, Peter C. B. Phillips, Jiti Gao
Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression, Degui Li, Peter C. B. Phillips, Jiti Gao
Research Collection School Of Economics
This paper studies nonlinear cointegrating models with time-varying coefficients and multiple nonstationary regressors using classic kernel smoothing methods to estimate the coefficient functions. Extending earlier work on nonstationary kernel regression to take account of practical features of the data, we allow the regressors to be cointegrated and to embody a mixture of stochastic and deterministic trends, complications which result in asymptotic degeneracy of the kernel-weighted signal matrix. To address these complications new local and global rotation techniques are introduced to transform the covariate space to accommodate multiple scenarios of induced degeneracy. Under regularity conditions we derive asymptotic results that differ …
Econometric Estimates Of Earth's Transient Climate Sensitivity, Peter C. B. Phillips, Thomas Leirvik, Trude Storelvmo
Econometric Estimates Of Earth's Transient Climate Sensitivity, Peter C. B. Phillips, Thomas Leirvik, Trude Storelvmo
Research Collection School Of Economics
How sensitive is Earth's climate to a given increase in atmospheric greenhouse gas (GHG) concentrations? This long-standing question in climate science was recently analyzed by dynamic panel data methods using extensive spatio-temporal data of global surface temperatures, solar radiation, and GHG concentrations over the last half century to 2010 (Storelvmo et al, 2016). Those methods revealed that atmospheric aerosol effects masked approximately one-third of the continental warming due to increasing GHG concentrations over this period, thereby implying greater climate sensitivity to GHGs than previously thought. The present study provides regularity conditions and asymptotic theory justifying the use of time series …
Estimating Smooth Structural Change In Cointegration Models, Peter C. B. Phillips, Degui Li, Jiti Gao
Estimating Smooth Structural Change In Cointegration Models, Peter C. B. Phillips, Degui Li, Jiti Gao
Research Collection School Of Economics
This paper studies nonlinear cointegration models in which the structural coefficients may evolve smoothly over time, and considers time-varying 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 kernel induced 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 path-dependent local coordinate transformation to reorient coordinates and …
Uniform Consistency Of Nonstationary Kernel-Weighted Sample Covariances For Nonparametric Regression, Degui Li, Peter C. B. Phillips, Jiti Gao
Uniform Consistency Of Nonstationary Kernel-Weighted Sample Covariances For Nonparametric Regression, Degui Li, Peter C. B. Phillips, Jiti Gao
Research Collection School Of Economics
We obtain uniform consistency results for kernel-weighted sample covariances in a nonstationary multiple regression framework that allows for both fixed design and random design coefficient variation. In the fixed design case these nonparametric sample covariances have different uniform asymptotic rates depending on direction, a result that differs fundamentally from the random design and stationary cases. The uniform asymptotic rates derived exceed the corresponding rates in the stationary case and confirm the existence of uniform super-consistency. The modelling framework and convergence rates allow for endogeneity and thus broaden the practical econometric import of these results. As a specific application, we establish …
Disentangling Greenhouse Warming And Aerosol Cooling To Reveal Earth's Climate Sensitivity, T. Storelvmo, T. Leirvik, U. Lohmann, Peter C. B. Phillips, M. Wild
Disentangling Greenhouse Warming And Aerosol Cooling To Reveal Earth's Climate Sensitivity, T. Storelvmo, T. Leirvik, U. Lohmann, Peter C. B. Phillips, M. Wild
Research Collection School Of Economics
Earth's climate sensitivity has long been subject to heated debate and has spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of its most likely range(1). Recent observational studies have produced estimates of transient climate sensitivity, that is, the global mean surface temperature increase at the time of CO2 doubling, as low as 1.3 K (refs 2,3), well below the best estimate produced by global climate models (1.8 K). Here, we present an observation-based study of the time period 1964 to 2010, which does not rely on climate models. The method incorporates observations of greenhouse gas …
Cointegration Of Matched Home Purchases And Rental Price Indexes: Evidence From Singapore, Badi H. Baltagi, Jing Li
Cointegration Of Matched Home Purchases And Rental Price Indexes: Evidence From Singapore, Badi H. Baltagi, Jing Li
Research Collection School Of Economics
This paper exploits the homogeneity feature of the Singapore private residential condominium market and constructs matched home purchase price and rental price series using the repeated sales method. These matched series allow us to conduct time series analysis to examine the long-term present value relationship in the housing market. Three key findings are obtained. First, we fail to establish a cointegrating relationship between the home purchase price and rental price based on nationally estimated indexes. Second, area-specific indexes demonstrate strong cross-correlations, invalidating the use of first generation panel unit root tests that ignore these cross-correlations. Third, Pesaran's CIPS test indicates …
Further Evidence On The Spatio-Temporal Model Of House Prices In The United States, Badi H. Baltagi, Jing Li
Further Evidence On The Spatio-Temporal Model Of House Prices In The United States, Badi H. Baltagi, Jing Li
Research Collection School Of Economics
Holly, Pesaran, and Yamagata (Journal of Econometrics 2010; 158: 160–173) use a panel of 49 states over the period 1975–2003 to show that state-level real housing prices are driven by economic fundamentals, such as real per capita disposable income, as well as by common shocks, such as changes in interest rates, oil prices and technological change. They apply the common correlated effects estimator of Pesaran (Econometrica 2006; 74(4): 967–101), which takes into account spatial interactions that reflect both geographical proximity and unobserved common factors. This paper replicates their results using a panel of 381 metropolitan statistical areas observed over the …
Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips
Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips
Research Collection School Of Economics
A local limit theorem is given for the sample mean of a zero energy function of a nonstationary time series involving twin numerical sequences that pass to infinity. The result is applicable in certain nonparametric kernel density estimation and regression problems where the relevant quantities are functions of both sample size and bandwidth. An interesting outcome of the theory in nonparametric regression is that the linear term is eliminated from the asymptotic bias. In consequence and in contrast to the stationary case, the Nadaraya-Watson estimator has the same limit distribution (to the second order including bias) as the local linear …
Limit Theory For Cointegrated Systems With Moderately Integrated And Moderately Explosive Regressors, Tassos Magdalinos, Peter C. B. Phillips
Limit Theory For Cointegrated Systems With Moderately Integrated And Moderately Explosive Regressors, Tassos Magdalinos, Peter C. B. Phillips
Research Collection School Of Economics
An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form rho(ni) = 1 + c(i)/n(alpha), involving moderate deviations from unity when alpha is an element of (0, 1) and c(i) is an element of R are constant parameters. When the data are moderately integrated in the stationary direction (with c(i) < 0), it is shown that least squares regression is consistent and asymptotically normal but suffers from significant bias, related to simultaneous equations bias. In the moderately explosive case (where c(i) > 0) the limit theory is mixed normal with Cauchy-type tail behavior, and the rate of convergence is explosive, as in the case of a moderately explosive scalar autoregression (Phillips and …
A New Approach To Robust Inference In Cointegration, Sainan Jin, Peter Phillips, Yixiao Sun
A New Approach To Robust Inference In Cointegration, Sainan Jin, Peter Phillips, Yixiao Sun
Research Collection School Of Economics
A new approach to robust testing in cointegrated systems is proposed using non-parametric HAC estimators without truncation. While such HAC estimates are inconsistent, they still produce asymptotically pivotal tests and, as in conventional regression settings, can improve testing and inference.