A M Robert Taylor
Biographic Data
| ID | 8920264 |
|---|---|
| NAME | A M Robert Taylor |
| GIVEN NAMES | A M Robert |
| FAMILY NAME | Taylor |
| SIGNATURE | TAYLOR A M R |
| AFFILIATIONS | University of Birmingham |
| ORCID | 0000-0003-0567-0276 |
| VERIFIED | Yes |
| TOTAL WORKS | 18 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 18 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1979 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Covariate-Augmented Cusum Bubble Monitoring Procedures
We explore how information from covariates can be incorporated into the CUSUM-based real-time monitoring procedure for explosive asset price bubbles developed in Homm and Breitung (2012, Journal of Financial Econometrics 10, 198–231). Where dynamic covariates are present in the data generating process (DGP), the false positive rate (FPR) of the basic CUSUM procedure, which is based on the assumption that prices follow a univariate DGP, under the …
Bonferroni‐Type Tests for Return Predictability With Possibly Trending Predictors
The Bonferroni test is widely used in empirical studies investigating predictability in asset returns by strongly persistent and endogenous predictors. Its formulation, however, only allows for a constant mean in the predictor, seemingly at odds with many of the predictors used in practice. We establish the asymptotic size and local power properties of the test, and the corresponding Bonferroni ‐test, under a local‐to‐zero specification for a lin…
Bonferroni Type Tests for Return Predictability and the Initial Condition
We develop tests for predictability that are robust to both the magnitude of the initial condition and the degree of persistence of the predictor. While the popular Bonferroni Q test of Campbell and Yogo displays excellent power properties for strongly persistent predictors with an asymptotically negligible initial condition, it can suffer from severe size distortions and power losses when either the initial condition is asymptotically non-neglig…
Semiparametric Tests for the Order of Integration in the Possible Presence of Level Breaks
Lobato and Robinson (1998) develop semiparametric tests for the null hypothesis that a series is weakly autocorrelated, or I(0), about a constant level, against fractionally integrated alternatives. These tests have the advantage that the user is not required to specify a parametric model for any weak autocorrelation present in the series. We extend this approach in two distinct ways. First, we show that it can be generalised to allow for testing…
Adaptive Inference in Heteroscedastic Fractional Time Series Models
We consider estimation and inference in fractionally integrated time series models driven by shocks which can display conditional and unconditional heteroscedasticity of unknown form. Although the standard conditional sum-of-squares (CSS) estimator remains consistent and asymptotically normal in such cases, unconditional heteroscedasticity inflates its variance matrix by a scalar quantity, λ>1, thereby inducing a loss in efficiency relative to th…
Real‐time detection of regimes of predictability in the US equity premium
We propose new real‐time monitoring procedures for the emergence of end‐of‐sample predictive regimes using sequential implementations of standard (heteroskedasticity‐robust) regression t ‐statistics for predictability applied over relatively short time periods. The procedures we develop can also be used for detecting historical regimes of temporary predictability. Our proposed methods are robust to both the degree of persistence and endogeneity o…
Multivariate fractional integration tests allowing for conditional heteroskedasticity with an application to return volatility and trading volume
We introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the Lagrange multiplier principle to a feasible generalised least squares estimate of the FIVAR model obtained under the null hypothesis. A key feature of the test we propose is that it is constructed using a heteroskedasticity‐robust estimate of the variance matrix. As a resul…
A Bootstrap Stationarity Test for Predictive Regression Invalidity
In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially al…
Religion in the Lives of African Americans
Deriving conclusions from the National Survey of Black Americans & other surveys, this text examines issues of religious involvement, the functions of religion, & the relationships between religion & physical & mental health & well-being
Robust Stationarity Tests in Seasonal Time Series Processes
This article builds on the existing literature on (stationarity) tests of the null hypothesis of deterministic seasonality in a univariate time series process against the alternative of unit root behavior at some or all of the zero and seasonal frequencies. This article considers the case where, in testing for unit roots at some proper subset of the zero and seasonal frequencies, there are unattended unit roots among the remaining frequencies. Mo…
Variance Shifts, Structural Breaks, and Stationarity Tests
This article considers the problem of testing the null hypothesis of stochastic stationarity in time series characterized by variance shifts at some (known or unknown) point in the sample. It is shown that existing stationarity tests can be severely biased in the presence of such shifts, either oversized or undersized, with associated spurious power gains or losses, depending on the values of the breakpoint parameter and on the ratio of the prebr…
Regression-Based Unit Root Tests With Recursive Mean Adjustment for Seasonal and Nonseasonal Time Series
This article considers tests for (seasonal) unit roots in a univariate time-series process that are similar with respect to both the initial values of the process and the possibility of (differential seasonal) drift under the (seasonal) unit root null. In contrast to existing approaches, the technique of recursive (seasonal) de-meaning and (seasonal) de-trending of the process is adopted. Representations are derived for the limiting distributions…
On the Properties of Regression-Based Tests for Seasonal Unit Roots in the Presence of Higher-Order Serial Correlation
We analyze the behavior of widely used regression-based tests for seasonal unit roots when the shocks are serially correlated. We show, in the quarterly case, that the common assumption that serial correlation may be accommodated by augmenting the test regression with appropriate lagged seasonal differences is only partially correct. The limiting null distributions of t statistics for unit roots at the zero and Nyquist frequencies are corrected b…
Tests of the Seasonal Unit-Root Hypothesis Against Heteroscedastic Seasonal Integration
This article considers the problem of testing for a nonstochastic seasonal unit root in a seasonally observed time series process against the alternative of a randomized seasonal root with mean unity; that is, the process displays heteroscedastic seasonal integration. The alternative hypothesis allows for potentially frequently occurring changes of regime in the process under investigation, allowing for more volatile forms of seasonal nonstationa…
Some comments on the Blair/Schroeder “Third Way/ Neue Mitte ” manifesto
Population Explosions and Housing, 1550—1850
An examination of the surviving building and alterations carried out in response to the early nineteenth-century population increase in Cambridgeshire and Northamptonshire reveals two separate phases. The first consists mainly of subdivision of existing houses, whereas the second consists mainly of building new dwellings. This general sequence can be applied to earlier population increases, and would help explain some of the instances where a lar…
Knee Principal Roofs
Career orientations and intra‐occupational choice
This paper reports a questionnaire survey of final‐year engineering students at Imperial College, London. Results indicate considerable self‐selection between students' career orientations and their job choices. Most students took jobs in engineering and most of these were within the branch of their training. Those students entering R & D or design had different career orientations from those entering ‘operations' or from those leaving engineerin…
No prominent works on this page.
Career orientations and intra‐occupational choice
This paper reports a questionnaire survey of final‐year engineering students at Imperial College, London. Results indicate considerable self‐selection between students' career orientations and their job choices. Most students took jobs in engineering and most of these were within the branch of their training. Those students entering R & D or design had different career orientations from those entering ‘operations' or from those leaving engineerin…
Knee Principal Roofs
Population Explosions and Housing, 1550—1850
An examination of the surviving building and alterations carried out in response to the early nineteenth-century population increase in Cambridgeshire and Northamptonshire reveals two separate phases. The first consists mainly of subdivision of existing houses, whereas the second consists mainly of building new dwellings. This general sequence can be applied to earlier population increases, and would help explain some of the instances where a lar…
Some comments on the Blair/Schroeder “Third Way/ Neue Mitte ” manifesto
On the Properties of Regression-Based Tests for Seasonal Unit Roots in the Presence of Higher-Order Serial Correlation
We analyze the behavior of widely used regression-based tests for seasonal unit roots when the shocks are serially correlated. We show, in the quarterly case, that the common assumption that serial correlation may be accommodated by augmenting the test regression with appropriate lagged seasonal differences is only partially correct. The limiting null distributions of t statistics for unit roots at the zero and Nyquist frequencies are corrected b…
Tests of the Seasonal Unit-Root Hypothesis Against Heteroscedastic Seasonal Integration
This article considers the problem of testing for a nonstochastic seasonal unit root in a seasonally observed time series process against the alternative of a randomized seasonal root with mean unity; that is, the process displays heteroscedastic seasonal integration. The alternative hypothesis allows for potentially frequently occurring changes of regime in the process under investigation, allowing for more volatile forms of seasonal nonstationa…
Regression-Based Unit Root Tests With Recursive Mean Adjustment for Seasonal and Nonseasonal Time Series
This article considers tests for (seasonal) unit roots in a univariate time-series process that are similar with respect to both the initial values of the process and the possibility of (differential seasonal) drift under the (seasonal) unit root null. In contrast to existing approaches, the technique of recursive (seasonal) de-meaning and (seasonal) de-trending of the process is adopted. Representations are derived for the limiting distributions…
Robust Stationarity Tests in Seasonal Time Series Processes
This article builds on the existing literature on (stationarity) tests of the null hypothesis of deterministic seasonality in a univariate time series process against the alternative of unit root behavior at some or all of the zero and seasonal frequencies. This article considers the case where, in testing for unit roots at some proper subset of the zero and seasonal frequencies, there are unattended unit roots among the remaining frequencies. Mo…
Variance Shifts, Structural Breaks, and Stationarity Tests
This article considers the problem of testing the null hypothesis of stochastic stationarity in time series characterized by variance shifts at some (known or unknown) point in the sample. It is shown that existing stationarity tests can be severely biased in the presence of such shifts, either oversized or undersized, with associated spurious power gains or losses, depending on the values of the breakpoint parameter and on the ratio of the prebr…
Religion in the Lives of African Americans
Deriving conclusions from the National Survey of Black Americans & other surveys, this text examines issues of religious involvement, the functions of religion, & the relationships between religion & physical & mental health & well-being
A Bootstrap Stationarity Test for Predictive Regression Invalidity
In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially al…
Real‐time detection of regimes of predictability in the US equity premium
We propose new real‐time monitoring procedures for the emergence of end‐of‐sample predictive regimes using sequential implementations of standard (heteroskedasticity‐robust) regression t ‐statistics for predictability applied over relatively short time periods. The procedures we develop can also be used for detecting historical regimes of temporary predictability. Our proposed methods are robust to both the degree of persistence and endogeneity o…
Multivariate fractional integration tests allowing for conditional heteroskedasticity with an application to return volatility and trading volume
We introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the Lagrange multiplier principle to a feasible generalised least squares estimate of the FIVAR model obtained under the null hypothesis. A key feature of the test we propose is that it is constructed using a heteroskedasticity‐robust estimate of the variance matrix. As a resul…
Semiparametric Tests for the Order of Integration in the Possible Presence of Level Breaks
Lobato and Robinson (1998) develop semiparametric tests for the null hypothesis that a series is weakly autocorrelated, or I(0), about a constant level, against fractionally integrated alternatives. These tests have the advantage that the user is not required to specify a parametric model for any weak autocorrelation present in the series. We extend this approach in two distinct ways. First, we show that it can be generalised to allow for testing…
Adaptive Inference in Heteroscedastic Fractional Time Series Models
We consider estimation and inference in fractionally integrated time series models driven by shocks which can display conditional and unconditional heteroscedasticity of unknown form. Although the standard conditional sum-of-squares (CSS) estimator remains consistent and asymptotically normal in such cases, unconditional heteroscedasticity inflates its variance matrix by a scalar quantity, λ>1, thereby inducing a loss in efficiency relative to th…
Bonferroni Type Tests for Return Predictability and the Initial Condition
We develop tests for predictability that are robust to both the magnitude of the initial condition and the degree of persistence of the predictor. While the popular Bonferroni Q test of Campbell and Yogo displays excellent power properties for strongly persistent predictors with an asymptotically negligible initial condition, it can suffer from severe size distortions and power losses when either the initial condition is asymptotically non-neglig…
Bonferroni‐Type Tests for Return Predictability With Possibly Trending Predictors
The Bonferroni test is widely used in empirical studies investigating predictability in asset returns by strongly persistent and endogenous predictors. Its formulation, however, only allows for a constant mean in the predictor, seemingly at odds with many of the predictors used in practice. We establish the asymptotic size and local power properties of the test, and the corresponding Bonferroni ‐test, under a local‐to‐zero specification for a lin…
Covariate-Augmented Cusum Bubble Monitoring Procedures
We explore how information from covariates can be incorporated into the CUSUM-based real-time monitoring procedure for explosive asset price bubbles developed in Homm and Breitung (2012, Journal of Financial Econometrics 10, 198–231). Where dynamic covariates are present in the data generating process (DGP), the false positive rate (FPR) of the basic CUSUM procedure, which is based on the assumption that prices follow a univariate DGP, under the …
Mathematics (12 works) · Econometrics (11 works) · Statistics (10 works) · Computer Science (9 works) · Financial Risk and Volatility Modeling (9 works) · Market Dynamics and Volatility (9 works) · Monetary Policy and Economic Impact (8 works) · Statistical hypothesis testing (6 works) · Heteroscedasticity (5 works) · Geography (4 works)