A significant obstacle to studying business cycle properties of job polarization has been the presence of inconsistencies in aggregate employment data for different occupation groups. In order to overcome this problem, we construct aggregate hours series using the method of 'conversion factors',...

This paper explores the relationship between job polarization and interindustry wage differentials. Using the U.S. Census and EU KLEMS data, we find that the progress of job polarization between 1980 and 2009 was more evident in industries that initially paid a high wage premium to workers than...

Manufacturing and services have been regarded as the ???twin engines' of growth for Singapore economy. As the economy is moving up the value chain from downstream to upstream activities, a significant proportion of FDI (foreign direct investment) has been attracted to the manufacturing and...

This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is proposed and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially...

This paper establishes a suite of uniform consistency results for nonparametric kernel density and regression estimators when the time series regressors concerned are nonstationary null-recurrent Markov chains. Under suitable conditions, certain rates of convergence are also obtained for the...

Local linear fitting is a popular nonparametric method in statistical and econometric modelling. Lu and Linton (2007) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this...

This paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the...

In this paper we propose a new methodology for selecting the window length in Singular Spectral Analysis in which the window length is determined from the data prior to the commencement of modeling. The selection procedure is based on statistical tests designed to test the convergence of the...

In Singular Spectrum Analysis (SSA) window length is a critical tuning parameter that must be assigned by the practitioner. This paper provides a theoretical analysis of signal-noise separation and reconstruction in SSA that can serve as a guide to optimal window choice. We establish numerical...