Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.     

Testing the effectiveness of regulatory interest rate risk measurement

A depository institution's interest rate risk (IRR) exposure is the sensitivity of its earnings or market value of equity to changes in interest rates. Since the mid-1980's, bank regulators have developed broadly applied, centralized IRR models which are used to help assess individual institutions' capital adequacy. This paper tests the effectiveness of the earliest of these regulatory IRR models: the incomegap estimates calculated by the Federal Home Loan Bank Board (FHLBB) during the latter 1980's. Despite the many problems caused by the broad application of generic assumptions and the presence of embedded options, we find that the FHLBB gap estimates provided a significant measure of IRR exposure. We believe that these results bode well for the success of ongoing, more sophisticated regulatory modeling efforts.     

Total factor productivity in South African agriculture, 1947‐91

Indices of total factor productivity (TFP) measure aggregate output per unit of aggregate input, providing a guide to the efficiency of agricultural production. This article outlines the relationship between production functions and TFP indices. Then, an index is constructed for South African agriculture for the period 1947‐91. The index shows that TFP grew at an average rate of 1,3 per cent per annum. However, TFP growth has increased since the reforms of the early 1980s. Since capital has been more realistically priced relative to labour, greater productivity growth has gone together with increasing employment, which must have improved social welfare.     

Agriculture: Toward the year 2000

When the World Food Conference of 1974 demanded the eradication of world hunger within the brief time span of ten years, experts and laymen alike were surprised. The target seemed too ambitious, and it can be safely expected that it will not be achieved. A study has now been submitted by FAO to its 20th Plenary Conference session which—without proposing a new target date—attempts to prove the feasibility of greatly reducing world hunger before the advent of the 21st century.