Journal of Applied Econometrics
Measurement of Total Factor Productivity Growth and Biases in Technological Change in Western Australian Agriculture [статья]
Опубликовано на портале: 11-09-2003Tim J. Coelli Journal of Applied Econometrics. 1970. Vol. 11. No. 1 . P. 77-91.
This study investigates productivity growth in broad-acre agriculture in Western Australia. Tornqvist indices of three output groups (crops, sheep products and other) and five input groups (livestock, materials and services, labour, capital and land) are constructed and discussed. Indices of total output and total inputs are also derived and used to form an index of total factor productivity, that is observed to grow at an average annual rage of 2.7%. The input and output indices are also used in the estimation of output supply and input demand equations, derived from a flexible profit function. The Generalized McFadden functional form is used, because it is possible to impose global curvature upon it without loss of flexibility. Asymptotic chi-square tests reject the hypotheses of Hicks-neutral technical change in inputs and in outputs. Technical change is observed to be `materials and services' saving relative to the other input groups, and also appears to favour wool and sheepmeat production relative to the other output groups.
Опубликовано на портале: 26-04-2003Anthony Garratt, Stephen G. Hall Journal of Applied Econometrics. 1996. Vol. Vol. 11. No. 2. . P. pp. 135-151.
Recently, interest in the methodology of constructing coincident economic indicators has been revived by the work of Stock and Watson (1989b). They adopt the framework of the state space form and Kalman filter in which to construct an optimal estimate of an unobserved component. This is interpreted as corresponding to underlying economic activity derived from a set of observed indicator variables. In this paper we apply the Stock and Watson approach to the UK where the observed indicator variables are those that make up the Central Statistical Office (CSO) coincident indicator. The time series properties of the indicator variables are examined and three of the five variables are first difference stationary and are cointegrated, the remaining two are stationary in levels. We then construct two alternative measures of economic activity, each of which deals with the different orders of stationarity of the variables. The first uses the levels of the observed component variables that allows for the cointegrating relationship. The second imposes stationarity on the I(1) variables before the estimation by taking first differences. The levels index is viewed as the preferred specification as it allows for the long-run relationships between the variables and has a superior statistical fit.