International comparisons of the effects of nonmarket-sector growth

This paper examines the implications for macroeconomic performance of differing rates of growth of the nonmarket sector in different countries. It provides a framework within which international comparisons of nonmarket-sector expansion can be made and identifies possible consequences of employment growth in both market and non-market sectors. This analysis is then applied to a sample of developed and less developed countries, which suggests that, among developed countries, the adverse effects associated with nonmarket-sector expansion have probably been greatest in the U.K. Similar effects, however, are evident in several less developed countries.     

Forecasting Using Long-Order Autoregressive Processes: An Example Using Housing Starts

A long autoregressive (AR) modeling procedure for monthly U.S. housing starts data is considered. Neither differencing to remove the trend, nor differencing to remove the seasonal component is required in this method. The model is fitted by a Householder transformation-Akaike AIC criterion algorithm. Forecast performance is compared to that obtained by the Box-Jenkins ARIMA method. The prediction error variance of the long AR model method tends to be smaller than the prediction error variance of the Box-Jenkins model method. The long AR method is well suited for housing market time-series which are characterized by both strong seasonal and slowly changing trend components.     

Modeling the urban land market: The case of Japan

Two sets of negative exponential functions, one for urban residential density and the second for land price, are estimated. The parameters of these functions are then employed in an econometric model of land use and urban form in 71 Japanese cities. Several variables are determined, including average land price, gross population density, housing size, and population.