大都市圏中心地域の人口動態・土地利用形態のマクロ的分析

抄録

In big urban area like Tokyo Metropolitan region, the concentration of population causes several big urban issues like shortage of Social Overhead Capital and of housing and creates the great financial difficulty for local governments to match these social needs. One of the basic factors which accelerate the difficulty of solving these issues is the shortage of adequate land space and resulted high land price in central area.
The purpose of this paper is to construct an econometric model about Tokyo Metropolis in narrow sense (23-ku or District at center of Tokyo Metropolitan Area) with special emphasis on interrelationships between tendencies of demography and of land price and resulting land use, and apply this model for simulation experiments to clarify the interlinkage of these factors and also to verify the effects of relevant urban policies.
We constructed the model with 28 equations (19 estimated equations & 9 identities) based upon the time series data for 1965-78. The model consists of five blocks: (1) demography and employment, (2) land-use, (3) spaces of buildings and houses, (4) land price, (5) other indices of Tokyo prefecture. The central area is a part of and tightly connected with Tokyo prefecture, so we need to treat some important indices of Tokyo prefecture to close the model. Some important endogenous variables are residential population, social inflow and outflow, number of households, employment, land space for farming, industrial and commercial use, housing, public use, and roads, space of housing, space of inflammable construction, space of offices, land price of residential area. The result of final test showed good fitting to actual tendencies in general.
We calculated five simulations in total within the observation period and compared with the controlled solution, that is, the final test. They are (1) increases the land price all through the period, (2) increase the suburb population throughout the period, (3) increase the residential population in central area all through the period, (4) increase the initial space of inflammable construction, (5) change the inner-city farming land to housing use initially. One of the remarkable observations in experiment (5) is that after initial increase of land space for housing the increases in residential population and office space follow and in the course of time the land price becomes higher than controlled solution pushed by increasing demand. Thus better environmental condition induces increase of population and makes the solution of urban issues more difficult. Another interesting observations are found in other simulations.
We want to improve this urban econometric model by introducing financial sector, combining with another model of the suburb area or of Japanese economy, and by integrating with tools of another disciplines in the future.