FORECASTING THE BUSINESS-CYCLE USING SURVEY DATA

被引:15
|
作者
OLLER, LE
机构
[1] Department of Economics, University of Helsinki
关键词
TURNING POINT PREDICTION; CARLSON-PARKING TRANSFORM; EXPONENTIAL SMOOTHING; COMBINING FORECASTS;
D O I
10.1016/0169-2070(90)90021-3
中图分类号
F [经济];
学科分类号
02 ;
摘要
Regular business survey data are published as percentages of firms predicting higher, equal or lower values of some reference variable. Time series of such percentages do not fit production data too well. Univariate models often produce forecasts which are just as accurarate. Still, surveys contain anticipative judgement which, when combined with univariate modeling and proper filtering, may produce a good indicator for business cycle turning points. The way survey data are transformed so as to fit statistics on production seems not to be of much importance. A case study of the Finnish forest industry is offered as an example. © 1991.
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页码:453 / 461
页数:9
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