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Focusing in particular on upper secondary education, this paper examines whether the relatively high level of expenditure on education in the Nordic countries is matched by high output from the educational sector, both in terms of student enrolment and indicators of output quality in the form of graduation/completion rates and expected earnings after completed education. We use data envelopment analysis (DEA) to compare (benchmark) the Nordic countries with a relevant group of rich OECD countries and calculate input efficiency scores for each country. We estimate a wide range of specifications in order to analyse different aspects of efficiency. In purely quantitative models (where inputs and outputs are expenditure and number of students at different levels of the educational system) and in models where graduation or completion rates are included as indicators of output quality, Finland is the most efficient Nordic country (often fully efficient), whereas Sweden and especially Norway and Denmark are clearly inefficient. However, using PISA test scores as indicators of student input quality in upper secondary education reduces the inefficiencies of these three countries. Also, when expected earnings after completed education are used as an indicator of output quality, all Nordic countries are estimated to be fully efficient (or nearly so).

A macroeconomic rationing model based on nested CES transaction functions for the goods and labour markets is presented. The model is estimated on quarterly data for the Danish private non-agricultural sector, using regime proportion indicators based on business survey information. The focus of the paper is on the method of estimation, which is a two-step procedure. To take account of the fact that some of the variables of the model are integrated of order one, the corresponding parameters are estimated by cointegration techniques (the Johansen method) in the first step. In the second step the other parameters of the model are estimated simultaneously by GMM. It is argued that this two-step estimation procedure is consistent. Finally, the estimation results are used to cast some light on the rise in Danish unemployment in the period 1971–1990.