Univariate Potential Output Estimations for Hungary

Potential output figures are important ingredients of many macroeconomic modelsand are routinely applied by policy makers and global agencies. Despite itswidespread use, estimation of potential output is at best uncertain and dependsheavily on the model. The task of estimating potential output is an even moredubious exercise for countries experiencing huge structural changes, such astransition countries. In this paper we apply univariate methods to estimate andevaluate Hungarian potential output, paying special attention to structural breaks.In addition to statistical evaluation, we also assess the appropriateness of variousmethods by expertise judgement of the results, since we argue that mechanicaladoption of univariate techniques might led to erroneous interpretation of thebusiness cycle. As all methods have strengths and weaknesses, we derive a singlemeasure of potential output by weighting those methods that pass both thestatistical and expertise criteria. As standard errors, which might be used forderiving weights, are not available for some of the methods, we base our weightson similar but computable statistics, namely on revisions of the output gap for alldates by recursively estimating the models. Finally, we compare our estimated gapswith the result of the only published Hungarian output gap measure of Darvas-Simon (2000b), which is based on an economic model.