Skyscraper Index - Recent Work That Tests The Skyscraper Index Hypothesis

Recent Work That Tests The Skyscraper Index Hypothesis

A recent study by Barr, Mizrach and Mundra (2011), entitled "Skyscraper Height and the Business Cycle: International Time Series Evidence" aims to see if there is, in fact, a correlation between skyscraper height and economic growth. The study looks at two types of data. First the paper looks at the announcement and completion dates of the world's tallest buildings and the peaks and troughs of the United States business cycle, as measured by the National Bureau of Economic Research. They find that there is virtually no relationship between the timing of record breaking buildings and the business cycle. Second, the authors investigate height and economic growth using the times series techniques of vector autoregression and cointegration tests. They investigate the time series relationship between the tallest building completed each year and the level of per capita GDP, for the United States, Canada, China and Hong Kong. The authors find that the two series are co-integrated, which means that they move together over time. That is to say, the tallest building completed each year in these countries does not systematically move away from the underlying income of the country, which provides evidence that, in general, skyscraper height is not fundamentally based on height competition among builders. Finally, the vector autoregression methods allow the authors to see if skyscraper height can predict changes in gross domestic product (GDP) (i.e., if height predict recessions). The authors find that height cannot, in fact, be used to predict changes in GDP. However, GDP can be used to predict changes in height. In other words, the study finds that extreme height is driven by rapid economic growth, but that height can not be used as an indicator of recessions.