Browsing by Author "Binge, Laurie H."

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Methods for aggregating microeconomic data : applications to art prices, business sentiment and historical commodity prices
    (Stellenbosch : Stellenbosch University, 2018-03) Binge, Laurie H.; Boshoff, Willem H.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.
    ENGLISH SUMMARY : In the modern world, large microeconomic datasets are becoming increasingly available due to technological developments. These datasets provide an opportunity to improve the measurement of a range of economic phenomena and to bolster economic research. One particular way in which these large datasets can aid economic analysis is to allow the creation of macroeconomic indicators from aggregated microeconomic data. Yet, there are often challenges in aggregating these large datasets and in identifying the underlying pattern in the data. The aim in this dissertation is to explore aggregation methods that overcome specific challenges in aggregating three relatively large microeconomic datasets to create time-series indicators. The first case explores aggregation methods for estimating South African art price indices (2000Q1-2015Q4), using a large database of art auction prices. The challenge in aggregating this dataset is that artworks are by and large unique and infrequently traded, which means that the composition of items sold is not constant over time. To address this challenge, central tendency, hedonic and hybrid repeat sales methods are used to estimate quality-adjusted South African art price indices. The second case explores aggregation methods for estimating indicators of business confidence and uncertainty for South Africa (1992Q1-2016Q3), using the Stellenbosch University Bureau for Economic Research’s (BER) business tendency surveys. The challenge in aggregating this dataset is to measure these concepts by identifying a pattern in the disparate views of individual agents. To address this challenge, aggregation methods for capturing the full distribution of the qualitative survey responses are explored. The cross-sectional weighted first and second moments of the distribution of responses are calculated to create new indicators of business confidence and uncertainty for South Africa. The third case explores aggregation methods for estimating monthly commodity price indices for the Cape Colony (September 1889 - July 1914), using two newly digitised datasets of commodity prices for various towns in the Colony. The challenge in aggregating these datasets is that both sets of records are incomplete, in terms of the coverage of both products and towns. The repeat sales method is used to aggregate the incomplete price series for various towns from both sources, to create more complete monthly commodity price indices for the Cape Colony. Testing specific hypotheses is useful, both in demonstrating the potential research applications for the aggregated indicators, and in assessing the validity of the proposed aggregation methods. The dissertation therefore uses the time-series indicators to test a specific hypothesis in each case. The first case examines the estimated South African art price indices for evidence of a bubble. The hypothesis that South African art prices exhibited mildly explosive behaviour between 2000 and 2015 is tested. The second case examines the relationship between business sentiment and real activity in South Africa, by testing the hypothesis that there was significant comovement between the sentiment indicators and real GDP growth. The third case examines the commodity price indices, as well as indicators of price dispersion, for evidence of increasing internal market integration in the Cape Colony. The hypotheses of price convergence between towns and cointegration of regional price indices are tested. This dissertation is a contribution to the literature in that it demonstrates suitable aggregation methods to overcome some of the challenges in aggregating relatively large microeconomic datasets. These aggregation challenges relate to (i) estimating quality-adjusted price indices for unique and infrequently traded items, (ii) developing aggregate measures of sentiment based on the disparate views of a large number of respondents, and (iii) estimating complete price indices from data that is incomplete. These aggregation methods may prove useful in a variety of settings where there are similar challenges. The estimated time series may prove useful for further research in each of the relevant fields and are reported in the chapter appendices.