Martin Wittenberg's research while affiliated with University of Cape Town and other places

A comparison of national census data and small-area health and demographic surveillance system (HDSS) data

The October Household Surveys (OHS) (1994–1999) and the General Household Surveys (GHS) (2002–present) collected by StatsSA comprise South Africa's only nationally representative time series with information on both people and households for (almost) every year of the post‐apartheid period. However, the quality of these data has been compromised by how the survey weights have been calibrated. We document these problems and their implications in detail and then use cross‐entropy estimation to recalibrate the survey weights for a stacked version of these surveys between 1995 and 2011 to address these weaknesses. The first issue with the weights is that calibration procedure breaks with sampling practise by calibrating person and household weights separately. This creates conceptual problems because the data are not properly representative of the population. It also creates statistical problems, including that a series of total population and household counts cannot be reliably extracted from the series, which is typically a first‐order output for such a time series. Second, the series of household counts extracted from the GHS is probably too low. Third, no compensation is made by the survey weights for the chronic undersampling of small households over the entire period. Our new weights make headway in resolving these issues.

Rising inequality in the developed world over the last 40 years has been accompanied by declining trade union power. Unions have been found to raise the wages of their members but also to reduce overall wage inequality through the standardisation of wages in the union sector. In this paper we examine the extent to which unions raise wages and affect the extremely high levels of wage inequality in South Africa, using comparable household surveys from 1993-2019. We find that union wage premia are extremely high, and that union membership has become increasingly concentrated at the top of the wage distribution and in the public sector. As a result, variance decompositions show that unions increased inequality slightly in more recent periods. We also find that earnings imputation from 2010 onwards makes estimating the true impact of unionisation on wages impossible without unimputed earnings data.

The Post-Apartheid Labour Market Series ( palms ) is a compilation of microdata from 69 household surveys conducted in South Africa. The dataset and the code used to create the data are publicly available from DataFirst, a data repository at the University of Cape Town ( www.doi.org/10.25828/gtr1-8r20 ). To harmonise the data required understanding the differences across the surveys, which has generated new knowledge about the South African labour market.

South Africa has seen a rapid rate of new household formation since 1994. The same period has also seen an impressive roll-out of housing and services. These interact since new household formation delays the elimination of backlogs. Based on data from the Agincourt study site and a novel decomposition technique we examine the process by which household size has been reduced and suggest that service delivery may actually fuel new household formation.

South Africa differentiated itself in the 20th century by embarking on a social experiment (grand apartheid) which intervened extensively in all facets of its citizens’ lives, including the labor market. With the demise of apartheid and reintegration into the world economy, South Africa's 21st century labor market dynamics increasingly resemble those of other economies, with a widening of the earnings distribution, particularly at the top. Nevertheless, there are still important vestiges of the late apartheid era, including a high unemployment rate, significant union power, and persistent racial and gender premia.

In microeconomics, people and households are key units of analysis making it important that they sensibly relate to each other in the data with which they are studied. Although most Statistics South Africa household surveys are designed to be simultaneously representative of people and households, weighting practise is to split the calibration of person and household weights, rendering the data only representative of either the household or the person universe at a time. This process introduces noise to inference and needlessly curtails the number of questions the data can be used to answer in a conceptually coherent way. The motivation for splitting the person and household weights was that policymakers in particular needed an accurate series of total household counts and it was unknown whether constraining the existing calibration on both person and household information would yield the desired outcome. This paper uses cross-entropy estimation to reweight a stacked series of cross-sections from the October Household Survey (1994-1999) and the General Household Survey (2002-2015) to restore representativeness and bring weighting practise back in line with sampling practise, whilst focusing on achieving accurate total counts of both people and households. The new weight not only achieves accurate total counts but outperforms the separate person and household weights overall.

Increased household formation, and its corollary of decreasing household size, is a global demographic trend with important consequences for human and environmental welfare. There are a host of potential demographic, economic, and institutional levers on household formation, many of which vary considerably across the developed and developing world. Understanding the factors driving household formation in both settings is therefore an important topic. In South Africa, household formation has been relatively quick by global standards. Yet, intensive income inequality , widespread poverty, and open unemployment would lead us to expect a slower trend. We empirically investigate a household headship model, by gender, to uncover the main drivers with special focus on the institutional factors that make South Africa stand out. These are the country's recent history of racial segregation, and, marriage rates that are much lower than would be expected in such a gender-conservative setting. We find that although men are still more likely to head households than women, women have increased the rate at which they form households more than men when the usual demographic factors are accounted for. The period we study is 1995-2011, and by the end of this period, most female heads had never been married. Headship rates have increased most amongst older female age cohorts and we find preliminary evidence that the generations of Black women who were prime-aged at the end of apartheid are the most likely to head households compared to both their younger and older counterparts. These women are conceptualised as taking advantage of their new political freedom whilst, like young adults around the world, younger cohorts of women of all population groups in South Africa are delaying moving out in a context of poor economic conditions.

Background: Household trends are generally tracked by means of repeated cross-sections, such as censuses or nationally representative surveys. However, the trends may be driven either by changes within households over time or the way in which the processes of household formation/dissolution interact with the measure in question. Objective: We aim to develop a method that enables us to apportion changes in a household measure to changes that happen within households and changes that occur due to household formation and dissolution. In particular we intend to show how South African households have reduced in size and how access to services has increased. Methods: We develop a formula for decomposing a household outcome measure. We apply the formula to household size and electricity access data from the Agincourt health and demographic surveillance site for the period 1994 to 2012. We also apply it to the National Income Dynamics Survey of South Africa from 2008 to 2012. We compare the results to the pattern derived from nationally representative surveys run by Statistics South Africa since 1994. Results: The overall reduction in household size is fuelled by rapid household formation, much of which is intertwined with shifts in location. Access to services has been reduced by the process of new household formation. Neither finding is evident from cross-sectional data. Contribution: We introduce a new decomposition technique which can be used with longitudinal data and discuss the insights that it provides.