The scope and scale of the informal food economy of South African urban residential townships: Results of a small-area micro-enterprise census

Growing urbanisation in South Africa is reflected in burgeoning Working class and informal township settlements on the fringes of its major towns and cities. Paired with this is an increasing reliance on cash as the primary means of economic transaction, which has in turn stimulated the growth of micro-enterprise business activities within the township context. This article discusses the findings of an eight-township small-area census which occurred between 2010 and 2013 in Cape Town, Johannesburg, Ekurhuleni and Durban townships representing 250 000 residents. The researchers were able to establish the scope and scale of informal food and drink retailing in these localities. Of the 10 049 micro-enterprises located in the study, some 3966 (or 39% of the total) trade in food. These include enterprises in primary production, fresh produce retailing, grocery retailing from house and spaza shops, and informal foodservice enterprises. Food is the basis for much township informal business and plays an important role in making food increasingly affordable and locally accessible, and in creating cash employment. The article builds on the knowledge base of the township informal economy role in bolstering food security needs for the marginalised.     

Testing Part of a DSGE Model by Indirect Inference

We propose a way of testing a subset of equations of a DSGE model. The test draws on statistical inference for limited information models and the use of indirect inference to test DSGE models. Using the numerical small sample distribution of our test for two subsets of equations of the Smets–Wouters model we show that the test has accurate size and good power in small samples, and better power than using asymptotic distribution theory. In a test of the Smets–Wouters model on US Great Moderation data, we reject the specification of the wage‐price but not the expenditure sector. This points to the wage‐price sector as the source of overall model rejection.     

COVID-19 and business renewal: Lessons and insights from the global airline industry

The emergence of the COVID-19 pandemic has adversely affected the fortunes of multiple companies around the globe. Accordingly, questions are increasingly being asked about how organizations can revitalize during and after a crisis. Yet, we have limited understanding of how organizations renew themselves during crises over time. We explore this question through the lens and examination of two South-Asian airlines: Pakistan International Airlines and Sri Lankan Airlines. The cases offer important insights into the reasons behind underperformance of state-controlled enterprises and renewal activities. We shed light on strategic renewal (SR) in the wake of increasing liberalization and deregulations in the global airline industry. To this end, we propose a four-stage approach towards renewing such underperforming organizations to respond effectively to black swan events and external shocks.     

Missing the Popular Vote: Pitfalls in US Democracy and Reform Proposals

Intereconomics - Only a few years ago, it was a widespread belief that globalisation would trigger processes of democratisation worldwide. However, even old and established democracies such as the...     

It is not just about paying your dues: Impact of generational cohort on active and passive union participation

The lack of a validated measure of active–passive union participation and a dearth of research into the relationship between generational cohort and union participation challenge union leaders to develop policies and practices to facilitate union renewal. We address these issues by (a) developing a multidimensional measure of union participation that captures both active and passive components, (b) using structural equation modelling to validate the measure within a nomological framework, and (c) investigating the impact of generational cohort on all paths in our framework. Data from members of a large American union confirm that generational cohort influences how union members participate in their union. The two‐factor measure developed in this study facilitates research into antecedents and outcomes of passive and active union participation. Our findings should also prove useful to unions seeking to increase participation within their membership, academics researching unions and generational cohort, and human resource practitioners operating in unionised environments.     

Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.