Obesity of politicians and corruption in Ukraine in 2000–2020– Reply

We collected 469 frontal face images of Ukrainian cabinet ministers who were in office in 2000–2020. For each image, the minister's body mass index was estimated using a computer vision algorithm. The time series of median estimated body mass index of cabinet ministers co-moves over time with two existing measures of corruption – World Bank worldwide governance indicator Control of Corruption, and the discrepancy between the quantity of luxury wristwatches exported from Switzerland to Ukraine (reported by Swiss statistics) and the corresponding quantity imported by Ukraine from Switzerland (reported by Ukrainian statistics).     

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.     

Information flows and crashes in dynamic social networks

We develop a dynamic model of information transmission and aggregation in social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity, in which agents’ opinions are widely dispersed.

     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

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...     

Shareholder Activism and Voluntary Disclosure Initiation: The Case of Political Spending

Demand for disclosures on environmental, social, and governance (ESG) issues has increased dramatically. Using corporate political spending disclosures as our setting, we conduct a detailed inquiry of 541 political spending‐related shareholder proposals from 2004 to 2012 to highlight the role of shareholder activism as a mechanism to motivate ESG disclosure. Unlike earlier studies, we examine both proposals that went to a vote and proposals that were withdrawn by the activist, allowing us to assess more comprehensively the success of shareholder activism. We find that 20 percent of firms targeted by disclosure proposals begin disclosing in the subsequent year, although implementation rates vary by proposal type—8 percent for proposals subject to a vote versus 56 percent for proposals withdrawn. The sponsor is also important: unions and public pension funds are less likely than other activists to target firms with agency problems and are less successful in having proposals withdrawn, and the implementations they obtain are viewed more negatively by the broader investor base. Our findings highlight shareholder proposals as one mechanism through which investors can successfully express their preferences for corporate disclosure policies. Given activists' long‐standing interest in environmental and social disclosure policies, we believe our findings generalize to a broader set of ESG disclosures.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.