Suchergebnisse

Political networks are an important feature of the political and economic landscape of countries. Despite their ubiquity and significance, information on such networks has proven hard to collect due to a pervasive lack of transparency. However, with the advent of big data and artificial intelligence, major financial services institutions are now actively collating publicly available information on politically exposed persons and their networks. In this study, we use one such data set to show how network characteristics vary across political systems. We provide results from more than 150 countries and show how the format of the network tends to reflect the extent of democratisation of each country. We also outline further avenues for research using such data.

Business and politician interaction is pervasive but has mostly been analysed with a binary approach. Yet the network dimensions of such connections are ubiquitous. We use a unique dataset for seven economies that documents politically exposed persons (PEPs) and their links to companies, political parties and other individuals. With this dataset, we can identify networks of connections, including their scale and composition. We find that all country networks are integrated having a Big Island. They also tend to be marked by small-world properties of high clustering and short path length. Matching our data to firm level information, we examine the association between being connected and firm-level attributes. The originality of our analysis is to identify how location in a network, including extent of ties and centrality, are correlated with firm scale and performance. In a binary approach such network characteristics are omitted and the scale and economic impact of politically connected business may be significantly mis/under-estimated. By comparing results of the binary approach with our network approach, we can also assess the biases that result from ignoring network attributes.

Business and politicians' interaction is pervasive but has mostly been analyzed with a binary approach, i.e. either a firm is connected to a politician or not. Yet the network dimensions of such connections are ubiquitous. This paper uses use a unique data set for seven economies that documents politically exposed persons and their links to companies, political parties, and other individuals. The data set is used to identify networks of connections, including their scale and composition. The analysis finds that all country networks are integrated having a Big Island. They also tend to be marked by small-world properties of high clustering and short path length. Matching the data to firm-level information, the paper examines the association between being connected and firm-level attributes. The originality of the analysis is to identify how location in a network, including the extent of ties and centrality, is correlated with firm scale and performance. In a binary approach, such network characteristics are omitted and the scale and economic impact of politically connected business may be significantly mis/under-estimated. By comparing the results of the binary approach with the network approach, the paper also assesses the biases that result from ignoring network attributes.

This paper investigates impacts, mechanisms and selection effects of prenatal exposure to multiple shocks, by exploiting the unique natural experiment of the Dutch Hunger Winter. At the end of World War II, a famine occurred abruptly in the Western Netherlands (November 1944 - May 1945), pushing the previously and subsequently well-nourished Dutch population to the brink of starvation. We link high-quality military recruits data with objective health measurements for the cohorts born in the years surrounding WWII with newly digitised historical records on calories and nutrient composition of the war rations, daily temperature, and warfare deaths. Using difference-in-differences and triple differences research designs, we show that the cohorts exposed to the Dutch Hunger Winter since early gestation have a higher Body Mass Index and an increased probability of being overweight at age 18, and that this effect is partly accounted for by warfare exposure and a reduction in energy-adjusted protein intake. Moreover, we account for selective mortality using a copula-based approach and newly-digitised data on survival rates, and find evidence of both selection and scarring effects. These results emphasise the complexity of the mechanisms at play in studying the consequences of early conditions.

This paper investigates impacts, mechanisms and selection effects of prenatal exposure to multiple shocks, by exploiting the unique natural experiment of the Dutch Hunger Winter. At the end of World War II, a famine occurred abruptly in the Western Netherlands (November 1944 - May 1945), pushing the previously and subsequently well-nourished Dutch population to the brink of starvation. We link high-quality military recruits data with objective health measurements for the cohorts born in the years surrounding WWII with newly digitised historical records on calories and nutrient composition of the war rations, daily temperature, and warfare deaths. Using difference-in-differences and triple differences research designs, we show that the cohorts exposed to the Dutch Hunger Winter since early gestation have a higher Body Mass Index and an increased probability of being overweight at age 18, and that this effect is partly accounted for by warfare exposure and a reduction in energy-adjusted protein intake. Moreover, we account for selective mortality using a copula-based approach and newly-digitised data on survival rates, and find evidence of both selection and scarring effects. These results emphasise the complexity of the mechanisms at play in studying the consequences of early conditions.