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As difficult as it might seem to define governance, it appears to be that much more difficult to measure it. Since the World Bank Institute launched the Worldwide Governance Indicators in the late 1990s, the governance indicators field has flourished and experienced significant advances in terms of methodology, data coverage and quality, and policy relevance. Other major initiatives have added to a momentum that propelled research on governance indicators seen in few other academic fields in the economic and social sciences. Given these developments and the prominence and policy relevance the field of governance indicator research has achieved, the time is ripe to take stock and ask what has been accomplished, what the shortcomings and potentials might be, and what steps present themselves as a way forward. This volume—the fifth edition in an annual series tackling different aspects of governance around the world—assesses what has been achieved, identifies strengths and weaknesses of current work, and points to issues that need to be tackled in order to advance the field, both in its academic importance as well as in its policy relevance. In short, the contributions to this volume explore the scope of existing governance indices and indicator frameworks, elaborate on current challenges in measuring and analysing governance, and consider how to overcome them.
The register-based census in Germany : Historical context and relevance for population research
(2016)
In 2011, Germany carried out its first census after a 20-year break. In light of the United Nations’ recommendations that countries initiate a population census at least every 10 years, the census was long overdue. Moreover, demographers had for some time been demanding a new enumeration that would enable them to place the calculation of demographic indicators on a reliable basis. With the 2011 census, Germany not only met the demand for a current population census, but also broke new ground by using a register-based approach. Unlike the Scandinavian countries, which have a long tradition of performing register-based data analyses, the linking of administrative data in Germany is restricted by the country’s legal framework. Thus, the 2011 census was an ambitious project. After contextualising the 2011 census historically, we discuss in this contribution the census’ relevance for generating central demographic data. Specifically, we compare the updated population estimates of the 1987 census to the results of the 2011 census in order to identify possible systematic sources of error that distort demographic indicators and analyses.
In this article, we investigate the impact of job displacement on women’s first-birth rates as well as the variation in this effect over the business cycle. We use mass layoffs to estimate the causal effects of involuntary job loss on fertility in the short and medium term, up to five years after displacement. Our analysis is based on rich administrative data from Germany, with an observation period spanning more than 20 years. We apply inverse probability weighting (IPW) to flexibly control for the observed differences between women who were and were not displaced. To account for the differences in the composition of the women who were displaced in a downturn and the women who were displaced in an upswing, we use a double weighting estimator. Results show that the extent to which job displacement has adverse effects on fertility depends on the business cycle. The first-birth rates were much lower for women who were displaced in an economic downturn than for those who lost a job in an economic upturn. This result cannot be explained by changes in the observed characteristics of the displaced women over the business cycle.
Nudges polarize!
(2016)
In a comprehensive empirical investigation (N = 71,405) we analyzed the development of legal expertise in a critical 1-year period of academic legal training in which advanced law students start practicing to solve complex cases. We were particularly interested in the functional form of the learning curve and inter-individual differences in learning. Performance increases monotonically with the number of practice exams following a slightly concave learning curve without any considerable kinks. Considering the performance development over time, however, the curve is not monotonic and shows intermediate drops in performance. We provide evidence which suggests that these drops are due to cyclic drops in motivation. There are about equally sized marginal effects of practicing law exams in general and practicing exams in the specific area of law. However, students with high (vs. low) initial performance profit more from practicing exams within a specific area of law whereas students with low initial performance profit more from practicing exams in general. The concave increase in performance with the number of practicing exams is mainly driven by individuals with low initial performance. Those with high initial performance mainly display a linear learning trend. We discuss the practical implications of these findings for academic legal training.
We run a large-scale natural field experiment to evaluate alternative strategies to enforce compliance with the law. The experiment varies the text of mailings sent to potential evaders of TV license fees. We find a strong effect of mailings, leading to a substantial increase in compliance. Among different mailings, a threat treatment which makes a high detection risk salient has a significant deterrent effect. Neither appealing to morals nor imparting information about others’ behavior enhances compliance on aggregate. However, the information condition has a weak positive effect in municipalities where evasion is believed to be common.
Nudges at the Dentist
(2014)
We implement a randomized field experiment to study the impact of reminders on dental health prevention. Patients who are due for a check-up receive no reminder, a neutral reminder postcard, or reminders including additional information on the benefits of prevention. Our results document a strong impact of reminders. Within one month after receiving a reminder, the fraction of patients who make a check-up appointment more than doubles. The effect declines slightly over time, but remains economically and statistically significant. Including additional information in the reminders does not increase response rates. In fact, the neutral reminder has the strongest impact for the overall population as well as for important subgroups of patients. Finally, we document that being exposed to reminders repeatedly does neither strengthen nor weaken their effectiveness.
We study the formation of advocacy groups and how they can impact policy outcomes by revealing information about voters׳ preferences to uninformed political candidates. We conduct a laboratory experiment based on a two-candidate spatial electoral competition setting where the policy preferences of voters are (initially) unknown and change over time. In the control treatment candidates learn about the preferred policy of the median voter through the voting outcome of elections. In the advocacy treatments, voters can organize themselves into advocacy groups in order to reveal their policy preferences. We find that voters often overcome the collective action problem of forming an advocacy group. In fact, we observe the formation of both informative advocacy groups, which convey new information, and uninformative advocacy groups, which do not. Overall, advocacy groups significantly speed up the convergence to the preferred policy of the median voter. However, advocacy does not lead to higher earnings as the gains from faster convergence are offset by the costs of group formation.
Economic performance is a key component of most election forecasts. When fitting models, however, most forecasters unwittingly assume that the actual state of the economy, a state best estimated by the multiple periodic revisions to official macroeconomic statistics, drives voter behavior. The difference in macroeconomic estimates between revised and original data vintages can be substantial, commonly over 100% (two-fold) for economic growth estimates, making the choice of which data release to use important for the predictive validity of a model. We systematically compare the predictions of four forecasting models for numerous US presidential elections using real-time and vintage data. We find that newer data are not better data for election forecasting: forecasting error increases with data revisions. This result suggests that voter perceptions of economic growth are influenced more by media reports about the economy, which are based on initial economic estimates, than by the actual state of the economy.