Selected Publications

State structures have experienced significant transformation with the spread of globalization. This paper examines how to measure one major change that has occurred in recent decades: the worldwide proliferation of public agencies with regulatory tasks. It remains unclear how their configurations vary across countries and sectors, and what can be learned from these variations. To better identify these agencies worldwide, we introduce a new dataset on the institutional features of 799 agencies in 115 countries and 17 policy sectors. The dataset contains variables from their institutional profiles, covering a broad range of formal characteristics. To examine the diverse faces the regulatory state has adopted along its globalization path in depth, our variables are grouped into four blocs: regulatory responsibilities, managerial autonomy, political independence, and public accountability. As such, we depart from the view that a single dimension does capture the actual diversity of institutional forms regulatory agencies may exhibit. We also use factor and cluster analyses to assess their various forms, and suggest a typology of agency institutional models to facilitate more precise studies on the regulatory state. Results confirm that the regulatory state shows greater variety than usually expected.
Regulation & Governance, 2018

The question of whether or not religion accounts for variance in the governance of moral issues, between and within countries over time, has long been debated but never conclusively answered. A novel data set encompassing innovative measurements of state regulation of ‘life-and-death’ issues and of the religious stratification of society enables us to answer why previous studies reached contradictory results. The time-series cross-sectional analysis of 26 countries over 50 years reveals that dominant religious denominations in society indeed influence state governance approaches regarding the issues of abortion and euthanasia. This denominational effect is shown to be contingent on the religiosity of a country’s population, but independent from the formal state–church relationship. Lastly, it is shown that the religious effect has an inverse U-shaped relationship with time, exposing the timeframe of analysis as decisive for inferences drawn in the study of morality policy.
Governance, 2017

This paper asks whether strong bureaucracies can effectively constrain the continuously growing stock of rules in modern democracies through organizational coordination and learning. To answer this question, the paper analyzes the growth of rule stocks in the areas of environmental policy and social policy in 23 OECD countries over the period between 1976 and 2005. To do so, it develops a new measure of rule growth based on the content of laws and regulations rather than their length. The analysis highlights that effective bureaucracies are indeed better able to contain rule growth in these areas than weak bureaucracies. Since rules have to be implemented, countries suffering from bureaucratic capacity and quality constraints thus appear to be stuck in an implementation deficit trap. Appropriate implementation is not only inherently more challenging for countries with weak public administrations, but the body of rules to be implemented also tends to grow quicker in these countries.
Policy Sciences, 2017

ggmcmc is an R package for analyzing Markov chain Monte Carlo simulations from Bayesian inference. By using a well known example of hierarchical/multilevel modeling, the article reviews the potential uses and options of the package, ranging from classical convergence tests to caterpillar plots or posterior predictive checks.
Journal of Statistical Software, 2016

The regulatory regionalism approach has increasingly claimed that a new mode of regional governance is emerging globally. Regional policy regimes, developed in broad social and economic territorial areas, affect the internal transformation of the state. The authors plan to provide comprehensive empirical evidence about the emergence of worldwide regulatory regionalism by identifying how regulatory agencies have diffused very successfully within the regional level in recent decades. The paper aims to identify, using an original methodological design, the ways in which such diffusion of agencies occurred, as this may have theoretical relevance for the study of regulatory regionalism. The authors’ hypothesis suggests that transnational political interactions in each regional cluster triggered agency diffusion, contributing to the development of the regulatory state within the countries of each region. To test this hypothesis, the authors employed a data set of regulatory agencies including the OECD (Organisation for Economic Co-operation and Development), and most Asian and Latin American countries (+59) from 1950 to 2007, for 15 sectors related to finance, risks, utility and competition. Bayesian data analysis was used to estimate the parameters of interest.
Contemporary Politics, 2016

Comparative Political Studies, 2011

Recent Publications

. A matter of timing: The religious factor and morality policies. Governance, 2017.

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. ggmcmc: Analysis of MCMC Samples and Bayesian Inference. Journal of Statistical Software, 2016.

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. The global diffusion of regulatory agencies: channels of transfer and stages of diffusion. Comparative Political Studies, 2011.

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Introduction This tutorial shows how to process the dataset of institutional characteristics of regulatory agencies in R. It presents the dataset presented at the journal article entitled “Agency proliferation and the globalization of the regulatory state: Introducing a data set on the institutional features of regulatory agencies”, by Jacint Jordana, Xavier Fernández-i-Marín and Andrea C. Bianculli, published at Regulation & Governance (December 2018). The necessary packages in R to follow the instructions are the following:

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(Check the forecast for the Bavarian state elections 2018.) Evaluation The Bavarian state elections evaluated here were in October 14th, 2018, with the following results: Party Election CSU 37.2 SPD 9.7 FW 11.6 Grüne 17.5 Others 5.5 FDP 5.1 Linke 3.2 AfD 10.2 When overlapped with the forecasts, the result is shown in the following Figure: Figure 1: Predicted support for every party as of the last day, with uncertainty bands at 90 and 95 percent.

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(Update: check also the evaluation of the forecasts.) Introduction The forecast of an election can be understood as the outcome of o measurement problem. We need to measure the day-to-day latent party support and make a prediction for a specific day (the election day). How is the party support known? We can approach to the support that a party is going to receive by looking at polls. Polls contain fuzzy information about the support that a party receives, measured for a very concrete time period and with a lot of noise.

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