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

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

Regulation & Governance, 2015

Governments and public bodies have been fostering the development of e‐Government services during the last decade, promoting more and better administrative services through digital channels. The impact of this process, however, has not been fully assessed. This article investigates the relative impact of two key factors on the diffusion of e‐Government services; the level of Internet penetration and investment by governments in more and better government services. The aim is to analyze across European countries the impact of e‐Government policies on their adoption, under different levels of Internet penetration, enabling an assessment of how promotion of e‐Government (through investment in more and better services, for example) can have the maximum impact on citizenship adoption. It reports analysis of a cross‐sectional dataset of European countries using a Bayesian linear model. Results show that when Internet users are scarce, policies to foster e‐Government adoption will have little ‐ although not negligible ‐ impact. But at a certain level of Internet penetration, focused e‐Government policies have a substantial impact on citizens’ adoption of the technology. The results also highlight the importance of investing in e‐Government in the appropriate moment, that is, when its impact can be greatest. The paper, then, addresses the factors that make eGovernment policy more effective. The Bayesian inference used allows the research to avoid artificial assumptions common in comparative politics research, to design more flexible models and to present the results in a more natural way.
Policy & Internet, 2012

Comparative Political Studies, 2011

Recent Publications

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. Extracting configurations of values mixing scores from experts and ignoramus using Bayesian modelling. Frontiers in Applied Mathematics and Statistics, 2019.

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. Measuring the impact of an organizational inclusion programme on absence among employees with disabilities: A quasi‐experimental design. International Labour Review, 2019.

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. The Power of EI Competencies Over Intelligence and Individual Performance: A Task-Dependent Model. Frontiers in Psychology, 2018.

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. Religious tides: The time‐variant effect of religion on morality policies. Regulation & Governance, 2018.

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. The Governance of Goal-Directed Networks and Network Tasks: An Empirical Analysis of European Regulatory Networks. Journal of Public Administration Research and Theory, 2017.

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. 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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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:


There is a pdf version of Using the ggmcmc package. Why ggmcmc? ggplot2, based on the grammar of graphics (Wilkinson et al. 2005), empowers R users by allowing them to flexibly crate graphics (Wickham 2009). Based on this idea, ggmcmc is aimed at bringing the design and implementation of ggplot2 to MCMC diagnostics, allowing Bayesian inference users to have better and more flexible visual diagnostic tools. ggplot2 is based on the idea that the input of any graphic is a data frame mapped to aesthetic attributes (colour, size) of geometric objects (points, lines).


L' és un guió de bash preparat per la terminal amb la finalitat d'accedir per línia de comandes al diccionari de l'Institut d'Estudis Catalans.



Courses and Seminars currently offered

  • Internet Governance (MS in Political Science, LMU Munich)
  • Measuring Governance (MS in Political Science, LMU Munich)
  • Analyzing Policy and Institutional Change (MS in Political Science, LMU Munich)
  • Politics of Regulation (MS in Political Science, LMU Munich)
  • “Science” in Political Science (BS in Political Science, LMU Munich)
  • Bayesian Modelling (Summer School in Survey Methodology, UPF)
  • Applied Hierarchical Bayesian Modelling and Measurement (Department of Comparative Politics, University of Bergen)