Computing the impact of central clearing on systemic risk

The paper uses a graph model to examine the effects of financial market regulations on systemic risk. Focusing on central clearing, we model the financial system as a multigraph of trade and risk relations among banks. We then study the impact of central clearing by a priori estimates in the model, stylized case studies, and a simulation case study. These case studies identify the drivers of regulatory policies on risk reduction at the firm and systemic levels. The analysis shows that the effect of central clearing on systemic risk is ambiguous, with potential positive and negative outcomes, depending on the credit quality of the clearing house, netting benefits and losses, and concentration risks. These computational findings align with empirical studies, yet do not require intensive collection of proprietary data. In addition, our approach enables us to disentangle various competing effects. The approach thus provides policymakers and market practitioners with tools to study the impact of a regulation at each level, enabling decision-makers to anticipate and evaluate the potential impact of regulatory interventions in various scenarios before their implementation

Democratic Transitions

Przeworski et al. (2000) challenge the key hypothesis in modernization theory: political regimes do not transition to democracy as per capita incomes rise, they argue. Rather, democratic transitions occur randomly, but once there, countries with higher levels of GDP per capita remain democratic. We retest the modernization hypothesis using new data, new techniques, and a three-way rather than dichotomous classification of regimes. Contrary to Przeworski et al. (2000) we find that the modernization hypothesis stands up well. We also find that partial democracies emerge as among the most important and least understood regime types.African and African American StudiesGovernmen

Alternative Models of Dynamics in Binary Time-Series-Cross-Section Models: The Example of State Failure

This paper investigates a variety of dynamic probit models for time-series-cross-section data in the context of explaining state failure. It shows that ordinary probit, which ignores dynamics, is misleading. Alternatives that seem to produce sensible results are the transition model and a model which includes a lagged latent dependent variable. It is argued that the use of a lagged latent variable is often superior to the use of a lagged realized dependent variable. It is also shown that the latter is a special case of the transition model. The relationship between the transition model and event history methods is also considered: the transition model estimates an event history model for both values of the dependent variable, yielding estimates that are identical to those produced by the two event history models. Furthermore, one can incorporate the insights gleaned from the event history models into the transition analysis, so that researchers do not have to assume duration independence. The conclusion notes that investigations of the various models have been limited to data sets which contain long sequences of zeros; models may perform differently in data sets with shorter bursts of zeros and ones

Delegation, Comitology, and the Separation of Powers in the European Union

In 1988, the European Community (EC) and the People s Republic ofChina signed an Agreement on Trade in Textile Products, which setquantitative restrictions on Chinese imports into member countries. In1996, the European Commission (Commission), which oversees and monitorsthe implementation of the agreement, found that the Chinese authoritieshad issued export licenses for textile products that exceeded the 1995quantitative limits agreed upon between the EU and China. As a result,the products sent from China remained blocked on entry at Europeancustoms ports. The Chinese authorities admitted that an error hadoccurred, mostly due to a breakdown of the computer system. But othercomplicating factors, especially the falsi cation of export licenses,also hindered the Chinese administration s ability to monitor thegranting of export and import authorizations. Under the circumstances,the Chinese authorities requested the application of exible measuresby admitting the 1995 imports and reducing the 1996 quotas by an equalamount.

Data Science and Political Economy: Application to Financial Regulatory Structure

The development of computational data science techniques in natural language processing and machine learning algorithms to analyze large and complex textual information opens new avenues for studying the interaction between economics and politics. We apply these techniques to analyze the design of financial regulatory structure in the United States since 1950. The analysis focuses on the delegation of discretionary authority to regulatory agencies in promulgating, implementing, and enforcing financial sector laws and overseeing compliance with them. Combining traditional studies with the new machine learning approaches enables us to go beyond the limitations of both methods and offer a more precise interpretation of the determinants of financial regulatory structure