In this paper we explore the variety of monetary policy transmission channels in an agent-based macroeconomic model. We identify eight transmission channels and present a model based on [Caiani et al., J. Econ. Dyn. Contr. 69 (2016) 375–480], extended with an interbank market. We then analyze model simulation results of interest rate shocks in terms of GDP and inflation for four of the transmission channels. We find these effects to be small, in line with the view that monetary policy is a weak tool to control inflation.

How effective are 'lockdown' measures and other policy interventions to curb the spread of Covid-19 in emerging market cities that are characterized by large heterogeneity and high levels of informality? The most commonly used models to predict the spread of Covid-19 are SEIR models which lack the spatial resolution necessary to answer this question. We develop an agent-based model of social interactions in which the distribution of agents across wards, as well as their travel and interactions are calibrated to real data for Cape Town, South Africa. We characterize the elasticity of various policy interventions including increased likelihood to self-isolate, travel restrictions, assembly bans, and behavioural interventions like washing hands or wearing masks. Even in an informal setting, where agents' ability to self-isolate is compromised, a lockdown remains an effective intervention. In our model, the lockdown enacted in South Africa reduced expected fatalities in Cape Town by 26% and the expected demand for intensive care beds by 46%. However, our best calibration predicts a substantially higher case load, demand for ICU beds, and expected number of deaths than the current best estimate published for Cape Town.

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W hile this dissertation presents my research findings over the last four years, it was not written in isolation. In this section, I would like to acknowledge some of the most important people on which I relied to make this work possible.First and foremost, I would like to thank Dirk Bezemer, my primary supervisor. The journey that led me towards this PhD started on Wednesday the 18 th of 2012, when I sent him an e-mail asking if he would be willing to discuss with me how it could be possible that banks create money, a question that many of my Finance professors at the time could not answer. His answer was typical of his scientific ethos. Dirk deeply appreciates curiosity, but only if it comes with a willingness to 'do the work,' meaning that someone who sends a question to others has first done research on his/ her own. In his e-mail, Dirk briefly explained how banks created money and sent me some links for further reading. He emphasized that I should read those first before scheduling a meeting. It so happened that, I had just spent the entire Christmas holiday reading papers about the subject. After a brief e-mail back and forth, this became clear to him and he invited me for a meeting. This led to many subsequent meetings, a student assistant position, and eventually a YouTube film production called 'Debt: the good, the bad, and the ugly.' It also led him to endorse me for a PhD level Winter school in Agent-Based Modelling (ABM) at the University of Limerick. Finally, after a brief stint as an on-line course coordinator at Leiden University, he called over the phone me and said: "Joeri.. I might have a PhD position in agent-based modelling and I want you to apply." I realized that I was extremely lucky because I was, on paper, not the right candidate for a PhD position. My university grades had been average. I had not Pahl and Daan Freeman. Both, Daan and Stefan have helped me to keep my spirit high during the stressful last years of the PhD. Along with