Determinants of the relationship between government shutdowns and real stock returns
Abstract: PART I: The effects of government shutdowns on financial markets in the US are still unclear to this day, as they have not garnered enough attention from researchers. The aim of this thesis is to expand the current knowledge on these effects by analyzing how the real returns on the utilities market in the US are Granger caused by government shutdowns. The research results and their comparison to past research give an insight into how reliance on government funding affects the impact of government shutdowns on the industry. The research is carried out by applying residual bootstrap likelihood ratio (LR) tests on 24-month-long rolling windows, showing how the causality relationship develops through time. The dataset used consists of monthly data on the government shutdown measure developed by Baker et al. (2016), Dow Jones Utilities Average Index, and Consumer Price Index for All Urban Consumers. The research is carried out in-sample in the period of 1985:M1-2018:M12. The thesis is structured in the following way: 1) introduction, describing the focus of the thesis; 2) literature review, analyzing the available literature on government shutdowns and their effects on the country; 3) research model, describing the data and empirical model applied; 4) empirical results, showing the outcomes of the model and comparing them to past research; 5) limitations and implications for further research; and 6) conclusions, summarizing the outcome of the thesis. PART II: The topicality of government shutdowns has been growing significantly over the last few decades, as these events have become more frequent and longer. While there has been some research carried out on how government shutdowns affect the country, the current research on the relationship between government shutdowns and financial markets is relatively sparse, and therefore it is unclear whether government shutdowns have any significant effects on financial markets and, if so, what determines the magnitude of these effects. This paper focuses on analyzing the Granger causality effect that government shutdowns may have on real stock returns in the US and whether the size of the company has any impact on the magnitude of this effect. Residual bootstrap likelihood ratio tests are carried out on 24-month-long rolling windows which consist of data on the following three stock indexes, representing small-cap, mid-cap and large-cap companies, respectively: S&P SmallCap 600, S&P MidCap 400, and S&P 500. The Granger causality relationship is tested for each of the rolling windows filled with monthly data on government shutdown index developed by Baker et al. (2016) and real returns on its respective index. The research covers the period of the years 1985-2018 (except for S&P SmallCap 600, which covers the period of the years 1989-2018). This essay is divided into five parts: 1) introduction; 2) literature review; 3) research model; 4) results; and 5) conclusions.
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