Policy uncertainty, economic distance, and macroeconomic variables in developing economies
| dc.contributor.author | Adjei, Abigail Naa Korkor | |
| dc.date.accessioned | 2023-10-10T09:46:50Z | |
| dc.date.available | 2023-10-10T09:46:50Z | |
| dc.date.issued | 2021 | |
| dc.description | A thesis submitted in fulfilment of the requirement for the degree Doctor of Philosophy to the Faculty of Commerce, Law and Management, Wits Business School, University of the Witwatersrand, Johannesburg, 2021 | |
| dc.description.abstract | Although economic policy uncertainty (EPU) is a less explored source of uncertainty that is related to economic policy, economic policy uncertainty in describing the state of an economy has assumed dominance in decision-making in countries and has remained relevant to investors, governments, and policy makers across the globe. This has become the standard because studies have proved that policy uncertainty has a significant effect on the overall economy and heightened EPU (especially during recessions) has the potential to harm economic activities. The literature review revealed evidence that EPU comoves with business cycles, that uncertainty influences the distance between economies, and that EPU spillover shocks from one economy to another have a significant impact on the recipient economy's economic activities. As yet, there has been scant systematic investigation of these possible interactions. The study of EPU is of major importance to emerging market economies (EMEs) because, although literature has proved the harmful effects of EPU on EMEs, the studies done is meager since majority of study on EPU have focused on developed countries. These implications of uncertainty on EMEs have made it very relevant to focus on the role uncertainty plays in EMEs. In order to make significant contribution to the role EPU plays in EMEs, this thesis focuses on addressing three main problems. To begin, the study examines whether EPU correlates with business cycles and, if so, whether EPU is the cause or effect of recessions across business cycles. The study makes an important contribution by finding answers to why business cycles fluctuate. This study deviates from traditional sources of fluctuations and focus on uncertainty as a potential cause or effect of business cycle fluctuations. We also propose new variables as measures of ii business cycles (GDP, CPI, SPX, import, export and broad money). The wavelet multiple correlation and wavelet multiple cross-correlation proposed by Fernandez-Macho (2012) is used to investigate the comovement between EPU ad business cycles. The analysis shows that business cycles commove with strong records of interdependence. The scale by scale analysis, on the other hand, has shown that the level of integration is strongest in the long-term. We further investigated the role EPU plays in the comovement of variables (gross domestic product (GDP), consumer price index (CPI), SPX (SPX), import, export and broad money) within each EME and discovered that positive correlation was generally recorded between EPU and CPI within each EME. Likewise, evidence of negative correlation for EPU was recorded between EPU and SPX across all EMEs. We also note that, although there is strong evidence of comovement between EPU and the macroeconomic variables, EPU has no lead/lag potential across all the time scales within the selected EMEs. To also clear all the inconsistencies of whether uncertainty is the cause or effect of fluctuations in the business cycle, the study adopts Diks and Panchenko (2005, 2006) nonparametric test. It was discovered that causality with respect to the economic indicators of business cycles is specific to each EMEs. We conclude that EPU is both a cause and effect of business cycles fluctuations in the selected EMEs except for India where business cycles cause EPU fluctuations. The second objective is to ascertain the relationship between EPU and distance in EMEs. The study focuses on the investigation of economic distance and geographical distance. This section makes two contributions to the study. First, we conduct a novel investigation on the relationship between economic distance and EPU. Second, we adopt a non-parametric geospatial analysis to investigate the spatial dependence between EMEs (with respect to their EPU measures). We first iii find an answer to the question, “can EPU influence economic distance in EMEs?”. The extent of similarities (or dissimilarities) of economic characteristics between units (or countries) is termed as economic. Despite evidence that uncertainty increases when the economic characteristics between countries are different, no study has investigated the relationship between economic distance and EPU although EPU has a greater significant impact on an economy than uncertainty in general. The dynamic linear regression method is adopted to investigate the relationship between EPU and economic distance. We discover that macroeconomic variables were largely statistically significant and have explanatory power to explain the economic distance between the EMEs as compared to the role EPU plays in explaining the economic distance between EMEs. We therefore find limited evidence of EPU’s effects on the economic distance between EMEs. We also discover that changes in the values of import, CPI and broad money in most EMEs are statistically relevant and significantly drive the changes in the values of economic distance between the selected EMEs. The second aspect of distance investigates the spatial autocorrelation between EMEs with respect to EPU. Tobler’s first law of geography that highlights that the nearer things are to each other, the more related they are than to distant things forms the foundation of this theoretical framework (Tobler, 1970). The Moran’s I (Moran, 1984) is used to investigate the presence of spatial autocorrelation. The results showed evidence of spatial autocorrelation across all the EMEs which support Tobler’s first law of geography. This implies that, the similarities and dissimilarities between the selected EMEs are significantly influenced by the distance between them. It was also observed that, country and geographical specific features (or characteristics) of each EME affect the outcome of the results. Thirdly, heterogeneity was recorded when the six EMEs were divided iv into sub regions. Finally, the study discovered that international policies (for example trade policies), terms of trade, spillover effects, monetary and fiscal policies are some of the factors that influence EPU spatial autocorrelation in EMEs. The study further investigates the spillover effects of EPU and macroeconomic variables in EMEs and measures the amount and direction of spillover from a country to other countries. This information is essential beacause previous studies have focused on developed (advanced) economies leaving little evidence of the effects of EPU spillover in EMEs. The study investigates the amount and direction of EPU spillovers between EMEs as well as the effect of EPU shocks on macroeconomic indicators (and vice versa). To investigate the network spillover effect and directional connectedness between EPU and related macroeconomic variables in EMEs and explore their time-frequency dynamics, this investigation will use Baruník and Křehlík’s (2018) methodology. The findings from this study shows evidence of spillover and causal spillover between EPU and macroeconomic variables within each EME. We discover that EPU does not dominate in the transition or receiving of spillover shocks in all the selected EMEs but rather, GDP and SPX were identified as the main transmitters of spillover shocks across all the selected EMEs. The time-varying total spillover index confirms arguments of volatilities of uncertainty in EMEs during the Great Recession that occurred during 2007-2009. Inter-country spillover analysis shows that Korea- EPU is the main transmitter of spillover shocks to the selected EMEs across all frequency bands. The study therefore makes significant contributions to the study. First, we find answers to why business cycles fluctuate. Second, we also propose new variables as measures of business cycles v (GDP, CPI, SPX, import, export and broad money). Third, we conduct a novel investigation on the relationship between economic distance and EPU. Forth, we adopt a non-parametric geospatial analysis to investigate the spatial dependence between EMEs (with respect to their EPU measures). Fifth, we investigate the severity of the amount and direction of EPU spillover received and contributed by one economy to another economy. The study offers a number of significant investment and policy recommendations arising from the findings in this thesis. The study offers a number of significant investment and policy recommendations arising from the findings in this thesis. Policymakers should establish a robust and precise implementation framework that ensures transparency and credibility to help minimise the wait-and-see (delay) approach of investors and agents as a result of the uncertainty of future happenings. Decisions made by policymakers should be communicated openly and promptly. Due to extensive understanding of the key transmitters and recipients of shocks at various frequencies, investors can intelligently plan their portfolio diversification methods. In the event of weak interactions, investors should diversify their portfolio to maximise their return on investment. With the detailed information about the short-, medium-, and long-term net spillover received from and contributed by the EMEs, policy makers are well equipped to efficiently forecast global and country specific uncertainty fluctuations, make well informed predictions and implement policies that can significantly reduce uncertainty in the economy. Based on the results on the causal relationship between EPU and business cycles, policy makers can now implement and amend predictable fiscal and monetary policies that will prevent or reduce the occurrence of uncertainty and business cycle fluctuations. This will make investors feel more secure to invest in the economy. Policy makers vi and regulators are advised not to generalise policy formulations, amendments and regulations but should rather be focused on each EME. | |
| dc.description.librarian | TL (2023) | |
| dc.description.sponsorship | Bradlow Foundation PhD Scholarship | |
| dc.faculty | Faculty of Commerce, Law and Management | |
| dc.identifier.uri | https://hdl.handle.net/10539/36636 | |
| dc.language.iso | en | |
| dc.phd.title | PhD | |
| dc.rights.holder | University of the Witswatersrand, Johannesburg | |
| dc.school | Wits Business School | |
| dc.subject | Economic policy uncertainty | |
| dc.subject | Emerging market economies | |
| dc.subject | Business cycles | |
| dc.subject | Comovement | |
| dc.subject | Economic distance | |
| dc.subject | UCTD | |
| dc.subject.other | SDG-8: Decent work and economic growth | |
| dc.title | Policy uncertainty, economic distance, and macroeconomic variables in developing economies | |
| dc.type | Thesis |