This research aims to investigate the nuanced association between surges in capital flows and credit booms, considering both total capital inflows and financial inflows in both gross and net dimensions. Employing four distinct metrics to quantify surges and credit booms, the analysis encompasses a dataset consisting of 42 emerging economies, inclusive of five European Periphery nations, and spans the years 1980 to 2017.Beyond scrutinizing each type of surge leading to credit booms within two-year periods, the study incorporates an analysis of the proportions of surges followed by credit booms and booms preceded by surges.Acknowledging the existing disparities in identifying both capital flow surges and credit booms, this paper conducts robustness testing with diverse measures. A particular emphasis is placed on the frequency analysis to scrutinize the nuanced relationship between surges and booms. For future inquiries, a comprehensive exploration of the factors influencing surges culminating in credit booms will be pursued through a linear panel data model, incorporating relevant control variables. Regression analyses of binary outcomes will be employed to investigate the impact of surges as an independent variable on credit booms. Noteworthy variations emerge in the number of surges identified by different measures in existing literature, underscoring that while surges do culminate in credit booms, this is not universally applicable. The outcomes are contingent on the metrics employed for surge identification, time-lagged periods, threshold measures, and the classification of inflow types. I found that the proportion of all credit boom measurements preceded by all surge measurement is higher than the proportion of surges followed by credit boom. While empirical evidence points to a positive correlation between surges and subsequent credit booms, it is crucial to highlight that this relationship is notably weaker than asserted in a majority of existing literature. These findings align with the fundamental conclusions drawn by Amri et al. (2016), underscoring the relatively feeble association between capital flow surges and ensuing credit booms. This paper found that many surges do not end in credit booms.
","abstract_html":"<p>This research aims to investigate the nuanced association between surges in capital flows and credit booms, considering both total capital inflows and financial inflows in both gross and net dimensions. Employing four distinct metrics to quantify surges and credit booms, the analysis encompasses a dataset consisting of 42 emerging economies, inclusive of five European Periphery nations, and spans the years 1980 to 2017.Beyond scrutinizing each type of surge leading to credit booms within two-year periods, the study incorporates an analysis of the proportions of surges followed by credit booms and booms preceded by surges.Acknowledging the existing disparities in identifying both capital flow surges and credit booms, this paper conducts robustness testing with diverse measures. A particular emphasis is placed on the frequency analysis to scrutinize the nuanced relationship between surges and booms. For future inquiries, a comprehensive exploration of the factors influencing surges culminating in credit booms will be pursued through a linear panel data model, incorporating relevant control variables. Regression analyses of binary outcomes will be employed to investigate the impact of surges as an independent variable on credit booms. Noteworthy variations emerge in the number of surges identified by different measures in existing literature, underscoring that while surges do culminate in credit booms, this is not universally applicable. The outcomes are contingent on the metrics employed for surge identification, time-lagged periods, threshold measures, and the classification of inflow types. I found that the proportion of all credit boom measurements preceded by all surge measurement is higher than the proportion of surges followed by credit boom. While empirical evidence points to a positive correlation between surges and subsequent credit booms, it is crucial to highlight that this relationship is notably weaker than asserted in a majority of existing literature. These findings align with the fundamental conclusions drawn by Amri et al. (2016), underscoring the relatively feeble association between capital flow surges and ensuing credit booms. This paper found that many surges do not end in credit booms.</p>","abstract_has_math":false,"creators":["Thanakornmonkkonchai, Kittiyaratch"],"institution":null,"degree_name":"Economics, PhD","degree_level":"Restricted to Claremont Colleges Dissertation","degree_discipline":"School of Social Science, Politics, and Evaluation","degree_department":null,"school":null,"contributors":["Graham Bird","Levan Efremidze"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-01T08:00:00Z","date_published":"2023-01-01T08:00:00Z","updated_at":"2026-07-24T01:41:01Z","subjects":["Capital Surges","Credit booms","International Monetary and Finance","Economics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarship.claremont.edu/cgu_etd/751","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Graham Bird","Levan Efremidze"]},{"key":"dc:creator","label":"Author","values":["Thanakornmonkkonchai, Kittiyaratch"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2024-03-04T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["School of Social Science, Politics, and Evaluation"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Restricted to Claremont Colleges Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Economics, PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Capital Surges","Credit booms","International Monetary and Finance","Economics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarship.claremont.edu/cgu_etd/751"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research aims to investigate the nuanced association between surges in capital flows and credit booms, considering both total capital inflows and financial inflows in both gross and net dimensions. Employing four distinct metrics to quantify surges and credit booms, the analysis encompasses a dataset consisting of 42 emerging economies, inclusive of five European Periphery nations, and spans the years 1980 to 2017.Beyond scrutinizing each type of surge leading to credit booms within two-year periods, the study incorporates an analysis of the proportions of surges followed by credit booms and booms preceded by surges.Acknowledging the existing disparities in identifying both capital flow surges and credit booms, this paper conducts robustness testing with diverse measures. A particular emphasis is placed on the frequency analysis to scrutinize the nuanced relationship between surges and booms. For future inquiries, a comprehensive exploration of the factors influencing surges culminating in credit booms will be pursued through a linear panel data model, incorporating relevant control variables. Regression analyses of binary outcomes will be employed to investigate the impact of surges as an independent variable on credit booms. Noteworthy variations emerge in the number of surges identified by different measures in existing literature, underscoring that while surges do culminate in credit booms, this is not universally applicable. The outcomes are contingent on the metrics employed for surge identification, time-lagged periods, threshold measures, and the classification of inflow types. I found that the proportion of all credit boom measurements preceded by all surge measurement is higher than the proportion of surges followed by credit boom. While empirical evidence points to a positive correlation between surges and subsequent credit booms, it is crucial to highlight that this relationship is notably weaker than asserted in a majority of existing literature. These findings align with the fundamental conclusions drawn by Amri et al. (2016), underscoring the relatively feeble association between capital flow surges and ensuing credit booms. This paper found that many surges do not end in credit booms.
"]},{"key":"dc:title","label":"Title","values":["The Relationship between Surges in Capital Flows and Booms in Credits"]}]}],"canonical_facts":{"dc:contributor":["Graham Bird","Levan Efremidze"],"dc:creator":["Thanakornmonkkonchai, Kittiyaratch"],"dc:date.available":["2024-03-04T08:00:00Z"],"dc:description.abstract":["This research aims to investigate the nuanced association between surges in capital flows and credit booms, considering both total capital inflows and financial inflows in both gross and net dimensions. Employing four distinct metrics to quantify surges and credit booms, the analysis encompasses a dataset consisting of 42 emerging economies, inclusive of five European Periphery nations, and spans the years 1980 to 2017.Beyond scrutinizing each type of surge leading to credit booms within two-year periods, the study incorporates an analysis of the proportions of surges followed by credit booms and booms preceded by surges.Acknowledging the existing disparities in identifying both capital flow surges and credit booms, this paper conducts robustness testing with diverse measures. A particular emphasis is placed on the frequency analysis to scrutinize the nuanced relationship between surges and booms. For future inquiries, a comprehensive exploration of the factors influencing surges culminating in credit booms will be pursued through a linear panel data model, incorporating relevant control variables. Regression analyses of binary outcomes will be employed to investigate the impact of surges as an independent variable on credit booms. Noteworthy variations emerge in the number of surges identified by different measures in existing literature, underscoring that while surges do culminate in credit booms, this is not universally applicable. The outcomes are contingent on the metrics employed for surge identification, time-lagged periods, threshold measures, and the classification of inflow types. I found that the proportion of all credit boom measurements preceded by all surge measurement is higher than the proportion of surges followed by credit boom. While empirical evidence points to a positive correlation between surges and subsequent credit booms, it is crucial to highlight that this relationship is notably weaker than asserted in a majority of existing literature. These findings align with the fundamental conclusions drawn by Amri et al. (2016), underscoring the relatively feeble association between capital flow surges and ensuing credit booms. This paper found that many surges do not end in credit booms.
"],"dc:identifier":["https://scholarship.claremont.edu/cgu_etd/751"],"dc:subject":["Capital Surges","Credit booms","International Monetary and Finance","Economics"],"dc:title":["The Relationship between Surges in Capital Flows and Booms in Credits"],"thesis:degree_discipline":["School of Social Science, Politics, and Evaluation"],"thesis:degree_level":["Restricted to Claremont Colleges Dissertation"],"thesis:degree_name":["Economics, PhD"]},"updated_at":"2026-07-24T01:41:01Z"}