Relevant bibliographies by topics / Personality (five factor model)

Academic literature on the topic 'Personality (five factor model)'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Personality (five factor model)"

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Jones, Celeste. "Five Factor Model: Insights into a College Population." Current Research in Psychology and Behavioral Science (CRPBS) 3, no. 6 (September 1, 2022): 1–6. http://dx.doi.org/10.54026/crpbs/1062.

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College is a time noted for identity development, personal challenges and growth all within a social context where students interact with people across the personality continuum. The five-factor model of personality is a theoretically and psychometrically robust personality model that can provide insight into the 1st year college population. We explored the personality profile and norms for this college population, including the relationship between personality factors and classic character virtues that were a part of their first-year college curriculum experience and the relationship between personality factors and selection of college major. Results showed the first-year students had higher scores on agreeableness and conscientiousness than the other personality factors. The analysis of character virtues and personality factors showed relationships between agreeableness with the virtues of empathy, justice and humility. The personality factor of openness correlated with creativity and curiosity, Neuroticism with temperance, and conscientiousness with curiosity. Exploration of the relationship between personality and college majors showed that students majoring in theology and business were lower in agreeableness than students in kinesiology, nursing, psychology, education or social work. Students in the school of design and psychology had relatively lower scores in neuroticism than did students in the natural sciences, engineering, business or nursing. These results suggest that the five factor personality assessment may provide helpful insights to students and faculty as they navigate their first year of college.
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Costa, Paul T., and Robert R. McCrae. "Personality Disorders and The Five-Factor Model of Personality." Journal of Personality Disorders 4, no. 4 (December 1990): 362–71. http://dx.doi.org/10.1521/pedi.1990.4.4.362.

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Widiger, Thomas A., and Jennifer Ruth Lowe. "Five-Factor Model Assessment of Personality Disorder." Journal of Personality Assessment 89, no. 1 (September 2007): 16–29. http://dx.doi.org/10.1080/00223890701356953.

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Miller, Joshua D., Paul A. Pilkonis, and Jennifer Q. Morse. "Five-Factor Model Prototypes for Personality Disorders." Assessment 11, no. 2 (June 2004): 127–38. http://dx.doi.org/10.1177/1073191104264962.

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Boudreaux, Michael J. "Personality-related problems and the five-factor model of personality." Personality Disorders: Theory, Research, and Treatment 7, no. 4 (October 2016): 372–83. http://dx.doi.org/10.1037/per0000185.

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Zuroff, David C. "Depressive Personality Styles and the Five-Factor Model of Personality." Journal of Personality Assessment 63, no. 3 (December 1994): 453–72. http://dx.doi.org/10.1207/s15327752jpa6303_5.

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Montag, Itzhak, and Joseph Levin. "The five‐factor personality model in applied settings." European Journal of Personality 8, no. 1 (March 1994): 1–11. http://dx.doi.org/10.1002/per.2410080102.

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Two studies of the Revised NEO‐Personality Inventory (NEO‐PI‐R) conducted on two different applicant samples (one consisting of 539 female subjects and the other consisting of 396 male subjects) are reported. Factor analysis of the female sample yielded a five‐factor solution, highly congruent with the factors presented by Costa, McCrae and Dye (1991). Results of the male data were less clear‐cut, yielding four to five factors which were moderately congruent with the American data. The combined male and female sample showed again high congruence coefficients. Various minor deviations in the location of the facet variables are discussed.
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Ramanaiah, Nerella V., Fred R. J. Detwiler, and Anupama Byravan. "Life Satisfaction and the Five-Factor Model of Personality." Psychological Reports 80, no. 3_suppl (June 1997): 1208–10. http://dx.doi.org/10.2466/pr0.1997.80.3c.1208.

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The hypothesis that happy and unhappy people have different personality profiles based on five personality factors (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness) was tested using 245 undergraduates (111 men and 134 women) who completed the Satisfaction with Life Scale and the NEO Personality Inventory. Analysis indicated that High and Low Satisfaction groups had significantly different personality profiles, supporting the hypothesis.
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Sharpe, J. Patrick, and Nerella V. Ramanaiah. "Materialism and the Five-Factor Model of Personality." Psychological Reports 85, no. 1 (August 1999): 327–30. http://dx.doi.org/10.2466/pr0.1999.85.1.327.

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The hypothesis that High and Low Materialism groups have different personality profiles was tested with 280 introductory psychology students (135 men and 145 women) who completed the Belk Materialism Scale and the NEO Five-Factor Inventory for partial course credit. Results of discriminant function analysis supported the hypothesis, indicating that groups High and Low in Materialism had significantly different personality profiles and that the standard discriminant function coefficients were substantial (>.30): for Neuroticism −.59, Agreeableness .53, and Openness .32.
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Pareke, Fahrudin JS, and Rina Suthia Hayu. "Empirical Investigation of Five-Factor Model of Personality." AFEBI Management and Business Review 1, no. 1 (June 14, 2016): 29. http://dx.doi.org/10.47312/ambr.v1i1.28.

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<p>The concept of Five-Factor Model (FFM) of Personality describes the basic dimension of human behavior, thinking, and emotions that related to the job. The FFM currently getting popular and reach more attention to from the scholars and practitioners as well, particularly in the area of human resource management. Therefore, the main goal of current research is to compile and to test the dimensions of FFM and its measure empirically. Eighty-four self report measures distributed to the 238 employees who work both for public and private organizations at the Northern Sumatera Island, Indonesia. The respondents are currently completing their graduate programs at the University of Bengkulu. Two-hundred-and-eighteen questionnaires completed and returned by respondents, and analyzed using Factor Analysis with Varimax Approach to extract them in to the several components. Based on the analyses, research confirmed the 5 dimensions for FFM, which is conscientiousness (18 items), extraversion-introversion (18 items), agreeableness (12 items), openness to experience (14 items), and emotional stability (12 items). The result strictly recommended that the use of FFP as a means of Human Resource Practices such as selection, promotion, training, and the like.</p><p><br />Keywords: Agreeableness, Conscientiousness, Emotional Stability, Extraversion, Openness to Experiences, Personality</p>
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Dissertations / Theses on the topic "Personality (five factor model)"

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Knap, Malgorzata A. "The Five-Factor Model of personality and psychopathy." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0002/NQ38312.pdf.

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Crego, Cristina. "BIPOLARITY AND THE FIVE FACTOR MODEL OF PERSONALITY DISORDER." UKnowledge, 2018. https://uknowledge.uky.edu/psychology_etds/143.

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The predominant model of general personality structure is arguably the Five Factor Model (FFM), consisting of the five broad domains of neuroticism, extraversion, openness, agreeableness, and conscientiousness. The FFM of personality disorder (FFMPD) has proposed maladaptive variants at both poles of the FFM. The purpose of the current study was to identify a subset of FFMPD scales, utilizing factor analysis, that illustrate, and provide a potential measure of, the bipolarity present in the FFMPD. All of the FFMPD scales were administered to 443 community participants recruited from Amazon Mechanical Turk. Bipolarity was evident in a series of factor analyses of subsets of FFMPD scales, with the exception of openness. The current study also demonstrated that the presence of bipolarity is impaired by a number of concerns, including the presence of non-diametric scales, bloated specific factors, general factor of personality disorder, and occupation of interstitial space.
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Crossman, Edward W. "Gambling behavior and the five factor model of personality." access full-text online access from Digital Dissertation Consortium, 2007. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?1443743.

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Veltri, Carlo O. C. "Assessing Compulsivity with the Personality Psychopathology Five and the Five Factor Model." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1350082837.

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Edmundson, Maryanne. "A FIVE-FACTOR MEASURE OF SCHIZOTYPAL PERSONALITY DISORDER." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/57.

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The current study provides convergent, discriminant, and incremental validity data for a measure of schizotypia from the perspective of the Five-Factor Model (FFM) of general personality structure. Nine schizotypia facet scales were constructed as maladaptive variants of respective facets of the FFM (e.g., Aberrant Ideas as a maladaptive variant of FFM Openness to Ideas). On the basis of data from 143 undergraduates the convergent validity of these nine facet scales was tested with respect to 11 established measures of schizotypia and the respective facets of the FFM. Discriminant validity was tested with respect to other personality disorders and facets from other FFM domains. Incremental validity was tested with respect to the ability of the FFM schizotypia facet scales to account for variance in two established measures of schizotypia, after variance accounted for by respective FFM facets and other established measures of schizotypia were first removed. The findings support the validity of these new facet scales as measures of schizotypia and as maladaptive variants of the FFM.
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Gore, Whitney L. "The DSM-5 Dimensional Trait Model and the Five Factor Model." UKnowledge, 2013. http://uknowledge.uky.edu/psychology_etds/12.

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The current thesis tests empirically the relationship of the dimensional trait model proposed for the fifth edition of the American Psychiatric Association’s (APA) Diagnostic and Statistical Manual of Mental Disorders with five-factor models (FFM) of personality disorder (PD). The DSM-5 Personality and Personality Disorders Work Group proposes to diagnose the disorders largely in terms of a 25 trait dimensional model organized within five broad domains (i.e., negative affectivity, detachment, antagonism, disinhibition, and psychoticism). Consistent with the authors of DSM-5, it was predicted that negative affectivity would align with FFM neuroticism, detachment with FFM introversion, antagonism with FFM antagonism, disinhibition with low FFM conscientiousness and, contrary to the authors of DSM-5, psychoticism would align with FFM openness. Suggested changes in trait placements according to FFM of PD research were also tested. Four measures of five factor models of general personality were administered to 445 undergraduates along with the Personality Inventory for DSM-5. The results of the present study provided support for the hypothesis that all five domains of the DSM-5 dimensional trait model are maladaptive variants of general personality structure, including the domain of psychoticism; however, the findings provided mixed support for suggested trait placement changes in the DSM-5 model.
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Bildtgård, Marcus. "Applying the Five-Factor Model to Game Design." Thesis, Uppsala universitet, Institutionen för speldesign, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-227628.

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What makes us like or dislike certain games? Is there relation between our tastes in games and our personalities and can it be measured? This dissertation examines gamer personalities and game attributes with the help of the Five-Factor Model, also called The Big Five. It treats an experiment on how to apply the Five-Factor Model to games and their players and what it may be used for. By interviewing gamers, recording their favored and unfavored games, letting the gamers take a Big Five personality test and then juxtapose their personalities with their games' attributes, those questions may be answered.
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Sullivan, Maureen 1955. "The five-factor model and the processing of self-relevant information /." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35631.

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The processing of self-relevant personality trait information was examined using the five factor model of personality. The major question addressed was whether these five personality dimensions impact on the manner in which individuals process information about themselves, relevant to these personalty dimensions, across a range of cognitive processes. Accessibility of self-knowledge, attention and memory were assessed in relation to each of the five factors. Given the strong relation between personality and affect, the role of affect in processing personality information was also examined. Overall, the results indicate that personality and mood states both influence the processing of self-relevent personality trait terms. On a self-endorsement task, Neuroticism, Extraversion and Conscientiousness were associated with shorter response latencies, indicating that individuals can access rapidly information about themselves in relation to these personality dimensions. The results of memory tasks indicate that negative mood exerted a largely disruptive influence on memory performance. On an analog Stroop task, individuals in negative mood states were found to orient to negatively-valenced trait information. An interaction was found between negative mood states and Neuroticism: individuals high in Neuroticism who were also in a negative mood state were more likely to orient to negative trait information. These findings indicate that both personality and mood factors are important variables which operate on different cognitive processes. The results are interpreted in terms of model of representation of the self.
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Masood, Ambrin Faraz Buckhalt Joseph Archie. "Correlations between the five factor model of personality and problem behavior." Auburn, Ala., 2009. http://hdl.handle.net/10415/1952.

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Brinkman, Craig. "The Big Five Personality Model and Motivation in Sport." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1375299442.

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Books on the topic "Personality (five factor model)"

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Personality disorders and the five-factor model of personality. 3rd ed. Washington, D.C: American Psychological Association, 2013.

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Costa, Paul T., and Thomas A. Widiger, eds. Personality disorders and the five-factor model of personality. Washington: American Psychological Association, 1994. http://dx.doi.org/10.1037/10140-000.

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McCrae, Robert R., and Jüri Allik, eds. The Five-Factor Model of Personality Across Cultures. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0763-5.

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Costa, Paul T., and Thomas A. Widiger, eds. Personality disorders and the five-factor model of personality (2nd ed.). Washington: American Psychological Association, 2002. http://dx.doi.org/10.1037/10423-000.

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Widiger, Thomas A., and Paul T. Costa, eds. Personality disorders and the five-factor model of personality (3rd ed.). Washington: American Psychological Association, 2013. http://dx.doi.org/10.1037/13939-000.

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Trull, Timothy J. Structured interview for the Five-Factor Model of Personality (SIFFM): Professional manual. Odessa, FL: Psychological Assessment Resources, 1997.

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T, Costa Paul, ed. Personality in adulthood: A five-factor theory perspective. 2nd ed. New York: Guilford Press, 2003.

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Paunonen, Sampo V. NPQ manual: Nonverbal Personality Questionnaire (NPQ) and Five-Factor Nonverbal Personality Questionnaire (FF-NPQ). Port Huron, MI (511 Fort St., Suite 435, Port Huron): Sigma Assessment Systems, 2004.

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Smith, Debra J. A five factor model of grief: A q-methodological study. St. Catharines, Ont: Brock University, Dept. of Psychology, 2001.

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Costa, Paul T. Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI). Odessa, Fla. (P.O. Box 998, Odessa 33556): Psychological Assessment Resources, 1992.

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Book chapters on the topic "Personality (five factor model)"

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Chmielewski, Michael S., and Theresa A. Morgan. "Five-Factor Model of Personality." In Encyclopedia of Behavioral Medicine, 884–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1226.

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Clemson, Lindy, J. Rick Turner, J. Rick Turner, Farrah Jacquez, Whitney Raglin, Gabriela Reed, Gabriela Reed, et al. "Five-Factor Model of Personality." In Encyclopedia of Behavioral Medicine, 803–4. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1226.

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Piedmont, Ralph L. "Five Factor Model of Personality." In Encyclopedia of Quality of Life and Well-Being Research, 2282. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_1055.

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McNulty, John L. "Five-factor model of personality." In Encyclopedia of Psychology, Vol. 3., 375–76. Washington: American Psychological Association, 2000. http://dx.doi.org/10.1037/10518-183.

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Conte, Jeffrey M. "Five-Factor Model Rating Form." In Encyclopedia of Personality and Individual Differences, 1601–4. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_32.

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Conte, Jeffrey M. "Five-Factor Model Rating Form." In Encyclopedia of Personality and Individual Differences, 1–3. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28099-8_32-1.

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Lodhi, P. H., Savita Deo, and Vivek M. Belhekar. "The Five-Factor Model of Personality." In The Five-Factor Model of Personality Across Cultures, 227–48. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0763-5_11.

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Lowman, Rodney L. "The five-factor model of personality." In Career assessment: Integrating interests, abilities, and personality., 279–310. Washington: American Psychological Association, 2022. http://dx.doi.org/10.1037/0000254-015.

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Lima, Margarida Pedroso. "Personality and Culture." In The Five-Factor Model of Personality Across Cultures, 249–60. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0763-5_12.

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Allik, Jüri, and Robert R. McCrae. "A Five-Factor Theory Perspective." In The Five-Factor Model of Personality Across Cultures, 303–22. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0763-5_15.

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Conference papers on the topic "Personality (five factor model)"

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Pramodh, Kasula Chaithanya, and Y. Vijayalata. "Automatic personality recognition of authors using big five factor model." In 2016 IEEE International Conference on Advances in Computer Applications (ICACA). IEEE, 2016. http://dx.doi.org/10.1109/icaca.2016.7887919.

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Tanasescu, Vlad, Christopher B. Jones, Gualtiero Colombo, Martin J. Chorley, Stuart M. Allen, and Roger M. Whitaker. "The Personality of Venues: Places and the Five-Factors ('Big Five') Model of Personality." In 2013 4th International Conference on Computing for Geospatial Research & Application (COM.Geo). IEEE, 2013. http://dx.doi.org/10.1109/comgeo.2013.12.

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Stidham, Hallie, Michelle Flynn, Joshua D. Summers, and Marissa Shuffler. "Understanding Team Personality Evolution in Student Engineering Design Teams Using the Five Factor Model." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85888.

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This research explores the role of personalities in engineering design teams in a capstone course using the Five Factor Model of Personality. Specifically, the self and peer assessed personality profiles are across a semester project. After four iterations, the expectation was that peers would be better able to identify their teammates personality traits. Results show that the peer evaluations do change over time. For the factors of Openness, Conscientiousness, and Agreeableness, the agreement between self and peer evaluations increased from Iteration 2 to Iteration 4. The Extraversion factor agreement increased, but not to the point where the peer and self-evaluations did not have statistically significant differences. The agreement between the self and peer evaluations for Neuroticism decreased over time. Extended results, limitations, and future work are also discussed.
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Drobnitsa, Irina. "CORRELATION BETWEEN EYSENCK’S THREE-FACTOR PERSONALITY MODEL, GOLDBERG’S FIVE-FACTOR MODEL (BIG FIVE) AND CATTELL’S FACTOR MODEL FROM THE PERSPECTIVE OF THE STRUCTURAL-ACTIVATION-NEUROCHEMICAL TEMPERAMENT MODEL (SAN-T)." In XVI International interdisciplinary congress "Neuroscience for Medicine and Psychology". LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1036.sudak.ns2020-16/192.

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Hsien-Lun Wong, Yi-Hsien Tu, and Mei-Chun Lin. "The Validity of Five-Factor Model of Personality to Predicting Impulse Buying Tendency." In 2010 Fourth International Conference on Genetic and Evolutionary Computing (ICGEC 2010). IEEE, 2010. http://dx.doi.org/10.1109/icgec.2010.45.

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Stidham, Hallie, Joshua Summers, and Marissa Shuffler. "USING THE FIVE FACTOR MODEL TO STUDY PERSONALITY CONVERGENCE ON STUDENT ENGINEERING DESIGN TEAMS." In 15th International Design Conference. Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Croatia; The Design Society, Glasgow, UK, 2018. http://dx.doi.org/10.21278/idc.2018.0508.

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Salleh, Norsaremah, Emilia Mendes, John Grundy, and Giles St J. Burch. "An empirical study of the effects of personality in pair programming using the five-factor model." In 2009 3rd International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 2009. http://dx.doi.org/10.1109/esem.2009.5315997.

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Sodiya, Adesina, H. O. D. Longe, Adebukola Onashoga, Oludele Awodele, and L. O. Omotosho. "An Improved Assessment of Personality Traits in Software Engineering." In InSITE 2007: Informing Science + IT Education Conference. Informing Science Institute, 2007. http://dx.doi.org/10.28945/3164.

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The success or otherwise of Software Engineering (SE) activities depends on the interactions among software engineers. Consequently, effective interactions depend largely on personality traits, which is a consistent and long-lasting tendency in behaviour. In psychology, five major trait factors (The Big Five Factors) have been generally used to assess personality of people. But, these might not be adequate in SE because of the required technical and cognitive skills. In this work, we first present Cognitive Ability as an additional factor that must be measured in order to adequately assess personality in SE. A research survey was conducted in order to capture personality requirements in SE. Based on the result of the survey conducted, we develop a model for assessing personality traits in SE. We then design an assessment technique that is based on responses to some well-structured and deductive on-line questions. The implementation of the model using Visual Basic resulted in a much-needed tool that can guide intending software engineers in choosing area of specialization in SE based on their personality traits.
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Salleh, Norsaremah, Emilia Mendes, John Grundy, and Giles St J. Burch. "An empirical study of the effects of conscientiousness in pair programming using the five-factor personality model." In the 32nd ACM/IEEE International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1806799.1806883.

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Shuto, Masashi, Hironori Washizaki, Katsuhiko Kakehi, Yoshiaki Fukazawa, Shoso Yamato, Masashi Okubo, and Bastian Tenbergen. "Relationship between the five factor model personality and learning effectiveness of teams in three information systems education courses." In 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2017. http://dx.doi.org/10.1109/snpd.2017.8022718.

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Reports on the topic "Personality (five factor model)"

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Nagahi, Morteza, Raed Jaradat, Mohammad Nagahisarchoghaei, Ghodsieh Ghanbari, Sujan Poudyal, and Simon Goerger. Effect of individual differences in predicting engineering students' performance : a case of education for sustainable development. Engineer Research and Development Center (U.S.), May 2021. http://dx.doi.org/10.21079/11681/40700.

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The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.
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Méndez-Vizcaíno, Juan C., and Nicolás Moreno-Arias. A Global Shock with Idiosyncratic Pains: State-Dependent Debt Limits for LATAM during the COVID-19 pandemic. Banco de la República, October 2021. http://dx.doi.org/10.32468/be.1175.

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Fiscal sustainability in five of the largest Latin American economies is examined before and after the COVID-19 pandemic. For this purpose, the DSGE model in Bi(2012) and Hürtgen (2020) is used to estimate the Fiscal Limits and Fiscal Spaces for Peru, Chile, Mexico, Colombia, and Brazil. These estimates advance the empirical literature for Latin America on fiscal sustainability by offering new calculations stemming from a structural framework with alluring novel features: government default on the intensive margin; dynamic Laffer curves; utility-based stochastic discount factor; and a Markov-Switching process for public transfers with an explosive regime. The most notable additions to the existing literature for Latin America are the estimations of entire distributions of public debt limits for various default probabilities and that said limits critically hinge on both current and future states. Results obtained indicate notorious contractions of Fiscal Spaces among all countries during the pandemic, but the sizes of these were very heterogeneous. Countries that in 2019 had positive spaces and got closer to negative spaces in 2020, have since seen deterioration of their sovereign debt ratings or outlooks. Colombia was the only country to lose its positive Fiscal Space and investment grade, thereby joining Brazil, the previously sole member of both groups
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