{"id":3431,"date":"2024-01-05T12:27:42","date_gmt":"2024-01-05T12:27:42","guid":{"rendered":"https:\/\/www.ub.edu\/riskcenter\/?page_id=3431"},"modified":"2024-10-15T12:39:37","modified_gmt":"2024-10-15T12:39:37","slug":"pid2019","status":"publish","type":"page","link":"https:\/\/www.ub.edu\/riskcenter\/pid2019\/","title":{"rendered":"PID2019"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-fullwidth-1  fusion-parallax-none nonhundred-percent-fullwidth\" style=\"border-color:#eaeaea;border-bottom-width: 0px;border-top-width: 0px;border-bottom-style: solid;border-top-style: solid;padding-bottom:40px;padding-top:40px;padding-left:40px;padding-right:40px;background-color:#ffffff;\"><style type=\"text\/css\" scoped=\"scoped\">.fusion-fullwidth-1 {\n                            padding-left: 40px !important;\n                            padding-right: 40px !important;\n                        }<\/style><div class=\"fusion-row\"><p><img loading=\"lazy\" decoding=\"async\" class=\"alignleft size-medium wp-image-3449\" src=\"https:\/\/www.ub.edu\/riskcenter\/wp-content\/uploads\/2024\/10\/ministerio1-300x122.jpg\" alt=\"\" width=\"300\" height=\"122\" srcset=\"https:\/\/www.ub.edu\/riskcenter\/wp-content\/uploads\/2024\/10\/ministerio1-200x81.jpg 200w, https:\/\/www.ub.edu\/riskcenter\/wp-content\/uploads\/2024\/10\/ministerio1-300x122.jpg 300w, https:\/\/www.ub.edu\/riskcenter\/wp-content\/uploads\/2024\/10\/ministerio1-400x163.jpg 400w, https:\/\/www.ub.edu\/riskcenter\/wp-content\/uploads\/2024\/10\/ministerio1.jpg 475w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<div class=\"oepd_desc\">\n<h3>Project ID: PID2019-105986GB-C21<\/h3>\n<h3>Summary<\/h3>\n<p>Risk quantification is mainly present in economic activities related to finance and insurance, although its methodology is increasingly\u00a0extended to a greater number of sectors within the framework of comprehensive risk management. This subproject studies how to analyze\u00a0and predict risk in complex situations from the following points of view: 1) when there is a multivariate behavior and dependencies between\u00a0the different sources of risk, 2) when analyzing the presence of uncertainty in the economic environment and \/ or whenever volatility should\u00a0be calibrated, 3) in the presence of big data, that is, when data are varied, with a large volume and generated at high speed and 4) when\u00a0risk prediction can bring benefits in decisions and in preventive actions. Methodological results with numerous applications in economics\u00a0are obtained from the studies on multivariate risk quantification. The main objectives of this subproject are: 1) to establish methodologies in\u00a0the specification, estimation and analysis of explanatory and predictive models of multivariate risk, as well as to define alternatives based\u00a0on a generalization of quantile regression, 2) to improve quantitative risk analysis in applications related to financial markets, for example,\u00a0in the valuation of financial assets at risk and in the identification of the connection between credit and liquidity risks in the public debt\u00a0market, 3) to propose advances that are relevant in the field of insurance, specifically, for automobile usage-based insurance through\u00a0telematic data or for pension systems, where the multidimensionality of risk comes from combining investment risk, longevity and loss of\u00a0personal autonomy (functional or cognitive dependence). The implications in financial and insurance regulations are studied, in the\u00a0directives of Basel III and Solvency II. In addition, predictive modeling is studied as a prescription tool, which gives importance to the use\u00a0of quantitative methodology for the design of risk mitigation systems. The results have an impact on all economic sectors because\u00a0comprehensive risk management systems are increasingly present in all companies. Likewise, the topic is of interest to all citizens at a microeconomic level, and in general, to all economic agents in decision making process that seek a balance between maximizing their expectations and minimizing the level of risk within acceptable margins.<\/p>\n<\/div>\n<p><strong>Publications (2020-2022)<\/strong><\/p>\n<p><strong>2022<\/strong><\/p>\n<ol>\n<li>Andrada-F\u00e9lix, J., Fernandez-Perez, A. and Fern\u00e1ndez-Rodr\u00edguez, F., Sosvilla-Rivero, S. (2022) \u201cTime connectedness of fear\u201d. <strong><em>Empirical Economics<\/em><\/strong>, 62: 905\u2013931. DOI: <a href=\"https:\/\/doi.org\/10.1007\/s00181-021-02056-w\">https:\/\/doi.org\/10.1007\/s00181-021-02056-w<\/a><\/li>\n<li>Andrada-F\u00e9lix, J., Fern\u00e1ndez-Rodr\u00edguez, F. and Sosvilla-Rivero, S. (2022) \u201cFinancial market analogies of the COVID-19 pandemic: evidence from the Dow Jones Industrial Average Index\u201d. <strong><em>Applied Economics Letters<\/em><\/strong>, 1-6. DOI: <a href=\"https:\/\/doi.org\/10.1080\/13504851.2022.2097172%20\">https:\/\/doi.org\/10.1080\/13504851.2022.2097172<\/a><\/li>\n<li>Berm\u00fadez, L. and Karlis, D. (2022) \u201cCopula-based bivariate finite mixture regression models with an application for insurance claim count data\u201d. <strong>Test<\/strong>. DOI: <a href=\"https:\/\/doi.org\/10.1007\/s11749-022-00814-1\">https:\/\/doi.org\/10.1007\/s11749-022-00814-1<\/a><\/li>\n<li>Bolanc\u00e9, C., Acu\u00f1a, C.A. and Torra, S. (2022) \u201cNon-Normal Market Losses and Spatial Dependence Using Uncertainty Indices\u201d. <strong>Mathematics<\/strong>, 10, 8, 1317.\u00a0DOI: <a href=\"https:\/\/doi.org\/10.3390\/math10081317\">https:\/\/doi.org\/10.3390\/math10081317<\/a><\/li>\n<li>G\u00f3mez-D\u00e9niz, E., P\u00e9rez-Rodr\u00edguez, J. V. and Sosvilla-Rivero, S. (2022) \u201cAnalyzing How the Social Security Reserve Fund in Spain Affects the Sustainability of the Pension System\u201d. <strong><em>Risks<\/em><\/strong>, 10(6), 120. DOI: <a href=\"https:\/\/doi.org\/10.3390\/risks10060120%20\">https:\/\/doi.org\/10.3390\/risks10060120<\/a><\/li>\n<li>G\u00f3mez-Puig, M., Sosvilla-Rivero, S. and Mart\u00ednez-Zarzoso, I. (2022) \u201cOn the heterogeneous link between public debt and economic growth\u201d. <strong>Journal of International Financial Markets, Institutions and Money<\/strong>, 77, 101528. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.intfin.2022.101528\">https:\/\/doi.org\/10.1016\/j.intfin.2022.101528<\/a><\/li>\n<li><strong>Guillen, M.<\/strong>, Robles, I.B., Cabrera, E.B., Rold\u00e1n, X.A., Bolanc\u00e9, C., Jorba, D. and Mori\u00f1a, D. (2022) \u201cAcute respiratory infection rates in primary care anticipate ICU bed occupancy during COVID-19 waves\u201d. <strong>PLoS ONE<\/strong>, 17, 5 May, e0267428. DOI: <a href=\"https:\/\/doi.org\/10.1371\/journal.pone.0267428\">https:\/\/doi.org\/10.1371\/journal.pone.0267428<\/a><\/li>\n<li>Pitarque, A. and <strong>Guillen M.<\/strong> (2022) \u201dInterpolation of Quantile Regression to Estimate Driver\u2019s Risk of Traffic Accident Based on Excess Speed\u201d. <strong>Risks<\/strong>, 10, 1, 19. DOI: <a href=\"https:\/\/doi.org\/10.3390\/risks10010019\">https:\/\/doi.org\/10.3390\/risks10010019<\/a><\/li>\n<li>Santolino, M., <strong>Alca\u00f1iz, M.<\/strong> and Bolanc\u00e9, C. (2022) \u201dHospitalizations from covid-19: a health planning tool\u201d. <strong>Revista de Saude publica<\/strong>, 56, 51. DOI: <a href=\"https:\/\/doi.org\/10.11606\/s1518-8787.2022056004315\">https:\/\/doi.org\/10.11606\/s1518-8787.2022056004315<\/a><\/li>\n<li>Vernic, R., Bolanc\u00e9, C. and Alemany, R. (2022) \u201dSarmanov distribution for modeling dependence between the frequency and the average severity of insurance claims\u201d. <strong>Insurance: Mathematics and Economics<\/strong>, 102, 111-125. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.insmatheco.2021.12.001\">https:\/\/doi.org\/10.1016\/j.insmatheco.2021.12.001<\/a><\/li>\n<\/ol>\n<p><strong>2021<\/strong><\/p>\n<ol>\n<li>Alca\u00f1iz, M., Guillen, M. and Santolino, M. (2021) \u201cDifferences in the risk profiles of drunk and drug drivers: Evidence from a mandatory roadside survey\u201d. <strong><em>Accident Analysis <\/em><\/strong><strong><em>&amp;<\/em><\/strong><strong><em> Prevention<\/em><\/strong>, 151, 105947. DOI:<a href=\"https:\/\/doi.org\/10.1016\/j.aap.2020.105947\">https:\/\/doi.org\/10.1016\/j.aap.2020.105947<\/a><\/li>\n<li>Andrada-F\u00e9lix, J., Fernandez-Perez, A. and Sosvilla-Rivero, S. (2021). \u00bb Stress spillovers among financial markets: Evidence from Spain\u00bb. <strong>Journal of Risk and Financial Management<\/strong>, Vol. 23, Art. DOI: <a href=\"https:\/\/doi.org\/10.3390\/jrfm14110527\">https:\/\/doi.org\/10.3390\/jrfm14110527<\/a><\/li>\n<li>Ayuso, M., Bravo, J. M., Holzmann, R. and Palmer, E. (2021) \u201cAutomatic Indexation of the Pension Age to Life Expectancy: When Policy Design Matters\u201d. <strong><em>Risks<\/em><\/strong>, 9(5), 96. DOI: <a href=\"https:\/\/doi.org\/10.3390\/risks9050096\">https:\/\/doi.org\/10.3390\/risks9050096<\/a><\/li>\n<li>Berm\u00fadez, L. and Karlis, D. (2021). \u00abMultivariate INAR (1) Regression Models Based on the Sarmanov Distribution\u00bb. <strong>Mathematics 2021<\/strong>, 9(5), 505.\u00a0DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9050505\">https:\/\/doi.org\/10.3390\/math9050505<\/a><\/li>\n<li>Bolanc\u00e9, C. and Acu\u00f1a, C. A. (2021). \u201cA New Kernel Estimator of Copulas Based on Beta Quantile Transformations\u201d. <strong><em>Mathematics<\/em><\/strong>, 9(10), 1078. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9101078\">https:\/\/doi.org\/10.3390\/math9101078<\/a><\/li>\n<li>Bolanc\u00e9, C. and Guillen, M. (2021) \u201cNonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk\u201d. <strong><em>Risks<\/em><\/strong>, 9(4), 77. DOI:<a href=\"https:\/\/doi.org\/10.3390\/risks9040077\">https:\/\/doi.org\/10.3390\/risks9040077<\/a><\/li>\n<li>Bravo, J. M., Ayuso, M., Holzmann, R. and Palmer, E. (2021) \u00abAddressing the life expectancy gap in pension policy\u00bb. <strong><em>Insurance: Mathematics and Economics<\/em><\/strong><em>, <\/em>99, 200-221. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.insmatheco.2021.03.025\">https:\/\/doi.org\/10.1016\/j.insmatheco.2021.03.025<\/a><\/li>\n<li>Bravo, J.M. and Ayuso, M. (2021) \u201cLinking pensions to life expectancy: Tackling conceptual uncertainty through bayesian model averaging\u201d. <strong>Mathematics<\/strong>, 9, 24, 3307. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9243307\">https:\/\/doi.org\/10.3390\/math9243307<\/a><\/li>\n<li>Chen, A., <strong>Guillen, M.<\/strong> and Rach, M. (2021) \u201cFees in tontines\u201d. <strong><em>Insurance: Mathematics and Economics<\/em><\/strong>, 100, 89-106. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.insmatheco.2021.05.001\">https:\/\/doi.org\/10.1016\/j.insmatheco.2021.05.001<\/a><\/li>\n<li>Claveria, O., Monte, E. and Torra S. (2021) \u201cA genetic programming approach for estimating economic sentiment in the baltic countries and the European union\u201d. <strong>Technological and Economic Development of Economy<\/strong>, 27, 1, 262-279. \u00a0DOI: <a href=\"https:\/\/doi.org\/10.3846\/tede.2021.13989\">https:\/\/doi.org\/10.3846\/tede.2021.13989<\/a><\/li>\n<li>Frees, E.W., Bolanc\u00e9, C., Guillen, M. and Valdez, E.A. (2021) \u201cDependence modeling of multivariate longitudinal hy<strong>b<\/strong>rid insurance data with dropout\u201d. <strong>Expert Systems with Applications<\/strong>, 185, 115552.<br \/>\nDOI: <a href=\"https:\/\/doi.org\/10.1016\/j.eswa.2021.115552\">https:\/\/doi.org\/10.1016\/j.eswa.2021.115552<\/a><\/li>\n<li>Guillen, M., Berm\u00fadez, L. and Pitarque, A. (2021) \u201cJoint generalized quantile and conditional tail expectation regression for insurance risk analysis\u201d. <strong><em>Insurance: Mathematics and Economics<\/em><\/strong>, 99, 1-8. DOI:<a href=\"https:\/\/doi.org\/10.1016\/j.insmatheco.2021.03.006\">https:\/\/doi.org\/10.1016\/j.insmatheco.2021.03.006<\/a><\/li>\n<li>Guillen, M., Bolanc\u00e9, C., Frees, E.W. and Valdez, E.A. (2021) \u201cCase study data for joint modeling of insurance claims and lapsation\u201d. <strong>Data in Brief<\/strong>, 39, 107639.\u00a0DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.dib.2021.107639\">https:\/\/doi.org\/10.1016\/j.dib.2021.107639<\/a><\/li>\n<li>Guillen, M., Nielsen, J.P. and P\u00e9rez-Mar\u00edn, A.M. (2021) \u201cNear\u2010miss telematics in motor insurance\u201d. <strong><em>Journal of Risk and Insurance<\/em><\/strong>, 1-21. DOI:<a href=\"https:\/\/doi.org\/10.1111\/jori.12340\">https:\/\/doi.org\/10.1111\/jori.12340<\/a><\/li>\n<li>Guillen, M., P\u00e9rez-Mar\u00edn, A.M. and Alca\u00f1iz, M. (2021) \u201cPercentile charts for speeding based on telematics information\u201d <strong>Accident Analysis &amp; Prevention<\/strong>, 150,105865. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.aap.2020.105865\">https:\/\/doi.org\/10<strong> Alca\u00f1iz, M.<\/strong>.1016\/j.aap.2020.105865<\/a><\/li>\n<li>Pesantez-Narvaez, J., Guillen, M. and (2021) \u201cRiskLogitboost Regression for Rare Events in Binary Response: An Econometric Approach\u201d. <strong>Mathematics 2021<\/strong>, 9, 579. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9050579\">https:\/\/doi.org\/10.3390\/math9050579<\/a><\/li>\n<li>Piulachs, X., Andrinopoulou, E. R., Guill\u00e9n, M. and Rizopoulos, D. (2021) \u201cA Bayesian joint model for zero\u2010inflated integers and left\u2010truncated event times with a time\u2010varying association: Applications to senior health care\u201d. <strong>Statistics in Medicine<\/strong>, 40(1), 147-166. DOI:<a href=\"https:\/\/doi.org\/10.1002\/sim.8767\">https:\/\/doi.org\/10.1002\/sim.8767<\/a><\/li>\n<li>Romo, E. and Ortiz-Gracia, L. (2021) \u00abSWIFT calibration of the Heston model\u00bb. <strong>Mathematics<\/strong>,9(5), 529. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9050529\">https:\/\/doi.org\/10.3390\/math9050529<\/a><\/li>\n<li>Santolino, M. (2021) \u201cMedian bilinear models in presence of extreme values\u201d. <strong>Statistics and Operations Research Transactions<\/strong>, 2021, 45(2). DOI: <a href=\"https:\/\/doi.org\/10.2436\/20.8080.02.114\">https:\/\/doi.org\/10.2436\/20.8080.02.114<\/a><\/li>\n<li>Santolino, M., Belles-Sampera, J., Sarabia, J.M. and Guillen, M. (2021) \u201dAn examination of the tail contribution to distortion risk measures\u201d. <strong>Journal of Risk<\/strong>, 23, 6. DOI: <a href=\"https:\/\/doi.org\/10.21314\/JOR.2021.014\">https:\/\/doi.org\/10.21314\/JOR.2021.014<\/a><\/li>\n<li>Sarabia, J.M., Prieto, F., Jord\u00e1, V. and Guillen, M. (2021) \u201cMultivariate Classes of GB2 Distributions with Applications\u201d. <strong>Mathematics 2021<\/strong>, 9(1), 72. \u00a0DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9010072\">https:\/\/doi.org\/10.3390\/math9010072<\/a><\/li>\n<li>Urbina, J., Santolino, M. and Guillen, M. (2021) \u201dCovariance principle for capital allocation: A time-varying approach\u201d. <strong>Mathematics<\/strong>, 9, 16, 2005. \u00a0DOI: <a href=\"https:\/\/doi.org\/10.3390\/math9162005\">https:\/\/doi.org\/10.3390\/math9162005<\/a><\/li>\n<\/ol>\n<p><strong>2020<\/strong><\/p>\n<ol>\n<li>Andrada-F\u00e9lix, J., Fernandez-Perez, A. and Sosvilla-Rivero, S. (2020). \u201cDistant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities\u201d. <strong><em>Journal of International Financial Markets, Institutions and Money<\/em><\/strong>, 67, 101219. DOI: <a href=\"https:\/\/doi.org\/10.1016\/j.intfin.2020.101219\">https:\/\/doi.org\/10.1016\/j.intfin.2020.101219<\/a><\/li>\n<li>Arvelo, E., de Armas, J. and Guillen, M. (2020) \u201cAssessing the Distribution of Elderly Requiring Care: A Case Study on the Residents in Barcelona and the Impact of COVID-19\u201d, <strong><em>International Journal of Environmental Research and Public Health<\/em><\/strong>, 17(20), 7486.DOI: <a href=\"https:\/\/doi.org\/10.3390\/ijerph17207486\">https:\/\/doi.org\/10.3390\/ijerph17207486<\/a><\/li>\n<li>Bolanc\u00e9, C., Guillen, M. and Pitarque, A. (2020) \u201cA Sarmanov Distribution with Beta Marginals: An Application to Motor Insurance Pricing\u201d, <strong><em>Mathematics<\/em><\/strong>, 8(11, 2020. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math8112020\">https:\/\/doi.org\/10.3390\/math8112020<\/a><\/li>\n<li>Bravo, J. M., and Ayuso, M. (2020) \u201cPrevis\u00f5es de mortalidade e de esperan\u00e7a de vida mediante combina\u00e7\u00e3o Bayesiana de modelos: Uma aplica\u00e7\u00e3o \u00e0 popula\u00e7\u00e3o portuguesa\u201d. <strong>RISTI &#8211; Revista Iberica de Sistemas e Tecnologias de Informacao<\/strong>, 40(12), 128-144.\u00a0\u00a0\u00a0\u00a0 DOI: 10.17013\/risti.40.128\u2013145<\/li>\n<li>Sun, S., Bi, J., Guillen, M. and P\u00e9rez-Mar\u00edn, A. M. (2020) \u201cAssessing driving risk using internet of vehicles data: an analysis based on generalized linear models\u201d <strong><em>Sensors<\/em><\/strong>, 20(9), 2712. DOI: <a href=\"https:\/\/doi.org\/10.3390\/s20092712\">https:\/\/doi.org\/10.3390\/s20092712<\/a><\/li>\n<li>Uribe, J. M. and Guillen, M. (2020) \u201cGeneralized Market Uncertainty Measurement in European Stock Markets in Real Time\u201d <strong><em>Mathematics<\/em><\/strong>, 8(12), 2148. DOI: <a href=\"https:\/\/doi.org\/10.3390\/math8122148\">https:\/\/doi.org\/10.3390\/math8122148<\/a><\/li>\n<li>Uribe, J., Mosquera-L\u00f3pez, S. and Guillen, M. (2020) \u201cCharacterizing electricity market integration in Nord Pool\u201d <strong><em>Energy<\/em><\/strong>, 208,118368.<br \/>\nDOI: <a href=\"https:\/\/doi.org\/10.1016\/j.energy.2020.118368\">https:\/\/doi.org\/10.1016\/j.energy.2020.118368<\/a><\/li>\n<li>Vida-Llana, X. and Guillen, M. (2020) \u201cAdvanced analytics pricing for the calculation of post-covid19 scenarios in automobile insurance\u201d <strong><em>Anales del Instituto de Actuarios Espa\u00f1oles<\/em><\/strong>, 26, 157-179\u00a0 DOI:<a href=\"https:\/\/doi.org\/10.26360\/2020_7\">https:\/\/doi.org\/10.26360\/2020_7<\/a><\/li>\n<\/ol>\n<p><small><big><small><big><small><big><small><big><b><small><big>Contributions to meetings (2020-2022)<\/big><\/small><\/b><\/big><\/small><\/big><\/small><\/big><\/small><\/big><\/small><\/p>\n<p>See link<\/p>\n<p><small><big><small><big><small><big><small><big><b><small><big>PhD theses defended (2020-2022)<\/big><\/small><\/b><\/big><\/small><\/big><\/small><\/big><\/small><\/big><\/small><\/p>\n<ul>\n<li>Garr\u00f3n, I. (2023) <em>Essays on Tail Risks in Macroeconomics<\/em><i>, <\/i>University of Barcelona, PhD in Economics. Dir: Helena Chuli\u00e0 \/ Jorge M. Uribe.<\/li>\n<li>Vidal-Llana, J.J. (2023) <i>Essays on Machine Learning for Risk Analysis in Finance, Insurance and Energy, <\/i>University of Barcelona, PhD in Business.\u00a0 Dir: Montserrat Guillen \/ Jorge M. Uribe.<\/li>\n<li>Acu\u00f1a, C.A. (2022) Dependence and Systematic Risks in Financial Markets: Spatial and Upper Tail Analysis, University of Barcelona, PhD in Business. Dir: Catalina Bolance \/ Salvador Torra.<\/li>\n<li>Pitarque M\u00e9ndez, A. (2022) <i>Essays on Estimation, Prediction and Evaluation of Insurance Risk, <\/i>University of Barcelona, PhD in Business.\u00a0 Dir: Montserrat Guillen.<\/li>\n<li>Pes\u00e1ntez-Narv\u00e1ez, J.E. (2021) <em>Risk Analytics in Econometrics<\/em>, University of Barcelona, PhD in Economics. Dir: Montserrat Guillen \/ Manuela Alca\u00f1iz.<\/li>\n<li>Koser, C. (2020) <em>Essays on Liquidity in Financial Markets<\/em>, University of Barcelona, PhD in Economics. Dir: Helena Chuli\u00e0 \/ Jorge M. Uribe.<\/li>\n<\/ul>\n<\/div><\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp;<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"_links":{"self":[{"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/pages\/3431"}],"collection":[{"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/comments?post=3431"}],"version-history":[{"count":11,"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/pages\/3431\/revisions"}],"predecessor-version":[{"id":3456,"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/pages\/3431\/revisions\/3456"}],"wp:attachment":[{"href":"https:\/\/www.ub.edu\/riskcenter\/wp-json\/wp\/v2\/media?parent=3431"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}