Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos

Este documento contiene tres aportes teóricos que se encuentran en la interacción entre los modelos estocásticos de equilibrio general, la macroeconomía dinámica y el control óptimo en tiempo continuo. En el primer capítulo, se estudia una solución analítica de dos modelos DSGE (Dynamic Stochastic G...

Full description

Autores:
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
spa
OAI Identifier:
oai:repository.urosario.edu.co:10336/31310
Acceso en línea:
https://doi.org/10.48713/10336_31310
https://repository.urosario.edu.co/handle/10336/31310
Palabra clave:
Modelos de agentes heterogéneos
Procesos de difusión con saltos aleatorios
Ecuaciones de Hamilton-Jacobi- Bellman y kolmogorov-Forward
Modelos económicos de equilibrio general aplicado
Modelos EGDE (equilibrio general dinámico estocástico) en tiempo continuo
Control óptimo estocástico en modelos Economicos
Método de diferencias finitas en modelación económica
Análisis de riesgo de desastres económico
Macroeconomía & temas relacionados
Heterogeneous agent models
Diffusion processes with random hops
Hamilton-Jacobi- Bellman and kolmogorov-Forward equations
Applied General Equilibrium Economic Models
Continuous-Time DSGE Models (Stochastic Dynamic General Equilibrium)
Optimal stochastic control in economic models
Finite difference method in economic modeling
Economic disaster risk analysis
Rights
License
Atribución-NoComercial-SinDerivadas 2.5 Colombia
id EDOCUR2_43cecb85fa8f69014869282e6dc0e44f
oai_identifier_str oai:repository.urosario.edu.co:10336/31310
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.spa.fl_str_mv Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
dc.title.TranslatedTitle.spa.fl_str_mv A theoretical approach in continuous time to dynamic general equilibrium models stochastics
title Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
spellingShingle Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
Modelos de agentes heterogéneos
Procesos de difusión con saltos aleatorios
Ecuaciones de Hamilton-Jacobi- Bellman y kolmogorov-Forward
Modelos económicos de equilibrio general aplicado
Modelos EGDE (equilibrio general dinámico estocástico) en tiempo continuo
Control óptimo estocástico en modelos Economicos
Método de diferencias finitas en modelación económica
Análisis de riesgo de desastres económico
Macroeconomía & temas relacionados
Heterogeneous agent models
Diffusion processes with random hops
Hamilton-Jacobi- Bellman and kolmogorov-Forward equations
Applied General Equilibrium Economic Models
Continuous-Time DSGE Models (Stochastic Dynamic General Equilibrium)
Optimal stochastic control in economic models
Finite difference method in economic modeling
Economic disaster risk analysis
title_short Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
title_full Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
title_fullStr Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
title_full_unstemmed Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
title_sort Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos
dc.contributor.advisor.none.fl_str_mv Serrano Perdomo, Rafael Antonio
dc.subject.spa.fl_str_mv Modelos de agentes heterogéneos
Procesos de difusión con saltos aleatorios
Ecuaciones de Hamilton-Jacobi- Bellman y kolmogorov-Forward
Modelos económicos de equilibrio general aplicado
Modelos EGDE (equilibrio general dinámico estocástico) en tiempo continuo
Control óptimo estocástico en modelos Economicos
Método de diferencias finitas en modelación económica
Análisis de riesgo de desastres económico
topic Modelos de agentes heterogéneos
Procesos de difusión con saltos aleatorios
Ecuaciones de Hamilton-Jacobi- Bellman y kolmogorov-Forward
Modelos económicos de equilibrio general aplicado
Modelos EGDE (equilibrio general dinámico estocástico) en tiempo continuo
Control óptimo estocástico en modelos Economicos
Método de diferencias finitas en modelación económica
Análisis de riesgo de desastres económico
Macroeconomía & temas relacionados
Heterogeneous agent models
Diffusion processes with random hops
Hamilton-Jacobi- Bellman and kolmogorov-Forward equations
Applied General Equilibrium Economic Models
Continuous-Time DSGE Models (Stochastic Dynamic General Equilibrium)
Optimal stochastic control in economic models
Finite difference method in economic modeling
Economic disaster risk analysis
dc.subject.ddc.spa.fl_str_mv Macroeconomía & temas relacionados
dc.subject.keyword.spa.fl_str_mv Heterogeneous agent models
Diffusion processes with random hops
Hamilton-Jacobi- Bellman and kolmogorov-Forward equations
Applied General Equilibrium Economic Models
Continuous-Time DSGE Models (Stochastic Dynamic General Equilibrium)
Optimal stochastic control in economic models
Finite difference method in economic modeling
Economic disaster risk analysis
description Este documento contiene tres aportes teóricos que se encuentran en la interacción entre los modelos estocásticos de equilibrio general, la macroeconomía dinámica y el control óptimo en tiempo continuo. En el primer capítulo, se estudia una solución analítica de dos modelos DSGE (Dynamic Stochastic General Equilibrium) en tiempo continuo con preferencias CRRA, tecnología tipo Cobb-Douglas y choques en la dinámica de acumulación de capital que combinan un proceso de difusión con saltos aleatorios asociados a eventos raros. El factor de tecnología puede tomar la forma de un proceso CIR con reversión a la media o un movimiento browniano geométrico. En el segundo capítulo, se propone la solución de un modelo de crecimiento neoclásico estocástico en tiempo continuo con un solo sector, de tipo Ramsey, con función de utilidad CRRA y tecnología tipo Cobb-Douglas, con acumulación de capital, efectividad y la fuerza del trabajo sujetos a choques exógenos que siguen procesos de difusión con saltos, dados por eventos raros. Finalmente, en el tercer capítulo, estudiamos un problema de agentes heterogéneos en tiempo continuo. Analizamos el efecto de los choques estocásticos con saltos en la dinámica y distribución del ingreso de los agentes, y su impacto en el consumo, el ahorro y la distribución conjunta de la riqueza e ingreso. En todos los modelos, el principio de programación dinámica, el teorema de veri cación y el método de diferencias nitas permitieron encontrar soluciones analíticas y numéricas de las ecuaciones de Hamilton-Jacobi-Bellman (HJB) y Kolmogorov-Forward (kF). Eso permite obtener las funciones de política óptimas para las variables de control, analizar en cada caso de forma analítica y numérica los efectos de este tipo de choques estocásticos sobre las decisiones económicas de los agentes; como también destacar que el empleo de modelos dinámicos, que siguen procesos de difusión con saltos, representan los fenómenos económicos de forma más realista y enriquecen el análisis en ambientes con riesgo e incertidumbre.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-04-29T16:58:51Z
dc.date.available.none.fl_str_mv 2021-04-29T16:58:51Z
dc.date.created.none.fl_str_mv 2021-04-22
dc.type.eng.fl_str_mv doctoralThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_db06
dc.type.document.spa.fl_str_mv Monografía
dc.type.spa.spa.fl_str_mv Tesis de doctorado
dc.identifier.doi.none.fl_str_mv https://doi.org/10.48713/10336_31310
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/31310
url https://doi.org/10.48713/10336_31310
https://repository.urosario.edu.co/handle/10336/31310
dc.language.iso.spa.fl_str_mv spa
language spa
dc.rights.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 2.5 Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/2.5/co/
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 2.5 Colombia
Abierto (Texto Completo)
http://creativecommons.org/licenses/by-nc-nd/2.5/co/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.spa.fl_str_mv 220 pp.
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad del Rosario
dc.publisher.department.spa.fl_str_mv Facultad de Economía
dc.publisher.program.spa.fl_str_mv Doctorado en Economía
institution Universidad del Rosario
dc.source.bibliographicCitation.spa.fl_str_mv Achdou, Yves & Capuzzo-Dolcetta, I. (2010). Mean field games: numerical methods. SIAM Journal on Numerical Analysis, 48(3):1136-1162.
Achdou, Y. (2013). Finite difference methods for mean field games. In Hamilton-Jacobi equations: approximations, numerical analysis and applications, pages 1-47. Springer.
Achdou, Y., Buera, F. J., Lasry, J.-M., Lions, P.-L., and Moll, B. (2014). Partial differential equation models in macroeconomics. Phil. Trans. R. Soc. A, 372(2028):20130397.
Achdou, Y., Han, J., Lasry, J.-M., Lions, P.-L., and Moll, B. (2017). Income and wealth distribution in macroeconomics: A continuous-time approach. Technical report, National Bureau of Economic Research.
Achdou, Y. and Laurière, M. (2020). Mean field games and applications: Numerical aspects. arXiv preprint arXiv:2003.04444.
Aiyagari, S. R. (1994). Uninsured idiosyncratic risk and aggregate saving. The Quarterly Journal of Economics, 109(3):659-684.
Aruoba, S. B., Fernandez-Villaverde, J., and Rubio-Ramirez, J. F. (2006). Comparing solution methods for dynamic equilibrium economies. Journal of Economic dynamics and Control, 30(12):2477-2508.
Barles, G. and Jakobsen, E. R. (2002). On the convergence rate of approximation schemes for hamilton-jacobi-bellman equations. ESAIM: Mathematical Modelling and Numerical Analysis, 36(1):33-54.
Barles, G. and Souganidis, P. E. (1991). Convergence of approximation schemes for fully nonlinear second order equations. Asymptotic analysis, 4(3):271-283.
Barro, R. and Sala-i Martin, X. (2004). Economic growth second edition.
Barro, R. J. (2006). Rare disasters and asset markets in the twentieth century. The Quarterly Journal of Economics, 121(3):823-866.
Barro, R. J. (2009). Rare disasters, asset prices, and welfare costs. American Economic Review, 99(1):243-64.
Barro, R. J. and Jin, T. (2011). On the size distribution of macroeconomic disasters. Econometrica, 79(5):1567-1589.
Barro, R. J. and Ursúa, J. F. (2012). Rare macroeconomic disasters. Annu. Rev. Econ., 4(1):83- 109.
Baten, M., Kamil, A. A., et al. (2013). Optimal consumption in a stochastic ramsey model with cobb-douglas production function. International Journal of Mathematics and Mathematical Sciences, 2013.
Baxter, M. and King, R. G. (1999). Measuring business cycles: approximate band-pass filters for economic time series. Review of economics and statistics, 81(4):575-593.
Bellman, R. (1957). Dynamic programming (dp).
Bernanke, B. S., Gertler, M., and Gilchrist, S. (1998). Credit market frictions and cyclical fluctuations. Handbook of Macroeconomics (North-Holland, Amsterdam).
Bertsekas, D. P. (1987). Dynamic progrcmming: Deterministic and. Stochastic Models, pages 12-22.
Bianchi, D., Büchner, M., and Tamoni, A. (2020). Bond risk premiums with machine learning. The Review of Financial Studies.
Blanchard, O. (2009). The state of macro. Annu. Rev. Econ., 1(1):209-228.
Boucekkine, R., Pintus, P. A., and Zou, B. (2018). Mean growth and stochastic stability in endogenous growth models. Economics Letters, 166:18-24.
Brunnermeier, M. K. and Sannikov, Y. (2014). A macroeconomic model with a financial sector. American Economic Review, 104(2):379-421.
Candler, G. V. et al. (1998). Finite-difference methods for continuous-time dynamic programming. QM&RBC Codes.
Carroll, C. D., Hall, R. E., and Zeldes, S. P. (1992). The buffer-stock theory of saving: Some macroeconomic evidence. Brookings papers on economic activity, 1992(2):61-156.
Castillo-Ramírez, C. E., Venegas-Martínez, F., and López-Herrera, F. (2016). Efectos de saltos inesperados en el gasto público y variables demográficas en el crecimiento económico. el caso mexicano con un enfoque garch con saltos (1936-2012). El trimestre económico, 83(332):725- 745.
Chang, F.-R. (2004). Stochastic optimization in continuous time. Cambridge University Press.
Chipeniuk, K., Katz, N. H., and Walker, T. (2014). Approximate aggregation in the neoclassical growth model with ideosyncratic shocks. arXiv preprint arXiv:1404.4665.
Cont, R. and Voltchkova, E. (2005). A finite difference scheme for option pricing in jump diffusion and exponential lévy models. SIAM Journal on Numerical Analysis, 43(4):1596-1626.
Cox, J. C., Ingersoll Jr, J. E., and Ross, S. A. (2005). A theory of the term structure of interest rates. In Theory of Valuation, pages 129-164. World Scientific.
Cruz, J. H. R. (2012). Usos y limitaciones de la dinámica estocástica en el análisis macroeconómico convencional. In Optimización-Estocástica-Recursiva-Coherente-Sistémica y sus variantes (probabilidad, econometría y estadística aplicada), pages 25-54. ECORFAN.
D'Avernas, Adrien & Vandeweyer, Q. (2019). A solution method for continuous-time models.
d'Halluin, Y., Forsyth, P. A., and Vetzal, K. R. (2005). Robust numerical methods for contingent claims under jump diffusion processes. IMA Journal of Numerical Analysis, 25(1):87-112.
Duarte, V. (2018). Machine learning for continuous-time economics. Available at SSRN 3012602.
Dynan, K. E. (1993). How prudent are consumers? Journal of Political Economy, 101(6):1104-1113.
Economics, V. (2013). The macroeconomics of climate change, report prepared for defra. Vivid Economics, London.
Fankhauser, Samuel y Tol, R. S. (2005). On climate change and economic growth. Resource and Energy Economics, 27(1):1-17.
Feicht, R. and Stummer, W. (2010). Complete closed-form solution to a stochastic growth model and corresponding speed of economic recovery. Technical report, IWQW Discussion Papers.
Fernández-Corugedo, E. (2004). Teoria del consumo. Handbooks in Central Banking N, 23.
Fernández-Villaverde, J. and Levintal, O. (2018). Solution methods for models with rare disasters. Quantitative Economics, 9(2):903-944.
Fernández-Villaverde, J. and Rubio-Ramírez, J. F. (2005). Estimating dynamic equilibrium economies: linear versus nonlinear likelihood. Journal of Applied Econometrics, 20(7):891-910.
Fernández-Villaverde, J., Rubio-Ramírez, J. F., and Schorfheide, F. (2016). Solution and estimation methods for dsge models. In Handbook of Macroeconomics, volume 2, pages 527-724.
Fleming, W. H. and Soner, H. M. (2006). Controlled Markov processes and viscosity solutions, volume 25. Springer Science & Business Media.
Fried, S. (2018). Climate policy and innovation: A quantitative macroeconomic analysis. American Economic Journal: Macroeconomics, 10(1):90-118.
Frische, U. and Gröÿl, I. (2010). New keynesian dsge models and the is-lm paradigm. Technical report, IMK Working Paper.
Galí, J. et al. (2008). Introduction to monetary policy, inflation, and the business cycle: An introduction to the new keynesian framework. Introductory Chapters.
Gaspar, J. and Judd, K. L. (1997). Solving large-scale rational-expectations models. Macroeconomic Dynamics, 1(1):45-75.
Gillingham, K., Nordhaus, W. D., Anthoff, D., Blanford, G., Bosetti, V., Christensen, P., McJeon, H., Reilly, J., and Sztorc, P. (2015). Modeling uncertainty in climate change: A multi-model comparison. Technical report, National Bureau of Economic Research.
Giulano, P. and Turnovsky, S. (2003). Intertemporal substitution risk aversion and economic performance in a stochastically growing economy. Journal of International Money and Finance, 22(4):529-556.
Gomes, D. A., Nurbekyan, L., and Pimentel, E. (2015). Economic models and mean-field games theory. In 30o Co16quio Brasileiro de Matemática.[30th Brazilian Mathematics Colloquium].
Gourio, F. (2012). Disaster risk and business cycles. American Economic Review, 102(6):2734-66.
Greenwood, J., Hercowitz, Z., and Huffman, G. W. (1988). Investment, capacity utilization, and the real business cycle. The American Economic Review, pages 402-417.
Group, W. B. (2018). Iraq Reconstruction and Investment: Damage and Needs Assessment of Affected Governorates. World Bank.
Guvenen, F. (2011). Macroeconomics with heterogeneity: A practical guide. Technical report, National Bureau of Economic Research.
Guvenen, F., Karahan, F., Ozkan, S., and Song, J. (2015). What do data on millions of us workers reveal about life-cycle earnings risk? Technical report, National Bureau of Economic Research.
Hallegate, S y Przyluski, V. (2010). The economic of floods: Concepts and methods. World Bank Policy Research Working Paper, 5507.
Hambel, C., Kraft, H., and van der Ploeg, R. (2020). Asset diversification versus climate action.
Hanson, F. B. (2007). Applied stochastic processes and control for Jump-diffusions: modeling, analysis, and computation, volume 13. Siam.
Heathcote, J., Storesletten, K., and Violante, G. L. (2009). Quantitative macroeconomics with heterogeneous households. Annu. Rev. Econ., 1(1):319-354.
Heathcote, J., Storesletten, K., and Violante, G. L. (2010). The macroeconomic implications of rising wage inequality in the united states. Journal of political economy, 118(4):681-722.
Heckman, J. J. (2001). Micro data, heterogeneity, and the evaluation of public policy: Nobel lecture. Journal of political Economy, 109(4):673-748.
Hernández, G. (2010). El método de diferencias finitas.
Hernández-Lerma, O. (1989). Adaptive markov control processes.
Hiraguchi, R. (2014). A note on the analytical solution to the neoclassical growth model with leisure. Macroeconomic Dynamics, 18(2):473-479.
Hirsa, A. (2016). Computational methods in finance. CRC Press.
Hodrick, R. J. and Prescott, E. C. (1997). Postwar us business cycles: an empirical investigation. Journal of Money, credit, and Banking, pages 1-16.
Huggett, M. (1993). The risk-free rate in heterogeneous-agent incomplete-insurance economies. Journal of economic Dynamics and Control, 17(5-6):953-969.
Ireland, P. N. (2004). A method for taking models to the data. Journal of Economic Dynamics and Control, 28(6):1205-1226.
Isoré, M. and Szczerbowicz, U. (2017). Disaster risk and preference shifts in a new keynesian model. Journal of Economic Dynamics and Control, 79:97-125.
Jacobson, L. S., LaLonde, R. J., and Sullivan, D. G. (1993). Earnings losses of displaced workers. The American economic review, pages 685-709.
Judd, K. L. (1996). Approximation, perturbation, and projection methods in economic analysis. Handbook of computational economics, 1:509-585.
Judd, K. L. (1998). Numerical methods in economics mit press books.
Kalman, R. (1963). The theory of optimal control and the calculus of variations. Mathematical optimization techniques, pages 309-331.
Kaplan, G., Moll, B., and Violante, G. L. (2018). Monetary policy according to hank. American Economic Review, 108(3):697-743.
Kendrick, D. (1976). Applications of control theory to macroeconomics. In Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190. NBER.
Kendrick, D. A. (1981). Stochastic control for economic models. McGraw-Hill Companies.
Khan, Aubhik y Thomas, J. K. (2008). Idiosyncratic shocks and the role of nonconvexities in plant and aggregate investment dynamics. Econometrica, 76(2):395-436.
Kimball, M. S. (1990). Precautionary saving and the marginal propensity to consume. Technical report, National Bureau of Economic Research.
King, R. G., Plosser, C. I., and Rebelo, S. T. (1988). Production, growth and business cycles: I. the basic neoclassical model. Journal of monetary Economics, 21(2-3):195-232.
King, R. G. and Rebelo, S. T. (1999). Resuscitating real business cycles. Handbook of macroeconomics, 1:927-1007.
Kompas, T. and Chu, L. (2012). Comparing approximation techniques to continuous-time stochastic dynamic programming problems: Applications to natural resource modelling. Environmental modelling & software, 38:1-12.
Krusell, Per y Smith, J. A. A. (1998). Income and wealth heterogeneity in the macroeconomy. Journal of political Economy, 106(5):867-896
Kydland, F. E. and Prescott, E. C. (1982). Time to build and aggregate fluctuations. Econometrica: Journal of the Econometric Society, pages 1345-1370.
Lasry, J.-M., Lions, P.-L., and Guéant, O. (2008). Application of mean field games to growth theory.
Lee, J.-J. and Sawada, Y. (2010). Precautionary saving under liquidity constraints: Evidence from rural pakistan. Journal of Development Economics, 91(1):77-86.
Leland, H. E. (1978). Saving and uncertainty: The precautionary demand for saving. In Uncertainty in economics, pages 127-139. Elsevier.
Li, Z., Qiao, Z., and Tang, T. (2017). Numerical solution of di erential equations: introduction to finite difference and finite element methods. Cambridge University Press.
Long Jr, J. B. and Plosser, C. I. (1983). Real business cycles. Journal of political Economy, 91(1):39-69.
Merton, R. C. (1971). Optimum consumption and portfolio rules in a continuous-time model. In Stochastic Optimization Models in Finance, pages 621-661. Elsevier.
Merton, R. C. (1975). An asymptotic theory of growth under uncertainty. The Review of Economic Studies, 42(3):375-393.
Merton, R. C. and Samuelson, P. A. (1992). Continuous-time finance.
Michael, W. (2003). Interest and prices: Foundations of a theory of monetary policy.
Miranda, M. J. and Fackler, P. L. (2004). Applied computational economics and finance. MIT press.
Moll, B. (2014). Productivity losses from financial frictions: Can self-financing undo capital misallocation? American Economic Review, 104(10):3186-3221.
Nakamura, E., Steinsson, J., Barro, R., and Ursúa, J. (2013). Crises and recoveries in an empirical model of consumption disasters. American Economic Journal: Macroeconomics, 5(3):35-74.
Nuño, Galo & Moll, B. (2017). Social optima in economies with heterogeneous agents. Review of Economic Dynamics.
Nuño, G. (2013). Optimal control with heterogeneous agents in continuous time.
Nuño, G. (2015). Continuous time methods for economics and finance. Review of Economics and Statistics, 51(3):247-257.
OIT, O. (2017). Perspectivas sociales y del empleo en el mundo. tendencias 2017.
Okahata, N. et al. (2018). An alternative solution method for continuous-time heterogeneous agent models with aggregate shocks. Technical report, Mimeo New York.
Øksendal, B. (2006). A universal optimal consumption rate for an insider. Mathematical Finance, 16(1):119-129.
Oksendal, B. and Sulem, A. (2009). Applied control of jump diffusions.
Parra-Alvarez, J. C. (2017). A comparison of numerical methods for the solution of continuoustime dsge models. Macroeconomic Dynamics, pages 1-29.
Parra-Alvarez, J. C., Posch, O., and Wang, M.-C. (2017a). Identification and estimation of heterogeneous agent models: A likelihood approach.
Parra-Alvarez, J. C., Posch, O., and Wang, M.-C. (2017b). Identification and estimation of heterogeneous agent models: A likelihood approach.
Phillips, A. W. (1954). Stabilisation policy in a closed economy. The Economic Journal, 64(254):290-323.
Phillips, A. W. (1957). Stabilisation policy and the time-forms of lagged responses. The Economic Journal, 67(266):265-277.
Pindyck, R. S. and Wang, N. (2013). The economic and policy consequences of catastrophes. American Economic Journal: Economic Policy, 5(4):306-39.
Pontryagin, L. (1962). Ordinary difeerential equations. translated from the russian by leonas kacinskas and walter b. counts. Reading: Addison-Wesley Publishing Company.
Posch, O. (2009). Structural estimation of jump-diffusion processes in macroeconomics. Journal of Econometrics, 153(2):196-210.
Posch, O. (2011). Risk premia in general equilibrium. Journal of Economic Dynamics and Control, 35(9):1557-1576.
Posch, Olaf y Trimborn, T. (2013). Numerical solution of dynamic equilibrium models under poisson uncertainty. Journal of Economic Dynamics and Control, 37(12):2602-2622.
Prescott, E. C. (1971). Adaptive decision rules for macroeconomic planning. Economic Inquiry, 9(4):369-378.
Preston, Bruce & Roca, M. (2007). Incomplete markets, heterogeneity and macroeconomic dynamics. Technical report, National Bureau of Economic Research.
Ramirez, J., H. E. (2016). Optimal decisions in illiquid hedge funds. PhD thesis, The University of Manchester (United Kingdom).
Riascos, A. J. V. (2009). Métodos matemáticos y computacionales en macroeconomía. Universidad de los Andes, Fac. de Economía, CEDE, Ediciones Uniandes.
Rietz, T. A. (1988). The equity risk premium a solution. Journal of monetary Economics, 22(1):117-131.
Rotemberg, J. J. and Woodford, M. (1997). An optimization-based econometric framework for the evaluation of monetary policy. NBER macroeconomics annual, 12:297-346.
Scheidegger, S. and Bilionis, I. (2019). Machine learning for high-dimensional dynamic stochastic economies. Journal of Computational Science, 33:68-82.
Schmitt-Grohé, S. and Uribe, M. (2004). Solving dynamic general equilibrium models using a second-order approximation to the policy function. Journal of economic dynamics and control, 28(4):755-775.
Scott, B. (1999). Computational methods for the study of dynamic economies. Oxford University Press.
Smith, W. T. (2006). An analytical solution to the ramsey model. Contributions to Macroeconomics, 6(1):1-28.
Smith, W. T. (2007). Inspecting the mechanism exactly: a closed-form solution to a stochastic growth model. The BE Journal of Macroeconomics, 7(1).
Steger, T. M. (2005). Stochastic growth under wiener and poisson uncertainty. Economics Letters, 86(3):311-316.
Stern, Nicholas y Stern, N. H. (2007). The economics of climate change: the Stern review. cambridge University press.
Stern, V., Peters, S., Bakhshi, V., et al. (2010). The stern review. Government Equalities Offce, Home O ce.
Storesletten, K., Telmer, C. I., and Yaron, A. (2001). The welfare cost of business cycles revisited: Finite lives and cyclical variation in idiosyncratic risk. European Economic Review, 45(7):1311- 1339.
Strikwerda, J. C. (2004). Finite difference schemes and partial di erential equations, volume 88. Siam.
Swanson, E. T. (2012). Risk aversion and the labor margin in dynamic equilibrium models. American Economic Review, 102(4):1663-91.
Taylor, J. B. and Uhlig, H. (1990). Solving nonlinear stochastic growth models: a comparison of alternative solution methods. Journal of Business & Economic Statistics, 8(1):1-17.
Tol, R. S. (2006). The stern review of the economics of climate change: a comment. Energy & Environment, 17(6):977-981.
Tsai, J. and Wachter, J. A. (2015). Disaster risk and its implications for asset pricing. Annual Review of Financial Economics, 7:219-252.
Turnovsky, S. (1999). On the role of government in a stochastically growing economy, 1999. Journal of Economic Dynamics and Control, 104:275-298.
Turnovsky, S. J. (1993). Macroeconomic policies, growth, and welfare in a stochastic economy. International Economic Review, pages 953-981.
Turnovsky, S. J. (1995). Methods of macroeconomic dynamics. Massachusetts Institute of Technology Press, Massachusetts.
Turnovsky, Stephen J & Smith, W. T. (2006). Equilibrium consumption and precautionary savings in a stochastically growing economy. Journal of Economic Dynamics and Control, 30(2):243-278.
Venegas-Martínez, F. (2001). Temporary stabilization: a stochastic analysis. Journal of Economic Dynamics and Control, 25(9):1429-1449.
Venegas-Martínez, F. (2005). Política fiscal, estabilización de precios y mercados incompletos. Estudios económicos, pages 3-25.
Venegas-Martínez, F. (2009). Un modelo estocástico de equilibrio macroeconómico: acumulación de capital, inflación y política fiscal. Investigación económica, 68(268):69-114.
Venegas Martínez, F. and Polanco Gaytán, M. (2011). Macroeconomía estocástica.
Wälde, K. (2005). Endogenous growth cycles. International Economic Review, 46(3):867-894.
Wälde, K. (2011). Production technologies in stochastic continuous time models. Journal of Economic Dynamics and Control, 35(4):616-622.
Wang, C., Wang, N., and Yang, J. (2016). Optimal consumption and savings with stochastic income and recursive utility. Journal of Economic Theory, 165:292-331.
Wang, N. (2004). Precautionary saving and partially observed income. Journal of Monetary Economics, 51(8):1645-1681.
Wang, N. (2007). An equilibrium model of wealth distribution. Journal of Monetary Economics, 54(7):1882-1904.
Wanner, G. and Hairer, E. (1996). Solving ordinary differential equations II. Springer Berlin Heidelberg.
Weil, P. (1990). Nonexpected utility in macroeconomics. The Quarterly Journal of Economics, 105(1):29-42.
Winberry, T. (2018). A method for solving and estimating heterogeneous agent macro models.
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
bitstream.url.fl_str_mv https://repository.urosario.edu.co/bitstreams/82d0b779-efca-472b-9ae9-5eef52dc6548/download
https://repository.urosario.edu.co/bitstreams/0544dab4-2427-4277-8943-2786549a564d/download
https://repository.urosario.edu.co/bitstreams/c70f714e-8e18-4d16-b056-ff4850d58185/download
https://repository.urosario.edu.co/bitstreams/628d61e7-5c39-49d5-96db-cf35bdca6553/download
https://repository.urosario.edu.co/bitstreams/00af4f9b-833f-425e-99fa-383c60ea804f/download
bitstream.checksum.fl_str_mv 931167bd8ed3d35b262f8ebdb90d4468
fab9d9ed61d64f6ac005dee3306ae77e
217700a34da79ed616c2feb68d4c5e06
9b34a37547b04bf97ca0be1636cb7055
927ee7943768e4d98077573f89925604
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
_version_ 1814167722151378944
spelling Serrano Perdomo, Rafael Antonio80085368600Zambrano Jurado, Juan CarlosDoctor en EconomíaFull time7225216d-1aa0-4e16-9441-8b094338d55f6002021-04-29T16:58:51Z2021-04-29T16:58:51Z2021-04-22Este documento contiene tres aportes teóricos que se encuentran en la interacción entre los modelos estocásticos de equilibrio general, la macroeconomía dinámica y el control óptimo en tiempo continuo. En el primer capítulo, se estudia una solución analítica de dos modelos DSGE (Dynamic Stochastic General Equilibrium) en tiempo continuo con preferencias CRRA, tecnología tipo Cobb-Douglas y choques en la dinámica de acumulación de capital que combinan un proceso de difusión con saltos aleatorios asociados a eventos raros. El factor de tecnología puede tomar la forma de un proceso CIR con reversión a la media o un movimiento browniano geométrico. En el segundo capítulo, se propone la solución de un modelo de crecimiento neoclásico estocástico en tiempo continuo con un solo sector, de tipo Ramsey, con función de utilidad CRRA y tecnología tipo Cobb-Douglas, con acumulación de capital, efectividad y la fuerza del trabajo sujetos a choques exógenos que siguen procesos de difusión con saltos, dados por eventos raros. Finalmente, en el tercer capítulo, estudiamos un problema de agentes heterogéneos en tiempo continuo. Analizamos el efecto de los choques estocásticos con saltos en la dinámica y distribución del ingreso de los agentes, y su impacto en el consumo, el ahorro y la distribución conjunta de la riqueza e ingreso. En todos los modelos, el principio de programación dinámica, el teorema de veri cación y el método de diferencias nitas permitieron encontrar soluciones analíticas y numéricas de las ecuaciones de Hamilton-Jacobi-Bellman (HJB) y Kolmogorov-Forward (kF). Eso permite obtener las funciones de política óptimas para las variables de control, analizar en cada caso de forma analítica y numérica los efectos de este tipo de choques estocásticos sobre las decisiones económicas de los agentes; como también destacar que el empleo de modelos dinámicos, que siguen procesos de difusión con saltos, representan los fenómenos económicos de forma más realista y enriquecen el análisis en ambientes con riesgo e incertidumbre.This document contains three theoretical contributions that lie in the interplay between stochastic general equilibrium models, dynamic macroeconomics, and optimal control in continuous time. In the first chapter, we study an analytic solution of two continuous-time DSGE models with CRRA preferences, Cobb-Douglas type technology, and shocks in the capital accumulation dynamics that combine a diffusion process with random jumps associated with rare events. The technology factor can take the form of, either a mean-reverting CIR process or a geometric Brownian motion. In the second chapter, we study a stochastic continuous-time one-sector neoclassical growth model of Ramsey type with CRRA utility function and a Cobb-Douglas type technology, with capital accumulation, efectivity and the labor force subject to exogenous shocks that follow diffusion processes with jumps, given by rare events. Finally, in the third chapter, we study a heterogeneous agent problem in continuous time. We analyze the effect of stochastic shocks with jumps in the dynamics and distribution of agent's income, and their impact on consumption, saving and joint distribution of wealth and income. In all models, the dynamic programming principle, the veri cation theorem and the method of finite differences allowed us to find analytical and numerical solutions of the Hamilton-Jacobi-Bellman (HJB) and Kolmogorov-Forward (kF) equations. This allows obtaining the optimal policy functions for the control variables, analyzing in each case analytically and numerically the effects of this type of stochastic shocks on the economic decisions of the agents; as well as highlighting that the use of dynamic models, which follow diffusion processes with jumps, represent economic phenomena in a more realistic way and enrich the analysis in environments with risk and uncertainty.2021-06-12 01:01:01: Script de automatizacion de embargos. info:eu-repo/date/embargoEnd/2023-04-282021-04-29 12:10:02: Script de automatizacion de embargos. Correo recibido: Juan Carlos Zambrano Jurado Jue 29/04/2021 8:11 AM Cordial saludo. Les escribo para informales que coloqué la notificación de restringido en el repositorio de la CRAI, al documento de mi disertación Doctoral en Economía, " Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos ". Dado que el documento final se compone de tres artículos los cuales van a ser enviados próximamente a revistas indexadas para su posterior publicación, por tanto, el documento no puede ser de dominio público hasta no completar esa etapa. Agradezco su atención y colaboración. Atentamente, Juan Carlos Zambrano Jurado. Estudiante Doctorado en Economía. - Respuesta : Repositorio Institucional EdocUR Jue 29/04/2021 12:04 PM Respetado Doctor Juan Zambrano, reciba un cordial saludo, Hemos realizado la publicación de su documento: Un enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticos, el cual puede consultar en el siguiente enlace: https://repository.urosario.edu.co/handle/10336/31310 De acuerdo con su solicitud, el documento ha quedado embargado por 2 años hasta el 2023-04-29 en concordancia con las Políticas de Acceso Abierto de la Universidad. Si usted desea dejarlo con acceso abierto antes de finalizar dicho periodo o si por el contrario desea extender el embargo al finalizar este tiempo, puede enviar un correo a esta misma dirección realizando la solicitud. Tenga en cuenta que los documentos en acceso abierto propician una mayor visibilidad de su producción académica. Quedamos atentos a cualquier inquietud o sugerencia.220 pp.application/pdfhttps://doi.org/10.48713/10336_31310 https://repository.urosario.edu.co/handle/10336/31310spaUniversidad del RosarioFacultad de EconomíaDoctorado en EconomíaAtribución-NoComercial-SinDerivadas 2.5 ColombiaAbierto (Texto Completo)EL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma. PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe. EL AUTOR, autoriza a LA UNIVERSIDAD DEL ROSARIO, para que en los términos establecidos en la Ley 23 de 1982, Ley 44 de 1993, Decisión andina 351 de 1993, Decreto 460 de 1995 y demás normas generales sobre la materia, utilice y use la obra objeto de la presente autorización. -------------------------------------- POLITICA DE TRATAMIENTO DE DATOS PERSONALES. Declaro que autorizo previa y de forma informada el tratamiento de mis datos personales por parte de LA UNIVERSIDAD DEL ROSARIO para fines académicos y en aplicación de convenios con terceros o servicios conexos con actividades propias de la academia, con estricto cumplimiento de los principios de ley. Para el correcto ejercicio de mi derecho de habeas data cuento con la cuenta de correo habeasdata@urosario.edu.co, donde previa identificación podré solicitar la consulta, corrección y supresión de mis datos.http://creativecommons.org/licenses/by-nc-nd/2.5/co/http://purl.org/coar/access_right/c_abf2Achdou, Yves & Capuzzo-Dolcetta, I. (2010). Mean field games: numerical methods. SIAM Journal on Numerical Analysis, 48(3):1136-1162.Achdou, Y. (2013). Finite difference methods for mean field games. In Hamilton-Jacobi equations: approximations, numerical analysis and applications, pages 1-47. Springer.Achdou, Y., Buera, F. J., Lasry, J.-M., Lions, P.-L., and Moll, B. (2014). Partial differential equation models in macroeconomics. Phil. Trans. R. Soc. A, 372(2028):20130397.Achdou, Y., Han, J., Lasry, J.-M., Lions, P.-L., and Moll, B. (2017). Income and wealth distribution in macroeconomics: A continuous-time approach. Technical report, National Bureau of Economic Research.Achdou, Y. and Laurière, M. (2020). Mean field games and applications: Numerical aspects. arXiv preprint arXiv:2003.04444.Aiyagari, S. R. (1994). Uninsured idiosyncratic risk and aggregate saving. The Quarterly Journal of Economics, 109(3):659-684.Aruoba, S. B., Fernandez-Villaverde, J., and Rubio-Ramirez, J. F. (2006). Comparing solution methods for dynamic equilibrium economies. Journal of Economic dynamics and Control, 30(12):2477-2508.Barles, G. and Jakobsen, E. R. (2002). On the convergence rate of approximation schemes for hamilton-jacobi-bellman equations. ESAIM: Mathematical Modelling and Numerical Analysis, 36(1):33-54.Barles, G. and Souganidis, P. E. (1991). Convergence of approximation schemes for fully nonlinear second order equations. Asymptotic analysis, 4(3):271-283.Barro, R. and Sala-i Martin, X. (2004). Economic growth second edition.Barro, R. J. (2006). Rare disasters and asset markets in the twentieth century. The Quarterly Journal of Economics, 121(3):823-866.Barro, R. J. (2009). Rare disasters, asset prices, and welfare costs. American Economic Review, 99(1):243-64.Barro, R. J. and Jin, T. (2011). On the size distribution of macroeconomic disasters. Econometrica, 79(5):1567-1589.Barro, R. J. and Ursúa, J. F. (2012). Rare macroeconomic disasters. Annu. Rev. Econ., 4(1):83- 109.Baten, M., Kamil, A. A., et al. (2013). Optimal consumption in a stochastic ramsey model with cobb-douglas production function. International Journal of Mathematics and Mathematical Sciences, 2013.Baxter, M. and King, R. G. (1999). Measuring business cycles: approximate band-pass filters for economic time series. Review of economics and statistics, 81(4):575-593.Bellman, R. (1957). Dynamic programming (dp).Bernanke, B. S., Gertler, M., and Gilchrist, S. (1998). Credit market frictions and cyclical fluctuations. Handbook of Macroeconomics (North-Holland, Amsterdam).Bertsekas, D. P. (1987). Dynamic progrcmming: Deterministic and. Stochastic Models, pages 12-22.Bianchi, D., Büchner, M., and Tamoni, A. (2020). Bond risk premiums with machine learning. The Review of Financial Studies.Blanchard, O. (2009). The state of macro. Annu. Rev. Econ., 1(1):209-228.Boucekkine, R., Pintus, P. A., and Zou, B. (2018). Mean growth and stochastic stability in endogenous growth models. Economics Letters, 166:18-24.Brunnermeier, M. K. and Sannikov, Y. (2014). A macroeconomic model with a financial sector. American Economic Review, 104(2):379-421.Candler, G. V. et al. (1998). Finite-difference methods for continuous-time dynamic programming. QM&RBC Codes.Carroll, C. D., Hall, R. E., and Zeldes, S. P. (1992). The buffer-stock theory of saving: Some macroeconomic evidence. Brookings papers on economic activity, 1992(2):61-156.Castillo-Ramírez, C. E., Venegas-Martínez, F., and López-Herrera, F. (2016). Efectos de saltos inesperados en el gasto público y variables demográficas en el crecimiento económico. el caso mexicano con un enfoque garch con saltos (1936-2012). El trimestre económico, 83(332):725- 745.Chang, F.-R. (2004). Stochastic optimization in continuous time. Cambridge University Press.Chipeniuk, K., Katz, N. H., and Walker, T. (2014). Approximate aggregation in the neoclassical growth model with ideosyncratic shocks. arXiv preprint arXiv:1404.4665.Cont, R. and Voltchkova, E. (2005). A finite difference scheme for option pricing in jump diffusion and exponential lévy models. SIAM Journal on Numerical Analysis, 43(4):1596-1626.Cox, J. C., Ingersoll Jr, J. E., and Ross, S. A. (2005). A theory of the term structure of interest rates. In Theory of Valuation, pages 129-164. World Scientific.Cruz, J. H. R. (2012). Usos y limitaciones de la dinámica estocástica en el análisis macroeconómico convencional. In Optimización-Estocástica-Recursiva-Coherente-Sistémica y sus variantes (probabilidad, econometría y estadística aplicada), pages 25-54. ECORFAN.D'Avernas, Adrien & Vandeweyer, Q. (2019). A solution method for continuous-time models.d'Halluin, Y., Forsyth, P. A., and Vetzal, K. R. (2005). Robust numerical methods for contingent claims under jump diffusion processes. IMA Journal of Numerical Analysis, 25(1):87-112.Duarte, V. (2018). Machine learning for continuous-time economics. Available at SSRN 3012602.Dynan, K. E. (1993). How prudent are consumers? Journal of Political Economy, 101(6):1104-1113.Economics, V. (2013). The macroeconomics of climate change, report prepared for defra. Vivid Economics, London.Fankhauser, Samuel y Tol, R. S. (2005). On climate change and economic growth. Resource and Energy Economics, 27(1):1-17.Feicht, R. and Stummer, W. (2010). Complete closed-form solution to a stochastic growth model and corresponding speed of economic recovery. Technical report, IWQW Discussion Papers.Fernández-Corugedo, E. (2004). Teoria del consumo. Handbooks in Central Banking N, 23.Fernández-Villaverde, J. and Levintal, O. (2018). Solution methods for models with rare disasters. Quantitative Economics, 9(2):903-944.Fernández-Villaverde, J. and Rubio-Ramírez, J. F. (2005). Estimating dynamic equilibrium economies: linear versus nonlinear likelihood. Journal of Applied Econometrics, 20(7):891-910.Fernández-Villaverde, J., Rubio-Ramírez, J. F., and Schorfheide, F. (2016). Solution and estimation methods for dsge models. In Handbook of Macroeconomics, volume 2, pages 527-724.Fleming, W. H. and Soner, H. M. (2006). Controlled Markov processes and viscosity solutions, volume 25. Springer Science & Business Media.Fried, S. (2018). Climate policy and innovation: A quantitative macroeconomic analysis. American Economic Journal: Macroeconomics, 10(1):90-118.Frische, U. and Gröÿl, I. (2010). New keynesian dsge models and the is-lm paradigm. Technical report, IMK Working Paper.Galí, J. et al. (2008). Introduction to monetary policy, inflation, and the business cycle: An introduction to the new keynesian framework. Introductory Chapters.Gaspar, J. and Judd, K. L. (1997). Solving large-scale rational-expectations models. Macroeconomic Dynamics, 1(1):45-75.Gillingham, K., Nordhaus, W. D., Anthoff, D., Blanford, G., Bosetti, V., Christensen, P., McJeon, H., Reilly, J., and Sztorc, P. (2015). Modeling uncertainty in climate change: A multi-model comparison. Technical report, National Bureau of Economic Research.Giulano, P. and Turnovsky, S. (2003). Intertemporal substitution risk aversion and economic performance in a stochastically growing economy. Journal of International Money and Finance, 22(4):529-556.Gomes, D. A., Nurbekyan, L., and Pimentel, E. (2015). Economic models and mean-field games theory. In 30o Co16quio Brasileiro de Matemática.[30th Brazilian Mathematics Colloquium].Gourio, F. (2012). Disaster risk and business cycles. American Economic Review, 102(6):2734-66.Greenwood, J., Hercowitz, Z., and Huffman, G. W. (1988). Investment, capacity utilization, and the real business cycle. The American Economic Review, pages 402-417.Group, W. B. (2018). Iraq Reconstruction and Investment: Damage and Needs Assessment of Affected Governorates. World Bank.Guvenen, F. (2011). Macroeconomics with heterogeneity: A practical guide. Technical report, National Bureau of Economic Research.Guvenen, F., Karahan, F., Ozkan, S., and Song, J. (2015). What do data on millions of us workers reveal about life-cycle earnings risk? Technical report, National Bureau of Economic Research.Hallegate, S y Przyluski, V. (2010). The economic of floods: Concepts and methods. World Bank Policy Research Working Paper, 5507.Hambel, C., Kraft, H., and van der Ploeg, R. (2020). Asset diversification versus climate action.Hanson, F. B. (2007). Applied stochastic processes and control for Jump-diffusions: modeling, analysis, and computation, volume 13. Siam.Heathcote, J., Storesletten, K., and Violante, G. L. (2009). Quantitative macroeconomics with heterogeneous households. Annu. Rev. Econ., 1(1):319-354.Heathcote, J., Storesletten, K., and Violante, G. L. (2010). The macroeconomic implications of rising wage inequality in the united states. Journal of political economy, 118(4):681-722.Heckman, J. J. (2001). Micro data, heterogeneity, and the evaluation of public policy: Nobel lecture. Journal of political Economy, 109(4):673-748.Hernández, G. (2010). El método de diferencias finitas.Hernández-Lerma, O. (1989). Adaptive markov control processes.Hiraguchi, R. (2014). A note on the analytical solution to the neoclassical growth model with leisure. Macroeconomic Dynamics, 18(2):473-479.Hirsa, A. (2016). Computational methods in finance. CRC Press.Hodrick, R. J. and Prescott, E. C. (1997). Postwar us business cycles: an empirical investigation. Journal of Money, credit, and Banking, pages 1-16.Huggett, M. (1993). The risk-free rate in heterogeneous-agent incomplete-insurance economies. Journal of economic Dynamics and Control, 17(5-6):953-969.Ireland, P. N. (2004). A method for taking models to the data. Journal of Economic Dynamics and Control, 28(6):1205-1226.Isoré, M. and Szczerbowicz, U. (2017). Disaster risk and preference shifts in a new keynesian model. Journal of Economic Dynamics and Control, 79:97-125.Jacobson, L. S., LaLonde, R. J., and Sullivan, D. G. (1993). Earnings losses of displaced workers. The American economic review, pages 685-709.Judd, K. L. (1996). Approximation, perturbation, and projection methods in economic analysis. Handbook of computational economics, 1:509-585.Judd, K. L. (1998). Numerical methods in economics mit press books.Kalman, R. (1963). The theory of optimal control and the calculus of variations. Mathematical optimization techniques, pages 309-331.Kaplan, G., Moll, B., and Violante, G. L. (2018). Monetary policy according to hank. American Economic Review, 108(3):697-743.Kendrick, D. (1976). Applications of control theory to macroeconomics. In Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190. NBER.Kendrick, D. A. (1981). Stochastic control for economic models. McGraw-Hill Companies.Khan, Aubhik y Thomas, J. K. (2008). Idiosyncratic shocks and the role of nonconvexities in plant and aggregate investment dynamics. Econometrica, 76(2):395-436.Kimball, M. S. (1990). Precautionary saving and the marginal propensity to consume. Technical report, National Bureau of Economic Research.King, R. G., Plosser, C. I., and Rebelo, S. T. (1988). Production, growth and business cycles: I. the basic neoclassical model. Journal of monetary Economics, 21(2-3):195-232.King, R. G. and Rebelo, S. T. (1999). Resuscitating real business cycles. Handbook of macroeconomics, 1:927-1007.Kompas, T. and Chu, L. (2012). Comparing approximation techniques to continuous-time stochastic dynamic programming problems: Applications to natural resource modelling. Environmental modelling & software, 38:1-12.Krusell, Per y Smith, J. A. A. (1998). Income and wealth heterogeneity in the macroeconomy. Journal of political Economy, 106(5):867-896Kydland, F. E. and Prescott, E. C. (1982). Time to build and aggregate fluctuations. Econometrica: Journal of the Econometric Society, pages 1345-1370.Lasry, J.-M., Lions, P.-L., and Guéant, O. (2008). Application of mean field games to growth theory.Lee, J.-J. and Sawada, Y. (2010). Precautionary saving under liquidity constraints: Evidence from rural pakistan. Journal of Development Economics, 91(1):77-86.Leland, H. E. (1978). Saving and uncertainty: The precautionary demand for saving. In Uncertainty in economics, pages 127-139. Elsevier.Li, Z., Qiao, Z., and Tang, T. (2017). Numerical solution of di erential equations: introduction to finite difference and finite element methods. Cambridge University Press.Long Jr, J. B. and Plosser, C. I. (1983). Real business cycles. Journal of political Economy, 91(1):39-69.Merton, R. C. (1971). Optimum consumption and portfolio rules in a continuous-time model. In Stochastic Optimization Models in Finance, pages 621-661. Elsevier.Merton, R. C. (1975). An asymptotic theory of growth under uncertainty. The Review of Economic Studies, 42(3):375-393.Merton, R. C. and Samuelson, P. A. (1992). Continuous-time finance.Michael, W. (2003). Interest and prices: Foundations of a theory of monetary policy.Miranda, M. J. and Fackler, P. L. (2004). Applied computational economics and finance. MIT press.Moll, B. (2014). Productivity losses from financial frictions: Can self-financing undo capital misallocation? American Economic Review, 104(10):3186-3221.Nakamura, E., Steinsson, J., Barro, R., and Ursúa, J. (2013). Crises and recoveries in an empirical model of consumption disasters. American Economic Journal: Macroeconomics, 5(3):35-74.Nuño, Galo & Moll, B. (2017). Social optima in economies with heterogeneous agents. Review of Economic Dynamics.Nuño, G. (2013). Optimal control with heterogeneous agents in continuous time.Nuño, G. (2015). Continuous time methods for economics and finance. Review of Economics and Statistics, 51(3):247-257.OIT, O. (2017). Perspectivas sociales y del empleo en el mundo. tendencias 2017.Okahata, N. et al. (2018). An alternative solution method for continuous-time heterogeneous agent models with aggregate shocks. Technical report, Mimeo New York.Øksendal, B. (2006). A universal optimal consumption rate for an insider. Mathematical Finance, 16(1):119-129.Oksendal, B. and Sulem, A. (2009). Applied control of jump diffusions.Parra-Alvarez, J. C. (2017). A comparison of numerical methods for the solution of continuoustime dsge models. Macroeconomic Dynamics, pages 1-29.Parra-Alvarez, J. C., Posch, O., and Wang, M.-C. (2017a). Identification and estimation of heterogeneous agent models: A likelihood approach.Parra-Alvarez, J. C., Posch, O., and Wang, M.-C. (2017b). Identification and estimation of heterogeneous agent models: A likelihood approach.Phillips, A. W. (1954). Stabilisation policy in a closed economy. The Economic Journal, 64(254):290-323.Phillips, A. W. (1957). Stabilisation policy and the time-forms of lagged responses. The Economic Journal, 67(266):265-277.Pindyck, R. S. and Wang, N. (2013). The economic and policy consequences of catastrophes. American Economic Journal: Economic Policy, 5(4):306-39.Pontryagin, L. (1962). Ordinary difeerential equations. translated from the russian by leonas kacinskas and walter b. counts. Reading: Addison-Wesley Publishing Company.Posch, O. (2009). Structural estimation of jump-diffusion processes in macroeconomics. Journal of Econometrics, 153(2):196-210.Posch, O. (2011). Risk premia in general equilibrium. Journal of Economic Dynamics and Control, 35(9):1557-1576.Posch, Olaf y Trimborn, T. (2013). Numerical solution of dynamic equilibrium models under poisson uncertainty. Journal of Economic Dynamics and Control, 37(12):2602-2622.Prescott, E. C. (1971). Adaptive decision rules for macroeconomic planning. Economic Inquiry, 9(4):369-378.Preston, Bruce & Roca, M. (2007). Incomplete markets, heterogeneity and macroeconomic dynamics. Technical report, National Bureau of Economic Research.Ramirez, J., H. E. (2016). Optimal decisions in illiquid hedge funds. PhD thesis, The University of Manchester (United Kingdom).Riascos, A. J. V. (2009). Métodos matemáticos y computacionales en macroeconomía. Universidad de los Andes, Fac. de Economía, CEDE, Ediciones Uniandes.Rietz, T. A. (1988). The equity risk premium a solution. Journal of monetary Economics, 22(1):117-131.Rotemberg, J. J. and Woodford, M. (1997). An optimization-based econometric framework for the evaluation of monetary policy. NBER macroeconomics annual, 12:297-346.Scheidegger, S. and Bilionis, I. (2019). Machine learning for high-dimensional dynamic stochastic economies. Journal of Computational Science, 33:68-82.Schmitt-Grohé, S. and Uribe, M. (2004). Solving dynamic general equilibrium models using a second-order approximation to the policy function. Journal of economic dynamics and control, 28(4):755-775.Scott, B. (1999). Computational methods for the study of dynamic economies. Oxford University Press.Smith, W. T. (2006). An analytical solution to the ramsey model. Contributions to Macroeconomics, 6(1):1-28.Smith, W. T. (2007). Inspecting the mechanism exactly: a closed-form solution to a stochastic growth model. The BE Journal of Macroeconomics, 7(1).Steger, T. M. (2005). Stochastic growth under wiener and poisson uncertainty. Economics Letters, 86(3):311-316.Stern, Nicholas y Stern, N. H. (2007). The economics of climate change: the Stern review. cambridge University press.Stern, V., Peters, S., Bakhshi, V., et al. (2010). The stern review. Government Equalities Offce, Home O ce.Storesletten, K., Telmer, C. I., and Yaron, A. (2001). The welfare cost of business cycles revisited: Finite lives and cyclical variation in idiosyncratic risk. European Economic Review, 45(7):1311- 1339.Strikwerda, J. C. (2004). Finite difference schemes and partial di erential equations, volume 88. Siam.Swanson, E. T. (2012). Risk aversion and the labor margin in dynamic equilibrium models. American Economic Review, 102(4):1663-91.Taylor, J. B. and Uhlig, H. (1990). Solving nonlinear stochastic growth models: a comparison of alternative solution methods. Journal of Business & Economic Statistics, 8(1):1-17.Tol, R. S. (2006). The stern review of the economics of climate change: a comment. Energy & Environment, 17(6):977-981.Tsai, J. and Wachter, J. A. (2015). Disaster risk and its implications for asset pricing. Annual Review of Financial Economics, 7:219-252.Turnovsky, S. (1999). On the role of government in a stochastically growing economy, 1999. Journal of Economic Dynamics and Control, 104:275-298.Turnovsky, S. J. (1993). Macroeconomic policies, growth, and welfare in a stochastic economy. International Economic Review, pages 953-981.Turnovsky, S. J. (1995). Methods of macroeconomic dynamics. Massachusetts Institute of Technology Press, Massachusetts.Turnovsky, Stephen J & Smith, W. T. (2006). Equilibrium consumption and precautionary savings in a stochastically growing economy. Journal of Economic Dynamics and Control, 30(2):243-278.Venegas-Martínez, F. (2001). Temporary stabilization: a stochastic analysis. Journal of Economic Dynamics and Control, 25(9):1429-1449.Venegas-Martínez, F. (2005). Política fiscal, estabilización de precios y mercados incompletos. Estudios económicos, pages 3-25.Venegas-Martínez, F. (2009). Un modelo estocástico de equilibrio macroeconómico: acumulación de capital, inflación y política fiscal. Investigación económica, 68(268):69-114.Venegas Martínez, F. and Polanco Gaytán, M. (2011). Macroeconomía estocástica.Wälde, K. (2005). Endogenous growth cycles. International Economic Review, 46(3):867-894.Wälde, K. (2011). Production technologies in stochastic continuous time models. Journal of Economic Dynamics and Control, 35(4):616-622.Wang, C., Wang, N., and Yang, J. (2016). Optimal consumption and savings with stochastic income and recursive utility. Journal of Economic Theory, 165:292-331.Wang, N. (2004). Precautionary saving and partially observed income. Journal of Monetary Economics, 51(8):1645-1681.Wang, N. (2007). An equilibrium model of wealth distribution. Journal of Monetary Economics, 54(7):1882-1904.Wanner, G. and Hairer, E. (1996). Solving ordinary differential equations II. Springer Berlin Heidelberg.Weil, P. (1990). Nonexpected utility in macroeconomics. The Quarterly Journal of Economics, 105(1):29-42.Winberry, T. (2018). A method for solving and estimating heterogeneous agent macro models.instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURModelos de agentes heterogéneosProcesos de difusión con saltos aleatoriosEcuaciones de Hamilton-Jacobi- Bellman y kolmogorov-ForwardModelos económicos de equilibrio general aplicadoModelos EGDE (equilibrio general dinámico estocástico) en tiempo continuoControl óptimo estocástico en modelos EconomicosMétodo de diferencias finitas en modelación económicaAnálisis de riesgo de desastres económicoMacroeconomía & temas relacionados339600Heterogeneous agent modelsDiffusion processes with random hopsHamilton-Jacobi- Bellman and kolmogorov-Forward equationsApplied General Equilibrium Economic ModelsContinuous-Time DSGE Models (Stochastic Dynamic General Equilibrium)Optimal stochastic control in economic modelsFinite difference method in economic modelingEconomic disaster risk analysisUn enfoque teórico en tiempo continuo para modelos de equilibrio general dinámicos estocásticosA theoretical approach in continuous time to dynamic general equilibrium models stochasticsdoctoralThesisMonografíaTesis de doctoradohttp://purl.org/coar/resource_type/c_db06ORIGINALZambranoJurado-JuanCarlos-2021.pdfZambranoJurado-JuanCarlos-2021.pdfDisertación Doctoralapplication/pdf10373473https://repository.urosario.edu.co/bitstreams/82d0b779-efca-472b-9ae9-5eef52dc6548/download931167bd8ed3d35b262f8ebdb90d4468MD51LICENSElicense.txtlicense.txttext/plain1475https://repository.urosario.edu.co/bitstreams/0544dab4-2427-4277-8943-2786549a564d/downloadfab9d9ed61d64f6ac005dee3306ae77eMD52CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repository.urosario.edu.co/bitstreams/c70f714e-8e18-4d16-b056-ff4850d58185/download217700a34da79ed616c2feb68d4c5e06MD53TEXTZambranoJurado-JuanCarlos-2021.pdf.txtZambranoJurado-JuanCarlos-2021.pdf.txtExtracted texttext/plain363998https://repository.urosario.edu.co/bitstreams/628d61e7-5c39-49d5-96db-cf35bdca6553/download9b34a37547b04bf97ca0be1636cb7055MD54THUMBNAILZambranoJurado-JuanCarlos-2021.pdf.jpgZambranoJurado-JuanCarlos-2021.pdf.jpgGenerated Thumbnailimage/jpeg3302https://repository.urosario.edu.co/bitstreams/00af4f9b-833f-425e-99fa-383c60ea804f/download927ee7943768e4d98077573f89925604MD5510336/31310oai:repository.urosario.edu.co:10336/313102021-06-12 01:01:09.374998http://creativecommons.org/licenses/by-nc-nd/2.5/co/Atribución-NoComercial-SinDerivadas 2.5 Colombiahttps://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.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

Publicaciones similares