Un modelo interdisciplinario para la macroeconomía

An interdisciplinary model for macroeconomics

Contenido principal del artículo

Andrew G. Haldane


La modelación macroeconómica está bajo intenso escrutinio desde la gran crisis financiera, que dejó al descubierto los graves defectos de la metodología utilizada para entender la economía en su conjunto. Se critican los supuestos empleados en los modelos dominantes, en particular que los agentes económicos son homogéneos y optimizadores y que la economía se equilibra. Este escrito explora un enfoque interdisciplinario de modelación macroeconómica con técnicas tomadas de otras ciencias, y examina la modelación basada en agentes como ejemplo de esas técnicas. Los modelos basados en agentes complementan los enfoques existentes y son adecuados para responder preguntas macroeconómicas donde la complejidad, la heterogeneidad, las redes y las heurísticas cumplen un papel importante.

Palabras clave:


Los datos de descargas todavía no están disponibles.

Detalles del artículo

Referencias (VER)

Aad, G., Abajyan, T. et al. (2012). Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC. Physics Letters B, 716(1), 1-29.

Abbott, B. P., Abbott, R. et al. (2016). Observation of gravitational waves from a binary black hole merger. Physical review letters, 116(6), 061102.

Abel, A. B. (1990). Asset prices under habit formation and catching up with the Joneses. NBER technical report. Cambridge, Mass.

Aikman, D., Galesic, M. et al. (2014). Taking uncertainty seriously: simplicity versus complexity in financial regulation. Bank of England financial stability paper 28. Londres.

Alfarano, S., Lux, T. y Wagner, F. (2005). Estimation of agent-based models: the case of an asymmetric herding model. Computational Economics, 26(1), 19-49.

Alfi, V., Cristelli, M. et al. (2009). Minimal agent based model for financial markets I. The European Physical Journal B, 67(3), 385-397.

Arber, T., Bennett, K. et al. (2015). Contemporary particle-in-cell approach to laser-plasma modelling. Plasma Physics and Controlled Fusion, 57(11), 113001.

Arinaminpathy, N., Kapadia, S. y May, R. (2012). Size and complexity in model financial systems. Proceedings of the National Academy of Sciences, 109(45), 18338-18343.

Arthur, W. B. (2006). Out-of-equilibrium economics and agent-based modeling. En L. Tesfatsion y K. Judd (eds.), Handbook of computational economics, v. 2 (pp. 1551-1564). Ámsterdam: Elsevier.

Ascari, G., Fagiolo, G. y Roventini, A. (2015). Fat-tail distributions and business-cycle models. Macroeconomic Dynamics, 19(02), 465-476.

Ashraf, Q., Gershman, B. y Howitt, P. (2017). Banks, market organization, and macroeconomic performance: an agent-based computational analysis. Journal of Economic Behavior & Organization, 135, 143-180.

Assenza, T., Brock, W. A. y Hommes, C. H. (2017). Animal spirits, heterogeneous expectations, and the amplification and duration of crises. Economic Inquiry, 55(1), 542-564.

Assenza, T., Gatti, D. D. y Grazzini, J. (2015). Emergent dynamics of a macroeconomic agent based model with capital and credit. Journal of Economic Dynamics and Control, 50, 5-28.

Assenza, T., Gatti, D. D. et al. (2016). Heterogeneous firms and international trade: The role of productivity and financial fragility. CESifo working paper series 5959. Múnich: CESifo Group.

Auclert, A. (2015). Monetary policy and the redistribution channel. 2015 meeting papers 381, Society for Economic Dynamics.

Ausloos, M., Miskiewicz, J. y Sanglier, M. (2004). The durations of recession and prosperity: does their distribution follow a power or an exponential law? Physica A: Statistical Mechanics and its Applications, 339(3), 548-558.

Avian Flu Working Group. (2006). The global economic and financial impact of an avian flu pandemic and the role of the IMF. Technical report, IMF.

Bagehot, W. (1873). Lombard Street: A description of the money market. Londres: Henry S. King and Co.

Baker, S. R., Bloom, N. y Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593-1636.

Baptista, R., Farmer, J. D. et al. (2016). Macroprudential policy in an agent-based model of the UK housing market. Staff working paper 619. Londres: Bank of England.

Bardoscia, M., Battiston, S. et al. (2017). Pathways towards instability in financial networks. Nature Communications, 8(14416).

Bartelsman, E. J. y Doms, M. (2000). Understanding productivity: Lessons from longitudinal microdata. Journal of Economic literature, 38(3), 569-594.

Batten, S., Sowerbutts, R. et al. (2016). Let’s talk about the weather: the impact of climate change on central banks. Staff working paper 603. Londres: Bank of England.

Battiston, S., Gatti, D. D. et al.. (2007). Credit chains and bankruptcy propagation in production networks. Journal of Economic Dynamics and Control, 31(6), 2061-2084.

Bernanke, B. (2004). The great moderation. Discurso en las reuniones de la Eastern Economic Association, 20 de febrero, Washington DC.

Bjørnland, H. C., Gerdrup, K. et al. (2012). Does forecast combination improve Norges Bank inflation forecasts? Oxford Bulletin of Economics and Statistics, 74(2), 163-179.

Blanchard, O. (2017). On the need for (at least) five classes of macro models, [https: //piie.com/blogs/realtime-economic-issues-watch/need-least-five-classes-macro-models].

Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99(supl. 3), 7280-7287.

Bottazzi, G. y Secchi, A. (2003). Common properties and sectoral specificities in the dynamics of US manufacturing companies. Review of Industrial Organization, 23(3-4), 217-232.

Bottazzi, G. y Secchi, A. (2006). Explaining the distribution of firm growth rates. RAND Journal of Economics, 37(2), 235-256.

Braun-M., K., Liu, Z. y Turrell, A. E. (2016). An agent-based model of dynamics in corporate bond trading. Staff working paper 592. Londres: Bank of England.

Brayton, F. y Tinsley, P. A. (1996). A guide to FRB/US: A macroeconomic model of the United States. FEDS paper 96-42. Washington DC. Federal Reserve Board.

Bronk, R. (2011). Uncertainty, modelling monocultures and the financial crisis. The business economist, 42(2), 5-18.

Bronk, R. y Jacoby, W. (2016). Uncertainty and the dangers of monocultures in regulation, analysis, and practice. MPIfG discussion paper 16/6, Colonia: Max Planck Institute.

Bulanov, S. y Khoroshkov, V. (2002). Feasibility of using laser ion accelerators in proton therapy. Plasma Physics Reports, 28(5), 453-456.

Burgess, S., Fernández-C., E. et al. (2013). The Bank of England’s forecasting platform: COMPASS, MAPS, EASE and the suite of models. Staff working paper 471. Londres: Bank of England.

Burke, M., Hsiang, S. M. y Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239.

Burns, A. F. y Mitchell, W. C. (1946). Measuring business cycles. Cambridge, Mass: NBER.

Caiani, A., Godin, A. et al. (2016). Agent based-stock flow consistent macroeconomics: Towards a benchmark model. Journal of Economic Dynamics and Control, 69(C), 375-408.

Campbell, J. Y. y Mankiw, N. G. (1989). Consumption, income, and interest rates: Reinterpreting the time series evidence. NBER macroeconomics annual, 4, 185-216.

Card, D. y DellaVigna, S. (2013). Nine facts about top journals in economics. Journal of Economic Literature, 51(1), 144-161.

Carney, M. (2017). Reflecting diversity, choosing inclusion. Discurso Bank of England. Londres.

Carroll, C. D. (1997). Buffer-stock saving and the life cycle/permanent income hypothesis. Quarterly Journal of economics, 112(1), 1-55.

Carroll, C. D. (2009). Precautionary saving and the marginal propensity to consume out of permanent income. Journal of Mmonetary Economics, 56(6), 780-790.

Carroll, C. D. y Kimball, M. S. (1996). On the concavity of the consumption function. Econometrica, 64(4), 981-992.

Carter, N., Levin, S. et al. (2015). Modeling tiger population and territory dynamics using an agent-based approach. Ecological Modelling, 312, 347-362.

Castaldi, C. y Dosi, G. (2009). The patterns of output growth of firms and countries: Scale invariances and scale specificities. Empirical Economics, 37(3), 475-495.

Chakraborty, C. y Joseph, A. (2017). Machine learning at central banks. Staff working paper 674. Londres: Bank of England.

Chan, C. K. y Steiglitz, K. (2008). An agent-based model of a minimal economy. Department of Computer Science. Princeton: Princeton University.

Cincotti, S., Raberto, M. y Teglio, A. (2010). Credit money and macroeconomic instability in the agent-based model and simulator Eurace. Economics discussion papers 2010-4, Kiel Institute for the World Economy (IfW).

Colander, D., Goldberg, M. et al. (2009). The financial crisis and the systemic failure of the economics profession. Critical Review, 21(2-3), 249-267.

Colussi, T. (2018). Social ties in academia: A friend is a treasure. Review of Economics and Statistics, 100(1), 45-50.

Cooper, D. y Dynan, K. (2016). Wealth effects and macroeconomic dynamics. Journal of Economic Surveys, 30(1), 34-55.

Cutler, D. M., Poterba, J. M. y Summers, L. H. (1989). What moves stock prices? The Journal of Portfolio Management, 15(3), 4-12.

Davis, M., Efstathiou, G. et al. (1985). The evolution of large-scale structure in a universe dominated by cold dark matter. The Astrophysical Journal, 292, 371-394.

Dawid, H., Gemkow, S. et al. M. (2012). The eurace@ unibi model: An agent-based macroeconomic model for economic policy analysis. Bielefeld working papers in economics and management 05-2012.

Dawid, H., Harting, P. y Neugart, M. (2014). Economic convergence: Policy implications from a heterogeneous agent model. Journal of Economic Dynamics and Control, 44(C), 54-80.

De Grauwe, P. (2010). Top-down versus bottom-up macroeconomics. CESifo Economic Studies, 56(4), 465-497.

Degli Atti, M. L. C., Merler, S. et al. (2008). Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PloS one, 3(3), e1790.

Di Guilmi, C., Gallegati, M. y Ormerod, P. (2004). Scaling invariant distributions of firms’ exit in OECD countries. Physica A: Statistical Mechanics and its Applications, 334(1), 267-273.

Doms, M. y Dunne, T. (1998). Capital adjustment patterns in manufacturing plants. Review of Economic Dynamics, 1(2), 409-429.

Dosi, G. (2007). Statistical regularities in the evolution of industries. A guide through some evidence and challenges for the theory. En F. Malerba y S. Brusoni (eds.), Perspectives on innovation (pp.153-186). Nueva York: Cambridge University Press.

Dosi, G., Fagiolo, G. et al. (2015). Fiscal and monetary policies in complex evolving economies. Journal of Economic Dynamics and Control, 52(C), 166-189.

Dosi, G., Fagiolo, G. y Roventini, A. (2010). Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles. Journal of Economic Dynamics and Control, 34(9), 1748-1767.

Elmendorf, D. W. et al. (1996). The effect of interest-rate changes on household saving and consumption: A survey. FEDS paper 96-27. Washington DC. Federal Reserve Board.

Epstein, J. M. (1999). Agent-based computational models and generative social science. Complexity, 4(5), 41-60.

Epstein, J. M. (2006). Remarks on the foundations of agent-based generative social science. En L. Tesfatsion y K. Judd (eds.), Handbook of computational economics, v. 2 (pp.1585-1604). Ámsterdam: Elsevier.

Erlingsson, E. J., Teglio, A. et al. (2014). Housing market bubbles and business cycles in an agent-based credit economy. Economics: The Open-Access, Open-Assessment E-Journal, 8(2014-8), 1-42.

Ernest, N., Carroll, D. et al. (2016). Genetic fuzzy based artificial intelligence for unmanned combat aerial vehicle control in simulated air combat missions. Journal of Defense Management, 6(144), 2167-0374.

Estrella, A. y Fuhrer, J. C. (2002). Dynamic inconsistencies: Counterfactual implications of a class of rational-expectations models. American Economic Review, 92(4), 1013-1028.

Ezrachi, A. y Stucke, M. (2016). Virtual competition. The promise and perils of algorithmic-driven economy. Cambridge, Mass.: Harvard University Press.

Fagiolo, G., Napoletano, M. y Roventini, A. (2008). Are output growth-rate distributions fat-tailed? Some evidence from OECD countries. Journal of Applied Econometrics, 23(5), 639-669.

Fagiolo, G. y Roventini, A. (2012). Macroeconomic policy in DSGE and agent-based models. Revue de l’OFCE, 5(124), 67-116.

Fagiolo, G. y Roventini, A. (2017). Macroeconomic policy in DSGE and agent-based models Redux: New developments and challenges ahead. Journal of Artificial Societies and Social Simulation, 20(1), 1-37.

Fair, R. C. (2012). Has macro progressed? Journal of Macroeconomics, 34(1), 2-10.

Foos, D., Norden, L. y Weber, M. (2010). Loan growth and riskiness of banks. Journal of Banking & Finance, 34(12), 2929- 2940.

Fourcade, M., Ollion, E. y Algan, Y. (2015). The superiority of economists. Revista de Economía Institutional, 17(33), 13-43.

Franke, R. y Westerhoff, F. (2012). Structural stochastic volatility in asset pricing dynamics: Estimation and model contest. Journal of Economic Dynamics and Control, 36(8), 1193-1211.

Friedman, J., Hastie, T. y Tibshirani, R. (2001). The elements of statistical learning, v. 1. Nueva York: Springer.

Friedman, M. (1957). A theory of the consumption function. Princeton: Princeton University Press.

Fukac, M. y Pagan, A. (2006). Issues in adopting DSGE models for use in the policy process. Australian National University, CAMA working paper 10: 2006.

Gabaix, X. (2011). The granular origins of aggregate fluctuations. Econometrica, 79(3), 733-772.

Gabaix, X. (2016). Behavioral macroeconomics via sparse dynamic programming. NBER technical report. Cambridge, Mass.

Gaffeo, E., Di Guilm. et al. (2012). On the mean/variance relationship of the firm size distribution: Evidence and some theory. Ecological Complexity, 11, 109-117.

Gai, P., Haldane, A. y Kapadia, S. (2011). Complexity, concentration and contagion. Journal of Monetary Economics, 58(5), 453-470.

Gai, P. y Kapadia, S. (2010). Contagion in financial networks. Proceedings of the Royal Society, 466(2120), 2401-2423.

Gatti, D. D. y Desiderio, S. (2015). Monetary policy experiments in an agent-based model with financial frictions. Journal of Economic Interaction and Coordination, 10(2), 265-286.

Geanakoplos, J., Axtell, R. et al. (2012). Getting at systemic risk via an agent-based model of the housing market. American Economic Review, 102(3), 53-58.

Gibson, B. (2007). A multi-agent systems approach to microeconomic foundations of macro. Technical report working paper. Amherst: University of Massachusetts.

Gigerenzer, G. y Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in cognitive science, 1(1), 107-143.

Gode, D. K. y Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of Political Economy, 101(1), 119-137.

Godley, W. y Lavoie, M. (2007). Monetary economics. Basingstoke: Palgrave Macmillan.

Gualdi, S., Tarzia, M. et al. (2015). Tipping points in macroeconomic agent-based models. Journal of Economic Dynamics and Control, 50, 29-61.

Guerini, M. y Moneta, A. (2017). A method for agent-based models validation. Journal of Economic Dynamics and Control, 82(C), 125-141.

Guerini, M., Napoletano, M. y Roventini, A. (2016). No man is an island: The impact of heterogeneity and local interactions on macroeconomic dynamics, [https://ssrn.com/abstract=2787164].

Guvenen, F. (2011). Macroeconomics with heterogeneity: A practical guide. NBER technical report. Cambridge, Mass.

Haldane, A. G. (2016). The dappled world. Discurso, Bank of England. Londres.

Haldane, A. G. y Madouros, V. (2012). El perro y el frisbee. Revista de Economía Institutional, 14(27), 13-56.

Haldane, A. G. y May, R. M. (2011). Systemic risk in banking ecosystems. Nature, 469(7330), 351-355.

Hamermesh, D. S. (2013). Six decades of top economics publishing: Who and how? Journal of Economic Literature, 51(1), 162-172.

Hausman, D. M. (1992). The inexact and separate science of economics. Gateshead, UK: Cambridge University Press.

Heathcote, J. (2005). Fiscal policy with heterogeneous agents and incomplete markets. Review of Economic Studies, 72(1), 161-188.

Heppenstall, A. J., Crooks, A. T. et al. (2011). Agent-based models of geographical systems. Dordrecht: Springer.

Hills, S., Thomas, R. y Dimsdale, N. (2016). Three centuries of data version 2.3, [http: //www.bankofengland.co. uk/research/Pages/onebank/threecenturies.aspx].

Hommes, C. H. (2006). Heterogeneous agent models in economics and finance. En L. Tesfatsion y K. Judd (eds.), Handbook of computational economics, v. 2 (pp. 1109-1186). Ámsterdam: Elsevier.

Hong, H. y Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. Journal of finance, 54(6), 2143-2184.

Jacobs, J. A. (2014). In defense of disciplines: Interdisciplinarity and specialization in the research university. Chicago: University of Chicago Press.

Jaimovich, N. y Floetotto, M. (2008). Firm dynamics, markup variations, and the business cycle. Journal of Monetary Economics, 55(7), 1238-1252.

Jawadi, F. y Sousa, R. M. (2014). The relationship between consumption and wealth: A quantile regression approach. Revue d’économie politique, 124(4), 639-652.

Kaplan, G., Moll, B. y Violante, G. L. (2016). Monetary policy according to HANK. NBER technical report. Cambridge, Mass.

Keogh-B., M. R., Wren-L., S. et al. (2010). The possible macroeconomic impact on the UK of an influenza pandemic. Health economics, 19(11), 1345-1360.

Keynes, J. M. (1924). Alfred Marshall, 1842-1924. Economic Journal, 34(135), 311-372.

Keynes, J. M. (1936). General theory of employment, interest and money. Londres: Palgrave Macmillan.

Kindleberger, C. P. (2001). Manias, panics, and crashes: A history of financial crises. Hoboken, NJ: John Wiley & Sons.

Kirman, A. P. (1992). Whom or what does the representative individual represent? Journal of Economic Perspectives, 6(2), 117-136.

Knight, F. H. (2012). Risk, uncertainty and profit. North Chelmsford, Mass.: Courier Corporation.

Krugman, P. (2011). The profession and the crisis. Eastern Economic Journal, 37(3), 307-312.

Kumhof, M., Ranciere, R. y Winant, P. (2015). Inequality, leverage, and crises. American Economic Review, 105(3), 1217-1245.

Kuznets, S. y Murphy, J. T. (1966). Modern economic growth: Rate, structure, and spread, v. 2. New Haven: Yale University Press.

Kydland, F. E. y Prescott, E. C. (1982). Time to build and aggregate fluctuations. Econometrica, 50(6), 1345-1370.

Laeven, L. y Valencia, F. (2013). Systemic banking crises database. IMF Economic Review, 61(2), 225-270.

Lamperti, F., Dosi, G. et al. (2017a). Faraway, so close: Coupled climate and economic dynamics in an agent-based integrated assessment model. Sciences Po OFCE working paper 10.

Lamperti, F., Roventini, A. y Sani, A. (2017b). Agent-based model calibration using machine learning surrogates. Paper 1703.10639, arXiv.org.

Leary, M. T. (2009). Bank loan supply, lender choice, and corporate capital structure. Journal of Finance, 64(3), 1143-1185.

Leibo, J. Z., Zambaldi, V. et al. (2017). Multi-agent reinforcement learning in sequential social dilemmas. DeepMind working paper, Londres.

Leijonhufvud, A. (2000). Macroeconomic instability and coordination: Selected essays. Cheltenham: Edward Elgar.

Lengnick, M. (2013). Agent-based macroeconomics: A baseline model. Journal of Economic Behavior & Organization, 86, 102-120.

Leombruni, R. y Richiardi, M. (2005). Why are economists sceptical about agent-based simulations? Physica A: Statistical Mechanics and its Applications, 355(1), 103-109.

Linde, J., Smets, F. y Wouters, R. (2016). Challenges for central banks’ macro models. En J. B. Taylor y H. Uhlig (eds.), Handbook of Macroeconomics, v. 2 (pp. 2185-2262). Ámsterdam: Elsevier.

Lindl, J. D., Amendt, P. et al. (2004). The physics basis for ignition using indirect-drive targets on the National Ignition Facility. Physics of Plasmas, 11(2), 339-491.

Lown, C. y Morgan, D. P. (2006). The credit cycle and the business cycle: new findings using the loan officer opinion survey. Journal of Money, Credit and Banking, 38(6), 1575-1597.

Lucas, R. E. (1972). Expectations and the neutrality of money. Journal of Economic Theory, 4(2), 103-124.

Lucas, R. E. (1976). Econometric policy evaluation: A critique. Carnegie-Rochester conference series on public policy, 1(1), 19-46.

Lucas, R. E. (1987). Models of business cycles, v. 26. Oxford: Basil Blackwell.

Lucas, R. E. y Sargent, T. J. (1979). After Keynesian macroeconomics. Quarterly Review, 3(2), 1-16.

Lux, T. y Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of a financial market. Nature, 397(6719), 498-500.

Mendoza, E. G. y Terrones, M. E. (2012). An anatomy of credit booms and their demise. NBER technical report. Cambridge, Mass.

Metroplis, N. (1987). The beginning of the Monte Carlo method. Los Alamos Science, 15(548), 125-130.

Metropolis, N., Rosenbluth, A. W. et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21(6), 1087-1092.

Metropolis, N. y Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association, 44(247), 335-341.

Mikolov, T., Chen, K. et al. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv: 13013781.

Minsky, H. P. (2008). Stabilizing an unstable economy, v. 1. Nueva York: McGraw Hill.

Muellbauer, J. y Murata, K. (2009). Consumption, land prices and the monetary transmission mechanism in Japan. Columbia University Academic Commons.

Muth, J. F. (1961). Rational expectations and the theory of price movements. Econometrica, 29(3), 315-335.

Napoletano, M., Roventini, A. y Sapio, S. (2006). Are business cycles all alike? A bandpass filter analysis of the Italian and US cycles. Rivista Italiana degli Economisti, 11(1), 87-118.

Nyman, R., Gregory, D. et al. (2015). News and narratives in financial systems: exploiting big data for systemic risk assessment. Bank of England staff working paper. Londres.

Page, S. E. (2008). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton: Princeton University Press.

Popoyan, L., Napoletano, M. y Roventini, A. (2016). Taming macroeconomic instability: monetary and macro prudential policy interactions in an agent-based model. Journal of Economic Behavior & Organization, 134, 117-140.

Ravn, M. y Sterk, V. (2016). Macroeconomic fluctuations with HANK & SAM: An analytical approach. Centre for Macroeconomics discussion papers 1633. University College London.

Reinhart, C. M. y Rogoff, K. S. (2009). The aftermath of financial crises. NBER technical report. Cambridge, Mass.

Romer, P. (2016). The trouble with macroeconomics. De próxima publicación en The American Economist.

Salle, I., Yildizoglu, M. y Senegas, M.-A. (2013). Inflation targeting in a learning economy: An MBA perspective. Economic Modelling, 34, 114-128.

Sands, P., Mundaca-S., C. y Dzau, V. J. (2016). The neglected dimension of global security - a framework for countering infectious-disease crises. New England Journal of Medicine, 374(13), 1281-1287.

Shaikh, A. (2016). Capitalism: Competition, conflict, crises. Nueva York: Oxford University Press.

Sherlock, M., Hill, E. et al. (2014). In-depth plasma-wave heating of dense plasma irradiated by short laser pulses. Physical review letters, 113(25); 255001-255036.

Shiller, R. J. (2017). Narrative economics. NBER working paper 23075. Cambridge, Mass.

Silver, N. (2012). The signal and the noise: the art and science of prediction. Londres: Penguin.

Simon, H. A. (1959). Theories of decision-making in economics and behavioral science. American Economic Review, 49(3), 253-283.

Sinitskaya, E. y Tesfatsion, L. (2015). Macroeconomies as constructively rational games. Journal of Economic Dynamics and Control, 61(C), 152-182.

Smets, F. y Wouters, R. (2003). An estimated dynamic stochastic general equilibrium model of the euro area. Journal of the European Economic Association, 1(5), 1123-1175.

Smith, N. (2014). Wall Street skips economics class. Bloomberg View, [https: //www.bloomberg.com/view/articles/2014-07-23/wall-street-skips-economics-class].

Solow, R. (2008). The state of macroeconomics. Journal of Economic Perspectives, 22(1), 243-246.

Sornette, D. (2014). Physics and financial economics (1776-2014): puzzles, Ising and agent-based models. Reports on progress in physics, 77(6), 062001-062014.

Souleles, N. S. (1999). The response of household consumption to income tax refunds. American Economic Review, 89(4), 947-958.

Spears, B. K., Munro, D. H. et al. (2015). Three-dimensional simulations of National Ignition Facility implosions: Insight into experimental observables a). Physics of Plasmas, 22(5), 056317.

Stern, N. (2016a). Current climate models are grossly misleading: Nicholas stern calls on scientists, engineers and economists to help policymakers by better modelling the immense risks to future generations, and the potential for action. Nature, 530(7591), 407-410.

Stern, N. (2016b). Economics: Current climate models are grossly misleading. Nature, 530(7591), 407-409.

Stern, N. H. (2007). The economics of climate change: the Stern review. Cambridge, UK: Cambridge University Press.

Stock, J. y Watson, M. (1999). Business cycle fluctuations in us macroeconomic time series. En J. B. Taylor y M. Woodford (eds.), Handbook of Macroeconomics, v, 1 (pp. 3-64). Ámsterdam: Elsevier.

Stock, J. H. y Watson, M. (2011). Dynamic factor models. En M. Clements y D. Hendry (eds.), Oxford Handbook on Economic Forecasting (pp. 35-60). Nueva York: Oxford University Press.

Stock, J. H. y Watson, M. W. (2006). Forecasting with many predictors. En G. Elliot. et al. (eds.), Handbook of economic forecasting, v. 1. (pp. 515-554). Ámsterdam: Elsevier.

Summers, L. H. (2002). Some skeptical observations on real business cycle theory. En B. Snowdon y H. Vane (eds.), A macroeconomics reader (pp. 389-394). Nueva York: Rutledge.

Tasoff, J., Mee, M. T. et al. (2015). An economic framework of microbial trade. PloS one, 10(7), e0132907.

Tesfatsion, L. (2002). Agent-based computational economics: Growing economies from the bottom up. Artificial life, 8(1), 55-82.

Timmermann, A. (2006). Forecast combinations. En G. Elliot. et al. (eds.), Handbook of economic forecasting, v. 1 (pp. 135-196). Ámsterdam: Elsevier.

Turrell, A. (2016). Agent-based models: Understanding the economy from the bottom up. Bank of England quarterly bulletin series 2016Q4. Londres.

Turrell, A., Sherlock, M. y Rose, S. (2015a). Self-consistent inclusion of classical large-angle Coulomb collisions in plasma Monte Carlo simulations. Journal of Computational Physics, 299, 144-155.

Turrell, A., Sherlock, M. y Rose, S. (2015b). Ultrafast collisional ion heating by electrostatic shocks. Nature Communications, 6, 8905.

Tversky, A. y Kahneman, D. (1975). Judgment under uncertainty: Heuristics and biases. En D. Wendt y C. Vlek (eds.), Utility, probability, and human decision making (pp. 141-162). Dordrecht: Reidel Publishing.

Van Noorden, R. (2015). Interdisciplinary research by the numbers: an analysis reveals the extent and impact of research that bridges disciplines. Nature, 525(7569), 306-308.

Walde, K. y Woitek, U. (2004). R&D expenditure in G7 countries and the implications for endogenous fluctuations and growth. Economics Letters, 82(1), 91-97.

Watts, D. J. (2002). A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences, 99(9), 5766-5771.

Welfe, W. (2013). Macroeconometric models, v. 47. Berlín: Springer.

Wren-L., S. (2016a). More on stock-flow consistent models, [https: //mainlymacro.blogspot.co.uk/2016/09/more-on-stock-flow-consistent-models.html].

Wren-L., S. (2016b). Unravelling the new classical counter revolution. Review of Keynesian Economics, 4(1), 20-35.

Wright, I. (2005). The duration of recessions follows an exponential not a power law. Physica A: Statistical Mechanics and its Applications, 345(3), 608-610.

Wuchty, S., Jones, B. F. y Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316(5827), 1036-1039.

Yegros-Y, A., Rafols, I. y D’Este, P. (2015). Does interdisciplinary research lead to higher citation impact? The different effect of proximal and distal interdisciplinarity. PloS one, 10(8), e0135095.

Yellen, J. L. et al. (2016, 14 de octubre). Macroeconomic research after the crisis: a speech at “The elusive ‘great’ recovery: Causes and implications for future business cycle dynamics”. 60 conferencia económica anual patrocinada por el Reserve Bank of Boston. Boston, Mass.

Zarnowitz, V. (1985). Recent work on business cycles in historical perspective: A review of theories and evidence. Journal of Economic Literature, 23(2), 523-580.

Citado por