| dc.relation | <p>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. <em>Physics Letters</em> <em>B</em>, <em>716</em>(1), 1-29.</p> <p>Abbott, B. P., Abbott, R. et al. (2016). Observation of gravitational waves from a binary black hole merger. <em>Physical review letters</em>, <em>116</em>(6), 061102.</p> <p>Abel, A. B. (1990). Asset prices under habit formation and catching up with the Joneses. NBER technical report. Cambridge, Mass.</p> <p>Aikman, D., Galesic, M. et al. (2014). Taking uncertainty seriously: simplicity versus complexity in financial regulation. Bank of England financial stability paper 28. Londres.</p> <p>Alfarano, S., Lux, T. y Wagner, F. (2005). Estimation of agent-based models: the case of an asymmetric herding model. <em>Computational Economics</em>, <em>26</em>(1), 19-49.</p> <p>Alfi, V., Cristelli, M. et al. (2009). Minimal agent based model for financial markets I. <em>The European Physical Journal B</em>, <em>67</em>(3), 385-397.</p> <p>Arber, T., Bennett, K. et al. (2015). Contemporary particle-in-cell approach to laser-plasma modelling. <em>Plasma Physics and Controlled Fusion</em>, <em>57</em>(11), 113001.</p> <p>Arinaminpathy, N., Kapadia, S. y May, R. (2012). Size and complexity in model financial systems. <em>Proceedings of the National Academy of Sciences</em>, <em>109</em>(45), 18338-18343.</p> <p>Arthur, W. B. (2006). Out-of-equilibrium economics and agent-based modeling. En L. Tesfatsion y K. Judd (eds.), <em>Handbook of computational economics</em>, v. 2 (pp. 1551-1564). Ámsterdam: Elsevier.</p> <p>Ascari, G., Fagiolo, G. y Roventini, A. (2015). Fat-tail distributions and business-cycle models. <em>Macroeconomic Dynamics</em>, <em>19</em>(02), 465-476.</p> <p>Ashraf, Q., Gershman, B. y Howitt, P. (2017). Banks, market organization, and macroeconomic performance: an agent-based computational analysis. <em>Journal of Economic Behavior & Organization</em>, 135, 143-180.</p> <p>Assenza, T., Brock, W. A. y Hommes, C. H. (2017). Animal spirits, heterogeneous expectations, and the amplification and duration of crises. <em>Economic Inquiry</em>, <em>55</em>(1), 542-564.</p> <p>Assenza, T., Gatti, D. D. y Grazzini, J. (2015). Emergent dynamics of a macroeconomic agent based model with capital and credit. <em>Journal of Economic Dynamics and Control</em>, 50, 5-28.</p> <p>Assenza, T., Gatti, D. D. et al. (2016). <em>Heterogeneous firms and international trade: The role of productivity and financial fragility</em>. CESifo working paper series 5959. Múnich: CESifo Group.</p> <p>Auclert, A. (2015). Monetary policy and the redistribution channel. 2015 meeting papers 381, Society for Economic Dynamics.</p> <p>Ausloos, M., Miskiewicz, J. y Sanglier, M. (2004). The durations of recession and prosperity: does their distribution follow a power or an exponential law? <em>Physica A: Statistical Mechanics and its Applications</em>, <em>339</em>(3), 548-558.</p> <p>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.</p> <p>Bagehot, W. (1873). <em>Lombard Street: A description of the money market</em>. Londres: Henry S. King and Co.</p> <p>Baker, S. R., Bloom, N. y Davis, S. J. (2016). Measuring economic policy uncertainty. <em>Quarterly Journal of Economics</em>, <em>131</em>(4), 1593-1636.</p> <p>Baptista, R., Farmer, J. D. et al. (2016). <em>Macroprudential policy in an agent-based model of the UK housing market</em>. Staff working paper 619. Londres: Bank of England.</p> <p>Bardoscia, M., Battiston, S. et al. (2017). Pathways towards instability in financial networks. <em>Nature Communications</em>, <em>8</em>(14416).</p> <p>Bartelsman, E. J. y Doms, M. (2000). Understanding productivity: Lessons from longitudinal microdata. <em>Journal of Economic literature</em>, <em>38</em>(3), 569-594.</p> <p>Batten, S., Sowerbutts, R. et al. (2016). <em>Let’s talk about the weather: the impact of climate change on central banks</em>. Staff working paper 603. Londres: Bank of England.</p> <p>Battiston, S., Gatti, D. D. et al.. (2007). Credit chains and bankruptcy propagation in production networks. <em>Journal of Economic Dynamics and Control</em>, <em>31</em>(6), 2061-2084.</p> <p>Bernanke, B. (2004). <em>The great moderation</em>. Discurso en las reuniones de la Eastern Economic Association, 20 de febrero, Washington DC.</p> <p>Bjørnland, H. C., Gerdrup, K. et al. (2012). Does forecast combination improve Norges Bank inflation forecasts? <em>Oxford Bulletin of Economics and Statistics</em>, <em>74</em>(2), 163-179.</p> <p>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].</p> <p>Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. <em>Proceedings of the National Academy of Sciences</em>, <em>99</em>(supl. 3), 7280-7287.</p> <p>Bottazzi, G. y Secchi, A. (2003). Common properties and sectoral specificities in the dynamics of US manufacturing companies. <em>Review of Industrial Organization</em>, <em>23</em>(3-4), 217-232.</p> <p>Bottazzi, G. y Secchi, A. (2006). Explaining the distribution of firm growth rates. <em>RAND Journal of Economics</em>, <em>37</em>(2), 235-256.</p> <p>Braun-M., K., Liu, Z. y Turrell, A. E. (2016). <em>An agent-based model of dynamics in corporate bond trading</em>. Staff working paper 592. Londres: Bank of England.</p> <p>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.</p> <p>Bronk, R. (2011). Uncertainty, modelling monocultures and the financial crisis. <em>The business economist</em>, <em>42</em>(2), 5-18.</p> <p>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.</p> <p>Bulanov, S. y Khoroshkov, V. (2002). Feasibility of using laser ion accelerators in proton therapy. <em>Plasma Physics Reports</em>, <em>28</em>(5), 453-456.</p> <p>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.</p> <p>Burke, M., Hsiang, S. M. y Miguel, E. (2015). Global non-linear effect of temperature on economic production. <em>Nature</em>, <em>527</em>(7577), 235-239.</p> <p>Burns, A. F. y Mitchell, W. C. (1946). <em>Measuring business cycles</em>. Cambridge, Mass: NBER.</p> <p>Caiani, A., Godin, A. et al. (2016). Agent based-stock flow consistent macroeconomics: Towards a benchmark model. <em>Journal of Economic Dynamics and Control</em>, <em>69</em>(C), 375-408.</p> <p>Campbell, J. Y. y Mankiw, N. G. (1989). Consumption, income, and interest rates: Reinterpreting the time series evidence. <em>NBER macroeconomics annual</em>, 4, 185-216.</p> <p>Card, D. y DellaVigna, S. (2013). Nine facts about top journals in economics. <em>Journal of Economic Literature</em>, <em>51</em>(1), 144-161.</p> <p>Carney, M. (2017). <em>Reflecting diversity, choosing inclusion</em>. Discurso Bank of England. Londres.</p> <p>Carroll, C. D. (1997). Buffer-stock saving and the life cycle/permanent income hypothesis. <em>Quarterly Journal of economics</em>, <em>112</em>(1), 1-55.</p> <p>Carroll, C. D. (2009). Precautionary saving and the marginal propensity to consume out of permanent income. <em>Journal of Mmonetary Economics</em>, <em>56</em>(6), 780-790.</p> <p>Carroll, C. D. y Kimball, M. S. (1996). On the concavity of the consumption function. <em>Econometrica</em>, <em>64</em>(4), 981-992.</p> <p>Carter, N., Levin, S. et al. (2015). Modeling tiger population and territory dynamics using an agent-based approach. <em>Ecological Modelling</em>, 312, 347-362.</p> <p>Castaldi, C. y Dosi, G. (2009). The patterns of output growth of firms and countries: Scale invariances and scale specificities. <em>Empirical Economics</em>, <em>37</em>(3), 475-495.</p> <p>Chakraborty, C. y Joseph, A. (2017). <em>Machine learning at central banks</em>. Staff working paper 674. Londres: Bank of England.</p> <p>Chan, C. K. y Steiglitz, K. (2008). An agent-based model of a minimal economy. Department of Computer Science. Princeton: Princeton University.</p> <p>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).</p> <p>Colander, D., Goldberg, M. et al. (2009). The financial crisis and the systemic failure of the economics profession. <em>Critical Review</em>, <em>21</em>(2-3), 249-267.</p> <p>Colussi, T. (2018). Social ties in academia: A friend is a treasure. <em>Review of Economics and Statistics</em>, <em>100</em>(1), 45-50.</p> <p>Cooper, D. y Dynan, K. (2016). Wealth effects and macroeconomic dynamics. <em>Journal of Economic Surveys</em>, <em>30</em>(1), 34-55.</p> <p>Cutler, D. M., Poterba, J. M. y Summers, L. H. (1989). What moves stock prices? <em>The</em> <em>Journal of Portfolio Management</em>, <em>15</em>(3), 4-12.</p> <p>Davis, M., Efstathiou, G. et al. (1985). The evolution of large-scale structure in a universe dominated by cold dark matter. <em>The Astrophysical Journal</em>, 292, 371-394.</p> <p>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.</p> <p>Dawid, H., Harting, P. y Neugart, M. (2014). Economic convergence: Policy implications from a heterogeneous agent model. <em>Journal of Economic Dynamics and Control</em>, <em>44</em>(C), 54-80.</p> <p>De Grauwe, P. (2010). Top-down versus bottom-up macroeconomics. <em>CESifo Economic Studies</em>, <em>56</em>(4), 465-497.</p> <p>Degli Atti, M. L. C., Merler, S. et al. (2008). Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. <em>PloS one</em>, <em>3</em>(3), e1790.</p> <p>Di Guilmi, C., Gallegati, M. y Ormerod, P. (2004). Scaling invariant distributions of firms’ exit in OECD countries. <em>Physica A: Statistical Mechanics and its Applications</em>, <em>334</em>(1), 267-273.</p> <p>Doms, M. y Dunne, T. (1998). Capital adjustment patterns in manufacturing plants. <em>Review of Economic Dynamics</em>, <em>1</em>(2), 409-429.</p> <p>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.), <em>Perspectives on innovation</em> (pp.153-186). Nueva York: Cambridge University Press.</p> <p>Dosi, G., Fagiolo, G. et al. (2015). Fiscal and monetary policies in complex evolving economies. <em>Journal of Economic Dynamics and Control</em>, <em>52</em>(C), 166-189.</p> <p>Dosi, G., Fagiolo, G. y Roventini, A. (2010). Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles. <em>Journal of Economic Dynamics and Control</em>, <em>34</em>(9), 1748-1767.</p> <p>Elmendorf, D. W. et al. (1996). The effect of interest-rate changes on household saving and consumption: A survey. <em>FEDS</em> paper 96-27. Washington DC. Federal Reserve Board.</p> <p>Epstein, J. M. (1999). Agent-based computational models and generative social science. <em>Complexity</em>, <em>4</em>(5), 41-60.</p> <p>Epstein, J. M. (2006). Remarks on the foundations of agent-based generative social science. En L. Tesfatsion y K. Judd (eds.), <em>Handbook of computational economics</em>, v. 2 (pp.1585-1604). Ámsterdam: Elsevier.</p> <p>Erlingsson, E. J., Teglio, A. et al. (2014). Housing market bubbles and business cycles in an agent-based credit economy. <em>Economics: The Open-Access, Open-Assessment E-Journal</em>, <em>8</em>(2014-8), 1-42.</p> <p>Ernest, N., Carroll, D. et al. (2016). Genetic fuzzy based artificial intelligence for unmanned combat aerial vehicle control in simulated air combat missions. <em>Journal of Defense Management</em>, <em>6</em>(144), 2167-0374.</p> <p>Estrella, A. y Fuhrer, J. C. (2002). Dynamic inconsistencies: Counterfactual implications of a class of rational-expectations models. <em>American Economic Review</em>, <em>92</em>(4), 1013-1028.</p> <p>Ezrachi, A. y Stucke, M. (2016). <em>Virtual competition. The promise and perils of algorithmic-driven economy</em>. Cambridge, Mass.: Harvard University Press.</p> <p>Fagiolo, G., Napoletano, M. y Roventini, A. (2008). Are output growth-rate distributions fat-tailed? Some evidence from OECD countries. <em>Journal of Applied Econometrics</em>, <em>23</em>(5), 639-669.</p> <p>Fagiolo, G. y Roventini, A. (2012). Macroeconomic policy in DSGE and agent-based models. <em>Revue de l’OFCE</em>, <em>5</em>(124), 67-116.</p> <p>Fagiolo, G. y Roventini, A. (2017). Macroeconomic policy in DSGE and agent-based models Redux: New developments and challenges ahead. <em>Journal of Artificial Societies and Social Simulation</em>, <em>20</em>(1), 1-37.</p> <p>Fair, R. C. (2012). Has macro progressed? <em>Journal of Macroeconomics</em>, <em>34</em>(1), 2-10.</p> <p>Foos, D., Norden, L. y Weber, M. (2010). Loan growth and riskiness of banks. <em>Journal of Banking & Finance</em>, <em>34</em>(12), 2929- 2940.</p> <p>Fourcade, M., Ollion, E. y Algan, Y. (2015). The superiority of economists. <em>Revista de Economía Institutional</em>, <em>17</em>(33), 13-43.</p> <p>Franke, R. y Westerhoff, F. (2012). Structural stochastic volatility in asset pricing dynamics: Estimation and model contest. <em>Journal of Economic Dynamics and Control</em>, <em>36</em>(8), 1193-1211.</p> <p>Friedman, J., Hastie, T. y Tibshirani, R. (2001). <em>The elements of statistical learning</em>, v. 1. Nueva York: Springer.</p> <p>Friedman, M. (1957). <em>A theory of the consumption function</em>. Princeton: Princeton University Press.</p> <p>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.</p> <p>Gabaix, X. (2011). The granular origins of aggregate fluctuations. <em>Econometrica</em>, <em>79</em>(3), 733-772.</p> <p>Gabaix, X. (2016). Behavioral macroeconomics via sparse dynamic programming. NBER technical report. Cambridge, Mass.</p> <p>Gaffeo, E., Di Guilm. et al. (2012). On the mean/variance relationship of the firm size distribution: Evidence and some theory. <em>Ecological Complexity</em>, 11, 109-117.</p> <p>Gai, P., Haldane, A. y Kapadia, S. (2011). Complexity, concentration and contagion. <em>Journal of Monetary Economics</em>, <em>58</em>(5), 453-470.</p> <p>Gai, P. y Kapadia, S. (2010). Contagion in financial networks. <em>Proceedings of the Royal Society</em>, <em>466</em>(2120), 2401-2423.</p> <p>Gatti, D. D. y Desiderio, S. (2015). Monetary policy experiments in an agent-based model with financial frictions. <em>Journal of Economic Interaction and Coordination</em>, <em>10</em>(2), 265-286.</p> <p>Geanakoplos, J., Axtell, R. et al. (2012). Getting at systemic risk via an agent-based model of the housing market. <em>American Economic Review</em>, <em>102</em>(3), 53-58.</p> <p>Gibson, B. (2007). A multi-agent systems approach to microeconomic foundations of macro. Technical report working paper. Amherst: University of Massachusetts.</p> <p>Gigerenzer, G. y Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. <em>Topics in cognitive science</em>, <em>1</em>(1), 107-143.</p> <p>Gode, D. K. y Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. <em>Journal of Political Economy</em>, <em>101</em>(1), 119-137.</p> <p>Godley, W. y Lavoie, M. (2007). <em>Monetary economics</em>. Basingstoke: Palgrave Macmillan.</p> <p>Gualdi, S., Tarzia, M. et al. (2015). Tipping points in macroeconomic agent-based models. <em>Journal of Economic Dynamics and Control</em>, 50, 29-61.</p> <p>Guerini, M. y Moneta, A. (2017). A method for agent-based models validation. <em>Journal of Economic Dynamics and Control</em>, 82(C), 125-141.</p> <p>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].</p> <p>Guvenen, F. (2011). Macroeconomics with heterogeneity: A practical guide. NBER technical report. Cambridge, Mass.</p> <p>Haldane, A. G. (2016). The dappled world. Discurso, Bank of England. Londres.</p> <p>Haldane, A. G. y Madouros, V. (2012). El perro y el frisbee. <em>Revista de Economía Institutional</em>, <em>14</em>(27), 13-56.</p> <p>Haldane, A. G. y May, R. M. (2011). Systemic risk in banking ecosystems. <em>Nature</em>, <em>469</em>(7330), 351-355.</p> <p>Hamermesh, D. S. (2013). Six decades of top economics publishing: Who and how? <em>Journal of Economic Literature</em>, <em>51</em>(1), 162-172.</p> <p>Hausman, D. M. (1992). <em>The inexact and separate science of economics</em>. Gateshead, UK: Cambridge University Press.</p> <p>Heathcote, J. (2005). Fiscal policy with heterogeneous agents and incomplete markets. <em>Review of Economic Studies</em>, <em>72</em>(1), 161-188.</p> <p>Heppenstall, A. J., Crooks, A. T. et al. (2011). <em>Agent-based models of geographical systems</em>. Dordrecht: Springer.</p> <p>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].</p> <p>Hommes, C. H. (2006). Heterogeneous agent models in economics and finance. En L. Tesfatsion y K. Judd (eds.), <em>Handbook of computational economics</em>, v. 2 (pp. 1109-1186). Ámsterdam: Elsevier.</p> <p>Hong, H. y Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. <em>Journal of finance</em>, <em>54</em>(6), 2143-2184.</p> <p>Jacobs, J. A. (2014). <em>In defense of disciplines: Interdisciplinarity and specialization in the research university</em>. Chicago: University of Chicago Press.</p> <p>Jaimovich, N. y Floetotto, M. (2008). Firm dynamics, markup variations, and the business cycle. <em>Journal of Monetary Economics</em>, <em>55</em>(7), 1238-1252.</p> <p>Jawadi, F. y Sousa, R. M. (2014). The relationship between consumption and wealth: A quantile regression approach. <em>Revue d’économie politique</em>, <em>124</em>(4), 639-652.</p> <p>Kaplan, G., Moll, B. y Violante, G. L. (2016). Monetary policy according to HANK. NBER technical report. Cambridge, Mass.</p> <p>Keogh-B., M. R., Wren-L., S. et al. (2010). The possible macroeconomic impact on the UK of an influenza pandemic. <em>Health economics</em>, <em>19</em>(11), 1345-1360.</p> <p>Keynes, J. M. (1924). Alfred Marshall, 1842-1924. <em>Economic Journal</em>, <em>34</em>(135), 311-372.</p> <p>Keynes, J. M. (1936). <em>General theory of employment, interest and money</em>. Londres: Palgrave Macmillan.</p> <p>Kindleberger, C. P. (2001). <em>Manias, panics, and crashes: A history of financial crises</em>. Hoboken, NJ: John Wiley & Sons.</p> <p>Kirman, A. P. (1992). Whom or what does the representative individual represent? <em>Journal of Economic Perspectives</em>, <em>6</em>(2), 117-136.</p> <p>Knight, F. H. (2012). <em>Risk, uncertainty and profit</em>. North Chelmsford, Mass.: Courier Corporation.</p> <p>Krugman, P. (2011). The profession and the crisis. <em>Eastern Economic Journal</em>, <em>37</em>(3), 307-312.</p> <p>Kumhof, M., Ranciere, R. y Winant, P. (2015). Inequality, leverage, and crises. <em>American Economic Review</em>, <em>105</em>(3), 1217-1245.</p> <p>Kuznets, S. y Murphy, J. T. (1966). <em>Modern economic growth: Rate, structure, and spread</em>, v. 2. New Haven: Yale University Press.</p> <p>Kydland, F. E. y Prescott, E. C. (1982). Time to build and aggregate fluctuations. <em>Econometrica</em>, <em>50</em>(6), 1345-1370.</p> <p>Laeven, L. y Valencia, F. (2013). Systemic banking crises database. <em>IMF Economic Review</em>, <em>61</em>(2), 225-270.</p> <p>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.</p> <p>Lamperti, F., Roventini, A. y Sani, A. (2017b). Agent-based model calibration using machine learning surrogates. Paper 1703.10639, arXiv.org.</p> <p>Leary, M. T. (2009). Bank loan supply, lender choice, and corporate capital structure. <em>Journal of Finance</em>, <em>64</em>(3), 1143-1185.</p> <p>Leibo, J. Z., Zambaldi, V. et al. (2017). Multi-agent reinforcement learning in sequential social dilemmas. DeepMind working paper, Londres.</p> <p>Leijonhufvud, A. (2000). <em>Macroeconomic instability and coordination: Selected essays</em>. Cheltenham: Edward Elgar.</p> <p>Lengnick, M. (2013). Agent-based macroeconomics: A baseline model. <em>Journal of Economic Behavior & Organization</em>, 86, 102-120.</p> <p>Leombruni, R. y Richiardi, M. (2005). Why are economists sceptical about agent-based simulations? <em>Physica A: Statistical Mechanics and its Applications</em>, <em>355</em>(1), 103-109.</p> <p>Linde, J., Smets, F. y Wouters, R. (2016). Challenges for central banks’ macro models. En J. B. Taylor y H. Uhlig (eds.), <em>Handbook of Macroeconomics</em>, v. 2 (pp. 2185-2262). Ámsterdam: Elsevier.</p> <p>Lindl, J. D., Amendt, P. et al. (2004). The physics basis for ignition using indirect-drive targets on the National Ignition Facility. <em>Physics of Plasmas</em>, <em>11</em>(2), 339-491.</p> <p>Lown, C. y Morgan, D. P. (2006). The credit cycle and the business cycle: new findings using the loan officer opinion survey. <em>Journal of Money, Credit and Banking</em>, <em>38</em>(6), 1575-1597.</p> <p>Lucas, R. E. (1972). Expectations and the neutrality of money. <em>Journal of Economic Theory</em>, <em>4</em>(2), 103-124.</p> <p>Lucas, R. E. (1976). Econometric policy evaluation: A critique. <em>Carnegie-Rochester conference series on public policy</em>, <em>1</em>(1), 19-46.</p> <p>Lucas, R. E. (1987). <em>Models of business cycles</em>, v. 26. Oxford: Basil Blackwell.</p> <p>Lucas, R. E. y Sargent, T. J. (1979). After Keynesian macroeconomics. <em>Quarterly Review</em>, <em>3</em>(2), 1-16.</p> <p>Lux, T. y Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of a financial market. <em>Nature</em>, <em>397</em>(6719), 498-500.</p> <p>Mendoza, E. G. y Terrones, M. E. (2012). An anatomy of credit booms and their demise. NBER technical report. Cambridge, Mass.</p> <p>Metroplis, N. (1987). The beginning of the Monte Carlo method. <em>Los Alamos Science</em>, <em>15</em>(548), 125-130.</p> <p>Metropolis, N., Rosenbluth, A. W. et al. (1953). Equation of state calculations by fast computing machines. <em>Journal of Chemical Physics</em>, <em>21</em>(6), 1087-1092.</p> <p>Metropolis, N. y Ulam, S. (1949). The Monte Carlo method. <em>Journal of the American Statistical Association</em>, <em>44</em>(247), 335-341.</p> <p>Mikolov, T., Chen, K. et al. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv: 13013781.</p> <p>Minsky, H. P. (2008). <em>Stabilizing an unstable economy</em>, v. 1. Nueva York: McGraw Hill.</p> <p>Muellbauer, J. y Murata, K. (2009). Consumption, land prices and the monetary transmission mechanism in Japan. Columbia University Academic Commons.</p> <p>Muth, J. F. (1961). Rational expectations and the theory of price movements. <em>Econometrica</em>, <em>29</em>(3), 315-335.</p> <p>Napoletano, M., Roventini, A. y Sapio, S. (2006). Are business cycles all alike? A bandpass filter analysis of the Italian and US cycles. <em>Rivista Italiana degli Economisti</em>, <em>11</em>(1), 87-118.</p> <p>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.</p> <p>Page, S. E. (2008). <em>The difference: How the power of diversity creates better groups, firms, schools, and societies</em>. Princeton: Princeton University Press.</p> <p>Popoyan, L., Napoletano, M. y Roventini, A. (2016). Taming macroeconomic instability: monetary and macro prudential policy interactions in an agent-based model. <em>Journal of Economic Behavior & Organization</em>, 134, 117-140.</p> <p>Ravn, M. y Sterk, V. (2016). Macroeconomic fluctuations with HANK & SAM: An analytical approach. Centre for Macroeconomics discussion papers 1633. University College London.</p> <p>Reinhart, C. M. y Rogoff, K. S. (2009). The aftermath of financial crises. NBER technical report. Cambridge, Mass.</p> <p>Romer, P. (2016). The trouble with macroeconomics. De próxima publicación en <em>The American Economist</em>.</p> <p>Salle, I., Yildizoglu, M. y Senegas, M.-A. (2013). Inflation targeting in a learning economy: An MBA perspective. <em>Economic Modelling</em>, 34, 114-128.</p> <p>Sands, P., Mundaca-S., C. y Dzau, V. J. (2016). The neglected dimension of global security - a framework for countering infectious-disease crises. <em>New England Journal of Medicine</em>, <em>374</em>(13), 1281-1287.</p> <p>Shaikh, A. (2016). <em>Capitalism: Competition, conflict, crises</em>. Nueva York: Oxford University Press.</p> <p>Sherlock, M., Hill, E. et al. (2014). In-depth plasma-wave heating of dense plasma irradiated by short laser pulses. <em>Physical review letters</em>, <em>113</em>(25); 255001-255036.</p> <p>Shiller, R. J. (2017). Narrative economics. NBER working paper 23075. Cambridge, Mass.</p> <p>Silver, N. (2012). <em>The signal and the noise: the art and science of prediction</em>. Londres: Penguin.</p> <p>Simon, H. A. (1959). Theories of decision-making in economics and behavioral science. <em>American Economic Review</em>, <em>49</em>(3), 253-283.</p> <p>Sinitskaya, E. y Tesfatsion, L. (2015). Macroeconomies as constructively rational games. <em>Journal of Economic Dynamics and Control</em>, <em>61</em>(C), 152-182.</p> <p>Smets, F. y Wouters, R. (2003). An estimated dynamic stochastic general equilibrium model of the euro area. <em>Journal of the European Economic Association</em>, <em>1</em>(5), 1123-1175.</p> <p>Smith, N. (2014). Wall Street skips economics class. Bloomberg View, [https: //www.bloomberg.com/view/articles/2014-07-23/wall-street-skips-economics-class].</p> <p>Solow, R. (2008). The state of macroeconomics. <em>Journal of Economic Perspectives</em>, <em>22</em>(1), 243-246.</p> <p>Sornette, D. (2014). Physics and financial economics (1776-2014): puzzles, Ising and agent-based models. <em>Reports on progress in physics</em>, <em>77</em>(6), 062001-062014.</p> <p>Souleles, N. S. (1999). The response of household consumption to income tax refunds. <em>American Economic Review</em>, <em>89</em>(4), 947-958.</p> <p>Spears, B. K., Munro, D. H. et al. (2015). Three-dimensional simulations of National Ignition Facility implosions: Insight into experimental observables a). <em>Physics of Plasmas</em>, <em>22</em>(5), 056317.</p> <p>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. <em>Nature</em>, <em>530</em>(7591), 407-410.</p> <p>Stern, N. (2016b). Economics: Current climate models are grossly misleading. <em>Nature</em>, <em>530</em>(7591), 407-409.</p> <p>Stern, N. H. (2007). <em>The economics of climate change: the Stern review</em>. Cambridge, UK: Cambridge University Press.</p> <p>Stock, J. y Watson, M. (1999). Business cycle fluctuations in us macroeconomic time series. En J. B. Taylor y M. Woodford (eds.), <em>Handbook of Macroeconomics</em>, v, 1 (pp. 3-64). Ámsterdam: Elsevier.</p> <p>Stock, J. H. y Watson, M. (2011). Dynamic factor models. En M. Clements y D. Hendry (eds.), <em>Oxford Handbook on Economic Forecasting</em> (pp. 35-60). Nueva York: Oxford University Press.</p> <p>Stock, J. H. y Watson, M. W. (2006). Forecasting with many predictors. En G. Elliot. et al. (eds.), <em>Handbook of economic forecasting</em>, v. 1. (pp. 515-554). Ámsterdam: Elsevier.</p> <p>Summers, L. H. (2002). Some skeptical observations on real business cycle theory. En B. Snowdon y H. Vane (eds.), <em>A macroeconomics reader</em> (pp. 389-394). Nueva York: Rutledge.</p> <p>Tasoff, J., Mee, M. T. et al. (2015). An economic framework of microbial trade. <em>PloS one</em>, <em>10</em>(7), e0132907.</p> <p>Tesfatsion, L. (2002). Agent-based computational economics: Growing economies from the bottom up. <em>Artificial life</em>, <em>8</em>(1), 55-82.</p> <p>Timmermann, A. (2006). Forecast combinations. En G. Elliot. et al. (eds.), <em>Handbook of economic forecasting</em>, v. 1 (pp. 135-196). Ámsterdam: Elsevier.</p> <p>Turrell, A. (2016). Agent-based models: Understanding the economy from the bottom up. Bank of England quarterly bulletin series 2016Q4. Londres.</p> <p>Turrell, A., Sherlock, M. y Rose, S. (2015a). Self-consistent inclusion of classical large-angle Coulomb collisions in plasma Monte Carlo simulations. <em>Journal of Computational Physics</em>, 299, 144-155.</p> <p>Turrell, A., Sherlock, M. y Rose, S. (2015b). Ultrafast collisional ion heating by electrostatic shocks. <em>Nature Communications</em>, 6, 8905.</p> <p>Tversky, A. y Kahneman, D. (1975). Judgment under uncertainty: Heuristics and biases. En D. Wendt y C. Vlek (eds.), <em>Utility, probability, and human decision making</em> (pp. 141-162). Dordrecht: Reidel Publishing.</p> <p>Van Noorden, R. (2015). Interdisciplinary research by the numbers: an analysis reveals the extent and impact of research that bridges disciplines. <em>Nature</em>, <em>525</em>(7569), 306-308.</p> <p>Walde, K. y Woitek, U. (2004). R&D expenditure in G7 countries and the implications for endogenous fluctuations and growth. <em>Economics Letters</em>, <em>82</em>(1), 91-97.</p> <p>Watts, D. J. (2002). A simple model of global cascades on random networks. <em>Proceedings of the National Academy of Sciences</em>, <em>99</em>(9), 5766-5771.</p> <p>Welfe, W. (2013). <em>Macroeconometric models</em>, v. 47. Berlín: Springer.</p> <p>Wren-L., S. (2016a). More on stock-flow consistent models, [https: //mainlymacro.blogspot.co.uk/2016/09/more-on-stock-flow-consistent-models.html].</p> <p>Wren-L., S. (2016b). Unravelling the new classical counter revolution. <em>Review of Keynesian Economics</em>, <em>4</em>(1), 20-35.</p> <p>Wright, I. (2005). The duration of recessions follows an exponential not a power law. <em>Physica A: Statistical Mechanics and its Applications</em>, <em>345</em>(3), 608-610.</p> <p>Wuchty, S., Jones, B. F. y Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. <em>Science</em>, <em>316</em>(5827), 1036-1039.</p> <p>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. <em>PloS one</em>, <em>10</em>(8), e0135095.</p> <p>Yellen, J. L. et al. (2016, 14 de octubre). <em>Macroeconomic research after the crisis: a speech at “The elusive ‘great’ recovery: Causes and implications for future business cycle dynamics”</em>. 60 conferencia económica anual patrocinada por el Reserve Bank of Boston. Boston, Mass.</p> <p>Zarnowitz, V. (1985). Recent work on business cycles in historical perspective: A review of theories and evidence. <em>Journal of Economic Literature</em>, <em>23</em>(2), 523-580.</p> | |
