The Great Recession after the financial crisis gave rise to a lot of criticism of contemporary macroeconomic models. The standard modeling assumptions were severely challenged by scholars and policy makers, as they could not account for frictions in the financial intermediary sector or behavioral aspects of a turbulent economy. In this article, I will walk you through some of the critiques and new strands of macroeconomic models.
Critical notes and financial frictions during the 2007-2008 crisis
In his speech in November 2010, former European Central Bank Governor Jean-Claude Trichet noted that “Macro models … seemed incapable of explaining what was happening to the economy in a convincing manner”. Similarly, Olivier Blanchard noted that “we were much closer to “dark corners” – situations in which the economy could badly malfunction – than we thought.” These “dark corners” are extremely important in bad times. Mainstream macroeconomic models were not adequate in dealing with financial crises. At that time, the workhorse model of many central banks was the Dynamic Stochastic General Equilibrium (DSGE) model. This model (and variants thereof) is widely used to assess how different parts of the economy (households, fiscal authorities and central banks) are interacting and reacting to ‘shocks’ to the economy. From a modeling perspective, the recent critiques by both Hurtado (2014) and Akerlof (2019) are a joy to read, and similarities can be found in the classic speech delivered by Hayek in 1989 when he obtained the Nobel Prize in Economics.
One of the critiques of the old DSGE models was that frictions in the financial intermediary sector, for instance commercial banks giving out too many loans, were not properly taken into account. Of course, an economic model cannot be encompassing, but that is also not the point of a model in the first place. However, leaving elements out of the models that will drastically change the conclusions and policy recommendations can be disastrous. As we saw during the financial crisis, amplification took place in the financial intermediary sector as commercial banks were allowed to give out loans without too much collateral. After these critiques, we saw a rise in models trying to incorporate these aspects (see for instance the development of the NK-DSGE models and the work by Gertler & Karadi (2011), Curdia & Woodford (2010, 2016) and Gilchrist, Yankov & Zakrajšek (2009)).
In his speech, Trichet mentions an interesting aspect missing in the macroeconomic models; economic agents are modeled as if they are always optimizing their welfare and are capable of forming perfectly rational expectations regarding the future economic circumstances. However, in practice we witness many imperfections in the optimizing behavior of agents; imperfect foresight, hyperbolic discounting, incorrect formation of expectations and so on. To add these elements to the macroeconomic models, we have witnessed a switch towards micro-based macro models, meaning that there are more accurate microeconomic foundations that try to fully encompass the imperfections in the behavior of individual agents in an economy. In his survey on behavioral macroeconomics, Hommes (2019) notes that both “non-rational expectations and bounded rationality” and “a rich behavioral theory of expectations that fits empirical time series” are important aspects of a model. Vines & Wills (2018) focus in their critique on four aspects: financial frictions, non-rational expectations, heterogeneity in economic agents (which for instance results in a more realistic income distribution in the macroeconomy) and more appropriate microeconomic foundations.
All the aforementioned critiques are from both a practical and methodological point of view highly relevant. The work of Hommes (2019) particularly striked me. In his review, he sketches how complexity and behavioral aspects are important for macroeconomic modeling. As he notes, the contemporary models do not fully take into account that households, investors and other agents fall short of the standard welfare maximizing identical entity. In reality, agents are boundedly rational, rely on simple heuristics to make decisions (the work by Daniel Kahneman is a wonderful exposition on this) and are widely different in all aspects. In reality, agents are also not fully aware of the information in the economy and misjudge (or in the first place have no knowledge about) the economic dynamics. Furthermore, he argues that the macroeconomy as a whole is a highly complex system and suffers from a variety of complex dynamics that the NK-DSGE models are not capable of showcasing. All in all an interesting (relatively) new strand of macroeconomic models. I hope you gained some insight into the critiques of macroeconomic models and an alternative modeling approach!
Akerlof, G. A. (2019). What They Were Thinking Then: The Consequences for Macroeconomics during the Past 60 Years. Journal of economic perspectives, 33(4), 171-86.
Curdia, V., & Woodford, M. (2010). Credit spreads and monetary policy. Journal of Money, credit and Banking, 42, 3-35.
Curdia, V., & Woodford, M. (2016). Credit frictions and optimal monetary policy. Journal of Monetary Economics, 84, 30-65.
Gertler, M., & Karadi, P. (2011). A model of unconventional monetary policy. Journal of monetary Economics, 58(1), 17-34.
Gilchrist, S., Yankov, V., & Zakrajšek, E. (2009). Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets. Journal of monetary Economics, 56(4), 471-493.
Hayek, F. V. (1989). The pretence of knowledge (Nobel Lecture). American Economic Review, 79(6), 3-7.
Hommes, C. (2021). Behavioral and experimental macroeconomics and policy analysis: A complex systems approach. Journal of Economic Literature, 59(1), 149-219.
Hurtado, S. (2014). DSGE models and the Lucas critique. Economic Modelling, 44, S12-S19.Vines, D., & Wills, S. (2018). The rebuilding macroeconomic theory project: an analytical assessment. Oxford Review of Economic Policy, 34(1-2), 1-42.