Generational Risk–Is It a Big Deal?: Simulating an 80-Period OLG Model with Aggregate Shocks

By Jasmina Hasanhodzic and Laurence Kotlikoff

http://d.repec.org/n?u=RePEc:byu:byumcl:201301&r=dge

The theoretical literature on generational risk assumes that this risk is large and that the government can effectively share it. To assess these assumptions, this paper simulates a realistically calibrated 80-period overlapping generations life-cycle model with aggregate productivity shocks. Previous solution methods could not handle large-scale OLG models such as ours due to the well-known curse of dimensionality. The prior state of the art is Krueger and Kubler (2004, 2006), whose sparse-grid method handles 10 to 30 periods depending on the model’s realism. Other methods used to solve large-scale, multi-period life-cycle models are tenuous because they rely on either local approximations (Rios-Rull, 1994, 1996) or summary statistics of state variables (Krusell and Smith, 1997, 1998). We build on a new algorithm by Judd, Maliar, and Maliar (2009, 2011), which restricts the state space to the model’s ergodic set. This limits the required computation and effectively banishes the dimensionality curse in models like ours. We find that intrinsic generational risk is quite small, that government policies can produce generational risk, and that bond markets can help share generational risk. We also show that a bond market can mitigate risk-inducing government policy. Our simulations produce very small equity premia for three reasons. First, there is relatively little intrinsic generational risk. Second, intrinsic generational risk hits both the young and the old in similar ways. And third, artificially inducing risk between the young and the old via government policy elicits more net supply as well as more net demand for bonds, by the young and the old respectively, leaving the risk premium essentially unchanged. Our results hold even in the presence of rare disasters and very high risk aversion. They echo Lucas’ (1987) and Krusell and Smith’s (1999) point that macroeconomic fluctuations are too small to have major microeconomic consequences.

Interesting application of promising new computational techniques. It is also interesting to see a result that indicates that the government introducing artificial risk is not necessarily welfare reducing. I have a paper with a similar result I need to finish now…

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Can the Mortensen-Pissarides Model Match the Housing Market Facts?

By Gaetano Lisi

http://d.repec.org/n?u=RePEc:eec:wpaper:1312&r=dge

In the housing markets three basic facts have been repeatedly reported by empirical studies: the existence of price dispersion, the positive correlation between housing price and time-on-the-market, and between housing price and trading volume. Since housing markets are characterised by a decentralised framework of exchange with important search and matching frictions, this paper examines whether the baseline search and matching model can account for these three basic facts. We find that the standard matching framework allows to obtain a direct relationship between market frictions and house prices which represents the key mechanism to explain the basic facts of the housing market.

This remarkably short paper shows that it does not take much to match the three principal facts of the housing market. Yet, I do not think search models have been much exploited to study housing markets. I hope this paper will encourage more people to pursue this research agenda.

Pledgability and Liquidity: A New Monetarist Model of Financial and Macroeconomic Activity

By Venky Venkateswaran and Randall Wright

http://d.repec.org/n?u=RePEc:nbr:nberwo:19009&r=dge

When limited commitment hinders unsecured credit, assets help by serving as collateral. We study models where assets differ in pledgability – the extent to which they can be used to secure loans – and hence liquidity. Although many previous analyses of imperfect credit focus on producers, we emphasize consumers. Household debt limits are determined by the cost households incur when assets are seized in the event of default. The framework, which nests standard growth and asset-pricing theory, is calibrated to analyze the effects of monetary policy and financial innovation. We show that inflation can raise output, employment and investment, plus improve housing and stock markets. For the baseline calibration, optimal inflation is positive. Increases in pledgability can generate booms and busts in economic activity, but may still be good for welfare.

When you want to trade today but can only offer a counterpart tomorrow, you either pledge an asset or use some asset as collateral. But this is fraught with frictions, the quality of the asset may be uncertain, for example.Traders should thus endogenously determine how much asset should be used as a medium of exchange or collateral, depending on circumstances. In such a context, inflation in fiat money, which is used for transactions as well , has a positive impact: as the opportunity cost of money increases, agents substitute into other assets and thus increase working capital. Higher steady-state inflation can thus mean higher output. That result is quite difficult to obtain in micro-founded models where the Friedman Rule tends to prevail.

Solution-Driven Specification of DSGE Models

By Francisco Blasques

http://d.repec.org/n?u=RePEc:dgr:uvatin:20130062&r=dge

This paper proposes a functional specification approach for dynamic stochastic general equilibrium (DSGE) models that explores the properties of the solution method used to approximate policy functions. In particular, the solution-driven specification takes the properties of the solution method directly into account when designing the structural model in order to deliver enhanced flexibility and facilitate parameter identification within the structure imposed by the underlying economic theory. A prototypical application reveals the importance of this method in improving the specification of functional nonlinearities that are consistent with economic theory. The solution-driven specification is also shown to have the potential to greatly improve model fit and provide alternative policy recommendations when compared to standard DSGE model designs.

Traditionally, we specify a model, calibrate it and then apply a solution method. The latter has an impact on the result, though. For example, if a solution uses polynomial functions and it only preserve the properties of functions locally around the steady state, there is no need to use functional forms that have required properties beyond locally, especially if global properties impose additional unwelcome constraints. This means that functional-form choice depends on the solution method. And as the example in the paper shows, it can matter.

Credit frictions and the cleansing effect of recessions

By Sophie Osotimehin and Francesco Pappadà

http://d.repec.org/n?u=RePEc:vir:virpap:403&r=dge

Recessions are conventionally considered as times when the least productive firms are driven out of the market. Do credit frictions hamper this cleansing effect of recessions? We build and calibrate a model of firm dynamics with endogenous exit and credit frictions to investigate this question. We find that, despite their distortionary effect on the selection of exiting firms, credit frictions do not reverse the cleansing effect of recession. Average idiosyncratic productivity rises following an adverse aggregate shock. Our results also suggest that recessions have a modest impact on average productivity whatever the level of credit frictions

Bernanke-Gertler meets Schumpeter, and neither seems to matter much. I was expecting the cleansing during recessions to be more important. As for frictions, it was not clear which way it would go, as more productive firms may face fewer frictions but frictions become more important in recessions, or something like that. In any case, it turns out that the popular claim that an occasional recession is good for the economy is not that true.