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479
The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study – the first in the context of long-run risk modeling – delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.
480
Consumption-based asset pricing with rare disaster risk : a simulated method of moments approach
(2014)
The rare disaster hypothesis suggests that the extraordinarily high postwar U.S. equity premium resulted because investors ex ante demanded compensation for unlikely but calamitous risks that they happened not to incur. Although convincing in theory, empirical tests of the rare disaster explanation are scarce. We estimate a disaster-including consumption-based asset pricing model (CBM) using a combination of the simulated method of moments and bootstrapping. We consider several methodological alternatives that differ in the moment matches and the way to account for disasters in the simulated consumption growth and return series. Whichever specification is used, the estimated preference parameters are of an economically plausible size, and the estimation precision is much higher than in previous studies that use the canonical CBM. Our results thus provide empirical support for the rare disaster hypothesis, and help reconcile the nexus between real economy and financial markets implied by the consumption-based asset pricing paradigm.
572
The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model's macroeconomic dynamics and the investor's preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S. data and provide a critical re-assessment of the long-run risk model's ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.
589
After the Lehman-Brothers collapse, the stock index has exceeded its pre-Lehman-Brothers peak by 36% in real terms. Seemingly, markets have been demanding more stocks instead of bonds. Yet, instead of observing higher bond rates, paradoxically, bond rates have been persistently negative after the Lehman-Brothers collapse. To explain this paradox, we suggest that, in the post-Lehman-Brothers period, investors changed their perceptions on disasters, thinking that disasters occur once every 30 years on average, instead of disasters occurring once every 60 years. In our asset-pricing calibration exercise, this rise in perceived market fragility alone can explain the drop in both bond rates and price-dividend ratios observed after the Lehman-Brothers collapse, which indicates that markets mostly demanded bonds instead of stocks.
673
Using the pandemic as a laboratory, we show that asset markets assign a time- varying price to firms' disaster risk exposure. In 2020 the cross-section of realized and expected stock returns reflected firms' different exposure to the pandemic, as measured by their vulnerability to social distancing. Realized and expected return differentials initially widened and then narrowed, but disaster exposure still commanded a risk premium in December 2020. When inferred from market outcomes, resilience correlates not only with social distancing, but also with cash and environmental ratings. However, vulnerability to social distancing is the only characteristic that identifies persistently scarred firms.