Refine
Year of publication
Document Type
- Working Paper (14)
- Report (2)
Language
- English (16)
Has Fulltext
- yes (16)
Is part of the Bibliography
- no (16)
Keywords
This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the likelihood of rare disasters drop to a much more pessimistic level once a disaster has occurred. Such a shift in beliefs can trigger massive declines in price-dividend ratios. Pessimistic beliefs persist for some time. Thus, belief dynamics are a source of apparent excess volatility relative to a rational expectations benchmark. Due to the low frequency of disasters, even an infinitely-lived investor will remain uncertain about the exact probability. Our analysis is conducted in continuous time and offers closed-form solutions for asset prices. We distinguish between rational and adaptive Bayesian learning. Rational learners account for the possibility of future changes in beliefs in determining their demand for risky assets, while adaptive learners take beliefs as given. Thus, risky assets tend to be lower-valued and price-dividend ratios vary less under adaptive versus rational learning for identical priors. Keywords: beliefs, Bayesian learning, controlled diffusions and jump processes, learning about jumps, adaptive learning, rational learning. JEL classification: D83, G11, C11, D91, E21, D81, C61
Modern macroeconomics empirically addresses economy-wide incentives behind economic actions by using insights from the way a single representative household would behave. This analytical approach requires that incentives of the poor and the rich are strictly aligned. In empirical analysis a challenging complication is that consumer and income data are typically available at the household level, and individuals living in multimember households have the potential to share goods within the household. The analytical approach of modern macroeconomics would require that intra-household sharing is also strictly aligned across the rich and the poor. Here we have designed a survey method that allows the testing of this stringent property of intra-household sharing and find that it holds: once expenditures for basic needs are subtracted from disposable household income, household-size economies implied by the remainder household incomes are the same for the rich and the poor.
Most simulated micro-founded macro models use solely consumer-demand aggregates in order to estimate deep economy-wide preference parameters, which are useful for policy evaluation. The underlying demand-aggregation properties that this approach requires, should be easy to empirically disprove: since household-consumption choices differ for households with more members, aggregation can be rejected if appropriate data violate an affine equation regarding how much individuals benefit from within-household sharing of goods. We develop a survey method that tests the validity of this equation, without utility-estimation restrictions via models. Surprisingly, in six countries, this equation is not rejected, lending support to using consumer-demand aggregates.
Based on OECD evidence, equity/housing-price busts and credit crunches are followed by substantial increases in public consumption. These increases in unproductive public spending lead to increases in distortionary marginal taxes, a policy in sharp contrast with presumably optimal Keynesian fiscal stimulus after a crisis. Here we claim that this seemingly adverse policy selection is optimal under rational learning about the frequency of rare capital-value busts. Bayesian updating after a bust implies massive belief jumps toward pessimism, with investors and policymakers believing that busts will be arriving more frequently in the future. Lowering taxes would be as if trying to kick a sick horse in order to stand up and run, since pessimistic markets would be unwilling to invest enough under any temporarily generous tax regime.
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.
US data and new stockholding data from fifteen European countries and China exhibit a common pattern: stockholding shares increase in household income and wealth. Yet, there is a multitude of numbers to match through models. Using a single utility function across households (parsimony), we suggest a strategy for fitting stockholding numbers, while replicating that saving rates increase in wealth, too. The key is introducing subsistence consumption to an Epstein-Zin-Weil utility function, creating endogenous risk-aversion differences across rich and poor. A closed-form solution for the model with insurable labor-income risk serves as calibration guide for numerical simulations with uninsurable labor-income risk.
In fifteen European countries, China, and the US, stocks and business equity as a share of total household assets are represented by an increasing and convex function of income/wealth. A parsimonious model fitted to the data shows why background labor- income risk can explain much of this risk-taking pattern. Uncontrollable labor-income risk stresses middle-income households more because labor income is a larger fraction of their total lifetime resources compared with the rich. In response, middle-income households re-duce (controllable) financial risk. Richer households, having less pressure, can afford more risk-taking. The poor take low risk because they avoid jeopardizing their subsistence consumption.
We build a search-and-matching algorithm of network dynamics with decision-making under incomplete information, seeking to understand the determinants of the observed gradual downgrading of expert opinion on complicated issues and the decreasing trust in science. Even without fake news, combining the internet’s ease of forming networks with (a) individual biases, such as confirmation bias or assimilation bias, and (b) people’s tendency to align their actions with those of peers, produces populist and polarization network dynamics. Homophily leads to actions with more weight on biases and less weight on expert opinion, and such actions lead to more homophily.
Differential games of common resources that are governed by linear accumulation constraints have several applications. Examples include political rent-seeking groups expropriating public infrastructure, oligopolies expropriating common resources, industries using specific common infrastructure or equipment, capital-flight problems, pollution, etc. Most of the theoretical literature employs specific parametric examples of utility functions. For symmetric differential games with linear constraints and a general time-separable utility function depending only on the player’s control variable, we provide an exact formula for interior symmetric Markovian-strategies. This exact solution, (a) serves as a guide for obtaining some new closed-form solutions and for characterizing multiple equilibria, and (b) implies that, if the utility function is an analytic function, then the Markovian strategies are analytic functions, too. This analyticity property facilitates the numerical computation of interior solutions of such games using polynomial projection methods and gives potential to computing modified game versions with corner solutions by employing a homotopy approach.
Marginal income taxes may have an insurance effect by decreasing the effective fluctuations of after-tax individual income. By compressing the idiosyncratic component o personal income fluctuations, higher marginal taxes should be negatively correlated with the dispersion of consumption across households, a necessary implication of an insurance effect of taxation. Our study empirically examines this negative correlation, exploiting the ample variation of state taxes across US states. We show that taxes are negatively correlated with the consumption dispersion of the within-state distribution of non-durable consumption and that this correlation is robust.