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This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies the martingale method. More precisely, we construct the non-separable value function by formalizing the optimal constrained terminal wealth to be a (conjectured) contingent claim on the optimal non-constrained terminal wealth. This is relevant by itself, but also opens up the opportunity to derive new solutions to constrained problems. As a second contribution, we thus derive new results for non-strict constraints on the shortfall of inter¬mediate wealth and/or consumption.
In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development.
This paper constructs a dynamic model of health insurance to evaluate the short- and long run effects of policies that prevent firms from conditioning wages on health conditions of their workers, and that prevent health insurance companies from charging individuals with adverse health conditions higher insurance premia. Our study is motivated by recent US legislation that has tightened regulations on wage discrimination against workers with poorer health status (Americans with Disability Act of 2009, ADA, and ADA Amendments Act of 2008, ADAAA) and that will prohibit health insurance companies from charging different premiums for workers of different health status starting in 2014 (Patient Protection and Affordable Care Act, PPACA). In the model, a trade-off arises between the static gains from better insurance against poor health induced by these policies and their adverse dynamic incentive effects on household efforts to lead a healthy life. Using household panel data from the PSID we estimate and calibrate the model and then use it to evaluate the static and dynamic consequences of no-wage discrimination and no-prior conditions laws for the evolution of the cross-sectional health and consumption distribution of a cohort of households, as well as ex-ante lifetime utility of a typical member of this cohort. In our quantitative analysis we find that although a combination of both policies is effective in providing full consumption insurance period by period, it is suboptimal to introduce both policies jointly since such policy innovation induces a more rapid deterioration of the cohort health distribution over time. This is due to the fact that combination of both laws severely undermines the incentives to lead healthier lives. The resulting negative effects on health outcomes in society more than offset the static gains from better consumption insurance so that expected discounted lifetime utility is lower under both policies, relative to only implementing wage nondiscrimination legislation.
This paper investigates whether preference interactions can explain why risk preferences change over time and across contexts. We conduct an experiment in which subjects accept or reject gambles involving real money gains and losses. We introduce within-subject variation by alternating subjectively liked music and disliked music in the background. We find that favourite music increases risk-taking, and disliked music suppresses risk-taking, compared to a baseline of no music. Several theories in psychology propose mechanisms by which mood affects risktaking, but none of them fully explain our results. The results are, however, consistent with preference complementarities that extend to risk preference.
The complexity resulting from intertwined uncertainties regarding model misspecification and mismeasurement of the state of the economy defines the monetary policy landscape. Using the euro area as laboratory this paper explores the design of robust policy guides aiming to maintain stability in the economy while recognizing this complexity. We document substantial output gap mismeasurement and make use of a new model data base to capture the evolution of model specification. A simple interest rate rule is employed to interpret ECB policy since 1999. An evaluation of alternative policy rules across 11 models of the euro area confirms the fragility of policy analysis optimized for any specific model and shows the merits of model averaging in policy design. Interestingly, a simple difference rule with the same coefficients on inflation and output growth as the one used to interpret ECB policy is quite robust as long as it responds to current outcomes of these variables.
We argue that the U.S. personal saving rate’s long stability (1960s–1980s), subsequent steady decline (1980s–2007), and recent substantial rise (2008–2011) can be interpreted using a parsimonious ‘buffer stock’ model of consumption in the presence of labor income uncertainty and credit constraints. Saving in the model is affected by the gap between ‘target’ and actual wealth, with the target determined by credit conditions and uncertainty. An estimated structural version of the model suggests that increased credit availability accounts for most of the long-term saving decline, while fluctuations in wealth and uncertainty capture the bulk of the business-cycle variation.
We test whether investor mood affects trading with data on all stock market transactions in Finland, utilizing variation in daylight and local weather. We find some evidence that environmental mood variables (local weather, length of day, daylight saving and lunar phase) affect investors’ direction of trade and volume. The effect magnitudes are roughly comparable to those of classical seasonals, such as the Monday effect. The statistical significance of the mood variables is weak in many cases, however. Only very little of the day-to-day variation in trading is collectively explained by all mood variables and calendar effects, but lower frequency variation seems connected to holiday seasons.
This paper examines data on financial sophistication among the U.S. older population, using a special-purpose module implemented in the Health and Retirement Study. We show that financial sophistication is deficient for older respondents (aged 55+). Specifically, many in this group lack a basic grasp of asset pricing, risk diversification, portfolio choice, and investment fees. Subpopulations with particular deficits include women, the least educated, persons over the age of 75, and non-Whites. In view of the fact that people are increasingly being asked to take on responsibility for their own retirement security, such lack of knowledge can have serious implications.