Optimal lockdown in altruistic economies

The recent COVID-19 crisis has revealed the urgent need to study the impact of an infectious disease on market economies and provide adequate policy recommendations. The present paper studies the optimal lockdown policy in a dynamic general equilibrium model where households are altruistic and they care about the share of infected individuals. The spread of the disease is modeled here using SIS dynamics, which implies that recovery does not confer immunity. To avoid non-convexity issues, we assume that the lockdown is constant in time. This strong assumption allows us to provide analytical solutions. We find that the zero lockdown is efficient when agents do not care about the share of infected, while a positive lockdown is recommended beyond a critical level of altruism. Moreover, the lockdown intensity increases in the degree of altruism. Our robust analytical results are illustrated by numerical simulations, which show, in particular, that the optimal lockdown never trespasses 60% and that eradication is not always optimal.     

Moral hazard,debt overhang and capital structure

This paper investigates the impact of managerial moral hazard on the debt overhang of a firm by constructing a contingent claims model in which the manager faces costly effort. Using a calibrated capital structure model, we show that the costs of debt overhang become more serious in the presence of managerial moral hazard. Such costs even account for more than half of the total agency costs at a high level of cash flow. Moreover, in contrast to the results of Hackbarth and Mauer (2012), our model predicts a U-shaped relationship between the leverage ratio and investment opportunities of a firm, which is caused by managers’ moral hazard. Finally, by considering this moral hazard, we also show the coexistence of low leverage ratios and high credit spreads, which explains the phenomenon of “low debt levels and high credit spreads” observed in practice.     

Equity premium prediction and optimal portfolio decision with Bagging

We propose using the statistical method of Bagging to forecast the equity premium out-of-sample for multivariate regression models. Bagging allows for the flexible and efficient extraction of valuable informational content from a large set of predictors, leading to statistically and economically significant gains relative to not only the historical mean, but also other soft-threshold methods such as forecast combinations and shrinkage estimators in our empirical results. Furthermore, we find that the source of economic gains for Bagging primarily comes from the fact that it encourages the investor to actively manage portfolio by flexibly utilizing short selling or leveraging to better time the market following correctly prognosticated trends. However, other strategies such as forecast combinations keep the equity shares nearly fixed regardless of the predicted market prospect.     

Examining the change in wellbeing following a holiday

Building on existing evidence that tourism contributes to wellbeing, this study aims to investigate how both hedonic and eudaimonic wellbeing changes after a holiday. A longitudinal inquiry involving three waves of observation (during, the fourth week, and the eighth week following a holiday) was carried out in five tourism cities in China, using Latent Growth Curve models to analyze change. Results suggest that life satisfaction – an indicator of hedonic wellbeing – does not decline as expected whereas other indicators of hedonic wellbeing declined dramatically in the first month and then mildly in the second month following a holiday. Comparatively, eudaimonic wellbeing declined gradually and mildly during the same two-month intervals. Higher levels of optimal tourism experiences predicted slower declines of both hedonic and eudaimonic wellbeing. Theoretical, methodological, and practical implications are discussed.     

Monetary policy,doubts and asset prices

Asset prices and the equity premium might reflect doubts and pessimism. Introducing these features in an otherwise standard New-Keynesian model changes optimal policy in a substantial way. There are three main results: (i) asset-price movements improve the inflation-output trade-off so that average output can rise without much inflation costs; (ii) a “paternalistic” policymaker – maximizing the expected utility of the consumers under the true probability distribution – chooses a more accommodating policy towards productivity shocks and inflates the equity premium; (iii) a “benevolent” policymaker – maximizing the objective through which decisionmakers act in their ambiguous world – follows a policy of price stability.     

Optimal granularity for portfolio choice

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because of parameter uncertainty. In this paper we suggest a grouping strategy in which we first form groups of equally weighted stocks and then optimize over the resulting groups only. This strategy aims at balancing the trade-off between the benefits from optimization and the losses from estimation risk. We rely on Monte-Carlo simulations to illustrate the performance of the strategy, and we derive the optimal group size for a simplified setup. Furthermore, we show that estimation risk also has an impact via the criterion by which the assets are sorted into groups (like the expected excess returns or betas), but does not negate the grouping approach. We relate our work to linear asset pricing models, and we conduct out of sample back-tests in order to confirm the validity of our grouping strategy empirically.     

Is econometrics useful for private policy making? A case study of replacement policy at an auto rental company

The goal of this paper is to illustrate the potential usefulness of econometrics as a tool to assist private policy makers. We provide a case study and detailed econometric analysis of the automobile replacement policy adopted by a large car rental company. Unlike public policy making–where the benefits from using econometric models and “science-based” approaches to policy making are hard to quantify because the outcomes of interest are typically subjective quantities such as “social welfare”–in the case of firms there is an objective, easily quantifiable criterion for judging whether policy A is better than policy B: profits. We introduce and estimate an econometric model of the rental histories of individual cars in the company’s fleet. Via stochastic simulations, we show that the model provides a good approximation to the company’s actual operations. In particular, the econometric model is able to reproduce the extraordinarily high rates of return that the company obtains on its rental cars, with average internal rates of return between purchase and sale of approximately 50%. However, the econometric model can simulate outcomes under a range of counterfactual vehicle replacement policies. We use the econometric model to simulate the profitability of an alternative replacement policy under pessimistic assumptions about the rate maintenance costs would increase and rental rates would have to be decreased if the company were to keep its rental cars longer than it does under the status quo. Depending on the vehicle type, we find that the company’s expected discounted profits would be between 6% to over 140% higher under the suggested alternative operating strategy where vehicles are kept longer and rental rates of older vehicles are discounted to induce customers to rent them. The company found this analysis to be sufficiently convincing that it undertook an experiment to verify the predictions of the econometric model.     

Gains from international monetary policy coordination: Does it pay to be different?

In a two country world where each country has a traded and a non-traded sector and each sector has sticky prices, optimal independent policy in general cannot replicate the natural-rate allocations. There are potential welfare gains from coordination since the planner under a cooperating regime internalizes a terms-of-trade externality that independent policymakers overlook. If the countries have symmetric trading structures, however, the gains from coordination are quantitatively small. With asymmetric trading structures, the gains can be sizable since, in addition to internalizing the terms-of-trade externality, the planner optimally engineers a terms-of-trade bias that favors the country with a larger traded sector.     

MIND THE GAP: UNEMPLOYMENT IN THE NEW EU REGIONS

Abstract.  The paper surveys the theoretical and empirical literature on regional unemployment during transition in Central and Eastern Europe. The focus is on optimal speed of transition (OST) models and on comparison of them with the neo-classical tradition. In the typical neo-classical models, spatial differences essentially arise as a consequence of supply side constraints and institutional rigidities. Slow-growth, high-unemployment regions are those with backward economic structures and constraints on factors mobility contribute to making differences persistent. However, such explanations leave the question unanswered of how unemployment differences arise in the first place. Economic transition provides an excellent testing ground to answer this question. Pre-figuring an empirical law, the OST literature finds that the high degree of labour turnover of high unemployment regions is associated with a high rate of industrial restructuring and, consequently, that low unemployment may be achieved by implementing transition more gradually. Moreover, international trade, foreign direct investment and various agglomeration factors help explain the success of capital cities compared to peripheral towns and rural areas in achieving low unemployment. The evidence of the empirical literature on supply side factors suggests that wage flexibility in Central and Eastern Europe is not lower than in other EU countries, while labour mobility seems to reinforce rather than change the spatial pattern of unemployment.     

Value creation with Dye’s disclosure option: optimal risk-shielding with an upper tailed disclosure strategy

Dye [J Account Res 23 (1985) 123] showed that the optimal disclosure policy, when a manager is randomly endowed with perfect private information, is upper tailed, i.e., the manager only discloses firm value above an appropriate cutoff level. We interpret this strategically as an optimal exercise by management of the embedded formal option to report value. Given any disclosure cutoff level, we value the corresponding option using contingent claims analysis. It is shown that the Dye disclosure cutoff value maximizes the formal option value. We find it to be the minimum possible conditional valuation (conditioned by non-disclosure) which is thus consistent with the intuition that investors should value conservatively. We show how the Dye cutoff can be interpreted as a strike price in a ‘protective put’ which offers a shield against risk of disclosure of low value. The strategic analysis is further extended by allowing the probability level that the manager is informed to be a choice variable. We show that the manager will never choose to be perfectly endowed with information, and is likely to be more endowed than unendowed. We also present a simple worked example which shows how the total value of the firm changes once the Dye option is formally incorporated.