Contributions in Merlin

Many statistical applications require an estimate of a covariance matrix and/or its inverse. When the matrix dimension is large compared to the sample size, which happens frequently, the sample covariance matrix is known to perform poorly and may suffer from ill-conditioning. There already exists an extensive literature concerning improved estimators in such situations. In the absence of further knowledge about the structure of the true covariance matrix, the most successful approach so far, arguably, has been shrinkage estimation. Shrinking the sample covariance matrix to a multiple of the identity, by taking a weighted average of the two, turns out to be equivalent to linearly shrinking the sample eigenvalues to their grand mean, while retaining the sample eigenvectors. Our paper extends this approach by considering nonlinear transformations of the sample eigenvalues. We show how to construct an estimator that is asymptotically equivalent to an oracle estimator suggested in previous work. As demonstrated in extensive Monte Carlo simulations, the resulting bona fide estimator can result in sizeable improvements over the sample covariance matrix and also over linear shrinkage.

We study the effect of civil conflict on social capital, focusing on the experience of Uganda during the last decade. Using individual and county-level data, we document causal effects on trust and ethnic identity of an exogenous outburst of ethnic conflicts in 2002-04. We exploit two waves of survey data from Afrobarometer 2000 and 2008, including information on socioeconomic characteristics at the individual level, and geo-referenced measures of fighting events from ACLED. Our identification strategy exploits variations in the intensity of fighting both in the spatial and cross-ethnic dimensions. We find that more intense fighting decreases generalized trust and increases ethnic identity. The effects are quantitatively large and robust to a number of control variables, alternative measures of violence, and different statistical techniques involving ethnic and county fixed effects and instrumental variables. We also document that the post-war effects of ethnic violence depend on the ethnic fractionalization. Fighting has a negative effect on the economic situation in highly fractionalized counties, but has no effect in less fractionalized counties. Our findings are consistent with the existence of a self-reinforcing process between conflicts and ethnic cleavages.

In this paper, we quantitatively analyze to what extent a benevolent government should issue debt in a model where households are subject to idiosyncratic productivity shocks, insurance markets are missing and borrowing is restricted. In this environment, issuing government bonds facilitates saving for self-insurance. Despite this, we find that in a calibrated version of the model that is consistent with the skewed wealth and earnings distribution observable in the U.S., the government should buy private bonds, and not issue public debt in the long run. The reason is that in the U.S., a large fraction of the population has almost no wealth or is even in debt. The wealth-poor, however, do not profit from an increase in the interest rate following an increase in public debt. Instead, they gain from higher wages that result from a reduction in debt. We show that even when the short run costs of higher capital taxation are taken into account, it still pays off to reduce government debt on overall. Moreover, we find that endogenizing household’s borrowing constraints by assuming limited commitment leads to even higher asset levels being optimal in the long run.

A strategy profile of a game is called robustly stochastically stable if it is stochastically stable for a given behavioral model independently of the specification of revision opportunities and tie-breaking assumptions in the dynamics. We provide a simple radius-coradius result for robust stochastic stability and examine several applications. For the logit-response dynamics, the selection of potential maximizers is robust for the subclass of supermodular symmetric binary-action games. For the mistakes model, the weaker property of strategic complementarity suffices for robustness in this class of games. We also investigate the robustness of the selection of risk-dominant strategies in coordination games under best-reply and the selection of Walrasian strategies in aggregative games under imitation.

This paper studies the effect of leadership on the level and evolution of pro-social behavior using an artefactual field experiment on local public good provision. Participants decide how much to contribute to an actual conservation project. They can then revise their donations after being randomly matched in pairs on the basis of their authority and having observed each other’s contributions. Authority is measured through a social ranking exercise identifying formal and moral leaders within the community. I find that giving by a pair is higher and shows a lower tendency to decrease over time when a leader is part of a pair. This is because higher-ranked pair members in general, and leaders in particular, donate more and are less likely to revise contributions downwards after giving more than their counterparts. Leadership effects are stronger when moral authority is made salient within the experiment, in line with the ethical nature of the decision under study. These findings highlight the importance of identifying different forms of leadership and targeting the relevant leaders in projects aimed at local public good provision.

Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the random variable. The problem of constructing a corresponding joint prediction region has been rather neglected in the literature so far: such a region is supposed to contain the entire future path with a prespecified probability. We develop bootstrap methods to construct joint prediction regions. The resulting regions are proven to be asymptotically consistent under a mild high-level assumption. We compare the finitesample performance of our joint prediction regions to some previous proposals via Monte Carlo simulations. An empirical application to a real data set is also provided.

We introduce intention-based social preferences into a mechanism design framework with independent private values and quasilinear payoffs. For the case where the designer has no information about the intensity of social preferences, we provide conditions under which mechanisms which have been designed under the assumption that agents are selfish can still be implemented. For the case where precise information about social preferences is available, we show that any tension between efficiency, incentive-compatibility, and voluntary participation may disappear. Impossibility results such as the one by Myerson and Satterthwaite (1983) are then turned into possibility results. We also provide a systematic account of the welfare implications of kindness sensations.

This study compares individual preferences across incentives (i.e., hypothetical vs. real incentives) and over time (i.e. elicitation at two different points in time) in a choice experiment involving charitable donating decisions. We provide evidence of hypothetical bias but little evidence of instability of individual giving. There is significant heterogeneity in individual preferences, with real incentives either dampening or pronouncing the observed donating behaviour. Neither hypothetical bias nor instability is observed when we examine the propensity of individuals to make internally consistent decisions over identical choices.

Governments all over the world have invested tens of billions of dollars in car scrappage programs to fuel the economy in 2009. We investigate the German case using a unique micro transaction dataset covering the years 2007 to 2010. Our focus is on the incidence of the subsidy, i.e., we ask how much of the € 2,500 buyer subsidy is captured by the supply-side through an increase in selling prices.Using regression analysis, we find that average prices in fact decreased for subsidized buyers in comparison to non-subsidized ones, suggesting that eventually subsidized customers benefitted by more than the subsidy amount. However, the incidence was heterogeneous across price segments. Subsidized buyers of cheap cars paid more than comparable buyers who did not receive the subsidy, e.g. for cars of € 12,000 car dealers reaped about 8% of the scrappage prime. The opposite was true for more expensive cars, e.g. subsidized buyers of cars of € 32,000 were granted an extra discount of about € 1,100. For cars priced about € 18,000, we find no price discrimination, i.e., in this price segment consumers fully captured the transfer. Our results can be explained by optimizing behavior on the supply-side both in the lower and upper price segments. The results are extremely robust to extensive sensitivity checks.