How do Training Programs Assign Participants to Training? Characterizing the Assignment Rules of Government Agencies for Welfare-to-Work Programs in California

A great deal of attention has been paid in the literature to estimating the impacts of training programs. Much less attention has been devoted to how training agencies assign participants to training programs, and to how these allocation decisions vary with agency resources, the initial skill levels of participants and the prevailing labor market conditions. This paper models the training assignment problem faced by welfare agencies, deriving empirical implications regarding aggregate training policies and testing these implications using data from Welfare-to-Work training programs run by California counties during the 1990s. I find that county welfare agencies do not seem to follow a simple returns-maximization model in their training assignment decisions. The results show that, as suggested by political economy models, the local political environment has a strong effect on training policies. In particular, I find that going from a Republican to a Democratic majority in a county's Board of Supervisors has a strong effect on training policies, significantly increasing the proportion of welfare recipients receiving human capital development training.Assignment to Training Rules, Welfare to Work Programs, Local Political Environment

Intergenerational transmission of welfare dependency: The effects of length of exposure

It is well documented that a positive correlation exists between receiving welfare as a child and depending on welfare as an adult. However, previous studies have not been able to explore many aspects of this relationship. This paper uses a unique administrative dataset for California, which follows welfare recipients since their teenage years until early adulthood, to study the causal effects of different lengths of welfare exposure as a child (conditional on welfare receipt) on future welfare dependency as a young adult. The econometric analyses in this paper use a recently developed method from the program evaluation literature, based on the estimation of a generalized propensity score (GPS). As in the binary-treatment case the GPS permits removing the biases associated with differences in the observed characteristics of individuals. In addition, for some analyses, family-level unobserved heterogeneity is controlled for by relying on pairs of siblings exposed to different lengths of exposure. The results show that there is no causal effect of length of exposure on future welfare dependency, nor on teenage childbearing. Conditional on teenage childbearing, there are no effects of length of exposure on adult welfare dependency either, but this dependency is almost three times larger for teenage mothers than for non-mothers. All results hold when controlling for unobserved heterogeneity. The results indicate that policies like time-limits are not likely to reduce the intergenerational correlation of welfare dependency.Welfare Dependency, Continuous Treatments

Not So Lucky Any More: CEO Compensation in Financially Distressed Firms

There is a debate on whether executive pay reflects rent extraction due to “managerial power” or is the result of arms-length bargaining in a principal-agent framework. In this paper we offer a test of the managerial power hypothesis by empirically examining the CEO compensation of U.S. public companies that were ever in financial distress between 1992 and 2005. Using a bias-corrected matching estimator that estimates the causal effects of financial distress, we find that, for the distressed firms, CEO turnover rates increase markedly and their CEOs, both incumbents and successors, experience significant reductions in total compensation. The bulk of the reduction in total compensation derives from the decline in value of stock option grants, which we argue is due to a change in the opportunistic timing of option grants. We define “lucky” grants as those with grant prices below or at the lowest stock price of the grant month, and we find that the proportion of lucky grants for financially distressed firms is higher before insolvency and lower upon and after insolvency, while the proportion for similar but solvent firms remains stable throughout the period. We interpret this evidence as consistent with a decrease in managerial power induced by a tightening in the “outrage” constraint due to the episode of financial distress.CEO compensation, CEO turnover, financial distress, lucky grants, bias-corrected matching estimators

CEO Power and Compensation in Financially Distressed Firms

We study the changes in CEO power and compensation that arise when firms go through financial distress. We use a matching estimator to identify suitable controls and estimate the causal effects of financial distress for a sample of U.S. public companies from 1992 to 2005. We document that, relative to those in control firms, the CEOs of distressed firms experience significant reductions in total compensation; the bulk of this reduction derives from the decline in value of new grants of stock options. These results hold not only for incumbent CEOs but also, surprisingly, for newly hired CEOs. Financial distress has important consequences on corporate governance, decreasing managerial influence over the board. We find that, among distressed firms, there is a significant decrease in the proportion of CEOs holding board chairmanship, and in the fractions of executives serving as directors or in the compensation committee of the board. We also show that periods of financial distress are associated with a decrease in opportunistic timing behavior of stock option awards. The results are suggestive of a link between managerial power and executive compensation.CEO compensation, financial distress, lucky grants, managerial influence, bias-corrected matching estimators

Wavefunctions from energies: Applications in simple potentials

A remarkable mathematical property—somehow hidden and recently rediscovered—allows obtaining the eigenvectors of a Hermitian matrix directly from their eigenvalues. This opens the possibility to get the wavefunctions from the spectrum, an elusive goal of many fields in physics. Here, the formula is assessed for simple potentials, recovering the theoretical wavefunctions within machine accuracy. A striking feature of this eigenvalue–eigenvector relation is that it does not require knowing any of the entries of the working matrix. However, it requires the knowledge of the eigenvalues of the minor matrices (in which a row and a column have been deleted from the original matrix). We found a pattern in these sub-matrix spectra, allowing us to get the eigenvectors analytically. The physical information hidden behind this pattern is analyzed.Fil: Mitnik, Dario Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Mitnik, Santiago A. H.. Universidad Nacional de San Martín. Escuela de Política y Gobierno; Argentin

Not So Lucky Any More: CEO Compensation in Financially Distressed Firms

There is a debate on whether executive pay reflects rent extraction due to "managerial power" or is the result of arms-length bargaining in a principal-agent framework. In this paper we offer a test of the managerial power hypothesis by empirically examining the CEO compensation of U.S. public companies that were ever in financial distress between 1992 and 2005. Using a bias-corrected matching estimator that estimates the causal effects of financial distress, we find that, for the distressed firms, CEO turnover rates increase markedly and their CEOs, both incumbents and successors, experience significant reductions in total compensation. The bulk of the reduction in total compensation derives from the decline in value of stock option grants, which we argue is due to a change in the opportunistic timing of option grants. We define "lucky" grants as those with grant prices below or at the lowest stock price of the grant month, and we find that the proportion of lucky grants for financially distressed firms is higher before insolvency and lower upon and after insolvency, while the proportion for similar but solvent firms remains stable throughout the period. We interpret this evidence as consistent with a decrease in managerial power induced by a tightening in the "outrage" constraint due to the episode of financial distress.CEO compensation, CEO turnover, financial distress, lucky grants, bias-corrected matching estimators

Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data

This paper assesses the effectiveness of unconfoundedness-based estimators of mean effects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among several control groups from a randomized experiment. We study linear regression estimators as well as partial mean and weighting estimators based on the generalized propensity score (GPS). We also study the use of the GPS in assessing the comparability of individuals among the different treatment groups, and propose a strategy to determine the overlap or common support region that is less stringent than those previously used in the literature. Our results show that in the multiple treatment setting there may be treatment groups for which it is extremely difficult to find valid comparison groups, and that the GPS plays a significant role in identifying those groups. In such situations, the estimators we consider perform poorly. However, their performance improves considerably once attention is restricted to those treatment groups with adequate overlap quality, with difference-in-difference estimators performing the best. Our results suggest that unconfoundedness-based estimators are a valuable econometric tool for evaluating multiple treatments, as long as the overlap quality is satisfactory.multiple treatments, nonexperimental estimators, generalized propensity score

Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data

This paper assesses the e¤ectiveness of unconfoundedness-based estimators of mean e¤ects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among several control groups from a randomized experiment. We study linear regression estimators as well as partial mean and weighting estimators based on the generalized propensity score (GPS). We also study the use of the GPS in assessing the comparability of individuals among the di¤erent treatment groups, and propose a strategy to determine the overlap or common support region that is less stringent than those previously used in the literature. Our results show that in the multiple treatment setting there may be treatment groups for which it is extremely di¢ cult to ?nd valid comparison groups, and that the GPS plays a signi?cant role in identifying those groups. In such situations, the estimators we consider perform poorly. However, their performance improves considerably once attention is restricted to those treatment groups with adequate overlap quality, with di¤erence-in-di¤erence estimators performing the best. Our results suggest that unconfoundedness-based estimators are a valuable econometric tool for evaluating multiple treatments, as long as the overlap quality is satisfactory.

Post-9/11 Media Coverage of Terrorism

Media coverage of terrorist attacks plays an important role in shaping the public understanding of terrorism. While there have been several studies analyzing coverage of terrorist incidents prior to 9/11, there has been little research examining post-9/11 coverage. This study fills this gap by examining the media’s coverage of terrorism in the United States between the dates of September 12, 2001 and December 31, 2015. The analysis is based on a list of terrorist-related incidents and New York Times articles written on each incident. This study documents the amount of coverage received by these incidents and identifies the variables influencing whether an incident is covered and how much space it receives. It also provides a qualitative analysis of coverage of the top 15 most news producing incidents. The results follow a similar pattern to pre-9/11 findings, where most terrorist incidents receive no coverage and a select few are sensationalized. Incidents with casualties or injuries, Jihadi perpetrators, governmental targets, or firearms are significantly more likely to be covered and receive more news space. Additionally, qualitative analysis indicates that coverage of Jihadi incidents tends to present them as international even when the perpetrators are domestic