Causal Effects of Monetary Shocks: Semiparametric Conditional Independence Tests with a Multinomial Propensity Score

Macroeconomists have long been concerned with the causal effects of monetary policy. When the identification of causal effects is based on a selection-on-observables assumption, non-causality amounts to the conditional independence of outcomes and policy changes. This paper develops a semiparametric test for conditional independence in time series models linking a multinomial policy variable with unobserved potential outcomes. Our approach to conditional independence testing is motivated by earlier parametric tests, as in Romer and Romer (1989, 1994, 2004). The procedure developed here is semiparametric in the sense that we model the process determining the distribution of treatment – the policy propensity score – but leave the model for outcomes unspecified. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. This leads to a generalized definition of Sims (1980) causality. A technical contribution is the development of root-T consistent distribution-free inference methods for full conditional independence testing, appropriate for dependent data and allowing for first-step estimation of the propensity score.monetary policy, propensity score, multinomial treatments, causality

Semiparametric Causality Tests Using the Policy Propensity Score

Time series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a semi-parametric test for causality in models linking a binary treatment or policy variable with unobserved potential outcomes. The procedure is semiparametric in the sense that we model the process determining treatment -- the policy propensity score -- but leave the model for outcomes unspecified. This general approach is motivated by the notion that we typically have better prior information about the policy determination process than about the macro-economy. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. This leads to a generalized definition of Sims (1980) causality. We also develop a test for full conditional independence, in contrast with the usual focus on mean independence. Our approach is illustrated using data from the Romer and Romer (1989) study of the relationship between the Federal reserve's monetary policy and output.

Charter Schools and the Road to College Readiness: The Effects on College Preparation, Attendance and Choice

The analysis here focuses on Boston's charter high schools. For the purpose of this report, an analysis of high schools is both a necessity and a virtue. It is necessary to study high schools because most students applying to charters in earlier grades are not yet old enough to generate data on postsecondary outcomes. Charter high schools are also of substantial policy interest: a growing body of research argues that high school may be too late for cost-effective human capital interventions. Indeed, impact analyses of interventions for urban youth have mostly generated disappointing results.This report is interested in ascertaining whether charter schools, which in Massachusetts are largely budget-neutral, can have a substantial impact on the life course of affected students. The set of schools studied here comes from an earlier investigation of the effects of charter attendance in Boston on test scores.The high schools from the earlier study, which enroll the bulk of charter high school students in Boston, generate statistically and socially significant gains on state assessments in the 10th grade. This report questions whether these gains are sustained

Causal effects of monetary shocks: semiparametric conditional independence tests with a multinomial propensity score

Macroeconomists have long been concerned with the causal effects of monetary policy. When the identification of causal effects is based on a selection-on-observables assumption, non-causality amounts to the conditional independence of outcomes and policy changes. This paper develops a semiparametric test for conditional independence in time series models linking a multinomial policy variable with unobserved potential outcomes. Our approach to conditional independence testing is motivated by earlier parametric tests, as in Romer and Romer (1989, 1994, 2004). The procedure developed here is semiparametric in the sense that we model the process determining the distribution of treatment - the policy propensity score - but leave the model for outcomes unspecified. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. This leads to a generalized definition of Sims (1980) causality. A technical contribution is the development of root-T consistent distribution-free inference methods for full conditional independence testing, appropriate for dependent data and allowing for first-step estimation of the propensity score

A genome blogger manifesto

Cheap prices for genomic testing have revolutionized consumers’ access to personal genomics. Exploration of personal genomes poses significant challenges for customers wishing to learn beyond provider customer reports. A vibrant community has spontaneously appeared blogging experiences and data as a way to learn about their personal genomes. No set of values has publicly been described to date encapsulating ideals and code of conduct for this community. Here I present a first attempt to address this vacuum based on my own personal experiences as genome blogger

What a difference a term makes:the effect of educational attainment on marital outcomes in the UK

Abstract In the past, students in England and Wales born within the first 5 monthsof the academic year could leave school one term earlier than those born later inthe year. Focusing on women, those who were required to stay on an extra termmore frequently hold some academic qualification. Using having been required tostay on as an exogenous factor affecting academic attainment, we find that holding alow-level academic qualification has no effect on the probability of being currentlymarried for women aged 25 or above, but increases the probability of the husbandholding some academic qualification and being economically active.33 Halama

'Making it count': incentives, student effort and performance

This paper examines how incentives to participate in online assessments (quizzes) affect students’ effort and performance. Our identification strategy exploits within-student weekly variation in incentives to attempt online quizzes. We find tournament incentives and participation incentives to be ineffective in increasing quiz participation. In contrast, making the quiz counts towards the final grade substantially increases participation. We find no evidence of displacement of effort between weeks. Using a natural experiment which provides variation in assessment weighting of the quizzes between two cohorts, we find that affected students obtain better exam grades. We estimate the return to 10% assessment weighting to be around 0.27 of a standard deviation in the in-term exam grade. We find no evidence that assessment weighting has unintended consequences, i.e., that increased quiz effort: displaces effort over the year; reduces other forms of effort; or reduces (effort and thus) performance in other courses. Finally, assessment weighting induced effort increases most for students at and below median ability, resulting in a reduction of the grade gap by 17%

What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?

We study models with discrete endogenous variables and compare the use of two stage least squares (2SLS) in a linear probability model with bounds analysis using a nonparametric instrumental variable model. 2SLS has the advantage of providing an easy to compute point estimator of a slope coefficient which can be interpreted as a local average treatment effect (LATE). However, the 2SLS estimator does not measure the value of other useful treatment effect parameters without invoking untenable restrictions. The nonparametric instrumental variable (IV) model has the advantage of being weakly restrictive, so more generally applicable, but it usually delivers set identification. Nonetheless it can be used to consistently estimate bounds on many parameters of interest including, for example, average treatment effects. We illustrate using data from Angrist & Evans (1998) and study the effect of family size on female employment

Technology and collective action: the effect of cell phone coverage on political violence in Africa

The spread of cell phone technology across Africa has transforming effects on the economic and political sphere of the continent. In this paper, we investigate the impact of cell phone technology on violent collective action. We contend that the availability of cell phones as a communication technology allows political groups to overcome collective action problems more easily and improve in-group cooperation, and coordination. Utilizing novel, spatially disaggregated data on cell phone coverage and the location of organized violent events in Africa, we are able to show that the availability of cell phone coverage significantly and substantially increases the probability of violent conflict. Our findings hold across numerous different model specifications and robustness checks, including cross-sectional models, instrumental variable techniques, and panel data method

Human Capital at Home: Evidence from a Randomized Evaluation in the Philippines

Children spend most of their time at home in their early years, yet efforts to promote human capital at home in many low- and middle-income settings remain limited. We conduct a randomized controlled trial to evaluate an intervention which encourages parents and caregivers to foster human capital accumulation among their children between ages 3 and 5, with a focus on math and phonics skills. Children gain 0.52 and 0.51 standard deviations relative to the control group on math and phonics tests, respectively (p\u3c0.001). A year later effects persist, but math gains dissipate to 0.15 (p=0.06) and phonics to 0.13 (p=0.12). Effects appear to be mediated largely through instructional support by parents and not other parent investment mechanisms, such as more positive parent-child interactions or additional time spent on education at home beyond the intervention. Our results show that parents can be effective conduits of educational instruction even in low-resource settings