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Displaying results 1 to 14 of 14.

  1. Local Projections
    Author: Jordà, Òscar; Taylor, Alan M.
    Published: August 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    A central question in applied research is to estimate the effect of an exogenous intervention or shock on an outcome. The intervention can affect the outcome and controls on impact and over time. Moreover, there can be subsequent feedback between... more

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    A central question in applied research is to estimate the effect of an exogenous intervention or shock on an outcome. The intervention can affect the outcome and controls on impact and over time. Moreover, there can be subsequent feedback between outcomes, controls and the intervention. Many of these interactions can be untangled using local projections. This method's simplicity makes it a convenient and versatile tool in the empiricist's kit, one that is generalizable to complex settings. This article reviews the state-of-the art for the practitioner, discusses best practices and possible extensions of local projections methods, along with their limitations

     
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  2. Building Non-Discriminatory Algorithms in Selected Data
    Author: Arnold, David; Dobbie, Will; Hull, Peter
    Published: May 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We develop new quasi-experimental tools to understand algorithmic discrimination and build non-discriminatory algorithms when the outcome of interest is only selectively observed. These tools are applied in the context of pretrial bail decisions,... more

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    We develop new quasi-experimental tools to understand algorithmic discrimination and build non-discriminatory algorithms when the outcome of interest is only selectively observed. These tools are applied in the context of pretrial bail decisions, where conventional algorithmic predictions are generated using only the misconduct outcomes of released defendants. We first show that algorithmic discrimination arises in such settings when the available algorithmic inputs are systematically different for white and Black defendants with the same objective misconduct potential. We then show how algorithmic discrimination can be eliminated by measuring and purging these conditional input disparities. Leveraging the quasi-random assignment of bail judges in New York City, we find that our new algorithms not only eliminate algorithmic discrimination but also generate more accurate predictions by correcting for the selective observability of misconduct outcomes

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w32403
    Subjects: Algorithmus; Schätztheorie; Prognose; Kriminalität; USA; Instrumental Variables (IV) Estimation; Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination; Illegal Behavior and the Enforcement of Law
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  3. Identifying the Cumulative Causal Effect of a Non-Binary Treatment from a Binary Instrument
    Author: Vohra, Vedant; Goldin, Jacob
    Published: May 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    The effect of a treatment may depend on the intensity with which it is administered. We study identification of ordered treatment effects with a binary instrument, focusing on the effect of moving from the treatment's minimum to maximum intensity.... more

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    The effect of a treatment may depend on the intensity with which it is administered. We study identification of ordered treatment effects with a binary instrument, focusing on the effect of moving from the treatment's minimum to maximum intensity. With arbitrary heterogeneity across units, standard IV assumptions (Angrist and Imbens, 1995) do not constrain this parameter, even among compliers. We consider a range of additional assumptions and show how they can deliver sharp, informative bounds. We illustrate our approach with two applications, involving the effect of (1) health insurance on emergency department usage, and (2) attendance in an after-school program on student learning

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w32425
    Subjects: Kausalanalyse; IV-Schätzung; Schätztheorie; Instrumental Variables (IV) Estimation
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  4. Causal Effects in Matching Mechanisms with Strategically Reported Preferences
    Author: Bertanha, Marinho; Luflade, Margaux; Mourifié, Ismael
    Published: May 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    A growing number of central authorities use assignment mechanisms to allocate students to schools in a way that reflects student preferences and school priorities. However, most real-world mechanisms incentivize students to strategically misreport... more

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    A growing number of central authorities use assignment mechanisms to allocate students to schools in a way that reflects student preferences and school priorities. However, most real-world mechanisms incentivize students to strategically misreport their preferences. In this paper, we provide an approach for identifying the causal effects of school assignment on future outcomes that accounts for strategic misreporting. Misreporting may invalidate existing point-identification approaches, and we derive sharp bounds for causal effects that are robust to strategic behavior. Our approach applies to any mechanism as long as there exist placement scores and cutoffs that characterize that mechanism's allocation rule. We use data from a deferred acceptance mechanism that assigns students to more than 1,000 university-major combinations in Chile. Matching theory predicts that students' behavior in Chile should be strategic because they can list only up to eight options, and we find empirical evidence consistent with such behavior. Our bounds are informative enough to reveal significant heterogeneity in graduation success with respect to preferences and school assignment

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Series: NBER working paper series ; no. w32434
    Subjects: Studierende; Matching; Hochschule; Asymmetrische Information; Bildungsniveau; Bildungsertrag; Schätzung; Chile; Econometrics; Hypothesis Testing: General; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Instrumental Variables (IV) Estimation
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  5. A Sharp Test for the Judge Leniency Design
    Author: Coulibaly, Mohamed; Hsu, Yu-Chin; Mourifié, Ismael; Wan, Yuanyuan
    Published: May 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the... more

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    We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed sharp test is asymptotically valid and consistent and will not make discordant recommendations. When the judge's leniency design assumptions are rejected, we propose a way to salvage the model using partial monotonicity and exclusion assumptions, under which a variant of the Local Instrumental Variable (LIV) estimand can recover the Marginal Treatment Effect. Simulation studies show our test outperforms existing non-sharp tests by significant margins. We apply our test to assess the validity of the judge leniency design using data from Stevenson (2018), and it rejects the validity for three crime categories: robbery, drug selling, and drug possession

     
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    Source: Union catalogues
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    Series: NBER working paper series ; no. w32456
    Subjects: IV-Schätzung; Statistischer Test; Kausalanalyse; Kriminalität; Ökonometrie; "Judge Leniency" Design; Econometric and Statistical Methods and Methodology: General; Hypothesis Testing: General; Methodological Issues: General; Instrumental Variables (IV) Estimation
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  6. On Recoding Ordered Treatments as Binary Indicators
    Author: Rose, Evan K.; Shem-Ṭov, Yotam
    Published: March 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    Researchers using instrumental variables to investigate ordered treatments often recode treatment into an indicator for any exposure. We investigate this estimand under the assumption that the instruments shift compliers from no treatment to some but... more

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    Researchers using instrumental variables to investigate ordered treatments often recode treatment into an indicator for any exposure. We investigate this estimand under the assumption that the instruments shift compliers from no treatment to some but not from some treatment to more. We show that when there are extensive margin compliers only (EMCO) this estimand captures a weighted average of treatment effects that can be partially unbundled into each complier group's potential outcome means. We also establish an equivalence between EMCO and a two-factor selection model and apply our results to study treatment heterogeneity in the Oregon Health Insurance Experiment

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Series: NBER working paper series ; no. w32234
    Subjects: IV-Schätzung; Schätztheorie; Ökonometrie; Econometrics; Instrumental Variables (IV) Estimation
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  7. "Something Works" in U.S. Jails
    Misconduct and Recidivism Effects of the IGNITE Program
    Author: Alsan, Marcella; Barnett, Arkey M.; Hull, Peter; Yang, Crystal
    Published: March 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    A longstanding and influential view in U.S. correctional policy is that "nothing works" when it comes to rehabilitating incarcerated individuals. We revisit this hypothesis by studying an innovative law-enforcement-led program launched in the county... more

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    A longstanding and influential view in U.S. correctional policy is that "nothing works" when it comes to rehabilitating incarcerated individuals. We revisit this hypothesis by studying an innovative law-enforcement-led program launched in the county jail of Flint, Michigan: Inmate Growth Naturally and Intentionally Through Education (IGNITE). We develop an instrumental variable approach to estimate the effects of IGNITE exposure, which leverages quasi-random court delays that cause individuals to spend more time in jail both before and after the program's launch. Holding time in jail fixed, we find that one additional month of IGNITE exposure reduces within-jail misconduct by 49% and reduces three-month recidivism by 18%, with the recidivism effects growing over time. Surveys of staff and community members, along with administrative test score records and within-jail text messages, suggest that cultural change and improved literacy and numeracy scores are key contributing mechanisms

     
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    Source: Union catalogues
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    Series: NBER working paper series ; no. w32282
    Subjects: Straftäter; Strafvollzug; Straffälligenhilfe; Bildungsertrag; Wirkungsanalyse; USA; Instrumental Variables (IV) Estimation; Returns to Education; Legal Procedure, the Legal System, and Illegal Behavior
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  8. Negative Weights are No Concern in Design-Based Specifications
    Author: Borusyak, Kirill; Hull, Peter
    Published: January 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    Recent work shows that popular partially-linear regression specifications can put negative weights on some treatment effects, potentially producing incorrectly-signed estimands. We counter by showing that negative weights are no problem in... more

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    Recent work shows that popular partially-linear regression specifications can put negative weights on some treatment effects, potentially producing incorrectly-signed estimands. We counter by showing that negative weights are no problem in design-based specifications, in which low-dimensional controls span the conditional expectation of the treatment. Specifically, the estimands of such specifications are convex averages of causal effects with "ex-ante" weights that average the potentially negative "ex-post" weights across possible treatment realizations. This result extends to design-based instrumental variable estimands under a first-stage monotonicity condition, and applies to "formula" treatments and instruments such as shift-share instruments

     
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    Source: Union catalogues
    Language: English
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    Series: NBER working paper series ; no. w32017
    Subjects: Kausalanalyse; Schätztheorie; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Instrumental Variables (IV) Estimation
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  9. The Role of Friends in the Opioid Epidemic
    Author: Adamopoulou, Effrosyni; Greenwood, Jeremy; Guner, Nezih; Kopecky, Karen A.
    Published: January 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    The role of friends in the US opioid epidemic is examined. Using data from the National Longitudinal Survey of Adolescent Health (Add Health), adults aged 25-34 and their high school best friends are focused on. An instrumental variable technique is... more

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    The role of friends in the US opioid epidemic is examined. Using data from the National Longitudinal Survey of Adolescent Health (Add Health), adults aged 25-34 and their high school best friends are focused on. An instrumental variable technique is employed to estimate peer effects in opioid misuse. Severe injuries in the previous year are used as an instrument for opioid misuse in order to estimate the causal impact of someone misusing opioids on the probability that their best friends also misuse. The estimated peer effects are significant: Having a best friend with a reported serious injury in the previous year increases the probability of own opioid misuse by around 7 percentage points in a population where 17 percent ever misuses opioids. The effect is driven by individuals without a college degree and those who live in the same county as their best friends

     
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    Source: Union catalogues
    Language: English
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    Series: NBER working paper series ; no. w32032
    Subjects: Droge; Drogenkonsum; Soziale Gruppe; Soziales Netzwerk; Jugendliche; Junge Erwachsene; IV-Schätzung; USA; Instrumental Variables (IV) Estimation; General; Health Behavior; Demographic Trends, Macroeconomic Effects, and Forecasts
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  10. Examiner and Judge Designs in Economics
    A Practitioner's Guide
    Author: Chyn, Eric; Frandsen, Brigham; Leslie, Emily C.
    Published: April 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    This article provides empirical researchers with an introduction and guide to research designs based on variation in judge and examiner tendencies to administer treatments or other interventions. We review the basic theory behind the research design,... more

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    This article provides empirical researchers with an introduction and guide to research designs based on variation in judge and examiner tendencies to administer treatments or other interventions. We review the basic theory behind the research design, outline the assumptions under which the design identifies causal effects, describe empirical tests of those assumptions, and discuss tradeoffs associated with choices researchers must make for estimation. We demonstrate concepts and best practices concretely in an empirical case study that uses an examiner tendency research design to study the effects of pre-trial detention

     
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    Source: Union catalogues
    Language: English
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    Series: NBER working paper series ; no. w32348
    Subjects: Wissenschaftliche Methode; Kausalanalyse; Empirische Methode; Schätztheorie; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Instrumental Variables (IV) Estimation; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models; Quantitative Policy Modeling; Criminal Law
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  11. Instrumental Variables with Unobserved Heterogeneity in Treatment Effects
    Author: Mogstad, Magne; Torgovitsky, Alexander
    Published: September 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    This chapter synthesizes and critically reviews the modern instrumental variables (IV) literature that allows for unobserved heterogeneity in treatment effects (UHTE). We start by discussing why UHTE is often an essential aspect of IV applications in... more

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    This chapter synthesizes and critically reviews the modern instrumental variables (IV) literature that allows for unobserved heterogeneity in treatment effects (UHTE). We start by discussing why UHTE is often an essential aspect of IV applications in economics and we explain the conceptual challenges raised by allowing for it. Then we review and survey two general strategies for incorporating UHTE. The first strategy is to continue to use linear IV estimators designed for classical constant (homogeneous) treatment effect models, acknowledge their likely misspecification, and attempt to reverse engineer an attractive interpretation in the presence of UHTE. This strategy commonly leads to interpretations of linear IV that involve local average treatment effects (LATEs). We review the various ways in which the use and justification of LATE interpretations have expanded and contracted since their introduction in the early 1990s. The second strategy is to forward engineer new estimators that explicitly allow for UHTE. This strategy has its roots in the Gronau-Heckman selection model of the 1970s, ideas from which have been revitalized through marginal treatment effects (MTE) analysis. We discuss implementation of MTE methods and draw connections with related control function and bounding methods that are scattered throughout the econometric and causal inference literature

     
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    Source: Union catalogues
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    Series: NBER working paper series ; no. w32927
    Subjects: IV-Schätzung; Kausalanalyse; Schätztheorie; Instrumental Variables (IV) Estimation
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  12. Lee Bounds With Multilayered Sample Selection
    Author: Kroft, Kory; Mourifié, Ismael; Vayalinkal, Atom
    Published: September 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    This paper investigates the causal effect of job training on wage rates in the presence of firm heterogeneity. When training affects worker sorting to firms, sample selection is no longer binary but is "multilayered". This paper extends the canonical... more

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    This paper investigates the causal effect of job training on wage rates in the presence of firm heterogeneity. When training affects worker sorting to firms, sample selection is no longer binary but is "multilayered". This paper extends the canonical Heckman (1979) sample selection model - which assumes selection is binary - to a setting where it is multilayered, and shows that in this setting Lee bounds set identifies a total effect that combines a weighted-average of the causal effect of job training on wage rates across firms with a weighted-average of the contrast in wages between different firms for a fixed level of training. Thus, Lee bounds set identifies a policy-relevant estimand only when firms pay homogeneous wages and/or when job training does not affect worker sorting across firms. We derive sharp bounds for the causal effect of job training on wage rates at each firm which leverage information on firm-specific wages. We illustrate our partial identification approach with an empirical application to the Job Corps Study. Results show that while conventional Lee bounds are strictly positive, our within-firm bounds include 0 showing that canonical Lee bounds may be capturing a pure sorting effect of job training

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w32952
    Subjects: Arbeitsmarktpolitik; Qualifikation; Weiterbildung; Berufsbildung; Beschäftigungseffekt; Wirkungsanalyse; Lohn; Schätzung; USA; Econometrics; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Instrumental Variables (IV) Estimation; General; Human Capital; Skills; Occupational Choice; Labor Productivity; Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions
    Scope: 1 Online-Ressource, illustrations (black and white)
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  13. On the Identifying Power of Generalized Monotonicity for Average Treatment Effects
    Author: Bai, Yuehao; Huang, Shunzhuang; Moon, Sarah; Shaikh, Azeem M.; Vytlacil, Edward
    Published: September 2024
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    In the context of a binary outcome, treatment, and instrument, Balke and Pearl (1993, 1997) establish that the monotonicity condition of Imbens and Angrist (1994) has no identifying power beyond instrument exogeneity for average potential outcomes... more

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    Universitätsbibliothek Freiburg
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    In the context of a binary outcome, treatment, and instrument, Balke and Pearl (1993, 1997) establish that the monotonicity condition of Imbens and Angrist (1994) has no identifying power beyond instrument exogeneity for average potential outcomes and average treatment effects in the sense that adding it to instrument exogeneity does not decrease the identified sets for those parameters whenever those restrictions are consistent with the distribution of the observable data. This paper shows that this phenomenon holds in a broader setting with a multi-valued outcome, treatment, and instrument, under an extension of the monotonicity condition that we refer to as generalized monotonicity. We further show that this phenomenon holds for any restriction on treatment response that is stronger than generalized monotonicity provided that these stronger restrictions do not restrict potential outcomes. Importantly, many models of potential treatments previously considered in the literature imply generalized monotonicity, including the types of monotonicity restrictions considered by Kline and Walters (2016), Kirkeboen et al. (2016), and Heckman and Pinto (2018), and the restriction that treatment selection is determined by particular classes of additive random utility models. We show through a series of examples that restrictions on potential treatments can provide identifying power beyond instrument exogeneity for average potential outcomes and average treatment effects when the restrictions imply that the generalized monotonicity condition is violated. In this way, our results shed light on the types of restrictions required for help in identifying average potential outcomes and average treatment effects

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w32983
    Subjects: Kausalanalyse; Schätztheorie; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models; Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Instrumental Variables (IV) Estimation
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  14. The role of friends in the opioid epidemic
    Author: Adamopoulou, Effrosyni; Greenwood, Jeremy; Guner, Nezih; Kopecky, Karen A.
    Published: 2024
    Publisher:  Universitätsbibliothek Mannheim, Mannheim