Ideology and Performance in Public Organizations

All papers and comparison plots · Results JSON · Quarto source

3 of 3 registered specifications have estimates. Every registered specification appears below.

Spenkuch et al. (2023), ECMA

Data and estimation

Outcomes are divided by their unweighted source-sample standard deviation (ddof=1), before exclusions; they are not centered. Treatment adoption is the first observed treated period. Models share an eligible sample, fixed effects, controls and weights. Initially treated units, missing −1 baselines and unsupported untreated-outcome predictions are removed. For switching treatments, untreated rows after first adoption are removed. Exact counts and settings are in the JSON.

Static TWFE uses the treatment indicator. Dynamic TWFE omits event time −1. BJS/did2s fits untreated outcomes, then averages imputation residuals. Sun–Abraham estimates cohort-by-event-time effects. The three dynamic estimates share post-period aggregation weights. Event-study tails are unbinned. These are common-sample reruns, not Peter’s original estimator-specific sample and tail-binning rules.

The homogeneity test restricts identified cohort deviations at positive event times to zero; leads and event time 0 remain unrestricted. It is a homoskedastic nested-model F-test. Estimate intervals are separately cluster-robust, with the did2s two-stage correction. Large panels use algebraically equivalent sparse regressions; backend and validation results are recorded in JSON.

Adoption timing

Treatment adoption timing

S13-P003: seeded sample of 100 of 2,909 eligible units. Purple untreated; yellow treated; white unobserved. Calendar periods follow the configured time grid. Each specification uses its own full eligible sample.

Specification Status F_pvalue Static TWFE Dynamic TWFE BJS / did2s Sun–Abraham
S13-P001 estimated 0 0.1136 0.0285 0.1036 0.02655
S13-P002 estimated 0 0.06328 0.4287 0.03225 0.2188
S13-P003 estimated 0.09481 0.01017 0.03978 -0.02235 0.002885

Specifications

Open a specification for its estimates, event studies and homogeneity test. Plots display −10 through 10; JSON contains the full paths. Large-panel intervals are calculated over the displayed window.

S13-P001 · IPPO-T3-C1-LOGPAY · homogeneity rejected

Specification JSON · Configuration

Log pay

Source rows: 57,445,624; fitted rows: 27,087,260; units: 998,045; clusters: 998,045; treated cohorts: 0. Source outcome SD: 0.53478748.

method estimate se lower upper
Static TWFE 0.11363 0.00077854 0.1121 0.11515
Dynamic TWFE 0.028502 0.00070108 0.027128 0.029877
BJS / did2s 0.10357 0.00092415 0.10176 0.10538
Sun–Abraham 0.026549 0.00074331 0.025093 0.028006

Post-period weighting: observations. Homogeneity F(42, 26088943) = 355; p = 0.

TWFE, imputation, saturated event studies and cohort deviations
S13-P002 · IPPO-T3-C3-TRANSFER-NONSES · homogeneity rejected

Specification JSON · Configuration

IPPO-T3-C3-TRANSFER-NONSES

Source rows: 6,169,574; fitted rows: 2,307,491; units: 92,706; clusters: 92,706; treated cohorts: 3. Source outcome SD: 0.072832038.

method estimate se lower upper
Static TWFE 0.063284 0.0026874 0.058017 0.068552
Dynamic TWFE 0.42872 0.012158 0.40489 0.45255
BJS / did2s 0.032245 0.002874 0.026612 0.037878
Sun–Abraham 0.21876 0.010076 0.19901 0.23851

Post-period weighting: observations. Homogeneity F(41, 2214516) = 59.39; p = 0.

TWFE, imputation, saturated event studies and cohort deviations
S13-P003 · IPPO-T3-C5-TRANSFER-SES

Specification JSON · Configuration

IPPO-T3-C5-TRANSFER-SES

Source rows: 146,434; fitted rows: 63,551; units: 2,909; clusters: 2,909; treated cohorts: 3. Source outcome SD: 0.065347214.

method estimate se lower upper
Static TWFE 0.010175 0.01743 -0.024001 0.04435
Dynamic TWFE 0.039778 0.044149 -0.046788 0.12634
BJS / did2s -0.02235 0.018001 -0.057647 0.012947
Sun–Abraham 0.0028855 0.032166 -0.060185 0.065956

Post-period weighting: observations. Homogeneity F(41, 60389) = 1.299; p = 0.09481.

TWFE, imputation, saturated event studies and cohort deviations

Reproduce

Code, configurations and environments · Generic Quarto template · Editable Jot template. Source datasets remain local. Run python templates/full_archive/run_archive.py, then python templates/full_archive/build_collection.py.