Bias Corrections for Probit and Logit Models with Two-way Fixed Effects

Cruz-Gonzalez, Mario; Fernández‐Val, Iván; Weidner, Martin

doi:10.1177/1536867x1701700301

Cited by 58 publications

(34 citation statements)

References 13 publications

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“…One approach would be to use a regression model based on a zero-inflated probability distribution. Still, this type of model is not well suited to include fixed effects due to the “incidental parameter problem” [ 31 ]. Without fixed effects we would not be able to adjust for unobserved clinic characteristics which is considered important to control for GP selection into POCT usage.…”

Section: Discussionmentioning

confidence: 99%

Effects of Point-Of-Care Testing in General Practice for Type 2 Diabetes Patients on Ambulatory Visits and Hospitalizations

Kristensen

Olsen

Skovsgaard

2020

IJERPH

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Point-of-care testing (POCT) of HbA1c means instant test results and more coherent counseling that is expected to improve diabetes management and affect ambulatory visits and hospitalizations. From late 2008, POCT has been implemented and adopted by a segment of the general practices in the capital region of Denmark. The aim of this study is to assess whether the introduction of POCT of HbA1c in general practice (GP) has affected patient outcomes for T2 diabetes patients in terms of hospital activity. We apply difference-in-differences models at the GP clinic level to assess the casual effects of POCT on the following hospital outcomes: (1) admissions for diabetes, (2) admissions for ambulatory care sensitive diabetes conditions (ACSCs), (3) ambulatory visits for diabetes. The use of POCT is remunerated by a fee, and registration of this fee is used to measure the GP’s use of POCT. The control group includes clinics from the same region that did not use POCT. The sensitivity of our results is assessed by an event study approach and a range of robustness tests. The panel data set includes 553 GP clinics and approximately 30,000 diabetes patients from the capital region of Denmark, observed in the years 2004–2012. We find that voluntary adoption of POCT of HbA1c in GP has no effect on hospital admissions and diabetes-related hospital ambulatory visits. Event study analysis and different treatment definitions confirm the robustness of these results. If implementation of POCT of HbA1c improves other parts of diabetes management as indicated in the literature, it seems worthwhile to implement POCT of HbA1c in the capital region of Denmark. However, doubts around the quality of POCT of HbA1c testing and a desire to capture data at central labs may prevent implementation of more value based HbA1c testing.

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Section: Discussionmentioning

confidence: 99%

Effects of Point-Of-Care Testing in General Practice for Type 2 Diabetes Patients on Ambulatory Visits and Hospitalizations

Kristensen

Olsen

Skovsgaard

2020

IJERPH

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“…If both N and T are relatively large, as is the case in our data with 72 countries and 36 years, the bias arising from the incidental parameters problem is unlikely to be large. However, to gain a better sense of the potential size of the bias, we implement a panel jackknife bias correction that has recently been proposed in the literature (Hahn and Newey, 2004;Fernández-Val and Weidner, 2016;Cruz-Gonzalez et al, 2017).…”

Section: The Effect Of Communication Technology On Imports Along the mentioning

confidence: 99%

Spinning the Web: The Impact of ICT on Trade in Intermediates and Technology Diffusion

Juhász¹,

Steinwender²

2018

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Wan provided excellent research assistance. The title of the paper is borrowed from www.spinningtheweb.org.uk. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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“…is a complementary tool to the commands and recently developed by Cruz-Gonzalez, Fernández-Val, and Weidner (2017). These commands implement analytical and jackknife bias corrections—including the SPJ—for common parameter and average marginal effect estimates in probit and logit models with individual effects, time effects, or both.…”

Section: Introductionmentioning

confidence: 99%

xtspj: A command for split-panel jackknife estimation

Sun

Dhaene

2019

The Stata Journal

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In this article, we present a new command, xtspj, that corrects for incidental parameter bias in panel-data models with fixed effects. The correction removes the first-order bias term of the maximum likelihood estimate using the split-panel jackknife method. Two variants are implemented: the jackknifed maximum-likelihood estimate and the jackknifed log-likelihood function (with corresponding maximizer). The model may be nonlinear or dynamic, and the covariates may be predetermined instead of strictly exogenous. xtspj implements the split-panel jackknife for fixed-effects versions of linear, probit, logit, Poisson, exponential, gamma, Weibull, and negbin2 regressions. It also accommodates other models if the user specifies the log-likelihood function (and, possibly but not necessarily, the score function and the Hessian). xtspj is fast and memory efficient, and it allows large datasets. The data may be unbalanced. xtspj can also be used to compute uncorrected maximum-likelihood estimates of fixed-effects models for which no other xt (see [XT] xt) command exists.

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Bias Corrections for Probit and Logit Models with Two-way Fixed Effects

Cited by 58 publications

References 13 publications

Effects of Point-Of-Care Testing in General Practice for Type 2 Diabetes Patients on Ambulatory Visits and Hospitalizations

Effects of Point-Of-Care Testing in General Practice for Type 2 Diabetes Patients on Ambulatory Visits and Hospitalizations

Spinning the Web: The Impact of ICT on Trade in Intermediates and Technology Diffusion

xtspj: A command for split-panel jackknife estimation

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