uu.seUppsala University Publications
Change search
Link to record
Permanent link

Direct link
BETA
Johansson, Per
Publications (10 of 70) Show all publications
Johansson, P., Schultzberg, M. & Rubin, D. (2019). On optimal re-randomization designs.
Open this publication in new window or tab >>On optimal re-randomization designs
2019 (English)Report (Other academic)
Abstract [en]

Blocking is commonly used in randomized experiments to increase efficiency of estimation. A generalization of blocking is to remove allocations with imbalance in covariates between treated and control units, and thenrandomize within the set of allocations with balance in these covariates. This idea of rerandomization was formalized by [5], who suggested using the affinely invariant Mahalanobis distance between treated and control covariate means as the criterion for removing unbalanced allocations. [3] proposed reducing the set of balanced allocations to the minimum. Here we discuss the implication of such an ‘optimal’ rerandomization design for inferences to the units inthe sample and to the population from which the units in the sample were randomly drawn. We argue that, in general, it is a bad idea to seak the optimal design for an inference to the population because that inference typically only reflects uncertainty from the usually hypothetical random sampling, and not the randomization of treatment versus control.

Publisher
p. 20
Series
Working paper / Department of Statistics, Uppsala University ; 2019:3
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-381381 (URN)
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-04-10Bibliographically approved
Schultzberg, M. & Johansson, P. (2019). Optimal designs and asymptotic inference. Uppsala universitet
Open this publication in new window or tab >>Optimal designs and asymptotic inference
2019 (English)Report (Other academic)
Abstract [en]

Recently an experimental design strategy, called rerandomization, has been proposed as acomplement to traditional blocked designs. The idea of rerandomization is to remove, from consideration, those allocations with large imbalances in observed covariates according to abalance criterion, and then randomize within the set of acceptable allocations. This paper clarifies the concept of an ‘optimal’ rerandomization design for inferences using the mean difference sample estimator, SATE. Based on the Mahalanobis distance criterion for balancing the covariates, we show that standard asymptotic inference to the population, from which the units in the sample are randomly drawn, is possible using only the set of best, or ‘optimal’, allocations.

Place, publisher, year, edition, pages
Uppsala universitet, 2019. p. 17
Series
Working paper / Department of Statistics, Uppsala University ; 2019:2
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-381384 (URN)
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-04-10Bibliographically approved
Schultzberg, M. & Johansson, P. (2019). Re-randomization: A complement or substitute for stratification in randomized experiments?. Uppsala University
Open this publication in new window or tab >>Re-randomization: A complement or substitute for stratification in randomized experiments?
2019 (English)Report (Other academic)
Abstract [en]

Rerandomization is a strategy for improving balance on observed covariates in randomized control trails. It has been proposed as a complement to traditional stratied (blocked) designs. However, the relationship and differences between stratification, rerandomization, and the combination of the two have not been previouslyinvestigated. In this paper, we show that stratified designs can be recreated by rerandomization and explain why, in most cases, stratification on binary covariates followed by rerandomization on continuous covariates is more efficient than rerandomization on all covariates at the same time.

Place, publisher, year, edition, pages
Uppsala University, 2019. p. 36
Series
Working paper / Department of Statistics, Uppsala University ; 2019:4
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-382225 (URN)
Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-04-25Bibliographically approved
Johansson, P. & Schultzberg, M. (2019). Re-randomization strategies for balancing covariates using pre-experimental longitudinal data. Department of Statistics, Uppsala University
Open this publication in new window or tab >>Re-randomization strategies for balancing covariates using pre-experimental longitudinal data
2019 (English)Report (Other academic)
Abstract [en]

This paper considers experimental design based on the strategy of rerandomization to increase the effciency in experiments. Two aspects of rerandomization are addressed. First, we propose a two-stage allocation sample scheme for randomization inference to the units of the experiments in balanced experiments that guarantees that the difference-in-mean estimator is an unbiased estimator of SATE for any experiment, conserves the exactness of randomization inference, and halves the time consumption of the rerandomization design. Second, we propose a rank-based covariate balance measure which can take into account the estimated relative weight of each covariate. Several strategies for estimating these weights using pre-experimental data are proposed. Using Monte Carlo simulations, the proposed strategies are compared to complete randomization and Mahalanobis-based rerandomization. An empirical example is given where the power of a mean difference test of the electricity consumption of 54 households is increased by 99%, in comparison to complete randomization, using one of the proposed designs based on high frequency longitudinal electricity consumption data.

Place, publisher, year, edition, pages
Department of Statistics, Uppsala University, 2019. p. 38
Series
Working paper / Department of Statistics, Uppsala University ; 2018:4
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-364864 (URN)
Note

Title of the first published version of the report was: Experimental design using longitudinal data

A revised version with a new title was published 2019-01-25.

Available from: 2018-11-05 Created: 2018-11-05 Last updated: 2019-01-25Bibliographically approved
Johansson, P., Karimi, A. & Nilsson, J. P. (2019). Worker absenteeism: peer influences, monitoring, and job flexibility. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(2), 605-621
Open this publication in new window or tab >>Worker absenteeism: peer influences, monitoring, and job flexibility
2019 (English)In: Journal of the Royal Statistical Society: Series A (Statistics in Society), ISSN 0964-1998, E-ISSN 1467-985X, Vol. 182, no 2, p. 605-621Article in journal (Refereed) Published
Abstract [en]

We study the presence of other-regarding preferences in the workplace by exploitinga randomized experiment that changed the monitoring of workers’ health during sick leave. We show that workers’ response to an increase in co-worker shirking, induced by the experiment,is much stronger than the response to a decrease in co-worker shirking. The asymmetric spillover effects are consistent with evidence of fairness concerns documented in laboratory experiments. Moreover, we find that the spillover effect is driven by workers with highly flexible and autonomous jobs, suggesting that co-worker monitoring may be at least as important as formal monitoring in alleviating shirking.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
National Category
Economics
Identifiers
urn:nbn:se:uu:diva-375107 (URN)10.1111/rssa.12406 (DOI)000456275600012 ()
Funder
The Jan Wallander and Tom Hedelius Foundation
Available from: 2019-01-26 Created: 2019-01-26 Last updated: 2019-02-11Bibliographically approved
Jans, J., Johansson, P. & Nilsson, P. (2018). Economic status, air quality, and child health: Evidence from inversion episodes. Journal of Health Economics, 61, 220-232
Open this publication in new window or tab >>Economic status, air quality, and child health: Evidence from inversion episodes
2018 (English)In: Journal of Health Economics, ISSN 0167-6296, E-ISSN 1879-1646, Vol. 61, p. 220-232Article in journal (Refereed) Published
Abstract [en]

Normally, the temperature decreases with altitude, allowing air pollutants to rise and disperse. During inversion episodes, warmer air at higher altitude traps air pollutants at the ground. By merging vertical temperature profile data from NASA with pollution monitors and health care records, we show that inversions increase the PM10 levels by 25% and children's respiratory health problems by 5.5%. Low-income children are particularly affected, and differences in baseline health seem to be a key mediating factor behind the effect of pollution on the SES health gap. Policies that improve dissemination of information on inversion status may hence improve child health, either through private action or via policies that curb emissions during inversion episodes.

Keywords
Air pollution, Inversions, Environmental policy, Nonparametric estimation, Socioeconomic gradient, Inequality, Labor supply
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:uu:diva-369006 (URN)10.1016/j.jhealeco.2018.08.002 (DOI)000447106100015 ()30193188 (PubMedID)
Available from: 2018-12-14 Created: 2018-12-14 Last updated: 2018-12-14Bibliographically approved
Skans, I. H. & Johansson, P. (2018). Self-screening Effects of Monitoring: Evidence from a Quasi Experiment in the Swedish Temporary Parental Benefit Program. Oxford Bulletin of Economics and Statistics, 80(5), 893-904
Open this publication in new window or tab >>Self-screening Effects of Monitoring: Evidence from a Quasi Experiment in the Swedish Temporary Parental Benefit Program
2018 (English)In: Oxford Bulletin of Economics and Statistics, ISSN 0305-9049, E-ISSN 1468-0084, Vol. 80, no 5, p. 893-904Article in journal (Refereed) Published
Abstract [en]

Monitoring and screening have been shown to be important to reduce moral hazard in social insurances. This paper empirically investigates whether monitoring in the Swedish temporary parental benefit program affects future benefit take-up. Identification is based on the fact that parents' benefit applications are monitored randomly by the insurer. The estimation results show that parents who are monitored are less likely to apply again in the near future.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-364169 (URN)10.1111/obes.12230 (DOI)000443403200002 ()
Available from: 2018-10-30 Created: 2018-10-30 Last updated: 2018-11-16Bibliographically approved
Avdic, D. & Johansson, P. (2017). Absenteeism, Gender and the Morbidity–Mortality Paradox. Journal of applied econometrics (Chichester, England), 32(2), 440-462
Open this publication in new window or tab >>Absenteeism, Gender and the Morbidity–Mortality Paradox
2017 (English)In: Journal of applied econometrics (Chichester, England), ISSN 0883-7252, E-ISSN 1099-1255, Vol. 32, no 2, p. 440-462Article in journal (Refereed) Published
Abstract [en]

Women are, on average, more often absent from work for health reasons than men, but live longer. This conflicting pattern suggests that the gender absenteeism gap arises partly from factors unrelated to objective health. An overlooked explanation is that men and women might have different preferences for absenteeism due to different attitudes to, for example, risk. Using detailed administrative data on absenteeism, hospitalizations, and mortality, we evaluate the existence of gender-specific preferences for absenteeism and analyze whether these differences are socially determined. We find robust evidence of gender differences in absenteeism that cannot be explained by poorer objective health among women.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-287913 (URN)10.1002/jae.2516 (DOI)000397856900011 ()
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, DNR 2004-2005 2009-0826 2013-2482
Available from: 2016-04-27 Created: 2016-04-26 Last updated: 2017-09-08Bibliographically approved
Engström, P., Hägglund, P. & Johansson, P. (2017). Early Interventions and Disability Insurance: Experience from a Field Experiment. Economic Journal, 127(600), 363-392
Open this publication in new window or tab >>Early Interventions and Disability Insurance: Experience from a Field Experiment
2017 (English)In: Economic Journal, ISSN 0013-0133, E-ISSN 1468-0297, Vol. 127, no 600, p. 363-392Article in journal (Refereed) Published
Abstract [en]

We estimate the effects of early assessments of an individual's need for vocational rehabilitation in the Swedish sickness insurance system using a field experiment. One of the interventions increases the flow to disability benefits by 20%. The effect is larger for unemployed individuals, who also are covered by the sickness insurance scheme. This result is in line with a theoretical model with moral hazard and asymmetric information in which individuals with low work incentives communicate worse health in response to the assessment for rehabilitation which then increases the hazard to disability benefits.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:uu:diva-288358 (URN)10.1111/ecoj.12310 (DOI)000395175900004 ()
Available from: 2016-04-27 Created: 2016-04-27 Last updated: 2017-04-18Bibliographically approved
de Luna, X., Fowler, P. & Johansson, P. (2017). Proxy variables and nonparametric identification of causal effects. Economics Letters, 150, 152-154
Open this publication in new window or tab >>Proxy variables and nonparametric identification of causal effects
2017 (English)In: Economics Letters, ISSN 0165-1765, E-ISSN 1873-7374, Vol. 150, p. 152-154Article in journal (Refereed) Published
Abstract [en]

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcomes framework, giving conditions under which it can be shown that causal effects are nonparametrically identified. We characterise two types of proxy variables and give concrete examples where the proxy conditions introduced may hold by design.

Keywords
Average treatment effect, Observational studies, Potential outcomes, Unobserved confounders
National Category
Economics and Business
Identifiers
urn:nbn:se:uu:diva-316421 (URN)10.1016/j.econlet.2016.11.018 (DOI)000392568300038 ()
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, DNR 2009-0826
Available from: 2017-03-01 Created: 2017-03-01 Last updated: 2017-11-29Bibliographically approved
Organisations

Search in DiVA

Show all publications