Multidimensional skills and the returns to schooling: Evidence from an interactive fixed‐effects approach and a linked survey‐administrative data set

Strong empirical links exist between the number of years spent schooling and earnings. However, the relationship may be masked due to the effect of unobserved factors that influence both wages and schooling. Two of the main econometric models, namely fixed-effects and selection-effects, used to analyse returns to schooling were compared using monozygotic and dizygotic twins’ datasets in Ghana. The efficiency of the models was assessed based on the standard errors associated with the return to schooling estimates. Goodness of fit measures was used as a basis for comparison of the performance of the two models. The results revealed that based on their standard errors, the regression estimates from the selection effects model (MZ = 0.1014±0.0197; DZ = 0.0947±0.0095) were more efficient than the regression estimates from the fixed-effects model (MZ = 0.1115±0.0353; DZ = 0.082±0.0127). However, the AICc values of the fixed effects model (MZAICc = 57.8 and DZAICc = 105.4) were smaller than the AICc values of the selection effects model (MZAICc = 151.6 and DZAICc = 221.6). Findings from the study indicate that, although both models produced consistent estimates of the economic returns to schooling, the fixed effects model provided a better fit to the twins’ data set.

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Mediating distributive politics: political alignment and electoral business cycle effects on municipality financing in Greece

The Annals of Regional Science ◽

10.1007/s00168-020-01038-7 ◽

2021 ◽

Author(s):

Anastasios Kitsos ◽

Antonios Proestakis

Keyword(s):

Business Cycle ◽

Fixed Effects ◽

Central Government ◽

Intergovernmental Transfers ◽

Negative Effects ◽

National Elections ◽

Data Set ◽

Resource Misallocation ◽

Run Up ◽

Political Alignment

AbstractWe examine the role of political alignment and the electoral business cycle on municipality revenues in Greece for the period 2003–2010. The misallocation of resources for political gain represents a waste of resources with significant negative effects on local growth and effective decentralization. The focus of our analysis is municipality mayors since they mediate the relationship between central government and voters and hence can influence the effectiveness of any potential pork-barrelling activity. A novel panel data set combining the results of two local and three national elections with annual municipality budgets is used to run a fixed-effects econometric model. This allows us to identify whether the political alignment between mayors and central government affects municipality financing. We examine this at different stages of local and national electoral cycles, investigating both direct intergovernmental transfers (grants) and the remaining sources of local revenues (own revenues, loans). We find that total revenues are significantly higher for aligned municipalities in the run-up to elections due to higher intergovernmental transfers. We also find evidence that the 2008 crisis has reduced such pork-barrelling activity. This significant resource misallocation increases vertical networking dependency and calls for policy changes promoting greater decentralization and encouraging innovation in local revenue raising.

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TESTING HOMOGENEITY IN PANEL DATA MODELS WITH INTERACTIVE FIXED EFFECTS

Econometric Theory ◽

10.1017/s0266466613000017 ◽

2013 ◽

Vol 29 (6) ◽

pp. 1079-1135 ◽

Cited By ~ 47

Author(s):

Liangjun Su ◽

Qihui Chen

Keyword(s):

Panel Data ◽

Fixed Effects ◽

Data Models ◽

Development Economic ◽

Strong Mixing ◽

Panel Data Models ◽

Finite Sample ◽

Test Statistic ◽

Lm Test ◽

Interactive Fixed Effects

This paper proposes a residual-based Lagrange Multiplier (LM) test for slope homogeneity in large-dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions that allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite-sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the Organization for Economic Cooperation and Development economic growth model.

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Excused Versus Unexcused: How Student Absences in Elementary School Affect Academic Achievement

Educational Evaluation and Policy Analysis ◽

10.3102/0162373709342467 ◽

2009 ◽

Vol 31 (4) ◽

pp. 392-415 ◽

Cited By ~ 103

Author(s):

Michael A. Gottfried

Keyword(s):

Elementary School ◽

Test Performance ◽

Fixed Effects ◽

Standardized Test ◽

Educational Achievement ◽

Quantitative Model ◽

Academic Risk ◽

Data Set ◽

Unexcused Absences ◽

Reading And Math

The literature on school absences has focused predominantly on the reasons for student truancy, or it has assessed only aggregate student absences in their effect on achievement. However, this study brings forth a new issue: the relationship between types of absences—excused versus unexcused—and school performance. With a quantitative model of educational achievement on a longitudinal multilevel data set of all second-through fourth-grade students in the Philadelphia School District from 1994 to 2000, this study disaggregated absence information to provide new insight on the attendance–achievement relationship. Specifically, a model using fixed effects with classroom-level clustering was employed to determine how the distinction among varying proportions of excused versus unexcused absences related to students’ standardized test performance in reading and math. This article demonstrates that distinguishing between students with high rates of excused or unexcused absences is significant. Having a higher proportion of excused absences to total absences exhibits a positive relationship between reading and math test scores. Conversely, students with a higher proportion of unexcused absences places them at academic risk, particularly in math achievement and as early as in elementary school. Implications for policy are discussed.

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Regime Switching Panel Data Models with Interactive Fixed Effects

SSRN Electronic Journal ◽

10.2139/ssrn.3282793 ◽

2018 ◽

Cited By ~ 1

Author(s):

Tingting Cheng ◽

Jiti Gao ◽

Yayi Yan

Keyword(s):

Panel Data ◽

Regime Switching ◽

Fixed Effects ◽

Data Models ◽

Panel Data Models ◽

Interactive Fixed Effects

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Three Essays on Adverse Events and Student Outcomes

10.26686/wgtn.17151098 ◽

2021 ◽

Author(s):

◽

Olivia Wills

Keyword(s):

High School ◽

High School Students ◽

Adverse Events ◽

Administrative Data ◽

Degree Completion ◽

Student Outcomes ◽

Fixed Effects ◽

Hospital Admissions ◽

The Impact ◽

Low Ability

<p>This dissertation contains three essays on the impact of unexpected adverse events on student outcomes. All three attempt to identify causal inference using plausibly exogenous shocks and econometric tools, applied to rich administrative data. In Chapter 2, I present evidence of the causal effects of the 2011 Christchurch earthquake on tertiary enrolment and completion. Using the shock of the 2011 earthquake on high school students in the Canterbury region, I estimate the effect of the earthquake on a range of outcomes including tertiary enrolment, degree completion and wages. I find the earthquake causes a substantial increase in tertiary enrolment, particularly for low ability high school leavers from damaged schools. However, I find no evidence that low ability students induced by the earthquake complete a degree on time. In Chapter 3, I identify the impact of repeat disaster exposure on university performance, by comparing outcomes for students who experience their first earthquake while in university, to outcomes for students with prior earthquake exposure. Using a triple-differences estimation strategy with individual-by-year fixed effects, I identify a precise null effect, suggesting that previous experience of earthquakes is not predictive of response to an additional shock two years later. The final chapter investigates the impact of injuries sustained in university on academic performance and wages, using administrative data including no-fault insurance claims, emergency department attendance and hospital admissions, linked with tertiary enrolment. I find injuries, including minor injuries, have a negative effect on re-enrolment, degree completion and grades in university.</p>

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Animal Model Versus Polynomial Legendre Test-Day In Dairy Cattle

Archiva Zootechnica ◽

10.2478/azibna-2020-0001 ◽

2020 ◽

Vol 23 (1) ◽

pp. 5-12

Author(s):

Mircea Cătălin Rotar ◽

Horia Grosu ◽

Mihail Alexandru Gras ◽

Rodica Ştefania Pelmuş ◽

Cristina Lazăr ◽

...

Keyword(s):

Animal Model ◽

Dairy Cattle ◽

Fixed Effects ◽

Rank Correlation ◽

Pedigree Information ◽

Lactation Period ◽

Data Set ◽

Breeding Values ◽

Normal Limits ◽

Model Versus

AbstractThe aim of the study was to compare the classical animal model (based on total milk for 305 days) with the Test-Day model (using monthly records of milk yield from Official Records of Performances). The data set derived from a total 175 animals (cows with records, parents of these animals and the descendants) from two Romanian breeds (Romanian Black Spotted and Montbeliarde), the phenotypic and the pedigree information arisen from National Research Development Institute for Animal Biology and Nutrition (IBNA-Balotesti). The selection criteria to be included in the analysis for each cow was to have at least 3 test-days and the days in milk between 200 and 330 for the Test-Day model and the total amount of the 305- day lactation yield for classical Animal Model respectively. Both models use B.L.U.P methodology and for that reason all the estimates were adjusted for fixed effects and all the breeding values and the solution for fixed effects were estimated simultaneous. For the animal model the fixed effects used was the breed and the year of performing and for the Test-Day model was an extra one, the test day effect. The correlation calculated between test days was very high (over 90%) for consecutive tests, and was getting lower when the days between tests was higher (under 40%). Also, in terms of heritability the values were in normal limits throughout lactation, except at the beginning and end of lactation period where these values were a little bit higher. The comparison of the ranking of breeding values with Spearman rank correlation shows that in 80% of the cases the ranking was similar for both models. As the ranking correlations shows, it is certain that the two models are very similar when they are used for genetic evaluation. But, in conclusion, we can say that for a better lactation curve estimation it is recommending to use test-day model for dairy cattle.

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Russian Regional Politicians’ Income and Property Declarations: a Pilot Study and Quality Assessment of Administrative Data

Sociological Journal ◽

10.19181/socjour.2021.27.3.8422 ◽

2021 ◽

Vol 27 (3) ◽

pp. 8-34

Author(s):

Tatyana Cherkashina

Keyword(s):

Pilot Study ◽

Data Quality ◽

Quality Assessment ◽

Administrative Data ◽

Measurement Errors ◽

Private Property ◽

Research Data ◽

Quality Of Data ◽

Data Set ◽

Research Problems

The article presents the experience of converting non-targeted administrative data into research data, using as an example data on the income and property of deputies from local legislative bodies of the Russian Federation for 2019, collected as part of anticorruption operations. This particular empirical fragment was selected for the pilot study of administrative data, which includes assessing the possibility of integrating scattered fragments of information into a single database, assessing quality of data and their relevance for solving research problems, particularly analysis of high-income strata and the apparent trends towards individualization of private property. The system of indicators for assessing data quality includes their timeliness, availability, interpretability, reliability, comparability, coherence, errors of representation and measurement, and relevance. In the case of the data set in question, measurement errors are more common than representation errors. Overall the article emphasizes the notion that introducing new non-target data into circulation requires their preliminary testing, while data quality assessment becomes distributed both in time and between different subjects. The transition from created data to «obtained» data shifts the functions of evaluating its quality from the researcher-creator to the researcheruser. And though in this case data quality is in part ensured by the legal support for their production, the transformation of administrative data into research data involves assessing a variety of quality measurements — from availability to uniformity and accuracy.

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Population Pharmacokinetics of Fluconazole in Young Infants

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.00569-08 ◽

2008 ◽

Vol 52 (11) ◽

pp. 4043-4049 ◽

Cited By ~ 120

Author(s):

K. C. Wade ◽

D. Wu ◽

D. A. Kaufman ◽

R. M. Ward ◽

D. K. Benjamin ◽

...

Keyword(s):

Fixed Effects ◽

Compartment Model ◽

Volume Of Distribution ◽

Relative Standard Error ◽

Data Set ◽

Mixed Effect ◽

Young Infants ◽

Relative Standard ◽

Population Pk ◽

The Impact

ABSTRACT Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 · (weight/1)0.75 · (BGA/26)1.739 · (PNA/2)0.237 · serum creatinine (SCRT)−4.896 (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 · (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.

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