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Displaying results 1 to 19 of 19.

  1. Weighted-Average Quantile Regression
    Author: Četverikov, Denis N.; Liu, Yukun; Tsyvinski, Aleh
    Published: May 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    In this paper, we introduce the weighted-average quantile regression model. We argue that this model is of interest in many applied settings and develop an estimator for parameters of this model. We show that our estimator is √T-consistent and... more

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    In this paper, we introduce the weighted-average quantile regression model. We argue that this model is of interest in many applied settings and develop an estimator for parameters of this model. We show that our estimator is √T-consistent and asymptotically normal with mean zero under weak conditions, where T is the sample size. We demonstrate the usefulness of our estimator in two empirical settings. First, we study the factor structures of the expected shortfalls of the industry portfolios. Second, we study inequality and social welfare dependence on individual characteristics

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w30014
    Subjects: Regressionsanalyse; Theorie; Econometrics
    Scope: 1 Online-Ressource, illustrations (black and white)
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    Hardcopy version available to institutional subscribers
  2. Partially Linear Models under Data Combination
    Author: D'Haultfœuille, Xavier; Gaillac, Christophe; Maurel, Arnaud
    Published: April 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very... more

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    We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using recent tools from optimal transport theory, we derive a constructive characterization of the sharp identified set. We then build on this result and develop a novel inference method that exploits the specific geometric properties of the identified set. Our method exhibits good performances in finite samples, while remaining very tractable. Finally, we apply our methodology to study intergenerational income mobility over the period 1850-1930 in the United States. Our method allows to relax the exclusion restrictions used in earlier work while delivering confidence regions that are informative

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w29953
    Subjects: Daten; Regressionsanalyse; Monte-Carlo-Simulation; Intergenerationale Übertragung; USA
    Scope: 1 Online-Ressource, illustrations (black and white)
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  3. Dynamic heterogeneous distribution regression panel models, with an application to labor income processes
    Author: Fernández-Val, Iván; Gao, Wayne Yuan; Liao, Yuan; Vella, Francis
    Published: April 2022
    Publisher:  IZA - Institute of Labor Economics, Bonn, Germany

    We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of interest are functionals of these coefficients including linear projections on unit level covariates. We also... more

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    We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of interest are functionals of these coefficients including linear projections on unit level covariates. We also consider predicted actual and stationary distributions of the outcome variable. We investigate how changes in initial conditions or covariate values affect these objects. Coefficients and their functionals are estimated via fixed effect methods, which are debiased to deal with the incidental parameter problem. We propose a cross-sectional bootstrap method for uniformly valid inference on function-valued objects. This avoids coefficient re-estimation and is shown to be consistent for a large class of data generating processes. We employ PSID annual labor income data to illustrate various important empirical issues we can address. We first predict the impact of a reduction in income on future income via hypothetical tax policies. Second, we examine the impact on the distribution of labor income from increasing the education level of a chosen group of workers. Finally, we demonstrate the existence of heterogeneity in income mobility, which leads to substantial variation in individuals' incidences to be trapped in poverty. We also provide simulation evidence confirming that our procedures work well.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/263452
    Series: Discussion paper series / IZA ; no. 15236
    Subjects: Panel; Regressionsanalyse; Bootstrap-Verfahren; Fixed-Effects-Modell; Lohn; Armut; Verteilungswirkung; USA; distribution regression; individual heterogeneity; panel data; uniform inference; labor income dynamics; incidental parameter problem; poverty traps
    Scope: 1 Online-Ressource (circa 103 Seiten), Illustrationen
  4. Partially linear models under data combination
    Author: D'Haultfœuille, Xavier; Gaillac, Christophe; Maurel, Arnaud
    Published: April 2022
    Publisher:  IZA - Institute of Labor Economics, Bonn, Germany

    We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very... more

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    We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using recent tools from optimal transport theory, we derive a constructive characterization of the sharp identified set. We then build on this result and develop a novel inference method that exploits the specific geometric properties of the identified set. Our method exhibits good performances in finite samples, while remaining very tractable. Finally, we apply our methodology to study intergenerational income mobility over the period 1850-1930 in the United States. Our method allows to relax the exclusion restrictions used in earlier work while delivering confidence regions that are informative.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/263446
    Series: Discussion paper series / IZA ; no. 15230
    Subjects: Daten; Regressionsanalyse; Monte-Carlo-Simulation; Intergenerationale Übertragung; USA; partially linear model; data combination; partial identification; intergenerational mobility
    Scope: 1 Online-Ressource (circa 64 Seiten), Illustrationen
  5. Dynamic heterogeneous distribution regression panel models, with an application to labor income processes
    Author: Fernández-Val, Iván; Gao, Wayne Yuan; Liao, Yuan; Vella, Francis
    Published: [2022]
    Publisher:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of interest are functionals of these coefficients including linear projections on unit level covariates. We also... more

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    We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of interest are functionals of these coefficients including linear projections on unit level covariates. We also consider predicted actual and stationary distributions of the outcome variable. We investigate how changes in initial conditions or covariate values affect these objects. Coefficients and their functionals are estimated via fixed effect methods, which are debiased to deal with the incidental parameter problem. We propose a cross-sectional bootstrap method for uniformly valid inference on function-valued objects. This avoids coefficient re-estimation and is shown to be consistent for a large class of data generating processes. We employ PSID annual labor income data to illustrate various important empirical issues we can address. We first predict the impact of a reduction in income on future income via hypothetical tax policies. Second, we examine the impact on the distribution of labor income from increasing the education level of a chosen group of workers. Finally, we demonstrate the existence of heterogeneity in income mobility, which leads to substantial variation in individuals' incidences to be trapped in poverty. We also provide simulation evidence confirming that our procedures work well.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/260391
    Series: Cemmap working paper ; CWP22, 10
    Subjects: Panel; Regressionsanalyse; Bootstrap-Verfahren; Fixed-Effects-Modell; Lohn; Armut; Verteilungswirkung; USA; distribution regression; individual heterogeneity; panel data; uniform inference; labor income dynamics; incidental parameter problem; poverty traps
    Scope: 1 Online-Ressource (circa 101 Seiten), Illustrationen
  6. What Can Time-Series Regressions Tell Us About Policy Counterfactuals?
    Author: Wolf, Christian; McKay, Alisdair
    Published: August 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We show that, in a general family of linearized structural macroeconomic models, knowledge of the empirically estimable causal effects of contemporaneous and news shocks to the prevailing policy rule is sufficient to construct counterfactuals under... more

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    We show that, in a general family of linearized structural macroeconomic models, knowledge of the empirically estimable causal effects of contemporaneous and news shocks to the prevailing policy rule is sufficient to construct counterfactuals under alternative policy rules. If the researcher is willing to postulate a loss function, our results furthermore allow her to recover an optimal policy rule for that loss. Under our assumptions, the derived counterfactuals and optimal policies are robust to the Lucas critique. We then discuss strategies for applying these insights when only a limited amount of empirical causal evidence on policy shock transmission is available

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w30358
    Subjects: Stabilisierungspolitik; Policy-Mix; Kausalanalyse; Regressionsanalyse; Zeitreihenanalyse; Neue klassische Makroökonomik; Business Fluctuations; Cycles; Policy Objectives; Policy Designs and Consistency; Policy Coordination
    Scope: 1 Online-Ressource, illustrations (black and white)
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  7. Wirksame Compliance im Rahmen der Corporate Governance
    empirische Erkenntnisse in börsenkotierten Schweizer Unternehmen
    Author: Hüter, Philippe Patrick
    Published: [2022]

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  8. Contamination Bias in Linear Regressions
    Author: Goldsmith-Pinkham, Paul; Hull, Peter; Kolesár, Michal
    Published: June 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We study the interpretation of regressions with multiple treatments and flexible controls. Such regressions are often used to analyze stratified randomized control trials with multiple intervention arms, to estimate value-added (for, e.g., teachers)... more

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    We study the interpretation of regressions with multiple treatments and flexible controls. Such regressions are often used to analyze stratified randomized control trials with multiple intervention arms, to estimate value-added (for, e.g., teachers) with observational data, and to leverage the quasi-random assignment of decision-makers (e.g. bail judges). We show that these regressions generally fail to estimate convex averages of heterogeneous treatment effects, even when the treatments are conditionally randomly assigned and the controls are sufficiently flexible to avoid omitted variables bias. Instead, estimates of each treatment's effects are generally contaminated by a non-convex average of the effects of other treatments. Thus, recent concerns about heterogeneity-induced bias in regressions leveraging potential outcome restrictions (e.g. parallel trends assumptions) also arise with "design-based" identification strategies. We discuss solutions to the contamination bias and propose a new class of efficient estimators of weighted average effects that avoid bias. In a re-analysis of the Project STAR trial, we find minimal bias because treatment effect heterogeneity is largely idiosyncratic. But sizeable contamination bias arises when effect heterogeneity becomes correlated with treatment propensity scores

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w30108
    Subjects: Regressionsanalyse; Systematischer Fehler; Kausalanalyse; Randomisierte kontrollierte Studie; Theorie; Semiparametric and Nonparametric Methods: General; Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; General
    Scope: 1 Online-Ressource, illustrations (black and white)
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  9. Essays on risk and econometrics
    Author: Yuan, Yue
    Published: [2022]
    Publisher:  Rozenberg Publishers, [Amsterdam]

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    Source: Union catalogues
    Language: English
    Media type: Dissertation
    Format: Print
    ISBN: 9789036106825
    Series: Tinbergen Institute research series ; no. 793
    Subjects: Immobilienpreis; Erdbeben; Risiko; Stadt; Japanisch; Ökonometrie; Regressionsanalyse; WALS estimator
    Scope: 130 Seiten, Illustrationen
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    Dissertation, Universiteit van Amsterdam, 2022
  10. Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects
    A Survey
    Author: de Chaisemartin, Clément; D'Haultfœuille, Xavier
    Published: [2022]
    Publisher:  SSRN, [S.l.]

    Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions. It has recently been shown... more

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    Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions. It has recently been shown that those regressions may produce misleading estimates, if the policy's effect is heterogeneous between groups or over time, as is often the case. This survey reviews a fast-growing literature that documents this issue, and that proposes alternative estimators robust to heterogeneous effects. We use those alternative estimators to revisit Wolfers (2006)

     
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    Media type: Book
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    Subjects: Differenz von Differenzen; Regressionsanalyse; Bibliometrie; Schätztheorie
    Scope: 1 Online-Ressource (32 Seiten)
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    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 8, 2021 erstellt
  11. Exploring external finance links to build back better a green UK SME economy
    small grant longitudinal small business survey (LSBS) report to Enterprise Research Centre (ESRC)
    Author: Owen, Robyn; Lodh, Suman; Plekhanov, Sergei; Anwar, Osman
    Published: [2022]
    Publisher:  ERC, Enterprise Research Centre, Coventry

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    Source: Union catalogues
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    Media type: Book
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    Series: ERC research paper ; 99 (June 2022)
    Subjects: Unternehmensfinanzierung; Nachhaltige Finanzierung; KMU; Regressionsanalyse; Großbritannien
    Scope: 1 Online-Ressource (circa 45 Seiten)
  12. Sparse network asymptotics for logistic regression under possible misspecification
    Author: Graham, Bryan S.
    Published: [2022]
    Publisher:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    Consider a bipartite network where N consumers choose to buy or not to buy M different products. This paper considers the properties of the logit fit of the N ×M array of "i-buys-j" purchase decisions, Y = [Yij ]1≤i≤N,1≤j≤M , onto a vector of known... more

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    Consider a bipartite network where N consumers choose to buy or not to buy M different products. This paper considers the properties of the logit fit of the N ×M array of "i-buys-j" purchase decisions, Y = [Yij ]1≤i≤N,1≤j≤M , onto a vector of known functions of consumer and product attributes under asymptotic sequences where (i) both N and M grow large, (ii) the average number of products purchased per consumer is finite in the limit, (iii) there exists dependence across elements in the same row or same column of Y (i.e., dyadic dependence) and (iv) the true conditional probability of making a purchase may, or may not, take the assumed logit form. Condition (ii) implies that the limiting network of purchases is sparse: only a vanishing fraction of all possible purchases are actually made. Under sparse network asymptotics, I show that the parameter indexing the logit approximation solves a particular Kullback-Leibler Information Criterion (KLIC) minimization problem (defined with respect to a certain Poisson population). This finding provides a simple characterization of the logit pseudo-true parameter under general misspecification. With respect to sampling theory, sparseness implies that the first and last terms in an extended Hoeffding-type variance decomposition of the score of the logit pseudo composite log-likelihood are of equal order. In contrast, under dense network asymptotics, the last term is asymptotically negligible. Asymptotic normality of the logistic regression coefficients is shown using a martingale central limit theorem (CLT) for triangular arrays. Unlike in the dense case, the normality result derived here also holds under degeneracy of the network graphon. Relatedly, when there "happens to be" no dyadic dependence in the dataset in hand, it specializes to recently derived results on the behavior of logistic regression with rare events and iid data. Simulation results suggest that sparse network asymptotics better approximate the finite network distribution of the logit estimator.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/272827
    Edition: This Draft: September 2022
    Series: Cemmap working paper ; CWP22, 15
    Subjects: Netzwerk; Regressionsanalyse; Schätztheorie; Networks; Exchangeable Random Arrays; Dyadic Clustering; Sparse Networks; Logistic Regression; Rare Events; Bipartite Network; Alternative Asymptotics; Sparse Network Asymptotics
    Scope: 1 Online-Ressource (circa 36 Seiten)
  13. Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects
    A Survey
    Author: Chaisemartin, Clément de; D'Haultfœuille, Xavier
    Published: 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions. It has recently been show... more

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    Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions. It has recently been show that those regressions may produce misleading estimates, if the policy's effect is heterogeneous between groups or over time, as is often the case. This survey reviews a fast-growing literature that documents this issue, and that proposes alternative estimators robust to heterogeneous effects

     
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    Language: English
    Media type: Book
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    Series: NBER working paper series ; no. w29691
    Subjects: Differenz von Differenzen; Regressionsanalyse; Bibliometrie; Schätztheorie
    Scope: 1 Online-Ressource, illustrations (black and white)
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    Hardcopy version available to institutional subscribers
  14. Using Digitized Newspapers to Refine Historical Measures
    The Case of the Boll Weevil
    Author: Ferrara, Andreas; Ha, Joung Yeob; Walsh, Randall P.
    Published: 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    This paper shows how to remove attenuation bias in regression analyses due to measurement error in historical data for a given variable of interest by using a secondary measure which can be easily generated from digitized newspapers. We provide three... more

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    This paper shows how to remove attenuation bias in regression analyses due to measurement error in historical data for a given variable of interest by using a secondary measure which can be easily generated from digitized newspapers. We provide three methods for using this secondary variable to deal with non-classical measurement error in a binary treatment: set identification, bias reduction via sample restriction, and a parametric bias correction. We demonstrate the usefulness of our methods by replicating two recent studies on the effect of the boll weevil. Relative to the initial analysis, our results yield markedly larger coefficient estimates

     
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    Source: Union catalogues
    Language: English
    Media type: Book
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    Series: NBER working paper series ; no. w29808
    Subjects: Baumwollanbau; Schädlinge; Zeitung; Regressionsanalyse; Statistischer Fehler; Ökonomen; USA
    Scope: 1 Online-Ressource, illustrations (black and white)
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  15. Regression Discontinuity Evidence on the Effectiveness of the Minimum Legal E-Cigarette Purchasing Age
    Author: DeSimone, Jeff; Grossman, Daniel; Ziebarth, Nicolas R.
    Published: October 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    Increases in youth vaping rates and concerns of a new generation of nicotine addicts recently prompted an increase in the federal minimum legal purchase age (MLPA) for tobacco products, including e-cigarettes, to 21 years. This study presents the... more

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    Universitätsbibliothek Freiburg
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
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    Increases in youth vaping rates and concerns of a new generation of nicotine addicts recently prompted an increase in the federal minimum legal purchase age (MLPA) for tobacco products, including e-cigarettes, to 21 years. This study presents the first regression discontinuity evidence on the effectiveness of e-cigarette MLPA laws. Using data on 12th graders from Monitoring the Future, we obtain robust evidence that federal and state age-18 MLPAs decreased underage e-cigarette use by 15-20% and frequent use by 20-40%. These findings suggest that the age-21 federal MLPA could meaningfully reduce e-cigarette use among 18-20-year-olds

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: NBER working paper series ; no. w30614
    Subjects: Zigarette; Altersgruppe; Drogenpolitik; Regressionsanalyse; USA; Government Expenditures and Health; State and Local Government: Health; Education; Welfare; Public Pensions; Health Behavior; Government Policy; Regulation; Public Health
    Scope: 1 Online-Ressource, illustrations (black and white)
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    Hardcopy version available to institutional subscribers
  16. A New Test for Market Efficiency and Uncovered Interest Parity
    Author: Baillie, Richard; Diebold, Francis X.; Kapetanios, George; Kim, Kun Ho
    Published: November 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parameter estimates, and is not dependent on assumptions of strict... more

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    We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parameter estimates, and is not dependent on assumptions of strict exogeneity. This new approach is asymptotically more efficient than the common approach of using OLS with HAC robust standard errors in the static forward premium regression. The coefficient estimates when spot return changes are regressed on the forward premium are all positive and remarkably stable across currencies. These estimates are considerably larger than those of previous studies, which frequently find negative coefficients. The method also has the advantage of showing dynamic effects of risk premia, or other events that may lead to rejection of UIP or the efficient markets hypothesis

     
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    Language: English
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    Series: NBER working paper series ; no. w30638
    Subjects: Zinsparität; Schätzung; Regressionsanalyse; Effizienzmarkthypothese; Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; General
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  17. Why Transform Y? A Critical Assessment of Dependent-Variable Transformations in Regression Models for Skewed and Sometimes-Zero Outcomes
    Author: Mullahy, John; Norton, Edward C.
    Published: December 2022
    Publisher:  National Bureau of Economic Research, Cambridge, Mass

    Dependent variables that are non-negative, follow right-skewed distributions, and have large probability mass at zero arise often in empirical economics. Two classes of models that transform the dependent variable y -- the natural logarithm of y plus... more

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    Dependent variables that are non-negative, follow right-skewed distributions, and have large probability mass at zero arise often in empirical economics. Two classes of models that transform the dependent variable y -- the natural logarithm of y plus a constant and the inverse hyperbolic sine -- have been widely used in empirical work. We show that these two classes of models share several features that raise concerns about their application. The concerns are particularly prominent when dependent variables are frequently observed at zero, which in many instances is the main motivation for using them in the first place. The crux of the concern is that these models have an extra parameter that is generally not determined by theory but whose values have enormous consequences for point estimates. As these parameters go to extreme values estimated marginal effects on outcomes' natural scales approach those of either an untransformed linear regression or a normed linear probability model. Across a wide variety of simulated data, two-part models yield correct marginal effects, as do OLS on the untransformed y and Poisson regression. If researchers care about estimating marginal effects, we recommend using these simpler models that do not rely on transformations

     
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    Series: NBER working paper series ; no. w30735
    Subjects: Regressionsanalyse; Theorie; Methodological Issues: General; General
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  18. Reflexion und Reflexivität im Kontext Grundschule. Perspektiven für Forschung, Lehrer:innenbildung und Praxis
    Contributor: Gläser, Eva (Herausgeber); Poschmann, Julia (Herausgeber); Büker, Petra (Herausgeber); Miller, Susanne (Herausgeber)
    Published: 2022
    Publisher:  DIPF Frankfurt am Main, NP-Ablieferer, Frankfurt

    Abstract: Reflexion und Reflexivität werden im Kontext verschiedener Reformanstrengungen in Schule, Unterricht und Lehrer:innenbildung verstärkt diskutiert und sind zudem mit hohen Professionalisierungserwartungen verbunden. Aktuelle... more

     

    Abstract: Reflexion und Reflexivität werden im Kontext verschiedener Reformanstrengungen in Schule, Unterricht und Lehrer:innenbildung verstärkt diskutiert und sind zudem mit hohen Professionalisierungserwartungen verbunden. Aktuelle Forschungsbefunde verweisen allerdings auf einen noch immer hohen Aushandlungs-, Systematisierungs- und Entwicklungsbedarf, auf Widersprüche und offene Fragen. Diese standen im Mittelpunkt der gemeinsamen Tagung der DGfE-Sektion Schulpädagogik im September 2021, innerhalb derer die 29. Jahrestagung der Kommission Grundschulforschung und Pädagogik der Primarstufe stattfand. Die Beiträge des vorliegenden Bandes perspektivieren Reflexion und Reflexivität im Kontext von Grundschule und Grundschulforschung: theoretisierend, konzeptionell, empirisch und multiparadigmatisch. (DIPF/Orig.)

     
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    Contributor: Gläser, Eva (Herausgeber); Poschmann, Julia (Herausgeber); Büker, Petra (Herausgeber); Miller, Susanne (Herausgeber)
    Language: German
    Media type: Book
    Format: Online
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    Deutsche Gesellschaft für Erziehungswissenschaft. Sektion Schulpädagogik. Jahrestagung (2021 : Online) (Verfasser)
    Series: Jahrbuch Grundschulforschung ; 26
    Subjects: Lehrerbildung; Grundschule; Professionalisierung; Unterricht; Schulpädagogik; Reflexion <Psychologie>; Lehrer
    Other subjects: Array
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    Bad Heilbrunn : Verlag Julius Klinkhardt 2022, 316 S. - (Jahrbuch Grundschulforschung; 26). ISBN 978-3-7815-5965-3; 978-3-7815-2525-2
  19. Reading Russian poetry: An expert–novice study
    Author: Fokin, Danil; Blohm, Stefan; Riekhakainen, Elena
    Published: 2022
    Publisher:  Universitätsbibliothek Bern, Bern ; Leibniz-Institut für Deutsche Sprache (IDS), Mannheim

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    Parent title: In: Bern : Universitätsbibliothek Bern, (2022)
    In: Journal of Eye Movement Research 13.2022, 3
    Subjects: Lyrik / Lyrik; Russisch; Lesen; Fachwissen; Verstehen; Leseverhalten; Augenfolgebewegung; Regressionsanalyse
    Other subjects: eye tracking; reading; poetry; art reception; individual differences; expert–novice; expertise
    Scope: Online-Ressource