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Displaying results 1 to 8 of 8.

  1. Fast and reliable jackknife and bootstrap methods for cluster-robust inference
    Author: MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, Matthew
    Published: 4-2022
    Publisher:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    We provide new and computationally attractive methods, based on jackknifing by cluster, to obtain cluster-robust variance matrix estimators (CRVEs) for linear regres- sion models estimated by least squares. These estimators have previously been com-... more

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    DS 216
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    We provide new and computationally attractive methods, based on jackknifing by cluster, to obtain cluster-robust variance matrix estimators (CRVEs) for linear regres- sion models estimated by least squares. These estimators have previously been com- putationally infeasible except for small samples. We also propose several new variants of the wild cluster bootstrap, which involve the new CRVEs, jackknife-based bootstrap data-generating processes, or both. Extensive simulation experiments suggest that the new methods can provide much more reliable inferences than existing ones in cases where the latter are not trustworthy, such as when the number of clusters is small and/or cluster sizes vary substantially.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/281089
    Series: Queen's Economics Department working paper ; no. 1485
    Subjects: bootstrap; clustered data; grouped data; cluster-robust variance estima-tor; CRVE; cluster sizes; jackknife; wild cluster bootstrap
    Scope: 1 Online-Ressource (circa 35 Seiten), Illustrationen
  2. Leverage, influence, and the jackknife in clustered regression models
    reliable inference using summclust
    Author: MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, Matthew
    Published: 3-2022
    Publisher:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    Cluster-robust inference is widely used in modern empirical work in economics and many other disciplines. The key unit of observation is the cluster. We propose measures of "high-leverage" clusters and "influential" clusters for linear regression... more

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    DS 216
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    Cluster-robust inference is widely used in modern empirical work in economics and many other disciplines. The key unit of observation is the cluster. We propose measures of "high-leverage" clusters and "influential" clusters for linear regression models. The measures of leverage and partial leverage, and functions of them, can be used as diagnostic tools to identify datasets and regression designs in which cluster-robust inference is likely to be challenging. The measures of influence can provide valuable information about how the results depend on the data in the various clusters. We also show how to calculate two jackknife variance matrix estimators, CV3 and CV3J, as a byproduct of our other computations. All these quantities, including the jackknife variance estimators, are computed in a new Stata package called summclust that summarizes the cluster structure of a dataset.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/260488
    Series: Queen's Economics Department working paper ; no. 1483
    Subjects: clustered data; cluster-robust variance estimator; grouped data; highleverageclusters; influential clusters; jackknife; partial leverage; robust inference
    Scope: 1 Online-Ressource (circa 39 Seiten)
  3. Estimating historical inequality from social tables
    towards methodological consistency
    Author: Fintel, Dieter von; Links, Calumet; Green, Erik
    Published: March 2023
    Publisher:  Department of Economics, University of Stellenbosch, Stellenbosch

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Stellenbosch economic working papers ; WP 2023, 01
    Subjects: Social tables; Gini; inequality; pre-industrial; grouped data
    Scope: 1 Online-Ressource (circa 37 Seiten), Illustrationen
  4. Estimating historical inequality from social tables
    towards methodological consistency
    Author: Fintel, Dieter von; Links, Calumet; Green, Erik
    Published: 2023
    Publisher:  Lund University, Department of Economic History, Lund

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Lund papers in economic history ; no. 247 (2023)
    Subjects: Social tables; Gini; inequality; pre-industrial; grouped data
    Scope: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  5. Cluster-robust jackknife and bootstrap inference for binary response models
    Author: MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, Matthew
    Published: 5-2024
    Publisher:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but... more

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    We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves jackknifing at the cluster level. We also propose a linearized version of the cluster-jackknife variance matrix estimator as well as linearized versions of the wild cluster bootstrap. The linearizations are based on empirical scores and are computationally efficient. Throughout we use the logit model as a leading example. We also discuss a new Stata software package called logitjack which implements these procedures. Simulation results strongly favor the new methods, and two empirical examples suggest that it can be important to use them in practice.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/301940
    Series: Queen's Economics Department working paper ; no. 1515
    Subjects: logit model; logistic regression; clustered data; grouped data; cluster-robust variance estimator; CRVE; cluster jackknife; robust inference; wild cluster boot-strap; linearization
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  6. Jackknife inference with two-way clustering
    Author: MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, Matthew
    Published: 5-2024
    Publisher:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    For linear regression models with cross-section or panel data, it is natural to assume that the disturbances are clustered in two dimensions. However, the finite-sample properties of two-way cluster-robust tests and confidence intervals are often... more

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    DS 216
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    For linear regression models with cross-section or panel data, it is natural to assume that the disturbances are clustered in two dimensions. However, the finite-sample properties of two-way cluster-robust tests and confidence intervals are often poor. We discuss several ways to improve inference with two-way clustering. Two of these are existing methods for avoiding, or at least ameliorating, the problem of undefined standard errors when a cluster-robust variance matrix estimator (CRVE) is not positive definite. One is a new method that always avoids the problem. More importantly, we propose a family of new two-way CRVEs based on the cluster jackknife. Simulations for models with two-way fixed effects suggest that, in many cases, the cluster-jackknife CRVE combined with our new method yields surprisingly accurate inferences. We provide a simple software package, twowayjack for Stata, that implements our recommended variance estimator.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/301941
    Series: Queen's Economics Department working paper ; no. 1516
    Subjects: cluster jackknife; cluster sizes; clustered data; cluster-robust variance estimator; CRVE; grouped data; two-way fixed effects
    Scope: 1 Online-Ressource (circa 31 Seiten), Illustrationen
  7. Cluster-robust inference
    a guide to empirical practice
    Author: MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, Matthew
    Published: 5-2021
    Publisher:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    Methods for cluster-robust inference are routinely used in economics and many other disciplines. However, it is only recently that theoretical foundations for the use of these methods in many empirically relevant situations have been developed. In... more

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    Methods for cluster-robust inference are routinely used in economics and many other disciplines. However, it is only recently that theoretical foundations for the use of these methods in many empirically relevant situations have been developed. In this paper, we use these theoretical results to provide a guide to empirical practice. We do not attempt to present a comprehensive survey of the (very large) literature. Instead, we bridge theory and practice by providing a thorough guide on what to do and why, based on recently available econometric theory and simulation evidence. The paper includes an empirical analysis of the effects of the minimum wage on teenagers using individual data, in which we practice what we preach.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/247198
    Series: Queen's Economics Department working paper ; no. 1456
    Subjects: clustered data; grouped data; cluster-robust variance estimator; CRVE; robust inference; wild cluster bootstrap
    Scope: 1 Online-Ressource (circa 51 Seiten)
  8. On historical household budgets
    Author: A'Hearn, Brian; Amendola, Nicola; Vecchi, Giovanni
    Published: June 2016
    Publisher:  University of Oxford, Oxford

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Discussion papers in economic and social history ; number 144
    Subjects: Household budgets; household budget surveys; living standards; inequality; poverty; survey; globalization; purchasing power parities; grouped data; post stratification
    Scope: 1 Online-Ressource (circa 44 Seiten)