Statistical matching using propensity scores: Theory and application to the analysis of the distribution of income and wealth

Kum, Hyunsub; Masterson, Thomas

doi:10.3233/jem-2010-0332

Cited by 28 publications

(23 citation statements)

References 20 publications

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“…This strategy often relies on a rank imputation, using broad strata variables to avoid undesirable matches. 3 This paper uses the methodology proposed in Kum and Masterson (2010), which has been used in the estimation of the Levy Institute Measure of Economic Well-Being (LIMEW) (Wolff and Zacharias 2003) and…”

Section: Methodsmentioning

confidence: 99%

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Quality of Match for Statistical Matches Used in the Development of the Levy Institute Measure of Time and Consumption Poverty (LIMTCP) for Ghana and Tanzania

Rios‐Avila

2016

SSRN Journal

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Section: Methodsmentioning

confidence: 99%

“…The hot deck matching uses ranked information based on some auxiliary information such as the propensity score. For further details on the matching procedure, seeKum and Masterson (2010).…”

mentioning

confidence: 99%

Quality of Match for Statistical Matches Used in the Development of the Levy Institute Measure of Time and Consumption Poverty (LIMTCP) for Ghana and Tanzania

Rios‐Avila

2016

SSRN Journal

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“…We statistically match the data for analysis from the 2008 CTUS and the 2008 CHIP using a procedure developed by Hyunsub Kum and Thomas Neal Masterson (2010). 7 As major disparities exist on the level of economic development across provinces, ensuring that we match the observations to the correct province is important.…”

Section: Datamentioning

confidence: 99%

Gender, Low-Paid Status, and Time Poverty in Urban China

Dong

2017

Feminist Economics

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Using synthetic data from the 2008 China Time Use Survey (CTUS) and the 2008 China Household Income Project (CHIP), this study estimates timepoverty rates and compares the profiles of time-poor men and women workers in urban China. In line with previous research, time poverty is defined as a lack of enough time for rest and leisure. Three time-poverty measures are adopted. By all three measures, women paid workers and low-paid workers account for a disproportionate share of the time poor. Regression analysis further shows that, other things being equal, workers who are women, low-paid, married, and who live with children or the elderly in counties with higher overtime rates and lower minimum wage standards are more likely to be time poor. Simulations indicate that enforcing working time regulations and raising minimum wage standards could be effective for reducing time poverty.

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“…For a technical description and results of our matching algorithm, seeKum and Masterson (2010). For documentation of the statistical matches used in the production of the LIMEW estimates for 1992 and 2007, seeMasterson (2010); for 2010, see Rios-Avila (2014); for 2013, see Rios-Avila (forthcoming).…”

mentioning

confidence: 99%

The Sources and Methods Used in the Creation of the Levy Institute Measure of Economic Well-Being for the United States, 1959–2013

2018

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Statistical matching using propensity scores: Theory and application to the analysis of the distribution of income and wealth

Cited by 28 publications

References 20 publications

Quality of Match for Statistical Matches Used in the Development of the Levy Institute Measure of Time and Consumption Poverty (LIMTCP) for Ghana and Tanzania

Quality of Match for Statistical Matches Used in the Development of the Levy Institute Measure of Time and Consumption Poverty (LIMTCP) for Ghana and Tanzania

Gender, Low-Paid Status, and Time Poverty in Urban China

The Sources and Methods Used in the Creation of the Levy Institute Measure of Economic Well-Being for the United States, 1959–2013

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