The relationship between hours worked and partner's disability in opposite‐ and same‐sex couples

Abstract

When a partner is disabled and not in the labour force, the need for earnings provided by the non‐disabled partner increases. However, the disabled partner's need for care raises the value of time spent at home by the non‐disabled partner. The direction of the relation between partner disability and hours worked varies with couple type because connecting links are affected by couple type. Relevant issues include foregone earnings, amount of income lost by the disabled partner, accumulated savings and healthcare coverage. In order to determine whether there is a significant relation between hours worked and having a disabled partner, controlling for other characteristics, Tobit regression equations were estimated using the US 2000 Decennial Census 5% sample. Among same‐sex partners, unmarried opposite‐sex partners and married men, individuals with disabled partners worked fewer hours in the labour force than did those without disabled partners. Only among married women did those with a disabled partner work more hours.

Résumé

Dans un couple, quand l’un des deux partenaires est handicapé et dans l’impossibilité de travailler, la responsabilité du partenaire non handicapé en ce qui concerne les revenus est accrue. Cependant, les besoins du partenaire handicapé en termes de soins augmentent la valeur du temps passé au foyer par le partenaire non handicapé. Le sens du rapport entre le handicap de l’un des partenaires et les heures travaillées varie selon le type de couple, parce que les connections dépendent du type de couple. Les questions pertinentes incluent les revenus passés, les sommes perdues par le partenaire handicapé, l’épargne accumulée et la couverture en soins de santé. Afin de déterminer s’il existe une relation significative entre les heures travaillées et le fait d’avoir un partenaire handicapé, en tenant compte d’autres caractéristiques, des estimations par la méthode de régression Tobit ont été réalisées en utilisant l’échantillon 5 % du recensement américain de la décennie 2000. Parmi les partenaires de même sexe, les partenaires de sexe opposé et non mariés, et les hommes mariés, les individus ayant un partenaire handicapé avaient un nombre d’heures travaillées inférieur à celui de ceux qui n’avaient pas de partenaire handicapé. C’est seulement parmi les femmes mariées, que celles qui avaient un partenaire handicapé avaient un nombre d’heures travaillées plus élevé.

Resumen

Cuando uno de los miembros de la pareja es discapacitado y no trabaja, aumenta la necesidad de ganar dinero por parte del otro miembro de la pareja no discapacitado. Sin embargo, también es más necesario que la persona discapacitada sea cuidada, lo que aumenta el valor del tiempo que la pareja no discapacitada pasa en el hogar. La dirección de la relación entre la discapacidad del compañero y las horas trabajadas varía según el tipo de pareja debido a que los enlaces de conexión están afectados por el tipo de pareja. Las ganancias previsibles, la cantidad de ingresos perdidos por parte de la pareja discapacitada, los ahorros acumulados y la cobertura sanitaria son algunas de las cuestiones importantes a tener en cuenta. A fin de determinar si existe una relación significativa entre las horas trabajadas y el tener un compañero discapacitado, utilizamos el método Tobit para estimar la ecuación de regresión usando una muestra de un 5% del Censo Decenal 2000 de los Estados Unidos y controlando otras características. Entre parejas del mismo sexo, parejas no casadas de diferente género y hombres casados, las personas con parejas discapacitadas trabajaban menos horas remuneradas que los que no tenían compañeros discapacitados. Sólo entre las mujeres casadas, las que tenían un compañero discapacitado trabajaban más horas.

Keywords:

• care
• cohabitation
• discrimination

Notes

1. One topic not addressed in this study, but an interesting area for future research, is the impact of school‐aged children on hours worked by individuals with disabled partners. The presence of school‐aged children creates a need for some childcare as well as for additional income. In many cases, those children also help to provide care for the disabled family member. In the USA in 2003, there were 1.4 million children between the ages of eight and eighteen who provided care for an adult relative (Hunt et al. 2005).

2. Since the analysis focuses on the labour force behaviour of prime‐aged workers, their partners are likely to be younger than the individuals discussed in most previous disability analyses. The disabled variable was defined in a highly restrictive manner in order to increase the likelihood that the disabled individuals are sufficiently limited to require frequent assistance. The disabled variable was not defined as those with either a personal care or mobility limitation because many people with mobility limitations are able to function quite well on their own. Some individuals with mobility limitations are sufficiently independent to live alone, often compensating for their limitations using wheelchairs and specially outfitted homes and vehicles. Unfortunately, the data do not indicate whether care is provided by the non‐disabled spouse. However, given the restricted definition of disabled, it seems highly probable that the non‐disabled spouse does provide some care. If an individual has either a mobility limitation or a personal care limitation, but not both, or has both but is still in the labour force, that individual is not defined as disabled. However, hours worked by these partially‐limited individuals are not considered in the analysis. Only the hours worked of their partners are included as dependent variables. Households in which both partners have limitations are excluded entirely from the analysis.

3. Since hours worked are left‐censored at zero, Tobit analysis was used instead of ordinary least squares.

4. Since in same‐sex couples without disabilities both partners are included in the same sample, observations would be correlated. Therefore, for these couples, one partner was selected at random and the Tobit analysis was performed on the resulting sample. This process was implemented 1,000 times and the resulting coefficients and their variances were averaged. The results obtained were quite similar to those obtained by running the full samples once, which generates confidence in the findings.

5. Since the estimated equations are reduced form equations, and wages and earnings are endogenous variables, they are not included as explanatory variables in the regression analysis.

6. Many of the explanatory variables are 0–1 dummy variables, whose means can easily be interpreted as the percentage of the sample with the specified characteristic. For example, among married women, the mean of the Hispanic variable is 0.053. This figure implies that 5.3% of the married women in the sample were Hispanic.

7. Information on wealth is not collected by the US Decennial Census.

8. The occupational categories are those used by Leppel (in press). More specifically, white‐collar occupations are Census Bureau occupational codes 001–259: management occupations; business operations specialists; financial specialists; computer and mathematical occupations; architecture and engineering occupations; life, physical and social science occupations; community and social services occupations; legal occupations; and education, training and library occupations. Service occupations are occupational codes 260–599: arts, design, entertainment, sports and media occupations; healthcare practitioners and technical occupations; healthcare support occupations; protective service occupations; food preparation and serving occupations; building and grounds cleaning maintenance occupations; personal care and service occupations; sales occupations; and office and administrative support occupations. Farming, fishing and forestry occupations are occupational codes 600–619. Blue‐collar occupations are occupational codes 620–979: construction trades; extraction workers; installation, maintenance and repair workers; production occupations; and transportation and material moving occupations.