How does intrahousehold bargaining power impact labor supply? European cross-country evidence
How does intrahousehold bargaining power impact labor supply? European cross-country evidence
Ignacio Belloc, José Alberto Molina, Jorge Velilla
Full text: https://ideas.repec.org/p/zbw/glodps/1132.html
This paper was awarded the Luis Toharia grant for young researchers in labour economics (V edition)
The study of the family was first addressed many years ago (Aristotle, Politics, Book 1, Part 2, according to Browning et al., 2014). However, it was as a result of the work of Gary Becker and Jacob Mincer in the 1960s and 1970s when a new school of Household Economics emerged in Columbia and Chicago (Grossbard, 2006). The field of Family Economics has evolved from that school during the recent years, mostly focusing on the link between households and labor economics, but also covering other topics and gaining importance in Economics. Family Economics is now defined as “the economic analysis of household decisions, including decisions regarding consumption, labor supply, and other uses of time, household formation and dissolution, demand for health and other forms of human capital, fertility and investment in children’s human capital, demand for environmental and other public goods, migration, demand for religiosity, and decisions by agricultural households”, according to the Society of Economics of the Household (https://sites.google.com/view/seho2018).
The classical framework with which to analyze household economic behaviors is the so-called “unitary” model. The unitary model considers the household as a single decision-making unit, with a homogeneous set of preferences and a unique utility function. In other words, the unitary model considers households as “black boxes” and ignores any type of intrahousehold issue. Consequently, this unitary approach has come under heavy criticism in recent decades, given its ad-hoc theoretical foundations and its empirical predictions, which have been constantly rejected (Chiappori and Mazzocco, 2017). Since the 1980s, various authors have developed different theories with the objective of reconciling the theory, modeling household behaviors more accurately, explicitly recognizing that individual preferences may differ, and by trying to model the decision process through which spouses’ preferences interact (Browning et al., 2014).
In that context, Chiappori (1988, 1992) proposed the first general framework to study intrahousehold decisions, the collective model, assuming only that there exists some type of cooperation among household members that leads to Pareto-efficient outcomes. Several studies have pointed to the empirical validity of the collective model since then; Chiappori et al. (2022) provide a recent review of the literature.
The collective model is a theoretical tool, as it invokes the second welfare theorem and allows to identify intrahousehold allocations and income sharing, which are typically unobservable, through household observed behaviors, namely consumption, leisure, and labor supply, conditional on such observed behaviors satisfying a series of testable restrictions (often referred to as “collective rationality”). This identification is partially driven by “distribution factors”, defined as variables that affect spouses’ intrahousehold bargaining power and allocations exogenously, i.e., without affecting utilities or the household budget constraint (Browning and Chiappori, 1998). A theoretical model of household collective labor supply, and an empirical reduced form application for the US is shown in the seminal paper by Chiappori et al. (2002), in which intrahousehold allocations are identified in terms of changes in divorce laws and sex ratios in the US. Such an approach has become the benchmark model for several derivations and contributions (Donni and Molina, 2018).
In this context, however, most of the empirical applications of the collective model are based on single-country analysis, concrete parametrizations of observed and unobserved behaviors, and on very specific distribution factors. Thus, whether distribution factors can be applied to different contexts and different economies remains unclear. For instance, the sex ratio has been found to be an appropriate distribution factors in some contexts, but seems not to operate as expected in others, even when studying the same country (Chiappori et al., 2022).
This paper then uses homogenized data for 17 European countries (Austria, Belgium, Czech Republic, Denmark, Estonia, France, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Poland, Portugal, Spain, Switzerland, and the United Kingdom), for the period 2004-2019, taken from the European Union Statistics on Income and Living Conditions. Our objective is to estimate the Chiappori et al. (2002) model for each of the analyzed countries, using the same vector of distribution factors for every country, and analyze whether intrahousehold allocations impact household labor supply similarly in each country, that is to say, if distribution factors have a homogeneous or heterogeneous impact on observed behaviors. Our distribution factors include: 1) The sex ratio (the relative number of males per female of a given age), which measures the supply of women in marriage markets. 2) The share of non-labor income coming from wives, which represents wives’ contribution to household unearned income. 3) Spouses’ age and education difference, which accounts for differences in spouses’ demographic attributes. 4) Fertility rates, which represent social norms towards marriage and childcare. The intuition behind distribution factors is that these variables should have opposite effects on male and female labor supplies. A distribution factor that empowers a given spouse should increase his/her demand for leisure, therefore decreasing his/her labor supply, with an opposite impact on the labor supply of the spouse.
Our results show that distribution factors have a heterogeneous impact on spouses’ labor supplies, as different distribution factors operate in different countries:
- Austria: age and education gap, fertility rate
- Belgium: wives’ share of non-labor income, age and education gap
- Czech Republic: sex ratio, wives’ share of non-labor income, age and education gap, fertility rate
- Denmark: sex ratio, age and education gap, fertility rate
- Estonia: wives’ share of non-labor income, age gap, fertility rate
- France: age and education gap, fertility rate
- Hungary: sex ratio, education gap
- Ireland: sex ratio, wives’ share of non-labor income, age and education gap, fertility rate
- Italy: sex ratio, wives’ share of non-labor income, age gap
- Latvia: wives’ share of non-labor income, fertility rate
- Lithuania: sex ratio
- Luxembourg: wives’ share of non-labor income, age and education gap
- Poland: sex ratio, wives’ share of non-labor income
- Portugal: wives’ share of non-labor income, education gap, fertility rate
- Spain: sex ratio, wives’ share of non labor income
- Switzerland: sex ratio, age gap, fertility rate
- The United Kingdom: wives’ share of non-labor income, age and education gap, fertility rate
To the best of our knowledge, this study offers the first empirical application of the collective model of household labor supply in a cross-country setting using homogeneous data, focusing on which variables are appropriate distribution factors in different countries. We report empirical evidence for a range of countries and report that different distribution factors affect intrahousehold decisions in different countries. These results should be considered for further research studying intrahousehold behaviors and inequality, and by planners when designing policies that aim at decreasing intrahousehold inequalities.
References
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