Women’s employment and the decline of home cooking: Evidence from France, 1985–2010


We here investigate the extent to which labour-market changes explain the decline in the time spent home cooking by married women in France between 1985 and 2010. Using time use data and Oaxaca-Blinder decompositions, we find that rising women’s employment and observed wages together account for about 60% of the fall in the time married women spent cooking. We then use a semi-parametric matching technique to construct an implicit wage rate, which better reflects the change in labour-market incentives that individuals face. The rise in women’s implicit wages explains no more than 20% of the decline in their cooking time, while the wage of their partner has no effect. Changing labour-market incentives are thus far from being the main driver of the decline in home-cooking. We also find evidence that home cooking continues to be structured by the gendered social norm of the “proper family meal”.

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  1. 1.

    In an interview with The Independent (23/01/2010), the famous French chef Alain Ducasse attributed the decline in home cooking to “the rising number of working women: ‘Unfortunately in France the women don’t really have time to cook, and we are going toward this trend of less and less home-cooking (…) it’s globalisation, it’s not good news. The Italians have kept this tradition—la mamma cooks for the family home”.

  2. 2.

    INSEE statistics from “Enquêtes Emploi” (labour force surveys): http://www.insee.fr/fr/themes/series-longues.asp?indicateur=taux-activite-femmes [Accessed: 18/07/2016].

  3. 3.

    Retirement has therefore been found to have a large and significant positive impact on food production at home and a negative effect on purchases of prepared food, especially for women (Aguiar and Hurst 2005; Stancanelli and Soest 2012).

  4. 4.

    These underline five mechanisms linking women’s employment, food preparation and obesity: (1) the price substitution effect from rising opportunity costs of time (increasing wage rates), which implies a greater reliance on ready-to-eat processed food that is of poor nutritional quality; (2) an income effect, as food-away (especially restaurant eating) is a normal good; (3) a “behavioural” effect of the greater availability of ready-to-eat food on impulsive consumers; (4) less parental supervision of children’s diet; and (5) fathers not offsetting the fall in mothers’ time inputs.

  5. 5.

    Davis (2014) discusses the most general formulation that makes the distinction between food products and food commodity (meals), where meals consumed away requires time to be produced. For simplicity here, we assume that purchasing food-away entails no time costs, or time costs that are negligible as compared to cooking times. Plessz and Gojard (2015) find no significant correlation between the time spent shopping and the consumption of fresh vegetables.

  6. 6.

    When food-away and meals prepared at home are perfect substitutes, and there is no joint production, η = kT = kN = 1, and the standard result that optimal time inputs depend only on wages, prices and the household-production technology holds.

  7. 7.

    Most technological innovations in household meal production actually originate from innovations in the food-away sector. See Cutler et al. (2003) for an extensive description of these technological advances.

  8. 8.

    The long-term macroeconomic impact of technological progress in the household sector on the rise in married female labour-force participation is analyzed in Greenwood et al. (2005). They estimate that technological progress in the household sector accounts for over 50% of the rise in female labour-force participation in the US over the last century. de V. Cavalcanti and Tavares (2008) estimate an elasticity of female labour-force participation to the price of home appliances in the range of (−0.73; −0.46) in the US over the 1977–1999 period.

  9. 9.

    Commensality refers to eating with other individuals, i.e. with colleagues at the workplace, other students at school, or with family members at home. Comparing family meal practices in France and England, Pettinger et al. (2006) find that French household members eat together more often, cook raw ingredients more often, and are more likely to follow a regular meal pattern. Unsurprisingly then, grazing and the disappearance of the family meal is a real and well-documented source of concern in the UK and the US, while it is much less of a problem in France and continental Europe (Fjellström 2009).

  10. 10.

    Writing a household maximisation program is easy but not very helpful, as it yields intractable results. The literature usually focuses on more restrictive models (goods are either public or private; there is no joint production etc.) when the objective is to recover deep structural parameters. This is not the case in this paper. In addition, it would be difficult to bring such a model to the data. We are able to observe meal commensality, but we do not know whether people eat something that has been cooked just before the meal, or some days in advance.

  11. 11.

    See Grossbard-Shechtman (2003). In collective decision models à la Chiappori, the price effect of the wage rates is further divided into a pure price substitution effect and an extra price effect that comes from the change in the relative bargaining power of spouses, i.e. in the relative welfare weights of each spouse in the household collective welfare function (Vermeulen 2002).

  12. 12.

    See Grossbard-Shechtman (2003) and Bloemen and Stancanelli (2014) for more formal discussions of these predictions. Time-use research in sociology also recognizes that cooking is “unpaid labour” and is therefore doomed to decline as long as people find alternative ways to provide meals and more rewarding ways of spending their time (Gershuny 2000; Ricroch 2011).

  13. 13.

    See https://www.timeuse.org/mtus/surveys. For simplicity, we refer to 1985 and 2010 as the survey years in the rest of this paper. The data were collected between September 1985 and September 1986 for the 1985–1986 FTUS, and between September 2009 and September 2010 for the 2009–2010 FTUS. These FTUS are part of the Multinational Time-Use Database maintained by the Centre for Time Use Research of the University of Oxford.

  14. 14.

    The data for the 998 households with incomplete data are not provided by INSEE. For more information on the completeness of the data, see the documentation of the survey, volumes 4 and 5.

  15. 15.

    About 40% of individuals completed only one day of diary. For these individuals, the distribution of days do not show any systematic bias in favour of a particular day. There are only 78 couples where one partner completed one day and the other two days.

  16. 16.

    Our restricted definition of cooking time follows Bittmann (2015). We chose it because the time spent “washing kitchen utensils” is not a precise category in the FTUS, and our conceptual framework specifically includes the direct utility from cooking. Adding the time spent on meal chores does not fundamentally alter our results.

  17. 17.

    Table S2 in the Supplementary Appendix shows that dropping these individuals has little effect on the average characteristics of the sample.

  18. 18.

    In the 1985–1986 FTUS, total household income is self-reported as an interval variable in 12 categories. We assume a log-normal distribution to extrapolate a continuous measure of total household monthly income (in 2010 Euros). We subtract total self-reported labour earnings from the latter to obtain a measure of unearned household income in Euros per month. The data from the 2009–2010 FTUS come with a continuous household income measure constructed by INSEE.

  19. 19.

    “Saturdays and Sundays off” are weekends for non-workers and off-work weekend days for workers.

  20. 20.

    The increase in the proportion of days off is largely due to the 35-h working week law that was adopted in February 2000. In many companies, unions and managers have agreed to maintain weekly working hours in exchange for additional days of holiday for employees.

  21. 21.

    All statistics are adjusted for individual-day sampling weights, so that the statistics for 2010 are representative of individuals. Given our sample selection choices, we do not claim that our estimation sample is perfectly representative of the entire French population of married women.

  22. 22.

    Following the economic and sociological literature on household decision making and marriage, age difference between spouses (or equivalently partner’s age) is a potential confounding factor for the effect of wages on gains from marriage, spouses’ bargaining powers. It is also related to norms regarding the division of household labour, see for instance Bozon (1991). The residential-area and region dummies control for cross-sectional variations in food prices. Conditional on these characteristics, the cross-sectional variations in local food prices are negligible as compared to time variations, because France is a small country with excellent transportation infrastructure.

  23. 23.

    The following alternative decomposition also holds: \({\Bbb E}\left( {{\mathrm{T}}_{{\mathrm{i}},2010}} \right) - {\Bbb E}\left( {{\mathrm{T}}_{{\mathrm{i}},1985}} \right) = {\mathrm{\beta }}_{1985}\left[ {{\Bbb E}\left( {{\mathrm{X}}_{{\mathrm{i}},2010}} \right) - {\Bbb E}\left( {{\mathrm{X}}_{{\mathrm{i}},1985}} \right)} \right]\) + \(\left[ {{\mathrm{\beta }}_{2010} - {\mathrm{\beta }}_{1985}} \right]{\Bbb E}\left( {{\mathrm{X}}_{{\mathrm{i}},2010}} \right) + c_{2010} - c_{1985}\). All decomposition are estimated using Ben Jann’s Stata command Oaxaca (Jann 2008). with the use of heteroskedasticity-robust matrices of variance-covariance. The effects of categorical variables are normalized, following Gardeazabal and Ugidos (2004).

  24. 24.

    This “long-run” perspective on time-use data assumes that day-to-day variations in time use are random and independent shocks that cancel out at the aggregate level, so that the unconditional mean can be estimated without bias by simple averages (Frazis and Stewart 2012). This does not hold for other statistics, like the median, and we thus do not consider decomposition techniques for distributions. Stewart (2013) also shows that OLS models yield better results than do Tobit models for the analysis of time-use data with zeros. The presence of zeros nevertheless requires the White correction of the variance-covariance matrix, as it likely produces heteroscedasticity in the residuals. Last, the separate modelling of the extensive and intensive margin, i.e. the zeros and the conditional mean, is of interest only when we consider short-term activity shifts in response to shocks, e.g. “do people cook more on sunny days”?

  25. 25.

    We do not include years of experience on the labour market as this was not measured in the 2010 survey. The impact of labour market experience is absorbed by the age and education variables.

  26. 26.

    See Table S2 in the Supplementary Appendix for the descriptive statistics of the variables. Table S11 in the Supplementary Appendix provides robustness checks with alternative time-use measures for 2010: these are calculated as 5/7 of the week day measure + 2/7 of the week-end measure, when the two diary days are available. Table S13 proposes additional results with cooking time including meal chores. The results for labour market variables are qualitatively similar.

  27. 27.

    The full table of results appear in the online Supplementary Appendix, Section S.2.

  28. 28.

    The structure effects and other composition effects appear in Table S6. The structure effects are mostly insignificant, except for those regarding age.

  29. 29.

    Controlling for kitchen equipment but not education does not change the estimated wage effects.

  30. 30.

    See Table S12 in the online Supplementary Appendix, Section S3

  31. 31.

    The results for eating-away are qualitatively similar: see Tables S8 and S9 in the online Supplementary Appendix.

  32. 32.

    These decomposition results are based on logit regressions. These reveal a fall in the implicit wage coefficient between 1985 and 2010, from 0.135 to 0.068 in the restaurant regression for instance. However, the marginal effects estimated at covariate sample means are the same: +1.014 pp/Euro in 1985 and +1.004 pp/Euro in 2010.

  33. 33.

    See Table S10 in the online Supplementary Appendix.

  34. 34.

    Edo and Toubal (2017) evaluate the impact of immigrant female workers on wages, over the period 1990–2010. Over this period, immigrant female workers contributed to an increase of about +3 percentage point in women’s employment. The study concludes that the estimated effect on native women’s wages is −0.11%. If we apply these numbers to our estimation sample, and assume that the entire rise in women’s employment is due to changing preferences, then we under-estimate the composition effect by 2.7% only.

  35. 35.

    For the evolution of the demand for skills in the U.S., see Goldin and Katz (2007). Goldin (2006) and Mulligan and Rubinstein (2008) discuss the human capital effects of the changing expectations of women regarding returns to education. Piketty and Saez (2014) argue that “the supply and demand for skills have increased approximately at the same pace in Europe” (p. 842), and the macroeconomic literature on growth has documented the empirical link between skills, productivity and growth.

  36. 36.

    These falls in cooking time are smaller than the fall for the entire sample (−13.2 min) due to the composition effects of education.

  37. 37.

    This finding is also reflected in the structure effects of education, which are positive for cooking (Table S6) but negative for eating away (Table S7).

  38. 38.

    The composition effect of unearned income is larger for the cooking time of the less educated. This might reflect a statistical artefact: as outlined in Section 3, unearned income are not well-measured. Alternatively, this large composition effect may be explained by the progressive concentration of low-educated people in the bottom of the income distribution. The rise in means-tested social benefits observed over the period has then acted as an incentive to favour household production over employment. Laroque and Salanié (2002) show that the disincentive effects of means-tested benefits can be large, especially for women with an unemployed husband.


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We would like to thank the referees and editors for their comments and suggestions, Andrew Clark and seminar participants at Monash University (Centre for Health Economics), Toulouse School of Economics (Food policy seminar), Oxford (Worshop on time use surveys) and the INRA-DID’IT annual workshop. We acknowledge funding from Institut National de la Recherche Agronomique’s Metaprogram DID’IT.

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Correspondence to Fabrice Etilé.

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Etilé, F., Plessz, M. Women’s employment and the decline of home cooking: Evidence from France, 1985–2010. Rev Econ Household 16, 939–970 (2018). https://doi.org/10.1007/s11150-018-9423-3

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JEL Codes

  • D13
  • I18
  • J22


  • Cooking
  • Household production
  • Labour supply
  • Wages
  • Gender