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Economic Development and Labour Supply in Underdeveloped Regions: An Analysis of the Labour Supply of Domestic Servants in Northern Akita Prefecture, Japan, 1910–1924

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Abstract

In industrialising Japan, labour supplies depended on regional differences in economic development. Large parts of Japan were underdeveloped regions characterised by delayed industrialisation and relatively low agricultural productivity. However, little is known about how economic conditions affected labour supplies in such regions. To answer this question, I investigated the employment of domestic servants in northern Akita Prefecture, a typical underdeveloped region, from the 1910s to the early 1920s. Until the early 1910s, wealthy families in this region recruited daughters from peasant families as domestic servants at a low fixed wage. This indicates that the supply of labour was unlimited, as defined by W. Arthur Lewis. From the late 1910s to the early 1920s, however, this region achieved remarkable agricultural growth. As a result, peasant families could obtain almost the same amount of income by having daughters work on farms as by sending them elsewhere to work as domestic servants. Employers of domestic servants therefore offered higher wages to recruit workers. This implies that in the underdeveloped regions, what had been an unlimited supply of labour was transformed into a limited supply due to agricultural growth.

This chapter is a translation of an article that originally appeared in Shakai Keizai Shigaku 75(4) (November 2009), pp. 27–49.

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Notes

  1. 1.

    I calculated total working population as follows. First, using the lists of people with principal occupations, I excluded those classified as “independent” from the total figure. Then, I added to that the figure pertaining to the number of live-in servants, who were not included in the population with principal occupations. I also calculated the number of workers in the non-agricultural sector by subtracting from the total working population the number of those whose principal occupations were listed as “agriculture” and “fishery”.

  2. 2.

    Since the 1930 census, unlike the 1920 census, classifies live-in servants as those with principal occupations, I calculated the total female working population by subtracting the number of women in the “principal occupations list” categorised as “independent” from the total number of females who had principal occupations.

  3. 3.

    I obtained the total number of female workers by subtracting females classified as “independent” in the list of principal occupations from the entire female population with principal occupations.

  4. 4.

    In this region, the number of women aged 15–19 expanded from 33,939 to 37,561 between 1920 and 1930 (Naikaku Tōkeikyoku 1927, pp. 8–17; Naikaku Tōkeikyoku 1934, pp. 8–17). Thus, this cohort increased, on average, by 363 a year during this period. As noted below in this section, without any labour outflow, the number of women aged 15–19 in this region would have expanded by 1,626 a year. I estimated the average annual net outflow at 1,263 by subtracting 363 from 1,626.

  5. 5.

    Nōrinshō (1930), a survey on the use of fertilisers, reports that as late as 1927, in Akita Prefecture, the average consumption of self-produced fertilisers per hectare, valued on a monetary basis, was 80.972 yen, whereas fertilisers purchased came to only 7.865 yen. The source converted the consumption of self-produced fertilisers into a monetary value as follows (Nōrinshō 1974, p. 3). It fixed the price of each nutrient, such as nitrogen, using fertiliser prices, multiplied the amount of each nutrient by its price, and aggregated the monetary value obtained for each nutrient. Since the monetary value of self-produced fertilisers consumed per hectare was far greater than that of the fertilisers purchased, it is clear that the supply of nutrients to farming mainly depended on the use of self-produced fertilisers such as manure.

  6. 6.

    The 1920 survey lists the types of fertilisers and the quantity of consumption of each, but it includes only the monetary value of the total consumption of fertilisers. Thus, I distinguished the costs of fertilisers purchased from the monetary value of self-produced fertilisers using the price of each nutrient (see note 5).

  7. 7.

    For a number of years, the sources divide each year into halves or quarters and list the highest, average, and lowest prices of each good or service. In this case, I calculated the annual average of each year using the average of these prices.

  8. 8.

    According to this source, the largest portion of fuel and lighting expenses went to charges for the use of electric light, but electric-light use became more widespread in rural Akita Prefecture after the mid-1920s (Akita-ken Nōkai 1929). Since oil lamps were used until the early 1920s, I used the price of kerosene as a substitute.

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Appendices

Appendix 1 Estimate of an Annual Net Outflow of Labour

The following is an explanation of how to estimate an annual net outflow of labour from an area. Official statistics divide temporary residents into two types defined as follows (Umemura et al. 1983; Saito 1998). The first are temporary residents who had migrated from an area to another; the second are temporary residents who had migrated to an area from another. The former denotes those who had registered an area as their place of permanent residence but who resided outside the area at the end of each year. The latter indicates those who resided inside an area at the end of each year but who had registered other areas as their places of permanent residence. I subtracted the number of temporary residents who had migrated to an area at the end of each year from the number who had migrated from the area at the same time. The annual increase (or decrease) in this difference is defined as the annual net outflow of labour from the area.

According to official data on temporary residents, the annual net outflow of women in northern Akita Prefecture was, on average, 762 between the ends of 1909 and 1915 (Akita-ken 1912–1925, 1909 and 1915 versions). At the end of 1913, the cohort aged 15–19 accounted for 11.5% of all female temporary residents who had migrated from this region (Akita-ken Kōbunshokan, Akita Kenchō Monjo, no. 12271). By multiplying 762 by 11.5%, I estimated the annual net outflow of women aged 15–19 at 88. However, this is an underestimate. When people left their homes to stay in other places as temporary residents, they had to register the places of their residence. The official data on temporary residents were based on this registration, but a considerable portion of temporary residents neglected the registration.

To assess the degree of underestimation, I calculated the exact difference between the number of female temporary residents who had migrated from and the number who had migrated to northern Akita Prefecture at the end of 1920. The 1920 census lists the exact number of those who stayed in this region at the time the census information was taken, namely on 1 October 1920 (Naikaku Tōkeikyoku 1927, pp. 2–5). Moreover, Akita Prefecture’s statistical yearbooks specify the number of those who had registered this region as the location of their homes at the end of 1920 (Akita-ken 1912–1925, 1920 version). Of these two numbers, the latter was larger than the former because the outflow of labour exceeded the inflow of labour. Thus, by subtracting the former from the latter, I obtained the exact difference between the numbers of temporary residents who had migrated from and to northern Akita Prefecture. This difference was 1.93 times greater than the counterpart obtained using only the official data on temporary residents. By multiplying 88 by 1.93, I revised the annual net outflow of women aged 15–19 to 170. In the same manner, I estimated the annual net outflow of women aged 15–19, on average, at 728 between the ends of 1915 and 1920.

Appendix 2 Estimate of the Living-Cost Index in Northern Akita Prefecture

The following is an explanation of how to estimate the living-cost index in northern Akita Prefecture. Ohkawa et al. (1967) have already estimated the national index for living costs and I used the same method for my estimations. Based on the case of a typical household, I classified its living expenses by category and, when necessary, divided each category into items. Then, using the Laspeyres formula, I fixed a benchmark year and weighted each category or item. Finally, I multiplied the price index of each category or item by its weight and aggregated the resulting figures to calculate an index of the cost of living. To examine how price changes affected the household budget of a lower-class farming family, I used a 1934 survey of the household budget of a peasant family cultivating tenanted lands in Kita-Akita District (Akita Eirinkyoku 1935, pp. 12–17). I classified the living expenses of this family by category or item and weighted each category or item. Here, living expenses are defined as regular household expenses. Thus, I excluded irregular expenses, such as those for ceremonial occasions, from the household expenses of the family. I also converted the consumption of self-produced foods into its monetary value using price data available in the source. Then, I set 1910 as the benchmark year and calculated the living-cost index using price data from Akita City (Akita-ken 1912–1925, 1910–1924 versions).Footnote 7

The categories, items, and weights (in percentage) of the model household’s living expenses are listed at the end of this appendix. The classification of categories is based on Ohkawa et al. (1967). The food expenses category, weighted at 79.02, is divided into items. For each item, or each category other than food expenses, I used the price of a specified good or service. In some cases, however, the survey includes a number of goods or services under the heading of a single category or item. In such cases, I chose as the representative good or service the one for which the expenses were largest and then used its price data. Price data are unavailable for a number of goods listed in the survey. For these goods, I used the prices of their substitutes. The final list specifies as “representative” or “substitute” those categories or items for which I adopted a representative good or service or a substitute good.

  1. A.

    Food expenses 79.02

    Items: rice (brown rice: substitute) 56.37, barely 3.32, soybean 2.52, soy source 1.18, salt 1.31, sugar (imported white sugar: substitute) 1.61, dishes other than staple food (dried bonito: representative and substitute) 7.15, beverages (saké: representative) 5.56

  2. B.

    Clothes expenses (cotton cloth: representative) 4.56

  3. C.

    Fuel and lighting expenses (kerosene: representative and substitute) 3.74Footnote 8

  4. D.

    Housing expenses (carpenter’s daily wage: representative) 10.07

  5. E.

    Miscellaneous expenses (writing papers: representative and substitute) 2.63.

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Ogiyama, M. (2019). Economic Development and Labour Supply in Underdeveloped Regions: An Analysis of the Labour Supply of Domestic Servants in Northern Akita Prefecture, Japan, 1910–1924. In: Okuda, N., Takai, T. (eds) Gender and Family in Japan. Monograph Series of the Socio-Economic History Society, Japan. Springer, Singapore. https://doi.org/10.1007/978-981-13-9909-1_2

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