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Farm mechanization on an otherwise ‘featureless’ plain: tractors on the Northern Great Plains and immigration policy of the 1920s

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Abstract

The 1920s marked the beginning of the diffusion of the gasoline tractor in North American agriculture. The tractor was a labor-saving technology by virtue of its speed of operation, reducing labor input per acre. During the same decade, immigration policies of the USA and Canada diverged sharply. While the USA implemented immigration quotas, Canada admitted large flows of Eastern Europeans, provided their destination was the Prairie West. With the essentially homogeneous nature of the plain on either side of the international border, this divergence in policy sets up a natural experiment that allows us to test the effects of different changes in labor supply on the adoption of labor-saving agricultural technology. We show that although Canadian farmers had earlier adopted tractors at the same rate as farmers in the USA, the relatively slower rate of adoption of the tractor on the Canadian Prairies following the policy divergence can be attributed to Canada’s shift to a more open immigration policy. We conclude that changes to macro-policies can have unexpected consequences as illustrated by this example of tractor diffusion.

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Notes

  1. They were very heavy, under-powered and had limited use in fieldwork other than plowing. They were used as a source of power for equipment.

  2. These northern Great Plains states considered are Minnesota, North Dakota, South Dakota, Montana, Nebraska and Kansas. Nebraska and Kansas are not strictly similar to the other states as winter wheat is the principal small grain grown, whereas spring wheat is grown from South Dakota north. Nevertheless, techniques did not differ too significantly.

  3. Average farm size in 1920 was 140 acres for the entire USA, while for the six Great Plains states average farm size was more than double at 330 acres. Canadian Prairie farms were even modestly larger, averaging 345 acres in 1921.

  4. Combines for tractors were available either with their own engines, which made them too heavy to be pulled by horses, or were powered by coupling to the tractor’s power takeoff.

  5. We are unable to compare countries prior to the first stocks of tractors recorded in the censuses of 1920 (USA) and 1921 (Canada). The US Historical Statistics reports 1000 tractors on farms in 1910 and 5000 in 1915 (Carter et al. 2006, series Da623). The only Canadian source reports 3000 on farms in Canada in 1910 and 15,000 in 1915 (Urquhart 1993). However, we cannot believe that a country with one-tenth the number of farms would have had three times as many tractors. And all tractors in Canada were imported from the USA implying the majority of US production was exported to Canada. The method used by Urquhart to construct the Canadian stock is suspect. He works backward from the 1920 stock reported in the census and adjusts by annual imports. The problem is the trade reports before 1918 do not record imports of tractors per se, but ‘engines, portable with boilers in combination, and traction engines for farm purposes’ as one category (Canada. Dominion Bureau of Statistics 1919). Some unknown share of these would likely have been stand-alone engines used as sources of power (Meyer 2013).

  6. For example, combines were adopted more rapidly in the Kansas and Nebraska because wheat dried more rapidly and uniformly in the Southern Great Plains.

  7. Tractor adoption rates by county are not reported in the 1925 US Census of Agriculture. As an approximation for 1925 only, we report instead the number of tractors adopted rather than number of farms adopting. The number of tractors adopted exceeds the number of farms adopting tractors as some, typically larger, farms report more than one tractor. The actual number of farms adopting tractors in the US counties in 1925 will be fewer than shown in the figure. The average adoption rate for these three border states in 1925 is 15%, while the rate reported in Fig. 3 is 21%. The equivalent adoption rate for the three Prairie provinces in 1925 is 26%.

  8. There is no observation for Ontario in 1925 as the Canadian Census of Agriculture in 1926 only applied to the three Prairie provinces.

  9. The large majority of tractors adopted were in this category.

  10. Rates on harvest equipment fell from 10 to 6%, tillage equipment from 12.5 to 7.5%, and plows from 15 to 10% (Phillips 1956).

  11. In the 1930s, both Canada and the USA undertook official investigations of the trade practices of the agricultural equipment industry (Canada. House of Commons 1937; US Federal Trade Commission 1938).

  12. Also, the Canadian dollar depreciated from 1931 to 1933, returning to par in 1934, accounting for much of the price gap.

  13. Both series were deflated using the cpi for each country and currency was converted using the exchange rate. All sources described in the “Data Appendix”.

  14. The absolute size reflects the difference in the mixes of tractors produced in the USA and consumed in Canada.

  15. While farm foreclosures became much more frequent on the US Northern Great Plain, they were not nearly as large a problem in Canada during this period. See Lew and McInnis (2007) for a discussion of this difference. For US mortgage foreclosures see Alston (1983) and for farm distress during the 1920s see Johnson (1973/1974).

  16. See Alston et al. (2000) for a discussion of wheat policy in this period for the USA and Canada. They conclude it had no affect on prices.

  17. There were other motives as well, particularly the demand by railway companies for settlers to purchase their land grant holdings (Green 1996).

  18. The USA did introduce a literacy test in 1917.

  19. Under the 1921 law, admission by national origin was based on each country’s share in immigration in the Census of 1910. In 1924 the reference year was moved back to the 1890 Census giving greater weight to Western Europe even while the total quota limit was reduced. For example, over 300,000 immigrants arrived in 1913 from countries of Eastern Europe (excluding Poland); from 1921–1924 immigrant numbers were approximately 35,000 annually; and from 1925–1930, there were about 5000 a year (Carter et al. 2006, series Ad114/115).

  20. Massey (2016) demonstrates this effect on skill due to the 1921 quota, which was much less restrictive than the 1924 law.

  21. We identify hired male labor from IPUMS 1% samples as classified by occ1950 codes: 123, 810, 820 and 840).

  22. California had a large share of immigrants from Asia and the majority of foreign-born in Arizona were Mexican.

  23. In 1910, Montana ranked next highest after Nevada, and North Dakota was close behind so they were among states with the largest share of European immigrants in their agricultural labor force.

  24. We exclude the South as the foreign-born made up a very small share of their agricultural labor force, less than 1% except for Florida and Louisiana.

  25. There is a modest increase in immigrant farm labor from the Americas in both Minnesota and Montana from 1920 to 1930. They are from Mexico, not Canada, and the numbers are small, approximately a thousand workers in total.

  26. Note that Table 3 shows only one relatively small labor market, agricultural labor, and so does not illustrate the overall impact of quotas on old versus new immigrants.

  27. These patterns are based on total populations, not just hired agricultural labor.

  28. This paragraph based on Green (1995), Kelley and Trebilcock (1998) and Canada. Parliament. House of Commons. Select Standing Committee on Agriculture and Colonization (1928).

  29. A farmer was the individual in charge of the farm regardless of ownership. Farm laborers were wage earners, and unpaid family members who worked regularly for their parents.

  30. Immigration flows to Canada were largest in the decade of the Wheat Boom from 1901 to 1911.

  31. To be clear, this was the supply as recorded in the census of 1931. The literature stresses that a large number of seasonal workers flowed through the Prairies during the 1920s, taking on various jobs in agriculture, lumber and resource extraction (Avery 1995; Danysk 1995). Some would not have remained in agriculture by the census date in 1931 so the data in the table undoubtedly understate the size of the agricultural labor force relative to the number of farmers in this period (Green and Green 2016).

  32. From the IPUMS 1930 census sample, using the occ1950 variable, farmers were counted as codes 100 and 830; and farm workers as codes 123, 810, 820 and 840.

  33. We focus on males because not all females working in agriculture were necessarily categorized as farmers or farm workers.

  34. While there were many immigrants from Canada born elsewhere, they are more difficult to find in the Census. Regardless of their numbers, the quotas specifically excluded European-born from transiting through Canada, requiring 5-year residency in the Americas to qualify as quota-exempt.

  35. Rather than reporting wages with and without board as does the USDA, the Canadian source reports wages with board and an estimate of the value of board. By implication wages without board are equal to wages with board plus the value of board. We find the value of board is inconsistent when compared with other measures of cost of living, so we choose to use wages with board.

  36. The agreement was controversial due to anti-immigration pressure, and was only renewed in 1928 after a formal Parliamentary review.

  37. System GMM requires that the fixed effects and the instrumenting variables be uncorrelated. Because immigration policy is correlated with the fixed effects—both Canada and the USA adopt immigration policies—we don’t expect that assumption to hold. Difference GMM does not require this assumption.

  38. We recognize these are rough estimates. For example, the Canadian Census of Manufactures excludes fuel costs, while these seem to be included in the US data.

  39. With respect to immigrant supply, Enflo et al. (2014) also use distance from port to each state, but given our use of difference GMM and given that this measure is time-invariant, it will drop out of our estimates. We could interact the measure with time, but that will dramatically expand the number of instruments in our estimates. In fact we did try this, but the inclusion of distance makes little difference to our results.

  40. To generate wages we take a population-weighted average of individual maritime province values.

  41. There is no dummy for country as it is absorbed in the fixed effects.

  42. Results are unchanged if we exclude South Dakota from the sample and use only the border states and provinces.

  43. The Canadian Prairie provinces are subdivided into census divisions.

  44. We start with 1925 because data by county are first reported in the 1925 US Census of Agriculture.

  45. As discussed above (in Footnote 7) we have substituted tractors per farm for the missing number of farms with tractors for US counties in 1925. The implication for our test is that because there are more tractors adopted per farm than there are farms adopting tractors, this edited measure of adopters will understate the increase in the number of adopters from 1925 to 1930 in the USA, which will bias our estimates against finding increasing divergence between the two countries between 1925 and 1930.

  46. Fixed effects for county/census division are included. Regressions are weighted by the number of farms and by the product of the number of farms with tractors times the number without divided by the number of farms for regressions on tractors per farm and odds ratios respectively.

  47. The interest rate is included rather than tractor cost because the coefficient on interest was statistically significant in Table 7. While including all covariates makes the estimate less precise due to weak identification, the conclusions do not change. We have dropped population density as it was not statistically significant in any specification.

  48. We also tried varying the instrument set to see how sensitive results were to changed instruments. If we used only one instrument: plumbers wages, the coefficient on farm wages was not statistically significant. We also tried using a larger set of instruments, adding in land prices and farm size. Again, their inclusion did not change the magnitude of the coefficients by much, but weak identification became a problem. We also tried several subsets of the four, but the use of the two instruments chosen provides the optimal results in terms of reducing weak identification.

  49. As a set of ratios, wheat prices show little variation. We did try running our iv regressions using all the possible subsets of the three instruments. The choice did affect the coefficient values on wages somewhat, but not the statistical significance.

  50. When we ran regression 1 using tractor user cost rather than the interest rate, the year indicator was statistically significant at the 5% level.

  51. Excluding the two MB1 observations increases the magnitude and the significance of the coefficient on wages in both regressions, but otherwise doesn’t affect inferences.

  52. Excluding the two observations with MB1 from regressions 3 and 5 yields no change to the statistical significance of either coefficient.

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Acknowledgements

The authors wish to thank Alan Green, Tim Guinnane, the participants of the CNEH meetings, and two anonymous reviewers for helpful comments.

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  1. Department of Economics, Trent University, Peterborough, Canada

    Byron Lew & Bruce Cater

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Data Appendix

Data Appendix

Wage Rates

  • Farm wages are the average annual monthly wages with board (US Department of Agriculture 1951, 1948/1955; Canada. Dominion Bureau of Statistics 1908/1930). USDA source reports wages with and without board. Canadian source reports wages with board and the value of board.

  • Plumbers wages are reported by city, so for the Prairie rates Calgary and Edmonton are averaged for Alberta, Regina is used for Saskatchewan, and Winnipeg for Manitoba (Canada. Department of Labour 1931/1932). For the US plumbers wages are reported in cities in all three states for 1920 only, but not for North Dakota after 1920 (US Department of Labor 1926, 1932). For 1925 and 1930, wages in Omaha, Butte and Minneapolis are averaged to represent wages in North Dakota since this average approximates very closely reported wage rates in Grand Forks in 1920, the year for which data in all three states are available.

Manufacturing Value Added

  • Reported in The Canada Yearbook (Canada. Dominion Bureau of Statistics 1926/1935) and the Statistical Abstract of the United States (US Bureau of the Census 1921/1935).

Price Deflators

  • All prices are expressed in real 1913 $US. US prices deflated using the BLS CPI Index (Carter et al. 2006, series Cc1); Canadian prices deflated using Department of Labour Cost of Living index for 1913 on (Urquhart 1965, series J139), and the Bertram-Percy index (Bertram and Percy 1979). Canadian values converted to $US using Canada–US dollar exchange rate (Urquhart 1965, series H625).

Immigration

  • Immigration rates by state or province of intended destination are taken yearly (US Bureau of Immigration 1910/1930; Canada. Department of Immigration and Colonization 1920–1925, 1924–1930/1931). Destination of immigrants to the Canadian Prairies in the period 1925–1930 is clearly distorted as reported in the Immigration Department reports, with a disproportionate number indicating Manitoba as destination. As immigrants from the non-preferred countries were admitted only for agricultural employment most of those indicating Manitoba were in fact using Winnipeg as a point to coordinate their employment elsewhere on the Prairies. Immigrant destination for these years in Canada are calculated as the total number of immigrants to all three Prairie provinces allocated according to the distribution of immigrant arrivals for this period as reported in the 1931 Census (Canada. Dominion Bureau of Statistics 1936a).

Crop Acreage, State/Province-level

  • Canada from Handbook of Agricultural Statistics (Canada. Dominion Bureau of Statistics 1964); USA from Yearbook of Agriculture (US Department of Agriculture 1910/1934).

Tractor User Cost

  • Tractor user cost is calculated as tractor prices \(\times\) (interest rate + inflation expectation + depreciation rate). Inflation expectations are derived using a centered 3-year moving average of the CPI for each country. US Tractor prices and depreciation rates are from Olmstead and Rhode (2001). Tractor prices for Canada from Canada. House of Commons (1937, pp. 124, 141)

Interest Rates

  • Canada: Annual Report (Canadian Farm Loan Board 1930/1931–1954/1955); Financial History of Canadian Governments (Bates 1939); and Farm Credit in Canada (Easterbrook 1938).

  • USA: Farm-Mortgage Credit Facilities in the United States (Horton 1942) andYearbook of Agriculture (US Department of Agriculture 1910/1934). The latter reports only regional rates.

Wheat Prices, State/Province-level

  • Prices received by farmers, Canada from Handbook of Agricultural Statistics (Canada. Dominion Bureau of Statistics 1964); USA from Yearbook of Agriculture (US Department of Agriculture 1910/1934).

County-level Farm Data

  • \(\left. \begin{array}{ll} \hbox {Farm}\,\hbox {counts} \\ \hbox {Tractor}\, \hbox {numbers}\, \hbox {and}\, \hbox {farms}\, \hbox {adopting} \\ \hbox {Crop}\, \hbox {acreage}\\ \hbox {Area}\, \hbox {in}\, \hbox {farms} \\ \hbox {Cattle}\, \hbox {stocks} \\ \hbox {Area}\, \hbox {in}\, \hbox {county}/\hbox {census}\, \hbox {division} \\ \hbox {Land}\, \hbox {values} \\ \end{array}\right\} \hbox {Census}\, \hbox {of}\, \hbox {Agriculture}, \hbox {various}\, \hbox {years}\)

Population

  • Census of Population, various years

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Lew, B., Cater, B. Farm mechanization on an otherwise ‘featureless’ plain: tractors on the Northern Great Plains and immigration policy of the 1920s. Cliometrica 12, 181–218 (2018). https://doi.org/10.1007/s11698-016-0157-2

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