Analysis of the Standard of Living in the District of Columbia in 1916

Ogburn, William F.

doi:10.2307/2964887

Cited by 13 publications

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“…A simple way of describing Engel's law in the early literature is to suppose a linear correlation between food consumption and income. For example, Ogburn (1919) and Allen and Bowley (1935) used

q_{i} = a_{i} + b_{i} y

as the basic model to carry out empirical studies with a sample of many countries, where

q_{i}

is the quantity of consumption on commodity i and y is the residents’ income. The results showed that the estimating error of this model was occasionally relatively large, which can be attributed to the heterogeneity in the tastes of consumers in different regions.…”

Section: Methodsmentioning

confidence: 99%

Engel’s law in China: Some new evidence

Chen

2022

Review Development Economics

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Engel's law states that the proportion of food in total consumption expenditure is negatively associated with household income. Different from other studies with time series, this paper investigates the applicability of Engel's law in China, with a sample of cross‐sectional data in 2016 covering the 31 provincial regions of China. The empirical results support Engel's law, and, especially after the consideration of food prices, which is represented by regional food purchasing power parities, the negative impact of income on Engel's coefficient becomes more statistically significant. Meanwhile, Engel's coefficient is positively related to the food price. According to different types of income elasticity, food is divided into two groups: life necessities and life nonnecessities. Then, the inferior Engel's coefficient (IEC) and superior Engel's coefficient (SEC) are calculated with the expenditures of necessary and nonnecessary food, respectively, and a further study shows that the negative relationship between income and the SEC is much weaker than that between income and the IEC. Besides, Engel's coefficient is more strongly affected by the price of food necessities than by that of food nonecessities.

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q_{i} = a_{i} + b_{i} y

as the basic model to carry out empirical studies with a sample of many countries, where

q_{i}

Section: Methodsmentioning

confidence: 99%

Engel’s law in China: Some new evidence

Chen

2022

Review Development Economics

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“…Machines were "taking jobs from men and increasing the already swollen ranks of the unemployed." They were also bringing "diseases and disasters," while reducing the influence of the family and the church (Ogburn, 1933;p. 3).…”

Section: Presenting a More Strident Case Through Pamphletsmentioning

confidence: 99%

“…3). If these impacts seemed worrisome and even appalling, the Chicago sociologist also tempered his assessment by pointing out that not all unemployment was brought about by machinery: "The estimates of the number of such technologically unemployed are usually no higher than ten or fifteen per cent of the total without jobs" (Ogburn, 1933;p. 7).…”

Section: Presenting a More Strident Case Through Pamphletsmentioning

confidence: 99%

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‘The Machine Takes Our Jobs Away’: The problem of technological unemployment in the work of Chicago sociologist William F. Ogburn

Kim

Solovey

2022

J History Behavioral Science

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This paper examines the Chicago sociologist William F. Ogburn's (1886–1959) views about technological unemployment, which were intimately connected to his analysis of the social impacts of technological developments and resulting social problems due to cultural lag. We trace the development of his views as seen through his well‐known 1922 book, Social Change with Respect to Culture and Original Nature, his important contributions to the President's Research Committee on Social Trends (1933), and his lesser‐known pamphlets designed for a broader audience—Living with Machines (1933), You and Machines (1934), and Machines and Tomorrow's World (1938). He used these pamphlets to educate the public about the dangers of new machines and technological unemployment. In doing so, he drew upon sociological analysis in his professional scholarly writings and his long‐standing personal interests in social betterment and social reform. Our analysis also calls into question the adequacy of existing scholarship on Ogburn that has emphasized his commitment to a statistical, dispassionate, and “objectivist” approach to social science research. We call for a revised, richer, and more complex view of Ogburn's work and legacy as one of the nation's leading social scientists during the first half of the 20th century.

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“…But his studies of demand and supply did lead on to the early work in agricultural economics (in midwest universities and the government Bureau of Agricultural Economics) after 1918, and statistical analysis was much more widespread in this arena than in mainstream economics in the interwar years (see Fox, 1989;Thomas, 1989;also David, 1998). Two of Moore's graduate students were Henry Schultz, who established statistical demand analysis in interwar Chicago (see Shultz, 1923;1928) and William Ogburn, who published on the analysis of living-costs (for example, Ogburn, 1919) and who became Professor of Sociology at Chicago and one of the influences on quantitative analysis in the Chicago School of sociology (Bulmer, 1981;Duncan, 1964;Thomas, 1989). In 1929 Ogburn provided a cross-sectional (geographical) multiple regression analysis of the 1928 presidential election (Ogburn and Talbot, 1929); it was Ogburn who decided to have his quantifier's paraphrase of Lord Kelvin (``When you cannot measure your knowledge is meagre and unsatisfactory'') carved on Chicago University's new Social Science Research Building (Bulmer, 1984, page 182)…”

Section: Other Social Science Applicationsmentioning

confidence: 99%

Multiple Regression and Spatial Policy Analysis: George Udny Yule and the Origins of Statistical Social Science

Hepple

2001

Environ Plan D

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Studies on the history of statistics by MacKenzie and on quantitative geography by Barnes have suggested that the lineaments and assumptions of statistical methods such as correlation and regression are closely related to their origin in biometrics and eugenics. This paper challenges that view by examining in detail the work of George Udny Yule. Yule was a colleague of Karl Pearson in the 1890s, but was interested in social science and social policy applications, not eugenics. In the late 1890s he constructed both the theory and application of multiple regression analysis, using geographical data. The paper examines Yule's work and its context, relating it to debates on the history of statistics, and traces the subsequent early diffusion of regression and correlation into the social sciences. The paper concludes by arguing for greater recognition of Yule's pivotal role, and also for further studies on the history of quantitative social science.

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Analysis of the Standard of Living in the District of Columbia in 1916

Cited by 13 publications

References 0 publications

Engel’s law in China: Some new evidence

Engel’s law in China: Some new evidence

‘The Machine Takes Our Jobs Away’: The problem of technological unemployment in the work of Chicago sociologist William F. Ogburn

Multiple Regression and Spatial Policy Analysis: George Udny Yule and the Origins of Statistical Social Science

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