国家智商与社会经济发展

-Sebastian Jensen, unaffiliated, sebastianxjensen@gmail.com-Emil OW Kirkegaard, Ulster Institute for Social Research Abstract Using 47 indicators of socioeconomic development and various sources of performance oncognitive tests, we constructed the SDI (socioeconomic development index) and a set ofnational IQs for 197 nations, the latter using no geographic imputations. Combining the variousdatasets reduced the estimated standard error of national IQs from 5.41 to 2.58, and a strongcorrelation between socioeconomic development and national IQs was observed (r = .88). Based on the prior that Flynn Effect gains do not pass measurement invariance, IQ scoresshould exhibit some non-negligible bias between countries. Empirical assessments ofmeasurement invariance across nations finds that measurement invariance violations areuncommon and typically found when verbal tests are given. In most countries, national IQsshow high levels of reliability and validity, and we encourage their use in the literature. 1.Introduction Differences in economic development between countries have traditionally been quantifiedusing GDP (gross domestic product) per capita, introduced in 1937 by Simon Kuznets tocapture all economic production (Dickinson, 2011). This measurement was popularized in 1944after the Bretton Woods conference and has become a commonly used measurement ofeconomic development. This measurement has faced various criticisms: the most notable onebeing that GDP does not take into account income earned abroad, leading some economists toadvocate for using GNI (gross national income) instead. In addition, socioeconomicdevelopment (socioeconomic development) extends beyond economic output -- other variablessuch as mortality, educational attainment, safety, and institutional quality must be taken intoconsideration. Consequently, researchers developed composite indices such as the HDI (humandevelopment index) and the SPI (social progress index) which use multiple indicators toconstruct a general index. Both of these indexes, while useful, have their respective issues. The HDI only uses threeindicators -- GDP, educational attainment, and life expectancy -- to calculate socioeconomicdevelopment, which leads to some non-negligible unreliability (ω = .93, when using GNI percapita, life expectancy, expected years of schooling, and mean years of schooling). The SPIreduces the influence of unreliability by using 50 indicators to calculate socioeconomicdevelopment, which is better, but many of these variables may suffer from non-invariance (bias)across cultures, notably indicators of sexual inequality, democracy, corruption, and freedom,which assume that current Western values are the best in a kind of “the end of history” approach(Fukuyama, 2006). While these values may be desirable or lead to higher levels ofsocioeconomic development, using more objective indicators of socioeconomic development(e.g. internet speed, median income) would be best to avoid the problem of cultural bias. Thereis also the question of scoring: most indices of socioeconomic development use arbitraryweighting methods, like the HDI, which changed to a geometric mean method in 2011 whichshifted the rank order a bit (United Nations, 2011). Similar to socioeconomic development, there is an issue with measuring human capital. Anexample of an early adopter of comparing test scores between different nations was BarbaraLerner (1983), who compared the performance of Western Europe, the United States, andJapan in test performance and hypothesized that it was related to economic development.Richard Lynn (1978; 2002) later collected IQ test scores from various countries, and found thatnational IQs and GDP per capita correlated at .82, though this dataset and other revisions of ithave been extensively criticized in the literature. Some economists have made indexes ofhuman capital based on child mortality, test scores, and educational attainment (Angrist et al.,2021), but it could be argued that child mortality and education are a function of both humancapital and socioeconomic development, making it an improper measurement. The purpose of this study is to use state-of-the-art statistical and machine learning techniques tocreate the most accurate measurements of socioeconomic development and human capital thatcan be made. Theoretically, socioeconomic development should affect human capital due to the fact that socioeconomic development causes nations to have better nutrition and health, andsocieties with higher levels of human capital should create societies with higher levels ofsocioeconomic development. Other researchers reported strong correlations between indicatorsof socioeconomic development (e.g. GDP per capita) and human capital (r = .6 - .8) (Lynn,2002; Rindermann, 2018), though these values are based on the national IQ datasets whichhave been unpopular in the literature. 2.Data Data on most national development indicators were sourced from the Social