There are, broadly speaking, two hypotheses on the relationship between population and economic growth, as explained in Sibe, Chiatchoua, and Megna (2016). The Malthusian view, named for Thomas Malthus and his famous essay on population (Malthus (1798)), holds that population growth tends to depress per-capita GDP. The Kremerian view, named for Kremer (1993) as discussed below and also termed the “revisionist” view by Darrat and Al-Yousif (1999), holds that more people leads to more opportunity to invent and to create wealth, ultimately increasing per-capita GDP. Darrat and Al-Yousif (1999) posit a third view, which they call transition theory, which holds that povery increases the rate of population growth, but there is little effect of population on growth.
Long-Term Growth
Kremer (1993) is among the researchers who have argued that technological advancement should be considered endogenous to population size, meaning that the rate of technological growth depends on population size, rather than occurring exogenously. The main mechanism by which population size drives technological advancement is through the nonrivalry of ideas, meaning that if one person benefits from new ideas, then the ability for others to benefit is not diminished. All else equal, a larger population implies more opportunity for people to come up with ideas, thereby increasing the rate of technological advancement and economic growth.
Kremer’s (1993) model combines the above insight with a Malthusian model of population dynamics: the population of a region is limited by the technological ability to support the necessities of life. The result of the model is that, as population growth, the rate of technological progress tends to grow as well, leading to a super-exponential population growth rate, in that the annual percentage growth rate also increases over time.
Under Kremer’s (1993) model, research productivity, or the amount of technological progress that is generated per-person, is not necessarily constant in either income levels or population size. A larger population might also increase research productivity by increasing the opportunity for specialization, fruitful intellectual contact, and market size, analogous to the drivers of agglomeration economies within cities, in that larger cities tend to generate greater per-capita economic output. Conversely, a larger population could depress research productivity by causing duplication of research effort.
While the Malthusian constraint seems to have governed long-run population levels fairly well for most of history, which some disruptive events such as the Mongol conquests and the Black Death, the model clearly fails to predict population dynamics in the 20th century, as population growth has slowed without any sign of ecological limits to population growth. Kremer (1993) extends his model with significant theoretical and empirical evidence that growth rates tend to decline with rising income and predicts that rising incomes should eventually cause overall population to stabilize and decline.
Kremer (1993) finds that the evidence from as far back as 1,000,000 BC is consistent with his model, in that growth rates generally rose from then to the mid-20th century. As an additional natural experiment to support the model, Kremer observes that rising sea levels around 10,000 BC caused many formerly connected areas of the world to become disconnected, as they remained until the Columbian exchange at around AD 1500. During the era of disconnection, technological progress was fastest on the largest and most populous Eurasian land mass, followed by the Americas, mainland Australia, and Tasmania. On Flinders Island, near Tasmania, technological progress ceased as the human population there became extinct.
It is unclear whether “technology” can be easily represented numerically, if the advancement of technology is best modeled as linear in the amount of research effort, and if carrying capacity at a given time is proportional to technology. All of these assumptions are made in Kremer’s (1993) base model, though he does consider ways in which each of them may be relaxed. The basic conclusion that a higher population accelerates technology growth holds unless these assumptions are far from accurate.
Population and Growth
As surved by London, Cayssials, and González (2022), many studies have sought to identify a causal relationship between population growth and economic growth, or the reverse. Most studies they survey find either a positive causal link between population and per-capita GDP, or no statistically significant relationship, while a smaller number find a negative causal link, in that population growth depresses per-capita GDP.
Garza-Rodriguez et al. (2016) consider the relationship between economic growth and population level in Mexico by applying Granger causality. Discussed more extensively in our analysis of energy and economic growth, Granger causality is a statistical tool test to determine if changes in one time series might cause changes in another by testing for correlation between lagged values of the first and the second. Garza-Rodriguez et al. find bidirectional causality between population and per-capita GDP in Mexico from 1960 to 2014.
Sibe, Chiatchoua, and Megna (2016) perform a similar causality test of panel data of population and gross domestic product for 30 countries that, as of 2013, accounted for 78% of the world’s population. The data cover the years 1960 to 2013. They find bidirectional Granger causality between GDP and population, meaning that each of them statistically causes the other.
London, Cayssials, and González (2022) consider panel data of GDP and population for 111 countries from 1960 to 2019. They find that the countries can be separated into three clusters, labeled mature, young, and transition. Of those, in the young and transition countries, there is observed bidirectional Granger causality between GDP and population. However, the causal effect from population to GDP is not observed in the mature countries.
Chang et al. (2017) offer a more mixed picture. Considering data from 1870 to 2013 and 21 countries, they find that GDP causes population growth in some, that population growth causes GDP in others, and both cause each other in still others, and in some, that there is no causal relationship in either direction. Overall, it is a minority of countries in which population growth Granger causes GDP growth. Singha and Jaman (2013) do not find a causal relationship between population and per capita GDP in India from 1950 to 2011.
Thornton (2001) does not find a causal relationship between long-run population and economic growth in Latin American countries. He observes that a mechanism by which a rising population may depress per-capita GDP is by increasing the capital to labor ratio in a country, necessitating measures to ensure full employment that decrease capital efficiency. Thirlwall (1972), testing the relationship between population and economic growth in 49 countries from 1950 to 1966, did not find a significant positive or negative impact of population growth on economic growth. Thirlwall sought to test the hypothesis of whether rapid population growth would serve as a barrier to capital formation and thus to growth.
Yao, Kinusaga, and Hamori (2013) are in the minority of studies in finding a negative causal relationship from population to GDP per capita, which they find in China from 1952 to 2007 with a vector error correction model. Using a variety of statistical methods, Furuoka (2018) comes to a similar conclusion that population exerts a negative influence on economic growth in China from 1961 to 2014.
Stockwell (1962), one of the earlier papers to study the link and worried as many researchers were at the time about the Malthusian impacts of long-term population growth, found a negative association between population growth and economic growth in 37 countries between 1957 and 1964. However, while this study finds a negative correlation, it does not convincingly demonstrate causation between population and growth.
A common weakness to most of the studies discussed above is that they focus on population and economic growth in single countries. Since ideas freely cross national borders, this approach misses the most important hypothesized mechanism by Kremer (1993) by which population might cause growth: through increasing the number of people who might develop growth-enhancing ideas.
Population Decline and Growth
World population growth rates have declined since the late 20th century and may become negative in the 21st century, which raises concerns of a significant headwind on economic growth. Lianos, Pseiridis, and Tsounis (2023) consider 19 country that saw flat or declining population levels from 2000 to 2020 and did not find a causal relationship between population growth and economic growth in these countries. They consider causality with a five year lag. The authors extrapolate their results to conclude that declining world population growth might not impede economic growth, though their extrapolation carries two weaknesses. First, as with many studies above, it neglects the Kremerian mechanism by considering only individual countries, and second, the five year lag may be insufficient to identify an economic growth-enhancing effect of population growth, at it does not allow for newly born children to enter the workforce.
References
Kremer M. “Population growth and technological change: One million BC to 1990”. The Quarterly Journal of Economics 108(3), pp. 681-716. August 1993.
Garza-Rodriguez, J., Andrade-Velasco, C., Martinez-Silva, K., Renteria-Rodriguez, F., Vallejo-Castillo, P. “The relationship between population growth and economic growth in Mexico”. Economics Bulletin 36(1), pp. 97-107. February 2016.
Sibe, J.P., Chiatchoua, C., Megne, M.N. “The long run relationship between population growth and economic growth: a panel data analysis of 30 of the most populated countries of the world”. Análisis Económico 31(77), pp. 205-218. 2016.
Malthus, T. R. An Essay on the Principle of Population. 1798.
Darrat, A.F., Al-Yousif, Y.K. “On the long-run relationship between population and economic growth: Some time series evidence for developing countries”. Eastern Economic Journal 25(3), pp. 301-313. July 1999.
London, S., Cayssials, G., González, F.A. “Population growth and economic growth: a panel causality analysis”. Asociación Argentina de Economía Política; 2022 Nov.
Chang, T., Chu, H-P., Deale, F. W., Gupta, R., Miller, S. M. “The relationship between population growth and standard-of-living growth over 1870–2013: evidence from a bootstrapped panel Granger causality test”. Empirica 44, pp. 175-201. February 2017.
Yao, W., Kinugasa, T., Hamori, S. “An empirical analysis of the relationship between economic development and population growth in China”. Applied Economics 45(33), pp. 4651-4661. November 2013.
Furuoka, F. “Is population beneficial to economic growth? An empirical study of China”. Quality & Quantity 52(1), pp. 209-225. 2018.
Singha, K., Jaman, M. S. “Nexus between population and economic growth in india: a co-integration analysis”. Scientific Journal of Pure and Applied Sciences 1(3), pp. 90-96. January 2013.
Thornton, J. “Population Growth and Economic Growth: Long-Run Evidence from Latin America”. Southern Scientific Journal 68(2), pp. 464-468. October 2001.
Thirlwall, A. P. “A Cross Section Study of Population Growth and the Growth of Output and Per Capita Income in a Production Function Framework”. The Manchester School 40(4), pp. 339-356. December 1972.
Stockwell, E. G. “The Relationship Between Population Growth and Economic Development”. American Sociological Review 27(2), pp. 250-252. April 1962.
Lianos, T. P., Pseiridis, A., Tsounis, N. “Declining population and GDP growth”. Humanities and Social Sciences Communications 10: 725. October 2023.