Endogenous fertility and human capital in a Schumpeterian growth model

Chu, Angus C.; Cozzi, Guido; Liao, Chih Hsing

doi:10.1007/s00148-012-0433-9

Cited by 46 publications

(41 citation statements)

References 39 publications

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“…However, there is disagreement on what this parameter should be. In particular, Jones and Williams (2000) argue that it is around 0.75, while Chu et al (2013) use a value of 0.2. These two papers however rely on thought experiments to justify their choices.…”

Section: Estimation Results: 1960 -2010mentioning

confidence: 99%

“…As mentioned in the introduction, the standard Aghion and Howitt (1992) framework implies a scale effect by virtue of which a larger population implies a large equilibrium growth rate of the economy, which is at odds with empirical evidence on modern growth. Instead we work with the scale-invariant formulation proposed by Chu et al (2013), where λ t,j is specified as a decreasing function of the scale of the economy. In particular, we define…”

Section: Innovations and Technological Progressmentioning

confidence: 99%

“…3 This is important in a setting with endogenous population, as it would imply that accumulating population would increase long-run technology and income growth. Following Chu et al (2013), we 'neutralise' the scale effect by making the growth rate of TFP a function of the share of labour allocated to R&D. This implies that long run growth can occur without the need for the population to grow. 4 To fix ideas, we start with a simple illustration of the theoretical mechanism underlying fertility and land conversion decisions in our model.…”

Section: Introductionmentioning

confidence: 99%

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Global Population Growth, Technology, and Malthusian Constraints: A Quantitative Growth Theoretic Perspective

Lanz

Dietz

Swanson

2017

Int Economic Review

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The MIT Joint Program on the Science and Policy of Global Change combines cutting-edge scientific research with independent policy analysis to provide a solid foundation for the public and private decisions needed to mitigate and adapt to unavoidable global environmental changes. Being data-driven, the Program uses extensive Earth system and economic data and models to produce quantitative analysis and predictions of the risks of climate change and the challenges of limiting human influence on the environment-essential knowledge for the international dialogue toward a global response to climate change.To this end, the Program brings together an interdisciplinary group from two established MIT research centers: the Center for Global Change Science (CGCS) and the Center for Energy and Environmental Policy Research (CEEPR). These two centers-along with collaborators from the Marine Biology Laboratory (MBL) at Woods Hole and short-and longterm visitors-provide the united vision needed to solve global challenges.At the heart of much of the Program's work lies MIT's Integrated Global System Model. Through this integrated model, the Program seeks to: discover new interactions among natural and human climate system components; objectively assess uncertainty in economic and climate projections; critically and quantitatively analyze environmental management and policy proposals; understand complex connections among the many forces that will shape our future; and improve methods to model, monitor and verify greenhouse gas emissions and climatic impacts.This reprint is one of a series intended to communicate research results and improve public understanding of global environment and energy challenges, thereby contributing to informed debate about climate change and the economic and social implications of policy alternatives. AbstractWe structurally estimate a two-sector Schumpeterian growth model with endogenous population and finite land reserves to study the long run evolution of global population, technological progress and the demand for food. The estimated model closely replicates trajectories for world population, GDP, sectoral productivity growth and crop land area from 1960 to 2010. Projections from 2010 onwards show a slowdown of technological progress, and because it is a key determinant of fertility costs, significant population growth. By 2100 global population reaches 12 billion and agricultural production doubles, but the land constraint does not bind because of capital investment and technological progress.

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Section: Estimation Results: 1960 -2010mentioning

confidence: 99%

Section: Innovations and Technological Progressmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Global Population Growth, Technology, and Malthusian Constraints: A Quantitative Growth Theoretic Perspective

Lanz

Dietz

Swanson

2017

Int Economic Review

View full text Add to dashboard Cite

show abstract

“…Hock and Weil (2012) take account of age structure. There are other formal models on determinants of fertility (Barro and Becker, 1989;Becker et al, 1990;Bosi and Seegmuller, 2012;Chu et al, 2013). There are also many studies on economic growth and mortality rate (e.g., (Robinson and Srinivasan, 1997;Chakraborty, 2004;Hazan and Zoabi, 2006;Bhattacharya and Qiao, 2007;Lancia and Prarolo, 2012) Life expectancy is influenced by factors such as health care, human capital level and environment (e.g., (Schultz, 1993;1998;Boucekkine et al, 2002;Cervellati and Sunde, 2005;Balestra and Dottori, 2012;Varvarigos and Zakaria, 2013)).…”

Section: Asian Journal Of Economic Modellingmentioning

confidence: 99%

“…Insert (5) We now model how the household makes decision on the number of children. Following Barro and Becker (1989) who assume that the parents' utility is dependent on the number of children, we include birth rate into utility function (see also, Chu et al (2013); Razin and Ben-Zion (1975); Yip and Zhang (1997)). Rather than the traditional Ramsey approach, we use the utility function proposed by Zhang (1993).…”

Section: Consumer Behaviorsmentioning

confidence: 99%