The paper discusses the relationship between idea-based growth models and increasing returns to scale. Ideas are nonrivalrous, meaning their use by one person does not prevent others from using them, leading to a tight link between idea-based growth models and increasing returns to scale. The paper reviews various models, including those by Romer, Grossman and Helpman, and Aghion and Howitt, which show that population growth can lead to increased per capita income growth. However, this prediction is at odds with empirical evidence. Subsequent models, such as those by Jones, Kortum, and Segerstrom, adjust the models to show that long-run per capita growth is proportional to population growth, rather than its rate. More recent models, including those by Young, Peretto, Aghion, and Howitt, propose a method to eliminate the growth effect of scale by introducing a second dimension to the models. These models show that an increase in scale does not affect growth, as the number of products increases proportionally. The paper concludes that the key difference between models lies in how they handle the relationship between scale and growth, with some models showing that changes in policy can affect long-run growth rates. The paper also highlights the importance of empirical work to determine which model best describes economic growth.The paper discusses the relationship between idea-based growth models and increasing returns to scale. Ideas are nonrivalrous, meaning their use by one person does not prevent others from using them, leading to a tight link between idea-based growth models and increasing returns to scale. The paper reviews various models, including those by Romer, Grossman and Helpman, and Aghion and Howitt, which show that population growth can lead to increased per capita income growth. However, this prediction is at odds with empirical evidence. Subsequent models, such as those by Jones, Kortum, and Segerstrom, adjust the models to show that long-run per capita growth is proportional to population growth, rather than its rate. More recent models, including those by Young, Peretto, Aghion, and Howitt, propose a method to eliminate the growth effect of scale by introducing a second dimension to the models. These models show that an increase in scale does not affect growth, as the number of products increases proportionally. The paper concludes that the key difference between models lies in how they handle the relationship between scale and growth, with some models showing that changes in policy can affect long-run growth rates. The paper also highlights the importance of empirical work to determine which model best describes economic growth.