This is Lecture 6 of the course ECON 85600, “Inequality, Economic Opportunity, and Public Policy,” that my class and I are now conducting online. You are welcome to participate, and can review all the course materials at https://milescorak.com/equality-of-opportunity/teaching/ .

Warning: this is likely to interest social scientists in sociology, economics, or other fields, interested in developing a specialized knowledge of the subject!

This lecture examines the influential theoretical model of intergenerational mobility published by Gary Becker and Nigel Tomes in 1986, offering an overview of the theory, some predictions it makes, and some directions it suggests for future research.

We learn in this lecture about the different forces that come together to determine the degree of intergenerational mobility, and how they might help us in understanding differences across time and space. The model more precisely defines how the family, the market, and the state come together to determine the degree of regression to the mean in parent and child incomes.

Be certain to leave a comment, question, or concern in the “What do you think?” box at the very bottom of this post. Frame your feedback in a way that is of benefit to the learning environment for all students, and don’t hesitate to raise a question of clarification if you don’t understand an issue.

As a bonus, you can also watch Gary Becker lecture on this topic!

14 thoughts on “Intergenerational mobility in theory”

When you talked about “Endowment”, did you mean transmission of ability? For instance, “my parents were smart and hence I am smart” or it was about wealth transfer? I guess it is the first one but I wanted to get the concept clear.

It does not refer to a financial transfer, but something broadly put like “ability”. But you have to appreciate the quote that I took from the Becker and Tomes paper. They are quite agnostic. And it is a very wide-ranging catch-all that could refer to genetically transmitted traits at one extreme, to other environmental factors like family connections at the other extreme. The point, I believe, is to make a distinction between those things that influence a child’s earnings capacity through monetary investment—human capital—and everything else.

The workhorse model that we see here assumes that all the agents are same. Is it interesting to modify the model using heterogeneous agents or it would not matter?

It depends along what lines you want to model the heterogeneity. One direction is to look at differences in parental altruism, and Mulligan pursues this in his 1997 University of Chicago book. Do you have particular ideas?

That is exactly what I had in mind, let some parents have altruistic preferences and some with not. I will go back and look at Mulligan’s approach. Thank you for the reply, prof. The lecture was great.

Hi Miles-
This has been an interesting lecture, and it’s bringing up questions about the regression to the mean model. Is regression to the mean actually observed empirically, or is it a theory that would potentially apply, but only in the absence of other environmental factors such as space or government policies (as you mentioned in the lecture)? I’m thinking about the role of grandparents and the finding that grandparents actually have a positive impact on children’s mobility. Does this slow inevitable regression to the mean, or is it something that may actually disrupt that trajectory altogether?

If I understand the question, and correct me if I am mistaken, we can think of regression to the mean in two ways. Up to now we have been thinking of it, and the all important intergenerational elasticity, entirely in a descriptive sense. As a statistic that gives us an overall sense of the degree of relative mobility.

Now we are making a transition in our reading list toward starting to understand the underlying process that determines the degree of mobility. So in this sense we are trying to rely on theory to help us frame those causal processes that might allow us to understand differences across time and space in the degree of intergenerational mobility. So our modeling has to be more subtle, and we need to recognize how far this workhorse model has to carry us, its testable implications, and questions that are beyond its scope. That is what I was trying to suggest toward the end of the lecture, highlighting for example the need for a more subtle understanding of grandparents.

This is helpful. I suppose my question is: do these more subtle models still overall reflect a regression to the mean model? I recognize that we are digging into the causal mechanisms that underly intergenerational elasticity/mobility, but are we taking these into account within a larger framework of understanding that intergenerational elasticity will regress to the mean in just a few generations? Or are these mechanisms that would challenge and possibly upend that pattern?

Hello Professor. My question is:
Are there also models that include annuity payment system and IGM together, so that based on that systems we can make implications about what kind of policy leads to how much IGM? My regards

I am struggling to understand, in slide 16, where can we find the relationship between intergenerational mobility and cross-sectional inequality. That it, I can see that function (10) let’s us know the elasticity of a child income to their parent and grandparent income, dues providing a degree of intergenerational mobility. Function (10) is speaking only about family i. Wouldn’t we need some more families to take out any insight about cross-sectional inequality? What do we mean by that in this context.

Also, in the 18th slide, where we read “the finding is that grandparent earnings figure positively” . Is that controlling for parents income, the way equation (10) does, or it is a direct elasticity child-grandparent?

Thank you for pulling this together. I think it worked well. Though I have no experience in online classes to be able to provide a very informed feedback.

I appreciated your point about the impact of progressive public investment, but did not understand how the equation (14) captured the degree of progressivity. Can you explain? Also, how is that degree measured?

A question I have from the lecture concerns the non-linear predictions introduced around 40:00. If the Y axis here is child’s income, the way that the curve levels off at higher parental income seems to suggest that once parents do not face credit constraints, then the investments they choose to make are boosting the chances of their children less than they would be if they were still constrained (the straight line). Is this because the perfect credit market allows for more equality among more wealthy families? Or, am I missing an additional piece here?

Looking at the presentation and the map from the World Bank report on Slide 8, I wonder about the implications of the relative value of educational IGM vs. income IGM. In the countries like Russia where educational IGM is higher than income IGM, does that generate a disincentive for education since you could have a good chance of getting a higher degree but still have a low chance of getting a higher income? Or does high educational IGM still give a society a sense of mobility if return to education is significant net of the other forces holding down income mobility?

I appreciated the point about the impact of progressive public investment as a supplement to parental investment, however, I didn’t understand how equation 14 illustrated the degree of progressivity. Can you explain? Also, how is that degree calculated?

I am curious about whether there are any overlapping generations models where human capital function type (High or Low) of the child is unknown to the parents and how that would end up affecting the results with perfect and imperfect capital markets. I feel like an imperfect capital market might somehow actually be helpful in that case.

When you talked about “Endowment”, did you mean transmission of ability? For instance, “my parents were smart and hence I am smart” or it was about wealth transfer? I guess it is the first one but I wanted to get the concept clear.

It does not refer to a financial transfer, but something broadly put like “ability”. But you have to appreciate the quote that I took from the Becker and Tomes paper. They are quite agnostic. And it is a very wide-ranging catch-all that could refer to genetically transmitted traits at one extreme, to other environmental factors like family connections at the other extreme. The point, I believe, is to make a distinction between those things that influence a child’s earnings capacity through monetary investment—human capital—and everything else.

The workhorse model that we see here assumes that all the agents are same. Is it interesting to modify the model using heterogeneous agents or it would not matter?

It depends along what lines you want to model the heterogeneity. One direction is to look at differences in parental altruism, and Mulligan pursues this in his 1997 University of Chicago book. Do you have particular ideas?

That is exactly what I had in mind, let some parents have altruistic preferences and some with not. I will go back and look at Mulligan’s approach. Thank you for the reply, prof. The lecture was great.

Hi Miles-

This has been an interesting lecture, and it’s bringing up questions about the regression to the mean model. Is regression to the mean actually observed empirically, or is it a theory that would potentially apply, but only in the absence of other environmental factors such as space or government policies (as you mentioned in the lecture)? I’m thinking about the role of grandparents and the finding that grandparents actually have a positive impact on children’s mobility. Does this slow inevitable regression to the mean, or is it something that may actually disrupt that trajectory altogether?

If I understand the question, and correct me if I am mistaken, we can think of regression to the mean in two ways. Up to now we have been thinking of it, and the all important intergenerational elasticity, entirely in a descriptive sense. As a statistic that gives us an overall sense of the degree of relative mobility.

Now we are making a transition in our reading list toward starting to understand the underlying process that determines the degree of mobility. So in this sense we are trying to rely on theory to help us frame those causal processes that might allow us to understand differences across time and space in the degree of intergenerational mobility. So our modeling has to be more subtle, and we need to recognize how far this workhorse model has to carry us, its testable implications, and questions that are beyond its scope. That is what I was trying to suggest toward the end of the lecture, highlighting for example the need for a more subtle understanding of grandparents.

Does this help?

This is helpful. I suppose my question is: do these more subtle models still overall reflect a regression to the mean model? I recognize that we are digging into the causal mechanisms that underly intergenerational elasticity/mobility, but are we taking these into account within a larger framework of understanding that intergenerational elasticity will regress to the mean in just a few generations? Or are these mechanisms that would challenge and possibly upend that pattern?

Hello Professor. My question is:

Are there also models that include annuity payment system and IGM together, so that based on that systems we can make implications about what kind of policy leads to how much IGM? My regards

Hi,

Hope everyone is safe.

I am struggling to understand, in slide 16, where can we find the relationship between intergenerational mobility and cross-sectional inequality. That it, I can see that function (10) let’s us know the elasticity of a child income to their parent and grandparent income, dues providing a degree of intergenerational mobility. Function (10) is speaking only about family i. Wouldn’t we need some more families to take out any insight about cross-sectional inequality? What do we mean by that in this context.

Also, in the 18th slide, where we read “the finding is that grandparent earnings figure positively” . Is that controlling for parents income, the way equation (10) does, or it is a direct elasticity child-grandparent?

Thank you for pulling this together. I think it worked well. Though I have no experience in online classes to be able to provide a very informed feedback.

I appreciated your point about the impact of progressive public investment, but did not understand how the equation (14) captured the degree of progressivity. Can you explain? Also, how is that degree measured?

A question I have from the lecture concerns the non-linear predictions introduced around 40:00. If the Y axis here is child’s income, the way that the curve levels off at higher parental income seems to suggest that once parents do not face credit constraints, then the investments they choose to make are boosting the chances of their children less than they would be if they were still constrained (the straight line). Is this because the perfect credit market allows for more equality among more wealthy families? Or, am I missing an additional piece here?

Looking at the presentation and the map from the World Bank report on Slide 8, I wonder about the implications of the relative value of educational IGM vs. income IGM. In the countries like Russia where educational IGM is higher than income IGM, does that generate a disincentive for education since you could have a good chance of getting a higher degree but still have a low chance of getting a higher income? Or does high educational IGM still give a society a sense of mobility if return to education is significant net of the other forces holding down income mobility?

I appreciated the point about the impact of progressive public investment as a supplement to parental investment, however, I didn’t understand how equation 14 illustrated the degree of progressivity. Can you explain? Also, how is that degree calculated?

Hello Professor,

I am curious about whether there are any overlapping generations models where human capital function type (High or Low) of the child is unknown to the parents and how that would end up affecting the results with perfect and imperfect capital markets. I feel like an imperfect capital market might somehow actually be helpful in that case.