Demographic Change and Inequality Summer School

Course Overview

Demographic change unfolds its main dynamics over the next 20 years by substantially falling working-age population ratios and increasing old-age dependency ratios leading to a relative scarcity of labor and a relative abundance of capital in economies. We need to understand the economic consequences of this Mega-Trend. This is the main objective of this course.

At the end of the course, you will have learned:

• how to solve analytically tractable models in a general equilibrium
• how to use these models to address important economic policy questions related to the Mega-Trend demographic change
• how to implement (much) more complex models on the computer

You will exit the class with a handbook of analytical solutions, related cooking recipes, and numerous computer codes for models in partial and general equilibrium.

Course Outline

Lecture 1: Two-period models of deterministic consumption and savings in partial equilibrium. Extension to income risk

Lecture 2: Textbook 2-period OLG model. Discussion of dynamics induced by demographic trends and policy reforms. Extension of 2-period OLG model with income risk. Discussion of policy reforms related to insurance of risk and insurance-efficiency trade-offs.

Lecture 3: Multi-period models of consumption and savings in partial equilibrium. Extension of multi-period models by borrowing constraints, endogenous labor supply, and bequests.

Lecture 4: Extension of multi-period models to risk and numerical solution methods by applied dynamic programming

Lecture 5: General equilibrium models with ex-ante and ex-post heterogeneity induced by idiosyncratic income risk.

References

Aguiar, Mark and Erik Hurst, 2005. Consumption versus Expenditure, Journal of Political Economy, 113(5), 919-948.

Aiyagari, S. Rao, 1987: Intergenerational linkages and government budget policies, Federal Reserve Bank of Minneapolis Quarterly Review.

Aubuchon, Craig P., Conesa, Juan Carlos and Carlos Garriga, 2011, A Primer on Social Security Systems and - Reforms, Federal Reserve Bank of St Louis Review 93, 19-36, 2011.

Börsch-Supan, A., A. Ludwig, and J. Winter, 2006: Ageing, Pension Reform and Capital Flows: A Multi‐Country Simulation Model, Economica 73 (292), 625-658.

Busch, C., D. Krueger, I. Popova, Z. Iftihkar, 2020: Should Germany Have Built a New Wall? Macroeconomic Lessons from the 2015-18 Refugee Wave, Journal of Monetary Economics, 113, pp. 28-55.

Diamond, Peter, 1965: National debt in a Neoclassical growth model, American Economic Review, 55, 5, 1126-1150.

Deaton, A. and C. Paxson, 1994: Intertemporal Choice and Inequality, Journal of Political Economy, Vol. 102, No. 3, pp. 437-467

De Nardi, M., 2015: Quantitative Models of Wealth Inequality: A Survey, NBER working paper No. 21106.

Diamond, P. and E. Saez, 2011: The Case for a Progressive Tax: From Basic Research to Policy Recommendations. Journal of Economic Perspectives, 25(4): 165-90.

Guner, N., Kaygusuz, R. and G. Ventura, 2014: Income taxation of U.S. households: Facts and parametric estimates, Review of Economic Dynamics October, Volume 17, No 4, 559–581.

Harenberg, D. and A. Ludwig, 2019: Idiosyncratic Risk, Aggregate Risk, and the Welfare Effects of Social Security, International Economic Review, 60(2), 661-692.

Heathcote, J., K. Storesletten and G. Violante 2009, Quantitative Macroeconomics with Heterogeneous Households, Annual Review of Economics 1: 319-354.

Heathcote, J., K. Storesletten, and G. Violante, 2017: Optimal Tax Progressivity: An Analytical Framework, Quarterly Journal of Economics

Krueger, D. and A. Ludwig, 2016: On the optimal provision of social insurance: Progressive taxation versus eduation subsidies in general equilibrium, Journal of Monetary Economics, Volume 77, 72–98

Krueger, D., A. Ludwig and S. Villalvazo, 2021: Optimal Taxes on Capital in the OLG Model with Uninsurable Idiosyncratic Income Risk, Journal of Public Economics, 201, Optimal taxes on capital in the OLG model with uninsurable idiosyncratic income risk .

Krueger, D. and A. Ludwig, 2007: On the Consequences of Demographic Change for Rates of Return to Capital, and the Distribution of Wealth and Welfare (with Dirk Krueger), Journal of Monetary Economics, 54(1), 49-87.

Krueger, D., K. Mitman and F. Perri, 2016: Macroeconomics and Household Heterogeneity, in: J.B. Taylor and H. Uhlig (ed.) Handbook of Macroeconomics,, edition 1, volume 2, pp. 843-921.

Ljungqvist, L., and T. Sargent, 2012: Recursive Macroeconomic Theory, MIT press. 

Ludwig, A., 2014: Heterogenous Agent models, Lecture Notes.

Ludwig, A., 2021, 2022: Handouts.

Ludwig, A., T. Schelkle and E. Vogel, 2012: Demographic Change, Human Capital and Welfare, Review of Economic Dynamics, 15(1), 94-107, 2012.

Software / Hardware

Matlab, Python. In order to participate in practical sessions, you must bring your own portable computer. 

About the Instructor

Alexander Ludwig (Ph.D. in 2005, University of Mannheim) is professor for Public Finance and Macroeconomics Dynamics at Goethe University Frankfurt, director of ICIR at Goethe University and Research Fellow at CEPR. Prior to joining the Goethe University in 2014, he was Professor of Macroeconomics at University of Cologne (since 2009). He has studied the effects of demographic change on growth, on the inter- and intra-generational distribution of wealth and welfare, and on the optimal design of social insurance schemes in numerous articles. His work has been published in the Journal of Monetary Economics, the International Economic Review and the Journal of Public Economics, and other leading journals and has received more than 4000 Google Scholar citations.

Course Overview

This component of the course we will be divided in two parts.

First, we will cover a number of quantitative papers on how labor markets and the assignment and formation of the human capital of workers shape inequality and macroeconomic outcomes. Here, we will review some mathematical tools (extreme value distributions) that allows for clean analytical solutions for individual decisions and for their aggregation. With this background in place, we will analyze a number of papers that use Roy static models of the labor markets to quantitatively explore inequality and the contribution of human capital on aggregate income. We will explore a number of more recent –and still ongoing—research that extends those models to dynamic settings and explore the life-cycle dynamics of workers. Computational and quantitative aspects will be center stage in the course and in its evaluation.

Second, we will cover a number of papers related to education choices, especially but not exclusively, related to college decisions. Here, we will integrate the elements developed in the first part of the course, which will be helpful for developing an equilibrium model for the return to college education but will also explore additional aspects such as geographic differences, family background and pre-college family decisions and demographic changes.

Prerequisites

Basic dynamic programming

Course Outline

Lecture 1: Overview of the Facts: Trends in Inequality: Labor Market Polarization. Inequality and Social Mobility. Education and Occupations. Automation and Globalization. A Static Roy Model in General Equilibrium. 

Lecture 2: Dynamic Roy Models. Occupation switches over the life-cycle. Labor Market Profiles of Different Cohorts. Demographics, Technology and Discrimination Changes. Applications for Growth Models.

Lecture 3: General Equilibrium Quantitative Implementation. 

Lecture 4: Heterogeneity, On-the-Job-Training and Lifecycles. Cross-cohort and cross-country implications.

Lecture 5: Families, Neighborhoods and Education Outcomes. College Education and Social Mobility. The Great Gatsby Curve. Social Mobility and the transition from Malthus to- Solow or to pseudo-Malthus.

References

I. Models of Human Capital Assignment & Inequality

Burstein, A., Morales, E. and Vogel, J. (2019) “Changes in between-group inequality: computers, occupations, and international trade.” AEJ Macro.

Costinot, A. and Vogel, J. (2010) “Matching and Inequality in the World Economy.” Journal of Political Economy, vol. 118, no. 4.

Costinot, A. and Vogel, J. "Beyond Ricardo: Assignment Models in International Trade" Annual Review of Economics, 2015, vol. 7, pp. 31-62

Dvorkin, M., Monge-Naranjo, A., (2019) “Occupation Mobility, Human Capital and the Aggregate Consequences of Task-Biased Innovations.”

Hsieh, C., Hurst, E., Jones, C., and Klenow, P. (2019) “The Allocation of Talent and U.S. Economic Growth” Econometrica, 2019

Lagakos, D., Waugh, M. (2013). "Selection, Agriculture, and Cross-Country Productivity Differences." American Economic Review, 103 (2): 948-80.

II. Background and Related Literature

Acemoğlu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In Handbook of labor economics (Vol. 4, pp. 1043{1171). Elsevier.

Acemoglu, D., & Restrepo, P. (2018). The race between man and machine: Implications of technology for growth, factor shares, and employment. American Economic Review, 108 (6), 1488{1542.

Acemoglu, D., & Restrepo, P. (2019). Robots and jobs: Evidence from U.S. labor markets. Journal of Political Economy, forthcoming.

Adao, R., Beraja, M., & Pandalai-Nayar, N. (2018). Skill-biased technological transitions. Working Paper.

Allen, R. (2009) “Engels’ pause: Technical change, capital accumulation, and inequality in the british industrial revolution” Explorations in Economic History, 2009.

Autor, D., & Dorn, D. (2013). The growth of low-skill service jobs and the polarization of the U.S. labor market. American Economic Review, 103 (5).

Autor, D., Katz, L. F., & Kearney, M. S. (2006). The polarization of the us labor market. American Economic Review, 96 (2), 189{194.

Autor, D., Levy, F., & Murnane, R. J. (2003). The Skill Content of Recent Technological Change: An Empirical Exploration. The Quarterly Journal of Economics, 118 (4), 1279-1333.

Caliendo, L., Dvorkin, M., & Parro, F. (2019). Trade and labor market dynamics: General equilibrium analysis of the China trade shock. Econometrica, 87 (3), 741{835.

Caselli, F., and Ciccone, A. 2019. "The Human Capital Stock: A Generalized Approach: Comment." American Economic Review, 109 (3): 1155-74.

Caselli, F. “Accounting for Cross-Country Income Differences.” 2005. Handbook of Economic Growth, Volume 1A. Edited by Philippe Aghion and Steven N. Durlauf, 2005 Elsevier B.V.

Cortes, M., Nekarda, C., Jaimovich, N., & Siu, H. (2016). The micro and macro of disappearing routine jobs: A flows approach. Working Paper.

Doms, M., & Lewis, E. (2006). Labor supply and personal computer adoption. Federal Reserve Bank of Philadelphia, Working Paper.

Eaton, J., & Kortum, S. (2002). Technology, geography, and trade. Econometrica, 70 (5), 1741-1779.

Foote, C. L., & Ryan, R. W. (2015). Labor-market polarization over the business cycle. NBER Macroeconomics Annual, 29 (1), 371-413.

Galle, S., RodrIguez-Clare, A., & Yi, M. (2017). Slicing the pie: Quantifying the aggregate and distributional effects of trade. NBER Working Paper.

Goos, M., & Manning, A. (2007). Lousy and lovely jobs: The rising polarization of work in britain. The Review of Economics and Statistics, 89 (1), 118-133.

Goos, M., Manning, A., & Salomons, A. (2014, August). Explaining job polarization: Routine biased technological change and offshoring. American Economic Review, 104 (8), 2509-26.

Greenwood, J., Hercowitz, Z., & Krusell, P. (1997). Long-run implications of investment-specific technological change. American Economic Review, 87 (3), 342-62.

Guvenen, F., Kuruscu, B., Tanaka, S., & Wiczer, D. (2019). The micro and macro of disappearing routine jobs: A Flows approach. Working Paper.

Heathcote, J., Perri, F., & Violante, G. L. (2010). Unequal we stand: An empirical analysis of economic inequality in the united states, 1967{2006. Review of Economic dynamics, 13 (1),15-51.

Hsieh, C.-T., Hurst, E., Jones, C. I., & Klenow, P. J. (2019). The allocation of talent and us economic growth. Econometrica, 87 (5), 1439-1474.

Jones, B. 2014. “The Human Capital Stock: A Generalized Approach.” American Economic Review. 104(11)

Kambourov, G., & Manovskii, I. (2008). Rising occupational and industry mobility in the United States: 1968{97. International Economic Review, 49 (1), 41-79.

Kambourov, G., & Manovskii, I. (2009). Occupational mobility and wage inequality. The Review of Economic Studies, 76 (2), 731-759.

Kambourov, G., & Manovskii, I. (2013). A cautionary note on using (March) Current Population Survey and Panel Study of Income Dynamics data to study worker mobility. Macroeconomic Dynamics, 17 (1), 172-194.

Krusell, P., Ohanian, L., Rios-Rull, J.-V., & Violante, G. (2000). Capital-skill complementarity and inequality: A macroeconomic analysis. Econometrica, 68 (5), 1029-1053.

Lagakos, D., Moll, B., Porzio, T., Qian, N., & Schoellman, T. (2018). Life cycle wage growth across countries. Journal of Political Economy, 126 (2), 797-849.

Lillard, L. A., & Willis, R. J. (1978). Dynamic aspects of earning mobility. Econometrica, 985-1012.

III. Education, Inequality and Social Mobility 

Athreya, Kartik, and Janice Eberly. 2021. "Risk, the College Premium, and Aggregate Human Capital Investment." American Economic Journal: Macroeconomics, 13 (2): 168-213. Working Paper version:

https://www.richmondfed.org/media/RichmondFedOrg/publications/research/working_papers/2013/pdf/wp13-02r.pdf

Capelle, Damien. “The Great Gatsby Goes to College: Tuition, Inequality and Intergenerational Mobility in the U.S.”

https://damiencapelle.com/wp-content/uploads/2020/06/Capelle_GreatGatsby_submitted.pdf

Raj Chetty, John Friedman, Emmanuel Saez, Nicholas Turner, Danny Yagan. “Income Segregation and Intergenerational Mobility Across Colleges in the United States.” Quarterly Journal Of Economics, Volume 135, Issue 3, August 2020, Pages 1567–1633, | February 2020

Raj Chetty, Nathaniel Hendren “The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates” Quarterly Journal Of Economics, 133(3): 1163-1228, 2018

Raj Chetty, Nathaniel Hendren “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects” Quarterly Journal Of Economics, 133(3): 1163-1228, 2018.

Deming, David J. And Kadeem Noray. “Earnings Dynamics, Changing Job Skills, And Stem Careers” The Quarterly Journal of Economics (2020), 1965–2005. doi:10.1093/qje/qjaa021

Lochner, Lance and Alexander Monge-Naranjo. “Student Loans and Repayment:Theory, Evidence, and Policy” 2016. Handbook of the Economics of Education 5, 397-478

https://economics.uwo.ca/people/lochner_docs/StudentLoansRepayment.pdf

Lochner, Lance and Alexander Monge-Naranjo. “Credit Constraints in Education.” Annual Review of Economics. Vol. 4:225-256 https://www.annualreviews.org/doi/abs/10.1146/annurev-economics-080511-110920

Software / Hardware

Matlab. Julia and Python are allowed as alternatives.

About the Instructor

Alexander Monge-Naranjo (Ph.D. University of Chicago, 1999) is a Professor of Economics at the European University Institute on 2021. He has also held positions at Northwestern University, Penn State, INCAE Business School and visiting positions at the University of Tokyo, Goethe University in Frankfurt and Universidad de Chile. His research is on human capital and its role in macroeconomic outcomes and income distribution, including structural transformation, misallocation of resources, growth and international trade and investment. His work has been published in Econometrica, American Economic Review, Quarterly Journal of Economics and other leading journals.