Alessandra Fogli on Social Context and Macroeconomic Outcomes
Alessandra Fogli is a Monetary Advisor and Assistant Director at the Research Department of the Federal Reserve Bank of Minneapolis. Her research interests lie at the intersection of macroeconomics and labor economics. Fogli’s RePEc/IDEAS profile.
The social context is an important determinant of economic outcomes: family, school, neighborhood and society at large significantly influence individual decision making. Standard economic models for the most part abstract from the social context: they are populated by atomistic individuals, who are endowed with homogeneous and exogenously given preferences, share common knowledge about past events, and interact through anonymous markets.
In my research I explicitly model the social context and investigate how and to what extent it affects aggregate economic outcomes. I combine theoretical models and a rich variety of micro data to identify the mechanisms through which local social interactions shape individual preferences and beliefs and affect the return from individual investment. Individuals in different social contexts interact with different people, hold different beliefs about relevant payoffs, and face different challenges and opportunities. Through these channels, the social context significantly affects aggregate outcomes such as labor force participation, human capital investment, and technology adoption. In turn, aggregate outcomes feed back into the social context: family structure, neighborhood composition, and individual friends’ networks evolve endogenously in response to the aggregate economy.
Below I focus on three key macro outcomes: female labor force participation, economic growth, and income inequality. I show that the structure of individual interactions at the micro level plays a crucial role in shaping the development of these outcomes over time and across space. These macro aggregates, in turn, affect the evolution of the social context.
Social Norms and Female Labor Force Participation
The dramatic rise in female labor force participation in the United States has been one of the most profound economic transformations of the last century. Many theories of this phenomenon have been proposed. Some of them emphasize the role played by market prices and technological factors (household durables reduced the time required for household chores in Greenwood, Seshadri, and Yorukoglu (2005):, the pill allowed to better control fertility according to Goldin and Katz (2002) and the baby formula freed up women from breast-feeding in Albanesi, and Olivetti (2016)); others focus on the role played by policies and institutions (less gender discrimination in the workplace according to Jones, Manuelli, and McGrattan (2015), more affordable childcare options in Attanasio, Low, and Sanchez-Marcos (2008), the rise of the service sector and the availability of jobs better suited to women as described in Goldin(1990)). All of them, however, abstract from the role played by preferences and beliefs in womens’ decision to work outside the home. In three of my papers I investigate the role played by cultural factors and develop both an empirical strategy and theoretical tools useful to identify their contribution and to quantify their effects.
1. The Role of the Country of Origin: an Empirical Investigation
Fernandez and Fogli (2009) presents an empirical investigation of the relationship between culture and labor supply decisions. We are primarily interested in differences in culture which we define as systematic differences in preferences and beliefs across either socially or geographically differentiated groups. The main challenge of any cultural analysis is how to disentangle the effects of preferences and beliefs from the effects of markets and institutions.
In this paper we propose an empirical strategy (which we define the “epidemiological approach”) to identify the effects of culture that exploits the difference in the “portability” of culture relative to economic and institutional conditions. When individuals emigrate, they may take some aspects of their culture with them and transmit them to their children, but they live in the economic and formal institutional environment of the host country. This suggests that studying immigrants or their descendants may be a useful strategy for isolating some aspects of culture. Following this logic, we study the work and fertility outcomes of second-generation American women. These women, born and raised in the United States, face the same markets and institutions but they potentially differ in their cultural heritage as reflected in their parents’ country of origin. Central to our approach is the use of a quantitative variable as a proxy for culture. In particular, we use past values of female labor force participation (LFP) as cultural proxies. This aggregate variable reflects the market work decisions of women and hence captures both the social context and the economic and institutional environment in the country of ancestry. However, and this is key, if this aggregate variable has explanatory power for the variation in work outcomes of second-generation American women, even after controlling for their individual economic attributes, only the cultural component of this variable can be responsible for the correlation. The economic and (formal) institutional conditions of the country of ancestry should no longer be relevant for second-generation American women (as neither the country nor even the time period is the same), whereas the preferences and beliefs embodied in these variables may still matter if parents and/or neighborhood transmitted them to the next generation.
We find that, ceteris paribus, women whose ancestry is from higher female LFP countries work more, even after control for a vast array of individual characteristics. To address the possibility that systematic differences in the intergenerational transmission of unobserved human capital play a role in our results, we investigate women’s wages: if the significance of our cultural proxy is being driven by unobserved human capital, then we expect it to be reflected in women’s productivity and to help explain variation in the wage rate. We run standard Mincer regressions with and without selection, and show that our cultural proxy does not help predict women’s wages.
A married woman’s decision is also likely to depend on her husband’s preferences. Whose culture is more important in deciding a married woman’s work behavior, her own or her husband’s? We show that the cultural proxies of both spouses play an important role, though perhaps surprisingly, the husband’s culture appears to be, if anything, more important in driving his wife’s work outcomes. Lastly, we show that there appears to be a social component to the behavior we study. In particular, we show that the impact of the cultural proxies is larger for those ancestries that show a greater tendency to cluster in the same neighborhoods.
The role of the family and that of social networks are at the center of the analysis in the other two papers I wrote on this topic.
2. The Role of the Family: a Theory of Social Norms
In Fernandez, Fogli and Olivetti (2004) we develop a theory in which the family is the key determinant of preferences. We argue that a significant determinant of the gradual but steady increase in women’s involvement in the formal labor market was the increasing number of men who, over time, grew up with a different family model—one in which their mother worked. Using several data sets, we show that the probability that a man’s wife works is positively and significantly correlated with whether his mother worked, even after controlling for many other background characteristics of husband and wife. Depending on the definition of working mother used, we find that, ceteris paribus, having a working mother increases the probability that a man’s wife works between 24 to 32 percentage points. Growing up with a working mother, we suggest, either influenced a man’s preferences for a working wife or directly made him a better partner (say, by increasing his ability to cooperate and be productive in household work) for a working woman. The presence of this different type of man, in turn, made investing in market skills and becoming a working woman more attractive. We develop a dynamic theory in which social norms and women’s labor supply affect each other and evolve endogenously over time: as the number of working mothers increased, so did the proportion of men raised with this different family model, which then helped to increase the relative supply of working women of the following generation. In this way, women who worked set an example for their sons, and thus made it easier for the next generation of women to follow in their footsteps. Thus, the gradual transformation of the family—long considered a source of transmission of moral, religious, and cultural beliefs—itself acted as a propagation mechanism of change in women’s role.
We investigate the dynamic implications of our theory by exploring the intergenerational consequences of an exogenous shock in the proportion of men brought up by working mothers. We follow Acemoglu, Autor and Lyle (2004) and make use of idiosyncratic differences across US states in the impact of World War II on married women’s labor supply to provide exogenous variation in the proportion of men raised by working mothers. We analyze the effect of World War II on the labor supply of the 1930-1935 cohort of women, a cohort that was too young to be directly affected by the war, but that was the right age to be affected by the change in the available pool of men a few decades later. We contrast the indirect effect of the war on this cohort with its direct effect on older cohorts and show that although the direct effect of World War II faded for the older cohorts over time, its indirect effect on the younger cohort persisted.
This paper shows that the evolution of the family and its interaction with the economy is an important determinant of the rise in women’s labor force participation over time. The micro interactions taking place within the family significantly affect women’s decision to work outside their homes. However, women are likely influenced also by other women around them: as they interact with neighbors and friends, women acquire information that affects their decision to work. In the next section I describe a theory in which the local transmission of information is the main driver of the joint evolution of social norms and labor force participation across time and space.
3. The Role of the Network: a Geographic Theory of Information Transmission
Fogli and Veldkamp (2011) provides theoretical micro-foundations to the mechanism of beliefs evolution by developing an information-based theory of local information diffusion. In the model, beliefs are transmitted across generations and they evolve over time as women learn from other women close by. Such a theory delivers rich empirical implications about the geographic distribution of women’s labor force participation and its evolution over time.
The paper focuses on learning and participation of women with children, because this sub-group is responsible for most of the rise in participation. A crucial factor in mothers’ participation decisions is the effect of their decision to work on their children. However, this effect is uncertain. The uncertainty makes risk-averse women unlikely to participate. Learning resolves their uncertainty, causing participation to rise. In our overlapping generations model, women learn from their neighbors about the relative importance of nature (innate ability) and nurture (the role of maternal employment) in determining children’s outcomes. Women inherit their parents’ beliefs and update them after observing the outcomes of neighboring women in the previous generation. Those outcomes reveal information about the effect of maternal employment on children only if nearby mothers were employed. This implies that higher local participation generates more information, which reduces uncertainty and makes participation of nearby women more likely. Thus, local participation snowballs and a gradual, but geographically concentrated, rise in participation rates ensues.
We use a novel county-level data set to show that the evolution of participation rates across time and space predicted by the model is consistent with that observed in the data and that our learning mechanism at the local level has quantitatively sizable effects on the aggregate.
The model also generates interesting implications for the cross section that distinguish our theory from technology-based ones. For example, according to technology-based theories, more women join the labor force as durable appliances and medical advances diffuse across the population and become cheaper over time. This implies that, according to these theories, the selection of women joining the labor force becomes poorer over time. Our theory generates the opposite implications: as the uncertainty about the consequences of maternal employment on children’s outcomes disappears over time, wealthier women will choose to join the labor force. At the beginning of the period, when uncertainty is high, only poor women take the risk of working in the market in order to increase their consumption. Such prediction is better supported by the empirical evidence.
In our paper women learn from other women that are geographically close. But another direction one could take this model is to interpret the concept of distance more broadly. Arguably, socioeconomic, ethnic, religious or educational differences create stronger social barriers between people than physical distance does. If that is the case, the learning dynamics that arise within each social group may be quite distinct. If the initial conditions in these social groups differ, changes in labor force participation, career choice, or social norms may arise earlier in one group than in another. This model provides a vehicle for thinking about the diffusion of new behaviors, with uncertain consequences, among communities of people.
Networks, technology diffusion, and growth
Motivated by our findings about the role of local information transmission for aggregate labor force participation, in Fogli and Veldkamp (2019) we explicitly explore the role of social networks for technology diffusion and growth. Using tools from network analysis, we investigate how and to what extent different social network structures might affect a country’s rate of technological progress. As some network structures are better suited to diffuse information and enhance growth, why would a social network structure that inhibits growth emerge and persist? Our theory for how networks evolve endogenously revolves around the idea that communicable diseases and technologies spread in similar ways – through human contact. We explore an evolutionary model in which networks that are stable, local, and have fewer connections reduce the risk of infection, allowing the participants to live longer. But such low-diffusion networks also restrict the group’s exposure to new technologies. In countries where communicable diseases are inherently more prevalent, the high risk of infection makes nodes with many, unstable, or distant linkages more likely to die out. A network that inhibits the spread of disease and technology will emerge. In countries where communicable diseases are less prevalent, nodes with few, stable, and local connections will be less economically and reproductively successful and will die off in the long run.
This paper merges two strands of literature: the one investigating the macroeconomic effects of culture (e.g., Bisin and Verdier (2001), Greenwood and Guner (2010), Doepke and Tertilt (2009)) and the micro literature that considers the effects of social networks on economic outcomes (e.g., Granovetter (2005); Rauch and Casella (2001)). As we explore the role of networks for aggregate outcomes, we are closer in scope to Ashraf and Galor (2012) and Spolaore and Wacziarg (2009) who investigate the role of social distance in the process of development. However, these papers measure social distance with genetic distance. Our network theory and findings complement this work by offering an endogenous mechanism to explain the origins of social distance and why it might be related to the diffusion of new ideas. We develop an evolutionary theory of endogenous network formation that explains why societies might adopt growth-inhibiting structures and use a variety of data sources to calibrate the model and use it to quantify the effect of networks on income.
Quantifying the model reveals that small initial differences in the epidemiological environment can give rise to large differences in network structure that persist. Over time, these persistent network differences can generate substantial divergence in technology diffusion and output.
We also find evidence of the effect of social networks in the data. Exploiting the differential mode of transmission of germs, we are able to identify a significant effect of social network structure on technology diffusion and income. More broadly, the paper’s contribution is to offer a theory of the origins of social institutions, propose one way in which these institutions might interact with the macro-economy, and show how to quantify and test this relationship.
Neighborhoods, segregation, and inequality
Another important macro development that has taken place over the last few decades is the significant increase in income inequality in the United States. What is the role played by the social context in the evolution of this aggregate outcome? In Fogli and Guerrieri (2019) we investigate the relationship between local interactions and macro inequality and in particular we explore the role of neighborhoods segregation in amplifying income inequality and reducing intergenerational mobility. The key ingredient of the theory is a local spillover that affects children’s future outcomes. Neighborhoods with richer residents and smarter children are characterized by higher returns from human capital investment. This spillover effect captures a variety of mechanisms through which neighborhoods affect children’s outcomes: differences in the quality of public schools, peer effects, social norms, learning from neighbors’ experience and so forth.
We develop a dynamic general equilibrium model in which parents choose both the neighborhood where they raise their children and the investment in their children’s human capital. The presence of the local spillover induces sorting in equilibrium: richer parents with more talented children will pay higher rents to live in the neighborhood with stronger spillover. As neighborhoods become more segregated by income, the future outcomes of poor and rich children progressively diverge, inequality increases, and the promise of the American Dream fades away. The rise in inequality, in turn, feeds back in more segregation as richer parents bid up housing prices in their attempt to live in better neighborhoods.
This paper merges two strands of literature: an elegant, mostly theoretical, literature studying the aggregate effects of local externalities that dates back to the ‘90s (Benabou (1993 and 1996), Durlauf (1996), Fernández and Rogerson (1996)), and the recent micro estimates obtained in the quasi-experiment of Chetty and Hendren (2018) using tax data.
We calibrate the model to a representative US city in order to quantify the increase in inequality driven by the increase in residential segregation. Using census tract level data, we target the level of income segregation and inequality of the average US city in 1980. A key target of our calibration is the effect of the local spillover. To discipline the strength of the spillover we use the micro estimates proposed by Chetty and Hendren (2018). We then use the model to analyze the dynamic effects of an exogenous shock to the skill premium. Despite the parsimony of the model, the exercise generates patterns for inequality and segregation that resemble the data. We can then use our model to ask our main quantitative question: how much does segregation by income contribute to the rise in inequality? To answer this question, we run a counterfactual exercise where we look at the response of the economy to the same initial shock, but assume that, after the shock, families are randomly re-located between the two neighborhoods, preventing families to sort according to income. The exercise shows that residential segregation by income contributes to 28% of the total increase in inequality between 1980 and 2010.
There are multiple interesting directions for future research. A particular important one would be to explore the normative implications of the theory, and assess the short and long run welfare impact of spatial policies geared to reduce urban segregation.
Overall, my research shows that the social context plays an important role in determining aggregate outcomes. There is an interesting and dynamic relationship between the social context in which micro interactions take place and the evolution of macro variables. The recent availability of rich micro data is crucial to identify these effects and discipline our macro models. In particular, the availability of geospatial data allows to explore the geographic dimension of economic phenomena and to better understand the underlying mechanisms of the macro economy and the role played by the social context. How do ideas and innovations spread through the economy? How do business cycles transmit across space? How do place based policies affect nearby locations? These are some examples of directions for future research. I feel that with my coauthors (and many others working in the area) I have only scratched the surface of a fascinating and promising line of research. I am already looking forward to the next developments.
Society for Economic Dynamics: Call for Papers, 2020 Meeting
The next annual meeting of the Society of Economic Dynamics will take place in Barcelona from June 21st to June 23rd, 2020. We are pleased to announce plenary talks by Nicola Fuchs-Schündeln, Guido Menzio, and Emi Nakamura. You can now submit your paper for the conference using ConferenceMaker. The deadline for submissions is February 15th, 2020. We are looking forward to receiving many exciting submissions for the academic program!
I want to start by congratulating both the program and the local committees for the success of the St. Louis meeting this past summer. Program co-chairs Marla Rippoll and Sevin Yeltekin did such a good job that I found it difficult to decide which of the parallel sessions to attend. This year, there were a total of 504 presentations in 14 parallel sessions with 3 presentations each—consisten with the last three meetings. Marla and Sevin also chose three excellent speakers—Laura Veldkamp, Jan Eeckhout, and Emmanuel Farhi—for the plenary sessions. Of course, an important part of any good meeting is the local team that coordinates everything from the coffee breaks to the facilities. This year’s team of B. Ravikumar, Chris Waller, Rody Manuelli, and Carlos Garriga managed to do this seemingly effortlessly—although I know firsthand that there were many hours put in by the team and their staff members at Wash U and the Fed to make this a successful event.
Next year, the Universitat de Autonoma in Barcelona (UAB) will host the summer meeting on June 21-23. This will be our 30th anniversary and 25 years after we first held the SED in Barcelona. The program chairs are Doireann Fitzgerald (Federal Reserve Bank of Minneapolis) and Nir Jaimovich (University of Zurich). I am happy to report that they have sent out the official announcement for the meeting and advertised that the submissions link is now open on our website. They have also announced that the three plenary speakers will be Nicola Fuchs-Schundeln, Guido Menzio, and Emi Nakamura. I should note that we welcome diversity in submissions. Recently, we have included buttons in Conferencemaker to indicate gender and location. Our hope is to avoid any bias in the submission process. The local organizers this year are Albert Marcet, Raul Santaeulalia-Llopis, Jordi Caballe, and Joan Llull—all from UAB. They are already hard at work making the arrangements. As in St. Louis, we are hoping to organize large receptions rather than hosting a formal dinner. The organizers are choosing beautiful spots in the city, what we will call “meeting points” where we can have tapas and drinks.
Plans are underway for the 2021 and 2022 summer meetings. I am pleased to announce that the Institute of Economics at the Academia Sinica in Taipei will host the summer meetings in 2021 with the lead organizer being Ping Wang of Washington University in St. Louis. The plan is to follow that in 2022 with a meeting in Cartagena hosted by the Universidad de los Andes with the lead organizer being David Perez-Reyna. Given facilities and venues must be secured well in advance, it is always necessary to plan the meetings several years in advance. That leaves time for past organizers to pass on their knowledge.
The Review of Economic Dynamics (RED) is the official journal of the Society for Economic Dynamics. The journal publishes contributions in any area of economics provided they meet the highest standards of scientific research. In particular, RED publishes original articles on applications of dynamic economic theory to a wide variety of problems in economics. Related measurement and empirical papers are also welcomed.
The following Associate Editors are stepping down from RED, and we are very grateful for their terrific service to the journal over the years: Guillermo Ordonez, Javier Bianchi, and Juan Rubio-Ramirez.
We welcome Vincent Sterk from UCL, who is joining RED as an Associate Editor.
Submissions and Turnaround Statistics
The number of submissions to RED continues to rise, and has roughly doubled over a five year period:
RED strives to deliver fast and efficient turnaround of manuscripts, without compromising the quality of the refereeing process. Around half of our submissions are desk-rejected. The average decision time for these desk-rejects is less than a week. The remaining submissions are sent out for review. For those submissions, the average number of weeks until first decision was 15.8 in 2017, 14.0 in 2018, and 14.6 in 2019 (year to date).
More than 97% of all submissions receive a decision within 5 months. We thank the journal’s reviewers for making these turnaround times possible.
RED has recently moved from the EVISE platform, to the Editorial Manager platform. This should offer a more user-friendly platform for paper submitters, reviewers and the editorial team.
The RED Newsletter (which you are reading!) is a bi-annual publication that has been running since 1999. It regularly features an interview with one prominent economist, and a commissioned summary of another economist’s research agenda. It occasionally includes book reviews. The Newsletter is also the vehicle for regular reports from the Editors of RED and from the President of the SED.
For many years Christian Zimmermann has been the main editor in charge of the Newsletter, with support from the Coordinating Editors of RED. He has recently stepped down from this position. Christian will continue manage the critical task of ensuring that the code and data associated with every published paper is publicly available here. We are enormously grateful for all the work Christian has done over the years to support RED, and to help disseminate frontier research through the Newsletter.
Marina Azzimonti has kindly agreed to take over as the new main editor for the Newsletter.
RED relies predominantly on regular submissions of manuscripts. Throughout our history, we have also published special issues representing the frontier of academic research on topics which are of particular interest to members of the Society. Articles in special issues all go through a full refereeing process.
The first commemorates the 25th anniversary of the publication of “Frontiers of Business Cycle Research”, edited by Tom Cooley. Tom is a former president of the SED, and a former Coordinating Editor of RED. The book he edited was foundational for the modern study of business cycles. The forthcoming special issue will cover a variety of new directions in business cycle research that has developed since the book was published. The papers were presented at a conference hosted by PIER at the University of Pennsylvania in May 2019.
The second special issue will contain a set of papers presented at a conference to memorialize Alejandro Justiniano. Alejandro was an Associate Editor at RED, and published several highly influential papers in the journal. He sadly passed away last year. The papers were presented at the Alejandro Justiniano Memorial Conference held at the Chicago Fed in November 2019.