George Bangham (Economics of Public Policy ’17) is an economic researcher at the Resolution Foundation, a London-based think-tank that carries out research and policy analysis to improve the living standards of people in the UK on low and middle incomes.
George Bangham (Economics of Public Policy ’17) is an economic researcher at the Resolution Foundation, a London-based think-tank that carries out research and policy analysis to improve the living standards of people in the UK on low and middle incomes. In recent years the Foundation has been influential in advocating for a living wage and for policymakers to consider the intergenerational impact of public policy. George’s own work focuses on labour markets and social security policy, with his recent publications covering issues from working hours to tax reform.
One of his recent papers, “The new wealth of our nation: the case for a citizen’s inheritance,” has received international attention in the media and was featured in an article in La Vanguardia newspaper this May.
The Intergenerational Commission has identified two major trends affecting young adults today, beside the weak performance of their incomes and earnings, which barely featured in political debate for much of the 20thcentury. The first is that risk is being transferred from firms and government to families and individuals, in their jobs, their pensions and the houses they live in. The second is that assets are growing in importance as a determinant of people’s living standards, and asset ownership is becoming concentrated within older generations – on average only those born before 1960 have benefited from Britain’s wealth boom to the extent that they have been able to improve on the asset accumulation of their predecessors. Both trends risk weakening the social contract between the generations that the state has a duty to uphold, as well as undermining the notion that individuals have a fair opportunity to acquire wealth by their own efforts during their working lives.
This paper, the 22nd report for the Intergenerational Commission, makes the case for the UK to adopt a citizen’s inheritance – a universal sum of money made available to every young person when they reach the age of 25 to address some of the key risks they face – as a central component of a policy programme to renew the intergenerational contract that underpins society.
Policy recommendations from the report:
From 2030, citizen’s inheritances of £10,000 should be available from the age of 25 to all British nationals or people born in Britain as restricted-use cash grants, at a cost of £7 billion per year.
To reflect the experiences of those who entered the labour market during and since the financial crisis, and to minimise cliff edges between recipients and non-recipients, the introduction of citizen’s inheritances should be phased in, starting with 34 and 35 year olds receiving £1,000 in 2020. Each subsequent year, citizen’s inheritance amounts should then rise and be paid to younger groups, until the policy reaches a steady-state in 2030 when it is paid to 25 year olds only from then on.
The citizen’s inheritance should have four permitted uses: funding education and training or paying off tuition fee debt; deposits for rental or home purchase; investment in pensions; and start-up costs for new businesses that are also being supported through recognised entrepreneurship schemes.
The citizen’s inheritance should be funded principally by the new lifetime receipts tax, with additional revenues from terminating existing matched savings schemes – the Help to Buy and Lifetime ISAs.
We want to know what the BGSE community is thinking and reading about the Brexit.
We invite all Barcelona GSE students and alumni to share their early reflections on the potential economic consequences of the UK’s recent vote to leave the EU. Did you focus on a related topic in your master project? Are you working at a think tank, central bank, or consulting firm where your projects will be impacted by this decision? Have you seen any articles or links that you found useful for understanding what lies ahead?
Here are a couple of pieces we’ve found to get the discussion going:
The BGSE participates in A Dynamic Economic and Monetary Union (ADEMU), a project of the EU Horizon 2020 Program. Last week, ADEMU researchers held a webinar to discuss the Brexit.
Europe has grown out of its crises when reason and solidarity have prevailed, but it has also been devastated by its crises when fear and nationalism have taken the lead. Brexit, in the aftermath of the euro crisis, brings this dichotomy back to the foreground. Since 2010 there have been important advances in the development of the Economic and Monetary Union (EMU) and flexible forms of participation have allowed other EU countries, reluctant to join the euro, to share the basic principles that define the EU and have a common presence in the interdependent global world.
According to the panelists, Brexit raises 3 crucial questions:
Should the EMU be accelerated to become a centre of gravity within the EU, or slowed down to avoid a centrifugal diaspora? If accelerated, how?
Should an ‘exit’ country be allowed free entry to the single market and other EU public goods without accepting freedom of movement?
Should the EU remain as it is, or increase its capacity to offer common public services (Banking Union, border security, research funding, environment, etc.), or limit its scope of activity to the EU single and integrated market?
– Joaquín Almunia (Former Vice-President of the European Commission, honorary president of the Barcelona GSE)
– Ramon Marimon (European University Institute and UPF – Barcelona GSE; ADEMU)
– Gorgio Monti (European University Institute; ADEMU)
– Morten Ravn (University College London; ADEMU)
Annika Zorn (European University Institute; Florence School of Banking & Finance)
Nobel Laureate and Barcelona GSE Scientific Council member Joseph Stiglitz shares some reflections in the wake of the Brexit decision
What are you thoughts on Brexit?
We want to know what the BGSE community is thinking and reading about the Brexit. Please share your ideas, favorite sources for analysis, or observations from economists you respect in the comments below.
With over 700,000 users, data from the app aquienvoto.org suggests how VAAs could represent a whole new way of surveying the general public before an election and collecting data on the political position of the population.
With over 700,000 users, data from the app aquienvoto.org suggests how VAAs could represent a whole new way of surveying the general public before an election and collecting data on the political position of the population.
The creator of the app is BGSE alum Hugo Ferradáns ’15, graduate from the Economics of Public Policy Program.Follow him on Twitter @Hferradans.
The rise of the internet era opened a door for innovative ways to help voters be informed about their political choices prior to casting their ballot. During the past 2015 Spanish General Election, new tools such as aquienvoto.org (whodoivote.org in English), an app that matches users’ policy preferences with parties’ proposed policies, became an easy and straightforward alternative for users to explore their political position and compare it to that of the biggest parties. Its success, with over 800,000 users and more than 30 million responses, suggests how technology and the social sciences can work successfully together to create a more informed and accountable electorate, especially in a multiparty political system such as the Spanish one.
But encouraging are more informed electorate is not the only benefit of Voting Advice Applications. In fact, the large amount of data that is generated from online applications such as aquienvoto.org can be a source of analysis and study regarding why people make their choices1, as well as a way to estimate what users care most about in a real-time basis before an election. This article, thus, will try to shed light on the usefulness of Voting Advice Applications to gather data on the political positioning of users. I will show some of the results that were acquired from aquienvoto.org, both on the policy preferences of users and on their most politically-aligned parties.
But first things first- What is exactly aquienvoto.org?
Aquienvoto.org is what is called in the field of political economy research a “Voting Advice Application” (VAA). VAAs are essentially an online test that matches users to parties depending on individual responses to policy-related statements. The user can either disagree or agree with the statements, as well as indicate whether that specific policy is important to him or her. After replying to several questions, the VAA gives the user a summary of what parties the user disagrees and agrees most with, mainly in the form of a ranking or a political map.
Even though there some VAAs more sophisticated than others2, all VAAs acquire essentially the same data:
the position of the user regarding a specific question (in a scale of completely agree to completely disagree with the statement in question),
whether that user gives importance to that question and
after answering all questions, the ranking of most preferred parties for each user.
Aquienvoto.org was able to gather information on 756,908 people, after dropping all users that did not complete at least level 1 (that is, replied to 31 questions).
What did users get as an advice from aquienvoto.org?
If we look at what party was the most first-ranked among users, we see that the centre-right Ciudadanos was the most preferred party throughout the whole period for roughly 33% of users. However, interestingly enough, the overall amount of people that voted for parties that are more leaned towards the left (Podemos,PSOE, United Left and Nós, representing 62.8% of votes) is much higher than those in line with liberal and conservative policies (Ciudadanos, PP, PNV and DiL, being 37.2% of users’ first choices), indicating that users from aquienvoto.org are consistently left-wing.
It is particularly noticeable the different layout that the results present when compared to the results from General Elections. For example, the conservative Partido Popular, which was ranked first in the elections with roughly 25% of votes, appeared last almost throughout the whole period for aquienvoto.org. It is clear that this might certainly come from the fact that VAA users are consistently younger and more left-wing than the average citizen, but it also poses a question that would be interesting to explore: do people vote in line with their policy preferences or are there other factors that are influencing voters’ decisions in the field of electoral politics?
How do people position themselves about certain issues and what they think are most important?
Unsurprisingly, the topics related to corruption were the ones users gave most importance to, with almost 10.67% of respondents (that is, 80,410 individuals) giving importance to the question “Politicians accused of corruption should resign and be illegitimated to run for office”, of which almost 93% of people responded that they agree or completely agree with the statement.
The second and third place of most-given-importance questions are related to the presence of religion in the political sphere (second place) and the presence of religion in the education curriculum (third place), for which both find a strong rejection towards religion. Furthermore, social policy is an area of much importance to individuals as well, surely very much related to Spain’s current economic woes. Indeed, Spanish law related to mass evictions over the past years3 takes fourth place in most-given importance question (8.06% of total questions replied), followed by a statement on the education budget (7,46%), for which most people agree that increasing the budget is a top priority within government policy. These results are roughly constant throughout time, although the amount of users that gave importance to questions declined (graph 2).
In terms of the most controversial topics out of all questions, where there are large amounts of people agreeing and disagreeing with the statement, we find the prohibition of bullfighting, the abolition of escuelas concertadas4 and the law regarding underage abortion5, having all of them a rather high rate of importance-responses as well.
Regarding what users are not interested on, that is, the questions that were least given importance to, it is seen that the four topics that are least important to users (starting from the least important) are the deficit and the ceiling of government expenditure, the legalization of prostitution, the regulation the financial sector, and the financing of the Autonomous Communities (the different regions of Spain).
What is the political position of the average user?
In order to give users the most interactive experience when analyzing their results, we created a map of their political position using eight different axis, as the Swiss VAA smartvote6 did. Using an algorithm, each response that a user gives contributes to create its “political map”, which can be later compared to the political map of the parties. Thus, using the responses from each user, we computed the political map for the average user, creating the image below.
As it can be seen, the average user is very much in favor of strong democratic institutions that condemn corruption at all levels, as it presents a rather high value for the axis related to democratic regeneration. Furthermore, it also presents a high value for welfare state and liberal society, and quite a low value for those questions supporting a liberal economy and a restrictive fiscal policy, which goes in line with the results mentioned above that users are more prone to identify themselves with left-wing policies.
Also, it can be seen that the average user rejects all statements related to regional nationalism, and favors those regarding state centralization. This changes, however, when comparing the average users from different regions, as people from Autonomous Communities such as Catalonia and the Basque Country strongly reject state centralization and favor regional nationalist policies.
What is left to be done from VAAs like aquienvoto.org?
Although VAAs can give academics a rich database, there are a number of methodological challenges that need to be overcome7, mainly regarding the representativeness of the sample. Indeed, if we want to make inferences on the positioning of the whole Spanish population, it is crucial that we acquire good quality data on the characteristics of users; something that has been proved difficult for online surveys. From aquienvoto.org, we are working to improve the process of data collection, providing users with the option to sign into an account where they can store their information and reply to surveys at any time. Nevertheless, we believe that more attention from Universities and governments should be given to these tools so that institutions and VAA organizations collectively work to make VAAs a better tool both for users and for the academia. Hopefully, that is what will happen in the next years to come.
Evan Seyfried ’16 (Economics of Public Policy) summarizes the lecture by Princeton’s Atif Mian.
Evan Seyfried ’16 shares the following summary of a talk given by Princeton’s Atif Mian this May to the UPF Department of Economics and Business. Follow Evan on Twitter @evanseyf
In 2006, house prices in the U.S. reached their all-time peak. The S&P/Case-Shiller Housing Price Index had doubled in just eight years (not accounting for inflation).1 The year before, Robert Shiller (whose work on historical housing prices led to the creation of the Case-Shiller Index) had published an update to his book Irrational Exuberance warning that recent growth in housing prices was historically unprecedented—he argued that houses were wildly overpriced and would likely revert back to a relatively constant historical value in the long run.2 His research showed that if you looked at real prices (inflation-adjusted) in the U.S. housing market prior to the early 2000s bubble, you would find that prices have not changed much since 1890!
The frenzy of the early 2000s finally caught up with lenders, homeowners, and investors, who began to doubt the continued rise of house prices. In late 2005, with interest rates rising, a growing number of homeowners with Adjustable-Rate Mortgages (ARM) began to default on their mortgages. Finally, by the end of 2006 the housing bubble began to collapse under its own weight, and the shockwaves ripped through the financial sector—which had bet heavily on the U.S. housing market through mortgage-backed securities and newer exotic financial instruments. French bank BNP Paribas, on August 7, 2007, famously suspended withdrawals from its investment funds associated with subprime mortgages, a move that triggered a shadow banking run, and is often considered the official start of the financial crisis—when the housing market instability truly began to upend the financial sector. What followed was the most severe financial crisis since the Great Depression and a long recession for the rest of the U.S. economy.
But there is still much to be learned about the interaction of the housing bust (leaving many homeowners with very high debt compared to their assets), the crisis in the financial sector (wherein banks have been generally unwilling to either extend new credit or restructure existing loans), and the continuing economic malaise in the U.S. and other economies around the world.
From the housing bubble to household debt
A great deal of Princeton economist Atif Mian’s research—much of it in collaboration with University of Chicago economist Amir Sufi—has studied these interactions, exploring the fallout from the housing bubble in the U.S. and the subsequent “debt overhang.”
What is household debt overhang?
Imagine a family owes $200,000 on their mortgage. If the market crashes and the house value suddenly declines to $180,000, then the family now owes $20,000 more than the value of their house. Thus, even if the family chooses to sell the house, they will not be able to pay back the mortgage in full. This is also called being “underwater” on a mortgage. In the context of all household finances, debt overhang is a similar concept to being underwater, and refers to the amount of indebtedness of a family beyond the value of their assets, taking into account their anticipated income. Debt overhang makes a household unattractive to lenders (both for new loans and for refinancing old loans), because they do not have any collateral that is not already used to cover existing debt.
Note that household debt is treated separately from other private sector debt (mainly non-financial firm debt), and shows notably different dynamics. All of Atif Mian’s research mentioned here focuses specifically on household debt.
In 2013, Mian published evidence that poorer families who were highly leveraged in the housing market reacted very sharply to the loss of wealth when their homes depreciated following the housing bust. Because their marginal propensity to consume out of housing wealth (how much families spend knowing that they have a certain amount of wealth in their house to fall back on) is higher than for middle- or upper-income families, their consumption dropped disproportionately in the years after the bubble.4 Of course, at the individual level this behavior is rational, but at the national level low consumption growth in a demand-constrained economy has created a negative feedback loop of lower job growth, lower income growth, and a further drop in consumption growth.
One of the takeaways from this body of research is that governments and international finance organizations need to do a better job of properly accounting for how private sector debt affects consumption. Optimistic forecasts for recovery from the 2008-2010 Great Recession did not sufficiently account for depressed demand as homeowners and those with credit card and student debt eschewed consumption to deleverage themselves. In a comment on Karen Dynan’s research on household debt overhang and consumption, Mian wrote: “… macroeconomic policy in a world where consumption is driven by debt overhang needs to be seen through its implications for the net worth of the borrowing households.”5
But Mian also wanted to take these insights from the Great Recession and ask more fundamental questions about private debt and predictions of economic growth: Was consumption affected similarly affected during other periods of high household debt? Do we see similar household debt effects in other countries? If so, how does this extra drag on consumption affect how economists forecast economic growth?
Mian recently gave a lecture at the Universitat Pompeu Fabra in Barcelona, presenting the findings from his attempt to answer those questions. (The working paper, coauthored with Amir Sufi and Emil Verner, is available from the National Bureau of Economic Research.6 ) They took a sample of 30 countries (mostly advanced economies) and compiled private debt data back to 1960. Then they identified shocks to household credit and looked at the relationship between those shocks and subsequent GDP growth. (In this context, shocks should be thought of as sudden increases in the availability of credit.)
Initially they found that high growth in household credit was predictive of subsequent low GDP growth. But they needed to identify the nature of those credit shocks to find possible causal channels. According to Mian they wanted to “rule out demand-driven shocks.” Demand-driven shocks come from the consumer side and could be an increase in the use of credit to smooth lifetime consumption, or as an “insurance effect” to get liquidity today due to uncertainty or an expectation of economic shocks tomorrow. On the other hand, a supply-driven credit shock would be banks extending more and more credit due to government policy changes or financial innovation.
The first demand-driven possibility is relatively simple to disprove. Because the Permanent Income Hypothesis suggests that households borrow today in the expectation of higher future income, the fact that household debt increases should be indicative of economic growth. As mentioned before, Mian, Sufi, and Verner find the exact opposite relationship. The second demand-driven possibility is unlikely because much of the growth in household debt across all the countries in the survey is in mortgage debt, which is generally not taken on to provide liquidity.
Next, they looked into the supply-driven credit shock mechanism and tried to find a way to overcome the presumably endogenous relationship between credit supply shocks and subsequent lower GDP growth. The mechanism must explain why people borrow in the first place, especially what causes them to over-borrow (what Mian calls an “aggregate demand externality”—an effect that spills over to other borrowers), and explain why excessive borrowing actually leads to a decline in real output (what Mian calls “macro frictions” that generate the slowdown, such as monetary policy and “wage rigidity”). As the authors write in the paper: “The key ingredient in this model is an aggregate demand externality that is not properly internalized by borrowing households at the time they make their borrowing decision.”
Two problems remained. First, the authors had to come up with a measure of “credit supply shocks” that could apply to dozens of different countries. Second, they had to choose a measure that could help identify the causal relationship, not just the correlation. Their solution was to use one measure for the U.S. (share of debt issuance by risky firms) and a simpler one for non-U.S. economies (the spread of sovereign debt yields compared to equivalent U.S. Treasury notes). According to Mian, these are “not instruments in the usual sense of the word” (which must satisfy the requirements of independence from the outcome variable and relevance to the explanatory variable). Rather, they are “imperfect instruments” (see Nevo and Rosen, 2012.7 for more information) and, per Mian, “as long as we can sign the covariance of the instrument, we can partially identify the range in which the coefficient lies.” In other words, because these proxies for credit supply shocks typically signify expectations of good times, then if we see that they actually predict bad times, we can at least identify a range of values for how strong the link is between an increase in household debt and subsequent low growth.
The methodology is admittedly complex, and audience members had some reservations about how the authors had dealt with household debt (particularly since household debt is mostly mortgage debt). One audience member suggested that housing bubbles could be the main driver of subsequent low growth, with the extension of credit simply a side effect. Mian acknowledged that he cannot outright reject this concern, but added that the results are robust to controls for house prices, so the bubbles should be controlled for. Another audience member suggested that this could be tested for if the data set included any countries which had seen a credit boom with no attendant housing bubble. There are, in fact, some countries in the data set, but, as Mian stressed, there was not enough of a subsample for a strong statistical test of this hypothesis.
Onward to global growth!
After presenting the “within country” results—showing that household credit supply shocks tended to lead to lower growth in the five or so years following—Mian pivoted to the global portion of the paper. The goal here was to establish the spillover effects of these credit supply shocks among different countries. Sure enough, Mian stated that “the global cycle is more destructive” due to financial spillovers between countries. Because the growth slowdown in a given country after the credit shock leads to a reduction in imports, the problem is transferred to that country’s trading partners. Furthermore, the effects are exacerbated by “macro frictions,” especially in countries that employ fixed exchange rate regimes, borrow primarily in foreign currency, and are near the zero interest rate lower bound (although recently the zero interest rate bound has been proving not to be much of a hard bound after all). Figure 2 shows these global aggregate effects.
Mian stressed that these dynamics between debt and growth, especially the global ones, should be seen as relatively recent (“last-forty-years effects”) side effects of globalization and the financialization of household debt. He concluded that governments must respond to these powerful forces with targeted macroprudential policies, and forecasters at organizations like the IMF and OECD must learn to better account for household debt in their growth projections.
In the past few weeks, there have been a barrage of media reports about educational achievement and, more generally, life outcomes for the youth of Durham.
The positive news is that these issues are receiving attention, but the downside is that the reports may be more harmful than helpful. At its best, data optimizes decision-making, but at its worst data can be deceptive and divisive.
Specialized knowledge is required to leverage data for decision-making, whereas selectively reporting figures requires some effort but no expertise. In the latter scenario, the ambiguity of statistical assumptions predisposes the audience to personal, as well as, framing bias. Those who go through the effort to produce data often have an agenda, and therefore, have incentives to make claims which imply causes and solutions. Data is dangerous when misused. It can create tension, undermine trust and unity, and result in costly adverse decision-making.
One key characteristic of amateur statistics, aside from lacking an experimental design, is that they do not account for the fact that outcomes are a function of many different variables. For example, schools clearly play a crucial role in influencing academic attainment, but a report drawing relative comparisons between attainment outcomes within or across cities usually implicates unidentified failures of one school district versus another while all but ignoring the effects of transportation, affordable housing, food, healthcare, and social support accessibility, as well as people’s different lived experiences, including traumatic exposure of various kinds.
Reactivity to outcomes is strongly linked to bias and emotion. Making decisions about problems and solutions based exclusively on outcomes is the logical equivalent to going with your gut.
Descriptive statistics alone have a tendency to reinforce what we already think we know rather than helping us to gain an objective understanding of the issues because we often overestimate our understanding of the context. Shards of truth may be buried in our presumptions or between the different storylines, but other times the truth isn’t within sight.
If one wanted to know what public schools are doing right and what positive changes could be made, the reported outcomes would not meaningfully increase understanding. This would be like a college basketball coach using the Ratings Percentage Index (RPI) to make game plans. The RPI is simply a function of outcome variables that are influenced by other, more influential variables over a team’s success, such as shot selection, rebounding, ball control and many others.
Similarly, objective inference about the determinants of academic achievement are impossible when we simply have some measure of the output, like grade level proficiency, graduation rates or achievement gaps. Summarized outcomes do not even begin to untangle the multifaceted causal factors of student achievement, or even point to which factors are within the schools’ control and which are shaped by other institutions that govern infrastructure, real estate development, credit markets and criminal justice.
Good intentions often lead to unintended consequences. Calculating outcomes or deriving slightly new definitions of them does not enhance the cultural or intellectual competence of our community, its citizens or the institutions within it.
This is troubling because the extent of harm done with every report that subjectively frames and selectively reports data will never be known. A symptomatic obsession can enable data to have a negative social impact, leading to the proliferation of economic and racial segregation, adverse selection of people and funds from public schools, victim blaming and the marginalization of objectivity. The focus needs to shift from symptoms to solutions.
Data should be collected and analyzed in a way that enables us to separately identify effects on outcomes, including those determinants within the school’s control and those outside, so that all can be addressed in order of impact and feasibility. Robust evaluations should yield insight, pointing out specific causal factors that affect outcomes that the schools, nonprofits policy and citizens can address.
Applying a scientific lens to social issues transforms data from punitive to instructive. Careful investigation using valid quantitative methods can help us gain an understanding of the inferences that the data will and will not permit. Through empirical analysis, we have the opportunity to disentangle the effects that different factors have on certain outcomes. This is powerful because it enables us to create informed strategies.
Subsequently, when we know how our potential actions will affect an outcome, a cost-benefit analysis can help decide which evidence should be brought to action. Operating in the public and nonprofit sectors, the cost-benefit analysis goes beyond fiscal considerations to examine social returns. Combining these empirical tools puts us in a position to optimize social welfare. Data or analysis vacant of these characteristics will result in suboptimal decision-making.
An empirical basis for decision-making that respects the complexity of determinants on outcomes and the tradeoffs between various actions or lack of action should be utilized at all levels – from the systemic to the programmatic. A symptomatic focus and a preoccupation with a single area will not result in systemic improvement. As institutions, organizations and programs, our goal should be to improve, which can only be achieved through learning.
Durham has great potential to grow while enhancing the well-being of all, including the most marginalized. Continuous improvement requires the commitment of people in the public, private, and social sectors to work together.
Part of analytical integrity is the acknowledgement that sometimes our data tells us nothing at all. If we truly care about addressing systemic issues, lack of information is a strong argument for why we should build more robust datasets that incorporate variables across institutions and the socio-economic environment. This requires a willingness to coordinate and to learn. Importantly, these actions imply the willingness to change.
The Made in Durham partnership exists to address issues of the highest importance. It is the job of data is to increase the role of evidence in the partnership’s decision-making, and because of the gravity of these decisions, I also feel an ethical accountability to this work.
If we aren’t asking the right questions, data can lead to costly decisions that undermine improvement. As members of the community, we should all be able to ask the right questions to hold decision-makers accountable to analytical standards that drive improvement.
Regardless of what the outcomes show now, or anytime in the future, what we should be asking is: what are the causes of these outcomes, what are their magnitudes, and thus, what can we do to improve.
Evan Seyfried ’16 (Economics of Public Policy) recaps the Barcelona GSE Lecture by Robert E. Lucas (Chicago, Nobel Laureate)
Lecture summary by Evan Seyfried ’16 (Master’s in Economics of Public Policy). Above, the author talks with Robert Lucas after the lecture.
The modish Banco Sabadell Lecture Hall, overlooking grand, prosperous Avinguda Diagonal, is filled to capacity this Thursday evening. Nobel laureate economist Robert Lucas is here to present the 34th Barcelona GSE Lecture, and the GSE community is eagerly anticipating the talk.
“What was the Industrial Revolution?”
The topic would have seemed almost trite in less-skilled hands. Lucas, however, over the past decade has focused his talents on exploring economic models that might explain rapid industrialization like that of the United Kingdom starting in the late 18th century. He views the rise of urbanization and industrialization through the lens of economist Gary Becker’s theory of population fertility and couples it with a human capital growth model.
This talk draws heavily from Lucas’s recent research on human capital and economic growth1, the diffusion of the Industrial Revolution2, and a rejection of the “great men” hypothesis of economic progress3.
The central hypothesis of his lecture tonight is, essentially, that of his 2015 paper on economic growth, with its blissfully short abstract:
“This paper describes a growth model with the property that human capital accumulation can account for all observed growth. The model is shown to be consistent with evidence on individual productivities as measured by census earnings data. The central hypothesis is that we learn more when we interact with more productive people.”1
From this basis, Professor Lucas presents his most recent work on the topic. He begins with a graph—how else would an economist begin any lecture?—showing the striking relationship between a country’s prosperity (measured in GDP per capita) and the share of its population employed in agriculture.
Why is the relationship between these two variables so consistent? Later in the lecture, Lucas will develop his model based on a “dual economy” of low-skilled agricultural workers and various levels of skilled urban dwellers.
But first, a little history.
“Macroeconomics’ finest hour.” (A brief historical digression.)
Thomas Robert Malthus, English cleric and scholar, became famous (and, to some, infamous) when he published “An Essay on the Principle of Population” in 1798. The essay neatly distilled a framework for pre-industrial population dynamics:
“Yet in all societies, even those that are most vicious, the tendency to a virtuous attachment is so strong that there is a constant effort towards an increase of population. This constant effort as constantly tends to subject the lower classes of the society to distress and to prevent any great permanent amelioration of their condition.”4
Its publication led to a massive controversy that rapidly spread across the landscape of political economy. Although Malthus’s work was not nearly as apocalyptic as his deriders asserted, it still pointed out uncomfortable truths about the seemingly unrelenting misery of the lower classes, even in “advancing” nations.
A century and a half later, economist Gary Becker took up the Malthusian mantle with his seminal work, “An Economic Analysis of Fertility,” a study of the dynamics of family planning and income. Becker explicitly acknowledged his debt to Malthus: “[…] Malthus’ famous discussion was built upon a strongly economic framework; mine can be viewed as a generalization and development of his.”5 Becker’s further research concluded that viewing fertility as a result of marginal-cost/marginal-benefit decisions is a satisfying way to explain the phenomenon of high-income families voluntarily lowering their fertility rates. His framework implies that families with more human capital invest more resources in fewer children.
Professor Lucas calls the Malthusian insight and the subsequent robust debate among political economists of the day “macroeconomics’ finest hour.”
The Path Off the Farm: What Is an Industrial Revolution?
Lucas now presents his synthesis: Becker’s fertility model combined with Lucas’s own human capital model, both placed in the context of the urban-agricultural dual economy.
Like Becker, Lucas’s model has parents view their children as “durable goods” that yield a “psychic utility” but also impose costs. As families move up the socioeconomic ladder, they make different decisions regarding investment in the “quality” of the children (everything from time spent teaching, to money invested in tutors and private schools). Over time, the quantity/quality balance leads to lowering fertility among higher socioeconomic classes.
In the dual-economy framework, rural (landless or small proprietor) farmers are pushed by wage considerations to move into dynamic urban environments as low-skilled workers. At first, with no wealth to invest in their children, they make “quantity” a priority over “quality.” Over generations, however, there is a tipping point where a given family has accumulated enough resources to make meaningful human-capital investments in their children. Once this occurs, they can now move up to the higher-skilled tiers of society. Crucially, it is this accumulation, not of wealth, but of human capital, that drives further growth in Lucas’s model. The speed at which these changes occur depends on the magnitude of “interactions” in society: how often and to what degree people engage with one another in productive exchanges—anything from academic discussions to business deals.
A key mechanism in the model is that economic growth itself is what allows the low-skilled workers, coming from the farms, to dependably get better and better jobs over time. Thus, the dynamic is self-reinforcing as more rural workers move to the cities.
When considering the Industrial Revolution, we can appreciate how natural it would be to dismiss the intangible, fuzzy concept of “human capital” and only focus on material capital: factories, infrastructure, mines, etc. But if we view the Industrial Revolution with Lucas’s model in mind, we can at the very least see that Lucas’s statement from his 2015 paper—”human capital accumulation can account for all observed growth”1—is quite plausible.
Later in the same paper, Lucas asserts: “The contribution of human capital accumulation to economic growth deserves a production function of its own.” 1 In the model Lucas has presented tonight, he answers his own demand. There is, indeed, a “production function” for human capital, and when it is coupled to a fertility model, it can show the dynamics of rapid urbanization and economic growth. In other words, it can model an industrial revolution.
To use Lucas’s own words from the lecture: “We used to think of the Industrial Revolution as factories and coal, but I think the main consequence was the emergence of the bourgeoisie who are just creating things out of nothing, generating wealth and production.”
What does this all mean? What are the implications of this model in 2016?
We go back to the graph showing the relation between GDP per capita and share of population in agricultural work. Lucas mentions how many areas of the world are still in the upper left portion of the graph—poor, agricultural, unskilled-labor-intensive economies. According to Lucas, we must not be deluded into thinking that a pastoral lifestyle is something to be preserved at the cost of indefinite poverty. Lucas states, “The idea that you can prettify this lifestyle is just plain wrong.” Rather, we have a collective interest in the flourishing of all people around the world, and we have emerging evidence that investment in human capital, coupled with smart urbanization, is one of the best ways to achieve it.
The questions following the lecture are—as expected from economists—pointed. In response to questions about the refugee and economic migrant crisis in the EU, Lucas denies that his model says anything specific about it, but states emphatically that he supports immigration in general. Finally, when asked about the prospects of continued economic growth, given recent anxiety about economic stagnation, Lucas responds that since the Industrial Revolution we have seen stable growth unlike any period before in recorded history. He believes that growth will continue, as capitalism reinvents itself yet again, this time for the information age—though he admits that “flush toilets are way more important than Facebook.”
With that, the lecture concludes, and the lucky attendees weigh the expected utility of waiting in line to speak with the most influential living economist against the expected utility of beating the rush to the cava and jamón ibérico at the reception. The gears of the market keep turning.
Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2015. The project is a required component of every master program.
Benjamin Anderson and Ramiro Antonio Burga
Economics of Public Policy
This paper provides empirical evidence of the persistent effects of exposure to civil conflict on political beliefs and participation. We exploit the variation in geographic incidence of conflict and birth cohorts to identify the long-term effects of exposure to violence on belief in democracy, trust in institutions, opinions in support of civil rights, voting turnout and casting of blank ballots, and participation in civic organizations. Conditional on being exposed to violence, the average person exposed to violence during certain sensitive stages of life still holds slightly more negative opinions about the value of democracy and are less likely to participate in civic / political organizations in the long-run.
About the paper
Political preferences heavily dictate the role of the government, the policy making processes that emerge, and potentially even the institutional framework, itself (Besley and Case, 2003; Aghion et al., 2004). Furthermore, consequential effects of various forms of political institutions is a primary focus of Political Economy, and justifiably so, for the array of welfare implications encompassed within, including, economic growth, inequality, health outcomes, and many others (Acemoglu et al., 2001; 2002). In countries where citizens have been exposed to violence during sensitive periods of life, it may be more difficult for governments to gain trust and build support for democratic processes and good institutions.
There are many logical pathways which one could speculate that civil conflict might affect citizens’ political beliefs; perhaps the most conspicuous of which being trust. Lack of protection, safety, and government accountability could lead to a decrease or lack of trust in the government, while exposure to violence, fear tactics, and other criminal behavior could result in distrust toward other members of society (Jaeger and Paserman, 2008; Rohner et al., 2013). Secondarily, residual effects of civil conflict in the form of fear, in particular for safety, could dissuade citizens from various forms of political participation (Salamon and Evera, 1973).
Summary of findings:
We examine the effect of exposure to conflict during sensitive developmental periods of life on persistent changes to various measures of political beliefs and participation. The results show that the average person exposed to conflict during the age range 13 to 17 will have slightly more negative opinions about democracy well over a decade after the conclusion of the violence. Very minor long-term effects are also present for participation in civic organizations. Our results show that the average person exposed to conflict during the age range of 7 to 12 has a decreased likelihood of participating in civic organizations of approximately 3% to 6% for each additional year that the individual experienced violence in his/her district during this period of life. While these effects are economically small, it is notable that any long-term effect is detected given the likely presence of strong attenuation bias as discussed in our threats to identification. We find that the most sensitive stages of life for the formation of political beliefs, with respect to exposure to conflict, are the pre-teen and teenage years. Contrary to the effects of violence exposure on human capital and labor market outcomes, we do not find effects occurring at the earliest life stages.
The detection of effects in both belief and action variables not only helps to validate one another, but it also suggests that beliefs indeed translate to actions. This connection provides some evidence that changes in political perception also corresponds with political behavioral change.
Even though the effects we detect are relatively small, they might have been severe during and shortly following the civil war.
Although we are unable to further analyze heterogeneous effects, the effects could be quite large for certain individuals who may have been exposed to more extreme amounts or types of violent acts.
Knowledge of the size and temporality of these consequential effects of civil conflict on political beliefs and participation as well as mechanisms which drive these changes would be invaluable. This would allow policy makers to develop targeted strategies to help combat the destructive effects of violence on citizens’ political beliefs and behavior that could undermine the healthy growth, development, and stability of society.
On the experience:
The thesis was almost certainly the most fun and rewarding assignment of the year, despite the imposing time constraint. Having received rigorous training to acquire the tools needed for such a project, and having discovered and nurtured our own interests via exposure to a multitude of prominent literature in various applied topics throughout the year, it was exciting to unleash the knowledge we had gained and apply some of our empirical techniques to a new and interesting research question of our own.
Throughout the program, but especially during the thesis, we were fortunate to have access to the knowledge and support of professors. Aided by some enthusiastic and accomplished mentors, we evolved our expectations of ourselves. Their expertise in areas related to those of our paper – conflicts, violence and political economy – optimized the quality of feedback and constructive critique we received in the process. The final presentation to our directors, professors and peers was another valuable component. It served as a welcome challenge that exercised essential communication skills, not only for conveying complex ideas to an audience, but adroitly and favorably reacting to questions and criticism.
The feeling of accomplishment derived from materializing a quality piece of empirical work is great motivation to build on for the future. Just one year ago, not only would this project have been impossible to execute, even the vision of it coming together was unfathomable. By the final term, we knew that we were prepared; now, we carry forth these tools, creativity, and confidence in our abilities.
On working with a coauthor:
At the outset, the thought of working with a coauthor for the thesis did not sound ideal, but ultimately, it had many advantages. It offered another opportunity to gain from the international and cultural diversity of one another and to develop these working and personal relationships; it was an invaluable intangible experience for which we will be forever thankful. Our complimentary skillsets and working styles prevented this beast from ever becoming a burden. We are proud of what we were able to achieve given the constraints, and ended up with a final project that far surpassed anything that we could have done independently within the same amount of time.
While the outcomes of most public investments schemes are not completely foreseeable, the benefits of investing in education to both children and broader society could not be more clear: education is strongly correlated with improvements in health and nutrition, it is one of the best protections against poverty, and it fosters civic participation and democratization.
Although the importance of education to individuals and society is apparent, access to education differs substantially between and within countries. In particular in developing countries the access to education is extremely restricted. Looking at within country disparities, these barriers to education often disproportionately affect girls. In the 1970s the Indonesia’s central government launched the Sekolah Dasar INPRES program (henceforth SD INPRES), one of the largest primary school construction programs in history in order to counteract this trend of stagnating primary school enrollment rates. This large-scale construction program led many economists to study the numerous impacts on the Indonesian population by taking advantage of its form as a natural experiment.
Previous literature on the impact of SD INPRES suggests that until recently only little attention has been paid to the effects of the primary school construction program on girls. This is not very surprising since Indonesia constantly performed poorly among international gender equality measurements such as the Gender Inequality Index by the United Nations or the Global Gender Gap Report by the World Economic Forum. Work by Hertz and Jayasundera (2007), Pettersson (2012), and Ashraf et al. (2014), take differing approaches in studying the effects of the SD INPRES program in women. The novelty in our approach lies in the fact that with our data set, containing more cohorts than previous analyses, we are able to check for persistency of the resulting effects of the school construction program on later cohorts by extending the time range used in Duflo’s pioneering analysis. We also investigate whether the effect of the program on women might not be reflected on the intensive margin, i.e. the actual duration of education, but rather on the extensive margin, in other words the likelihood of completing primary school education.
A key element of our identification strategy to identify causality of the school construction program on educational outcomes relies on variations of an individual’s exposure to the program based on date and region of birth. For the purpose of our analysis, we only treat the combination of these two variations as exogenous. By its nature, the SD INPRES program was designed to allocate more schools to regions where primary enrollment was particularly low, inducing heterogeneity in the number of average schools built per district. A second source of variation is reflected in the age of the students. A child of 12 years of age or older in 1974 when the SD INPRES schools started to operate, could not benefit from the program. On the other hand, a child aged 6 or younger in 1974 was young enough to fully benefit from the newly constructed schools. Similarly, children between 6 and 12 years of age in 1974 only enjoyed partial exposure to the program. If the program had an effect on an individual’s years of education, we would expect the program to have the largest effects for fully exposed cohorts, a somewhat mediocre effect on the partially exposed individuals, and no effect on children that were too old in 1974 to benefit from the program. The large, exogenous shock of the SD INPRES program enables us to differentiate between treatment and comparison groups, in the manner of a quasi-experiment using a difference-in-differences approach.
In line with previous literature, we find that the SD INPRES program had significant effects on schooling outcomes of Indonesia’s children. However, children did not benefit from the primary school construction program equally. In fact, we find substantial heterogeneity of the program’s effect between genders, mostly favoring boys over girls. On average, one more school per 1,000 children in the district of birth increased schooling duration by 0.12 to 0.21 years for boys. However, this effect is less clear-cut for women: depending on the sample specification and type of analysis, we were able to obtain significant results for women albeit substantially smaller in magnitude. In particular when breaking down the analysis on each birth year cohort, our estimates suggest that only the youngest cohorts hitherto benefited from the program, with effects ranging from 0.1 to 0.17 additional years of schooling for an additional school built in the district of birth. Such suggestive late onset of the program’s effectiveness on women motivated us to perform a persistency analysis on later female cohorts. Including eight additional birth year cohorts, we find increasing and significant effects of on average 0.2 additional years of schooling. These findings suggest that a potential effect on women’s schooling might have set in later. Our mixed evidence thus far gives rise to doubts whether the SD INPRES program worked on the extensive margin of schooling attainment. Due to possible selection disadvantages at the transition between primary and secondary school, the effect of the program for girls might not be reflected in the in years schooling but merely in their likelihood of primary school completion. We find significant but negligible effects on women’s likelihood to graduate from primary school.
Ideally, a policy trying to increase education should be targeted at disadvantaged groups of society in order to decrease inequality and break the vicious cycle of poverty. Our findings suggest that women in Indonesia are particularly disadvantaged when analyzing educational outcomes. Further research should hence try to identify other possible heterogeneities when stratifying the sample interest. During our analysis, we made first attempts by looking at different specifications such as the difference in effects between individuals living in rural versus urban areas, or looking at potential heterogeneity varying by ethnicity. Such deviations of our analysis might unmask further heterogeneity, which will be essential to identify when assessing and improving Indonesia’s education policy. It will therefore be necessary to devote further research and policy attention towards the long-term impacts of the program by analyzing the educational and labor market outcomes of later cohorts, captured in the SUPAS 2005 and 2015 polls. On the basis of these results it will be necessary to identify and study potential policy remedies to overcome the tremendous challenges Indonesia’s education system faces.
Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2015. The project is a required component of every master program.
Authors: Genevieve Jeffrey, Yi-Ting Kuo, Laura López and Stella Veazey
Economics of Public Policy
We examine the effect of income on birth weight by employing two identification strategies using US Vital Statistics Natality data. First, following a study by Hoynes et al. (2015), we take advantage of an exogenous increase in income from the Earned Income Tax Credit using a difference-in-differences methodology. The Earned Income tax credit (EITC), enacted in 1975, is a refundable transfer to lower-income working families through the tax system and is one of the primary tools used in the United States to fight poverty. The EITC underwent an expansion is 1993 (Omnibus Budget Reconciliation Act), increasing the maximum credit families with and without children could receive. Following Hoynes et al. (2015), we take advantage of the difference in maximum credit available for families with different numbers of children. We find that the increase from the EITC reduces the incidence of low birth weight and increases mean birth weight. In addition, we discover that maternal smoking and drinking behavior during gestation is reduced.
Next, in order to try to capture the effect of income on birth weight across the population (as opposed to just high-impact groups), we exploit income variation from a policy change in Alaska that allowed payments from oil wealth to be distributed to all Alaska residents. We employ a comparative case study methodology using a synthetic control group following Abadie et al. (2010). Our comparison group is comprised of a combination of North Dakota, Oregon, Delaware, Kentucky and Nevada. The analysis shows a substantial increase in Alaska’s average birth weight over its synthetic counterpart around the onset of the policy. However, we refrain from attributing the divergence to the dividend payments alone, given significant changes in Alaska’s economy that coincide with the policy and are not well-mirrored by the control states.
Adam Aten ’13 (Health Economics and Policy) is a researcher at The Brookings Institution focusing on evidence development and biomedical innovation within the Center for Health Policy. Prior to joining Brookings, he was a civil servant at the U.S. Department of Health and Human Services developing policy expertise in health insurance for low-income populations, digital information systems and information governance, and cost effectiveness of public health programs.
This week he has written a post for the World Bank’s Investing in Health blog on universal health coverage (UHC). Here are some excerpts:
Decision-makers now have many tools at their disposal to analyze trends and take strategic decisions – increasingly in real-time – thanks to the rapid diffusion and adoption of information and communications technologies. New approaches to collect, manage and analyze data to improve health systems learning, such as how the poor are benefitting (or not) from health care services, are helping to ensure the right care is given to the right patient at the right time, every time – the goal of UHC.
It is relatively easy to agree on public health targets, but actual progress requires a management structure supported by dashboards that can allow monitoring of intermediate outcomes in real-time.
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