Category: Economics

Environmental Investment Tax Incentive Reform in Spain: a Lost Opportunity?

Nada es Gratis article by Kinga Tchórzewska ’15 (Economics)

Photo by Clayton Cardinalli on Unsplash

Editor’s note: this article was originaly published in Spanish in the popular economics blog, Nada es Gratis, and is based on Kinga Tchórzewska’s PhD from the University of Barcelona. Her Job Market Paper was honorably mentioned in the third annual Nada es Gratis Job Market Paper awards.

Firms are often reluctant to invest in green technology. As for the reason why – they point to high fixed costs and the resulting capital market failure. However, instruments that could possibly address this problem, such as environmental investment tax incentives, are not very popular among regulators – even though they may offer an interesting alternative to environmental taxation or even investment subsidies, since tax incentives are easier to implement at the administrative level. Could Environmental Investment (EI) tax incentives be successful at encouraging green investment? And how do firms react to the modifications in existing EI tax credits with respect to employment and innovation decisions? I try to tackle those questions using the EI tax credit reform in Spain.

Spanish Environmental Investment (EI) Tax Credit

Spain is a very interesting country in which to study a large-scale national tax incentive program because the EI tax credit went through some unusual transformations over the years of its existence. The specific EI tax incentive analyzed in this paper was first introduced in 1996 at 10% of the firm’s level of investment and survived in such form until 2006, when its slow phase-out was announced. The phase-out was implemented as the then government believed that the tax incentive was mostly financing end-of-pipe technologies (which do not affect the production process but purely reduce the pollution level at the end of the production line e.g. filters and sulphur scrubbers) rather than cleaner production technologies, very often required by law already. The phase-out was then successfully continued until tax credit’s complete elimination in January 2011. Unexpectedly, in March of 2011, this tax credit was re-introduced for 4 more years at the stable rate of 8% investment level. It was possibly done to mediate the effect of the financial crises on the industrial sectors. Figure 1. shows the chronology of events and the expected versus actual rates of the tax credit.

What makes this EI tax credit reform especially interesting is that it generated a lot of confusion until the very last moment and while introduced in March 2011 – it was done specifically with the intention to favor cleaner production over end-of-pipe technologies. In the analysis, I focus on industrial firms as the main beneficiaries of the program and consider the time period between 2008 and 2014. In the first part, I compare firms’ behavior before and after the change in this policy instrument using difference-in-difference analysis. This will show if the modification of the tax credit discouraged end-of-pipe technologies as well as how the policy reform affected green employment. In the second part of the analysis, by using instrumental variable approach with difference-in-difference, I examine the proportionate effect of an increase in the amount of the tax credit. I study its proportional effect on firms’ investment, employment and R&D outcomes. Thus, I perform the first quasi-experimental econometric analysis of the effectiveness of EI tax credit at encouraging adoption of green technologies directly, but also indirect green employment and green R&D effects.

Results

I find evidence that firms did in fact decrease their investment through the tax credit in the end-of-pipe technologies as a result of the policy change. This also includes the technologies specifically reducing air-pollution alone such as filters/sulphur scrubbers. We can, therefore, conclude that the modification was implemented quite successfully. That being said, there is no evidence to support the claim that this policy change led to an increase in the investment in cleaner production technologies. Unfortunately, the policy change also had a few unexpected indirect effects. It appears that firms reduced the number of green employees as well as the expenditure associated with the salaries of green employees, as can be seen in Figures 2a and 2b.

After performing the heterogeneous analyses, it is also clear that firms responded differently depending on their size – Figures 3a and 3b. More specifically, small firms seem to have benefited the most from the policy change, by considerably increasing their investment in cleaner production technologies. The opposite has happened to the large firms, who decreased their investment in the cleaner production technologies through the modified tax incentive.

By studying the proportional effect of the EI tax credit on investment outcomes it becomes apparent that Spanish environmental investment tax incentive was generally successful at inducing all types of green investment. This means that even during times of financial crises tax credit was drove firms’ green investment. However, they favored air-pollution-reducing over energy-efficient technologies, not necessarily end-of-pipe over cleaner production technologies, as per the concern of the government at the time. Additionally, I find further evidence that the increase in the amount of environmental investment tax credit results in a proportionate increase in the number of green employees and even private environmental R&D. Those indirect effects are quite hopeful, showing that a successful EI tax credit can also drive employment and create positive externalities through R&D.

Policy

This analysis provides a multitude of important implications for policy makers. Firstly, it encourages the usage of EI tax credits, which is also in agreement with previous literature, especially the work done by Ohrn (2019). However, this is in stark contrast to the decision of the Spanish government to eliminate this fiscal incentive from the Spanish Corporate Income Tax completely. This analysis supports its continuous use and perhaps even further modification, rather than a complete phase-out.

What we can learn from this green tax incentive is quite straightforward – adopting green depreciation incentives leads to increased business incentives and green employment outcomes, even during times of economic downturn. Additionally, the government can be successful at modifying the existing tax incentives, such that they discourage those technology choices that the central government considers undesirable. While the results clearly indicate that the tax credit should have been redefined even further so as to also encourage more investment in cleaner production technologies, this empirical work does not justify its complete phase-out. The fact that there is an increased investment in cleaner production technologies for smaller firms is also very important, as those are exactly the companies frequently faced with capital market failure – especially in the time of financial recession such as this one.

Of course, more research is needed to assess whether these types of incentives are the most efficient way to improve firms’ economic outcomes, and how the tax credit also affected their employees over the short- and long-run – especially after the complete elimination of the tax credit in 2015. Lastly, even given the financial burden that tax deductions and subsidies entail, they might still be economically justified in some cases. For instance, when positive externalities appear, such as increased green private R&D, which is the case here.

References

Ohrn, E. (2019). The effect of tax incentives on US manufacturing: Evidence from state accelerated depreciation policies. Journal of Public Economics, 180, 104084.

Connect with the author

Kinga B. Tchórzewska ’15 is a Postdoctoral Researcher at the ZEW – Leibniz Centre for European Economic Research. She is an alum of the Barcelona GSE Master’s in Economics.

This post was edited by Ashok Manandhar ’21 (Economics).

Is the COVID-19 pandemic a consumption game changer?

Research co-authored by Alex Hodbod ’12 (ITFD) and Steffi Huber ’10 (Economics)

The CEPR journal on Covid Economics recently included the paper, “Is COVID-19 a consumption game changer? Evidence from a large-scale multi-country survey” by Alexander Hodbod ’12 (ITFD), Cars Hommes, Stefanie J. Huber ’10 (Economics), and Isabelle Salle.

Steffi gave an interview to CEPR’s Tim Phillips about the team’s research:

Policies to avoid zombification of the economy

In an accompanying VoxEU column, the authors discuss the risks that government responses to COVID-19 could “zombify” the economy.

“A representative consumer survey in five EU countries indicates that many consumers do not miss certain goods and services they have cut down on since the COVID-19 outbreak,” the authors explain in their column. “Fiscal policy must recognise that some firms will become obsolete in the altered post-COVID-19 environment. To achieve a swift recovery, these obsolete firms must be allowed to fail fast so that resources can be reallocated to more efficient uses. Instead, fiscal support should be laser-like in targeting those households who are particularly hard hit by the crisis. Such support should be oriented towards helping displaced workers retrain and find new jobs.”

Read the VoxEU column

Paper abstract and download

Prospective economic developments depend on the behavior of consumer
spending. A key question is whether private expenditures recover once
social distancing restrictions are lifted or whether the COVID-19 crisis
has a sustained impact on consumer confidence, preferences, and, hence,
spending. Changes in consumer behavior may not be temporary, as they
may reflect long-term changes in attitudes arising from the COVID-19
experience. This paper uses data from a representative consumer survey
in five European countries conducted in summer 2020, after the release
of the first wave’s lockdown restrictions. We document the underlying
reasons for households’ reduction in consumption in five key sectors:
tourism, hospitality, services, retail, and public transports. We identify
a large confidence shock in the Southern European countries and a
permanent shift in consumer preferences in the Northern European
countries. Our results suggest that horizontal fiscal support to all firms
risks creating zombie firms and would hinder necessary structural
changes to the economy.

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Connect with the authors

  • Alexander Hodbod ’12 (International Trade, Finance, and Development). Counsellor to ECB Representative to the Supervisory Board, European Central Bank (DGSGO-SO), Frankfurt, Germany.
  • Cars Hommes. Professor of Economic Dynamics at CeNDEF, Amsterdam School of Economics, University of Amsterdam, and research fellow of the Tinbergen Institute, Amsterdam, The Netherlands, Senior Research Director (Financial Markets Department), Bank of Canada.
  • Stefanie J. Huber ’10 (Economics). Assistant Professor at CeNDEF, Amsterdam School of Economics, University of Amsterdam, and research candidate fellow of the Tinbergen Institute, Amsterdam, The Netherlands. 
  • Isabelle Salle. Principal Researcher at the Bank of Canada (Financial Markets Department), research fellow at the Amsterdam School of Economics, University of Amsterdam, and research fellow of the Tinbergen Institute, Amsterdam, The Netherlands. 

Does Air Pollution Exacerbate Covid-19 Symptoms? Evidence from France

Economics master project by Mattia Laudi, Hubert Massoni, and James Newland ’20

The Eiffel Tower under a dark red sky
Image by Free-Photos from Pixabay

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Abstract

For patients infected by Covid-19, underlying health conditions are often cited as a source of increased vulnerability, of which exposure to high levels of air pollution has proven to be an exacerbating cause. We investigate the effect of long-term pollution exposure on Covid-19 mortality, admissions to hospitals and admissions to intensive care units in France. Using cross-sectional count data at the local level, we fit mixed effect negative binomial models with the three Covid-19 measures as dependent variables and atmospheric PM2.5 concentration (µg/m3) as an explanatory variable, while adjusting for a large set of potential confounders. We find that a one-unit increase in PM2.5 concentration raised on average the mortality rate by 22%, the admission to ICU rate by 11% and the admission to hospital rate by 14% (rates with respect to population). These results are robust to a large set of sensitivity analyses. As a novel contribution, we estimate tangible marginal costs of pollution, and suggest that a marginal increase in pollution resulted on average in 61 deaths and created a 1 million euro surcharge in intensive care treatments over the investigated period (March 19th – May 25th).

A map of air pollution and a map of Covid deaths in France

Conclusions

The study is a strong indication that air pollution is a crucial environmental factor in mortality risks and vulnerability to Covid-19. The health risks associated with air pollution are well documented, but with Covid-19 in the spotlight we hope to increase awareness of the threat caused by pollution, not only through direct increased health risks, but also through external factors, such as pandemics.

We show the aggravating effect of long-term pollution exposure to three levels of severity of Covid-19 symptoms in France: admission to hospitals for acute Covid-19 cases, admission to intensive care units for the most severe vital organ failures, and fatalities (all expressed per 100,000 inhabitants). Using cross-sectional data at the départemental (sub-regional) level, we fit mixed effect negative binomial models with the three Covid-19 measures as dependent variables and the average level of atmospheric concentration of PM2.5 (µg/m3) as an explanatory variable. We adjust for a set of 18 potential confounders to isolate the role of pollution in the spread of the Covid-19 disease across départements. We find that a one-unit increase in average PM2.5 levels increases on average the mortality rate by 22%, the admission to ICU rate by 11% and the admission to hospital rate by 14%. These results are robust to a set of 24 secondary and sensitivity analyses per dependent variable, confirming the consistency of the findings across a wide range of specifications.

We further provide numerical – and hence more tangible – estimates of the marginal costs of pollution since March 19th. Adjusting for under-reporting of Covid-19 deaths, we estimate that long-term exposure to pollution marginally resulted in an average 61 deaths across French départements. Moreover, based on average daily costs of intensive care treatments, we estimate that pollution induced an average 1 million euros in costs borne by hospitals treating severe symptoms of Covid-19. These figures strongly suggest that areas with greater air pollution faced substantially higher casualties and costs in hospital services, and raise concerns about misallocation of resources to the healthcare system in more polluted areas.

Our paper provides precise estimates and a reproducible model for future work, but is limited by the novelty of the phenomenon at the centre of the study. Our empirical investigation is restricted to the scope of France alone due to cross-border inconsistencies in Covid-19 data collection and reporting. Once Covid-19 data reporting is complete and consistent, we hope future studies will examine the effects of air pollution at a greater scale, or in greater detail. On the other hand, more disaggregated data – at the individual or hospital level – would allow more precise estimates and a better understanding of key factors of Covid-19 health risks and would also allow the use of surface-measured air pollution. Measured pollution data is available for France, but is inherently biased when aggregated at the départemental level, due to lack of territorial coverage. If precise data tracking periodic Covid-19 deaths becomes available for a wider geographic region, we specifically recommend a MENB panel regression incorporating a PCFE for spatially correlated errors. This will produce the most accurate estimates.

Going forward, more accurate and granular data should motivate future research to uncover the exact financial costs attributable to air pollution during the pandemic. Precise estimation of costs of Covid-19 treatments and equipment (e.g. basic protective equipment for personnel or resuscitation equipment), should feature in a more accurate cost analysis. Hospital responses should be thoroughly analysed to understand the true cost of treatments across all units.

It is crucial that the healthcare costs of pollution are globally recognised so that future policy decisions take them into account. Ultimately, this paper stresses that failure to manage and improve ambient air quality in the long run only magnifies future burdens on healthcare resources, and cause more damage to human life. During a global pandemic, the costs of permitting further air pollution appears ever more salient.

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About the BSE Master’s Program in Economics

The importance of norms for development

Essay by Oguz Korkut Keles ’20 (Economics)

Photo by Anthony Garand on Unsplash

The relationship between institutions and development is a long-standing topic in economic research. However, economists have tended to only evaluate formal institutions (such as laws and property rights), neglecting the informal (like conventions and norms). This overspecialisation precludes the analysis of ideas and ideologies. Without considering these abstract drivers of development, the space for ethically and politically dangerous explanations of success appears (such as for genetic reasons).

Contrary to recent literature, I argue that informal constraints are actually the basis of institutions and therefore the real generators of growth and development. I show this by examining revolutions – the cauldrons where new systems, ideas, and conventions begin, and old ones end.

The illusion of separation

Scholars of comparative development have noted the increasing divergence between developed and developing countries: the gap between Northern and Southern Europe and the underdevelopment of the Middle East and sub-Saharan Africa being major examples. Several theories attempt to explain this divergence, considering possible factors such as geographical characteristics and institutional differences. Notably, comparative development has even been attributed to levels of genetic diversity (Ashraf & Galor, 2013).

In particular, the crucial historical link between institutions and development is well known. Famous examples include the advantage of limited royal power (Acemoglu, 2005); reformed constitutional arrangements and strengthened property rights (North & Weingast, 1989); and the balance of power between merchants and princes (De Long, 1993). Yet, these studies put their emphasis on formal rules, neglecting the norms, ideas and ideologies that underwrite them.

The latter are fundamental elements of institutions as they influence formal rules. In a seminal contribution to institutional economics, North (1994) distinguishes between two forms of institutions: formal rules (constitutions, laws, property rights etc.) and informal constraints (norms of behaviour, conventions, self-imposed codes of conduct etc.). In a later work, he argued that institutions evolve incrementally and successively over time (North, 1991). When those two forms are approached as two separated sources of institutions, the role of informal constraints in institutional evolution will be missed, throwing a veil over a core aspect of institutions and leading us to fallacious conclusions about the key determinants of growth and development.

Similarly, Karl Popper (1945) distinguishes an open society from a closed society based on whether a distinction exists between normative laws and natural laws. Where there is none – what Popper calls a closed “tribal society”– taboos and conventions act as if they were natural law. This gives them a powerful role in society and a fundamental role in development. By creating formal laws, societies recognise the distinction between norms and natural laws, weakening the effect of conventions (although, as we will see, they still act through both formal and informal laws).

Both North and Popper agree on this chronological development of institutions meaning a better understanding of causation is needed. Myrdal (1978) convincingly argues that the mechanisms of social systems are determined by an endogenous cycle of causation that affects the distribution of power in a society and economic, social and political stratification). This means that a change in informal constraints will alter formal rules, which will then return to affect the former. Therefore the scaffolding of institutions consists of norms of behaviour, conventions and self-imposed codes of conduct.

The revolutionary crevasse

Just as a crevasse provides a glimpse deep into the ice, revolutions open a window to the creation and destruction of social systems. Revolutions are beloved by social scientists (especially in institutional economics) as they provide natural experiments to investigate causal effects. They can shed some light on the importance of norms and convention, as well as their relationship with ideas, ideologies and leaders.

In the literature, for example, Acemoglu et al. (2008) and North & Weingast (1989) have respectively examined the impact of the French Revolution on development and the Glorious Revolution on institutional structure. However, these types of studies have focused only on the secondary changes (in laws and property rights) instead of the initial causes of change (norms and conventions). In this regard, a re-evaluation of revolutions and their characteristics is necessary to observe the initial changes.

Let us first consider which elements prepare amenable conditions for the emergence of revolutions. Gottschalk (1944) identifies three broad factors:

  1. demand for change stemming from (a) personal discontent and (b) social dissatisfaction
  2. hopefulness derived from (a) popular programs of reform and (b) a leader
  3. weakness of the conservative forces – perhaps the most important.

Demand comes from widespread provocations (corruption, taxation, poor infrastructure etc.) which generate social dissatisfaction. Yet, demand by itself is not sufficient for the revolution. Some hope of success is also needed. This comes from programs of reform, as provided by the Voltaires and Rousseaus, the Lockes and Ademses, and the Marxes and Kropotkins (Gottschalk, 1994). However, tuneless emphasis on widespread provocations that are based on the formal rules underestimates the phycological mechanisms that are mainly based on informal constraints.

Personal discontent (arising for idiosyncratic reasons) only appears at the individual level yet plays an essential role in generating the leaders of revolutions. These leaders then support the new-born ideas and ideologies based on the program of reform which has a multiplier effect by coherently spreading revolutionary sentiment. This is crucial once we think of revolutions as risky events over which individuals have varying valuations of the possible outcomes.  Gneezy et al. (2006) show that individuals, faced with a complex choice, may choose to stay in the old system if they value the risky benefits of revolution less than the worst outcomes of rebelling. However, once the revolutionary “lottery” is based on intellectuals’ programs of reforms and explained by leaders it becomes easier to code.

In this way, agents facing complex task (in this case revolution), might act following the leader through many of the channels identified by behavioural economics such as Tversky and Kahneman’s simple heuristics, Walker and Wooldridge’s conventions and Shiller’s narratives. These share common features which affect the majority’s decision-making processes – especially when tasks are complex.

This process is essential to notice the importance of informal constraints and how they become formal rules since leaders are the symbol of ideologies and ideas. As Axelrod indicates norms precede laws and laws strengthen norms. After the success of the revolution laws strengthen the norms through formalization. And after social conventions are entrenched, they become thoughtlessly accepted by individuals (Epstein, 2001).

As with the example of revolutions, before a change in the formal rules, an ideological revolution has occurred when intellectuals provide the programs of reforms. The ideas become conventions during the revolution, changing societal expectations. Notions of equality and liberty – in the case of the French Revolution – became the convention as the system was upended. The relationships between ideas, ideologies, norms and leaders encourage us to take them into account when evaluating growth and development.  

Conclusion

I have argued that ideas, norms and ideologies are the initial drivers of development and have had an immense effect on our civilizations. However, traditional political economy’s overemphasis of formal rules fails to capture this. The insularity of this approach is highlighted by examining Revolutions, which provide evidence in favour of more inclusive definitions of institutions and the importance of ideas, ideologies and leaders in creating social systems. Therefore, I contend that a more holistic approach to analysing development is required otherwise alternative and ill-founded explanations of growth with remain.

References

Acemoglu, D., Cantoni, D., Johnson, S., & Robinson, J. A. (2008). From ancien regime to capitalism: the French Revolution as a natural experiment. Natural Experiments…, op. cit, 221-256.

Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). The rise of Europe: Atlantic trade, institutional change, and economic growth. American Economic Review, 95(3), 546-579.

Ashraf, Q., & Galor, O. (2013). The ‘Out of Africa’ hypothesis, human genetic diversity, and comparative economic development. American Economic Review, 103(1), 1-46.

Axelrod, R. (1986). An evolutionary approach to norms. The American Political Science Review, 1095-1111.

De Long, J. B., & Shleifer, A. (1993). Princes and merchants: European city growth before the industrial revolution. The Journal of Law and Economics, 36(2), 671-702.

Epstein, J. M. (2001). Learning to be thoughtless: Social norms and individual computation. Computational economics, 18(1), 9-24.

North, D. C. (1991). Institutions. Journal of Economic Perspectives, 5(1), 97-112.

North, D. C. (1994). Economic performance through time. The American Economic Review, 84(3), 359-368.

North, D. C., & Weingast, B. R. (1989). Constitutions and commitment: the evolution of institutions governing public choice in seventeenth-century England. The Journal of Economic History, 49(4), 803-832.

Popper, K. R. (1945). The open society and its enemies. Routledge, London.

Myrdal, G. (1978). Institutional economics. Journal of Economic Issues, 12(4), 771-783.

Gottschalk, L. (1944). Causes of revolution. American Journal of Sociology, 50(1), 1-8.

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Oguz Kortut Keles ’20 is an alum of the Barcelona GSE Master’s in Economics.

This post was edited by Ashok Manandhar ’21 (Economics).

Can adjustment costs of intangible capital explain the decline in the labor share?

Economics master project by Pierre Coster, Pia Ennuschat, Raquel Lorenzo, Giacomo Stazi, and Robert Wojciechowski ’20

Two tiny figurines of construction workers stand on an asphalt road

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Abstract

Labor share, once thought to be a constant, has experienced a secular decline in many developed economies. We investigate whether adjustment costs to intangible capital can be used to explain this trend. We develop a simple partial equilibrium model with a profit maximizing firm that produces using a three factor CES production function and faces convex adjustment costs to intangible capital. We find an intuitive expression for the steady state labor share as a function of parameters and the steady state level of investment in intangible capital.

We then run simulations to better understand the behaviour of the labor share in our model. Somewhat surprisingly, we find that adjustment costs do not affect the steady state labor share for any given elasticity of substitution. However, their presence creates a strong relationship between the labor share and the elasticity of substitution. We also find a number of short-run dynamics that are affected by the level of adjustment costs.

chart
Labor share trends over the last 60 years in the United States. Source: AMECO

Conclusions

We find that our model with adjustment costs leads to a very clear relationship between the elasticity of substitution and the labor share. Therefore, one could use it to explain the secular decline in the labor share as a result of a falling elasticity of substitution in presence of convex adjustment costs to intangible capital. However, in our simple model there does not appear to be a meaningful relationship between the level of convex adjustment and the steady state labor share. Moreover, adjustment costs affect a number of interesting short-run dynamics. The level of adjustment costs changes the responsiveness of the labor share to variations in the price of inputs. Lastly in our simple model the volatility of the price process does not alter the steady state labor share, even though it does matter for short-run dynamics.

We see room for further research in the following directions. Our analysis assumes perfectly competitive markets. A model of monopolistic competition in the goods market could lead to long-run effects of the level of adjustment costs on the labor share. Karabarbounis and Neiman, 2013 showed that in such a model price decreases can explain part of the decrease in the labor share. Therefore, analysing the effect of adjustment costs in the context of monopolistic competition seems promising. Another potential avenue is the generalization of the analysis to a general equilibrium setting.

Understanding endogenous changes in wages that were set to be fixed throughout our analysis, could be important in explaining the changes in the labor share.

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Broadstreet: a blog for inter-disciplinary conversation about Historical Political Economy

Vicky Fouka ’10 (Economics) is an editor of this new meeting point for HPE researchers

A map shows the original location of the Broad Street Pump

About the project

Broadstreet is a blog dedicated to the study of historical political economy (HPE). Its goal is to foster conversations across disciplines in the social sciences, namely economics and political science, but also history, sociology, quantitative methods, and public policy. Correspondingly, its editors (and guest contributors) are drawn from these respective disciplines. 

Given the boundaries that typically exist across academic disciplines, scholars who work on similar subjects – like HPE – rarely talk to one another or read each other’s work. Our hope in starting Broadstreet is to break down some of these artificial boundaries, generate true cross-disciplinary dialogues, and produce better and more wide-ranging HPE research.

The blog’s name, Broadstreet, is a nod to the legendary John Snow and his study of the 1854 cholera outbreak in London. Snow found convincing evidence for a previously unproven water-born theory of cholera transmission, with a rigorous yet interdisciplinary approach — using detailed socio-economic data, ethnography, historical patterns of disease transmission, and early techniques of causal inference. The Broad Street water pump in London’s Soho district was not only a meeting place for the diverse residents of the neighborhood, but served as the focal point for Snow’s interdisciplinary breakthrough. While the Broad Street pump is no more, the legacy of this innovative research lives on. We hope that Broadstreet will be go-to location for all those with interests in HPE.

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Vicky Fouka ’10 (Economics) is Assistant Professor of Political Science at Stanford University. She is an alum of the Barcelona GSE Master’s in Economics and earned her PhD in Economics at GPEFM (UPF and Barcelona GSE).

Check out her most recent post on Broadstreet, “The Great Northward Migration and Social Transformation, Part I” which looks at the mass exodus of more than 5 million Black Americans from the Southern United States between 1915 and 1970.

Read the post on Broadstreet

Eliciting preferences for truth-telling in a survey of politicians

Publication in PNAS by Katharina Janezic ’16 (Economics) and Aina Gallego (IBEI and IPEG)

logo

Honesty is one of the most valued traits in politicians. Yet, because lies often remain undiscovered, it is difficult to study if some politicians are more honest than others. This paper examines which individual characteristics are correlated with truth-telling in a controlled setting in a large sample of politicians. We designed and embedded a game that incentivizes lying with a non-monetary method in a survey answered by 816 Spanish mayors. Mayors were first asked how interested they were in obtaining a detailed report about the survey results, and at the end of the survey, they had to flip a coin to find out whether they would be sent the report. Because the probability of heads is known, we can estimate the proportion of mayors who lied to obtain the report.

We find that a large and statistically significant proportion of mayors lied. Mayors that are members of the two major political parties lied significantly more. We further find that women and men were equally likely to lie. Finally, we find a negative relationship between truth-telling and reelection in the next municipal elections, which suggests that dishonesty might help politicians survive in office.

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6 Real Policy Solutions to the U.S. Mental Health Crisis

Article by Patricia Paskov ’18 (Economics) on Medium

In a post on Medium’s Elemental, Patricia Paskov outlines six mental health policy recommendations for the United States during Covid-19 and beyond:

  • Destigmatize mental health
  • Widen accessibility of mental health care
  • Break down barriers to telehealth care
  • Strengthen labor policies for low-skilled workers
  • Build a body of rigorous data and research
  • Harness artificial intelligence and predictive analytics
Read the article on Medium

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Patricia Paskov ’18 is an Impact Evaluation Analyst at The World Bank. She is an alum of the Barcelona GSE Master’s in Economics.

The Impact of the Sharing Economy on Housing Rental Prices: The Case of Airbnb in Barcelona

Economics master project by Marc Agustí, Magnus Asmundsson, Christof Bischofberger, Pablo de Llanos, Alberto Font, and Lucía Kazarian ’20

Source: Airbnb

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Peer-to-peer home-sharing platforms such as Airbnb are a new phenomenon which many researchers consider to be responsible for significant disruptions in the housing market. Prior to the introduction of these platforms into the rental market, hotels were the primary supplier of short-term rentals, while residential properties almost exclusively operated on the long-term rental market. The introduction of short-term rental platforms like Airbnb, allows homeowners to choose either to supply on the short-term or the long-term rental markets. As a result, when residential properties are moved to the short-term rental market, the quantity of housing supplied on the long-term rental market decreases, inducing an upward pressure on long-term rents.

In our paper, we offer a novel approach to investigate the extent to which the expansion of the sharing economy is responsible for increases in long-term rents and prices on the housing market. To this end, we construct a theoretical framework for the housing market that allows for spillover effects between neighborhoods, and other local externalities caused by tourism. The model allows for the short-term housing market devoted to tourism to impact both long-term rental rates and housing prices. Using a panel of quarterly data on newly signed rental contracts and transaction prices in Barcelona from 2015-Q2 to 2018-Q4, we implement a fixed-effects spatial 2SLS method allowing for endogeneity in the variable which measures the presence of Airbnb.

figure
Airbnb listings in Barcelona (2018-Q2)

Barcelona, which hosts the sixth largest concentration of Airbnb listings in the world, serves as a prime case study to investigate these effects because our dataset covers growth rates in contractual rental rates, transaction prices and the number of active Airbnb listings of 27.42%, 27.41% and 29.38%, respectively.

Key results

The theoretical model predicts that a change in the level of Airbnb activity might affect both long-term rents and housing prices. In fact, if negative externalities generated by tourists are sufficiently small, Airbnb leads to increases in long-term rental prices. Yet, these effects ultimately depend on the values of parameters such as the size of the stock of housing units and the level of externalities emerging from tourism. In addition, the model bears upon the effects of Airbnb on gentrification and displacement: we find that for a positive increase in the negative externalities generated by tourism, the proportion of homeowners renting in the short-term market will increase. As the degree to which residents are harmed by negative externalities increases, more of them will decide to abandon their neighborhood, reducing the local demand for long-term housing. As a result, rents will suffer a downward pressure, increasing the relative profitability of the short-term rental market for homeowners. Besides, this effect will be aggravated if the degree of inter-neighborhood dependence generated by externalities is high. Residents will be prone to move to other neighborhoods in which not only the presence of Airbnb is low, but also in which the penetration of this marketplace is low in the surrounding areas.

We refer to this process as Airbnb-induced gentrification. Similarly, if the profitability of renting a property on Airbnb increases, a similar process as the one we have just described above would arise, which would also lead to gentrification.

For another thing, our main empirical results show that Airbnb positively and significantly affects rents, even when accounting for spatial dependence and inter-neighborhood spillovers. In a given neighborhood (as classified in this paper), for every additional 100 Airbnb listings, rents increase by an average of 2.1% when indirect spillovers coming from adjacent neighborhoods are included. In particular, the direct effect of Airbnb within a given neighborhood accounts for much of this effect: the own-neighborhood effect is to induce a 1.7% increase in rents. The maximum average indirect effect found in the sample data accounts for 35% of the total effect. The implications of these findings are far reaching and suggest that spillover effects can indeed explain a large portion of rent increases. Likewise, we identify a potential bias in the previous literature in that the total effect is falsely interpreted as the direct effect, thereby misinterpreting the direct effect of Airbnb on long-term rents.

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Empirical Results: Main Impact Measures

In contrast, our empirical results show that Airbnb has had no significant effect on transaction prices. The most plausible explanation for the non-significant results for prices is that homeowners do not believe that Airbnb is sustainable in the long-run, and therefore they do not adjust their predicted future cash flows when valuing their properties.

Finally, we believe that future research could delve into more detailed theoretical models, especially with respect to the price setting by homeowners in light of the establishment of Airbnb. Additionally, we think that making a distinction between direct and indirect neighborhood effects is vital in order to truly understand the dynamics of the housing markets, especially in the growing metropoles. Accordingly, we encourage scholars to further apply and develop spatial econometric methods that measure indirect spillover effects in studies related to housing markets.

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Industrial Robots and Where to Find Them: Evidence and Theory on Derobotization

Economics master project by Amil Camilo, Doruk Gökalp, Julian Klix, Daniil Iurchenko, and Jeremy Rubinoff ’20

An abandoned factory robot
Image by Peter H from Pixabay

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Around the world, and especially in high-tech economies, the demand and adoption of industrial robots have increased dramatically. The abandonment of robots (referred to as derobotization or, more broadly, deautomation) has, on the other hand, been less discussed. It would seem that the discussion on industrial robots has rarely been about their abandonment because, presumably, the abandonment of industrial robots would be rare. Our investigation, however, shows that the opposite is true: not only do a substantial number of manufacturing firms deautomate, a fact which has been overlooked by the literature, but the reasons for which they deautomate are highly multi-dimensional, suggesting that they depend critically on the productivity of firms and those firms’ beliefs about robotization.

Extending the analysis of Koch et al. (2019), we use data from SEPI Foundation’s Encuesta sobre Estrategias Empresariales (ESEE), which annually surveys over 2000 Spanish manufacturing firms on business strategies, including on whether they adopt robots in their production lines. We document three major facts on derobotization. First, firms that derobotize tend to do so quickly, with over half derobotizing in the first four years after adoption of robots. Second, derobotizing firms tend to be relatively smaller than firms which stay automated for longer periods of time. Third, firms that abandon robots demand less labor and increase their capital-to-labor ratios. The prompt abandonment of robots, we believe, is indicative of a learning process in which firms robotize production with expectations of higher earnings, but later learn information which causes them to derobotize and adjust their production accordingly.

With this in mind, we propose a dynamic model of automation that allows firms to both adopt robots and later derobotize their production. In our setup, firms face a sequence of optimal stopping problems where they consider whether to robotize, then whether to derobotize, then whether to robotize again, and so on. The production technology in our model is micro-founded by the task-based approach from Acemoglu and Autor (2011). In this approach, firms assign tasks to workers of different occupations as well as to robots in order to produce output. For simplicity, we assume two occupations, that of low-skilled and high-skilled workers, where the latter workers are naturally more productive than the former. When firms adopt robots, the firm’s overall productivity (and the relative productivity of high-skilled workers) increases, but the relative productivity of low-skilled workers decreases. At the same time, once firms robotize they learn the total cost of maintaining robots in production, which may exceed their initial expectations. At any point in time, firms can derobotize production with the newfound knowledge of the cost. Likewise, firms can reautomate at a lower cost with the added assumption that firms retain the infrastructure of operating robots in production.

The simulations of our model can accurately explain and reproduce the behavioral distribution of automation across firms in the data (see Figure 1). Indeed, we are able to show that larger and more productive firms are more likely to robotize and, in turn, the firms which derobotize tend to be less productive (referred to as the productivity effect). However, the learning process which reveals the true cost of robotized production (referred to as the revelation effect) also highlights the role of incomplete information as a plausible explanation for prompt abandonment.  Most importantly, our simulations suggest that analyses which ignore abandonment can overestimate the effects of automation and, therefore, must be incomplete. 

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Figure 1: The distribution (left) of firms by robotization behavior, and the distribution (right) of firms’ derobotization behavior (if they derobotize). The data from ESEE is in gray, while the calibrated simulation of our model is in blue.

Our project is the first, to our knowledge, to document the pertinent facts on deautomation as well as the productivity effect and the revelation effect. It is apparent to us, based on our investigation, that any research seeking to model automation would benefit from modeling deautomation. From that starting point, there remains plenty of fertile ground for new questions and, consequently, new insights.

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