A displaced worker might rationally prefer to wait through a long spell of unemployment instead of seeking employment at a lower wage in a job he is not trained for. I evaluate this trade-off using micro data on displaced workers. To achieve identification, I exploit the fact that the more a worker has invested in occupation-specific human capital, the more costly it is for him to switch occupations and therefore the higher is his incentive to wait. I find that between 9% and 17% of total unemployment in the United States can be attributed to wait unemployment
Publication in Journal of Banking and Finance by Alex Hodbod (ITFD ’12) and Steffi Huber (Economics ’10, GPEFM ’17)
We have a forthcoming article “Sectoral Risk Weights and Macroprudential Policy” in the Journal of Banking & Finance with our co-author Konstantin Vasilev (Essex).
The authors!
Paper abstract
This paper analyses bank capital requirements in a general equilibrium model by evaluating the implications of different designs of such requirements regarding their impact on the tendency of banks to amplify the business cycle.
Interest rate spreads structure. This figure gives an overview of the different interest rate spreads within the model and the factors that affect them. The asset-specific interest rate spreads determine the borrowing costs of households and firms and hence the quantities of specific loan types in the economy.
We compare the Basel-established Internal Ratings-Based (IRB) approach to risk-weighting assets with an alternative macroprudential approach which sets risk-weights in response to sectoral measures of leverage. The different methods are compared in a crisis scenario, where the crisis originates from the housing market that affects the banking sector and is then transmitted to the wider economy.
Variance decomposition – real consumption during the Great Recession. This variance decomposition shows that the model identifies the productivity shock and the shock to mortgage lending risk to be the main drivers of the crash in real consumption during the Great Recession. In our model, the main channel through which the shock to mortgage risk has a procyclical effect on consumption is through lending and house prices.
We investigate both boom and bust phases of the crisis by simulating an unrealized news shock that leads to a gradual build-up and rapid crash in the economy. Our results suggest that the IRB approach creates procyclicality in regulatory capital requirements and thereby works to amplify both boom and bust phases of the financial cycle. On the other hand, our proposed macroprudential approach to setting risk-weights leads to counter-cyclicality in regulatory capital requirements and thereby attenuates the financial cycle.
Impulse Response Function – Unrealised news shock. Here, we model both the build-up and crash phases of the crisis and use this to examine how different policy approaches perform in handling the boom phase of the cycle. In periods 1-4 agents start with expectations that a housing boom will occur, but at period 4 a shock arrives as this boom does not materialise. At the top of the chart one sees that the policy setup based on the IRB approach (red) generates the biggest macroeconomic consequences from this shock; it is the most procyclical. The macroprudential approach to risk-weighting (in green) is the least procyclical. An unweighted “leverage ratio” approach (blue) is less procyclical than the IRB approach, but more so than our macroprudential approach.
Conclusions in brief
We show that IRB risk-weights can induce procyclicality of capital requirements and amplify both boom and bust phases of the business cycle. This is particularly concerning because procyclical risk weights could undermine other macroprudential tools, as these other tools are themselves based on risk-based measures of capital requirements e.g. Counter Cyclical Capital Buffers.
Our alternative approach of macroprudential
risk weights could induce countercyclicality of capital requirements, which may
offer benefits in terms of smoothening financial cycles. Targeting
macroprudential intervention on bank risk-weights is likely to be more
effective when it is sector-specific. This will alter banks’ incentives in a
sensitive way – thereby tending to attenuate sectoral asset booms.
The results complement the ongoing debate about the potential merits of a Sectoral Counter Cyclical Capital Buffer, which is ongoing internationally.
Stefanie J. Huber ’10 is Assistant Professor at the University of Amsterdam. She is an alum of the Barcelona GSE Master’s in Economics and GPEFM PhD Program (UPF and Barcelona GSE).
Forthcoming paper in Review of Economics and Statistics by Philipp Ager ’08 and Benedikt Herz ’08 (Economics)
Paper abstract
This paper provides new insights on the relationship between structural change and the fertility transition. We exploit the spread of an agricultural pest in the American South in the 1890s as plausibly exogenous variation in agricultural production to establish a causal link between earnings opportunities in agriculture and fertility. Households staying in agriculture reduced fertility because children are a normal good, while households switching to manufacturing reduced fertility because of the higher opportunity costs of raising children. The lower earnings opportunities in agriculture also decreased the value of child labor which increased schooling, consistent with a quantity-quality model of fertility.
A more in-depth summary of the paper is available in the VoxEU column “From the farm to the factory floor: How the structural transformation triggered the fertility transition.”
Philipp Ager ’08 is an Associate Professor of Economics, University of Southern Denmark and CEPR Research Affiliate. He is an alum of the Barcelona GSE Master’s in Economics.
Benedikt Herz ’08 is member of the Chief Economist’s Team, European Commission Directorate-General for Internal Market and Industry. He is an alum of the Barcelona GSE Master’s in Economics.
Empirical connections between local anti-Muslim hate crimes and international jihadi terror attacks are studied. Based upon rich administrative data from Greater Manchester Police, event studies of ten terror attacks reveal an immediate big spike up in Islamophobic hate crimes and incidents when an attack occurs. In subsequent days, hate crime is amplified by real-time media. It subsequently attenuates, but hate crime incidence cumulates to higher levels than prior to the series of attacks. The overall conclusion is that, even when they reside in places far away from where jihadi terror attacks take place, local Muslim populations face a media magnified likelihood of hate crime victimization following international terror attacks. This matters for community cohesion in places affected by discriminatory hate crime and, from both a policy and research perspective, means that the process of media magnification of hate crime needs to be better understood.
Publication in “Journal of Business & Economic Statistics” by
Gergely Ganics ’12 (with A. Inoue and B. Rossi)
Abstract
In this article, we propose methods to construct confidence intervals for the bias of the two-stage least squares estimator, and the size distortion of the associated Wald test in instrumental variables models with heteroscedasticity and serial correlation. Importantly our framework covers the local projections—instrumental variable model as well. Unlike tests for weak instruments, whose distributions are nonstandard and depend on nuisance parameters that cannot be consistently estimated, the confidence intervals for the strength of identification are straightforward and computationally easy to calculate, as they are obtained from inverting a chi-squared distribution. Furthermore, they provide more information to researchers on instrument strength than the binary decision offered by tests. Monte Carlo simulations show that the confidence intervals have good, albeit conservative, in some cases, small sample coverage. We illustrate the usefulness of the proposed methods in two empirical situations: the estimation of the intertemporal elasticity of substitution in a linearized Euler equation, and government spending multipliers.
Supplementary materials for this article are available online. The online appendix contains the proofs, further theoretical and Monte Carlo results, and the description of the datasets used in the present article. Replication code is available on the journal’s website.
Economics master project by Julie Balitrand, Joseph Buss, Ana Monteiro, Jens Oehlen, and Paul Richter ’19
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
We study the effects of the #BlackLivesMatter movement on the law abiding behavior of African-Americans. First, we derive a conceptual framework to illustrate changes in risk perceptions across different races. Second, we use data from the Illinois Traffic Study Dataset to investigate race ratios in police stops. For identification, we apply a linear probability OLS regression on media coverage as well as an event study framework with specific cases. We find that the number of black people committing traffic law violations is significantly reduced after spikes in media coverage and notable police shootings. In the latter case, we further find that the effect holds for an approximate ten day period. We argue that these observed changes in driving behavior are a result of the updated risk beliefs.
Game Tree. Balitrand et al.
Conclusions
Beginning with our model, we show that media related changes in risk perceptions cause a change in the proportion of people committing crimes. Using this model, we further predict that this change would be different across different racial groups. More specifically, it predicts that Blacks became more cautious in order to decrease the chance of a negative interaction with the police. On the other hand, whites were predicted to not change their behavior, since the violence in media coverage is not relevant to their driving decisions.
In order to test our model, we develop a hypothesis testing strategy that allows us disentangle police actions from civilian decisions. By considering the proportion of stopped people who are black at nighttime, we completely remove any effect caused by changes in policing intensity and bias. Instead, we create a testable hypothesis that only focuses on the differences in behavior between racial groups.
To test this hypothesis, we use a linear probability model along with traffic data from Illinois. We test the hypothesis using both an event study approach, as well as using media intensity data from the GDELT Project. Both approaches verify our model’s predictions with high significance levels. Therefore, we have shown that Blacks became more cautious in response to these events compared to other racial groups. In addition, our robustness check on the total number of stops supports the claim that non-blacks do not have a significant response to media coverage of police brutality toward Blacks. This leads to the conclusion that the expected proportion of Blacks breaking traffic laws goes down in response to coverage of these events.
An implicit assumption in our model was that as media coverage goes to zero, Blacks would revert back to their original level of caution. To test this we looked at three days intervals following each media event. We showed that after approximately 10 days, the coefficients were not significant anymore, showing that the media only caused a short term change in behavior. Since this was a robustness check, and not a main focus of our model, we did not investigate this further. This is an interesting conclusion, and warrants future analysis.
On a final note, we want to address the type of media we use for our analysis. Our model section considers media in a general sense. This can include, but is not limited to, social media platforms such as Twitter and Facebook, as well as more traditional media platforms such as television and print newspapers. All of these sources cover police brutality cases at similar intensities. We use TV data for media intensity, since it affects the broadest demographic and therefore best represents the average driver’s exposure to the topic. Different media age medians might affect different demographics more or less. For example, social media may have a greater effect on younger drivers than older drivers. We believes this topic warrants further analysis, in a addition to the topic of the previous paragraph.
Fall 2019 roundup of CaixaBank Research by Barcelona GSE alumni
It’s time once again to check in with Barcelona GSE Alumni who are now Economists and Senior Economists at CaixaBank Research in Barcelona. As part of their duties, they regularly publish working papers and reports on a range of topics. Below are some of their latest contributions.
(If you’re a Barcelona GSE alum and you’re also writing about Economics, Finance, or Data Science, let us know where we can find your stuff!)
Communication is one of the most powerful monetary policy tools. For this reason, CaixaBank Research has developed an index to measure the sentiment of the ECB’s statements.Our ECB sentiment index shows a strong correlation with euro area economic activity indicators and foresees changes in the reference interest rate. The index notes a significant deterioration in ECB sentiment between late 2017 and Q3 2019 and shows how geopolitical uncertainty has affected the ECB’s view of the economic outlook.
In this article, we analyse the extent to which it will be more difficult for Spanish companies to establish relations for international expansion with the United Kingdom following Brexit. We use the CaixaBank Index for Business Internationalisation (CIBI), which classifies foreign countries according to the potential for internationalisation they offer for Spanish companies, and we analyse the impact of the four Brexit scenarios put forward by the Bank of England.
Digital technologies permeate the debate on the future of the economy. Monetary policy and its main vehicle, money, are no exception. More and more products are sold over the internet and cash is used less and less. This new digital economy creates new demands on the financial sector and digital money emerges as a new means of payment that appeals to consumers. How does all this affect monetary policy? What can central banks do (and what are they doing) about it?
Mario Draghi ends his eight-year mandate at the ECB on October 31, leaving the central bank at the cutting edge of monetary policy. Under Draghi’s leadership, the ECB has offered significant support to the recovery of the euro area. However, the latest measures have raised doubts over the margin for action and effectiveness of monetary policy. Christine Lagarde, with a less technical profile but a vision of continuity in monetary policy, will take over in a sombre economic environment in which signs of fragmentation between ECB members have appeared.
Recent years have seen significant improvements in female representation in the workplace. Information campaigns, feminist associations, female employment quotas and a rising number of female role models all contribute to an improved gender balance in Western European and US workplaces.
Despite this progress, we remain far from achieving gender balance in the workplace. A significant contributor to the reform slowdown is the emergence of diversity fatigue and inclusion backlash among many companies trying to implement more gender inclusion in the workplace. It becomes increasingly clear that we need to find a way to redefine popular gender discourse if we wish to deliver more inclusion.
According to the 2018 Global Gender Gap Report, current projections place the closing of the gender gap at 108 years from now. Yet success stories of female economists such as Esther Duflo, Christine Lagarde and Laurence Boone make it easy to cast data aside. They often let us forget about the existence of glass cliffs, implicit gender bias in recruitment and publication processes, pregnancy discrimination, sexual harassment, office favouritism, lack of role models, and restroom gossip, just to name a few. As compelling as success stories might be, they seem not to be bellwethers for reform.
In the fight against gender discrimination, we face an elusive enemy. A recent International Labour Organisation survey found discrimination and unconscious gender bias to be among the five main challenges for women holding leadership positions. Unconscious bias stems from social norms, values, and experiences that contribute to decision-making. Such bias often manifests itself in an overall masculine corporate culture, along with preconceptions related to social roles and abilities of men and women, and the masculine nature of management positions.
Limited reflection on the effect of unconscious bias towards women in the workplace risks understating the urgency to push for more equality, allowing for a feeling of diversity fatigue to set in. Cundiff and Vescio (2016) show that individuals with strong gender stereotypes are less prone to attribute workplace gender disparities to discrimination. In 2017, James Damore, a Google engineer, unintentionally sided publicly with Cundiff and Vescio when he sued his employer on the grounds of intolerance against individuals holding unpopular political beliefs. The lawsuit came as a response to Google terminating the contract of Mr. Damore, following his drafting of an internal memo in which he argued that female underrepresentation in the tech industry is due to abilities, rather than flagrant discrimination.
The Google case describes too well the feeling of exhaustion towards diversity and inclusion issues that motivates us to take action. The recent gender inclusion backlash points to a need to revisit how we discuss gender. We should both question the validity of the design of inclusion programmes and acknowledge that we still have a long way to go until we reach equality of opportunity between genders.
We need to reinvent the way we discuss gender by taking the focus away from high-level gender policies and fairness approaches. Instead, we propose to address gender stereotypes and to develop a strong performance-oriented approach to discussing inclusion. Only by acknowledging that our profession has a gender issue will we be able to revisit this old problem through a new perspective – one that brings together practitioners across both genders, to work towards a more inclusive workplace.
About the Women in Economics Initiative
Together with some friends, we have recently launched the Women in Economics Initiative (WiE). The Women in Economics Initiative was established to advance gender equality in the field of economics. Our goal is to encourage equal opportunity and a balanced representation of genders in the economics profession across the academic, business and public sectors. To achieve this, we offer a platform that highlights the work of women economists, a network to connect and exchange ideas and interactive data about the status of diversity in economics.
We are looking for new members, supporters as well as submissions of articles from women economists on their work.
Entrants and incumbents can create new products and displace the products of competitors. Incumbents can also improve their existing products. How much of aggregate productivity growth occurs through each of these channels? Using data from the U.S. Longitudinal Business Database on all nonfarm private businesses from 1983 to 2013, we arrive at three main conclusions: First, most growth appears to come from incumbents. We infer this from the modest employment share of entering firms (defined as those less than 5 years old). Second, most growth seems to occur through improvements of existing varieties rather than creation of brand new varieties. Third, own‐product improvements by incumbents appear to be more important than creative destruction. We infer this because the distribution of job creation and destruction has thinner tails than implied by a model with a dominant role for creative destruction.
Burcu Kücükkeles (Economics ’12) has published a paper in the Academy of Management Discoveries. In this paper, “Small Numbers, Big Concerns: Practices and Organizational Arrangements in Rare Disease Drug Repurposing,” Burcu and her colleagues looked into the societal challenge of developing drugs for rare diseases (a rare disease is a condition that affects less than 200,000 people in the United States or 1 in 2,000 people in the European Union).
By studying the market and government failures in rare diseases and practices of two nonprofit organizations, Burcu and her colleagues contribute to the Agenda on the Sustainable Development Goals beyond the implications of their study to the management literature.
Burcu is currently a PhD candidate at the Chair of Strategic Management and Innovation, Department of Management, Technology, and Economics, ETH Zurich. Voice readers are welcome to email her for access to the full paper or with any questions about this research: burcuk [ at ] ethz [. ]ch
Paper Abstract
Due to their small market size, many rare diseases lack treatments. While government incentives exist for the development of drugs for rare diseases, these interventions have yielded insufficient progress. Drawing on an in-depth case study of rare diseases therapies, we explore how the practices of two nonprofit organizations allowed them to circumvent the endemic market and government failures involving positive externalities by using generic drug repurposing—i.e., seeking new therapeutic applications for existing generic drugs. Beyond elucidating the potential of generic drug repurposing for those suffering from rare diseases, our discoveries provide important insights into the mutual constitution of organizational arrangements for societal challenges and the practices they host. By showing how organizational arrangements can both reinforce and extend practices such that they enable practitioners to achieve a standard of excellence, our study advances practice theory and research on the comparative efficacy of alternative organizational arrangements for tackling societal challenges.
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