Alessandro Franconi ’17 (Macroeconomic Policy and Financial Markets)
“Mini-Bot: Ingenuity or Ignorance” is my first policy brief for the Luiss School of European Political Economy.
“The concept of using mini-BOTs to pay off trade payables may seem like a good idea, but if we analyze it in detail we can intuitively conclude that such a tool is futile and limited…It is clear that the mini-BOTs are a completely sterile, if not harmful, device for public finances, as their implementation (or just the information that the government is officially studying their implementation) would put again Italy on the road to leaving the euro.
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.
Maryam Rahbaralam ’19 (Data Science) presented “Machine Learning for the Sustainable Management of Main Water Supply Assets” with Jaume Cardús (Aigües de Barcelona) during the Pioneering Fields and Applications (Strong AI) session at the 2019 Big Data and AI Congress in Barcelona.
Abstract
The developed machine learning model gives the prediction of the probability of failure for each pipe section of the water supply network, allowing an early renewal of those in more detrimental conditions in terms of social, environmental and economic consequences.
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.
International Trade, Finance, and Development master project by Zhuldyz Ashikbayeva, Marei Fürstenberg, Timo Kapelari, Albert Pierres, Stephan Thies ’19
Source: NY Times
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
This thesis studies the impacts of flooding on income and expenditures of rural households in northeast Thailand. It explores and compares shock coping strategies and identifies household level differences in flood resilience. Drawing on unique household panel data collected between 2007 and 2016, we exploit random spatio-temporal variation in flood intensities on the village level to identify the causal impacts of flooding on households. Two objective measures for flood intensities are derived from satellite data and employed in the analysis. Both proposed measures rely on the percentage area inundated in the surrounding of a village, but the second measure is standardized and expressed in comparison to the median village level flood exposure. We find that household incomes are negatively affected by floods. However, our results suggest that rather than absolute levels of flooding, deviations from median flood exposure are driving negative effects on households. This indicates a certain degree of adaptation to floods. Household expenditures for health and especially food rise in the aftermath of flooding. Lastly, we find that above primary school education helps to completely offset potential negative effects of flooding.
Conclusion
This paper adds to the existing body of literature by employing a satellite based measure to investigate the long-run effects of recurrent floods on household level outcomes. We first set out to identify the causal impacts of flooding on income and expenditures of rural households in Thailand. Next, we explored and compared shock coping strategies and identified potential differences in flood resilience based on household characteristics. For this purpose, we leveraged a detailed household panel data set provided by the Thailand Vietnam Socio Economic Panel. To quantify the severity of flood events, we calculated flood indices based on flood maps collected by the Geo-Informatics and Space Technology Development Agency (GISTDA) measuring the deviation from median levels of flooding in a 5km radius around a respective village. The figure below illustrates the construction of the index for a set of exemplary villages that lie in the Nang Rong district of Buri Ram in northeast Thailand.
(a) 2010 flooding in Buri Ram and surrounding provinces. Red lines mark the location of the Nong Rong district.
(b) Detailed overview of flood index construction. Red dot shows the exact location of each village with the 5 km area around each village marked by the red circle.
Our results suggest a negative relationship between floods and per household member income, for both total income and income from farming. Per household member expenditure, however, does not seem to be affected by flood events at all. The only exemptions are food and health expenditures, which increase after flood events that are among the top 10 percent of the most severe floods. The former is likely to be driven by the fact that many households in northeastern Thailand live at subsistence level, and therefore consume their farming produce. A lack of production in a given year may lead these households to substitute this loss by buying produce from markets. Rising health expenditures may be explained by injuries caused or diseases obtained during a heavy flood.
Investigating potential risk mitigation strategies revealed that households with better educated household heads suffer less during flood events. However, this result does not necessarily point to a causal relationship, as better educated households might settle in locations of the village which are less likely to be flooded. While our data does not allow to control for such settlement choices on the micro-spatial level, our findings still provide valuable insights for future policy-relevant research on the effects of education on disaster resilience in rural Thailand. Moreover, our data suggests that only very few households are insured against potential disasters. Future research will help to investigate flood impacts and risk mitigation channels in more detail.
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.
Publication by Mohammad Habibullah Pulok ’12 (HEP)
My first paper from PhD is out in the European Journal of Health Economics: “Measuring horizontal inequity in healthcare utilisation: a review of methodological developments and debates”
Paper abstract
Equity in healthcare is an overarching goal of many healthcare systems around the world. Empirical studies of equity in healthcare utilisation primarily rely on the horizontal inequity (HI) approach which measures unequal utilisation of healthcare services by socioeconomic status (SES) for equal medical need. The HI method examines, quantifies, and explains inequity which is based on regression analysis, the concentration index, and the decomposition technique. However, this method is not beyond limitations and criticisms, and it has been subject to several methodological challenges in the past decade.
This review presents a summary of the recent developments and debates on various methodological issues and their implications on the assessment of HI in healthcare utilisation. We discuss the key disputes centred on measurement scale of healthcare variables as well as the evolution of the decomposition technique. We also highlight the issues about the choice of variables as the indicator of SES in measuring inequity. This follows a discussion on the application of the longitudinal method and use of administrative data to quantify inequity.
Future research could exploit the potential for health administrative data linked to social data to generate more comprehensive estimates of inequity across the healthcare continuum. This review would be helpful to guide future applied research to examine inequity in healthcare utilisation.
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.
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