Inspired by their 2019 book Good Economics for Hard Times, I decided to cover here one of the academic papers that Abhijit Banerjee and Esther Duflo referred to when delving in the subject of immigration. While the question of how immigration impacts labour market outcomes is very popular among policymakers, answering it is not a straightforward endeavour: by just looking at the correlation between the proportion of immigrants and the wage rate on a given location, we are certainly not viewing the whole story. There are a number of considerations that makes it challenging to study the causal relationship between immigration and labour market outcomes: Workers typically choose to migrate to locations where they anticipate better economic opportunities. This behaviour would indicate that immigration is correlated to higher wages. Immigration policy tends to become more strict when a country is experiencing an economic downturn. This pattern might lead to the interpretation that less immigration is correlated with a poor economic environment. Firms might decide to move to cities where they expect an influx of immigrants in the near future. In this case market expectations play a dynamic role that is not factored in when only looking at the correlation between wages and immigration. In order to address the concerns above, we would need to observe a sharp change in the supply of immigrants that is not directly related to the wages or unemployment levels in that particular location. Also, workers and firms from other locations should not be able to anticipate and respond to this change. The Case Study On the 20th of April in 1980, Fidel Castro proclaimed that Cubans who wanted to leave the country were able to do so from the port of Mariel. This political announcement led to the arrival of 125,000 Cubans, also referred to as the ‘Mariels’, between April and October on the same year of the announcement. The historical event is known as the Mariel Boatlift and it led to a 7% increase on the Miami labour force, predominantly in ‘low-skilled’ professions. If we assume that the ‘Mariels’ chose to migrate to Miami because of geographic proximity rather than the city’s specific employment circumstances relative to other places in the United States, the Mariel Boatlift offers a suitable natural experiment to evaluate the causal relationship between immigration and wage rates. In his paper, David Card studies the effects of immigration on wages and unemployment rates of Miami’s labour market. Card compares the trend of wages and unemployment rate of non-Cuban residents in Miami before and after the arrival of the ‘Mariels’ to the trend in Atlanta, Los Angeles, Houston and Tampa. Since these four cities followed a similar economic growth pattern to Miami before the Mariel Boatlift, they provide an appropriate counterfactual state of what Miami’s wages and unemployment rate would have been if the Mariel Boatlift had not happened. Results The author found out that that the influx of Mariel immigrants had no effect on the wage rate or the unemployment levels of ‘low-skilled’ non-Cuban workers. The data also reveals that the Mariel boatlift had essentially no impact on the wage rate of Cuban workers that resided in Miami before the boatlift. These results suggest that there was a rapid absorption of the Mariel immigrants into Miami's labour force. The paper also explores two potential explanations as to why an increase in labour supply didn’t lead to adverse effects on labour market outcomes as we would suspect if the market would operate under the traditional demand and supply economic framework. One of them is that ‘Mariels’ displaced other immigrants who would have moved to Miami in the early 1980s had the Boatlift not happened. The data seems to support this hypothesis to some extent as net migration of natives and non-Mariel immigrants slowed down after the Boatlift. Another explanation comes from the industry distribution in Miami and how it was suitable to welcome in a large number of ‘low-skilled’ immigrants. Evidence suggests that industries such as Apparel and Textile, which demand relatively ‘low-skilled’ labour, were predominant in Miami in the late 1970s. Finally, the effect of immigration on labour market opportunities has been widely studied and the results of Card’s paper challenges the traditional economic view. Evidently, the claim that immigration always leaves unaffected labour market outcomes cannot be made by just looking at one single case study, and further research is required to understand the channels through which immigration affects the economy and if there are any distributional effects that exist within a wider context. However, experiences as the one portrayed by the Mariel boatlift encourage us to keep our minds open and not always assume that the theory we were taught will always hold in real labour markets.

Former American President Barack Obama declared inequality “the defining challenge of our time.” Meanwhile, levels of inequality around the developed world have been on the rise. Unsurprisingly, rising levels of inequality have not gone unnoticed by academic researchers. Renowned economists such as Thomas Picketty have become household names with their work on this topic. However, this line of academic inquiry is not new. Quite the opposite, inequality has been a subject of academic research for a long time. An interesting article on the topic of inequality is Korpi et al's (1998) research paper, which investigates the impact of the share of government benefits to low-income groups on societal inequality. The paper concludes that where a smaller share of government benefits reaches those most in need, social welfare is less likely to reduce inequality. Albeit surprising, their conclusion begins to make more intuitive sense once their argument is fully understood. Essentially, they argue that receiving government benefits fosters an affinity for those benefits. Therefore, when a political party credibly promises to provide benefits to the lower and middle class (or has already done so), both groups are likely to support that party. When this occurs, the combined political will of both classes is more likely to bring the pro-redistribution parties into power. They theorize that social programs that exclude the middle class tend to be unpopular and less politically viable. Korpi and Palme argue that when the “poverty line splits the working class and tends to generate coalitions between better-off workers and the middle class against the lower sections of the working class” this “can result in tax revolts and (a) backlash against the welfare state.” They go on to argue that programs that benefit a broader swath of the population enjoy greater and longer-lasting political support. As noted in their study, the participation of the middle class in social welfare programs “tends to encourage coalition formation between the working class and the middle class in support of continued welfare state policies. The poor need not stand alone." Based on this line of reasoning, a tradeoff exists between the extent to which a program targets those who need it the most and the overall popularity and generosity of the program. According to their findings, it is the latter that wins out over the long run. Where countries adopt universal social programs that benefit the middle class, welfare regimes have a greater impact on inequality.

Economists sometimes neglect the discipline’s ethical dimensions by 1) ignoring the distributional impact of policy and growth and 2) relying on people’s revealed preferences to guide their policy direction. Economics is often much like studying a map: it can help you understand how to get somewhere but tells you little about where exactly you want to go. It is on this basis that John Broome’s (2009) essay argues for a re-focus on the ‘ethical’ side of economics: no matter how good your map is if your destination is a dump, a dump is where you will go. Broome focuses on the two following ways economists sometimes neglect the discipline’s ethical dimensions: Ignoring distributional impacts: economists often assess an economy’s performance based on its aggregate performance (e.g. GDP, IP, disposable income). The reason for these measures’ popularity partially is convenience, as they result in the reduction of many data points to a single figure. However, by focusing on aggregate measures, one can easily miss the distribution of wins and losses. As a result, one risks of missing the ethical question of “who should the economy support”, being instead presented with an artificial reality in which everyone wins. Arguments surrounding free trade are a clear example of this, with the so-called ‘efficiency gains’ occasionally presented as a universally good thing. In reality, however, in the absence of worker re-education, such policies can lead to higher structural unemployment: some jobs are not required if better products can be imported. A similar argument can be made with respect to manufacturing automation: consumers win from a cheaper product, but workers lose via redundancies. Of course, this is not to say that there should be no free trade agreements and technological development: it is just to say that there need to be some ethical guidelines over how to treat the losers. Relying on people’s preferences to deduce their ‘world vision’: every policy decision is intricately linked to a vision of how the world should be. A good example of this can occasionally be observed with regards to onshore wind and forest preservation. Wind energy proponents emphasize their vision of a carbon-neutral future, whereas conservationists emphasize the area’s importance for wildlife, beauty, etc. Furthermore, the debate is likely to be inconclusive as each group values each thing very differently. The way economists sometimes deal with such situations is by trying to quantify the value people put on different things and subsequently deciding which thing should be given a higher priority. This can be done via a variety of ways, the most straightforward one being calculating people’s willingness to pay: how much one values conservation is indicated by how much they are willing to pay for it. This way, economists transform the ethically heavy question of “how should the world be” to a methodology question of “how should we measure people’s willingness to pay”. This method can help deduce whether people prefer apples to oranges (people who would pay more for apples are likely to prefer apples) but when it comes to questions of the value of natural beauty and human life, the method breaks down. People simply do not know how to value such things and, as a result, the questionnaire data becomes problematic, leading to nonsensical conclusions. This effect is indicated by research showing people underinvesting in health insurance as they fail to quantify the value of their own health. As a result, an ethical emphasis on policymaking may be a more appropriate tool to guide decision-making. Overall, economics needs to rely on some form of ethical theory in relation to wealth distribution and ‘world vision’. Furthermore, it is important to highlight that by ignoring ethical theory one does not avoid its implications: by ignoring distributional effects and siding with one side of society according to people’s ‘preferences’, the discipline makes implicit ethical decisions about the world it envisions. And by making them implicit instead of explicit, it risks of blindly moving towards a non-desirable world vision.

In the Cem Çakmakl et al (2020) NBER working paper, the authors set forth a model outlining the macroeconomic effects of the Covid-19 outbreak. The model is interesting in that it integrates domestic and foreign supply and demand dynamics, notably taking international sectoral linkages into account through an input-output analysis. I will not focus on this though, as I wish to bring to centre stage another aspect of the paper: its contribution to the recent COVID-19-related research agenda which focuses on ‘Emerging Markets’ (EM) and their idiosyncrasies when faced with the challenges of the current crisis (the paper uses Turkey as a case study). How are emerging markets (EMs) different from developed countries in their reaction to the COVID-19 crisis? It is a consensus that governments must act to reduce the health and economic impacts of the pandemic. In advanced economies, sizable fiscal stimulus packages have been designed and are to be funded mostly through monetary financing, mainly QE and debt issuance. Stimuli have also been announced in non-developed economies but at a much lower level than at richer peers. The underlying reason is that, on average, the less developed a country is, the more limited its fiscal space and general room for manoeuvre. The authors argue that it is much harder for EMs to rely on QE (or alternative monetary financing) as the enlargement of their central banks’ balance sheets may feed into credibility issues, rising inflation and sharp currency depreciation. Furthermore, the authors highlight the importance of external funding for developing economies, which is also central to their post-pandemic economic recovery. Since the crisis hit, capital outflows from ‘exotic countries’ have been extremely large (in March, the Institute of International Finance’s Capital Flows Tracker registered the largest historical portfolio outflows from EM, above US$80 billion) and the risk premia of EM assets have significantly increased. Consequently, EM liquidity shortage risks have risen alongside difficulties to rollover their external debt. Therefore, many EMs will need to undertake a number of measures, to prevent such a liquidity crisis and support the domestic economy. In this regard, the authors outline a set of different policy alternatives; from swap agreements with reserve countries/institutions and FX agreements with international institutions to capital controls and debt memorandums. They also highlight problems and shortcomings associated with such alternatives. Conclusion The NBER working paper is an interesting piece both with respect to its modelling assumptions and results - especially with regard to the indirect effects of the pandemic through supply chain linkages - as well its insights on the differences between developed and developing country responses to the COVID-19 crisis. Although a ‘solution’ to the challenges faced by such economies is not yet clear, by bringing EMs to the centre stage, the paper helps to shed light into the matter.

The Kolliopoulos (2020) paper discusses the determinants of the conditions surrounding the first (2013), second (2014), and third (2016) Greek bank recapitalizations (bailouts) on the back of the Greek economic crisis. In doing that, the paper argues that the first two recapitalizations occurred in line with the conventional ‘Varieties of Capitalism’ institutional framework, whereas the last one did not, as its conditions were dictated by external (instead of domestic) institutions. What is the ‘Varieties of Capitalism’ framework? The ‘Varieties of Capitalism’ framework is based on the premise that capitalist countries can be grouped in distinct types of ‘varieties’ which share common institutional characteristics and behaviors. Kolliopoulos (2020) refers to the work of Hall and Soskice (2001)[1] and Moline and Rhodes (2005)[2] to group countries in the following three categories: Liberal market economies (LMEs): firm interactions are characterized by low levels of collective action and ‘arm’s length’ relationships. Examples of such countries are the USA, Canada, UK, Ireland, Australia, and New Zealand. Coordinated market economies (CMEs): firms rely on collaborative relationships to resolve their coordination problems. Some examples are Germany, Japan, Denmark, and Sweden. Mixed market economies (MMEs): the hybrid form of LMEs and CMEs, which are characterized by weaker coordination than CMEs but stronger collective structures than LMEs. Greece, as well as France, Spain, Portugal, and Turkey are classified in this category. How do the first two Greek bank recapitalizations support other ‘Varieties of Capitalism’ literature? According to previous research, bank-based CMEs and MMEs offer more generous banking bailouts than LMEs, due to 1) the banking sector’s higher collective bargaining power and 2) strong bank-industry links which support continuous bank lending (in LMEs banks would more easily become reluctant to support struggling businesses). According to Kolliopoulos (2020), Greece’s first two bank recapitalizations supported the above hypothesis in three ways: Bank support was facilitative instead of mandatory. State support had very lenient conditions, resulting in significant governmental losses: the IMF estimates that from the €57 billion spent on capital support, only €7 billion was recovered. There were high levels of collective action by systemic banks (National Bank of Greece, Alpha Bank, Eurobank, Piraeus Bank). How and why is the third recapitalization different? The third (2016) recapitalization was different in that it 1) involved the extensive buyout of systemic Greek banks by foreign investors (de-Hellenization); 2) involved the forced replacement of a big part of systemic bank’s executive and non-executive director boards. In other words, it incorporated strict and highly unpopular to the banking sector conditions, contrasting with the previous more accommodating approach. Greece’s dire economic situation in 2015 and the ECB’s role as a lender of last resort were instrumental in preventing the Greek government and banking sector to set their own bailout conditions. As a result, the conventional ‘Varieties of Capitalism’ framework breaks as domestic institutions were unable to dictate the bailout conditions, which were mainly chosen by the EU-led third ‘Memorandum of Understanding’ program. More specifically, on the back of the banking sector’s deterioration and the Greek referendum announcement in 2015, the ECB’s Governing Council refused to recapitalize Greek banks via the emergency liquidity assistance provision (ELA) until a third memorandum program was approved. Furthermore, being a Eurozone member, Greece was unable to refinance its banking sectors effectively as it does not have its own central bank to act as a lender of last resort. As a result, the Greek government was forced to accept the make-or-break August 2015 memorandum deal, with its much stricter recapitalization conditions. Conclusion Overall, the key message of the paper is that domestic institutions do affect banking bailout conditions. However, in the case of Greece’s third recapitalization program, the Greek government and banking sector were unable to set their own rescue conditions. As a result, external institutions were the determining factor of the recapitalization program. [1] Hall, P. A. and Soskice, D. (2001). Varieties of capitalism and institutional foundations of comparative advantage. Cambridge, UK: Cambridge University Press. [2] Molina, O. and Rhodes, M. (2005). ‘Varieties of Capitalism and Mixed Market Economics’. APSA-EPS Newsletter.

The gender wage gap still exists in the US, but when ‘explained’ factors (years of experience, education level, hours worked) are considered, the wage gap for high-earning American men and women entering into similar jobs is almost non-existent. However, this wage gap increases as women progress in their careers, likely due to motherhood and its unequal distribution of non-paid household and child-rearing duties. Source: Campaign What does the data show? As the global ‘Me Too’ movement highlights, there is still an unacceptable amount of sexism and bias in all sectors of society. However, as Claudia Goldin’s (2014) paper demonstrates, the empirical data surrounding gender wage discrimination are more nuanced. Goldin’s work uses earnings data for highly educated (JDs, MBAs, etc.) men and women, dating back to the 1950s. As her data demonstrate, the gender wage gap has decreased since the 1950s, which she concludes is mostly a factor of women’s increases in human capital as they 1) attended university at higher rates and 2) chose and/or gained access to “more remunerative and career-oriented ones”. In Goldin’s study, male and female workers with similar education and experience earn almost exactly equal remuneration at the start of their careers. But the gap widens 15 years after graduation because of motherhood’s dual impacts – recovery from childbirth and a higher likelihood of working fewer hours to stay at home with children. Unsurprisingly, women in Goldin’s (high achieving) sample worked 24% hours less on average. Another key facet is that these wages are nonlinear, meaning the more hours worked, there is a ‘multiplier’ for higher salaries: working 35 hours might earn someone $50,000, but an employee working 70 hours would earn $150,000. Additionally, there is a wage premium for working irregular hours and client-facing roles, which are particularly difficult to achieve for mothers without equal household division of labor. When Goldin breaks down the data, certain industries do better than others: Technology and Science occupations have the least premium for hour-inflexibility, which might explain the nearly non-existent wage gap there. Business and Law, conversely, are highly hour-inflexible and the hourly wages are highly nonlinear and inelastic. Is the paper’s sample representative? Goldin’s paper is incredibly valuable, and it is fantastic work on an important (and sensitive) topic. But its conclusions might go beyond what its parameters should allow because her data only focuses on upper-middle-class to rich Americans – who also tend to be disproportionately white. Not only is her data not broadly applicable globally, but it also is not even convincingly applicable in the United States, where nearly 40% of American women are people of color, and this share is only set to increase. Goldin’s paper is a fantastic foundation, but further cross-section research involving not only multiple other nations but also broader segments of socio-economic populations would put its thematic conclusions on much more solid footing. In the meantime, Goldin’s work deserves attention and adds much toward solving an issue that is of great importance to all genders. What policy could be used to correct the gender wage gap? Goldin proves the gender gap is most correlated with motherhood. Therefore, while not a panacea, expanded paternal leave and norms around the equal division of household work and child-rearing would help ensure that if women work less, that it is their choice. If this market failure is left unaddressed, it would have two salient negative effects: 50% of the workforce are not working at their full potential, and/or birth rates will decline and drag down GDP.

Working on data on the institutions in the antiquity, Roland(2018) distinguishes them into two institutional clusters resulting in either statist or market systems. The former were present in ancient states like Egypt or China and relied mostly on some form of central planning in the allocation of resources, while the latter emphasized private property with relatively strong property rights. The paper then connects these institutional differences in the modern distinction of the cultural traits of individualism and collectivism. These traits, along with the modern institutional framework, impact today’s economic performance. Didn't history begin with the advent of the internet? How did this all come to be in the first place? Geographical, psychological, biological, historical, random reasons: differences in historical pathogen prevalence, frequency of gene variants affecting the intensity of pain from social exclusion, the propensity to depression when faced with stressful events, rice versus wheat, past use of irrigation, all played their part in whether an ancient state would end up resembling the statist or market example. In the same context, factors like the importance of the clan versus family, differences in initial relative benefit of trade versus specialized production (led either to the development of markets, property right protection, or strong state development embracing all society), family structure (whether family trees were unilineal or bilateral), appropriability of agricultural production by the central state, storability of agricultural production, religious forms fostering either individualism or collectivism, affected particular early institutions which were in turn likely to have affected particular values and beliefs. How are ancient institutions still present in today's social structure? To accurately measure the institutional structure along with the geographical and economic conditions Roland's paper uses the following variables: The legal, political, and sociological indexes (created from the relative variables) support the original hypothesis regarding two institutional clusters, the statist and market ones. Similarly, the geographical index capturing potential gains from trade presents a strong positive correlation with the joint (created by aggregating the legal, political, and sociological) institutional index. Finally, to explore how institutions in the antiquity still bear their mark in today’s world, the author presents the correlation between the aforementioned joint institutional index and the modern cultural trait of individualism (One should keep in mind though, that the present analysis does not purport in favor of solid causal channels. Instead, it attempts to elucidate the existence of a strong two-way path of influence between ancient institutions, geographical factors, and contemporary cultural traits): To sum up... Distinct institutional differences in ancient states led to cultural differences (statist systems led to collectivism, market systems to individualism). Given the inertia of culture, early institutions may have affected cultural values and beliefs that are still relevant today. This has resulted in the contemporary mix of culture and institutions that determine economic performance within each society.

Gesiarz et al (2020) carried out three randomised control experiments to investigate the impact of reward inequality on human motivation. More specifically, they investigated the impact of the opportunity gap on motivation, with opportunity gaps representing the different sets of rewards available to a person for an equivalent amount of effort. Their findings supported the hypothesis that high inequality and the sense of unfairness leads to less motivation across the entire rewarded population. Paper hypothesis The paper investigates the impact of reward inequality on people’s motivation for the reward. The study has two central hypotheses: People with a higher relative reward would be more motivated than those with a lower relative reward. The hypothesis reflects people’s tendency to value their own rewards relative to the rewards of others. As a result, people with a relatively lower reward value it less, not merely due to its absolute size, but also due to the comparison effect. The opposite occurs with people who receive a relatively higher reward. . The wider the opportunity gap the less people get motivated by the reward, regardless of its relative size, due to a sense of unfairness. Methodology The two central hypotheses are investigated via one main and two robustness check experiments. In the main experiment, participants were informed that the task would consist of a mandatory book transcribing task, for which they will be paid £0.25, and an optional transcribing task for which they would receive a bonus payment. They were also informed that the wage for the optional task would be randomly drawn. Once their randomly drawn bonus wage was revealed to them, they were also presented with the payments offered to other participants. By manipulating the participants’ perception of their bonus size and the fairness of the whole reward distribution, researchers estimate the impact of the opportunity gap on work motivation: would participants accept or reject the optional task? Result The results verified both hypotheses: firstly, participants valued the reward more if they were higher on the reward distribution. Secondly, more unequal wage distribution led to a lower willingness to work across all groups. In fact, participants reported a sense of unhappiness when put under the unfairness condition, which demotivated them from accepting the task. Conclusion The paper concludes that people get demotivated to pursue a reward when 1) there is a big variance of rewards and 2) people do not feel they deserve their relative place in the reward distribution. At first glance, it seems that in our highly unequal global society rewards are also distributed randomly and thus can be viewed as unfair. For example, person’s nationality itself, which one may assume is given at random , can explain 66% of global variation in living standards[1]. However, the real world is much more complex than the study setting: people do not necessarily compare themselves to the entire human population, nor do they perceive their partially randomly generated rewards as unfair. As a result, the Gesiarz et al (2020) paper opens an interesting discussion on the impact of inequality on motivation , but further research is needed to understand the paper’s relevance. [1] Milanovic B. Global Inequality of Opportunity: How Much of Our Income Is Determined by Where We Live? The Review of Economics and Statistics. 2014; 97: 452–460. https://doi.org/10.1162/REST_a_ 00432

Ever since Muhammad Yunus founded the Grameen Bank in Bangladesh in 1983, microfinance targeting poor women has been the talk of the town among development economists. Unfortunately, more and more evidence suggests that women are, in fact, not as successful in the role of business owners as men. Erica Field and her co-authors conducted a randomized control trial in India, finding that women are not necessarily worse entrepreneurs, but that the low number of successful female peers may hamper women’s success in business. How did they show this? Field et al. (2016) worked with India’s largest women’s bank, offering a two-day business course to a random sample of female customers. Half the participants were asked to bring a friend along to the training, the other half came alone. They also had a control group of women who did not attend the training. Four months later, the researchers compared how the women had changed their business practices. They found that only those who attended the training with a friend increased their business activity. To be precise, they were 7 percent more likely to take out a loan from the bank than those who had attended the training without a friend. They also reported a higher household income and were less likely to describe themselves as housewives. Why might friendship be good for business? One could think of many reasons why having a peer might be good for business. The authors hypothesize that women have more business confidence when they feel supported by their peers. However, when they asked women about this in their follow-up survey, this did not seem to be the case. Another hypothesis is that women who have a better network have better access to labor, information, and capital. After all, you would expect that friends help each other out. But again, according to the surveys, this did not turn out to be true. What they found instead was that women who attended the course with a friend set fundamentally different business goals for themselves from the start. Attending the workshop with a friend helped the women identify what they wanted to achieve. Field et al. also find that the effects described above are particularly strong for women coming from casts who face restrictive social norms. Having a peer was particularly important for those women’s business success. What shortcomings does this study have? The researchers test the effect of receiving the training on many indicators – and find that it does not affect many of them significantly at all. For instance, there was no significant effect on earnings set aside for business investments or cost reductions. This implies, perhaps not surprisingly, that a two-day business course is not sufficient to turn anyone into a great entrepreneur. Conclusion This study suggests that programs supplying women with grants or loans could yield better results when involving peers in business trainings. This is particularly true when working with women from restrictive social backgrounds.

Alondra Nelson and Kate Crawford discuss how the Covid-19 pandemic has served as a pretext for tech companies and governmental institutions to push for a centralized set of surveillance tools despite their troubling legacies. The authors beg the question: as technological solutionism becomes normalized, what will be the legacy of our compliance? How can we engage in the politics of refusal? Technology as panacea The first keynote of the Association of Internet Researchers’s (AoIR) Conference 2020 comprised of a broadcast featuring Kate Crawford and Alondra Nelson in a spirited discussion over “The Pandemic as Pretext: The Politics after Covid 19.” The keynote began with a proposition that technological infrastructures have been ushered in at this time of crisis to detangle the plethora of issues engendered or heightened by the Covid-19 pandemic. For instance, the WHO reports that contact tracing “will break the chains of transmission of an infectious disease and is thus an essential public health tool for controlling infectious disease outbreaks” (2020). However, Crawford argued that policy around contact tracing apps threatens to undermine public trust. She brought up that, in the UK, the Department of Health and Social Care was to grant law enforcement access to test-and-trace data in order to better enforce isolation regulation. Who can access the backend of test-and-trace applications? What channels do these data flow through? How long are they kept for? There appears to be minimal supervision over the infrastructuralisation of these technologies. Long-term effects and the digital divide Nelson challenges the notion that a state of emergency should call for the increased use of surveillance technologies. When analog solutions like social distancing and face masks have proven to be effective, why is there a need for full-scale surveillance technology? The author heralds the long-term consequences of the centralization of policing power around technology companies and recalls that many still live with the “terrorist” infrastructures established after 9/11 such as facial recognition algorithms. Crawford complements that “coming out of this period, we will have set up these infrastructures to keep.” In other words, not only should we question the necessity of implementing widespread surveillance practices before examining analog alternatives, but we should remain vigilant because history suggests that technological surveillance will follow us out of the crisis period. In addition, we need to look at the effects of the pandemic from an intersectional angle. Surveillance measures are bound to affect different populations asymmetrically. For instance, the proposal to make tracker applications mandatory on smartphones presupposes the ownership of a smartphone. For those who cannot afford the luxury of an app-tracker, it is likely that they will be supplied with wearable technologies such as bracelets in order to effectuate technocratic control. However, Crawford underlines that the experience of these wearables is akin to that of incarceration. This digital divide prompts us to consider how marginalized communities have previously been the targets of state violence. After all, as Nelson points out, our health systems are ‘politics made material’ and as such, they reveal the contempt and dehumanization of the marginalized. The author continues that it is for this reason that movements like the Black Panthers expressed a profound and tragic distrust of the state, positing that black bodies are the center of dialectics of both hyper surveillance and neglect at once. The seductive power of the promise of normalcy Yet, people are not blind to the acceleration of totalizing surveillance. Nevertheless, Crawford suggests that people are eager to accept whatever regulations are on the table for a chance at a return to normalcy. We are happy to accept biometric surveillance and tracking technologies should that mean that we will be able to inhabit public spaces, return to workplaces and schools, go out for dinner. However, the two authors remind us that any return to normalcy ‘requires a return to care and humanization of our lives.’ In other words, we need to make room for public debate on these issues and question how technocratic control implemented through surveillance technologies will affect, now and in the long

Rema Hanna and Benjamin Olken (2018) explore the trade-offs associated with universal basic income and targeted income transfers as a means for developing countries to fight poverty. Their findings suggest that although universal basic income helps to overcome targeting errors, targeted programmes in developing countries allow for a bigger transfer on a per-beneficiary basis and hence are more effective at improving social welfare. Background In the fight against poverty, many governments around the world resort to income transfer programmes that aim to target poor populations. However, a key challenge with this mechanism is that, typically, in developing countries, a large proportion of the poor work in the informal sector, which prevents governments from observing their income and identifying those who are eligible for the transfer. An alternative solution is to use proxy income measures, however, these lead to targeting errors such as giving the transfer to those who are not poor (Inclusion error) or failing to provide the transfer to poor individuals (Exclusion error). A way to overcome targeting errors is to apply a universal basic income programme, where everyone is given equally a transfer. Since the government does not need to verify income, these programmes are relatively easier to implement and involve lower administrative costs. On the other hand, for most developing countries, these programmes need to be financed through domestic taxation, which again is challenging due to the high level of informality and a large number of people outside the tax net. Hence, to provide a transfer, the government might need to increase marginal tax rates substantially for those few inside the tax net. Case Studies The authors evaluate the social welfare implications of implementing these types of programmes by using nation-wide household data and simulating different eligibility thresholds in Indonesia and Peru. Both countries run various transfer programmes and also have a high percentage of their population working in the informal sector. When examining the welfare effects of each programme, they assign different weights to exclusion and inclusion errors so that they reflect how important it is that the poor have access to the transfer and how much benefit there is if non-eligible individuals also get to enjoy the transfer. They also consider that by allowing more people into the programme, if the total budget for the programme is fixed, then the transfer given per person falls. Finally, the comparison also considers the savings in administrative costs that arise from not having to target individuals in a universal basic income scenario. Overall, when comparing utility levels between the two programmes, they find out that narrowly targeted programmes, where the government distributes large transfers per person to the poorest of the poor, are optimal from a social welfare perspective. Conclusion While the paper concludes that despite targeting errors, targeted programmes might be a better option, it also argues that the results do not consider dynamic changes in household income. In fact, if survey data is not collected frequently, then identifying poor households becomes a more challenging task and therefore the size of the relative inclusion and exclusion errors might increase, which might lead to a different optimal threshold. Finally, the authors also argue that the choice of programme depends principally on the policy context. A programme might receive better political support and funding if everyone gets to benefit directly from it. Equally, a targeted programme might be harder to implement if the proxy income measure for eligibility lacks transparency or if a country has high levels of corruption. Thus, governments should consider other factors, besides targeting errors, when choosing between the programmes.

Eichengreen et al. (2020) are trying to predict whether the current pandemic will enhance people’s trust in science in the long-run by analysing how living through an epidemic has affected people’s attitudes in the past. They find that experiencing an epidemic during the “impressionable years” of 18 to 25 significantly reduced those persons’ trust in science later in life. Epidemics have a long-term impact on people's world perception Without a doubt, the Covid-19 pandemic has had and continues to have detrimental effects on people’s lives and the global economy. However, one of the potential positive outcomes is an enhanced trust in science as the world realizes the importance of scientific research for finding treatments and vaccines against Covid-19. In order to predict whether the pandemic could, indeed, increase people’s trust in science in the long-run, Eichengreen, Aksoy and Saka (2020) matched data from a recent global opinion poll by the Wellcome Trust with data on global epidemics since 1970. They find that respondents who had experienced an epidemic in their “impressionable years”, meaning between the age of 18 and 25, are, on average, 11 percent less likely to trust scientists than those who had not. The effect they find is not a general decline in trust in science, but only in scientists, specifically, those researching healthcare-related issues. Why does epidemic exposure diminish trust in scientists? The researchers argue that the reason for the decrease in trust is due to the sudden surge of public interest in scientific research during an epidemic. During such a crisis, the scientific community is under a lot of pressure to produce results quickly. Often, previous assumptions have to be corrected along the way. While this is common practice in the scientific learning process, the public does not usually notice it. Especially people who do not usually engage with science may be confused by contradictory statements and, as a result, start doubting scientists. Indeed, Eichengreen et al. find that it is the people with little science education driving the results. What consequences could this effect have? The authors find that people’s attitude towards scientists has implications for their behaviour as well. Individuals exposed to epidemics during their impressionable years were more likely to have negative attitudes towards vaccination and less likely to vaccinate their children. This finding points to the importance of science education in general and broad science communication in the current pandemic.