Does a higher share of immigrants affect the school performance of both immigrants and natives? Do desegregation policies improve efficiency? The existing evidence suggests that a higher share of immigrants has a negative (and often sizable) effect on the school performance of immigrants and a negative but probably small effect on the performance of natives. When average school performance is considered, this asymmetry generates concave peer effects, a key condition for the efficiency of desegregating policies. The broad message from the empirical literature is that these policies are not only equitable, in that they provide better opportunities to individuals with relatively low parental background, but also efficient.
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Article
The Effect of Immigration on Education
Giorgio Brunello
Article
The Effects of Monetary Policy Announcements
Chao Gu, Han Han, and Randall Wright
The effects of news (i.e., information innovations) are studied in dynamic general equilibrium models where liquidity matters. As a leading example, news can be announcements about monetary policy directions. In three standard theoretical environments—an overlapping generations model of fiat currency, a new monetarist model accommodating multiple payment methods, and a model of unsecured credit—transition paths are constructed between an announcement and the date at which events are realized. Although the economics is different, in each case, news about monetary policy can induce volatility in financial and other markets, with transitions displaying booms, crashes, and cycles in prices, quantities, and welfare. This is not the same as volatility based on self-fulfilling prophecies (e.g., cyclic or sunspot equilibria) studied elsewhere. Instead, the focus is on the unique equilibrium that is stationary when parameters are constant but still delivers complicated dynamics in simple environments due to information and liquidity effects. This is true even for classically-neutral policy changes. The induced volatility can be bad or good for welfare, but using policy to exploit this in practice seems difficult because outcomes are very sensitive to timing and parameters. The approach can be extended to include news of real factors, as seen in examples.
Article
The Effects of Parental Job Loss on Children’s Outcomes
Jenifer Ruiz-Valenzuela
Severe economic downturns are typically characterized by a high incidence of job losses. The available evidence suggests that job losers suffer short-run earning losses that persist in the long run, are more likely to remain unemployed, suffer negative health impacts, and experience an increased likelihood of divorce. Job losses have therefore the potential to generate spillover effects for other members of the household, including children. This comes about because most of the negative consequences of job loss have a direct effect on variables that enter both the production function of cognitive achievement and the health production function.
Workers who lose their jobs are likely different from those who remain employed in ways that are unobserved to the researcher and that might, in turn, affect child outcomes. Omitted variable bias poses a challenge to obtaining causal estimates of parental job loss. The way the literature has tried to approximate the ideal experiment has mainly depended on whether the child outcome under analysis could be observed both before and after the shock (i.e., both before and after parental job loss), normally relying on job losses coming from plant closures or downsizes and/or individual fixed effects. A survey of the literature shows that father’s job losses seem to have a detrimental impact on outcomes measuring children’s health and school performance. The impact of mother’s job losses on these same outcomes is mixed (including negative, null, and positive impacts). The impact on more long-term outcomes is less clear, with very mixed findings when it comes to the effect of parental job loss on college enrollment, and small impacts on earnings. In many studies, though, average effects mask important differences across subgroups: the negative impact of parental job loss seems to be mostly concentrated on disadvantaged households.
Article
The Effects of Prenatal Care on Birth Outcomes: Reconciling a Messy Literature
Hope Corman, Dhaval Dave, and Nancy E. Reichman
Prenatal care, one of the most frequently used forms of healthcare in the United States, involves a series of encounters during the gestational period, educates women about pregnancy, monitors existing medical conditions, tests for gestational health conditions, and refers expectant mothers to services such as support groups and social services. However, an increasingly methodologically rigorous literature suggests that the effects of prenatal care timing and quantity on birth outcomes, particularly low birthweight, are modest at the population level. A review and synthesis of the literature suggests that the questions typically being asked may be too narrow and that more attention should be paid to the characterization of infant health, characterization of the content and quality of prenatal care, potential heterogeneous effects, potential indirect effects on health behaviors that may benefit offspring, potential long-term effects, potential spillover effects (i.e., on mothers and their subsequent children), effects of preconceptional and lifetime care, and intergenerational effects.
Article
The Empirics of Network Models
Pedro CL Souza
The literature documenting a wide range of network or peer effects has blossomed in the past decade and have appeared in most major economics journals, using a variety of methods and identification strategies. Reviewing the empirics of those papers suggests a few broad classes of econometric models. The first and canonical model is the “linear-in-means,” which grows from Manski’s seminal work. More recently, it has shown that network asymmetry conditions (known as “peers-of-peers” instrument approach) can be used to instrument the endogeneity inherently present in the linear-in-means model. Moving to more recent empirical practice reveals novel and creative instrumentation strategies exploring particular empirical settings. The network identification strategies can also be combined with traditional differences-and-differences, event-study, and regression discontinuity designs. For example, under certain conditions, one can explore the variation that stems from the differential comparison of the evolution over time of well-connected versus less-well-connected individuals; or explore the variation in the network structure induced by a discontinuous change in the network. Randomized, controlled studies had substantial importance in revealing network effects in the past literature using standard methods; and, more recently, in understanding the extent to which networks can themselves be endogenous to the provision of the treatment itself. This, in turn, will present future challenges for the econometrics of networks and the identification or evaluation of treatment effects under a causal framework with endogenous interference.
Article
The Employment Effects of Minimum Wages: Some Questions We Need to Answer
David Neumark
The literature on the employment effects of minimum wages is about a century old, and includes hundreds of studies. Yet the debate among researchers about the employment effects of minimum wages remains intense and unsettled. Questions have arisen in the past research that, if answered, may prove most useful in making sense of the conflicting evidence. However, additional questions should be considered to better inform the policy debate, in particular in the context of the very high minimum wages coming on line in the United States, about which past research is quite uninformative.
Article
Energy Finance
William Megginson, Herber Farnsworth, and Bing (Violet) Xu
Defined as a single industrial sector, the global production, distribution, and consumption of energy is the world’s largest in terms of annual capital investment (US$1.83 trillion in 2019, the last prepandemic year for which full data are available) and the second largest nonfinancial industry in terms of sales revenue (US$4.51 trillion). Production and consumption of more than 100 million barrels of oil occurs each day—with 70% being traded across borders. Each of the world’s 7.5 billion citizens consumes an average of 3,181 kilowatt-hours per year, although per capita energy consumption varies enormously and is much higher in rich than in poor countries.
Properly analyzing the financial economics of the global energy industry requires focusing on both the physical aspects of production and distribution—how, where, and with what type of fuel energy is produced and consumed—and the capital investment required to support each energy segment. The global energy “industry” can be broadly categorized into two main segments: (a) provision of fuels for transportation and production and (b) distribution of electricity for residential and industrial consumption. The fuels sector encompasses the production; processing; and distribution of crude oil and its refined products, mostly gasoline, kerosene (which becomes jet fuel), diesel, gas oil, and residual fuel oil. The electric power sector includes four related businesses: generation, transmission, distribution, and supply.
Two imperatives drive the ongoing transformation of the global energy industry. These are (a) meeting rising demand due to population growth and rising wealth and (b) addressing climate change through greener energy policies and massive capital investments by corporations and governments. The pathway to decarbonizing electricity production and distribution by 2050 is fairly straightforward technologically; however, doing so will require both scientific innovations (particularly regarding scalable battery storage) and sustained multitrillion dollar annual investments for the next three decades. Decarbonizing transportation is a far more difficult and expensive proposition, which will require fundamental breakthroughs in multiple technologies, coupled with unusually farsighted policy action. Extant academic research already provides useful guidance for policymakers in many areas, but far more is required to help shape the future policy agenda.
Article
Equality of Opportunity in Health and Healthcare
Florence Jusot and Sandy Tubeuf
Recent developments in the analysis of inequality in health and healthcare have turned their interest into an explicit normative understanding of the sources of inequalities that calls upon the concept of equality of opportunity. According to this concept, some sources of inequality are more objectionable than others and could represent priorities for policies aiming to reduce inequality in healthcare use, access, or health status.
Equality of opportunity draws a distinction between “legitimate” and “illegitimate” sources of inequality. While legitimate sources of differences can be attributed to the consequences of individual effort (i.e. determinants within the individual’s control), illegitimate sources of differences are related to circumstances (i.e. determinants beyond the individual’s responsibility).
The study of inequality of opportunity is rooted in social justice research, and the last decade has seen a rapid growth in empirical work using this literature at the core of its approach in both developed and developing countries. Empirical research on inequality of opportunity in health and healthcare is mainly driven by data availability. Most studies in adult populations are based on data from European countries, especially from the UK, while studies analyzing inequalities of opportunity among children are usually based on data from low- or middle-income countries and focus on children under five years old.
Regarding the choice of circumstances, most studies have considered social background to be an illegitimate source of inequality in health and healthcare. Geographical dimensions have also been taken into account, but to a lesser extent, and more frequently in studies focusing on children or those based on data from countries outside Europe. Regarding effort variables or legitimate sources of health inequality, there is wide use of smoking-related variables.
Regardless of the population, health outcome, and circumstances considered, scholars have provided evidence of illegitimate inequality in health and healthcare. Studies on inequality of opportunity in healthcare are mainly found in children population; this emphasizes the need to tackle inequality as early as possible.
Article
Estimation and Inference for Cointegrating Regressions
Martin Wagner
Widely used modified least squares estimators for estimation and inference in cointegrating regressions are discussed. The standard case with cointegration in the I(1) setting is examined and some relevant extensions are sketched. These include cointegration analysis with panel data as well as nonlinear cointegrating relationships. Extensions to higher order (co)integration, seasonal (co)integration and fractional (co)integration are very briefly mentioned. Recent developments and some avenues for future research are discussed.
Article
Estimation Error in Optimal Portfolio Allocation Problems
Jose Olmo
Markowitz showed that an investor who cares only about the mean and variance of portfolio returns should hold a portfolio on the efficient frontier. The application of this investment strategy proceeds in two steps. First, the statistical moments of asset returns are estimated from historical time series, and second, the mean-variance portfolio selection problem is solved separately, as if the estimates were the true parameters. The literature on portfolio decision acknowledges the difficulty in estimating means and covariances in many instances. This is particularly the case in high-dimensional settings. Merton notes that it is more difficult to estimate means than covariances and that errors in estimates of means have a larger impact on portfolio weights than errors in covariance estimates. Recent developments in high-dimensional settings have stressed the importance of correcting the estimation error of traditional sample covariance estimators for portfolio allocation. The literature has proposed shrinkage estimators of the sample covariance matrix and regularization methods founded on the principle of sparsity. Both methodologies are nested in a more general framework that constructs optimal portfolios under constraints on different norms of the portfolio weights including short-sale restrictions. On the one hand, shrinkage methods use a target covariance matrix and trade off bias and variance between the standard sample covariance matrix and the target. More prominence has been given to low-dimensional factor models that incorporate theoretical insights from asset pricing models. In these cases, one has to trade off estimation risk for model risk. Alternatively, the literature on regularization of the sample covariance matrix uses different penalty functions for reducing the number of parameters to be estimated. Recent methods extend the idea of regularization to a conditional setting based on factor models, which increase with the number of assets, and apply regularization methods to the residual covariance matrix.
Article
European Trade Policy in the 19th Century
Markus Lampe
Trade policy is one determining factor of 19th-century globalization, alongside transport and communication innovations and broader institutional changes that made worldwide commodity and factor flows possible.
Four broad periods, or trade policy regimes, can be discerned at the European level. The first starts at the end of the French Revolutionary and Napoleonic wars that had led to many disruptions in trade relations. Governments tried to recover from the financial impact of the wars and to mitigate the adjustment shocks to domestic producers that came with the end of the wars. Very restrictive trade policies were thus adopted in most places and only slowly dismantled over the following decades as some of the welfare costs of, for example, agricultural protection became evident.
The second period dated from the mid-1840s, which saw the liberalization of protective grain tariffs in many European countries, to the mid-1870s, when trade liberalization reached its maximum. This period witnessed unilateral trade liberalizations, but is most famous for the spread of a network of bilateral trade agreements across Europe in the wake of the Cobden–Chevalier treaty between France and the United Kingdom in 1860.
From the 1870s, industrial and commercial crises and falling prices in agriculture due to global market integration led governments to search for solutions to these policy challenges. Many European countries thus increased protection for agriculture and manufactured goods in which domestic import-competing producers struggled. At the same time, demands for renegotiations threatened the treaty network, and lapsing agreements were only provisionally prolonged.
From the late 1880s, the struggle between protection for import-competing producers and market access abroad for export-oriented producers led to internal and external conflicts over trade policy in many countries, including trade (or tariff) “wars.” A renewed network of less ambitious trade treaties than those of the 1860s restored a fragile equilibrium from the early 1890s, to be renewed and renegotiated roughly every 12 years as treaties approached their expiration date.
When looking at the country and commodity level it can easily be appreciated that the more or less common shifts during these periods at the European level were more pronounced in some countries than in others. For example, the United Kingdom, the Netherlands, Switzerland, and Belgium shifted more decisively to free trade and remained there, while liberalization was much less pronounced and more decisively undone in Portugal, Spain, Russia, and the Habsburg monarchy. The experiences of the Scandinavian countries, Germany, and France lie somewhere in between. Turkey and the countries that gained independence from the Ottoman Empire in the 19th century started as (forced) free traders and from the 1880s increased their duties, in part to meet growing fiscal demands. At the commodity level, tariffs on raw materials remained generally low and did not follow the protectionist backlash that affected foodstuffs. One exception was (initially) “tropical” goods such as sugar, coffee, tea, and tobacco, where many countries levied high tariffs to extract fiscal revenue. For manufactured goods, liberalization and protectionist backlash were milder than in agriculture, although there are many exceptions to this rule.
Article
Evaluation of Mental Health Interventions
Martin Knapp
Mental illnesses are highly prevalent and can have considerable, enduring consequences for individuals, families, communities, and economies. Despite these high prevalence rates, mental illnesses have not received as much public policy commitment or funding as might be expected. One result is that mental illness often goes unrecognized and untreated. The resultant costs are felt not only in healthcare systems, but across many other sectors, including housing, social care, criminal justice, welfare benefits, and employment.
This article sets out the basic principles of economic evaluation, with illustrations in this mental health context. It also discusses the main practical challenges when conducting and interpreting evidence from such evaluations.
Decisions about whether to spend resources on a treatment or prevention strategy are based on whether it is likely to be effective in avoiding, reducing, or curing symptoms, improving quality of life, or achieving other individual-level outcomes. The economic evaluation question is whether the outcomes achieved are sufficient to justify the cost that is incurred in delivering the intervention.
An economic evaluation has five elements: clarification of the question to be addressed; specification of the intervention to be evaluated and with what alternative it is being compared; the outcomes to be measured; the costs to be measured (including the cost of implementing the intervention and any savings that might accrue); and finally, how outcome and cost findings are to be blended to make a recommendation to the decision-maker. Sometimes, if an evaluation finds that one intervention has better outcomes but higher costs, then the evaluation should also how one (the outcomes) might be trade-off for the other (the costs).
The article illustrates how economic evaluations have been undertaken and employed to address a range of questions, from the very strategic issue to the more specific clinical question. The purpose of the study can, to some extent, determine the type of evaluation that is needed.
Examples of evaluations are given in a number of areas: perinatal maternal mental illness; parenting programs for conduct disorder; anti-bullying programs in schools; early intervention services for psychosis; individual placement and support; collaborative care for physical health problems; and suicide prevention. The challenges of economic evaluation are discussed, specifically in the mental health field.
Article
The Evolution of Forecast Density Combinations in Economics
Knut Are Aastveit, James Mitchell, Francesco Ravazzolo, and Herman K. van Dijk
Increasingly, professional forecasters and academic researchers in economics present model-based and subjective or judgment-based forecasts that are accompanied by some measure of uncertainty. In its most complete form this measure is a probability density function for future values of the variable or variables of interest. At the same time, combinations of forecast densities are being used in order to integrate information coming from multiple sources such as experts, models, and large micro-data sets. Given the increased relevance of forecast density combinations, this article explores their genesis and evolution both inside and outside economics. A fundamental density combination equation is specified, which shows that various frequentist as well as Bayesian approaches give different specific contents to this density. In its simplest case, it is a restricted finite mixture, giving fixed equal weights to the various individual densities. The specification of the fundamental density combination equation has been made more flexible in recent literature. It has evolved from using simple average weights to optimized weights to “richer” procedures that allow for time variation, learning features, and model incompleteness. The recent history and evolution of forecast density combination methods, together with their potential and benefits, are illustrated in the policymaking environment of central banks.
Article
The Evolution of Mental Health Policy and Economics
Sherry Glied and Richard Frank
Mental health economics addresses problems that are common to all of health economics, but that occur with greater severity in this context. Several characteristics of mental health conditions—age of onset, chronicity, observability, and external effects—make them particularly economically challenging, and a range of policies have evolved to address these problems. The need for insurance—and for social insurance—to address mental health problems has grown. There is an expanding number of effective treatments available for mental health conditions, and these treatments can be relatively costly. The particular characteristics of mental health conditions exacerbate the usual problems of moral hazard, adverse selection, and agency. There is increased recognition, in both the policy and economics literatures, of the array of services and supports required to enable people with severe mental illnesses to function in society’s mainstream. The need for such non-medical services, generates economic problems of cross-system coordination and opportunism. Moreover, the impairments imposed by mental disorders have become more disruptive to the labor market because the nature of work is changing in a manner that creates special disadvantages to people with these conditions. New directions for mental health economics would address these effects.
Article
Evolution of the Family: Theory and Implications for Economics
Ingela Alger and Donald Cox
Which parent can be expected to be more altruistic toward their child, the mother or father? All else equal, can we expect older generation members to be more solicitous of younger family members or vice versa? Policy interventions often target recipients by demographic status: more money being put in the hands of mothers, say, or transfers of income from young to old via public pensions. Economics makes predictions about pecuniary incentives and behavior but tends to be agnostic about how, say, a post-menopausal grandmother might behave, just because she is a post-menopausal grandmother. Evolutionary theory fills this gap by analyzing how preferences of family members emerge from the Darwinian exigencies of “survive and reproduce.” Coin of the realm is so-called “inclusive fitness,” reproductive success of oneself plus that of relatives, weighted by closeness of the relationship. Appending basic biological traits onto considerations of inclusive fitness generates predictions about preferences of family members. A post-menopausal grandmother with a daughter just starting a family is predicted to care more about her daughter than the daughter cares about her, for example. Evolutionary theory predicts that mothers tend to be more altruistic toward children than fathers, and that close relatives would be inclined to provide more support to one another than distant relatives. An original case study is provided, which explains the puzzle of diverging marriage rates by education in terms of heterogeneity in preferences for commitment. Economists are justifiably loathe to invoke preferences to explain trends, since preference-based explanations can be concocted to explain just about anything. But the evolutionary approach does not permit just any invocation of preferences. The dictates of “survive and reproduce” sharply circumscribe the kinds of preference-related arguments that are admissible.
Article
Exchange Rate Policies and Economic Development
Eduardo Levy Yeyati
While traditional economic literature often sees nominal variables as irrelevant for the real economy, there is a vast body of analytical and empirical economic work that recognizes that, to the extent they exert a critical influence on the macroeconomic environment through a multiplicity of channels, exchange rate policies (ERP) have important consequences for development.
ERP influences economic development in various ways: through its incidence on real variables such as investment and growth (and growth volatility) and on nominal aspects such relative prices or financial depth that, in turn, affect output growth or income distribution, among other development goals. Additionally, ERP, through the expected distribution of the real exchange rate indirectly, influences dimensions such as trade or financial fragility and explains, at least partially, the adoption of the euro—an extreme case of a fixed exchange rate arrangement—or the preference for floating exchange rates in the absence of financial dollarization. Importantly, exchange rate pegs have been (and, in many countries, still are) widely used as a nominal anchor to contain inflation in economies where nominal volatility induces agents to use the exchange rate as an implicit unit of account. All of these channels have been reflected to varying degrees in the choice of exchange rate regimes in recent history.
The empirical literature on the consequences of ERP has been plagued by definitional and measurement problems. Whereas few economists would contest the textbook definition of canonical exchange rate regimes (fixed regimes involve a commitment to keep the nominal exchange rate at a given level; floating regimes imply no market intervention by the monetary authorities), reality is more nuanced: Pure floats are hard to find, and the empirical distinction between alternative flexible regimes is not always clear. Moreover, there are many different degrees of exchange rate commitments as well as many alternative anchors, sometimes undisclosed. Finally, it is not unusual that a country that officially declares to peg its currency realigns its parity if it finds the constraints on monetary policy or economic activity too taxing. By the same token, a country that commits to a float may choose to intervene in the foreign exchange market to dampen exchange rate fluctuations.
The regime of choice depends critically on the situation of each country at a given point in time as much as on the evolution of the global environment. Because both the ERP debate and real-life choices incorporate national and time-specific aspects that tend to evolve over time, so does the changing focus of the debate. In the post-World War II years, under the Bretton Woods agreement, most countries pegged their currencies to the U.S. dollar, which in turn was kept convertible to gold. In the post-Bretton Woods years, after August 1971 when the United States abandoned unilaterally the convertibility of the dollar, thus bringing the Bretton Woods system to an end, the individual choices of ERP were intimately related to the global and local historical contexts, according to whether policy prioritized the use of the exchange rate as a nominal anchor (in favor of pegged or superfixed exchange rates, with dollarization or the launch of the euro as two extreme examples), as a tool to enhance price competitiveness (as in export-oriented developing countries like China in the 2000s) or as a countercyclical buffer (in favor of floating regimes with limited intervention, the prevalent view in the developed world). Similarly, the declining degree of financial dollarization, combined with the improved quality of monetary institutions, explain the growing popularity of inflation targeting with floating exchange rates in emerging economies. Finally, a prudential leaning-against-the-wind intervention to counter mean reverting global financial cycles and exchange rate swings motivates a more active—and increasingly mainstream—ERP in the late 2000s.
The fact that most medium and large developing economies (and virtually all industrial ones) revealed in the 2000s a preference for exchange rate flexibility simply reflects this evolution. Is the combination of inflation targeting (IT) and countercyclical exchange rate intervention a new paradigm? It is still too early to judge. On the one hand, pegs still represent more than half of the IMF reporting countries—particularly, small ones—indicating that exchange rate anchors are still favored by small open economies that give priority to the trade dividend of stable exchange rates and find the conduct of an autonomous monetary policy too costly, due to lack of human capital, scale, or an important non-tradable sector. On the other hand, the work and the empirical evidence on the subject, particularly after the recession of 2008–2009, highlight a number of developments in the way advanced and emerging economies think of the impossible trinity that, in a context of deepening financial integration, casts doubt on the IT paradigm, places the dilemma between nominal and real stability back on the forefront, and postulates an IT 2.0, which includes selective exchange rate interventions as a workable compromise. At any rate, the exchange rate debate is still alive and open.
Article
Exchange Rates, Interest Parity, and the Carry Trade
Craig Burnside
The uncovered interest parity (UIP) condition states that the interest rate differential between two currencies is the expected rate of change of their exchange rate. Empirically, however, in the 1976–2018 period, exchange rate changes were approximately unpredictable over short horizons, with a slight tendency for currencies with higher interest rates to appreciate against currencies with lower interest rates. If the UIP condition held exactly, carry trades, in which investors borrow low interest rate currencies and lend high interest rate currencies, would earn zero average profits. The fact that UIP is violated, therefore, is a necessary condition to explain the fact that carry trades earned significantly positive profits in the 1976–2018 period. A large literature has documented the failure of UIP, as well as the profitability of carry trades, and is surveyed here. Additionally, summary evidence is provided here for the G10 currencies. This evidence shows that carry trades have been significantly less profitable since 2007–2008, and that there was an apparent structural break in exchange rate predictability around the same time.
A large theoretical literature explores economic explanations of this phenomenon and is briefly surveyed here. Prominent among the theoretical models are ones based on risk aversion, peso problems, rare disasters, biases in investor expectations, information frictions, incomplete financial markets, and financial market segmentation.
Article
Experimental Economics and Experimental Sociology
Johanna Gereke and Klarita Gërxhani
Experimental economics has moved beyond the traditional focus on market mechanisms and the “invisible hand” by applying sociological and socio-psychological knowledge in the study of rationality, markets, and efficiency. This knowledge includes social preferences, social norms, and cross-cultural variation in motivations. In turn, the renewed interest in causation, social mechanisms, and middle-range theories in sociology has led to a renaissance of research employing experimental methods. This includes laboratory experiments but also a wide range of field experiments with diverse samples and settings. By focusing on a set of research topics that have proven to be of substantive interest to both disciplines—cooperation in social dilemmas, trust and trustworthiness, and social norms—this article highlights innovative interdisciplinary research that connects experimental economics with experimental sociology. Experimental economics and experimental sociology can still learn much from each other, providing economists and sociologists with an opportunity to collaborate and advance knowledge on a range of underexplored topics of interest to both disciplines.
Article
Explaining the Mathematics Gender Gap: The Role of Stereotypes
Pilar Cuevas Ruiz, Ismael Sanz, and Almudena Sevilla
Descriptive stereotypes such as “girls are not good at mathematics” or prescriptive stereotypes, that is, fixed views about women’s societal roles, can explain the persistent gender gap in mathematics. Stereotypes lower girls’ beliefs, expectations, and incentives to put forth effort, and can constrain girls’ choices in male-dominated high-paying careers that are math-intensive and that require strong math skills. This gap slows progress toward gender equality in the labor market and hinders productivity and economic growth.
Policy interventions to alleviate the negative impacts of descriptive stereotypes aim to prevent girls from internalizing socially constructed behaviors aligned with prevalent gender stereotypes regarding the innate mathematical abilities of boys and girls. Boosting girls’ confidence in their math skills includes introducing them to female role models, such as women math teachers, using gender-neutral language, and providing textbooks and other teaching materials that challenge gender stereotypes. A different set of policies focuses on altering the environment in which girls learn, rather than modifying their beliefs. By adjusting the testing methods (such as reducing the level of competition) or adapting the instructional approach to better align with the learning style of girls, it is possible to create an environment that enables more girls to achieve their maximum potential and to accurately assess their math abilities and interests, rather than simply their test-taking or classroom performance.
However, interventions that aim to modify the beliefs and attitudes of girls and women ex post, as well as those that seek to alter the environment, may not work in the long term because they reinforce preexisting stereotypes and operate within the constraints of those stereotypes. For instance, while modifying the testing environment may result in higher grades for girls, it may not necessarily alter the perception that girls are incapable of excelling in math. In some cases, these interventions may even have negative consequences. Encouraging girls to “lean in” and behave like boys, for example, can lead to unequal, unjust, and inefficient outcomes because the benefits (economic returns) of doing so are lower or even negative for girls in light of existing gender stereotypes.
One popular and affordable approach to combating gender stereotypes involves addressing (unconscious) biases among teachers, parents, and peers through initiatives such as unconscious bias training and self-reflection on biases. The underlying premise is that by increasing awareness of their own (unconscious) biases, individuals will engage their more conscious, non-gender-stereotypical thinking processes. However, such behavioral interventions can sometimes have unintended consequences and result in backlash, and their effectiveness may vary significantly depending on the context, so that their external validity is often called into question.
The recognition of the adaptable nature of both conscious and unconscious stereotypes has led to progress in economics, with the development of social learning and information-based theories. Interventions resulting from these models can effectively counteract prescriptive stereotypes that limit girls’ education to certain fields based on societal expectations of gender roles. However, prescriptive gender stereotypes are often based on biased beliefs about the innate abilities of girls and women. Overcoming deeply ingrained descriptive stereotypes about innate abilities of boys and girls is a fruitful avenue for future economics research and can help close the gender performance gap in mathematics.
Article
Famines, Hunger, and Later-Life Health
Gerard J. van den Berg and Maarten Lindeboom
Modern-day famines are caused by unusual impediments or interventions in society, effectively imposing severe market restrictions and preventing the free movement of people and goods. Long-run health effects of exposure to famine are commonly studied to obtain insights into the long-run effects of malnutrition at early ages. This line of research has faced major methodological and data challenges. Recent research in various disciplines, such as economics, epidemiology, and demography, has made great progress in dealing with these issues. Malnutrition around birth affects a range of later-life individual outcomes, including health, educational, and economic outcomes.
