The right mix of migrants to meet Germany’s needs

kfz2“In past decades, Germany has made great strides with the integration of foreigners. Those achievements must be defended prudently and balanced with the country’s demographic challenges. Indiscriminately admitting all refugees from war, including often illiterate and unskilled youths, is bound to undermine these very impressive gains,” writes IZA’s founding director Klaus F. Zimmermann in today’s Wall Street Journal.

These are the key points he makes:

  • The increasingly heated debate over refugees inside German is causing a divide between the “welcomers” and the “door-closers”.
  • Germany needs a regular annual inflow of immigrants, including refugees, but their composition matters.
  • Therefore, an Immigration Act defining specific criteria and procedures for new arrivals is long overdue.
  • The most important driver of quick integration into a new society is a job.
  • However, the need for low to medium skilled manufacturing workers has greatly declined since the 1960s.
  • Germany must attract productive workers from all over the world, not just one war-torn region.
  • A mismanaged refugee crisis could convince many Germans to take the opposite stance, no longer wanting any more foreigners in their midst.

Read the complete article:
The Right Mix of Migrants to Meet Germany’s Needs

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Employee incentives: Bonuses or penalties? large empirical literature supports the view that linking payment to performance is highly effective in raising productivity. However, often little attention is paid to how performance incentives are implemented in employment contracts. While most employers work with bonuses, some also arrange penalty contracts that set a base wage, part of which can be lost if performance targets are not reached.

Daniele Nosenzo (University of Nottingham, UK) illustrates in his new IZA World of Labor article why penalties may be more effective than bonuses in order to reach performance targets. However he stresses that working with penalties may include hidden costs and other pitfalls as well.

Productivity gains of “carrots that look like sticks”

In an experiment, 68 MBA students were randomly assigned to one of two payment conditions. In the “bonus” condition, students were paid a base salary of $20 plus a bonus of $10 if the firm met the desired production target. In the “penalty” condition, students were paid a base salary of $30 minus a $10 penalty if the firm did not meet the target.

Objectively, both conditions are equivalent: in either case, the employee receives $30 if the target is met and $20 if it is not. However, the language used in the contracts differs: incentives were presented as rewards (“carrots”) in the bonus condition and as penalties (“sticks”) in the penalty condition. The results of the experiment are striking: Despite the economic equivalence of the two contracts, employees in the penalty condition were 17% more productive than those in the bonus condition.

Studies undertaken in real companies have confirmed that employees can be motivated to work harder when pay-for-performance contracts emphasize negative consequences of performance failure (“penalty contracts”) rather than positive consequences of bonus contracts. This is because individuals tend to be loss averse, i.e., they are typically more sensitive to the pain of losing something that they already have, than to the joy of gaining something they do not have.

The hidden costs of penalty contracts

Following the concept of loss aversion, firms could reap productivity gains by simple language adjustments of their employment contracts, at no extra financial cost to the firms. However, Nosenzo also highlights that penalty contracts may entail hidden costs for the employer.

First, as employers usually do not like provisions that are framed in terms of losses they might demand higher payments from firms to accept such employment contracts. Second, penalty contracts may be perceived as being unfair and controlling and can damage the trust relationship between employer and employee. Workers could become less productive in areas not regulated by the contract and might even, as some evidence suggests, resort to cheating or corrupt behavior.

While such pitfalls might explain why penalty contracts are rarely used by most firms, Nosenzo stresses that more evidence is needed on the potential drawbacks of penalty contracts to improve our understanding of their costs. He recommends that firms should closely monitor employees’ levels of satisfaction and perceptions of fairness when using penalty contracts, in order to promptly identify any impairments of the trust environment that may potentially offset any productivity advantage.

Read the complete article on IZA World of Labor:

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Labor market policy: Parts of the picture are missing

By Patrick Arni, Gerard van den Berg, and Rafael Lalive

front9457The standard empirical evaluations of labor market policy only consider the direct effects of single programs on their participants. This column* (based on IZA Discussion Paper No. 9457) argues that this fails to capture important aspects of real-world labor market policy – policy regimes and strategies. Using Swiss data, it employs a novel empirical approach that concurrently examines the effects of supportive and punitive policies (‘carrots’ and ‘sticks’). Policy regimes are shown to exert economically relevant effects, and accounting for these effects is crucial when designing labour market policy.

In many countries, governments spend substantial amounts on measures of labor market policy (LMP) for unemployed workers with the aim of increasing their chances and speed of finding a job. Spending on LMP may go above 1% of GDP in some OECD countries, reaching maximum burdens during recessions. During the Great Recession in the US, the OECD strongly recommended spending additional resources on supportive LMP, notably training and job search assistance. Surprisingly, empirical evidence on the effectiveness of LMP as a system is broadly missing, despite its widespread use in many OECD countries.

In the last two decades a considerable empirical literature on the effects of single LMP measures – like training, job search assistance, or sanctioning – has emerged (see IZA Discussion Paper No. 9236 for an overview). But in the real-world context of current unemployment insurance (UI) systems, several LMP programs run at once, following the policy strategies defined by public employment service (PES) authorities and implemented by caseworkers with discretionary powers. Depending on the goals of (local) policymakers, the weights on different types of programs and ‘philosophies’ may differ – do they provide support or put pressure on job seekers?

Assessing policy regimes

Getting a consistent picture on the effects of LMP within a UI or welfare system requires more than evaluating the direct treatment effects of a single program. We focus on one key aspect: the regime effect of a program. We operationalize this by how intensively a caseworker or a PES intends to use a program. Policymakers and implementers, PES agencies and caseworkers produce policy regimes which act over and beyond single treatments.

Regime effects may act through the general comprehensive guidance approach of the PES agencies and the caseworkers towards their clients, for example, through applying different levels of strictness or different frequencies of use of certain policy types. Moreover, regimes may operate via information spillovers. Strongly supportive regimes may invest more effort in getting to know the job seeker in order to set up a more targeted treatment plan.

A more effective service may enhance the job seeker’s search efficiency (how and where to search) and increase job offer arrival rates, also before participation or even without individuals actually joining an LMP program. The same applies to restrictive policies like sanctioning and monitoring; they may affect job seekers through ‘threat’ or pressure, also without the sanction being actually (yet) imposed. Thus, the potential relevance of regime effects is supported by the fact that they can affect everyone in the system, treated or untreated.1

We show how regime effects can be identified and estimated using detailed large-scale register data on job seekers in Switzerland. We discuss how to measure policy regime intensities and develop a framework to jointly estimate different effects – of regimes by PES agencies and caseworkers on the one hand, and of specific treatments on program participants on the other hand.

Moreover, we distinguish the effects of supportive policies (‘carrots’) – notably, training and job search assistance programs – from the effects of punitive policies (‘sticks’) – sanctions and workfare programs. Assessing all these effects in one model offers the crucial advantage that we can evaluate the relative importance of different elements in the system as well as their interplay. This offers a substantially more comprehensive picture of the impacts that labor market policy really exerts on concerned individuals.

Results: Regime effects matter

We exploit detailed register data for 130,000 individual job search spells for men of all ages in Switzerland between 2000 and 2005. Switzerland is particularly suitable for such an exercise since the different LMP intensities vary substantially across the country. We combine registers that report LMP events in daily precision, detailed socio-demographic and UI benefit-related eligibility information as well as individual social security earnings data for several years before and after unemployment. Importantly, we observe policy implementers – PES agencies and caseworkers – in the data as well.

The study considers two individual labor market outcomes, which cover the mid run and the short run: average monthly earnings within the 3.5 years after unemployment exit on the one hand, and unemployment duration on the other. Figure 1 visualizes some key results on the effects of different types of regimes and treatments on mid-run earnings. As to be expected from existing evidence, being treated by at least one ‘stick’ significantly reduces individual earnings after unemployment; on the other hand, participating in a supportive program affects earnings positively.

Figure 1. Treatment and regime effects of Carrots and Sticks, in % of average earningsNotes: Effects are expressed in percent of average monthly earnings within 3.5 years after unemployment (3547 CHF = 3290 EUR = 3575 USD in sample). Treatment effects: effects of being exposed to at least one carrot (job search assistance, training) or stick (sanction, workfare program). Regime effects: marginal effect of changing policy intensity by 0.1.

However, on top of these effects directly arising from program participation, we find economically relevant effects of supportive and punitive policy regimes. Both PES agencies and caseworkers contribute to these additional LMP effects. Increasing the intended frequency of use of restrictive policies by 10 percentage points (i.e., about half a standard deviation) reduces realized earnings by about 4%. Increasing the use of supportive policies, on the other side, improves earnings by about 2.5%.

Interestingly, more intense use of both carrot and stick regimes causes significant reductions in unemployment duration. It is important to note that these regime effects apply to everyone at any time, not only to program participants after treatment as in the case of the ‘classical’ treatment effects. This underlines the economic relevance of these newly identified LMP effects.

We also address the question how labor market policy mixes could be optimized. Our study provides a set of ‘experiments’ which simulate how marginal policy regime changes would affect earnings and unemployment durations of the job seekers as well as the cost of UI. Figure 2 summarizes the results for two ‘experiments’. The first assumes that PES agencies and caseworkers would decide to increase the use of both types of regimes – carrots and sticks – by half a standard deviation (about 10 percentage points) above median policy intensity. The second assumes an increase in the supportive policy regime and a decrease in the punitive regime of the same size.

Figure 2. Marginal effects of changing policy regimes: Two scenariosNotes: Marginal effects of changing the regimes by 0.5 standard deviation (i.e., about 0.1 in policy intensity). Earnings changes: in percent of average monthly earnings of non-treated individuals. Cost changes: in percent of total benefit cost per person.

The results are striking in documenting the relevance of policy regimes and their interplay. Intensifying both carrots and sticks generates a relevant reduction in individual unemployment duration (-20 days), at the expense of achieving lower earnings (-3%) after unemployment. UI saves about 6.2% of cost, mostly due to the reduced unemployment durations. The second experiment, which puts more weight on supportive regimes, is favorable for the individual’s pay, at the expense of some additional cost for UI.


This novel empirical approach of jointly assessing the effects of labor market policies demonstrates that we miss out on an important part of LMP impacts when only focusing on the consequences of single treatments. Policy regimes matter – their effect, which comes on top of classical program effects, is significant. Considering regime effects can change the assessment of the total effect of certain types of policies on individual labor market outcomes. For instance, supportive policies are positive when taking into account regime effects. Only considering short-run treatment effect results in a negative evaluation, since unemployment duration appears to be prolonged (due to the so called ‘lock-in’ effect).

However, when including regime effects the picture changes – supportive regimes as a whole can reduce unemployment durations and show positive impacts on individual earnings. Applying a comprehensive framework to UI or welfare registers in different countries can offer instructive new empirical tools for policy optimization.2 The framework can easily be extended to other different types of assessed policies. Applying it on a large scale, covering different policy intensities, can produce useful sets of estimates of marginal effects of LMP. These can be used as inputs for policy optimization exercises. Policymakers need, however, to first fix their objectives. What is most important – reducing unemployment durations, improving individual job stability and welfare, or saving on the UI budget?

(*This column was originally published on; edited and reposted with permission.)

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New forms of work and shady employers: How reputation can discipline the “gig economy”

onlineworkersUber, Airbnb, TaskRabbit, and other online platforms have drastically reduced the price of micro-contracting and grown a “gig” economy, where workers must more frequently decide which potential employers to trust. Traditionally, workers have used labor unions and professional associations as a venue for exchanging information about working conditions and coordinating collective withdrawal of trade in order to discipline employers.

The rise of new institutions that facilitate information sharing may take up some of this role, a recent IZA discussion paper by Alan Benson, Aaron Sojourner and Akhmed Umyarov (all University of Minnesota) suggests. In two experiments in an online labor market (Amazon’s Mechanical Turk or M-Turk), the authors show that a public, employer-reputation system has value for:

  1. workers who use it to screen potential employers on otherwise unobservable differences, and
  2. employers who can benefit when a better reputation makes it easier to attract more workers of any given quality, basically shifting out the labor supply curve they face.

The experiments provide the first estimates of the value of employer reputation measured outside the lab based on any design more credible than a control function and highlight the under-appreciated struggles workers face in navigating the labor market.

The first experiment tests the validity of the reputations from the perspective of a worker. The researchers act as a worker to assess whether other workers’ public ratings reflect real variation in employer quality. One research assistant (RA) randomly selects tasks from employers who have good reputations, bad reputations, or no reputation and sends them to a second RA who is blind to employers’ reputations. Benson, Sojourner and Umyarov  find that, holding work effort fixed, effective wages while working for good-reputation employers is 40 percent greater than effective wages while working for bad-reputation employers.

Employers with bad reputation must post 200% higher wages

The second experiment measures how employers’ reputations affects their ability to recruit workers. We create multiple employers on M-Turk with varying reputations and, holding all else fixed, measure differences in the rate at which they attract workers to posted jobs. Good-reputation employers attract workers about 50 percent more quickly than our otherwise-identical no-reputation employers and 100 percent more quickly than bad-reputation employers. Average quality of work does not differ. This implies employers with better reputations can operate at a faster pace, a larger scale, or be more selective in hiring. Existing estimates of M-Turk wage elasticities imply that posted wages would need to be almost 200 percent greater for bad-reputation employers to attract workers at the same rate as good-reputation employers do.

Most models of the labor market assume workers have perfect information about employer differences and gloss over the difficulty workers face in navigating these matters. The authors of the IZA Discussion Paper propose a simple, equilibrium-search model consistent with their results. Informed-type workers screen employers with bad reputations, and the threat of losing a good reputation and thus losing informed workers discourages employers from engaging in wage theft and other forms of opportunism. In this way, employers’ reputation serves as collateral against wage theft, effectively substituting for the role that formal contracts normally play in the labor market.

Overcoming the information problem

What relevance does this have for labor markets broadly? All workers strive to distinguish which employers will treat them well or ill. Two prospective employers that offer identical employment contracts may actually differ widely in the criteria they apply for raises, promotions, terminations, scheduling, bonuses, task assignment, and many other working and payment conditions. In contingent, undocumented, and low-wage labor markets, concerns are as basic as whether employers will pay for all hours worked or pay at all.

Workers have always made decisions with partial information about employer quality and, so, these forces have always shaped labor markets. Falling communications costs have made it easier for workers to share information and several websites now enable this exchange, including Glassdoor, Turkopticon, Contratados, Kununu, JobeeHive, TheJobCrowd, and the Freelancers Union’s Client Scorecard. Attention to the worker’s information problem suggests innovative directions for policy and institution-building.

Download the complete paper (IZA DP No. 9510):

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Employers will check you out! Facebook profile pictures affect hiring chances

profile-picturesWhat many have already suspected has now been scientifically proven: Employers are screening job candidates through Facebook. In fact, your Facebook profile picture affects your callback chances about as strongly as the picture on your resume. This is the finding of a new IZA discussion paper by Stijn Baert (Ghent University).

Employers have very limited information when they make their first selection of applicants for their vacancies. A CV and short motivation letter may provide little insight into the personality of the candidates. In contrast, nowadays, the internet offers a lot of information to further refine a first impression. One potential source of information is the social networking website Facebook.

The research team from Ghent University examined on a scientific basis whether employers actually use Facebook during a first screening. They sent fictitious application letters in response to genuine vacancies. Entering the names of these fictitious job candidates in the Facebook search bar or in Google led exclusively to one of four fictitious Facebook profiles controlled by the research team. Only the Facebook profile picture was publicly visible. The four photos used varied in terms of physical attractiveness and apparent personality traits.

More screening of educated workers via Facebook

The researchers then compared the chances of positive responses for applicants with different Facebook profiles. The respective picture was viewable on Facebook but not included in the application letter. The candidate with the most favorable Facebook profile picture received approximately 21% more positive responses compared to the candidate with the least favorable profile picture. The chances to get an immediate invitation to a job interview even differed by almost 40%. “Given that these strong differences can be driven only by the Facebook profile picture, it is clear that many employers screen via Facebook,” says Stijn Baert.

The results also show that highly educated applicants are more likely to be screened via Facebook than the less educated. Contrary to what one should expect, occupations with regular customer contact are not more prone to Facebook screening than others.

Photos on Facebook and CV have similar effects

In a parallel experiment, the researchers added the Facebook profile pictures of the first experiment to the CVs of applicants whose names did not lead to a (unique) Facebook profile. The differences in attractiveness and personality had about the same impact in terms of callback rates as when they were posted on Facebook.

This finding is remarkable because not all employers are screening via Facebook, but they all see the photograph attached to the CV. A possible explanation why a Facebook profile picture and a resume photo can have the same impact is that employers may regard a Facebook profile picture as a more “honest” signal, given that not all candidates are aware that employers will check them on Facebook.

Ethical and appropriate?

The fact that employers are screening via Facebook does not imply that this is ethically and economically justified. Regarding the ethical side, employers should not be blamed since it is the responsibility of those who use social networking sites to manage their privacy settings and keep track of what information they make public. On the other hand, anti-discrimination laws may apply. In Belgium, where the experiment was conducted, a 2007 federal law prohibits unequal treatment of applicants on the basis of information gathered on ethnicity, religion, sexual orientation, health status and related characteristics.

From an economic perspective, screening via Facebook seems efficient. “Facebook allows employers to collect information on job candidates in a quick and easy way. Moreover, international research suggests that the impression gained on Facebook reflects the person’s actual personality traits and not their self-idealization,” says Stijn Baert.

How the experiment was set up

Within the framework of the study, a total of 2,112 job applications were sent out in response to vacancies in various sectors of the Flemish labor market. For each job opening, a pair of male graduates with degrees in commerce, business administration, or applied economics was constructed.

The CVs and motivation letters differed in detail and layout but were similar in productivity-influencing characteristics. The only substantial difference was the candidate’s name (first part of the experiment) or picture (second part). These features were randomly assigned to the application pairs. The photos used were selected for their different scores in attractiveness and personality (with a focus on conscientiousness) as recorded in an earlier study (IZA DP No. 7847) on the importance of these features in the labor market.

This study is the first to directly measure the impact of Facebook profiles on hiring chances. Previous research relied mainly on surveys of employers about their Facebook use. The results of such research may be distorted because reported attitudes may deviate from actual hiring behavior, and using social media does not mean letting social media affect hiring decisions.

Download the complete study (IZA DP No. 9584):

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Award-winning paper on the costs of environmental policy

ylea2015The study by Reed Walker (UC Berkeley) on “The Transitional Costs of Sectoral Reallocation: Evidence from the Clean Air Act and the Workforce” (Quarterly Journal of Economics, 2013) is recognized with the 2015 IZA Young Labor Economist Award. The author received the award at the IZA reception held during the ASSA Annual Meeting in San Francisco earlier this week. The key findings from the award-winning paper are summarized below.

coal-fired-power-plantEnvironmental policy pertaining to air pollution has been estimated to have large health benefits. However, these policies also come with costs. Production is typically reallocated away from newly regulated industries to other sectors and locations, and this creates a broad set of private and social costs. In terms of labor inputs, this reallocation is often framed in terms of “jobs lost,” and the distinction between “jobs versus the environment” is one of the more politically salient aspects of these regulations.

However, workers often find new jobs elsewhere, perhaps in different locations and/or industries. If workers simply transition from one employer to the next without significant earnings loss, then job loss should not be considered a cost when evaluating policy. If workers lose job- or industry-specific skills and/or experience long periods of unemployment following job transitions, the cost of reallocating the workforce could be quite large. There also may be costs to workers who remain in these potentially less productive industries.

Shift in production and employment away from polluting sectors

The paper by Reed Walker uses newly available longitudinal data on workers and firms to estimate the incidence of regulation-induced worker reallocation stemming from the 1990 Clean Air Act Amendments (CAAA) in the United States. The 1990 CAAA created a new class of pollution standards and strengthened existing standards so that many areas of the United States fell under a new regulatory regime. These regulations led to a sectoral shift in production and employment away from newly regulated, polluting sectors. The empirical framework estimates the effect of this regulatory shock on the evolution of earnings for the workers in newly regulated plants.

In doing so, the paper offers an approach to characterizing the costs and consequences of external labor market innovations when production and workers are not instantly reallocated elsewhere within the economy. Using the confidential Longitudinal Employer Household Dynamics (LEHD) data set from the U.S. Census Bureau, Walker is able to follow workers across their jobs over time to explicitly incorporate two substantive features of labor market adjustment that are typically studied in isolation: the wage costs borne by workers who remain in the newly regulated, now less productive sector and the long-run earnings losses for those who leave the sector

Although the empirical setting pertains to environmental regulations, the analysis relates to a large literature on the costs and incidence of labor market adjustment to external factors, such as trade, immigration, or innovations in labor demand. Traditionally, work in this area examines how prices in industries or regional labor markets respond to external labor market shocks, and then the estimates are used to back out a measure of welfare or incidence.

Reallocative costs are significant, but pale compared to health benefits

In contrast, the study observes and estimates both worker-specific nonemployment durations and any long-run earnings changes associated with the reallocation of production and workers. In doing so, the paper provides an empirical framework for better understanding the distributional implications associated with the short- and medium-run reallocation of the labor force in the context of external labor market innovations.

The results suggest that the reallocative costs to the workforce from the 1990 CAAA are significant. For those workers in the regulated sector prior to the change in regulation, the average earnings declined by more than 5% in the three years after the regulation. These earnings declines are persistent and only begin to recover some five years after the policy.

The average worker in a regulated sector experienced a total earnings loss equivalent to 20% of their preregulatory earnings. While these one-time transitional costs are substantial for the affected workforce, they pale in comparison to the contemporaneous and future health benefits of the 1990 Clean Air Act Amendments.

[Download the paper here]

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Subsidized high-quality early care improves child development especially among children in low-income families

sun-handsHuman development starts early, and neuroscientists point to the first three years of brain development as especially consequential. Foundations for academic and social success later in life are created through the experiences in children’s earliest years.

Parents, relatives and many other non-relatives are responsible for the upbringing of children in modern societies. Public policy plays a crucial role in the process, either through the regulation of market-based care or through the direct provision of subsidized child care services. It is critical to understand the constraints and the incentives faced by families to choose a certain combination of caregivers for their young children.

There is little evidence available on how public policies that expand access to early care services during the first 36 months of life affect household behavior and consequently dictate effects on child development. A recent IZA discussion paper by Juan Chaparro and Aaron Sojourner, from the University of Minnesota, explores this issue using data from the Infant Health and Development Program (IHDP).

Same program, different outcomes

The IHDP was an intervention done in the United States during the 1980s with the goal of supporting the development of low birth weight and premature babies. Participants were selected at birth and randomly assigned to either a treatment or control group. Infants in the treatment group had access to home visits and free, high-quality childcare service between the ages of 12 months and 36 months. Family income was not a selection criteria for participation.

Therefore, the IHDP allows the study of household behavior across a broad range of family economic circumstances. 608 infants were assigned to the control group and 377 to the treatment group. The IHDP also collected extraordinarily rich data on quality and quantity of maternal and non-maternal care each child experienced, the allocation of mothers’ time between child care, work, and other uses, and each child’s skill development.

Previous literature has found a positive and significant treatment effect of the IHDP intervention on cognitive development by the end of the program, especially among children with birth weight closer to normal (Gross et al., 1997) and among children from low-income families (Duncan & Sojourner, 2013). However, each of these dimensions represents an opaque combination of stable characteristics and family choices. For instance, family income reflects parents’ choice of how many hours to work in the labor market and how much they can earn per hour. Low-income families include those who work for low wages and those with higher-earning potential who do not work outside the home.

Chaparro and Sojourner offer new evidence on the mechanisms driving the differences in effects. Their study explores if there are differences in the treatment effects depending on three key dimensions of heterogeneity across families: 1) the mother’s potential wage in the labor market; 2) the quality of prenatal investments chosen by the mother; and 3) the child’s endowment at birth, a measure of differences in child health status at birth compared to other children born under similar circumstances.

Interaction between quantity and quality of care matters

Figure 1 presents the gap of IQ at 36 months between children in the treatment and control group. The program had an effect on infants with a birth weight of at least 1.5 kilograms (first panel). The treatment effect varies by the mother’s potential wage (second panel). Children of mothers who could earn only a very low wage are the ones who benefited the most. The program had almost no effect on the cognitive development of children from mothers with a high earning potential in the labor market.

Figure 1: Predicted IQ at 36 months for IHDP treatment and control groups (National average = 100; Standard deviation = 16)

Figure 1: Predicted IQ at 36 months for IHDP treatment and control groups
(National average = 100; Standard deviation = 16)

Any effect of the IHDP intervention on child development must account for how families react to the intervention by reallocating their time and money, thus providing the child with a new combination of care inputs. The paper by Chaparro and Sojourner finds evidence of time and effort reallocation in response to the IHDP intervention across different types of families.

Figure 2: IHDP treatment effects on quality of maternal care (q^r)

Figure 2: IHDP treatment effects on quality of maternal care (qr)


Figure 3: IHDP treatment effects on hours per week of maternal care (r)

Consider Figures 2 and 3. They summarize the treatment effect on the quality and quantity of maternal care. The quality of maternal care is measured using components of the HOME score related to the promotion of learning and literacy, and the quantity of maternal care is measured in hours per week. The IHDP intervention triggered substantial changes in the behavior of low-wage mothers. The quality of maternal care provided by mothers with a low earnings potential was positively affected by the intervention (Figure 2, second panel). Simultaneously, this same group of mothers reduced their hours per week of maternal care (Figure 3, second panel).

In contrast to mother’s potential wage, neither differences in prenatal investment levels, which may proxy for family willingness to invest in child human capital development, nor differences in child endowment explain much of the variation in effects on child development or household resource allocation.

In conclusion, the paper offers new evidence that subsidies for high-quality early care improve child development especially among children in families with tight budget constraints due to low earning power. Biological factors and individual preferences appear much less important in driving the differences. Policies that promote the access to early childcare services must take into account the quality of the services provided and how different types of households will reallocate their own resources in response. Potential positive effects of any intervention could be augmented or eliminated by how families react to them.

Download the complete paper (IZA DP No. 9552):

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