Learning about job search: A ‘nudge’ to tackle long-term unemployment

Steffen Altmann, Armin Falk , Simon Jäger, Florian Zimmermann 03 August 2015

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Combatting unemployment is a first-order policy challenge. A key question that has attracted the attention of policymakers and researchers alike is how long-term unemployment can be effectively reduced (see, for example, Black et al. 2003 and Blundell et al. 2004 for the evaluation of policies aimed at tackling long-term unemployment in the US and UK). Long unemployment spells are particularly costly because they diminish job seekers’ future labour market opportunities. This is what economists refer to as ‘negative duration dependence’ (see Kroft et al. 2013 and Ericsson and Rooth 2014 for recent evidence). Typical labour market policies that aim at cutting down job seekers’ unemployment spells include a combination of training and counselling services as well as direct monetary incentives to take up new employment.

Using behavioural insights to improve job seekers’ employment prospects

In a new study, we systematically evaluate the effectiveness of a much less invasive policy tool—the provision of information and encouragement (Altmann et al. 2015). Recent research in labour, public, and behavioural economics has documented a multitude of informational and motivational challenges associated with unemployment and job search. We incorporate this body of knowledge into an information brochure, in order to help job seekers master precisely these challenges. Our intervention is inspired by a ‘nudge’-based approach that uses behavioural insights to inform the design of new policy instruments (Thaler and Sunstein 2008). Specifically, the brochure provided concise and easy-to-understand information about the current labour market situation as well as selected research results related to the effectiveness of active job search, different search strategies, and the non-pecuniary benefits of employment. In addition, the brochure aimed at motivating job seekers and encouraged them to actively search for new employment.

We evaluate the effectiveness of the brochure in a large-scale field experiment among roughly 54,000 job seekers in Germany. In the experiment, people who had recently entered unemployment were randomly allocated to a treatment or control group. Individuals assigned to the treatment group were sent a letter containing the information brochure. Job seekers in the control group did not receive the brochure, while otherwise facing identical conditions in terms of employment services and job search assistance. To investigate how the brochure affects job seekers’ labour market outcomes, we combined information on treatment assignment with administrative data from social security records. Our data set contains extensive information on sociodemographic characteristics and individuals’ employment history, as well as comprehensive information on individuals’ labour market outcomes in terms of employment and earnings after the intervention. Comparing these outcomes between treated and untreated individuals in administrative data allows us to cleanly identify the causal effects of the brochure untainted by measurement issues such as attrition bias that can plague survey studies.

Effects of the treatment on employment and earnings

The treatment effects in the overall sample are summarised in Figure 1. In the left panel, we document the treatment effect in terms of the difference in the overall number of days on which individuals in the treatment and control group were employed over the course of one year after the intervention. We depict estimates in intervals of four weeks, starting with the week immediately after our intervention. The point estimates for the treatment effects on employment suggest a generally positive influence of the brochure.

  • One year after the intervention, individuals in the treatment group are, on average, employed for approximately 1.2 additional days relative to the control group.

Figure 1 also presents results in terms of cumulative earnings.

  • The corresponding increase in labour market earnings for treated individuals amounts to €155.

While the long-term effects of the intervention in the overall sample are generally positive and non-negligible, they are too imprecisely estimated so that the point estimates are not statistically significant.

Figure 1. Key outcome measures for the overall sample

Notes: Each blue dot denotes the point estimate for the treatment effect at a given time horizon. The blue lines denote 95% confidence intervals.

In a second step of our analysis, we examine how our treatment affects a subgroup of job seekers that is of particular interest to policymakers and researchers, individuals who are at risk of becoming long-term unemployed. This group has been at the centre of the policy debate in the last decades, in particular since the Great Recession. In addition, previous research has documented a tight theoretical and empirical link between the prevalence of behavioural biases—specifically present bias as well as biases in probability judgment and confidence—and longer unemployment duration (see, e.g., DellaVigna and Paserman 2005 and Spinnewijn 2015). As our brochure aims to tackle the informational and behavioural challenges that job seekers face, it is plausible that treatment effects are concentrated among individuals at risk of long-term unemployment, since the challenges themselves are likely to be particularly prevalent in this group.

To evaluate the causal effects of our treatment among individuals at risk of long-term unemployment, we first identify a subsample of job seekers who are prone to remain unemployed for a particularly long time period given their educational background, labour market history, and other pre-determined individual characteristics. Our key findings for this group are summarised in Figure 2. Our data document strongly positive treatment effects for the at-risk group that are both economically as well as statistically significant.

  • Specifically, we find that the brochure causes an increase in cumulative employment and earnings in the year after the intervention of about 4% (4.7 days and €450, respectively), relative to the corresponding group of at-risk individuals in the control condition.

Notably, the employment effects do not come at the cost of lower wages, suggesting that the brochure improves the employment prospects of individuals at risk of long-term unemployment without having detrimental consequences for the quality of resulting employment matches. Furthermore, the results are qualitatively robust to considering alternative definitions of individuals at risk of long-term unemployment, e.g., based on previous unemployment durations or the wage level prior to the intervention.

Figure 2. Results for individuals at risk of long-term unemployment

Notes: Each blue dot denotes the point estimate for the treatment effect at a given time horizon. The blue lines denote 95% confidence intervals.

As a further robustness check, we estimate the treatment effects of our intervention for the subgroup of individuals at risk of long-term unemployment based on repeated split-sample estimators. This follows a suggestion by Abadie et al. (2013) who document that endogenous stratification approaches such as the one we employ to determine the at-risk group may lead to substantial biases in the estimated treatment effects. Reassuringly, the estimated increases in employment and earnings in the at-risk group are almost identical in specifications using the repeated split-sample estimator, which solves the potential problem with endogenous stratification procedures and suggests that the strong positive estimates for the treatment effects in the at-risk group are not spurious.

Summary and concluding remarks

We find that:

  • Informing job seekers about insights in labour, public, and behavioural economics can be an effective policy tool to improve their employment prospects.
  • The treatment effects of our intervention are concentrated among job seekers who are at risk of becoming long-term unemployed, rendering the brochure an effective tool to complement existing policies that aim at combatting long-term unemployment.
  • In light of the extremely low costs of the brochure (the total costs of production and mailing were less than €1 per brochure), our intervention yields a tremendously positive cost-benefit ratio for a targeted intervention.

References

Abadie, A, M M Chingos, and M R West (2013), “Endogenous Stratification in Randomized Experiments”, NBER Working Paper No. 19742.

Altmann, S, A Falk, S Jäger, and F Zimmermann (2015), “Learning about Job Search: A Field Experiment with Job Seekers in Germany”, IZA Discussion Paper No. 9040.

Black, D A, J A Smith, M C Berger, and B J Noel (2003), “Is the Threat of Reemployment Services More Effective than the Services Themselves? Evidence from Random Assignment in the UI System”, The American Economic Review, 93 (4), 1313–1327.

Blundell, R, M Costa Dias, C Meghir, and J Van Reenen (2004), “Evaluating the Employment Impact of a Mandatory Job Search Program”, Journal of the European Economic Association, 2 (4), 569–606.

DellaVigna, S and M Daniele Paserman (2005), “Job Search and Impatience", Journal of Labour Economics, 23 (3).

Eriksson, S, and D-O Rooth (2014), “Do Employers Use Unemployment as a Sorting Criterion When Hiring? Evidence from a Field Experiment”, The American Economic Review, 104 (3), 1014-1039.

Kroft, K, F Lange, and M J Notowidigdo (2013), “Duration Dependence and Labour Market Conditions: Evidence from a Field Experiment”, Quarterly Journal of Economics, 128 (3), 1123–1167.

Spinnewijn, J (2015), “Unemployed but Optimistic: Optimal Insurance Design with Biased Beliefs,” Journal of the European Economic Association, 13 (1), 130–167.

Thaler, R and C Sunstein (2008), Nudge – Improving Decisions About Health, Wealth, and Happiness,  New Haven, CT: Yale University Press, 2008.

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Topics:  Labour markets

Tags:  unemployment, long-term unemployment, job seeking

Associate Professor of Economics, University of Copenhagen

Professor of Economics at the University of Bonn and CEPR Research Affiliate

PhD candidate in economics, Harvard University

Postdoc, University of Zurich

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