Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies
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Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies. / Caliendo, Marco; Mahlstedt, Robert; Mitnik, Oscar A.
I: Labour Economics, Bind 46, 06.2017, s. 14-25.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies
AU - Caliendo, Marco
AU - Mahlstedt, Robert
AU - Mitnik, Oscar A.
PY - 2017/6
Y1 - 2017/6
N2 - The main concern for many evaluation studies is that controlling for individuals' observed characteristics may not be enough to obtain valid treatment effects. We exploit a unique dataset that contains a rich set of administrative information on individuals newly entering unemployment in Germany, as well as several usually unobserved characteristics like personality traits, attitudes, expectations, social networks and intergenerational information. This allows us to empirically assess the effect of including these usually unobserved variables on the propensity score distribution, the matching quality, and the treatment effects obtained using unconfoundedness-based estimators. Our findings indicate that these variables play a significant role for selection into active labor market programs (ALMP), but do not make a significant difference in estimating treatment effects on wages and employment prospects. This suggests that the usually unobserved variables we analyze are not a threat to the validity of the estimated treatment effects, if comprehensive control variables of the type usually used in modern ALMP evaluations (which include labor market histories) are available. Our results also suggest that rich administrative data may be good enough to draw policy conclusions on the effectiveness of ALMPs.
AB - The main concern for many evaluation studies is that controlling for individuals' observed characteristics may not be enough to obtain valid treatment effects. We exploit a unique dataset that contains a rich set of administrative information on individuals newly entering unemployment in Germany, as well as several usually unobserved characteristics like personality traits, attitudes, expectations, social networks and intergenerational information. This allows us to empirically assess the effect of including these usually unobserved variables on the propensity score distribution, the matching quality, and the treatment effects obtained using unconfoundedness-based estimators. Our findings indicate that these variables play a significant role for selection into active labor market programs (ALMP), but do not make a significant difference in estimating treatment effects on wages and employment prospects. This suggests that the usually unobserved variables we analyze are not a threat to the validity of the estimated treatment effects, if comprehensive control variables of the type usually used in modern ALMP evaluations (which include labor market histories) are available. Our results also suggest that rich administrative data may be good enough to draw policy conclusions on the effectiveness of ALMPs.
KW - Matching
KW - Unconfoundedness
KW - Unobservables
KW - Selection bias
KW - Personality traits
KW - Active labor market policy
U2 - 10.1016/j.labeco.2017.02.001
DO - 10.1016/j.labeco.2017.02.001
M3 - Journal article
VL - 46
SP - 14
EP - 25
JO - Labour Economics
JF - Labour Economics
SN - 0927-5371
ER -
ID: 181994289