Average effects Sample Clauses

Average effects. Figure 2 shows Xxxxxx-Xxxxx estimates of the survival functions until exit to employment, that is, estimates of the probability of having found a job as a function of the time t since the start of the unemployment spell. Note that we do not censor observations if they leave registered unemployment without entering employment directly. Therefore, the estimated survival rate at a duration t simply equals the ratio of the number of individuals at risk (i.e. who have not found a job yet) divided by the size of the corresponding treatment group. We discuss standard errors of estimated effects in binary-outcome analyses below, so the discussion of the estimated functions is brief. The estimated functions for the four groups are virtually indistinguishable in first 120 days after the unemployment entry. This suggests that signing an IA very early has on average no short-term impact on the probability of getting a job. At higher durations (around the median of about 200 days) individuals assigned to group D have a lower probability of having entered employment. There seem to be no systematic differences between groups A, B and C. Next, we estimate linear probability models. In what follows we take treatment arm D (not-previously announced IA at 6 months) to be the reference category. The outcome yit is a binary indicator which is one iff an individual i moved to work before t, and Ai = 1 iff i is assigned to group A, etc. yit = β0 + AiδA + BiδB + CiδC + εit (4) We also estimate versions including a vector xi containing individual characteristics like age, nationality, education, last observed daily earnings and other labor market history indicators. Table 3 reports the latter results, for t equal to 90, 180, 270 and 365 days. Not surprisingly, the results without xi are virtually identical to those in the table. The coefficients for A, B and C are close to zero and insignificant at 90 days after entry into unemployment. At t = 180 and t = 270 the differences are not statistically significant either. The point estimates for effects at 270 days are around 2 to 3 percentage points for A, B and C as compared to D. At one year, the effect estimates range from 3 to 5 percentage points; these are statistically significant at the 5% level for A and C and at the 10% level for B. Thus, on average, being assigned to a late IA reduces the probability of re-employment within a year by about 4 percentage points, from 69% to 65%, and it commensurately increases the probability o...
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