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Why Cash Transfer Programs Can Both Stimulate and Slow Down Job Finding Cover

Why Cash Transfer Programs Can Both Stimulate and Slow Down Job Finding

Open Access
|Nov 2019

Figures & Tables

Table 1

Functional Forms and Parameters

FunctionsDescriptionFunctional FormSource
u(cu)Utility function(ccmin)1σ1σ,σ>0,1Chetty (2008)
λ(s, a)Cost of search efforte(μ1s+μ2a)1,μ1,μ20Cockx et al. (2018)
g(a)Subsistence productionGaγ,G>0,1>γ>0Our choice
P(s, a)Probability of finding a jobEsβ1eβ2a,E>0Our choice
ParametersBenchmarkSource
ɸJob destruction rate0.00443Shimer and Werning (2007)
rInterest rate0.001Shimer and Werning (2007)
βDiscount rate0.9991/1 + r
ECoefficient in front of P(s, a)0.2
β1Exponent of s in P(s, a)0.5
β2Exponent of a in P(s, a)0.5
wWage100
cminSubsistence level20
σRelative risk aversion (RRA)1.75Chetty (2008)
μ1Parameter of s in λ(s, a)0.3
μ2Parameter of a in λ(s, a)0.3
GScale parameter of g(a)22
𝛾Exponent if g(a) is isoelastic0.8
Figure 1

Baseline model [BM]. The three graphs show the level of a, s, and P(s, a), respectively, in the [BM] for different values of b. The functions and parameters are those of Table 1.

Figure 2

Sensitivity Analysis for the Baseline Model [BM]. These graphs report the results for 43 different specifications, all using the functions of Table 1. We take the parameterization of Table 1 and change one parameter at the time whose values are on the horizontal axis. “argmax P” is the level of b on the right vertical axis for which P(s, a) reaches the maximum.“Gross RR*” (respectively, “Net RR*”) gives the corresponding optimal gross (respectively, net) replacement rates on the left vertical axis: b/w (respectively, b/(w - 𝜏)).

Figure 3

These graphs show the shape of the job-finding probability P(s, a) for different values of β1, β2 and β1, n, respectively. The other functions and parameters are those of Table 1.

Figure 4

Finite Entitlement [FE]. The three graphs show the level of at, st and P(st, at), respectively, at the start of the unemployment spell, in the model [FE] for different values of b. The functions and parameters are those of Table 1, except for φ, which is now equal to zero. We set T = 200, the total quantity of time, and B = 100, the number of periods in which the agent is entitled to the flat benefit b.

Figure 5

Incomplete Financial Markets [FM]. The three graphs show the level of at, st, and P(st, at), respectively, at the start of the unemployment spell in the model [FM] for different values of b. The functions and parameters are those of Table 1, except for φ, which is now equal to zero; moreover, we allow the agent to get indebted up to 200 (two times the wage) and we assume that the agent has to repay her debt at the end of the T = B = 200 periods.

Figure 6

Stochastic Wage Offers [SWO]. The three graphs show the level of at and st and the exit probability, respectively, at the start of the unemployment spell, in the model [SWO] for different values of b. The functions and parameters are those of Table 1, except for φ, which is now equal to zero, and σ = 2. We set T = B = 200, the total quantity of time. We assume that wages are Pareto distributed with parameters wmin = 66.66 and α = 3.

Figure 7

Cash Transfer Effect [BM]. This graph shows the job-finding probability P(s, a) for different values of b. The continuous line is generated with the functions and parameters of Table 1. The dashed line uses the same functions and parameters, the only difference being that the agent receives a transfer of 10 regardless of her employment status.

Figure 8

Cash Transfer Effect. These graphs show the job-finding probability P for different values of b, for the extensions: [FE], [FM], and [SWO]. The continuous line is generated with the functions and parameters discussed in the previous section for each model, and the dashed line is generated with the same parameters except for the fact that the agent receives a transfer of 10 regardless of her employment status.

Language: English
Published on: Nov 27, 2019
Published by: Sciendo
In partnership with: Paradigm Publishing Services
JEL:

© 2019 Juliana Mesén Vargas, Bruno Van der Linden, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 License.