the part-time premium enigma: an assessment of the chilean case

The Part-time Premium Enigma:An Assessment of the Chilean Case

Andrea Bentancor? and Virginia Robano§

? ComunidadMujer and Universidad Adolfo Ibanez§ Institute for International Economic Policy, George Washington University

GDN 14th Annual Global Development ConferenceJune 19-21, 2013

Manila, Philippines

Bentancor and Robano (CM, UAI, IIEP) Part-time work GDN 2013 1 / 15

Outline

1 Contribution 1: document that in Latin America there is a positivecorrelation between part-time and hourly earnings

2 Contribution 2: Analysis of the case of Chile; part-time penalty

3 Contribution 3: Possible explanations for the sign reversal

4 Conclusions and Policy Implications


What do we do in this paper? Contribution 1

Part-time work is being promoted in order to increase female laborforce participation rates.

The evidence for Chile (Rau 2010) and Honduras (Lopez Boo et al.2010) shows a positive relationship between hourly earnings andpart-time work.

We show that the positive correlation between part-time job statusand hourly earnings is present in several Latin American countries.


Contribution 1: The Part-time Premium in Latin America

OLS estimations with robust s.e.

HH surveys circa 2005, sample offemales in the [15-64] age bracket.

In developed countries, the hourly ratein part-time is smaller than in full-time(OECD).

FemalesArgentina 0.16

(0.02)***Bolivia 0.55

(0.08)***Brazil 0.25

(0.01)***Costa Rica 0.35

(0.03)***Chile 0.34

(0.01)***Honduras 0.43

(0.02)***Mexico 0.31

(0.02)***Paraguay 0.28

(0.03)***Peru 0.50

(0.08)***Uruguay 0.22

(0.01)***Venezuela, RB 0.12

(0.03)***


Descriptive Statistics, Female Working Population

� Rau (2010, 2012) callspart-time work‘precarious’� Descriptive Statisticsconfirm that females inpart-time are (comparedto those in full-time):

Poorer

Less educated

More likely to havechildren aged 5-14in the house

Part-time Full-time Difference

Hours worked 19.11 47.09 -27.98***(0.14)

Monthly earnings in $ 172436.11 276880.34 -104444.23***in USD 211.00 341.00 (4411.63)

Hourly earnings 2879.00 1432.71 1446.29***approx. in USD 3.50 1.76 (41.96)

Ln of hourly earnings 7.42 7.02 0.40***(0.01)

Urban 0.77 0.74 0.03***(0.01)

Poor 0.13 0.05 0.08***(0.00)

Years of schooling 10.32 11.21 -0.89***(0.05)

Age 38.88 37.86 1.02***(0.16)

Married/with partner 0.52 0.49 0.03***(0.01)

Number of children 5-14 0.73 0.65 0.07***(0.01)

Number of children 0-4 0.30 0.29 0.01(0.01)

Number of observations 5826 21338


What do we do in this paper? Contribution 2

We identify and unbiasedly estimate the causal effect of working part-timeon hourly earnings for Chilean females.

Had we available random data, we would use OLS.

Though the standard answer in the literature is to use instrumentalvariables, there is no strong, credible instrument (to our knowledge)capable of distinguishing between the decision of working part-timeand the decision of participating in the labor market.

� Using an estimation strategy that does not rely on the existence of aninstrument(s) for identification, we find that there is a negative causaleffect from working part-time on hourly earnings of about 20 percent forsome groups of workers.


The Model

Consider the triangular model:

wi = α + βPTi + X ′i ϕ+ εi (1)

PTi = 1{X ′i κ+ νi > 0} (2)

where wi denote earnings; PTi is the probability of working part-time; Xi isa vector of human capital characteristics and 1{·} is the indicator function.

� Our objective is to identify and unbiasedly estimate β. intuition

Mroz (1999) noted that even if errors were homoskedastic, becausethe probability model is non linear, it would still be possible toidentify the model, but using data only from the tails.

Rigobon (2003) and Klein and Vella (2009, KV) noted that if theerrors in equation (2) are heteroskedastic, this fact induces anexclusion restriction and it is thus possible to identify the model.


The Model

Assume that the error term in equation (2) is heteroskedastic of thefollowing form: νi = S(X ′π)ν∗i , where ν∗i is a zero-meanhomoskedastic error.

The probability of working part-time can be written as:

E[PT|X ] = Pr( X ′i κ

S(X ′π)

)(3)

derivation

thus the predicted probability of treatment becomes a validinstrument.


Sources of Heteroskedasticity in the part-time equation:

Education

Age (experience)

Regional variables

Demographic characteristics

Measurement Error

Selectivity issues


Results from OLS and IV regressions - Part-time coefficient

OLS IV KV-IV KV-IV KV-IV(1) (2) (3) (4) (5)

All females 15-59 0.42 0.62 -0.04 -0.07 -0.08(0.01)*** (0.35)** (0.12) (0.16) (0.16)

in percentages 52% 86% -4% -7% -8%

Dependent workers 0.32 0.84 -0.36 -0.25 -0.48(0.01)*** (0.56)* (0.12)*** (0.14)** (0.16)***

in percentages 38% 132% -30% -22% -38%

Formal status 0.39 -0.74 -0.17 n/a -0.40(0.02)*** (0.90) (0.18) n/a (0.20)**

in percentages 48% -52% -16% n/a -33%

column 3: KV-IV with same explanatory variables than column 1, no selcorrection

column 4: KV-IV with same than column 3 plus informal status on the wageequation

column 5: KV-IV with column 4 plus selection correction on the wageequation


Results from OLS and IV regressions, including experiencein present job - Part-time coefficient

OLS IV KV-IV KV-IV KV-IV(1) (2) (3) (4) (5)

All females 15-59 0.43 1.46 -0.14 -0.26 -0.32(0.01)*** (0.44)*** (0.12) (0.17)* (0.18)**

In percentages 54% 331% -13% -23% -27%

Dependent workers 0.33 3.41 -0.56 -0.45 -0.40(0.01)*** (1.27)*** (0.14)*** (0.18)** (0.18)**

In percentages 39% 2927% -43% -36% -33%

Formal status 0.40 3.79 -0.38 n/a -0.36(0.02)*** (1.73)** (0.18)** (0.18)**

In percentages 49% 4326% -32% -30%


Contribution 3: Possible explanations for the sign reversal

� Possible explanations:

precariousness conditions

interaction with informality

demand side factors

measurement errors


Conclusions

Contribution 1: Similar to other studies in developing countries, we showthe existence of a positive association between part-time jobsand hourly earnings.

Contribution 2: When we address the presence of unobserved factors andidentify the effect of part-time on hourly earnings, theobserved positive correlation becomes a penalty.

Contribution 3: We conjecture that the reasons behind the sign reversal.


Policy Implications

Part-time work might increase female labor force participation,but it has adverse consequences in terms of gender equality:

Women are side-tracked

We show that formal/salaried workers are penalized

If part-time is involuntary (full-time jobs do not exist for them),then public policy has to assure that:

females do not face neither monetary penalties

nor low probability of accessing public social welfare benefits


THANK YOU!

www.comunidadmujer.cl/estudios www.virginiarobano.com


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the part-time premium enigma: an assessment of the chilean case

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