ERF 22nd Annual Conference

Labour Markets: Special Event Session

Migration & Informality: ERF’s role

Jackline WahbaUniversity of Southampton (UK) and ERF

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ERF’s Role• Micro Data

•Funding and collecting e.g. Labour Market Survey Panels; Micro and Small Enterprise Surveys

•Open Access Micro Data Initiative (OAMDI)

•Funding of research papers and projects

•Training and building capacity

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ERF’s Impact• Enabling high quality research that:

•addresses gaps in our knowledge about applications to ERF countries

•informs policy

•advances the economics literature

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Publications•Working Papers:ERF, IZA, CReAM (UCL), MPRA (University of Munich), ERC (Middle East Technical University); Turkish Economic Association, Koç University-TUSIAD.

•Journals:Journal of Population Economics, Labour Economics, World Development, Regional Science and Urban Economics, Economica, Scottish Journal of Political Economy, IZA Journal of Migration, International Migration Review, Middle East Journal of Development.

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Migration

Effects of Emigration and Remittances on the Left Behind• Female labour supply:a decrease in wage work in urban areas, but an increase in unpaid family work and subsistence work. Labour supply’s response is driven by the household's need to replace the migrant's labour rather than by a loosening of a financing constraint. Binzel & Assad (LE, 2014)

• Investment in education:Migrant remittance receipt has a positive effect on education: larger for males than females in Jordan, Syria and Egypt, but not in Lebanon showing that gender dimensions are still important in the household’s human capital investment decisions (Chaaban and Mansour (2012) and Elbadawy and Roushdy(2010))

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Effects of Emigration and Remittances on the Left Behind• Wealth and inequality:Migrant departures significantly increase standards of living in origin households, suggesting that returns to migration through human capital accumulation, savings and investment outweigh those from remittances. Benefits from migration appear to be larger and more titled toward poor households in rural areas.(David and Jarreau (2015)).

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Impact of Migration on Norms and Institutions•Institutions• Emigration has a positive influence on different indicators of institutional

quality. The effects appear stronger when skilled emigration is considered. Beine & Sekkat (IZAJOM, 2013)

•Fertility• Return migration from Arab countries has a positive and significant influence

on marital childbearing in Egypt. Marchetta and Bertoli (WD 2015)

•Gender Norms• Find evidence of transfer of gender norms through return migration in Jordan.

Destinations matter: migration to highly discriminatory destinations lead to more gender inequality. Tuccio and Wahba (2015). 8

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Impact of Return Migration

•Return migrants are more likely to become entrepreneurs, their enterprise survive longer, and they accumulate human capital whilst overseas which positively impact their wages and their occupational mobility after return.

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Selection, Selection, Selection: the impact of return migration (Wahba 2015, JPopE)

•In order to be able to quantify the impact of temporary migration, one needs to observe current migrants, return migrants and non-migrants and thus to control for the emigration and for the return migration decisions.

•Also control for labor market participation and occupational choice

•All of which have not been addressed before in the migration literature simultaneously using non-experimental data and would biased the estimates if ignored.

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ELMPS12

•Unique data on current migrants collected from those left behind.

•Extensive data on return migrants.

•Employment histories.

•The paper quantifies the wage premium of returnees relative to non-migrants.

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Table 1: Average Predicted ValuesReturnee Non-migrant % Diff.

Probability of EmploymentWork 0.877 0.872 0.57

Entrepreneurship 0.361 0.342 5.59Waged employment 0.632 0.646 -2.17

Predicted Log real hourly wagesNo correction 1.076 0.895 19.84

Waged employment, labor market

participation and return migration corrections

0.983 0.747 26.55

All corrections 1.039 0.911 13.63

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Table 1: Average Predicted ValuesReturnee Non-migrant % Diff.

Probability of EmploymentWork 0.877 0.872 0.57

Entrepreneurship 0.361 0.342 5.59Waged employment 0.632 0.646 -2.17

Predicted Log real hourly wagesNo correction 1.076 0.895 19.84

Waged employment, labor market

participation and return migration corrections

0.983 0.747 26.55

All corrections 1.039 0.911 13.63

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Table 1: Average Predicted ValuesReturnee Non-migrant % Diff.

Probability of EmploymentWork 0.877 0.872 0.57

Entrepreneurship 0.361 0.342 5.59Waged employment 0.632 0.646 -2.17

Predicted Log real hourly wagesNo correction 1.076 0.895 19.84

Waged employment, labor market

participation and return migration corrections

0.983 0.747 26.55

All corrections 1.039 0.911 13.63

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Implications of the paper

•Highlighting the importance of correcting for emigration as well as return migration- double selection.

•Advocating collecting data on current migrants and return migrants in censuses, labour force surveys and household surveys, in particular where temporary migration is common.

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Informality

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Defining & Measuring Informality•Defining informality in the Turkish labour market.

•Enterprise definition •Social security definition

•The social security registration criterion is found to be a better measure of informality in the Turkish labour market given its ability to capture the key relationships between several individual and employment characteristics and the likelihood of informality. (Oznur Acar and Tansel 2014)

•Cited in the OECD Employment Outlook 2015.

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Effects of Informal Employment & Transitions

•Wages:•There is an informal wage penalty, that has increased over time and is larger for the better educated but smaller for the more experienced in Egypt. Tansel, Keshin & Ozdemir (2015)

•Transition:•Mobility from informal to semi-formal/formal employment is highly segmented along education and gender in Egypt. Informal employment is a stepping stone for highly educated male workers, but is a dead end for the uneducated, and for female workers (Wahba (2009)).

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Do Flexible Labour Regulations increase formalisation? Wahba & Assaad (2015)

•Labor market regulations have significant impacts on the functioning and the outcomes of labour markets.

•However, there is a wide disagreement among economists on the benefits of labor market regulations and on the impact of labor market flexibility on employment.

•Examine whether the introduction of more flexible labor regulations lead to an increase in formal employment.

•Use the introduction of the 2003 labor law in Egypt to study the impact of regulations that aim to provide more flexibility in the labor market.

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Do Flexible Labour Regulations increase formalisation? Wahba & Assaad (2015)•Make use of the life histories and retrospective information on first jobs and previous employment characteristics.

•Also rich data on informality; contract holding and social security coverage

•Focus on contract holding (formal employment).

•Enable us to evaluate policy change and advance the economic literature.

Difference in Difference : Identification Strategy• In order to identify the impact of the policy change the empirical challenge is to

find a group that is unaffected by the change in the law.

• We identify two types of non-contracted workers based on their employer & co-workers. • F is those non-contracted workers who work for formal/semi-formal employers,

where other co-workers are contracted and are covered by social security; directly affected by the change in law since their co-workers are already formalized, which implies that the marginal cost for the employer is relatively low.

• I is those non-contracted workers working for informal employers, where all other co-workers have no job contracts and no social security coverage; would not be affected by the change in law given the expected cost of formalizing all workers. 21

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Difference in Difference : Identification Strategy

•We compare the difference in acquiring job contracts between both groups before and after 2003.

•We control for time trends, and macroeconomic factors.

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Base Line: 1998-2002 Post : 2004-2008Outcome Control

a Treateda+b

Diff b

Controla+g

Treateda+b+g+d

Diffb+d

Diff in Diffd

Panel A: No controlsCoef 0.075 0.091 0.017 -0.062 0.114 0.052*** 0.036*t-statistics 14.02 1.36 1.19 -2.43 3.23 2.90 1.89

 Panel B: Controlling for Individual Characteristics

Coef 0.012 0.010 -0.002 -0.008 0.029 0.037*** 0.039**t-statistics 0.72 -0.08 -0.13 -1.18 2.09 3.16 2.10

 Panel C: Controlling for Individual Characteristics and Macroeconomic trends

Coef 0.176 0.175 -0.001 0.178 0.215 0.037*** 0.038**t-statistics 2.58 0.16 -0.08 0.20 0.66 3.13 2.08

 Panel D: Controlling for Individual Characteristics, Macroeconomic trends and time trend

Coef 0.002 0.004 0.002 -0.018 0.018 0.036*** 0.034*t-statistics 0.03 0.03 0.13 -0.25 0.41 2.82 1.87

Difference in Difference Estimation: Determinants of Acquiring Job Contract

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Do Flexible Labour Regulations increase formalisation? Wahba & Assaad (2015)

•Our findings show that the passage of the new labor law did in fact increase the probability of transitioning to formal employment for non-contractual workers employed in formal firms.

•Overall, the results show that the more flexible law increased formalisation of workers.

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Conclusion

ERF has played, and continues to play, a pivotal role in advancing the literature on migration and informality.

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Recommendations for the future•Migration: Little is known about intra-regional migration in MENA; in particular from host countries’ (Gulf States) perspective.

•Informality: Limited firm level and (in)formal enterprises data.

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Jackline Wahbae: j.wahba@soton.ac.uk

https://sites.google.com/site/jackiewahba/