This study examines the overall effects of a set of personal characteristics, search channels and financial variables on the probability of transitioning from unemployment to employment. Using the National Occupational and Employment Survey 2005-2015 (ENOE in Spanish). There seems to be a positive and strong correlation between being formally employed and transitioning to a formal employment in period
Este estudio examina los efectos generales de un conjunto de características personales, canales de búsqueda y variables de financiamiento, en la probabilidad de experimentar una transición del desempleo al empleo. Utilizando la Encuesta Nacional de Ocupación y Empleo de 2005-2015 (ENOE). Los resultados muestran una correlación fuerte y positiva entre haber sido trabajador formal y experimentar una transición hacia trabajo formal en el periodo t + 1. Hay un efecto de desempleo prolongado para individuos con escolaridad superior, debido a que aquellos con menos escolaridad experimentan más transiciones. Los resultados muestran un efecto “scarring”, que aparece cuando se introduce la variable de duración de búsqueda de empleo, esto indica que la duración del desempleo está positivamente asociada con permanecer desempleado. Finalmente, las mujeres parecen beneficiarse más cuando utilizan diferentes tipos de canales de búsqueda tales como buscar empleo por internet o mediante clasificados en periódico.
For many years the Mexican labour market has had low rates of unemployment compared to other countries in the OECD (3.74% on average since year 2000). The low rates of unemployment might be partially explained by the fact that much of the workforce is employed in the informal sector.
Given the lack of unemployment insurance in the Mexican labour market, the means and channels through which job searchers exit unemployment become important to understand the dynamics of a labour market that has two exits out of unemployment: formal and informal jobs. Recent literature has analyzed how different search channels impact on exits out of unemployment, duration and the type of jobs unemployed individuals exit to. (
This analysis is done by examining the factors that could determine exit rates into formal and informal jobs. Specifically, I explore if severance payments, government aid (via training scholarships, aid from a government program and financial aid to start a new business) and assistance from social networks (via remittances or cash transfer) in conjunction with the search channels
Studies that have analized search channels have concluded that most of the job searchers ask directly to employers for job or via friends and relatives. And these channels are also the most effective in securing a job (
Given the availability of self-reported information in the survey I am able to address the following questions: What is the impact of different job search channels on the probability of finding a formal or informal job from one period of time to the other? And what is the impact of different means by which a person finances job search on the probability of transitioning to employment? In particular, what is the impact on the probability of a person transitioning to a formal or informal job conditioned on personal characteristics and different search channels used?
Some interesting findings arise from the analysis of the transitions of job searchers in the Mexican labour market. There seems to be a positive and strong correlation between being formally employed and transitioning to a formal employment in period
The structure of the paper is as follows. In the second section I review the existing literature on search channels and job outcomes in developed and developing countries. In the third section, I describe some features of the Mexican labour market, the data used and discuss some summary statistics. In the fourth section, I describe the econometric methodology and in the fifth section report the empirical results. The final section provides some conclusions.
The theoretic framework for job search derives from the economics of information and uncertainty (
The basic model of job search can be extended and the assumption of offers that are exogenous and arrive randomly according to a Poisson process can be relaxed. One can argue that search intensity of the worker has an effect on the probability of receiving a job offer. This is because as the worker searches more intensively, the probability increases. But increasing this effort represents additional costs (
There are several studies that extend the basic model and analyze search intensity and the type of search channels used as endogenously given. The results obtained depend on the settings and characteristics of the labour market under study (i.e., access to unemployment insurance, search channels used, cost of search). For example, The model of job search with variable search intensity by
One of the studies that provides an insight into the importance of search intensity and the different channels used by unemployed individuals is
One would anticipate that specific methods have specific outcomes. In this sense,
Understanding the dynamics of the labour market and how the different methods of job search affect the probability of escaping unemployment is important for policy purposes. New methods such as searching for jobs online have different outcomes and target different individuals compared to the traditional channels. Understanding this is key to devote more public and private resources to increase the offer of jobs through this channel. In this way,
Also using duration analysis to inquire into whether internet job search has an impact on diminishing the unemployment spell. They find that it does not appear to decrease search time. In contrast, it appears to have a negative effect, prolonging the time of job search.
One of the implications of their empirical results is that the effectiveness of the public employment service in Portugal is low. This might be because employers tend to avoid employment service placement. The public employment service has a low success rate and leads to jobs that do not last, where the pay is low and the rewards for observed human capital attributes as well as other job-finding routes are small.
The channels used for job search can be further subdivided into formal and informal ones. Presumably there are certain channels that would be more effective in ensuring a job offer given a worker’s characteristics and the desire to access these type of jobs.
The authors also use a multinomial logit model to estimate the probability of individuals exiting unemployment to inactivity or employment conditional on search methods, personal characteristics and previous job status. In their findings, almost three quarters of job seekers in their sample are using either informal networks of family and friends or direct contact with employers. They find that previous job status (being employed or unemployed) has a dominant impact on transitions to employment.
Individuals will use more intensively those channels that give them a higher chance of securing a job according to their personal characteristics and previous experience. However, there can be a tradeoff between finding a job faster through these channels and the quality of them and in some cases, even a wage penalty can be expected. In this sense, the study by
The author concludes that most job search in Brazil relies on methods that involve directly asking either an employer or friends and family. The effects of search channels on exit rates on different labour force states are also distinguished by the author. For example, the category ‘asked employer’ is the most effective in transitioning to the above mentioned categories, followed by ‘advertisement’ and ‘friends and family’. The categories ‘examination’ and ‘agency or union’ do not appear to have a significant impact. According to the findings of all the search channels only ‘asked employer’ and ‘advertisement’ yield significant effects for a transition to a formal job. In addition, ‘asked employer’ and ‘asked friends and family’ also seem to be highly significant in influencing the odds of getting an informal job against ‘searching’.
Finally, for the specific case of México, the paper by
Not all the empirical evidence supports the fact that increasing search intensity leads to a greater probability of job offer arrival and hence a shorter unemployment spell. One of the main reasons for this is that a worker must devote the time and resources to this process, hence it becomes costly. In this sense,
As can be observed throughout the literature review, different methodologies for different countries have been used to analyse labour market transitions and the duration of unemployment for unemployed workers. The review of what has been done becomes important to provide a framework in which to place this study, given that the same methodology can be applied to the case of México in order to shed light on how different search channels affect the transition of unemployed job searchers to different labour force states in the Mexican context. Although many of the research has been done using duration analysis, the aim of this research is to analyze a two episode transition (i.e., transition from quarter one to quarter two), given the information provided by the Mexican Employment Survey (ENOE).
In México there is no national unemployment insurance program.
Quitting a job affords no right to a worker in terms of severance payment. Workers in the formal sector have access to fringe benefits. These benefits (provided mainly by the two major health institutions IMSS and ISSSTE
Formal workers in México can be defined as those that are wage earning individuals that have access to public social security provided by the government. A person that owns a small business with employees has to formally register his business to provide these services to all his workers to be considered as formal. In this way, using the self-reported information from the survey, workers are classified as formal, if by the time of the interview, they report being employed and receiving health service from the government. They are defined as informal workers otherwise. It is important to mention that a worker can be hired by a formally constituted firm but have informal worker status.
In this paper the Mexican National Employment Survey (ENOE in Spanish) is used from 2005 to 2015. This survey constitutes a nationally representative random sample of individuals. The National Statistical Office in México (INEGI) asks individuals in this survey about different socioeconomic characteristics and their current employment status. This survey is designed to be a rotating panel where the interviewed individuals remain in the sample for five periods and then exit. Two types of questionnaires are used in this survey: the basic and the extended version. The basic version is used in the second to fourth quarters of each year and the extended version is only used in the first quarter of each year.
The extended version contains a duration indicator (number of weeks searching for a job) and questions on issues such as financial and other types of support. The objective of this set of questions is to capture if a person receives any form of financial aid from the government or from friends and relatives regardless of their employment status. As the sample represents only unemployed job searchers, it is of interest to determine if this aid (pecuniary or not) assists a person in exiting unemployment. Considering that this detailed information is only available on the extended versions of the questionnaire. The analysis is limited to the first and second quarter of each year from 2005 to 2015 as this information is important for this analysis. The survey includes questions regarding the job search channel used by individuals. These questions are asked in both surveys (basic and extended) and they capture the alternative search methods used by job searchers. Responses are divided into 11 categories and these are not mutually exclusive. The categories comprise: Directly, private placement agency, government placement agency, job government program, formalities to start a new business, online job advertisement, published or answered a newspaper or other printed source advertisement, went to a union or guild, asked relatives to recommend or inform about a job, check advertisements on newspapers and others. Due to the similarity between categories, the responses were merged into six broader categories in the following way: Ask for job directly, online job advertisement, advertisement (printed, newspaper, radio, and television), social networks, allocation services (public and private allocation service, went to union or guild) and other (arrangements to start a new business and other).
The survey contains questions that facilitates the identification of sources of income to finance job search. According to the questions, income comes from three main sources: Financial aid from friends and relatives, financial aid from a government program and income after employment (e.g., severance payment). Financial aid from friends can come from: Someone abroad, someone in another Mexican state or someone in the same state. In the same way, aid from government may come from the following sources: Fellowship, financial aid to start a new business, financial aid from any other government program. Finally, income after employment can come from either a severance payment, sale of a former business, a retirement pension, unemployment insurance
As the number of people that did not have access to any of the three sources of income to finance job search is relatively small, the categories are merged to create three binary variables that capture whether they had access to income or not. Hence, a zero captures if a person did not have access (to aid from government, friends or income from a previous job) and one captures if the person did have access to any of the above.
Finally, the survey is a rotating panel of five interviews and for the purpose of the analysis I only considered those individuals that by the first quarter of each year were in their first to fourth interview. This allows tracking them to the next quarter of the survey and identify which channels they used to find a job in the first quarter and their labour market status in the second quarter. All these individuals state that by the first quarter they were unemployed and actively looking for a job. In this way I also drop all those that appear only in one quarter of the sample and I only retain those cases that had previous job experience.
Understanding the different channels by which unemployed individuals have access to jobs in México becomes important given its dual nature. There is a large debate on the segmentation of the Mexican labour market. Some argue that individuals have to work in informal jobs because the formal sector cannot offer sufficient jobs and thus individuals have to engage in informal activities to secure an income. On the other hand, there are others that argue that workers choose freely in which sector to work and the choice only depends on the wage and other factors that are preferred by them.
Source: Own elaboration.
Age Category
Aid from friends or relatives
18 to 22 years
0.24
No financial aid
0.95
23 to 28 years
0.25
Financial aid
0.05
29 to 35 years
0.18
Previous job
36 to 44 years
0.16
Formal
0.45
45 years and more
0.17
Informal
0.55
Position in the household
Reason for job loss
Head
0.65
Dismissed of finished previous job
0.60
Non Head
0.35
Dissatisfaction with previous job
0.31
Marital status
Left or closed previous business
0.06
Married or free unión
0.56
Other
0.03
Not married
0.44
Search Channel
Gender
Directly
0.74
Male
0.7
On-line job advertisement
0.08
Female
0.3
Advertisement
0.13
Education
Social networks
0.14
Elementary school
0.21
Allocation service
0.04
Secondary School
0.30
Other forms of job search
0.04
High School
0.22
Mexican Regions
More than high school
0.27
North
0.30
Financial cushion
West
0.12
No Financial cushion
0.94
East
0.12
Financial cushion
0.06
Center
0.29
Government aid
South
0.17
No Government aid
0.98
Weeks of job search (mean)
1.89
Aid from government
0.02
(1.26)
Number of observations
35,730
Finally, a variable that captures the mean weeks of job search is also included in the analysis. The purpose of adding a time variable to the model is to capture the possible existence of a “scarring effect” as explained in
It is important to acknowledge that the search channels used by job searchers are endogenous to personal characteristics of the individual and previous work experience in a given sector. Moreover, an unemployed individual will use the channels that are more likely to help him to secure a job. For this reason, the results presented here in section 5 should be interpreted with care as I am not claiming causality. Instead, this exercise aims at looking how one search channel increases the probability of securing a job relative to others. Looking at how different search channels affect the probability of securing a job is by itself an interesting exercise that allows to draw conclusions on the dynamics of a labour market that is characterized by being dual.
Another thing that it is worth mentioning is that even though I am not explicitly addressing the possible issue of self-selection into either formal or informal jobs. As I am only analyzing the choice of channels rather than wage returns of each of these sectors. The multinomial logit is estimating the preference of individuals for a given job conditioned on personal characteristics and the channels used. To properly address the issue of self-selection, information on wages is necessary.
For the case where more than two destinations in the dependent variable are possible, the ordering among the destinations is irrelevant and regressors do not vary over alternatives, the multinomial logit model (MNL) is more appropriate.
Let
One can express this four category multinomial logit model using the index relationship
The parameters of the multinomial logit model are estimated by specifying the following log likelihood function after substituting for
The multinomial logit can be re-expressed in a general form as:
Where
For this four-outcome model of labour force transitions described by equations (1) to (4), the restriction implies that the probabilities are re-expressed as:
Given that exp (0) = 1.
The parameters of the multinomial logit model are estimated by specifying the following log likelihood function after substituting for
Finally, for this multinomial logit model there is no single conditional mean of the dependent variable,
The effects of personal characteristics, search channels and financial aid on the probability of transitioning from unemployment in the first quarter of the survey to either a formal or informal job or even out of the labour force is estimated. As described before, the categories are: unemployed, employed in a formal job, employed in an informal job and out of the labour force.
I also introduce three variables to capture if a person is in receipt of any sort of financial aid (i.e., financial aid from friends and relatives, financial aid from government or any sort of income after work which can be considered as a “financial cushion”). I introduce the different search channels used by workers to find a job (i.e., directly to the workplace, job offer on line, advertisement in newspaper or classifieds, friends and relatives, used public or private allocation service and others).
Finally, I introduce the duration variable to the estimation, which captures the number of weeks that a person spent searching for a job. Adding the information of weeks of job search is important because the time an individual devotes to job search is positively correlated with remaining unemployed. Although as shown in
In order to shed light on any gender differences that may arise in the Mexican labour market transitions, the model is divided by male and female workers subsamples. The results for the estimation of labour market transitions for the full sample are not presented here due to space constraint. However, the results are available upon request.
Looking at gender differences provides additional information to understand the dynamics of the labour market and observe if any channel is being more efficient for one group compared to the other. However, it is important to test first whether there are any gender differences in the model. For this purpose, I conducted a composite likelihood ratio test to see if there are systematic differences between the fit of the full model against the model with only male workers and the model with only female workers. The null hypothesis is that there are no systematic differences. The result of the test rejects the null hypothesis with
Standard errors in parentheses. * p<0.1 ** p<0.05 *** p<0.01 Source: Own elaboration.
Outcome Employment Status
Unemployed
Formal
Informal
Out of the labour force
1 if married or free union
-0.0883***
-0.0503***
-0.0366***
0.175***
(0.00854)
(0.00817)
(0.00986)
(0.0112)
Head of household
0.0119
-0.00250
0.0555***
-0.0649***
(0.0126)
(0.0120)
(0.0139)
(0.0139)
18 to 22 years
0.0121
0.0800***
-0.0599***
-0.0323
(0.0192)
(0.0218)
(0.0175)
(0.0200)
23 to 28 years
0.0571***
0.0970***
-0.0445***
-0.110***
(0.0191)
(0.0208)
(0.0169)
(0.0180)
29 to 35 years
0.0692***
0.0897***
-0.0232
-0.136***
(0.0205)
(0.0223)
(0.0174)
(0.0168)
36 to 44 years
0.0468**
0.0900***
-0.0176
-0.119***
(0.0201)
(0.0225)
(0.0173)
(0.0170)
Elementary school
-0.0727***
-0.0618***
0.0442***
0.0903***
(0.0117)
(0.0118)
(0.0159)
(0.0176)
Secondary school
-0.0542***
-0.0243***
0.0301**
0.0484***
(0.00954)
(0.00937)
(0.0121)
(0.0132)
High school
-0.0386***
-0.00657
-0.00344
0.0486***
(0.00970)
(0.00976)
(0.0123)
(0.0134)
Previous job formal
0.0195**
0.127***
-0.105***
-0.0416***
(0.00815)
(0.00812)
(0.00919)
(0.00994)
Dismissed or finished previous job
0.0275***
0.0165**
-0.00653
-0.0374***
(0.00820)
(0.00771)
(0.00923)
(0.00989)
Left or closed previous business
-0.0235
-0.0541***
0.0682***
0.00942
(0.0201)
(0.0203)
(0.0222)
(0.0228)
Other reasons for job loss
-0.0157
-0.0329
0.0280
0.0206
(0.0245)
(0.0230)
(0.0260)
(0.0289)
Financial cushion
-0.00253
0.0199
0.0211
-0.0384*
(0.0171)
(0.0163)
(0.0209)
(0.0210)
Financial aid from government
-0.0285
-0.0615***
0.00989
0.0801***
(0.0194)
(0.0173)
(0.0211)
(0.0235)
Financial aid from relatives
0.00259
-0.00928
-0.0289*
0.0356**
(0.0144)
(0.0139)
(0.0150)
(0.0181)
Went directly to the work place
0.0121
0.0319***
-0.00884
-0.0352**
(0.0110)
(0.0105)
(0.0134)
(0.0146)
Uploaded or replied to a job offer online
0.0268*
0.0302**
-0.0211
-0.0359**
(0.0141)
(0.0140)
(0.0160)
(0.0172)
Used advertisement in newspaper or classifieds to get job
0.00984
0.0267**
0.00494
-0.0415***
(0.0117)
(0.0118)
(0.0133)
(0.0139)
Asked to relatives and friends to recommend his job
-0.0277**
-0.00307
0.0241
0.00666
(0.0131)
(0.0134)
(0.0160)
(0.0169)
Used allocation services to get job (public of private)
0.0666***
0.0417**
-0.0599***
-0.0485**
(0.0190)
(0.0185)
(0.0187)
(0.0214)
Used other channels to find a job
-0.00507
-0.0118
0.0339
-0.0170
(0.0214)
(0.0209)
(0.0244)
(0.0252)
Weeks of job search
0.00903***
-0.0129***
-0.00264
0.00655*
(0.00298)
(0.00329)
(0.00361)
(0.00380)
Observations
11,177
Pseudo R-squared
0.051
Standard errors in parentheses. * p<0.1 ** p<0.05 *** p<0.01 Source: Own elaboration.
Outcome Employment Status
Unemployed
Formal
Informal
Out of the labour force
1 if married or free union
-0.0540***
0.0578***
0.0650***
-0.0688***
(0.00789)
(0.00722)
(0.00936)
(0.00604)
Head of household
-0.0334***
0.00652
0.0418***
-0.0149**
(0.00854)
(0.00791)
(0.0102)
(0.00672)
18 to 22 years
-0.0707***
0.139***
-0.0122
-0.0558***
(0.00975)
(0.0134)
(0.0134)
(0.00631)
23 to 28 years
-0.0594***
0.134***
0.0165
-0.0916***
(0.00917)
(0.0122)
(0.0124)
(0.00530)
29 to 35 years
-0.0554***
0.122***
0.0255**
-0.0922***
(0.00889)
(0.0120)
(0.0121)
(0.00484)
36 to 44 years
-0.0448***
0.0597***
0.0635***
-0.0784***
(0.00885)
(0.0110)
(0.0117)
(0.00502)
Elementary school
-0.0915***
-0.0853***
0.179***
-0.00224
(0.00784)
(0.00762)
(0.0110)
(0.00676)
Secondary school
-0.0711***
-0.00824
0.117***
-0.0379***
(0.00750)
(0.00742)
(0.0102)
(0.00618)
High school
-0.0452***
0.0236***
0.0261**
-0.00454
(0.00796)
(0.00826)
(0.0111)
(0.00673)
Previous job formal
0.0498***
0.161***
-0.179***
-0.0316***
(0.00619)
(0.00611)
(0.00705)
(0.00466)
Dismissed or finished previous job
0.0221***
-0.00489
0.0159**
-0.0332***
(0.00665)
(0.00604)
(0.00804)
(0.00530)
Left or closed previous business
-0.00131
-0.0516***
0.0774***
-0.0245***
(0.0144)
(0.0130)
(0.0163)
(0.00877)
Other reasons for job loss
-0.0120
-0.0363**
0.0469**
0.00144
(0.0175)
(0.0150)
(0.0199)
(0.0123)
Financial cushion
0.00647
0.0307***
-0.0389***
0.00168
(0.0113)
(0.0103)
(0.0142)
(0.00969)
Financial aid from government
-0.0714***
0.0176
-0.0333
0.0871***
(0.0221)
(0.0250)
(0.0292)
(0.0227)
Financial aid from relatives
0.0176
-0.0337**
-0.0183
0.0343***
(0.0162)
(0.0133)
(0.0184)
(0.0129)
Went directly to the work place
0.0206**
0.0197**
-0.0352***
-0.00501
(0.00851)
(0.00815)
(0.0110)
(0.00684)
Uploaded or replied to a job offer online
0.0203
0.0103
-0.0384**
0.00777
(0.0124)
(0.0114)
(0.0154)
(0.0102)
Used advertisement in newspaper or classifieds to get job
0.0485***
0.0273***
-0.0652***
-0.0106
(0.00986)
(0.00906)
(0.0113)
(0.00719)
Asked to relatives and friends to recommend his job
-0.0154*
-0.0196**
0.0234**
0.0116
(0.00924)
(0.00865)
(0.0112)
(0.00728)
Used allocation services to get job (public of private)
0.0558***
0.0217
-0.0591***
-0.0184
(0.0165)
(0.0149)
(0.0188)
(0.0116)
Used other channels to find a job
0.0184
-0.0309*
0.0285
-0.0160
(0.0186)
(0.0158)
(0.0217)
(0.0127)
Weeks of job search
0.0107***
-0.00458**
-0.00507*
-0.00109
(0.00211)
(0.00216)
(0.00269)
(0.00170)
Observations
24,553
Pseudo R-squared
0.070
The category of schooling is usually a good predictor of the type of job. Ex-ante it is expected that those with higher levels of education will be more likely to access a formal job relative to an informal one. The results from this estimation confirm that relative to those unemployed and that have education beyond high school, having elementary or secondary school increases the probability of transition to an informal job for both male and female job searchers. But this also decreases the probability of transition to a formal one. Having high school only increases the probability of a transition to formal jobs for male job searchers. In addition, having only elementary education increases the probability of going out of the labour force by 9.0 percentage points for female job searchers.
Relative to remaining unemployed in the second period. Being previously employed in the formal labour market has a positive impact on the probability of a transition to a formal job for both female and male workers as can be observed in
The information regarding the reason for unemployment was included as this permits the identification of how different reasons for losing a job in the past affect the probability of securing a job in the future. For females,
For the case of male job searchers. Results in
One of the main characteristics of the Mexican labour market is the absence of unemployment insurance. Having no financial support to finance job search pushes workers to exit unemployment relatively fast. This might partially explain why the duration of job search is no more than two weeks on average as seen in
Furthermore, the results show that relative to remaining unemployed. Receiving financial assistance from the government via scholarships or other type of support decreases the probability of a female experiencing a transition to a formal job in the second quarter of each year. Additionally, it increases the probability of going out of the labour force. For the case of receiving financial assistance from relatives, the results show that this decreases the probability of experiencing a transition to an informal job by 2.8 percentage points and it increases the probability of going out of the labour force by 3.5 percentage points. These results are consistent with the literature that points out that receiving assistance can extend the time a worker spends searching for a job. In this case, females would stop searching for a job actively either when they receive financial assistance from friends or relatives or any other help from the government. This result is not surprising, as it is a known fact that Mexican families typically have a male figure as the head of household and female labour in many cases is only a complement of the household income.
Additionally, it can be observed that Male job searchers benefit from having a severance payment as this would help finance job search. In specific, having a financial “cushion” increases the probability of a male job searcher of experiencing a transition to a formal job by 3.0 percentage points. But this reduces the probability of a transition to an informal job by 3.8 percentage points. In México receiving a severance payment after a job dismissal is strongly associated with a formal job, as this benefit is established by law. Individuals with a severance payment would most likely get a formal job, because this is what their previous labour status was. Receiving financial help from the government or any other type of help increases the probability of a male job searcher exiting the labour force by 8.7 percentage points. Aid from the government might discourage workers from an active job search and take time off instead. Receiving financial assistance from friends or relatives also increases the probability of the job searchers going out of the labour force by 3.4 percentage points and it decreases the probability of a transition to a formal job.
These results confirm that having a financial support increases workers’ reservation wages and this allows them to search for a job that is more appropriate to their personal characteristics and preferences rather lowering their expectations and take any job to secure an income. The findings presented here are in line with the related literature findings on the effect of a financial cushion on the duration of unemployment which suggest that those who are without this income would transit to employment faster.
For the case of males. Going directly to the workplace increases the probability of experiencing a transition to a formal job by 1.9 percentage points but it decreases the probability of a job as an informal by 3.5 percentage points. Using advertisements in newspapers increases the probability of a formal job by 2.7 percentage points whereas it decreases the probability of an informal job by 6.5 percentage points. Asking for friends or relatives to recommend for a job increases the probability of a job searcher experiencing a transition to an informal job by 2.3 percentage points but it has the opposite effect for the case of a formal job. This channel does not seem to be efficient as it reduces the probability of a formal job by 1.9 percentage points. In contrast,
Finally, the variable that captures the weeks of job search is also introduced in the regression for both male and female. The results suggest that on average, an additional week of job search decreases the probability of a female job searcher securing a formal job by 0.01 percentage points. In contrast, the probability of remaining unemployed increases by 0.09 percentage points. According to these results, there is some evidence of a scarring effect for women, although the coefficient is not big. This can be partly explained by the fact that in this particular case, job searchers do not seem to be experiencing long periods of unemployment prior to securing a job. For the case of the male subsample,
There seems to be a scarring effect for both genders but this result is not robust enough, which in part might be minimized by the fact that on average job searchers spend two weeks before they secure a job. Financial assistance is having a discouraging effect as it increases the probability of quitting active job search for both male and female. A notable exception is having a severance payment, labelled here as “financial cushion”, having this actually increases the probability of securing a formal job, although this is only effective for male job searchers. Allocation services seem to benefit more female job searchers compared to their male counterparts.
The aim of this study was to disentangle the effects of a set of personal characteristics and different search channels on the probability of an individual experiencing a transition to different labour market states. The empirical literature suggests that the use of search channels is associated to their underlying costs and expected productivities (
Some interesting facts arise from the analysis of labour market transitions. First, the results of the estimation reveal that there seems to be a strong and positive correlation between being formally employed and transitioning to employment in the formal sector in period
Third, there seems to be a “scarring effect” which is picked up from the negative effect of the variable weeks of search, unemployment spells are positively associated with remaining unemployed and negatively associated with transitions to either formal or informal jobs. However, this as on average job searchers spent 2 weeks before exiting unemployment. This should be interpreted with care. Fourth, the results of the analysis show the existence of a gender difference when using the different search channels. Women seem to benefit more to some extent when using various types of search channels and securing a formal jobs such as going directly to the workplace, uploading or replying a job offer online and using newspaper ads to get a job. Male job searchers on the other side, to secure formal job seem to benefit from attending directly to the workplace and using advertisements in newspapers. For informal jobs, males benefit more from asking friends or relatives to recommend for a job.
Even though this study is merely a description of the dynamics of a transition of workers from quarter 1 to quarter 2 from a period of 2005-2015, conditioned on using different types if search channels and given personal characteristics. Some conclusions are worth being pointed out for policy purposes. The fact that male job searchers are not being benefited from the use of channels such as allocation offices (public of private), is a signal that these offices can be improved to help workers get a formal or informal job. Not only it is important for this channel to work, but the quality of jobs that can be accessed through this channel is also important. In this sense,
According to most recent statistics from the National Statistical Office (INEGI) 60% of employed individuals are informally employed possessing no social security or any of the job benefits that come with being formally employed.
These search channels are: asking directly in the workplace, searching online, replying to advertisements, asking friends and relatives, using allocation services and others.
The longer an individual remains unemployed, the less likely is to be hired, as this to some extent indicates that the individual’s skills depreciate with time (
The only Mexican state that has an unemployment insurance scheme is México City. This was implemented in 2010 as a state policy by the Local Labour Office. It consists of financial aid for up to six months to finance job search and enhance the transition to formality.
IMSS provides social security and health services to workers employed in the private sector whilst ISSSTE provides these services to workers in the public sector.
This applies to those living in the México City and that have Access to this benefit.
I dropped those that stated that they did not have job experience because I could not distinguish between those having no work experience and those that did not report whether they had experience or not.
See
Moreover, given that individuals can choose among more than one option, modelling this self-selection issue can be addressed using a multinomial logit model as employed in
See chapter 15 of
All of the individuals are unemployed in the first quarter of the sample. Therefore they transition to four different labour market states in the second quarter: remaining unemployed (U-U), formal job (U-F), Informal job (U-I) and Out of the labour force (U-O).
This is a variable divided into four categories: population of more than 100,000; population from 15,000 to 99,999; population from 2,500 to 14,999; population from 2,500 to 14,999; and population of less than 2,500.
As part of the econometric analysis of the model the Independence of Irrelevant Alternatives (IIA) proposition is tested for the three outcomes of the model: remaining unemployed, transitioning to employment in the formal sector and transitioning to employment in the informal sector. The result of the Small Small-Hsiao test supports the null hypothesis. This means that the alternatives are independent of each other and thus supports the use of the MNL model.
Full results including the regional and size of community are available upon request from the author.
For an analysis of “wait unemployment” in public sector jobs for highly skilled workers for Pakistan see
I constructed a variable to capture the number of search channels used by individuals by adding the 5 search channels. The variable shows that the maximum number of channels used were 4, and the mean of search channels used is 1.17. This confirms that workers in this sample, on average, generally rely only on just one search channel.
The different specifications used are available upon request from the author.