Career Progression within Large Firms

Transcription

1 Career Progression within Large Firms Francisco Lima and Pedro Telhado Pereira Abstract The objective of this paper is to study the worker s career progression in large firms. The new evidence presented comes from a longitudinal sample of large firms and a systematic analysis is made with a model of job assignment, human capital accumulation, and learning. The data contain information about the worker s job transitions and about the timing of promotions. Thus, it is possible to identify if the worker moved up or down in the hierarchy and, in addition, if he is classified as promoted or not by the employer. The estimation results show that education has a positive influence on a new employee s promotion within the job level and on the incumbent s movements to upper job levels. The career events defined as promotion within job levels, promotion to upper job levels, and demotion show that the major determinant is an unobservable signal sent by the variation in the worker s expected innate ability the learning effect. Faculdade de Economia da Universidade Nova de Lisboa. Travessa Estêvão Pinto, P Lisboa, Portugal. Tel: (351) Fax: (351) francisco.lima@mail.telepac.pt and ppereira@fe.unl.pt Financial support from PRAXIS XXI, grant 2/2.1/CSH/781/95 and SAPIENS is acknowledged. Francisco Lima also acknowledges the support from PRAXIS XXI - Subprograma Ciência e Tecnologia do 2 Quadro Comunitário de Apoio. We also thank the Bank of Portugal, where this research was carried out.

2 1. Introduction What happens inside the firm? When a worker is hired, he faces several internal procedures and rules that define his career inside the organization. In some respects he becomes an agent in an internal labor market set up by the employer. The issues raised by these facts are some of the main questions that the field of personnel economics engages. The objective of this paper is to study the worker s career progression. The new evidence presented comes from a set of large firms, and a systematic analysis is made with a model of job assignment, human capital acquisition, and learning. The data used is a sample of firms personnel records gathered annually by the Portuguese authorities - the survey Quadros de Pessoal (QP). Although the QP was formerly used in the applied research, the worker s promotion history and job assignment was never fully explored and deserves a closer look. 1 The survey covers virtually every firm in the Portuguese economy and contains information about all of the workers who are employed therein. The employer must post the firm s responses (the information on employees) sent to the Ministry of Employment in a public place inside the firm. This opportunity for the employees to check the information considerably reduces the risk of measurement error and increases the confidence in the information contained in the survey. 1 The recently published work focus mainly on wage issues (Cardoso 1999, 2000a, b, Hartog, Pereira and Vieira 2000, Vieira 2000). See also Machado and Mata (2000), in which the QP is used to study the distribution of firm sizes. 1

3 The survey has the advantage of covering the entire work force of multiple firms, as opposed to single-firm-based studies or individual-based studies. Not only is the type of survey an advantage, but also the type of information it makes available. It is a matching employer-employee panel where workers are followed during the period covered by the sample. Every firm has to report the workers hierarchical position using the same ranking system, so the information is comparable across firms. Moreover, the employer reports the dates of employees promotions. In combination with the year-to-year job transition within firms, this information provides the identification of several career events. For example, two workers can experience the same movement to an upper job level, but only one receives a promotion. It can also be the case that a worker keeps the same job assignment and at the same time is promoted. Therefore, the promotion variable gives information about the relative performance, that is, distinguishes between apparently equal career progressions. It identifies the employer s perception of what the employee s performance is, an insight usually hidden from the researcher. A theoretical set-up based on the model presented in Gibbons and Waldman (1999a) motivates the econometric analysis. The model is extended and captures several aspects of the worker s career. Namely, how the worker s human capital accumulation and the employer s learning about the worker s ability determine the efficient job assignment and the career progression inside the firm. Other models could be explicitly considered, but the one presented here accounts for a broader set of results. 2 The analysis performed with the data set, in conjunction with the theoretical framework, allows us to depart further from the work of Baker, Gibbs, and 2 Surveys of the literature can be found in Gibbons and Waldman (1999b), Prendergast (1999), and Gibbons (1997). 2

4 Holmstrom (1994a, b), which provided the original research lines to this paper. These authors offer one of the first and most complete works in the field, where 20 years of personnel data from one firm are analyzed. There are not many other studies on careers inside firms, mainly because there is a lack of suitable data. Recent examples of such studies are the Ariga, Ohkusa and Brunello (1999) and Pergamit and Veum (1999) papers. 3 The first paper studies the promotion policy of a large Japanese manufacturing firm. The authors found evidence on the existence of fast-track effects and selection of stars as opposed to late selection commonly associated with the Japanese firms. The second paper studies the causes and the consequences of promotions using the National Longitudinal Survey of Youth. Both papers show how difficult it is to get the best of two worlds: single-firm surveys or individual surveys. The data used in the present paper have several features that are present in both types of surveys. There is detailed information available on multiple firms that allows us to relate the individual attributes with the hierarchical position and to identify how firms select workers, that is, the determinants of the individual career outcomes. The next section presents the theoretical model and the empirical specification suitable to study the worker s job assignment and career progression. In the third section, the data set used is presented and a preliminary insight is provided. The econometric analysis is performed in the fourth section. Detailed results are obtained for the worker s career progression with the estimation of the determinants of different career events across job levels. Finally, the paper ends with some concluding comments. 3 Other papers are McCue (1996) on position changes, Winter-Ebmer and Zweimüller (1997) on gender differences in career outcomes, and Seltzer and Merrett (2000) who extensively analyze personnel files from a bank. 3

5 2. The Model and Empirical Specification The Model The framework is based on the Gibbons and Waldman (1999a) integrative model. It combines job assignment, human capital accumulation, and learning about the employees abilities. This combination has the advantage of producing a set of results that are in line with the available evidence on firms personnel policies. 4 Two extensions are made to the model. First, the individual s initial education endowment is introduced. The objective is to account for the observed fact that other forms of human capital affect workers careers, other than labor market experience. The workers with more education generally have better career prospects, namely, have higher probability of achieving upper hierarchical positions and receive higher wages on average. Second, hierarchy with an arbitrary fixed number of ranks is introduced. Consider an economy where there is free entry in production and where all firms are equal. Firms and workers are risk neutral. Workers supply one unit of labor in each period. Assume that worker i has an innate ability θ i and that his effective ability η it while working in the labor market is given by η it = θ i f ( x, s ) it i (1) 4 There are other models where job assignment and career progression are contemplated. The examples are abundant, to name a few: matching (Jovanovic 1979); comparative advantage (Sattinger 1975); scale-of-operations effect (Waldman 1984a); up-or-out contracts (Kahn and Huberman 1988 and Waldman 1990); tournaments (Lazear and Rosen 1981); asymmetric information and signaling (Waldman 1984b, Ricart I Costa 1988, Bernhardt and Scoones 1993 and Bernhardt 1995); asymmetric information and visibility in the labor market (Milgrom and Oster 1987). 4

6 with f > 0, f > 0, f < 0, f < 0, and f 0 x s xx ss xs, where x it represents his labor market experience and s i his education (or more generally other forms of human capital acquired before entering the labor market). The worker chooses education s i before starting his working life and he can have high ( θ H with θ > θ > 0 H L. ) or low ( θ L ) innate ability, Firms are hierarchies with J job levels and only use labor as input. The worker i is assigned to job level j = 1,!, J and produces in period t, y ijt = d j + c j ( η + ε ) it ijt (2) where d j and c j are technological coefficients, with 0 < d J < d J 1 <! < d1 and cj > cj 1 >! > c1 > 0 ; the term ε ijt is a normal error term with mean 0 and variance 2 σ. Furthermore, define j η as the cut-off point where d j c d j j + jη = j+ 1 + j+ 1η. By c J 1 1 assumption, the parameters of the model are such that η >! > η > 0. Assume that if j η it = η, then worker i is assigned to job j + 1. The information structure is such that there is gradual learning about the worker s ability due to the presence of the error term in the production equation (2). Assume that learning is symmetric in the sense that all firms (and the worker) have the same amount of information in every period. By observing the worker s output the firm e forms an expectation about his ability. Denote θ = E ( θ η + ε,! η + ε ) it i it x ijt x, it 1 ijt 1 5

7 as the worker i's expected ability in period t as a function of his past performance in e e the labor market and = θ f ( x, s ) η as the expected effective ability. 5 it it it i It is easy to show that the efficient job assignment is such that worker i is assigned to job 1 if 1 η e it < η, to job j < J 2 if η j η e it < η j+1, and to job J if η e J 1 it η. Wages are given by w it = d + c η. The discussion of the model in this paper is j j e it centered on career progression. There are two main effects that determine the worker s promotion to upper job levels. First, the human capital accumulation effect, that is, the increase in effective ability due to the increase in the labor market experience. Second, the learning effect, induced by the variation in expected ability. If the learning effect is positive and sufficiently large, then the interaction with the human capital accumulation effect can increase expected effective ability in such a way that it becomes higher than the cutoff ability level that determines the assignment to the next job level. The result is the worker s promotion to the next job level. If the learning effect is negative and large enough to outweigh the human capital accumulation effect, then the interaction of the two effects generates a reduction in expected effective ability. If the reduction is very strong, then the expected effective ability can be lower than the cut-off level that determines the assignment to the previous job level. In this case, the worker is demoted. The model predicts that demotions are rare and that they are always associated with wage decreases. 6 5 The worker s performance in period t 1 is nothing more than the signal sent to the market by the realization of output in t 1. Moreover, the signal is independent of job assignment because η ( ) it + ε ijt = yijt d j c j from equation (1). 6 The distribution of the error term ε is symmetric around zero, which implies that roughly half of the workers will experience a decrease in expected innate ability. The interaction with the accumulation of human capital produces a minority of wage decreases. Demotions are rare because only some of the workers with wage decreases will be demoted. 6

8 What are the effects of introducing education in the human capital function f(.)? Even without any interaction with labor market experience, there is a positive association between education and hierarchical level. This is in line with the observation that upper job levels generally correspond to higher average years of education. As the human capital function is increasing in s, so too is the expected effective ability. It means that the less educated workers have a disadvantage relative to the other workers. The disadvantage is particularly evident in the first period of employment where all workers are alike except for education. If there is a positive interaction ( f > 0 ), the interaction will foster the education advantage. When the xs interaction is present, the labor market experience is more valuable to the more educated workers, in the sense that the change in the human capital function, induced by one unit increase in experience, is greater for more educated workers. Considering only this effect, the more educated will climb the job ladder faster. 7 Empirical Specification The worker s advancement is a dynamic matter. The worker who experiences an increase (decrease) in his expected effective ability can be promoted (demoted) to a higher (lower) job level. The previous discussion of the interaction between the human capital and learning effects shows that an explicit empirical specification is harder to get than in a simple (static) job assignment. First, the change in the worker s 7 It can also be the case that an individual accumulates other forms of human capital while working, other than labor market experience, and this should be taken into account in the formulation of the model. Furthermore, the model does not consider the information content of education. In a model with asymmetric information, the more educated can be considered more visible to the external labor market, and thus have better prospects of career progression. This type of argument is modeled by Milgrom and Oster (1987). 7

9 effective ability can induce the employer to promote or demote the worker. Second, these decisions are not governed by the same parameters across job levels. Thus, not only are there different career events to consider, promotion or demotion, but also the layers in the hierarchy where the career events take place. 8 The solution is to define the career event E, which is observable when the condition for it is fulfilled. That is, E = 1 if C 0 E = 0 if C < 0 (3) where C is a latent variable that defines the condition for the occurrence of the career event E. This unobservable can be formulated as C = β z + u (4) where z is a vector of individual characteristics and u is an i.i.d. residual. What variables should we consider in z? The vector z comprises the determinants for the occurrence of the career event E in each job level. Thus, there is a vector of coefficients β for each of such occurrences. The individual characteristics considered are the following. The labor market experience is separated into two variables: tenure at the firm and prior work experience, both with second order polynomials. Education is defined by the last level attained. An indicator for gender is included to capture possible unequal job 8 For example, a worker who is assigned to job 1 in period t and is promoted to job 2 in period t + 1, 1 1 changes his expected effective ability from a value lower than η to a value higher than η. In other words, the distance between effective ability in period t and t + 1 is higher than the distance between 1 the cut-off η and the effective ability in period t. 8

10 assignment, a dummy variable for working less than thirty weekly hours to capture situations of part-time work or temporary hours fluctuations, and a dummy variable for bargaining regime other than sector level (the most frequent one). The model assumes that firms are all equal, but in reality there is always some feature that distinguishes one firm from another. Firm-specific effects are included in the regression to account for this fact. The market conditions can vary from year to year, and a set of dummies for time is also included. The above formulation for career events that define the worker s progression inside the firm can be estimated using a bivariate probit model where ( E = 1) = Prob( β z u) = Φ( β z) Prob (5) is the probability associated with the career event E. As is standard, the marginal effects of variable z k can be computed as Φ β k ( ) k = φ β z β (6) where z is the sample mean of z, Φ (). is the cumulative normal distribution and φ(). is the normal density function. If z k is a dummy variable, then the marginal effect is computed for a change from 0 to 1 and the other variables are kept at their sample means. This empirical specification is similar to what usually appears in the related literature. Recent applications used for estimating promotion determinants in different 9

11 contexts are presented in Ariga, Ohkusa and Brunello (1999), Pergamit and Veum (1999), and Winter-Ebmer and Zweimüller (1997). 9 Note again that the coefficients β do not have to be the same for the different career events and across job levels. 10 Thus, for each job level the worker can be promoted to an upper level or demoted to a lower level, and the effects of the variables included in z do not need to be the same. There are more possible career events not explicitly contemplated in the model. For example, one such event occurs when the worker is promoted even though he remains in the same job level, which can be defined as promotion within job level. This job transition is horizontal in the sense that the worker continues to hold the same responsibility level and perform tasks with the same complexity, if this is what defines the job level (as is the case with the data used in this paper). The other possible career events are related to the possibility that the firm has more than one job ladder. That is, more than one hierarchy inside the major hierarchy that constitutes (or is identified as being) the firm. This last point will become clearer when examining the data. A final note concerning the timing of the variables is called for. The observations are pooled in the bivariate probits for career events. However, there is the problem of independence when one worker appears in the data more than one period. The solution was to use the White/Huber estimator to obtain the variance-covariance matrix of the estimators. In this way, the possible correlation between two observations of the same individual is taken into account (see, for example, Greene 2000 or even Stata 1999 for a discussion). However, this means that the information 9 Medoff and Abraham (1980) also estimated the probability of promotion when discussing the relationship between experience and performance. 10 This fact, coupled with the information on the individual careers available in the data, allows us to depart from the previous results found in the literature. Furthermore, as one possible extension of this work, the estimated cut-off points from an ordered probit for job assignment could somehow be used in the empirical specification of the career events. 10

12 content of the timing of different career events is not fully explored. The strategy pursued has the objective of first trying to achieve manageable results concerning the determinants of each career event. When time is explicitly introduced, for example with a hazard specification, the relationships become much more complex in the sense that one must account for the initial position of the employee and all of his subsequent career progression. 11 It is better to proceed by stages, and leave such a line of work to future research. 3. The Data and Preliminary Overview The Data The data used come from the survey Quadros de Pessoal (QP) collected annually by the Ministry of Employment. A random sample of firms was drawn, stratified according to economic activity, location, firm s legal form, and number of employees. The sample is a longitudinal matched employer-employee panel of 74 large firms in the manufacturing sector, having more than 500 workers per year, and followed between 1991 and The sample has 391,618 initial observations and there is valid information for 326,975 worker-years. The employment history of all workers in the firm and several worker s and firm s characteristics are available. The data appendix describes the data source and the variables and provides the summary statistics. 11 For example, McCue (1996) studies the worker s position changes using the PSID and applying a hazard specification. 11

13 The choice of larger firms is considered appropriate considering the specific issues treated in this study. Analyzing only larger firms has the advantage of allowing the focus on the firms personnel policies with no interference caused by firms size, major firms reorganization, or missing data problems and guarantees that those policies can be identified. These firms represent roughly 60% of all the individuals working in firms with the same characteristics in the economy manufacturing sector and with more than 500 workers per year. A preliminary analysis of the individual data is made in the remainder of this section. Job Levels Job levels are classified using the grade levels reported by the firm. It means that the data supplied by the employer mirrors a hierarchy. It is not the true hierarchy, but rather, a filtered representation, shaped by the norms of the survey. There are eight job levels defined by law. 12 Table 1 shows the description of the job levels and the number of employees assigned to each level. Table A4 in the Appendix supplies the full description of the levels. The first job level at the bottom of the hierarchy Level 1 is the one where firms place the new employees for the initial skill acquisition necessary to move to another job level or simply to fulfill a probationary period. Level 1 can be considered a port of entry almost by definition. 13 As the job level increases, the task complexity, skill requirement, and the responsibility level also increases. Generally, the employees average age, education, and tenure are increasing in the job level (see 12 By coincidence the same number found in Baker, Gibbs, and Holmstrom (1994a, b). 13 There is entry and exit in all levels, but mainly in the four bottom hierarchical levels. 12

14 Table A3 in the data appendix). There is a special case, however: the employees assigned to Level 6 supervisors, team leaders, foremen have lower education than employees in Level 5 higher skilled professionals and are older and have higher tenure than employees in Level 7 and 8 intermediary and top executives. These facts suggest that they are workers with skills mainly acquired in the firm and with authority over employees in Levels 4 and under, but not necessarily over employees in Level 5. The job levels are intended (by definition) to be clearly ordered, but it is not true that they can accommodate all the complexity showed by some hierarchies. The Job Ladder and Promotions The worker career progression is identified with the year-to-year job level transition. Usually, promotion is identified with the move to upper job levels, and demotion with the move to lower levels. In the case of the data available there is additional information. Not only the job level change (or no change) is observed, but also whether the worker received a promotion or not. Thus, it is possible to identify six career events: move to an upper job level upon promotion; stay in the same job level with a promotion (promotion within job level); move to a lower job level upon promotion; move to an upper job level without a promotion; stay in the same job level without a promotion; move to a lower job level without a promotion (demotion). 13

15 The information about promotion allows us to capture something usually unknown to the researcher the promoted worker has higher performance, or some other individual attribute valuable to the firm, than the unpromoted one, ceteris paribus. Thus, it is possible to find two workers experiencing the same upper movement, but one is promoted and the other is not. The definition of promotion is the employer s responsibility because no supplementary information is given by the norms of the survey (only the headline date of last promotion ). Table 2 presents each of the career events defined above across job levels. The majority of the employees remain in the same job level and roughly one tenth of these are promotees promotion within job level. This type of promotion can be considered as a promotion to a higher horizontal rank where the worker changed his relative position inside the job level and compensation, but with no change in task complexity and responsibility level. Looking across job levels, the group of apprentices and internships (Level 1) holds the highest percentage of promotees, 43%. Thus, it seems that employers make a great effort to screen the new employees even before any change of job level occurs. These issues will be investigated in the next section. Almost half of the employees that move to an upper level received a promotion. This proportion is relatively stable across job levels, except for Level 3. Once again, it is possible to distinguish two types of career events, a move to upper job levels with or without a promotion. Remember that the survey provides information concerning the employees date of last promotion. This information is taken together with the year-to-year job transition to identify the career movements mentioned earlier. Concerning the workers who move to lower levels, several reasons are possible: firm s reorganization not captured by the fixed job level structure; different 14

16 hierarchies that overlap; or demotions. Excluding the employees who are promoted (20%), the remaining are the best candidates to be considered as demoted. They represent 2.5% of all workers employed at the 74 firms. It is a small number, in line with the predictions of the model of Section 2 and with the evidence available. Baker, Gibbs, and Holmostrom (1994a) found that fewer than 1% of job movements were demotions. Part of the demotions can still be due to the existence of job transitions not fully captured by the fixed hierarchical ladder imposed by the norms of the survey. 14 Career Paths One last issue must be addressed before moving to the econometric analysis of the next section: the employees career paths. Several questions are in order, namely, the job level before and after the worker s job level change, the timing of these job level changes, and the comparability across firms. The preliminary overview provided below also gives some clues to future research. The workers career paths are computed by looking at what happens over the years, in Table 3. Consider the workers assigned to a given job level in 1991 and observe where they are in the following years. The percentages presented are for the workers who stay in the same firm, so in each year the initial pool is reduced by the number of exits. There are two types of panels in Table 3. The first and the third panels present the new employees to Level 1 and Level 3, respectively. Level 1 is a natural choice to study the progression of new employees because they represent 50% 14 A similar situation appears in Seltzer and Merrett (2000). In a single-firm study, using the personnel records from a bank, the authors argue that part of these movements are not really demotions, but rather some form of job rotation. 15

17 of the employees in this job level. Moreover, the average years of tenure in Level 1 is two years. Though only 6% are new employees in Level 3, it is the job level where the number of new employees is higher, representing one third of all entries. The remaining panels present the workers with more than one year of tenure the incumbents. The objective is to show that there is a job ladder and to find the major career profiles. 15 Only 2% of the new employees who enter Level 1 in 1991 remain in this level five years later and transitions are mainly to Level 3 and Level 4, showing, once again, that this job level is a port of entry by definition. Looking to the progression of the incumbents, in each level there is a clear pattern of transitions to one or two upper job levels. This result is general, in the sense that it is for all different firms all firms use the same type of job ladder. It is also clear that not all transitions to downward levels are demotions. They are the drawback of imposing a rigid hierarchy equal to all firms. Comparing the incumbents with the new employees in Level 3, part of the new employees move faster to upper job levels. After five years, only 66% remain in the original level, as opposed to 81% for the incumbents. It is also true that 15% of the Level 3 new employees have moved down to Level 1 after 3 years and 13% have moved down to Level 2 after 5 years. 16 It shows to some extent the problem of not having the original firms personnel records, which does not allow us to identify forms of job rotation and/or to determine if more than one job ladder is present. It is also possible that there are some forms of coding error present. However, we must 15 A different version of Table 3 was implemented. The strategy was to look for the career path of workers with tenure higher than a cut-off point. The cut-off point was defined by the 25% workers with lower tenure: 2 years for Level 2; 4 years for Level 3; 6 years for Level 4; 10 years for Level 5; and 12 years for Level 6. The idea was to capture the transitions after an expected minimum period of years in a certain job level. It turns out that the figures are slightly higher for the stayers in the original level (the difference is always lower than 2 percentage points). This difference, though small, means that a part of the workers with lower tenure at the firm are also the ones with faster career progression Somehow, this can be interpreted as a sign that fast-track is present. 16 The same firm is the main responsible for the two cases. 16

18 stress the great advantage of having a survey that is valid to make analyses across firms. Table 3 clearly shows that the firms reported hierarchical ladders are somewhat similar and comparable across firms. 4. Econometric Analysis The objective of this subsection is to determine who is selected for promotion, or more generally, who is selected for a given career event. With the model presented in Section 2, we know that if performance is higher than a cut-off level then the worker is promoted, and demoted if performance is bad enough. The worker can stay in the same level for one year more (promoted or not) or he can be moved/promoted to an upper or lower job level, given the information available in the data set. These career events were described in Section 3. There are five career events to analyze in each job level: promotion within job level, considering in addition the special case of new employees; move to upper job levels, regardless of promotion; promotion to upper job levels; demotions; move to lower job levels with promotion. The details are presented below. If an employee stays in the same job level in two consecutive periods and he is promoted promotion within job levels then he performed better than his coworkers who stayed in the same job level, but were not promoted. Thus, the first career event to study is promotion within job levels, where the pool analyzed is that of workers who remain in the same hierarchical layer in two consecutive years. The analysis has to be done for each job level because it is clear from the theoretical framework that the ability cut-off levels are not the same across job levels. 17

19 A special case of this event is considered the new employees. As there is information available about their promotions in the first year of employment in a particular firm, and the new employer probably puts great effort into screening the best ones, it is justifiable to analyze this particular case. So, the sample of new employees assigned to each job level is studied separately to discover who is promoted in the first career year. 17 The second career event is the movement to upper job levels, regardless of promotion. The workers who experience this event must be compared with the workers who were in the same level as them in the previous year. A sub-group of the workers who move to upper levels is classified as promoted by the employers. If for the same upper movement they are promoted, then they should be different in some dimension perhaps performance or simply another ladder not captured by the information contained in the survey. This is the third event studied where the promoted workers are compared with unpromoted workers, but both experiencing an upper movement from the same job level. The fourth event is the movement to lower job levels demotion. The comparison group is the pool of all the other workers. Finally, the fifth event is the movement to lower job levels upon promotion. This last type of job transition is the one that most obviously shows the information limitations of the survey, which, nevertheless, can be tentatively studied like the other career events. The comparison group is the pool of the other workers who were in the same job level prior to promotion. Finally, a last issue must be addressed before moving to the econometric analysis. Note that it is possible to have some firms that promote all of its workers in one year or never use any type of promotion. The estimation procedure has to take this fact into 17 Assuming that the new employees maintain the same job level during the first year at the firm. 18

20 account. The solution adopted was to use firm-specific effects in a way that, for example, if a firm never uses promotion within Level 4 (in the five-year sample), then its employees are excluded from the analysis of promotions within this job level. Each of the events described above are estimated separately by a probit model with the specification presented in Section 2. The estimation is performed for each job level because the decision to move/promote does not necessarily have the same proprieties across job levels, as mentioned above. The marginal effects, computed as in equation (6), are shown in the tables. The sample means are presented in Tables A5-A9 in the data appendix. The problem of a small number of observations for some career events in several job levels does not allow us to obtain any significant econometric result and these cases are not analyzed. In the cases presented there are also several variables excluded from some estimations, mainly the higher levels of education, because there are too few workers holding these levels in particular jobs, and generally, all have the same value for the career event. A multinomial estimation could be applied, but it is infeasible in this framework: the pool of workers for each career event is not equal across job levels. Furthermore, the individual-year observations are pooled. This seems to be the best procedure given that the objective is to capture differences between individual year-to-year job transitions and not differences within the same individual career path (see the discussion in Section 2). A. Promotion of New Employees within Job Level The new employees are first analyzed in Table 4. The probit for promotion was estimated at each job level, though only the first four bottom job level regressions are 19

21 presented, given that there are too few observations in the remaining levels. The estimates from Level 1 show that females are 5 percentage points (p.p.) less likely to be promoted, while in Level 2 they are 3 p.p. more likely. 18 In the other job levels the difference is not significant. Thus, it is not clear if females have fewer opportunities than males. 19 The results show that overall the more educated are more likely to be promoted first, but, for example, in Level 3 there is no significant difference with the level of education held by the employees. This supports the prediction of the model that the more educated hold higher expected effective ability at the start and are thus promoted first. Prior work experience has almost no effect. Individuals working less than 30 hours per week in Level 1 and Level 2 have a 9 p.p. lower probability of receiving a promotion. The difference in the promotion probabilities is not significant in Level 3 and Level 4. Almost no one with a labor contract other than one negotiated at the sector level (the most frequent) has a positive probability of being promoted in Level 2 and Level The marginal effects are calculated at the sample means when the variables are continuous or for changes from 0 to 1 when the variables are dummies, as in equation (6). With this procedure there is the problem of constraining one dummy variable to be at its sample mean whenever computing the marginal effect of another variable. To test if this constraint changes the results much, some representative cases were computed and the new marginal effects compared with the ones presented in the tables of this subsection. It is expected that some effects will change, mainly because the specification includes firm-specific effects. The results are to be interpreted for the set of firms and when one in particular is considered, the marginal effects will necessarily be different. Nevertheless, the sign, and the relative influence of the variables does not change much when the above comparisons are made. For example, take a new female employee assigned to Level 1 holding the upper secondary, and with the experience variables at their sample means (see Table A5), working more than 30 hours per week, in the year 1991, and employed at the most representative firm. The marginal effects are: , 0.06*, 0.73, 1.02, -0.88, 9.33, -0.04, 0.08*, Comparing with the results from Level 1 in Table 4, the main conclusions continue to hold. 19 As it would be the case, for example, if females have higher quitting rates (Lazear and Rosen 1990) or if females are less visible to the external labor market (Milgrom and Oster 1987). 20

22 B. Promotion within Job Levels The workers who stay in the same job level in two consecutive years are studied in Table 5. The estimation was performed separately for each job level. What should we expect? Is this type of promotion a result of seniority rules, rendering in an automatic promotion, or is it the result of a better perceived individual performance that induces the employer to promote the employee a learning effect? The estimation results seem to support the latter view. Gender is not a major determinant of this career event. Employees with less than two years of tenure have a lower probability of receiving a promotion in Level 1, and a higher probability in Level 2. Tenure generally has a negative effect on promotion but it is more pronounced in Level 1. Education has no effect, that is, being more educated does not imply higher probability of receiving a promotion. Prior work experience has a small negative or no effect. Working less than 30 hours has a positive effect on Level 1 (10 p.p.) but it is close to zero in all the other job levels, except in Level 7 (-8 p.p.). The effect on the probability of promotion is generally negative, because it probably means that workers have a more precarious attachment to the firm. Nevertheless, in Level 8 a worker with a bargaining regime other than the most frequent one is 75 p.p. more likely to receive a promotion. A specification without this variable was also attempted, and the results are maintained: the other coefficients are not affected for all job level equations. 20 The promotion within job level is probably the result of individual characteristics unobservable to the researcher. The best candidate is the worker s performance. In the context of our model, this type of career event is induced by the learning effect. The 20 Can the type of contract identify different job ladders? It is plausible, and it may be worthwhile to investigate it. 21

23 promoted workers are those whose positive variation in expected innate ability is higher, when controlling for the other possible determinants of promotion. The learning effect is unobservable and, by assumption, uncorrelated with the control variables. If this is the main determinant of promotion within job level, then the empirical specification does not capture it. Furthermore, by virtue of the minor role played by education in determining this career event, we can infer that education is not correlated with ability, supporting the assumptions of the model. C. Move to Upper Job Levels The workers who move to upper job levels regardless of receiving a promotion or not are compared with the co-workers in the same job levels prior to this career event in Table 6. The estimates show that there are small differences by gender. The workers who have less than two years of tenure are less likely to be promoted and this negative effect is stronger at the bottom levels. Tenure has a small positive effect. Education has a clear positive effect, but is not equal across job levels. Prior work experience plays a minor role. Individuals working less than 30 hours per week are 8 p.p. less likely to receive a promotion in Level 1, but there is no significant difference in the other job levels. The type of bargaining regime has different effects across job levels. The conclusions from this type of career event are clearly different from the previous one. The human capital plays an important role in the career advancement, namely education, in line with the predictions of the model. The more educated workers hold an advantage reflected in a higher expected effective ability, and this advantage seems to persist, even after controlling for tenure. In other words, the 22

24 learning about the workers innate ability is not the major determinant of movements to upper job levels, when compared with the workers human capital endowments. D. Move with Promotion to Upper Job Levels Table 7 presents the determinants of promotion to upper job levels. The promoted workers were taken together with the unpromoted who move to upper job levels in the previous table. Now, the objective is to find out what it is that differentiates each type of worker, promoted or unpromoted, for the same job transition move to upper job levels. Only the estimates for Levels 1-4 are presented because there were too few observations in the other job levels. With no measure of individual performance, can any difference between the two groups of workers be identified? The estimates show that there is no marked difference apart from a negative coefficient associated with tenure and prior work experience, though the latter effect is small. The effect of tenure is more pronounced in the first two job levels and the sign is maintained even after computing the overall marginal effect (taken into account the term squared). 21 This can be interpreted as the promotion of workers with a shorter employment period, and, thus, a sign of faster career progression. Loosely interpreted, a sign of fast-track. Regarding the effect of education, the majority of the coefficients associated with the dummies for the levels of education are not significant. This result is similar to the one obtained for 21 The overall marginal effect of tenure can be computed as Φ z k ( z)[ β + β ] = φ β z1 where 1 β and 2 β are the coefficients associated with tenure and tenure squared, and 1 z is the sample mean of tenure (see equation 6). 23

25 promotion within job levels the more educated are not necessarily the ones who get promoted. Furthermore, the estimates from Level 4 show that the more educated are less likely to receive a promotion. That is, for the pool of workers who move up from Level 4, the ones who receive a promotion have a lower educational attainment. Overall, as in the case of promotion within job level, the promotion decision is driven by an unobservable variation in the worker s expected innate ability not captured by the empirical specification used. E. Move to Lower Job Levels Demotions The results for demotions are presented in Table 8. Demotion is defined as the move to lower job levels (without promotion). Probably not all movements to lower levels without promotion can be considered as demotions. Some transitions are probably lateral or upward movements masked by the fixed hierarchy imposed by the norms of the survey, as previously discussed. The results show that the majority of the effects are small (less than 1 p.p.) or not significant. Once again, as in the analysis of promotion within job levels or promotion to upper job levels, it is difficult to identify individual attributes that determine the career event. The exception is the effect of education in Level 8, given that the marginal effects from education are negative and large (and increase in absolute value with education), which means that, at least in this level, the more educated have a lower demotion probability. 24

26 F. Move with Promotion to Lower Job Levels The results are similar to the ones presented with promotion to upper job levels but the quality of the regressions is very low due to the small number of observations and are omitted. It is not a surprise that it is so because it is not clear in which direction the worker goes with this career event. Moreover, it is a consequence of the difficulty in fitting a particular hierarchy to the one implied by the ordered job levels defined in the survey. 5. Conclusion One aspect of firms personnel policies was characterized in this study: the worker s career progression. The predictions from a model of careers inside the organization were placed against the empirical evidence. The career events that define the worker progression within firms were identified. The data used contain information about the workers job transitions and about the timing of promotions. Thus, it was possible to determine if the worker moved up or down in the hierarchy or if he maintained the current position and, in addition, if he was promoted or not. The analysis showed that education has a positive influence on the promotion of new employees within job levels and on the incumbents movements to upper job levels. The major determinant of the career events defined as promotion within job levels, promotion to upper job levels, and demotion is an unobservable signal sent by the variation in the worker s expected innate ability the learning effect. 25

27 The model also predicts the existence of serial correlation in promotions. This prediction, or more generally the serial correlation between different career events, can also be inspected with the data. This information can be used to insert the past history on the analysis of individual career progression. The timing of the career events can be analyzed with discrete time hazard models, as mentioned, which can take advantage of the time variable not explicitly introduced in the framework, and to better account for the individual heterogeneity. The existence of fast tracks could also be investigated. However, more years in the survey will allow a clearer insight into these issues. The workers transition between firms was omitted from the analysis, but it is possible to know the subsequent job attachment, at least for those workers that move between firms included in the sample. Therefore, this issue could also be studied. The relationship between wage growth and career profiles is analyzed in a companion paper. The analysis is limited to large firms, but it could be extended to smaller ones. This extension gives rise to new issues, not only in the theoretical framework, but also in the empirical specification and econometric modeling. The research made here provides future paths to be followed. Finally, it must be stressed that the economic research on firms personnel policies is important when policy considerations are in order. The different ways firms manage their human resources must be taken into account when there is an intervention in the labor market. 26

28 Data Appendix Table A1 presents the distribution of workers across several firms characteristics. The average number of workers in each firm is 1,681. For the five years, the lowest firm has roughly 2,500 workers, and the largest has more than 20,000 workers. Firms from the industry of textiles, clothing, leather, and footwear employ the greatest number of workers. This industry is traditionally a very important economic activity in Portugal. Workers employed by the firms in the sample are concentrated in the North and Lisbon and the predominant firm s legal type is the corporation. The unit of observation is the employee and as a consequence, all other workers employers and unpaid family workers are excluded from the analysis (1,519 observations). Employees without identification number cannot be followed and are also excluded (14,524 observations). The variables are for the reference month. The reference month is March up until Following this year the reference month is October. This fact introduces a problem with the timing of the variables the 1994 values were obtained more than one year after the 1993 values. Thus, a special care must be taken whenever addressing yearly change in the variables. Those employees with zero earnings are excluded (18,288 observations). The zero earnings exclusion is equivalent to zero working hours exclusion in this sample. As this variable is prone to having a measurement error, a simple wage regression was estimated (omitted) to identify possible outliers. The rule was to exclude observations with wages outside an interval defined by five times the standard error around the predicted value (1,003 observations). Years of education. Number of years corresponding to the last completed level of education (years assigned to each level between brackets): illiterate or can read and 27