Job Mobility and Measurement Error

Transcription

1 Job Moblty and Measurement Error by Adele Bergn A thess submtted n fulflment of the requrements for the degree of Ph.D. In the Department of Economcs, Fnance and Accountng, Natonal Unversty of Ireland, Maynooth (NUIM), Maynooth, Co. Kldare, Ireland. August 2 Head of Department: Professor Rowena Pecchenno Thess Supervsors: Professor Donal O Nell (Lead Supervsor), Dr. Aedn Dors and Dr. Olve Sweetman

2 Table of Contents Lst of Tables v Lst of Fgures. v Summary... x Lst of Presentatons and Publcatons... x Acknowledgements x. Introducton. x 2. Lterature Revew on Job Moblty.. 2. Introducton Why do Workers Change Jobs and how does Job Moblty affect Wages? Theoretcal Consderatons Patterns we should observe n the Data Emprcal Fndngs on Wage Impacts Job Moblty n Ireland Introducton Dataset, Defnng Job Moblty and Descrptve Statstcs Dataset and Sample Constructon Calculaton of Job Moblty Descrptve Statstcs Determnants of Job Change Decomposng the Increase n the Rate of Voluntary Job Change Non-Lnear Decomposton Technque Conclusons... 4 Appendx Tables 4 4. The Performance of the Hausman et al. Estmator n Correctng for Msclassfcaton n the Dependent Varable n Bnary Choce Models Introducton and Motvaton Bnary Choce Model wth Msclassfcaton 47

3 4.2. Effect of Measurement Error n the Dependent Varable Standard Model of Msclassfcaton Emprcal Applcatons Identfcaton of the Model Monte Carlo Smulatons Identfcaton of the Model Extensons to the Basc Model Specfcaton Weakenng the Impact of the Explanatory Varable n the Model Effect of Sample Sze Increasng the Proporton of ~ y n the Sample Asymmetrc Msclassfcaton When the Explanatory Varable s Dchotomous Coeffcent Estmates from Hausman et al. and Probt Models Extensons of the Model where the Estmator Performs Poorly Poor Performance of the Estmator Extendng the Range of the Explanatory Varable Increasng the Importance of the Explanatory Varable Conclusons Appendx Tables Measurement Error n Survey Data: A Model of Job Moblty for Ireland Introducton Labour Market Survey Data Measurement Error Dataset and Defnng Job Changes Consstency of Startng Dates wthn Jobs Bnary Choce Model wth Msclassfcaton Covarate Dependent Msclassfcaton Estmaton Results Estmaton Results: Msclassfcaton Independent of Covarates Estmaton Results: Covarate Dependent Msclassfcaton Conclusons. 2

4 Appendx 5A: An Alternatve Measure of Job Moblty Appendx Tables Measurement Error n Survey Data: Models of Job Moblty Across Europe Introducton and Motvaton Dataset and Defnton of Job Moblty Measurement Error n Responses Estmaton Results Conclusons. 52 Appendx 6A: Dfferences n Irsh Data between LIS and ECHP.. 55 Appendx Tables Wage Changes and Job Changes: Estmaton wth Measurement Error n a Bnary Regressor Introducton Econometrc Approach Unobserved Heterogenety Reverse Causalty Msclassfcaton Emprcal Strategy Descrptve Statstcs Results Conclusons. 92 Appendx 7A: Msclassfcaton Bas n Multvarate Regresson.. 94 Appendx 7B: Bas n Instrumental Varable Estmates n a Model wth a Sngle Bnary Regressor. 96 Appendx 7C: Consstency of Estmator n Two-Step Approach References.. 2

5 Lst of Tables Table 3.: Revolvng Balanced Panel of Indvduals aged 2 to Table 3.2: Job Moblty Rate... 8 Table 3.3: Number of Job Changes per Worker... 8 Table 3.4: Job Moblty Rates, Average between for Workers under 3 n Table 3.5: Reason for Stoppng Prevous Job... 2 Table 3.6: Job Moblty Rate... 2 Table 3.7: Age Dstrbuton of Workers & Job Change Rate by Age Group... 2 Table 3.8: Gender Dstrbuton of Workers & Job Change Rate by Gender Table 3.9: Educaton Dstrbuton of Workers & Job Change Rate by Educaton Level Table 3.: Occupatonal Dstrbuton of Workers & Job Change Rate by Occupaton Table 3.: Sectoral Dstrbuton of Workers & Job Change Rate by Sector Table 3.2: Multnomal Probt Model of Job Moblty Table 3.3: Probt Models of Voluntary Job Moblty Table 3.4: Non-Lnear Decomposton of the Dfference n Job Moblty Rates between and 998- usng the Farle Method Appendx Table 3.: Explanatory Varables: Defntons and Summary Statstcs... 4 Appendx Table 3.2: Non-Lnear Decomposton of the Dfference n Job Moblty Rates between and 998- usng the Farle Method, ncludng Age nstead of Experence Appendx Table 3.3: Non-Lnear Decomposton of the Dfference n Job Moblty Rates between and 998- usng the Farle Method, ncludng the Unemployment Rate Table 4.: Estmates of Msclassfcaton Probabltes for Model Table 4.2: Comparson of Probt Models wth and wthout Msclassfcaton Table 4.3: Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of x ' for Model wth % Symmetrc Msclassfcaton, usng the Hausman et al. Estmator... 6 v

6 Table 4.4: Estmates of Msclassfcaton Probabltes for Models Table 4.5: Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of the x Dstrbuton for Model 3 wth % Symmetrc Msclassfcaton when ˆ s Table 4.6: Estmates of Msclassfcaton Probabltes for Models Table 4.7: Asymmetrc Msclassfcaton n Model... 7 Table 4.8: Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of the x ' Dstrbuton for Model 9 where =5% and =5%... 7 Table 4.9: Estmates of Msclassfcaton Probabltes when the Models only nclude Dummy Varables Table 4.: Comparson of Hausman et al. Coeffcent Estmates wth Probt Model 77 Table 4.: Estmates of Msclassfcaton Probabltes for Models Table 4.2: Estmates of Msclassfcaton Probabltes for Models Table 4.3: Comparson of Coeffcent Estmates from Hausman et al. Model and Probt Model for Models 3, Appendx Table 4.: Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of x ' for Model wth 5% Symmetrc Msclassfcaton... 9 Appendx Table 4.2: Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of x ' for Model wth % Symmetrc Msclassfcaton... 9 Appendx Table 4.3 Comparson of Predcted Probabltes wth Observed Proporton of s by Groups of x ' for Model wth 2% Symmetrc Msclassfcaton... 9 Appendx Table 4.4: Proporton of ~ y n Each Model... 9 Table 5.: Number of Workers and Job Changes Table 5.2: Consstency of Startng Dates wthn Jobs Table 5.3: Consstency of the Majorty of Startng Dates wthn Jobs... Table 5.4: Tmng of Inconsstences wthn Jobs... 2 Table 5.5: Problematc Jobs by Worker Characterstcs... 4 Table 5.6: Coeffcent Estmates from Models of Job Change... Table 5.7: Margnal Effects from Models of Job Change... Table 5.8: Model of Job Change where Msclassfcaton Depends on Experence.. 7 Table 5.9: Model of Job Change where Msclassfcaton Depends on Gender... 8 v

7 Table 5.: Model of Job Change where Msclassfcaton Depends on Workng Part- Tme... 9 Appendx Table 5.: Number of Workers and Job Changes Appendx Table 5.2: Explanatory Varables: Defntons and Summary Statstcs Table 6.: Number of Jobs Observed over the Sample Perod Table 6.2: Number of Recent Jobs Observed over the Sample Perod Table 6.3: Margnal Effects from Models of Job Change for Austra Table 6.4: Margnal Effects from Models of Job Change for Belgum Table 6.5: Margnal Effects from Models of Job Change for Denmark Table 6.6: Margnal Effects from Models of Job Change for Fnland Table 6.7: Margnal Effects from Models of Job Change for France Table 6.8: Margnal Effects from Models of Job Change for Germany... 4 Table 6.9: Margnal Effects from Models of Job Change for Greece... 4 Table 6.: Margnal Effects from Models of Job Change for Ireland Table 6.: Margnal Effects from Models of Job Change for Italy Table 6.2: Margnal Effects from Models of Job Change for The Netherlands Table 6.3: Margnal Effects from Models of Job Change for Portugal Table 6.4: Margnal Effects from Models of Job Change for Span Table 6.5: True Moblty Rates Derved from Estmates of Table 6.6: Inconsstences n Job Start Dates and Estmates of Appendx Table 6.: Revolvng Balanced Panels, Number of Workers and Job Changes Appendx Table 6.2: Revolvng Balanced Panels and the Number of Cases where the Year that a Worker s Job Started s Mssng Appendx Table 6.3: Number of Recent Jobs Observed over the Sample Perod usng ECHP data Appendx Table 6.4: Number of Recent Jobs Observed over the Sample Perod usng LIS data Appendx Table 6.5: Number of Recent Jobs Observed over the Sample Perod usng LIS data that have an Inconsstency n Startng Dates Appendx Table 6.6: Descrptve Statstcs v

8 Table 7.: Average Wthn-Person Wage Growth Table 7.2: Average Wage Growth for Job Stays and Job Moves Table 7.3: Average Wthn-Person Wage Growth by Experence Table 7.4: Average Wage Growth for Job Stays and Job Moves by Experence Table 7.5: Average Wthn-Person Wage Growth by Gender Table 7.6: Average Wage Growth for Job Stays and Job Moves by Gender Table 7.7: Average Wthn-Person Wage Growth by Educaton Table 7.8: Average Wage Growth for Job Stays and Job Moves by Educaton Table 7.9: Pooled OLS Wage Growth Model... 8 Table 7.: Pooled OLS, Fxed Effects and Random Effects Wage Growth Models Table 7.: Random Effects Wage Growth Models, Controllng for Type of Job Moblty Table 7.2: Effect of Job Moblty on Wage Growth Controllng for Msclassfcaton Table 7.3: Adjusted Pooled OLS Estmates for a Range of Msclassfcaton Rates Table 7.4: Satsfacton wth Varous Aspects of Job Table 7.5: Satsfacton wth Varous Aspects of Job for those not Satsfed wth Earnngs... 9 Table 7.6: Second Stage IV Estmates of Job Moblty on Wage Growth... 9 Table 7.7: IV Estmates of Job Moblty on Wage Growth, Controllng for Msclassfcaton... 9 Table 7.8: Summary of Estmates of Job Moblty on Wage Growth v

9 Lst of Fgures Fgure 5.: Margnal Effect of Experence n Models of Job Moblty.5 Fgure 6.: Annual Average Moblty Rates derved from the ECHP.. 29 Fgure 6.2: Comparson of Cross Country Moblty Rates from ECHP and OECD. 3 v

10 Summary Ths thess conssts of essays nvestgatng job moblty and measurement error. Job moblty, captured here as a change of employer, s a strkng feature of the labour market. In emprcal work on job moblty, researchers often depend on self-reported tenure data to dentfy job changes. There may be measurement error n these responses and consequently observatons may be msclassfed as job changes when truly no change has taken place and vce versa. These observatons serve as a startng pont for ths thess. Chapter 3 explores the level and determnants of job moblty n Ireland, usng the Lvng n Ireland Survey, the Irsh component of the European Communty Household Panel. One of the fndngs s that the rate of voluntary (.e. employee ntated) job moblty n Ireland trebled over the perod 995 to 2. A decomposton technque ndcates that composton changes only explan around one-ffth of the ncrease, whle the remander reflects changes n operaton of the labour market. Chapter 4 uses Monte Carlo smulaton technques to nvestgate the performance of a modfed probt estmator developed by Hausman, Abrevaya and Scott-Morton (998) that controls for msclassfcaton n a dependent varable. An analyss of the data ndcates that there s the possblty of substantal measurement error whch may make t dffcult to capture job changes. The Hausman et al. (998) estmator s used to formally control for measurement error n models of job change for Ireland (Chapter 5) and other European countres (Chapter 6). The man fndngs are that the true rates of job change are beng severely undercounted n several countres and also that smlar factors are mportant n determnng job changes across countres. Fnally, Chapter 7 contrbutes to the exstng lterature that examnes the mpact of job moblty on wage growth. It fnds that by controllng for measurement error n job changes, the effect of job moblty on wage growth s larger than prevalng estmates suggest. x

11 Lst of Presentatons and Publcatons A verson of chapter 3 has been publshed as Bergn, A. (29), Job Moblty n Ireland, The Economc and Socal Revew, No., Sprng, pp Presentatons: Job Moblty n Ireland, Irsh Economc Assocaton, 22nd Annual Conference, Mayo, Ireland, Aprl 28. Measurement Error n Survey Data: Job Moblty n Ireland, NUI Maynooth, Department of Economcs, Fnance and Accountng, December 28. Measurement Error n Survey Data: Job Moblty n Ireland, 2th IZA European Summer School n Labor Economcs, Ammersee, Germany, 27th Aprl to 3rd May, 29. Measurement Error n Survey Data: Job Moblty n Europe, NUI Maynooth, Department of Economcs, Fnance and Accountng, May 2. Wage Changes and Job Changes: Estmaton wth Measurement Error n a Bnary Regressor, NUI Maynooth, Department of Economcs, Fnance and Accountng, Aprl 2. x

12 Acknowledgements I would lke to thank many people for ther help n completng ths thess. Frst and foremost, I would lke to express my grattude and apprecaton to my supervsors, Professor Donal O Nell, Dr. Aedn Dors and Dr. Olve Sweetman, for ther gudance, nsght and commtment over the course of my doctoral studes. I have learned a lot from them. I am ndebted to the late Professor Dens Connffe for hs advce and valuable comments at dfferent stages of ths work. I would lke to thank Dr. Alan Barrett for hs contnuous encouragement. I am also grateful to the staff and my fellow students n the Department and my colleagues n the ESRI for ther help, advce and constructve comments and suggestons. Fnally, I would lke to express my heartfelt thanks to my frends and famly, especally my parents, for ther treless support, patence and encouragement. x

13 . Introducton Ths thess conssts of sx chapters (n addton to ths ntroducton) nvestgatng jobto-job moblty and measurement error n capturng job changes. Job moblty s an mportant phenomenon to understand because the movement of workers from one job to another allows for flexblty n the labour market by provdng workers and frms wth a mechansm to adapt to changng economc and personal crcumstances. Ths churnng can be seen as the effcent workng of the labour market; workers can seek out new employment matches that they are more productve n and for whch they wll be better rewarded. Survey data are very often used n appled work on job moblty. Typcally, surveys do not contan a drect queston askng respondents f they have changed jobs; nstead job changes are nferred from responses to a queston about tenure. It s documented n the lterature that there s substantal measurement error n the responses to questons that are used to determne job changes (Brown and Lght (992)). However, most research gnores ths measurement error and so there s a rsk of msclassfyng cases as job changes when truly no change has taken place and vce versa. Ths s one of the central concerns of ths thess. In emprcal research, job changes are captured n a bnary varable (an observaton s coded as a job change or a job stay). Measurement error n ths case s non-classcal n nature, as t s negatvely correlated wth the true varable. The decson to change jobs can be analysed n a bnary choce model, such as a probt model. Measurement error n the dependent varable n a nonlnear model leads to estmates that are based and nconsstent (Hausman (2)). Hausman, Abrevaya and Scott-Morton (998) develop an estmator that controls for msclassfcaton n the dependent varable n dscrete choce models. The estmator explctly ncorporates the msclassfcaton probabltes as addtonal parameters to be estmated. Hausman et al. (998) show that even when only a small amount of data s msclassfed that ordnary probt estmates are severely based. See Bound, Brown and Mathowetz (2) for a survey of measurement error n survey data. x

14 There are also serous nference problems when a bnary job change varable s used as an explanatory varable n a regresson model, e.g. n estmatng the wage effects assocated wth job moblty. Agner (973) demonstrates how, n the presence of a msclassfed bnary regressor, OLS coeffcent estmates are based towards zero. Therefore, n cases where msclassfcaton s lkely, t s essental to control for t, both when the potentally msclassfed varable s the dependent varable n an analyss and when t s an ndependent varable. The determnants of job moblty and also the wage mpacts of changng jobs have long been studed n labour economcs. One of the contrbutons of ths thess s to examne how the results from these types of analyses are altered by measurement error n calculatng job changes. In partcular, t examnes the extent to whch job changes may be under- or over-counted n Ireland, and also n a range of other European countres. It also seeks to assess the mpact that gnorng msclassfcaton has on covarate effects n models of job change. In addton, t nvestgates the relatonshp between job moblty and wage growth for Ireland and the degree to whch the estmated mpact of job moblty on wage growth s affected by measurement error. In what follows, I summarse each chapter and the man conclusons. Chapter 2 contans a lterature revew on job moblty that s common to several of the subsequent chapters. It covers the theoretcal approaches to job moblty and the assocated wage effects, the patterns we should observe n the data and emprcal evdence. Chapter 3 nvestgates the factors that determne job-to-job moblty n Ireland over the perod 995 to 2, usng the Lvng n Ireland Survey, the Irsh component of the European Communty Household Panel. Changng jobs appears to be an mportant part of worker s experence n the labour market yet lttle s known, n an Irsh context, about how prevalent job changng s, as well as what types of worker are most lkely to swtch jobs and ths chapter seeks to brdge that gap. It fnds that each year approxmately per cent of workers change jobs. x

15 The chapter dstngushes between voluntary (employee ntated) and nvoluntary (employer ntated) moblty. It fnds that labour market experence, workng n the publc sector, whether a person s oversklled, the sector they work n and ther occupaton are mportant determnants of voluntary job change. The dataset used covers most of the Celtc Tger perod, a tme where growth n the Irsh economy was exceptonal. The chapter fnds the rate of voluntary job moblty n Ireland trebled over the perod 995 to 2. The sample s dvded nto two tme perods and a decomposton technque s appled to ascertan how much of the ncrease n moblty s attrbutable to compostonal changes and how much s due to other factors. Compostonal changes explan around one-ffth of the ncrease, whle the changes n the labour market condtons facng workers are also an mportant factor drvng the ncrease. Chapter 4 analyses n detal the estmator developed by Hausman et al. (998) to control for msclassfcaton n bnary choce models. The chapter uses Monte Carlo smulatons to compare the estmates from the Hausman et al. model wth those from an ordnary probt model for dfferent model specfcatons wth varyng levels of msclassfcaton. There are many sources of msclassfcaton n models that employ bnary dependent varables, such as codng error, self-reportng, recall error and where a dummy varable s used to serve as a proxy for some true underlyng varable. The am of the chapter s to provde nsghts nto when t s reasonable to use the Hausman et al. estmator to control for msclassfcaton. In general, the Hausman et al. estmator outperforms an ordnary probt model but n some cases, especally when the range of x ' s lmted or when both the sample sze s small and the level of msclassfcaton s low, a probt model s superor. Chapter 5 explores the extent of measurement error evdent n responses to the queston used to capture job changes for Ireland usng the Lvng n Ireland Survey. It fnds that the extent of measurement error n the data s consderable but t s smlar to what Brown and Lght (992) fnd for the US usng the Panel Study of Income Dynamcs. The chapter uses the Hausman et al. (998) estmator to formally control for msclassfcaton n job changes. It fnds that, by gnorng msclassfcaton, the xv

16 true number of job changes s underestmated by around 6 per cent. To put ths fgure n context, the average moblty rate n the dataset s calculated at around 9.7 per cent and ths estmate mples that the true moblty rate s around 5.6 per cent. In addton, the chapter fnds that gnorng msclassfcaton leads to dmnshed covarate effects. The chapter also explores the possblty of covarate dependent msclassfcaton but no support s found for ths hypothess. Chapter 6 extends the analyss n Chapter 5 to other European countres n the European Communty Household Panel dataset. The chapter fnds that the true rates of job moblty are undercounted n several countres, typcally n the perpheral countres of the EU. In addton, t fnds that smlar factors are mportant n determnng job moblty across countres. Apart from age, personal and household characterstcs are generally not mportant n explanng job changes, whle frm and job characterstcs have an mportant role n explanng job changes. For the countres, where the model ncorporatng msclassfcaton s accepted, the mpact of the covarates s much stronger ndcatng that ordnary probt estmates are based downwards. Chapter 7 focuses on the wage effects assocated wth changng jobs. Prevous research has examned the role that job moblty makes to lfe cycle wage growth (e.g. (Topel and Ward (992)) or how gender dfferences n the returns to job moblty may help explan the gender pay gap (e.g. Loprest (992)). Estmates of the returns to job moblty are crucal to such studes. The chapter fnds OLS estmates (that gnore msclassfcaton) of the effect of job moblty on wage growth of around 8 per cent. Ths effect perssts even after controllng for unobserved ndvdual heterogenety. Ths estmate s very smlar to what has been found n other studes (e.g. OECD (2)). However these estmates gnore measurement error n job changes. The chapter adopts a two-step approach to controllng for msclassfcaton n a bnary explanatory varable. It fnds that controllng for msclassfcaton has a substantal effect on the estmated mpact changng jobs has on wage growth. The effect of job moblty on wage growth s estmated to be closer to 4 per cent when measurement error s controlled for. xv

17 2. Lterature Revew on Job Moblty 2. Introducton Ths chapter dscusses the theoretcal and emprcal background for some of the subsequent chapters. 2 Secton 2.2 revews theores of job moblty and the assocated mplcatons for wages. Secton 2.3 explores the types of patterns we should observe n the data and the related emprcal evdence. Fnally, Secton 2.4 focuses on the emprcal research on the wage effects of job moblty. 2.2 Why do Workers Change Jobs and how does Job Moblty affect Wages? Theoretcal Consderatons It s wdely accepted that human captal accumulaton, both general and specfc to the job, s a major drvng force of wage growth over the lfe-cycle. In equlbrum, n a compettve labour market wth perfect nformaton, workers are pad ther margnal product whch depends on human captal nvestment. However, f the labour market s charactersed by heterogenety n workers and frms and by ncomplete nformaton, t s only after a seres of job matches, separatons and new job matches that ths equlbrum s acheved. For example, mperfect nformaton may mean that frms are uncertan about the productvty of workers at the begnnng of employment relatonshps. As a result, workers may not be ntally employed n the jobs n whch they are the most productve. Job moblty provdes a mechansm for the labour market to move towards a more effcent allocaton of resources whereby workers sort themselves nto jobs that maxmse ther productvty. Therefore job moblty may make an mportant contrbuton to lfe-cycle wage growth. In the emprcal lterature, t s qute dffcult, and not always possble, to dstngush between dfferent models of job moblty and often they are seen as complementary n the sense that each contrbutes to our understandng of a worker s decson to change 2 Sectons 2.2 and 2.3 essentally provde the theoretcal background and emprcal evdence on job moblty relevant for Chapters 3, 5 and 6. In addton to Sectons 2.2 and 2.3, Secton 2.4 s mportant for Chapter 7.

18 jobs and the effect ths can have on wages (Veum (997)). 3 A few papers attempt to dsentangle the wage effects from dfferent models of job moblty (e.g. Lght and McGarry (998), Campbell (2) and Munasnghe and Sgman (24)). Underlyng the varous models are dfferent causal mechansms through whch job moblty affects wages. Also, some of the theoretcal models make dfferent predctons about the mpact of changng jobs on wages. As a result, t s useful to understand and to dentfy these dfferent mechansms and the assocated predcted wage effects. 4 Four man theoretcal approaches can be dstngushed n the lterature, namely the moverstayer model, job search models, job matchng models and human captal models. Mover-Stayer Model The mover-stayer model of Blumen et al. (955) comes from the socology lterature and s one of the earlest models of job moblty. In ths model some ndvduals are nstnctvely more lkely to change jobs than others. Ths nherent tch or hobo syndrome arses from some underlyng unobservable personal characterstc(s). Ths characterstc results n people beng consstently hgh or low moblty ndvduals over tme. It s assumed that ths nstablty makes movers less productve than stayers. The mplcaton for wages s that movers earn lower wages because they are less productve workers. In ths model, moblty s negatvely correlated wth wages because t s correlated wth the unobservable characterstc that determnes productvty. Therefore, n emprcal work controllng for unobserved ndvdual heterogenety should mean that the wages of movers and stayers do not dffer. Emprcal evdence tends to refute the predctons of ths model (e.g. Lght and McGarry (998) and Munasnghe and Sgman (24)). Job Search Models In job search models (e.g. Burdett (978)) there s heterogenety n worker productvty across jobs and so a worker s productvty depends on the frm they are employed n. The qualty (.e. productvty) of an employment match s known n advance. Workers search for better matches and so they move from lower to hgher payng jobs as the opportunty arses. 3 In fact, many models of job moblty combne some of the approaches outlned here. For example, the job separaton model n Jovanovc (979a) merges the specfc captal approach wth job search theory. 4 In the models examned n ths secton, job moblty refers to voluntary (employee ntated) job changes. 2

19 In Burdett (978) when the worker enters the labour market, f they accept the frst job offer they obtan, ther wage can be seen as a random draw from a dstrbuton of wage offers reflectng ther dfferng productvtes n each of the jobs avalable. Once employed, the worker can engage n search actvty. Any job offer they receve from a frm wll reflect ther productvty n that frm. The more ntensely a worker searches, the faster s the arrval rate of alternatve offers. Workers wll have an ncentve to swtch jobs f the present value of the wage n the alternatve job exceeds that of the exstng job, net of any moblty costs. Therefore, the model predcts that job moblty has a postve effect on wages. In ths type of search model, the wage gan arsng from moblty comprses a dscrete jump n the wage level at the pont of job change. Wages are not affected by moblty as such, but rather by an mprovement n match qualty whch s constant (wthn the job). Therefore, moblty should have no effect on wages once tme constant jobspecfc effects are controlled for. The wage effects predcted by ths model have receved mxed emprcal support. Lght and McGarry (998) fnd that job moblty has an effect on wages, even after controllng for observed and unobserved personal and job characterstcs. However, Campbell (2) estmates how much of the wage effect assocated wth moblty s attrbutable to a change n the wage level when the job change occurs and how much s due to a change n wage growth. He fnds that around 4 per cent of the gan assocated wth job moblty s attrbutable to an ncrease n the wage level at the tme of changng jobs and the remander s due to hgher on-the-job wage growth n the new job so ths type of search model only provdes a partal explanaton of the wage effect assocated wth changng jobs. More recent models extend the approach n Burdett (978). For example, Burdett and Mortensen (998) ncorporate the reactons of frms. Natcchono and Pango (24) classfy ths type of search model as statc n the sense that s does not allow for any wthn-job wage dynamcs. Other search models allow for on-the-job wage growth. For example, n Burdett and Coles (23) and Stevens (24), employers post wagetenure contracts (nstead of just wages) that allow wages to ncrease wth tenure, to reduce the qut probablty of ther employees. In Postel-Vnay and Robn (22) wages ncrease on-the-job because of outsde offers. In these more recent search 3

20 models, the gan from changng jobs wll not necessarly comprse a dscrete jump n the wage level at the tme of job change but rather depend on the wage growth n the new job. Job Matchng Models The key feature of the job matchng approach s that match qualty s not known ex ante. In matchng models (e.g. Johnson (978), Jovanovc (979b) and Vscus (979)), jobs are consdered as experence goods and t s only over tme that nformaton about the qualty of the match s revealed. Smlar to the job search approach, matchng models tend to assume there s heterogenety n worker productvty across jobs. In Jovanovc (979b), workers face a dstrbuton of wages reflectng frm s estmates of ther productvty, rather than ther actual productvty, n dfferent jobs. As tenure on the job ncreases frms accumulate addtonal nformaton about a worker s true productvty. Ths can lead to an upward or downwards adjustment to wages. 5 Workers who experence wage cuts or have low on-the-job wage growth are lkely to separate from ther employer. Specfcally, job changes occur f the expected value of an offer at another frm exceeds the expected value of the wage n the exstng job. Ths model predcts a postve relatonshp between job moblty and wage growth, although t s not a drect relatonshp but rather wage growth s affected by superor perceptons of match qualty. One of the mplcatons of the model s that a worker may be wllng to accept a wage cut at the tme of changng jobs (.e. n the short-run) f they receve hgher on-the-job wage growth n the new job. Natcchono and Pango (24) classfy ths type of model as dynamc as t ncorporates wthn-job wage dynamcs. However, on-the-job wage growth s not attrbutable to changes n productvty but rather from changes n the frm s assessment of the worker s productvty. In matchng models, moblty s drven by changes n observatons of match qualty. Although true match qualty s constant wthn the job, vews about match qualty can change over tme. Therefore, there wll be a relatonshp between job moblty and 5 Other models (e.g. Greenwald (986) and Gbbons and Katz (99)) explore the possblty of nformatonal asymmetres where employers have prvate nformaton about the ablty of ther employees and how ths affects employees wages and moblty. 4

21 wages even after ndvdual and job specfc observable and unobservable effects are controlled for. Although we expect the relatonshp between job moblty and wages to be postve, t can be negatve n the short-term. Lght and McGarry (998) fnd that moblty has an effect on wages after controllng for ndvdual and job specfc unobservable effects and argue ths fndng s consstent wth the job matchng model. Specfc Human Captal Approach The specfc human captal approach (e.g. Becker (962), Jovanovc (979a), Mortensen (978) and Parsons (972)) hghlghts a negatve relatonshp between nvestment n specfc human captal and the lkelhood of job change. Workers acqure specfc human captal as tenure n a job ncreases. As these sklls are not transferable to a new job, workers and frms share the costs and benefts of ths nvestment. The acquston of ths specfc human captal rases productvty and consequently wages n the current job so the lkelhood of a job separaton decreases wth tenure. In the short-term, we expect changng jobs to result n wage losses because of the non transferablty of specfc captal to another job. However, as the rate of specfc human captal accumulaton declnes wth job tenure, wage growth wll also declne as tenure on the job ncreases. Although exstng specfc captal s lost when changng jobs whch can lead to a lower startng wage n an alternatve job, there may be more opportuntes for nvestment n specfc human captal n an alternatve job whch means that the worker could have faster on-the-job wage growth than n the current job (Mortensen (988)). Other Approaches Many modern theoretcal models buld on the models descrbed above. However, there are alternatve approaches. For example, n Lazear s (986) radng model, frms compete for hgh qualty workers and they use workers prevous wages as an ndcator of ther qualty. Consequently, hgh productvty workers experence more moblty than low productvty workers because the hgh payng frms wll poach workers from other frms. Ths s contrary to the predcton of the mover-stayer model; n ths radng model moblty acts as a postve sgnal of productvty and leads to wage gans. 5

22 2.3 Patterns we should observe n the Data Labour Market Condtons Turnover rates should vary over the course of the busness cycle. Shmer (23) hghlghts the fact that vacances are procyclcal. Therefore, durng an upturn there s an ncrease n vacances and so there are more potental employment opportuntes avalable to workers. In job search models, ths would lead to an ncrease n the job offer arrval rate. In job matchng models there s an ncrease n the number of alternatve jobs a worker can swtch to. In general, we would expect workers to have a hgher probablty of quttng when they have a good chance of obtanng a better job quckly. Therefore, when labour market condtons are tght we would expect to see more quts than when they are loose (e.g. Cornelssen, Hubler and Schneck (27)). Conversely, layoff rates tend to be ant-cyclcal; when demand falls employers wll layoff workers. Burgess, Lane and Stevens (2) say that the relatonshp between job turnover and the busness cycle s more complex. They argue and fnd emprcal support for ther hypothess that n an upturn, where there s a surge n hrng by frms, there s also an ncrease n the number of workers whose productvty s unknown and ths may lead to hgher subsequent job separatons. Smlarly, downturns n actvty provde employers wth an opportunty to shed ther least productve workers, thus reducng the need for subsequent adjustments n ther workforce. Other studes focus on the effect of labour market condtons at the tme of labour market entry for workers; the mpact ths has on wages and how t affects job moblty (e.g. Oreopoulos, von Wachter and Hesz and (28) and Bachmann, Bauer and Davd (2)). Cross Country Dfferences Borghans and Golsteyn (2) document dfferences n moblty patterns across countres for college graduates. They fnd that graduates n the US are more moble than European graduates and that there are large dfferences n job moblty wthn Europe; graduates n Norway and the Netherlands are more moble than those n France, Sweden and Germany. They also fnd that moblty rates n Japan are close to 6

23 the European average moblty rate. We would expect to see hgher moblty rates n countres wth more flexble labour markets. Several studes hghlght dfferences n labour market nsttutons and regulatons across countres whch may help explan dfferences n moblty rates and wage changes (e.g. Dava (25), Dustmann and Perera (28), Ibsen, Trevsan and Westergaard-Nelsen (28) and Pavlopoulos, Fouarge, Muffels and Vermunt (27)). Tenure, Age and Experence Age s an mportant factor determnng job moblty and turnover declnes wth age. In Stgler (962) younger workers are more lkely to try a varety of jobs n order to acqure knowledge of the labour market and ther own preferences and ablty for dfferent jobs (a process known as job shoppng ), so we expect to see hgher moblty rates for younger workers. In job search models, as workers gan labour market experence, they have more opportuntes to search for, assess and accept superor job offers. Consequently, as experence ncreases so does the worker s reservaton wage for changng jobs so the probablty of job moblty declnes wth experence. Ths s supported emprcally by numerous studes. For example, Topel and Ward (992) fnd that for young men, two thrds of ther total lfetme job moblty occurs wthn the frst ten years of ther career. They see job moblty for young workers as a crucal phase n workers movement to more long-term stable employment relatonshps. Booth, Francescon and Garca-Serrano (999) use retrospectve work-hstory data from the Brtsh Household Panel Survey to study moblty over the perod 95 to 99 and they fnd that on average workers hold fve jobs over the course of ther workng lves and that half of all lfetme job changes occur wthn the frst ten years of labour market entry. The probablty of job moblty also declnes wth tenure. In job matchng models, when the qualty of the match s revealed, workers n a successful match may be rewarded wth hgher wages or match specfc rents. If tenure ndcates the exstence of a successful match then these rents may reduce job moblty for workers wth longer tenures. 6 In human captal models, the relatve value of an exstng job, n terms of productvty and wages, ncreases wth tenure because of specfc human 6 Ths negatve relatonshp between job moblty and job tenure s usually evdent usng annual data. However, usng more frequent data can show there s an ncrease n the hazard of a job endng n the frst few months of an employment relatonshp (e.g. Farber (994)). 7

24 captal accumulaton. Therefore, as workers acqure specfc human captal the probablty of turnover s reduced. In addton, Groot and Verberne (997) argue that moblty s lkely to be hgher for younger people or for those wth less labour market experence or less tenure due to the presence of moblty costs. There are both fnancal and psychologcal costs to changng jobs. Older people are more lkely to have made nvestments n housng and be more settled or attached to ther envronment. Therefore, the costs of changng jobs are lkely to be hgher for older people, especally f changng jobs nvolves movng house. Workers wth longer tenure are also lkely to have hgher psychologcal costs n changng jobs. To the extent that longer tenure reflects hgh qualty matches, these workers may feel a stronger attachment to ther organsaton and colleagues. In addton, even f the costs assocated wth changng jobs are the same for younger and older people, younger people have more tme before retrement to make up these costs. Workers change jobs f the expected utlty from dong so exceeds the costs. If the gans nvolved n changng jobs put a worker on a hgher wage path, younger workers wll beneft for longer from these gans. Fnally, older workers may have hgher tme preferences and therefore apply a hgher dscount rate on future earnngs so job moblty declnes wth age. 7 Gender Central to why we mght expect dfferental moblty rates by gender s that women have a lower attachment to the labour force. Barron, Black and Loewensten (993) develop a job-matchng model where workers dffer n ther attachment to the labour force. The model predcts that those wth a weaker attachment to the labour force are sorted nto jobs that offer less tranng and that use less captal and as a result have less to lose by changng jobs n terms of specfc captal. On the other hand, women s moblty decsons may be more constraned by nonmarket varables such as ther partner s locaton or the rearng of chldren. In addton, women spend more tme on household tasks than men (Hersch and Stratton (997)). Therefore the opportunty cost of job search may be hgher for women. Emprcally, several studes have found that by controllng for characterstcs, such as labour market experence, gender 7 Whle there are theoretcal arguments supportng the mportance of varables such as age, experence and tenure, emprcally, they tend to be correlated wth each other, whch may make the dentfcaton of separate effects dffcult. 8

25 dfferences n turnover rates dmnsh or dsappear (e.g. Blau and Kahn (98) for worker-ntated separatons n the US and Booth and Francescon (2) for workerntated separatons n the UK). However, there are nstances where we expect to see dfferences n job change rates. For example, wthn voluntary moblty, women may be more lkely to make changes for non-job related reasons, for example they may be more motvated to change jobs to help them combne ther professonal and famly lfe (e.g. Keth and McWllams (999)). Educaton There are several reasons to expect a relatonshp between educaton and job moblty but there s no consensus n the lterature as to whether t s postve or negatve. Barron et al. (993) argue that educaton may qualfy workers for hgh tranng jobs or captal-ntensve jobs and so ncentves are offered to decrease the expected number of quts for better-educated workers. Connolly and Gottschalk (26) observe that less educated workers may nvest less n human captal and consequently have less to lose by changng jobs. They wll therefore have a lower reservaton value when approached wth an alternatve job offer. Wess (984) suggests that there s an unobservable characterstc, whch he calls stck-to-tveness, that affects both the value of educaton and the value of stayng n an exstng job. Neal (999) proposes a model of job search that nvolves both employment matches and career matches. He argues that less educated workers are lkely to experence more job turnover because they experence moblty that nvolves career change and then they search for a good employment match. Therefore, t s possble that the process of fndng a good career match may add consderably to the wage growth of younger workers, especally the less educated. To the extent that better educated workers (especally those wth college degrees) use tme spent n educaton as a form of pre-market search, they are less lkely to experence moblty that nvolves career changes. However, t s also possble that there could be a postve relatonshp between educaton and moblty. Wess (984) argues that educaton ncreases workers 9

26 alternatve opportuntes and so may ncrease job moblty. Johnson (979) argues that hgher wage varance may ncrease the opton value of job moblty, so hghly educated workers may experence more job turnover as they face more varable but potentally more rewardng alternatve job offers. In addton, Greenwood (975) contends that hghly educated ndvduals may be more effcent job searchers and so have lower transactons costs and therefore may change jobs more easly. It s possble that better educated workers are more lkely to have faster careers and wll change jobs more frequently as a means of advancng up the career ladder (Borsch- Supan (987)). Fnally, Bartel and Lchtenberg (987) put forward the dea that hghly educated workers have a comparatve advantage n learnng and mplementng new technologes and so frms may provde ncentves to reduce job quts. 2.4 Emprcal Fndngs on Wage Impacts Many emprcal studes of the wage changes assocated wth job moblty fnd a postve effect on wage growth of around per cent. Ths result s reasonably robust across countres. Campbell (2) fnds that the wage gan assocated wth changng job over a three-year perod s around per cent n the UK. Abbott and Beach (994) fnd that the average wage gan for Canadan women who change jobs s around 8-9 per cent. Topel and Ward (992) report a per cent return to moblty for young men n the US. OECD (2) fnd an average of a 3 to 4 percentage pont wage premum assocated wth changng jobs for a range of European countres. Ther estmate for the Irsh wage premum s hgher at around 9 per cent. Several studes (e.g. Lght and McGarry (998), Topel and Ward (992)) do not dstngush between voluntary and nvoluntary moblty. There are several reasons why t may not be entrely useful to dfferentate between them. In some nstances, the dstncton between the two may be somewhat arbtrary. For example, an employee n a frm that s n dffculty may be concerned about beng lad off and so may search for and obtan alternatve employment. Ths would count as a voluntary qut even though t s motvated by the rsk of beng lad off. In addton, f we count all employee ntated separatons as voluntary, then voluntary quts nclude those caused by llness and famly reasons, n addton to those due to fndng a better job. Fnally, very often a sgnfcant proporton of respondents n surveys ether do not gve a

27 reason for why they left ther prevous job or they do so for a reason not ncluded n the questonnare. These people ether have to be arbtrarly assgned as voluntary or nvoluntary movers or excluded from the analyss (Lght and McGarry (998)). However, other studes have found the dstncton between voluntary and nvoluntary moblty to be mportant when estmatng wage mpacts. A common result n the lterature s that voluntary moblty leads to hgher wage growth than not changng jobs or for nvoluntary moves. (e.g. Mncer (986)). In addton, n many nstances nvoluntary moves are assocated wth wage losses, especally when there s an ntervenng spell of unemployment between jobs (e.g. Garca Perez and Rebollo Sanz (25)). Dfferent types of separatons (wthn voluntary and nvoluntary changes) have been found to have dfferental wage mpacts. For example, Bartel and Borjas (98) and Keth and McWllams (999) fnd hgher wage growth for voluntary separatons that are job-related and not due to personal reasons. Keth and McWllams (997) fnd that beng lad off has a smaller wage penalty assocated wth t than beng fred. Keth and McWllams (999) also fnd that those who engaged n employed job search pror to separatng from ther employer receve hgher returns to moblty. There s consstent evdence n the lterature that moblty related wage gans decrease wth age as well as tenure (e.g. Bartel and Borjas (98)). In fact most of the emprcal lterature focuses on younger workers because job moblty s more common n the earler stages of ndvduals workng lves. For example, Topel and Ward (992) fnd that job moblty accounts for one thrd of total wage growth for men n ther frst ten years n the labour market. Other studes argue that the effect of changng jobs on wage growth depends on the poston n the wage dstrbuton. For example, Pavlopoulos et al. (27) fnd that job moblty leads to a wage ncrease for low-pad workers but not for hgh-pad workers. Other studes focus on gender dfferences n the returns to moblty and the extent to whch ths could account for the gender wage gap (e.g. Caparros Ruz, Navarro Gomez and Rueda Narvaez (24)). Gender dfferences n the mpact of moblty may arse as women are more lkely than men to separate from ther jobs for famly-related

28 reasons (e.g. Keth and McWllams (997)). In addton, the opportunty cost of job search may be hgher for women, especally marred women, and so they may search less ntensvely than men for a better job match. Kahn and Gresnger (989) argue that female job quts may be less responsve to wages than male ones because women place a hgher value on non-monetary aspects of a job than men. Loprest (992) fnds that women only experence half the wage growth of men when changng jobs. However, Keth and McWllams (997) do not fnd gender dfferences n the returns to moblty once the reason for job separaton s controlled for. Another strand of the lterature focuses on the effect of pror moblty on current wages. Keth (993) argues that hghly moble workers generate greater turnover costs for employers so they vew people wth a hgh probablty of turnover as undesrable and so there may be reputaton effects assocated wth a hgh moblty past. Mncer and Jovanovc (98) aggregate voluntary and nvoluntary changes and they fnd that pror moblty does not affect current wages. However Keth (993) fnds that each voluntary separaton ncreases wages by 2 per cent whle each nvoluntary qut reduces wages by a smlar magntude so that aggregatng the two types of moblty dsguses the offsettng mpact of each. Lght and McGarry (998) also fnd that persstent moblty leads to a lower wage. 2

29 3. Job Moblty n Ireland 3. Introducton The focus of ths chapter s to nvestgate the varous factors that determne job-to-job moblty n Ireland. The dataset used covers most of the Celtc Tger perod, a tme where growth n the Irsh economy was exceptonal, and the chapter addresses the effect the changng labour market had on job moblty. Job moblty s an mportant phenomenon to understand because the movement of workers from one job to another allows for flexblty n the labour market by provdng workers and frms wth a mechansm to adapt to changng economc and personal crcumstances. Ths churnng can be seen as the effcent workng of the labour market; as workers can seek out new employment matches that they are more productve n and for whch they wll be better rewarded. Over the course of the 99s the Irsh economy experenced spectacular growth rates wth GNP growth averagng 7.9 per cent per annum over the perod 995 to 2. The success of the Irsh economy over ths perod was bult on factors that affected labour supply, such as the favourable demographc structure of the labour force, a dramatc rse n female partcpaton rates and net mmgraton, partcularly towards the end of the perod, and accompaned by factors that affected the demand for labour such as foregn drect nvestment and compettveness. Over ths perod, labour supply growth averaged 3.4 per cent per annum and employment ncreased by an average of 67, per annum (on a PES bass), mplyng that the number of jobs created over the perod far exceeded the number of jobs that were destroyed. Exstng research tells us that some of these jobs were flled by those returnng to the labour market, partcularly women (see Dors (2)), and mmgrants or returnng natonals (see Barrett, Ftz Gerald and Nolan (22)). Changng jobs appears to be an mportant part of worker s experence n the labour market yet lttle s known, n an Irsh context, about how prevalent job changng s, as well as what types of worker are most lkely to swtch jobs and ths chapter seeks to brdge that gap. 3