Directory UMM :Data Elmu:jurnal:L:Labour Economics:Vol8.Issue1.2001:

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www.elsevier.nlrlocatereconbase

Churning dynamics: an analysis of hires and

separations at the employer level

Simon Burgess

, Julia Lane

b,)

, David Stevens

UniÕersity of Bristol, CEP and CEPR, England, UK

Economics Department, The American UniÕersity and Census Bureau, 4400 Massachusetts AÕe. NW,

Washington, DC 20016-8029, USA

Regional Employment Dynamics Centre, UniÕersity of Baltimore, USA

Received 19 October 1994; received in revised form 23 July 1999; accepted 29 August 2000

Abstract

This paper provides evidence on job flows and worker flows at the level of the employer. We ask whether firms grow by increasing hires, reducing separations, or both, and we develop a graphical approach to address this. We use a new dataset to estimate the relationship between job flows and worker flows at the employer level. We show that most employers are simultaneously hiring and facing separations. We also show that declining firms continue to hire, and growing firms continue to lose workers. The relationship between hires and separations differs between employers, varying with size, average wage and industry.q_{2001 Elsevier Science B.V. All rights reserved.}

JEL classification: J60; J63

Keywords: Job flows; Worker flows; Churning; Job reallocation; Worker reallocation

1. Introduction

This paper provides evidence on the relationship between job flows and worker flows from employer-level data.1 _{Recent work has demonstrated that there are}

)_{Corresponding author. Tel.:}_q_{1-202-885-3781; fax:}_q_{1-202-885-3790.}

Ž .

E-mail address: [email protected] J. Lane .

Job flows refer to changes in the number of filled jobs at an employer; worker flows refer to the flow of workers through those jobs.

Ž .

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high levels of such flows in the United States Burgess et al., 1999; Davis et al.,

. Ž .

1996; Anderson and Meyer, 1994 , the Netherlands, Hamermesh et al., 1996 ,

Ž . Ž .

France Abowd et al., 1999 and Denmark Albæk and Sørensen, 1998 —an

Ž .

excellent survey is provided in Davis and Haltiwanger 1999 . The latter two studies demonstrate that worker flows are distinct from job flows: many contract-ing employers hire workers and many workers leave expandcontract-ing employers. In previous work, we have referred to those worker flows in excess of job flows as

Ž .

churning Burgess et al., 1996, 1999 and documented the levels and character-istics of churning.

This paper extends the literature by focusing on the distribution of churning over job flows. We seek to answer the following question: do firms achieve an expansion by raising hires or reducing separations? Similarly, do they achieve a reduction in employment by acting on hires or separations? We address this by first developing a graphical approach to jointly describe the worker flows into and out of the firm. We then fit our data to this framework and reveal a complex relationship between hires and separations. We establish that most employers churn: declining firms continue to hire and growing firms continue to lose workers. Churning levels vary widely, depending on the firm’s size, age and industry. So the answer to the question posed is: growing firms mostly increase their hiring and do not act to reduce turnover; declining firms generally maintain hiring but increase separations.

The structure of the paper is as follows. Section 2 describes the data, defines our terms and establishes our graphical approach to the analysis. Section 3 characterizes the overall relationship between churning flows and job flows.

Ž .

Section 4 investigates the role of covariates employer characteristics in affecting this. Section 5 concludes the paper.

2. Data and background

2.1. Data

Ž .

Maryland, like every other state in the US except New York , collects quarterly employment and earnings information through its State Employment Security Agency to manage its unemployment compensation program. Each quarter more than 100,000 employers report earnings and employment for over two million employees. Each wage record includes both employee and employer identifiers, enabling us to construct a quarterly longitudinal dataset on employers. The employer’s four digit Standard Industrial Classification is then added from another administrative file. Virtually, all business employment in Maryland is

Ž .2

covered. We use the most recent decade of data 1985:3 to 1994:3 .

2 _Ž _.

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2.2. Background

We use standard definitions and terminology in defining worker and job flows.3 Employment at employer i at time t is denoted E . In calculating rates, we followi t

Ž .

Davis and Haltiwanger 1999 in using as the denominator the average of current

Ž .

and past employment, denoted N_{i t}s E_{i t}qE_{i t}_y₁ r2. Job flows refer to the change in employment: JF_{i t}sE_{i t}yE_{i t}_y₁. The corresponding rate, JFR , is the_{i t}

4 _Ž _.

level divided by N , the employment growth rate. Total worker flows WF are_{i t}

Ž . Ž .

defined as the sum of hires H and separations S , WF_{i t}sH_{i t}qS . Again, we_{i t} derive the rates by dividing by N . The job flow rate is clearly JFRi t i tsHRi ty

Ž .

SRi ts Ei tyEi ty1 rN . The worker flow rate can thus be written as WFRit i ts

<JFRi t<qCFRi t where CFR is the rate of excess worker flows, or churning. Note an alternative way of writing that will be useful below is CFRi ts2=

Ž . < <

min HR ,SRi t i t . Thus JFR represents the minimum amount of worker turnover required for the firm to achieve its desired employment growth, and CFR represents worker turnover over and above that level. This might arise from

workers churning firms quitting for other opportunities and being replaced by

. Ž

their current employer or firms churning workers firms attempting to change the .5

skill mix of their workforce .

Ž .

Fig. 1 shows the micro employer-level relationship between the hiring rate and the separations rate. Clearly, we could display our data simply as a scatter plot on this diagram. In fact, it is easier and more revealing to recast the problem in terms of JFR and CFR. The organizing feature is a continuum of 458 lines combined with the distance along the 458 line. This locates any point on the diagram uniquely. Along any 458line, the JFR is constant. Different points strung out along a given 458 line represent different levels of worker turnover, that is different churning rates. For example, an employer with a hiring rate of 10% and a separation rate of 5% clearly has a JFR of 5% and a CFR of 5%. The particular 458line tells us the job flow rate and the distance along it gives us the churning

'

Ž Ž ..

flow rate in fact simple geometry tells us that the CFRs 2 distance . We think of the economic decisions underlying this diagram as follows. Given an expected quit rate, the firm chooses its HR and SR to achieve its desired

3 _Ž _.

These terms follow those used by Davis and Haltiwanger 1990, 1994 , Anderson and Meyer

Ž1994 and Burgess et al. 1996 .. Ž .

4 _Ž

Note that though this is the standard definition of job flows in the literature, see for example,

Davis and Haltiwanger, 1990, 1994 , and that this therefore forces all other flows to be labeled churning flows, other views are possible. Our view is based on a job as a relationship between a worker and a firm, simply, a match. Changes in the number of such matches then reflect job flows. But it is also possible to think of a job as a task, a set of skills. In this case, the firm can keep the total number

Ž .

of jobs the same but reconfigure its skill mix, replacing jobs tasks, skill sets of one type with another. In our framework, such changes would be called churning flows; other analysts may prefer to think of these as job flows.

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Fig. 1. Hires, separations and employment growth.

employment growth rate. It is also true that the firm, through its personnel policies, wage setting and the like, can influence the average quit rate. Thus points drawn in HRrSR space trace out the firm’s decisions on employment growth and optimal churning.6

There are clearly a number of choices open to the firm. Consider a firm at point A in Fig. 1 currently with JFRs0, HRsSRs20%. Suppose that the employer decides to grow by 5% in the next quarter. This could be achieved using a continuum of combinations of hiring and separation rates, three of which are

It is of course true that churning probably involves a substantial element of replaced quits and the firm does not directly control quits. But we assume that the firm knows the function relating the likelihood of quits to the firm’s compensation package and other aspects of its personnel policies. The

Ž .

firm also computes its optimal level of turnover see below . It then sets the optimal wage in the light of the effect this will have on churning. So while the firm cannot choose the quit rate, it can choose the parameters facing potential quitters. This is the sense in which the firm chooses the churning rate.

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identified in the figure. Point B indicates a hiring rate of 25% accompanied by the unchanged separation rate of 20%. In this case, the growth was accomplished entirely through a revised hiring strategy. Point C shows the employer choosing to maintain hiring at 20%, but reducing separations to 15%, which illustrates a very different personnel management strategy. Points D and E represent adjustment of both hiring and attrition strategies. Each strategy implies a different level of churning: point B involves a churning rate of 40%, C 30%, D 20% and E 50%. The standard case considered in theory models of zero churning occurs where the

Ž . Ž .

458line intersects the vertical axis JFR)0 or the horizontal axis if JFR-0 . Similar argument applies for a decline in employment.

We will address the question we have set ourselves using this diagram as a framework for organizing the data. Do expanding firms tend to move upwards Žraising hires, not reducing separations or leftwards maintaining hires, reducing. Ž

separations ? Similarly, do declining firms move downwards or rightwards? Given

Ž . Ž .

our data description device of 458lines JFR and distance along them CFR , the natural way to display the data would be as a continuum of density plots lying along the 458lines. Visually, this would be very difficult, so we can equivalently show the data as a box plot of CFR split up by narrow JFR bands.7

3. Empirical description of job and churning flows

Ž .

The evidence on this is presented in Fig. 2. Positive negative job flow rates

Ž . 8

correspond to 458 lines in Fig. 1 that intersect the vertical horizontal axis. The density function of CFR out along any particular 458line is the variable summa-rized in the box plot. It is immediately apparent that churning is characteristic of

most of the employers in the dataset 90% of employers in most job bands engage .

have positive churning flows . Churning levels in excess of 10% characterize more than 75% of the employers in most job bands. The figure also shows that median churning generally increases as absolute job flows increase. At both the bottom and the top of the job flow distribution, churning is both higher in magnitude and more disperse. The pattern is also relatively symmetric across positive and negative job flow bands.

Ž .

This ubiquitous churning confirms the findings of Hamermesh et al. 1996 that not only do contracting employers still hire workers but also workers leave expanding employers.9 We can show this most strikingly by plotting the

his-7

The box plot shows the distribution of churning flows for each band of the job flow rate. For each

Ž . Ž

job flow rate band, the graph shows the 25th and 75th percentile the limits of the box , the median the

line within the box and the lines emerging from the box show the upper and lower adjacent values

Žextreme values .. 8

These are ‘wide’ 458lines to give enough points to summarise.

This pattern is consistent throughout the 1985–1994 period: although the graph shows all time periods, a quarter by quarter analysis shows similar patterns.

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Fig. 2. Box plot of churning rates against job flow rates.

tograms of hiring and separations rates by job flow bands: see Fig. 3. The figure shows a pattern, which is remarkably similar to that found in the Dutch data: although hiring rates are higher for expanding employers, contracting employers still hire. The separation pattern is almost the mirror image of hiring, demonstrat-ing that even expanddemonstrat-ing employers have workers who exit.

This section has established that there is quite a complex micro relationship between churning and job flows at the level of the employer. We now move to a

Ž more formal analysis of this relationship and allow for differences over time the

. Ž .

overall macro environment and between firms firm characteristics .

4. Job and churning flows and firm characteristics

In this section, we examine how the HRrSR decisions of firms vary with the size, age, industry and average pay of the establishment. We present the results in a table and also as a plot in HRrSR space as in Fig. 1. To be clear: we are not saying that there is a causal mechanism between HR and SR—Fig. 1 traces out the simultaneous choices of firms on both accessions and separations. Similarly, when we recast the problem in terms of JFR and CFR, such regressions are quantifying the relationship between these two facets of firms’ turnover decisions, not showing causation.

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Nevertheless, we can briefly review some views on the determinants of firm’s Ž

worker and job turnover decisions see Lane et al., 1996a,b; Burgess et al., 1999 .

for more detail and further evidence . There has been a great deal of work on

Ž .

firm’s decisions on their optimal personnel policies: see Parsons 1986 , for a

Ž .

survey of early work and Lazear 1996 , for recent work. The firm’s decisions on who to hire, how much to pay them and in what way, on firing rules and organisational structure will all likely affect their churning rate. Indeed, they are chosen in the light of the effect on the churning rate. To give a concrete example, the degree of screening before hiring will affect the extent to which the wrong people are hired, and this will be reflected in the subsequent churning rate as the mistakes are rectified. This will depend on the relative cost to the firm of type I and type II errors in hiring. Relating this to observables, if churning is a result of poor hiring choices, small employers may not have personnel departments to screen out poor hires. Hence we would expect churning to be negatively related to employer size. If wage policies are set to reduce turnover, as suggested by efficiency wage theories, then higher average payroll should, on average, be associated with lower churning.10 The effect of a tight aggregate labour market on churning is difficult to predict, though we might expect workers to turnover more quickly in tight labour markets. All of these will affect the level of churning on a given job flow band. Switching from equilibrium considerations to dynamic issues, there are several reasons to expect higher churning levels at higher job flow levels. If the employer is expanding, it is more likely to make hasty hiring decisions, which lead to increased churning.

Ž .

To quantify the HRrSR relationship the turnover decisions of firms , we can clearly directly correlate HR and SR. Alternatively, we can correlate CFR with JFR and rearrange the resulting description to yield an HRrSR pattern.11 _We

choose the latter because we want to allow for a forward bending relationship

Ž .

between HR and SR see example A–E in Fig. 1 which a regression of HR on SR necessarily excludes. However, from the discussion above, we would like to control for the impact of employer size, wage setting practices and age, which suggests the use of a simple regression framework. We therefore estimate the following multivariate relationship

CFR sf JFR qb SIZE qb SIZE2

qb AGE

Ž

.

i t i t 1 i ty1 2 i ty1 3 i t

4

qb4AV.PAYROLLi tqb5CFRi ty1 IND. DUMMIES i t

qb5MACROqmiq´i t.

Ž .

Here f JFRi t is a sixth-order polynomial in JFR , the size variable refers toi t

the number of employees in the previous period and age is the time since the

We would argue that this link is likely to reflect joint determination, not exogenous wages causing churning.

This follows straightforwardly: HRsCFRr2 if JFRF0; HRsJFRqCFRr2 if JFR)0; SRs HRyJFR in both cases.

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employer first filed for an identification number. We control for wage setting Ž

practices by including average payroll total employer payroll divided by the .

number of workers . Since there is likely to be some persistence in employer behavior, we include a lagged value of churning. We also control for macroeco-nomic changes by including the aggregate Maryland employment growth rate. The unit of observation is an employer–employee match, and the time units are quarterly.

Since we expect employers to differ in the levels of turnover Burgess et al., .

1999 , we allow for employer level fixed effects—we correct for the bias inherent with a lagged dependent variable when using fixed effects by using Nickell’s Ž_{1981 approximation.}. 12 _{We also reran the regressions separately by industry but}

little difference was found and the results are not reported here.

We are also interested in the distribution of these relationships: since it is evident from Fig. 2 that there is quite a broad spread of churning at every job flow rate. We thus estimate a set of quantile regressions, reflecting the relationship at the 25th, median, and 75th percentiles.

The results are given in Table 1. The polynomial terms are difficult to interpret and are portrayed graphically in HRrSR space—we discuss this below. In terms of the firm controls, we see that churning is slightly decreasing in the age of the firm. This can be interpreted as the firm gradually adjusting its personnel policies as it learns its best strategies. The relationship between firm size and churning is

Ž .

quite complex. On average OLS results , churning is unrelated to size; but looking at the quantile regressions, we see that churning is increasing in size for low churning firms and decreasing in size for high churning firms.13 _{There is a}

general pattern in Table 1 showing that wages are negatively related to churning rates across the mass of firms. To reiterate, we see this not as a causal relationship but as a correlation capturing the firms’ joint decisions on personnel policies including wage setting. Note that in the fixed effect regression, the sign is reversed. This does not contradict the previous point: the OLS captures primarily variation across firms and hence traces out the choices firms have made between

high turnover or high wages. The fixed effect regression reflects the average .

response to shocks to a single firm that affect both its turnover policy and its wage setting policy. For example, better outside opportunities for workers may lead the firm to both increase its optimal wage offer somewhat and also to permit slightly higher worker turnover.

Industry effects show significant variation, but quantitatively the differences are not large against a constant term of 0.3. Finance, insurance and real estate and professional services show the highest mean effect on churning rates.

We estimate this for employers with more than 20 employees; the results are substantively unchanged when this is reduced to 10 employees.

13 _{Ž .}

We omit size from column 1 as the level of employment would be highly colinear with job flows in a fixed effect regression.

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Table 1

Regression results for CFR

Ž .1 FE Ž .2 OLS Ž .3 25% Ž .4 50% Ž .5 75%

JFR 0.108 0.132 0.054 0.123 0.142

) ) ) ) ) ) ) ) ) )

Ž49.74. Ž35.14. Ž64.03. Ž72.63. Ž58.60. 2

JFR y0.107 0.056 y0.144 y0.031 0.187

) ) ) ) ) ) ) ) ) )

Ž19.86. Ž5.37. Ž76.24. Ž7.71. Ž32.41. 3

JFR y0.037 y0.035 0.008 y0.047 y0.037

) ) ) ) ) ) ) ) ) )

Ž9.89. Ž4.49. Ž5.36. Ž16.28. Ž9.15.

JFR 0.089 y0.019 0.104 0.029 y0.106

) ) ) ) ) ) ) )

Ž17.94. Ž1.80. Ž56.81. Ž7.58. Ž19.71. 5

JFR 0.006 0.006 y0.003 0.009 0.007

) ) ) ) ) ) ) ) ) )

Ž6.28. Ž2.62. Ž8.73. Ž10.66. Ž6.01.

JFR y0.017 0.001 y0.019 y0.006 0.015

) ) ) ) ) ) ) )

Ž16.13. Ž0.45. Ž48.05. Ž7.42. Ž13.49.

Size y0.00056 0.041 0.006 y0.043

) ) ) ) ) )

Ž0.26. Ž51.42. Ž4.30. Ž20.33. 2

Size y0.00025 y0.005 y0.001 0.004

) ) ) ) ) )

Ž1.34. Ž73.26. Ž4.54. Ž24.14.

Age y0.0030 y0.00039 y0.00006 y0.0002 y0.00064

) ) ) ) ) ) ) ) ) )

Ž85.04. Ž28.88. Ž19.70. Ž34.66. Ž52.21.

Ave. Wage 0.00016 y0.0007 y0.00018 y0.00049 y0.00045

) ) ) ) ) ) ) ) ) )

Ž9.23. Ž33.62. Ž55.26. Ž72.05. Ž57.05. Ž .

CFR ty1 0.214 0.572 0.417 0.586 0.738

) ) ) ) ) ) ) ) ) )

Ž162.65. Ž84.40. Ž1055.22. Ž773.48. Ž659.31.

MACRO 0.399 0.448 0.116 0.313 0.396

) ) ) ) ) ) ) ) ) )

Ž26.79. Ž23.43. Ž20.00. Ž26.55. Ž23.55.

MFG 0.019 0.000 0.013 0.030

) ) ) ) ) )

Ž8.27. Ž0.71. Ž9.75. Ž15.61.

TCU 0.012 0.001 0.008 0.022

) ) ) ) ) )

Ž8.48. Ž1.04. Ž7.93. Ž14.67.

FIRE 0.070 0.024 0.059 0.087

) ) ) ) ) ) ) )

Ž31.79. Ž51.96. Ž62.22. Ž64.50.

WHL 0.013 0.002 0.010 0.021

) ) ) ) ) ) ) )

Ž7.90. Ž4.01. Ž8.91. Ž12.84.

RET 0.009 y0.001 0.007 0.020

) ) ) ) ) )

Ž6.51. Ž1.26. Ž7.03. Ž13.98.

Prof Ser 0.053 0.005 0.031 0.055

) ) ) ) ) ) ) )

Ž26.28. Ž11.37. Ž32.22. Ž39.87.

Oth Ser y0.044 y0.007 y0.031 y0.057

) ) ) ) ) ) ) )

Ž26.13. Ž9.91. Ž20.11. Ž26.01.

Constant y0.040 y0.313 y0.101 y0.228 y0.220

) ) ) ) ) ) ) ) ) )

Ž2.64. Ž16.33. Ž17.23. Ž19.23. Ž13.00. 2

R 0.61 0.47 0.1807 0.2589 0.3445

486,866 observations. Robust t-statistics in parentheses)_{significant at 5% level;}) ) _{significant at 1%}

Ž . Ž .

level; column 1 has fixed effects on firm; column 2 has standard errors corrected for firm specific clustering; omitted sector public admin. MACRO is Maryland growth rate.

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The aggregate environment, as measured by the Maryland growth rate, has a clear effect on the churning rate. Both in the OLS and in the fixed effect regressions, a buoyant labour market tends to increase the churning rate. This is consistent with evidence that total engagements and separations are procyclical.

The quantile regressions show that most of these factors have significant effects on the distribution of churning beyond simply shifting the location of the distribution. So for example, the aggregate labour market conditions have a significantly greater effect on high churning firms than on low churning firms—the distribution spreads out in booms. Similarly, the relationship between churning and wages is much weaker in low churning firms.

We map the CFRrJFR coefficients in Table 1 into HRrSR space. This traces out the nature of the relationship between HR and SR: see Fig. 4. The point of interest here is the shape of the figure not the position. Panel A shows the mean effect from the OLS regression. It is clear that most employment growth is accomplished by raising hires. In fact, if anything, separations appear to be higher not lower at higher expansion rates. This means that hires need to be greater still to achieve the desired increase. There are two possible explanations of this. First, as firms expand, workers quit and are replaced. Second, as firms expand, they choose to upgrade their workforce. Employment falls are on average accomplished by raising separations, rather than reducing hiring. Thus we can speculate that

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declines in employment are usually achieved by either involuntary separations or induced quits. Panel B shows the figure corresponding to the fixed effects regression. There is less evidence here of an increase in separations as employ-ment rises, but the same pattern is generally maintained. Panels C and D show the 25th and 75th percentiles. Unsurpisingly, the latter shows a much greater degree of churning than the former and than the mean. This is particularly evident in the range where firms are expanding. This therefore suggests that high churning firms are firms that experience and replace a lot of quits, particularly when they are expanding.

This result is in marked contrast to the behavior of firms in France. Abowd et

Ž . Ž

al. 1999 find that employment adjustments in France for firms with more than .

50 workers are primarily made by adjusting entry, rather than exit rates. In their study, jobs are created by hiring three and separating two workers in a year; jobs are destroyed by hiring one and laying off two workers in a year. It is interesting to speculate that the difference in separation behaviour is linked to the difference in employment protection legislation in the two countries. Firms in the US operate more or less underAemployment at willBwhereas their counterparts in France face

important constraints on their ability to fire workers see OECD, 1999, Annex .

2A .

5. Discussion and summary

What is the answer to our question? The first point to make is that almost all firms almost all the time are simultaneously hiring and experiencing separations. Or, put differently, churning is a ubiquitous feature of the labour market. We have shown that on average firms expand by raising their hiring and not reducing separations. Conversely, firms reduce the workforces by increasing separations and slightly reducing hiring. There are, however, substantial differences in this behavior between firms. This confirms yet again the idiosyncratic behavior of

Ž .

firms, which has most recently been noted by both Davis and Haltiwanger 1999

Ž .

and Abowd et al. 1999 .

The overall message of these results is that firms in general want some minimum level of worker turnover. They preserve this even when employment is changing quite rapidly and despite the known costs of worker turnover. The reasons why they want this merits further research. It might increase numerical flexibility to have a constant stream of people through an organisation; it might be that some organisations have a particular need for a continual supply of ‘new blood’; for some firms a low payrhigh turnover strategy may simply be the cheapest.

These results substantiate the need for the micro level analysis of employment

Ž .

adjustment pointed out by Hamermesh and Pfann 1996a . The fact that most employers churn, but that there is also a great deal of difference in the levels of

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churning, by age, size, average payroll, and job flow rates, suggests that aggregate analysis is not sufficient to understand the phenomenon. The difference in hiring and firing patterns between countries further suggests that institutional differences in legal penalties may provide part of the answer.

Acknowledgements

We would like to thank two thoughtful referees for their contribution to this paper.

Appendix A. Means and standard deviations of variables

Variable Mean Standard deviation Job flow rate y0.002 0.25

Churning rate 0.25 0.35 Average payroll 5781.15 4146.22

Ž .

Age of employer in quarters 49.21 40.26 Size of employer 43.54 264.85

Ž .

Maryland growth rate index 1.004 0.02

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Burgess, S., Lane, J., Stevens, D., 1996. Job flows and worker flows: issues and evidence from a panel

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contracts. In: Ashenfelter, O., Layard, R. Eds. , Handbook of Labour Economics vol. 2. North-Holland, Amsterdam.

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employer first filed for an identification number. We control for wage setting

practices by including average payroll total employer payroll divided by the

Since we expect employers to differ in the levels of turnover Burgess et al.,

1999 , we allow for employer level fixed effects—we correct for the bias inherent with a lagged dependent variable when using fixed effects by using Nickell’s

Ž_{1981 approximation.}. 12 _{We also reran the regressions separately by industry but}

little difference was found and the results are not reported here.

Ž .

high turnover or high wages. The fixed effect regression reflects the average

We estimate this for employers with more than 20 employees; the results are substantively unchanged when this is reduced to 10 employees.

13 _{Ž .}

We omit size from column 1 as the level of employment would be highly colinear with job flows in a fixed effect regression.

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Table 1

Regression results for CFR

Ž .1 FE Ž .2 OLS Ž .3 25% Ž .4 50% Ž .5 75%

JFR 0.108 0.132 0.054 0.123 0.142

) ) ) ) ) ) ) ) ) )

Ž49.74. Ž35.14. Ž64.03. Ž72.63. Ž58.60.

JFR y0.107 0.056 y0.144 y0.031 0.187

) ) ) ) ) ) ) ) ) )

Ž19.86. Ž5.37. Ž76.24. Ž7.71. Ž32.41.

JFR y0.037 y0.035 0.008 y0.047 y0.037

) ) ) ) ) ) ) ) ) )

Ž9.89. Ž4.49. Ž5.36. Ž16.28. Ž9.15.

JFR 0.089 y0.019 0.104 0.029 y0.106

) ) ) ) ) ) ) )

Ž17.94. Ž1.80. Ž56.81. Ž7.58. Ž19.71.

JFR 0.006 0.006 y0.003 0.009 0.007

) ) ) ) ) ) ) ) ) )

Ž6.28. Ž2.62. Ž8.73. Ž10.66. Ž6.01.

JFR y0.017 0.001 y0.019 y0.006 0.015

) ) ) ) ) ) ) )

Ž16.13. Ž0.45. Ž48.05. Ž7.42. Ž13.49.

Size y0.00056 0.041 0.006 y0.043

) ) ) ) ) )

Ž0.26. Ž51.42. Ž4.30. Ž20.33.

Size y0.00025 y0.005 y0.001 0.004

) ) ) ) ) )

Ž1.34. Ž73.26. Ž4.54. Ž24.14.

Age y0.0030 y0.00039 y0.00006 y0.0002 y0.00064

) ) ) ) ) ) ) ) ) )

Ž85.04. Ž28.88. Ž19.70. Ž34.66. Ž52.21.

Ave. Wage 0.00016 y0.0007 y0.00018 y0.00049 y0.00045

) ) ) ) ) ) ) ) ) )

Ž9.23. Ž33.62. Ž55.26. Ž72.05. Ž57.05.

Ž .

CFR ty1 0.214 0.572 0.417 0.586 0.738

) ) ) ) ) ) ) ) ) )

Ž162.65. Ž84.40. Ž1055.22. Ž773.48. Ž659.31.

MACRO 0.399 0.448 0.116 0.313 0.396

) ) ) ) ) ) ) ) ) )

Ž26.79. Ž23.43. Ž20.00. Ž26.55. Ž23.55.

MFG 0.019 0.000 0.013 0.030

) ) ) ) ) )

Ž8.27. Ž0.71. Ž9.75. Ž15.61.

TCU 0.012 0.001 0.008 0.022

) ) ) ) ) )

Ž8.48. Ž1.04. Ž7.93. Ž14.67.

FIRE 0.070 0.024 0.059 0.087

) ) ) ) ) ) ) )

Ž31.79. Ž51.96. Ž62.22. Ž64.50.

WHL 0.013 0.002 0.010 0.021

) ) ) ) ) ) ) )

Ž7.90. Ž4.01. Ž8.91. Ž12.84.

RET 0.009 y0.001 0.007 0.020

) ) ) ) ) )

Ž6.51. Ž1.26. Ž7.03. Ž13.98.

Prof Ser 0.053 0.005 0.031 0.055

) ) ) ) ) ) ) )

Ž26.28. Ž11.37. Ž32.22. Ž39.87.

Oth Ser y0.044 y0.007 y0.031 y0.057

) ) ) ) ) ) ) )

Ž26.13. Ž9.91. Ž20.11. Ž26.01.

Constant y0.040 y0.313 y0.101 y0.228 y0.220

) ) ) ) ) ) ) ) ) )

Ž2.64. Ž16.33. Ž17.23. Ž19.23. Ž13.00.

R 0.61 0.47 0.1807 0.2589 0.3445

486,866 observations. Robust t-statistics in parentheses)_{significant at 5% level;}) ) _{significant at 1%}

Ž . Ž .

level; column 1 has fixed effects on firm; column 2 has standard errors corrected for firm specific clustering; omitted sector public admin. MACRO is Maryland growth rate.

(3)

(4)

This result is in marked contrast to the behavior of firms in France. Abowd et

Ž . Ž

al. 1999 find that employment adjustments in France for firms with more than

important constraints on their ability to fire workers see OECD, 1999, Annex

2A .

5. Discussion and summary

Ž .

firms, which has most recently been noted by both Davis and Haltiwanger 1999

Ž .

and Abowd et al. 1999 .

These results substantiate the need for the micro level analysis of employment

Ž .

adjustment pointed out by Hamermesh and Pfann 1996a . The fact that most employers churn, but that there is also a great deal of difference in the levels of

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Acknowledgements

We would like to thank two thoughtful referees for their contribution to this paper.

Appendix A. Means and standard deviations of variables

Variable Mean Standard deviation

Job flow rate y0.002 0.25

Churning rate 0.25 0.35

Average payroll 5781.15 4146.22

Ž .

Age of employer in quarters 49.21 40.26

Size of employer 43.54 264.85

Ž .

Maryland growth rate index 1.004 0.02

References

Abowd, J., Corbell, P., Kramarz, F., 1999. The entry and exit of workers and the growth of

Ž .

employment: an analysis of French establishments. Review of Economics and Statistics 81 2 , 170–187.

Albæk, K., Sørensen, B., 1998. Worker flows and job flows in Danish manufacturing, 1980–1991.

Ž .

Economic Journal 108 451 , 1750–1771.

Anderson, P., Meyer, B., 1994. The extent and consequences of job turnover. Brookings Papers on Economic Activity: Microeconomics 2, 495–594.

Burgess, S., Lane, J., Stevens, D., 1996. Job flows and worker flows: issues and evidence from a panel

Ž .

of US firms. In: Schettkatt, R. Ed. , Flow Analysis of Labor Markets: International Perspectives. Routledge, London.

Burgess, S., Lane, J., Stevens, D., 1999. Job flows, worker flows and churning. Journal of Labor

Ž .

Economics 18 3 , 473–502.

Davis, S., Haltiwanger, J., 1990. Gross Job Creation and Destruction: Microeconomics Evidence and Macroeconomics Implications NBER, Macroeconomics Annual 5, pp. 123–168.

Davis, S., Haltiwanger, J., 1994. Measuring Gross Worker and Job Flows Prepared for NBERrCRIW Conference on Labor Statistics Measurement Issues, Washington D.C. December 15-16. .

Ž .

Davis, S., Haltiwanger, J., 1999. Gross job flows. In: Ashenfelter, O., Card, D. Eds. , Handbook of Labor Economics vol. 3. North-Holland, Amsterdam, in press.

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Davis, S., Haltiwanger, J., Schuh, S., 1996. Job Creation and Destruction. Massachusetts Institute of Technology, Cambridge, MA.

Hamermesh, D., Pfann, G., 1996a. Turnover and the dynamics of labour demand. Economica 251, 359–368.

Hamermesh, D., Hassink, W., Van Ours, J., 1996. New facts about factor demand dynamics: employment, jobs and workers. Annales d’Economie et Statistique 41r42, 21–40.

Lane, J., Isaac, A., Stevens, D., 1996a. Firm heterogeneity and worker turnover. Review of Industrial Organization 11, 275–291.

Lane, J., Stevens, D., Burgess, S., 1996b. Worker and job flows. Economics Letters 51, 109–113. Lazear, E., 1996. Personnel Economics. MIT Press, Cambridge, MA.

Nickell, S., 1981. Biases in dynamic models with fixed effects. Econometrica 49, 1417–1426. OECD, 1999. OECD Employment Outlook. OECD, Paris.

Parsons, D., 1986. The employment relationship: job attachment, work effort and the nature of

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contracts. In: Ashenfelter, O., Layard, R. Eds. , Handbook of Labour Economics vol. 2. North-Holland, Amsterdam.

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