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Unformatted text preview: DISCUSSION PAPER SERIES IZA DP No. 570 Technological Change, Organizational Change, and Job Turnover Thomas K. Bauer Stefan Bender September 2002 Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor Technological Change, Organizational Change, and Job Turnover Thomas K. Bauer IZA Bonn and CEPR Stefan Bender IAB, Nrnberg Discussion Paper No. 570 September 2002 IZA P.O. Box 7240 D-53072 Bonn Germany Tel.: +49-228-3894-0 Fax: +49-228-3894-210 Email: iza@iza.org This Discussion Paper is issued within the framework of IZA's research area Mobility and Flexibility of Labor. Any opinions expressed here are those of the author(s) and not those of the institute. Research disseminated by IZA may include views on policy, but the institute itself takes no institutional policy positions. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent, nonprofit limited liability company (Gesellschaft mit beschrnkter Haftung) supported by the Deutsche Post AG. The center is associated with the University of Bonn and offers a stimulating research environment through its research networks, research support, and visitors and doctoral programs. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. The current research program deals with (1) mobility and flexibility of labor, (2) internationalization of labor markets, (3) welfare state and labor market, (4) labor markets in transition countries, (5) the future of labor, (6) evaluation of labor market policies and projects and (7) general labor economics. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available on the IZA website (www.iza.org) or directly from the author. IZA Discussion Paper No. 570 September 2002 ABSTRACT Technological Change, Organizational Change, and Job Turnover* This paper uses a German employer-employee matched panel data set to investigate the effect of organizational and technological changes on gross job and worker flows. The empirical results indicate that organizational change is skill-biased because it reduces predominantly net employment growth rates of unskilled and medium-skilled workers via higher job destruction and separation rates, whereas the employment patterns of skilled workers are not affected significantly. New information technologies do not have significant effects on gross job and worker flows as soon as establishment fixed-effects are controlled for. JEL Classification: Keywords: J63, L23, O33 linked-employer-employee data set, information technology, organizational change, job turnover, worker turnover Corresponding author: Thomas Bauer IZA P.O. Box 7240 53072 Bonn Germany Tel.: +49 228 3894 529 Fax: +49 228 3894 510 Email: bauer@iza.org * Parts of this paper have been written while Stefan Bender was visiting the IZA. We would like to thank David Jaeger, Arnd Klling, Julia Lane, the participants of the New Zealand Conference on th Database Integration and Linked Employer-Employee Data, March 2002, Wellington, the 16 Annual Conference of the European Society for Population Economics (ESPE), June 2002, Bilbao and the 10th International Conference on Panel Data, July 2002, Berlin, as well as seminar participants at the Australian National University and the University of Heidelberg for helpful comments on earlier drafts of the paper. 1. Introduction In the past two decades, most advanced industrialized countries have witnessed an increase in the relative demand for skilled labor, as evidenced by rising earnings inequality in the US and the UK and an increase in the relative unemployment rates of unskilled labor in continental Europe.1 The economic literature focuses on two main phenomena to explain these developments: increased trade with developing countries and skill-biased technological change. More recent literature suggests that changes in the organizational structure of rms, which is characterized by an increasing use of so-called exible or innovative workplace systems or High Performance Work Organizations (HPWOs), might be another important determinant of the observed labor market developments.2 Even though the dissemination of HPWOs varies between countries, industries, and rms, the observed reorganization process appears to be of quantitative importance in almost all industrialized economies.3 Recent empirical studies by Bresnahan, Brynjolfsson and Hitt (1999) for the US, and Caroli and van Reenen (2001) for France and the UK suggest that HPWOs are complementary with skills and hence could add to the explanation of the relative increase in the demand for skilled labor. Based on a standard static labor demand framework, most empirical studies on the wage and employment e ects of technological and organizational change estimate wage or employment share equations for di erent skill groups. In these equations the estimated coe cient of indicators for technological and organizational change is used to test whether new technologies or exible workplace practices are complementary to skills. Many theoretical models, however, view technological and organizational Surveys of the literature are given, among others, by Gottschalk and Smeeding (1997), Katz and Author (1999), Machin and Manning (1999) and Snower (1999). 2 In the literature, there is no consensus on the de nition of HPWOs. Usually, measures such as team work and job rotation, decentralization of decision-making within rms, a reduction in the number of hierarchical levels, the replacement of vertical by horizontal communication channels, the introduction of employee problem-solving groups or quality circles, Total Quality Management (TQM) and a change from task specialization to task diversi cation are subsumed under the term HPWO. 3 Evidence for Europe is given by the European Foundation (1997, 1998). See also Osterman (1994, 2000) for the US, NUTEK (1996, 1999) for the Nordic countries and Gallie et al. (1998) for the UK. Surveys are given by Snower (1999) and OECD (1996, 1999). 1 1 change as a process of creative destruction which involves the reallocation of jobs and workers across and within rms (Aghion and Howitt 1992 Kremer and Maskin, 1996 Mortensen and Pissarides, 1998, 1999a Thesmar and Thoenig, 2000). These models suggest that it is important to analyze the e ects of technological and organizational change in a dynamic framework to obtain a more detailed picture of the adjustment processes associated with these changes. It has very di erent policy implications whether such changes result in an increased destruction of jobs for unskilled workers, a relative decrease in the rate of job creation for unskilled workers or whether jobs that employ the newest technology and exible workplace systems are only created for skilled workers leaving employment of unskilled workers una ected. An analysis of employment shares cannot uncover these di erent processes because it is not able to distinguish di erent patterns of job creation and job destruction. Using a standard dynamic labor demand speci cation by regressing net employment changes on indicators for technological and organizational change, however, might mask important heterogeneity and asymmetry patterns in employment creation and destruction. Mortensen and Pissarides (1998), for example, developed a model in which rms have several options to adjust their workforce when implementing new technologies or new organizational structures.4 In their model, rms have the possibility to update their technology or organization by paying a xed renovation cost. These renovation costs subsume the costs of buying new machines as well as internal adjustment costs, such as the costs to train workers to operate in a new technological and organizational environment. If these renovation costs are lower than the costs of creating a new job, rms will adjust internally, i.e. they will update their existing jobs by training their incumbent workers. If the adoption costs are high relative to the job creation costs, rms will destroy the old jobs and and hire new workers with the necessary skills to work with the new technology and/or the new organizational environment. The model of Mortensen and Pissarides (1998) has important implications for See also the discussion in Mortensen and Pissarides (1999b) and Aghion and Howitt (1999, chapter 4.) 4 2 the empirical investigation of employment adjustment patterns arising from technological and organizational change. First, focusing solely on net employment changes might not provide su cient insights into the adjustment patterns associated with technological and organizational change because these changes might have signi cant e ects on job and worker reallocation without necessarily a ecting net employment. Therefore, it seems to be important to investigate also gross job and worker ows. Second, if rms in an industry or economy rely predominantly on internal adjustment, industry-level studies of net employment changes might erroneously conclude that technological or organizational change is not skill-biased. Since there is no clear relationship between job and worker reallocation across rms on the one hand and technological and organizational change on the other, it is important to take into account ows occurring across di erent skill groups within rms. If rms rely predominantly on external adjustment, technological and organizational change should lead to higher job and worker turnover across rms. If, however, rms rely predominantly on internal adjustment, technological and organizational change should not a ect turnover rates across rms. Hence, if rms rely on internal adjustment, studies of gross job and worker ows at the industry level might come to misleading conclusions regarding the question of whether technological and organizational change is skill-biased. To avoid these problems, one has to rely on rm or establishment data. Using an employer-employee matched panel data set for Germany, this paper aims at analyzing the employment e ects resulting from the introduction of new information technologies and HPWOs. Several issues are addressed. First, we investigate whether technological and organizational changes are skill-biased and whether these changes involve di erent patterns of job creation and destruction for di erent skill groups. By looking only at di erent job ow measures, we might miss important employment adjustment patterns that occur during the process of technological and organizational change. It is possible, for example, that rms replace their incumbent workers without changing the overall employment level and skill-mix. We therefore also analyze worker turnover rates. We focus in particular on the question whether plants that introduced new technologies or HPWOs show higher worker replacement 3 rates than plants that did not change their technological or organizational structure. The paper further contributes to the empirical literature on the relationship between exible workplace systems and establishment outcomes.5 Several studies on this issue nd that HPWOs increase productivity (see for example, Ichniowski et al. 1997, Batt 1999, Appelbaum et al. 2000). Empirical research on the wage e ects of HPWOs suggests that these systems also increase wages, indicating that the relationship between HPWOs and pro tability is ambiguous (Appelbaum et al. 2000, Capelli and Neumark 2001, Bauer and Bender 2002). Focusing solely on wages, however, this literature does not take into account other important components of total labor costs that might also be a ected by HPWOs. It is possible, for example, that exible workplace systems reduce labor turnover. The resulting reduction in hiring and ring costs might compensate for the increasing wage costs and thereby lead to a reduction of total labor costs. This paper contributes to this literature by providing some evidence on the relationship between exible workplace practices and labor turnover. Finally, the paper complements recent work on the relationship between job ows and workers ows using employer-level data.6 This literature is concerned with the question whether rms increase (reduce) employment by increasing (decreasing) hires or by reducing (increasing) separations. Di erent from most other studies in this area, our data set allows us to study gross job and worker ows at the skill level rather than the plant or industry level (but see Abowd, Corbell and Kramarz, 1999). The paper is organized as follows. The next section de nes the di erent job and worker ow measures and describes our empirical approach. Section 3 provides a detailed description of the data set. A descriptive analysis of gross job and worker ows resulting from technological and organizational change is given in Section 4. Section 5 presents the e ects of organizational change on worker turnover in a mulA recent survey of the literature is given by Capelli and Newark (2001). See Burgess, Lane and Stevens (2000,2001), Davis, Haltiwanger and Schuh (1996) and Anderson and Meyer (1994) for the US, Hamermesh, Hassink and van Ours (1996) for the Netherlands, Abowd, Corbell and Kramarz (1999) for France, and Alb k and S rensen (1998) for Denmark. A survey is given by Davis and Haltiwanger (1999). 5 6 4 tivariate setting comparing cross-section results to xed e ects estimates. Section 6 summarizes our analysis. 2. Empirical Approach 2.1. Gross Job and Worker Flows: De nitions We closely follow the existing literature by de ning gross job and worker ows (Burgess, Lane and Stevens, 2000 Davis and Haltiwanger, 1999 and Hamermesh, Hassink and van Ours, 1996). Our de nition of a job, however, departs from the standard de nition in the literature. Usually, a job is de ned as a relationship between a worker and a rm or simply a match. Changes in the number of such matches are viewed as job ows. This de nition, however, would not allow us to capture job reallocation between di erent skill groups within an establishment in an appropriate way. Technological and organizational change might lead rms to recon gure the skill-mix of the workers in the rm keeping the total number of jobs constant, by replacing jobs of one skill-type with jobs of another skill type. Based on the standard de nition of jobs, these changes would be labeled as replacement or churning ows. To be able to study the reallocation of jobs and workers between di erent skill groups within a plant, we de ne a job as a set of skills that the employer recognizes as being attached to an employment position. Using this de nition, the change of a worker from one skill type to another within a rm through training, for example, is considered as a job ow. Note, by taking within-establishment ows of jobs and workers between di erent skill groups into account, the measures of job and worker ows reported below should be higher and the calculated churning ows lower than those we would have obtained by using the standard de nition of jobs. Job ows are de ned as the change in employment of skill group i in establishment e at time t ( E ), which equals the di erence in hirings (H ) and separations (S ), i.e. JF = E H ; S , where E = E ; E ;1 . In the empirical analysis we di erentiate between three skill-groups based on the occupation of an iet iet iet iet iet iet iet iet iet iet 5 individual as it has been speci ed by the employer. A more detailed description of these skill-groups is given in the next section. The level of job reallocation is the absolute value of the corresponding job ows, JR = jJF j job creation is a positive job ow, JC = JF if JF 0 and 0 otherwise job destruction is a negative job ow, JD = jJF j if JF < 0 and 0 otherwise. Worker ows, WF , equal the sum of total hires and total separations, which occurred between t ; 1 and t. Following Davis and Haltiwanger (1999), the corresponding rates (JFR , JRR , JDR , JCR , HR , SR , WFR ) are obtained by dividing the levels with the average of current and past employment, i.e. Z = (E + E ;1)=2. Denoting the plant-level average of current and past employment as Z = (E + E ;1 )=2 and de ning the employment shares of the di erent skill groups as ES = Z =Z , the plant-level job ow, creation, destruction and reallocation rates can be written as the sum of the skill-level rates weighted by the respective employment shares, i.e. iet iet iet iet iet iet iet iet iet iet iet iet iet iet iet iet iet iet iet et et et iet iet et JFR = et P i ES JFR iet iet (1) iet JCR JRR e t = = = P i J Fiet 0 ES iet JFR (2) (3) (4) JDR P i J Fiet < e t 0 ES iet iet jJFR j iet iet P i e t ES jJFR j: Based on these measures, we investigate whether technological and organizational changes results in employment changes at di erent margins, i.e. whether they are associated with di erent job creation or job destruction patterns. They enable us, for example, not only to investigate whether technological and organizational change is skill-biased, but also whether relative employment changes mainly occur through the destruction of jobs for low-skilled workers or mainly through the creation of jobs for high-skilled workers. A nal question we address in this paper is the issue of worker reallocation. Imagine a rm that introduces a new machine. In this case, it is possible that the rm res ve incumbent skilled workers that do not have the skills to work 6 with the new machine and hires ve new workers with appropriate skills without changing the employment of the other skill groups. Then, net employment change and hence measured establishment job ows would be zero for all skill groups, if one relies only on the concepts de ned above. Worker ows can be written as the sum of worker ows due to changes in the employment size of a particular skill group in the establishment and worker ows due to replacements of existing jobs, i.e. WF = JR + C , where C is often called excess worker ows or churning (Burgess, Lane and Stevens, 2000, 2001 Hamermesh, Hassink and van Ours, 1996). The churning rate, CR , which is obtained by dividing C by Z , gives an indication of the worker ows in excess of the job ows which are necessary to accomplish an establishment's desired growth or decline in the employment of a particular skill group. Churning ows describe the sum of hirings and separations which are due to the replacement of workers who quit and workers who have been red by the employer. Assuming that there are no vacancies, replacement hirings equal replacement separations in equilibrium. Based on this assumption, some authors use replacement rates, RR , which in equilibrium equal half of the churning rate (see, for example, Alb k and S rensen, 1998). iet iet iet iet iet iet iet iet 2.2. Econometric Speci cation To assess the e ects of technological and organizational change on job and worker ows, we specify the following model, which is estimated on the plant-level e separately for three skill categories i: Y = iet 0X et + 0Z + 0I + et et iet : (5) We further estimate equation (5) for all workers in an establishment. As dependent variables we consider the measures for gross job and worker ow rates described above, i.e. JFR , JDR , JCR , HR , SR , and CR . The vectors I and Z consists of variables describing the introduction of new information technologies and exible workplace practices at establishment e, respectively. These variables will be described in more detail in the next section. As iet iet iet iet iet iet et et 7 already discussed above, it is not entirely clear how organizational and technological changes a ect the di erent measures of gross job and worker turnover. If organizational and technological change are skill-biased, one would expect a relative increase in the employment of skilled workers. This relative employment increase could be achieved through various channels. For example, technological change might increase job creation for skilled workers and professionals and engineers if compared to non-quali ed workers and increase relative job destruction for the latter. Alternatively, however, technological change might only a ect job creation rates of skilled workers, leaving unskilled workers una ected. New information technologies could also be mainly a substitute for non-quali ed labor, increasing job destruction rates for unskilled labor without necessarily a ecting job creation and destruction rates of skilled workers. Similar arguments can be put forward for the e ects of organizational change. It has often been argued that innovative work systems raise skill demands, since workers employed in rms relying on HPWOs need to be willing to acquire new skills, to perform multiple tasks, and to care about quality and productivity. Skilled workers are more able to better able to communicate information, they have a relative advantage in multi-tasking, and the costs of training them is lower compared to unskilled workers. Hence, the returns to innovative work practices could be expected to be higher when the skill level of the workforce in an establishment is higher (Caroli and van Reenen, 2001). Similar to the case of a skill-biased technological change, one would expect a relative increase in the employment of skilled workers and professionals and engineers. It is unclear, however, how HPWOs a ect the di erent gross job and worker ow rates for di erent skill groups. The vector X captures other variables that might a ect gross job and worker ows. This vector includes the log of total employment in establishment e, the employment share of unskilled and skilled workers, the employment share of females, foreigners, and part-time workers, and the median age of the employees. In addition, we consider two dummy variables indicating whether the revenues of an establishment increased or decreased during the last year as well as two dummy variables et 8 indicating whether the establishment expects rising or falling revenues in the next year. We further include a variable indicating whether a rm uses state-of-theart production technology, the share of exports on total revenues in the last year, eight industry and seven regional dummies. A detailed description of the variables together with descriptive statistics is given in Appendix Table 1. Several econometric problems arise when estimating equation (5). First, Z and I are likely to be endogenous (Caroli and van Reenen, 2001 Athey and Stern, 1998). A positive demand shock, for example, might enable rms to increase the number of skilled workers, to invest in new technologies, and to experiment with innovative workplace systems. To circumvent this problem, we use lagged values of organizational change when estimating equation (5), i.e. we consider gross job and worker ow rates in the period from 1995 to 1996 and regress these on organizational and technological changes between 1993 and 1995. Second, even though our data set allows us to control for many characteristics of an establishment and the structure of its workforce, estimates of and based on equation (5) might still su er from omitted variable bias due to unobserved establishment characteristics. To address this problem, we eliminate all observed and unobserved time-invariant establishment xed-e ects by taking rst di erences. In particular, we report estimates of the form et et Y ;Y iet iet ;2 = 0 (X ; X ;2 ) + 0 Z ;1 + 0 I ;1 + et et et et iet (6) where t ; 2 refers to a period before organizational and technological changes are observed, i.e., the period from 1992 to 1993. Finally, our dependent variables are truncated. The job ow rates, JFR , vary between -2 and 2 all other job and worker ow rates between 0 and 2. To take the limited range of our dependent variables into account, we estimated equation (5) using a Tobit model with the respective restrictions. Note that this problem disappeared after taking rst di erences. Therefore, we estimated equation (6) using OLS. iet 9 3. Data The following analysis of the e ects of technological and organizational change on labor turnover is based on a German employer-employee linked data set that was constructed through the combination of the IAB Establishment Panel and the Employment Statistics Register. The IAB Establishment Panel is an annual representative survey of establishments employing at least one employee who pays social security contributions.7 Starting in 1993, the survey was administered through personal interviews. The second data source, the Employment Statistics Register, is an administrative panel data set of individuals based on the integrated notifying procedure for the German health insurance, statutory pension scheme, and unemployment insurance.8 Both data sets contain a unique rm identi cation number, which allows us to merge the information on employees provided by the Employment Statistics Register with the information in the IAB Establishment Panel. Matching of the data sets occurred in two steps. First, we selected West German rms who participated in the establishment panel between 1993 and 1996, resulting in a sample of 2,579 establishments. In a second step, we used the Employment Statistics Register to merge with our sample of establishments the work history information for all employed persons who worked for at least one day in at least one year from 1992 to 1996 in one of the selected establishments. The individual information has been extracted for every 30th of June, the day of reference for the IAB-establishment panel. In our analysis, we di erentiate three skill groups: unskilled worker (u), skilled worker (s), and professionals and engineers (h). Our classi cation of individuals into these three skill-groups follows a scheme proposed by Blossfeld (1995), which See Bellmann, Kohaut and Kuhl (1994), Bellmann (1997) and Kolling (2000) for a detailed description of the IAB-Establishment Panel. 8 Since 1973, employers are obliged to provide information to the social security agencies for those employees registered by the social security system. Employers have to notify the social security agencies about the beginning and ending of any employment relationship. In addition, they have to provide an annual report for each employee covered by social insurance who is employed on the 31st December of each year. This report includes information on the sex, year of birth, nationality, marital status, number of children, occupation, and quali cation of the employee. See Bender et al. (1996) and Bender, Haas and Klose (2000) for a detailed description of the data set and the notifying procedure. 7 10 is based on the 3-digit occupation of an individual as it was speci ed by the employers in the noti cation to the social security agencies. Following this scheme, all blue-collar workers who are classi ed by the employer into an occupation which is characterized by simple manual tasks and white-collar workers performing simple services are considered to be unskilled blue-collar workers who practice an occupation which involves complicated tasks, white-collar workers performing quali ed tasks, as well as semi-professionals are considered to be skilled workers. The third group consists of engineers, technicians, professionals and managers. Note that the resulting classi cation of individuals into the three skill-groups based on their occupation is highly correlated with their completed occupational education.9 We excluded apprentices, trainees, persons who are temporarily out of the labor force due to child bearing or military service, part-time workers, and individuals older than 65 from our individual sample. Using the rm identi er, the two data sets were matched to a linked employer-employee data set, providing detailed information on the characteristics of all employees in an establishment who are covered by the social security system. Excluding all establishments in the agricultural, mining and non-pro t sector, those with missing values for the variables used in the empirical analysis and all establishments that do not employ a single worker in any of the three skill groups in the whole period from 1992 to 1996, a total of 1,305 observations remained for the empirical analysis.10 The di erent measures for gross job and worker ows described above were constructed in the following way. Inter- rm mobility is measured as a change of an individual's rm identi er between two consecutive years. Movements into and out of unemployment or the labor force occur if a person has a gap between two years, which means that the individual is not employed on the 30th of June of a particular year, or if the person does not have a noti cation at the beginning (1992) or the 9 About 50% of the individuals classi ed as being unskilled have no occupational education and another 50% received apprenticeship training. Less than 0.5% of the unskilled workers hold a university degree. Among those classi ed as being quali ed, only 17% do not have any occupational education, 80% have at least received apprenticeship training, and about 3% hold a university degree. Finally, among professionals and engineers, about 30% hold a university degree, another 65% have at least apprenticeship training, and only about 5% do not have any occupational training. 10 Restricting the analysis to rms with at least one worker in one of the three skill groups reduces our initial sample by about 900 observations. 11 end (1996) of our observation window. In ows and out ows of workers for every establishment are obtained by counting inter- rm mobility and movements into and out of unemployment or the labor force for every year and skill group. Intra- rm mobility is de ned as a change in the skill classi cation of an individual that does not change the rm identi er. In 1995, establishments participating in the IAB-establishment panel were asked the following questions: \Have there been any of the following organizational changes in your establishment over the last 2 years?" From the possible answers, we created dummy variables indicating whether an establishment (i) reduced the number of hierarchy levels, (ii) transferred responsibilities to subordinates, and (iii) introduced team-work or self-responsible working groups. Note that that these changes cover three out of four practices that were identi ed by Betcherman (1997) and OECD (1999) as main characteristics of exible workplace systems.11 The work of Milgrom and Roberts (1990, 1995) indicates that only the introduction of a cluster of new practices allows rms to reach a new optimal organization. If practices are introduced in clusters, the above-described indicators of organizational change should be highly correlated with each other, making it di cult to identify the separate e ects of these indicators. We therefore applied a principal component analysis to the three dummy variables described above to derive an index of decentralization.12 Table 1 summarizes the extent of organizational change in our sample. Between 1993 and 1995, about 27% of all establishments reduced the number of hierarchy levels, 42% transferred responsibilities to lower hierarchy levels, and about 31% introduced self-managed teams. Table 1 further shows that these changes are relatively more common in the manufacturing sector, which is in line with the experience of organizational changes in other countries (OECD, 1999).13 The fourth characteristic is a job design that involves multi-tasking. The rst principal component accounted for 57% of the variance and had an eigenvalue of 1.720. The second and third principal component have eigenvalues below 1, supporting the aggregation of the information on organizational change into one common factor. The scoring coe cients used for the calculation of the decentralization index are 0.439 for the reduction of hierarchy levels, 0.464 for the delegation of responsibilities, and 0.416 for the introduction of team work. 13 Since our variables on organizational change are based on retrospective questions, one might be concerned that these variables su er from measurement error. One of the most serious problems with this kind of questions is \forward telescoping", i.e., respondents report events that occurred 11 12 12 Between 1993 and 1995, the IAB Establishment Panel contains detailed information on the type of investments in the last year. We employ this information to create two dummy variables that proxy a technological change between 1993 and 1995. The rst dummy variable indicates whether an establishment reported any investments in communication and information technologies either between 1993 and 1994 or between 1994 and 1995. The second variable indicates whether these investments have been the single biggest investment of the establishment in the respective year. According to Table 1, more than 81% of the establishments report investments in IT in 1993 or 1994. Nearly 27% of the establishments indicated that their IT investments were the single biggest investment. Even though the share of establishment with IT investments is slightly higher in the manufacturing sector if compared to the non-manufacturing sector, a higher share of the latter report that these investments have been the single biggest investment. 4. Descriptive Analysis 4.1. Gross Job and Worker Flows in Germany Table 2 reports job and worker ow rates between 1995 and 1996 for establishments with increasing and decreasing total employment as well as establishment without any employment change. The measures are given for all workers as well as for the three skill groups. In parentheses we further report the job and worker ow measures for the di erent skill groups divided by the average total employment of the establishment between 1995 and 1996, which show the contribution of the respective skill-level job and worker ows on the establishment-level job and worker ows (see equations (1)-(4)). The majority of rms in our sample (63%) show negative employment growth rates. Furthermore, the job ow rates in establishments with decreasing employment outside of the time under consideration, resulting in over-reporting. Note that the questions on organizational change in the IAB-establishment panel followed a two-step bounded recall procedure, which can e ectively reduce over-reporting in retrospective questions (see, for example, Brennan et al., 1996). A more detailed discussion of this problem is given by Bauer and Bender (2002). 13 are higher in absolute terms than the respective job ow rates in establishments with increasing employment, indicating that the overall employment level decreased. These numbers re ect that the German economy experienced a downturn in this period. Between 1995 and 1996, overall employment in West Germany decreased by almost 1.3%, and the unemployment rate increased from 8.2% to 8.3%. Establishments with increasing employment during the period 1995-1996 created on average 7.5 jobs establishments with decreasing employment destroyed on average 12 jobs per 100 workers. Growing rms hired on average 20 workers and separated from 12 workers, indicating that the creation of one job involves hiring three workers and separating from two workers. Establishments with decreasing employment hired on average one worker and separated from two workers for every job destroyed. Note that these numbers are similar to those reported by Abowd, Corbel and Kramarz (1999) for France. The comparison of hiring and separation rates between establishments with positive and negative employment growth rates shows that the di erences in the separation rates between these two types of establishments are smaller than the corresponding di erences in the hiring rates. This nding resembles those in other countries (Abowd, Corbel and Kramarz, 1999 Alb k and S rensen, 1998) and indicates that a reduction of employment is achieved mainly by reducing hirings rather than increasing separations. Compared to skilled workers and professionals and engineers, the di erence between the separation rates of establishments with increasing and those with decreasing employment is higher for unskilled workers, whereas the di erences in hiring rates are roughly similar across the three skill groups, indicating that employment adjustment predominantly occurs through adjusting the employment of unskilled workers. This conclusion is con rmed when comparing the respective shares of the three skill groups on the total, establishment-level job ow rates, which could be obtained by dividing the numbers reported in parentheses by the respective job ow rates for all workers. In rms with increasing employment, the average share of unskilled workers on the total establishment-level job ow is about 37%, which is smaller than their respective average employment share of 40%. About 42% of an 14 employment decrease is obtained by decreasing the employment of unskilled workers, even though the employment of unskilled workers in shrinking establishments constitutes on average only about 40% of total employment. Table 2 further shows high churning rates for all groups considered, indicating an enormous amount of worker reallocation in excess of the amount which would be necessary to accomplish an establishment's desired change in employment. Churning ows constitute between 48% and 70% of all worker ows (the sum of hiring and separation ows). They are higher in establishments with positive if compared to establishments with negative net employment growth. Worker replacement is relatively more important for unskilled and skilled workers than for professionals and engineers, especially in rms with growing employment. The latter might re ect relatively high turnover costs for professionals and engineers, which in turn gives rms an incentive to put relatively more e ort into matching/hiring this group of workers with the consequence of lower churning rates (Burgess, Lane and Stevens, 2000, 2001). 4.2. Organizational Change, Technological Change, and Labor Turnover Table 3 shows the job and worker ow rates for all rms and for the subset of rms that either introduced one of the exible workplace systems we consider or reported main investments in IT. On average, establishments in our sample decreased employment by 5.0%, re ecting again the overall development in the German labor market. This employment decrease is largely driven by unskilled workers, who experienced an employment decrease of about 6.6%, and professionals and engineers, who experienced an employment decrease of about 6.7%. Di erent from these two skill groups, the employment of skilled workers decreased only by 3.7%. Note that almost 46% of the overall decrease in employment was obtained by reducing the employment of unskilled workers, even though they constituted only 40% of total employment in 1995. Overall, establishments in our sample destroyed three jobs for every job created. For every job created, three jobs were destroyed for unskilled 15 workers, two for skilled workers, and 2.5 for professionals and engineers. Comparing the sub-samples of rms that experienced an organizational or technological change reveals some interesting patterns. The overall decrease in net employment between 1995 and 1996 is almost three percentage points higher in establishments that reduced the number of hierarchy levels if compared to the average establishment. The ratios of job destruction to job creation rates in establishments that attened their hierarchy structure are 5.86 for unskilled workers, 3.98 for skilled workers and 2.63 for professionals and engineers. These numbers suggests that the reduction of hierarchy levels is skill-biased in the sense that the di erence in the job destruction to job creation ratio between rms that reduced their hierarchy level and the average rm is lower for professionals and engineers than that for unskilled and skilled workers. This conclusion can also be obtained by calculating the shares of the job ows of the di erent skill groups on the establishment-level job ow rate. Professionals and engineers contribute only 18% and skilled workers an additional 33% to the overall employment reduction of 7.8%, even though they constitute on average 20% and 38% of total employment in these establishments, respectively. The decrease in employment of unskilled workers, which represent 42% of the workers in these establishments, explains about 49% of the overall employment decrease. Establishments that reduced the number of hierarchy levels show higher separation and lower hiring rates if compared to those of the average establishment, especially for unskilled and skilled workers. Note further that the relative increase in the separation rates and the respective decrease in the hiring rates are very similar for these two groups. Hence, there is almost no di erence between the total worker ow rates (the sum of hiring and separation rates) to the average rm for unskilled and skilled workers. The churning rates among establishments that reduced the number of hierarchy levels are also not very di erent to those of the average establishment. To summarize, a reduction in the number of hierarchy levels appears to be skill-biased in the sense that it reduces the relative employment of unskilled and skilled workers. The reduction in the employment shares of unskilled and skilled workers is achieved mainly through higher job destruction. Assuming that the skill 16 level of workers is positively correlated with their position in the hierarchy level, these results suggest that a reduction in the number of hierarchy levels is achieved mainly by employees in higher hierarchy levels taking over tasks from lower levels. A slightly di erent picture emerges for rms that transferred responsibilities to lower hierarchy levels. Again, these rms experienced higher negative employment growth rates if compared to the average rms. The employment reduction in these rms, however, is smaller than in rms that reduced the number of hierarchy levels. Di erent than the reduction of hierarchy levels, the transfer of responsibilities seems not to be skill-biased - it seems to be rather bene cial for skilled workers, whereas professionals and engineers su er from this change. The latter contribute more than 28% to the overall employment decrease in these rms, even though they represent only 21% of total employment in these rms. The reduction of the employment of unskilled workers in rms that transferred responsibilities is similar to their employment share in 1995, and skilled workers contribute to less to the overall employment reduction than their employment share in 1995. Again, the di erences of the employment development in rms that transferred responsibilities and the average rm can mainly be explained by di erences in job destruction and separation rates. Di erent than the other two practices, the employment decrease in rms that introduced self-managed teams is lower than in the average rm. The introduction of self-managed teams has similar e ects to a transfer of responsibilities in the sense that only skilled workers bene t from this practice. Whereas the job creation and hiring rates are not very di erent to the average rm, job destruction and separation rates are considerably lower, resulting also in lower worker ow rates. These di erences may re ect that the functioning of self-managed teams is in particular dependent on a substantial commitment of employees to their enterprise (Ostermann, 2000). According to Table 3, a technological change leads to relatively lower employment growth rates for unskilled workers and professionals and engineers and to relatively higher employment growth rates for skilled workers if compared to the average rm. This relative employment development manifests itself in considerably higher job 17 destruction rates for unskilled workers and the most skilled. Main investments in IT increase the (JDR/JCR)-ratio for unskilled workers and professionals and engineers and decrease the respective ratio for skilled workers. Hence, technological change appears not to be skill-biased. Di erent than the patterns observed for organizational changes, however, establishments that invest in IT increase both hiring and ring rates. Consequently, churning rates are also higher in these establishments compared to the average establishment. These patterns indicate that a technological change does not only result in a reduction of the relative employment of unskilled and highly skilled labor, but is also associated with a substantial replacement of incumbent workers. 5. Estimation Results In this section we want to explore whether the results of the descriptive analysis remain the same after controlling for observed characteristics of the establishment. Table 4 presents the estimated coe cients for di erent indicators of organizational and technological change as well as the main and interactive e ects of investments in IT and main investments in IT, which we obtained by estimating equation (5) using a Tobit model.14 The estimation results for the e ects of introducing HPWOs on job ows largely con rm the results from the descriptive analysis of the last section. Panel A of Table 4 shows that net employment growth rates are about 2.6% lower in establishments that reduced their number of hierarchy levels if compared to rms that did not change their hierarchical structure. Reducing the number of hierarchy levels does not a ect job creation and hiring rates but has signi cant positive e ects on job destruction and separations rates. The estimated marginal e ects (not reported here) imply that the reduction of hierarchy levels increases the probability of job destruction by 7.5% and, conditional on destroying jobs, increases the de14 A full set of all estimation results is available upon request. 18 struction rate by 1.7%. Similar to the reduction of the number of hierarchy levels, a transfer of responsibilities between 1993 and 1995 reduces net employment growth rates between 1995 and 1996, whereas the introduction of self-managed teams results in signi cantly higher growth rates. These e ects can mainly be attributed to the signi cant positive e ect of a transfer of responsibilities on the separation rate and the signi cant negative e ects of the introduction of self-managed teams on both job destruction and separation rates. Investments in IT appear to increase net employment growth rates through lower separation rates. The estimated main and interactive e ects show, however, that these e ects disappear as soon as these investments constitute the single biggest investment. Panels B - D of Table 4 show the estimation results for the three di erent skill groups. A reduction in the number of hierarchy levels decreases net employment growth rates for unskilled and skilled workers, even though the e ect for the former is statistically signi cant only at the 10%-level. The job destruction and separation rates of both groups increase signi cantly through this change. Even though job destruction and separation rates of professionals and engineers are also positively a ected by a reduction of hierarchy levels, their net employment growth rate does not seem to change signi cantly. The delegation of decision rights has a signi cant e ect on net employment growth of skilled workers only. Di erent from the descriptive analysis above, however, the transfer of responsibilities leads to signi cantly lower net employment growth rates and signi cantly higher job destruction and separation rates for skilled workers when establishment characteristics are controlled for. The introduction of self-managed teams has signi cantly positive e ects on the employment growth rates of unskilled and skilled workers. For both groups, this e ect could mainly be explained by the negative impact of teams on job destruction and separation rates. Investments in IT show positive e ects on the job ow rates of skilled and unskilled workers. If these investments constitute the biggest single investment in the period from 1993 and 1995, however, this positive e ect disappears for skilled workers and becomes signi cantly negative for unskilled workers. These results indicate that new information technologies are skill-biased in the sense that 19 a main change in the use of these technologies decreases the employment share of unskilled workers. Note, nally, that professionals and engineers have signi cantly higher churning rates in rms that reported main investment in IT. Table 5 shows the estimation results when using the index of decentralization, obtained through a principal component analysis, as indicator of organizational change rather than dummy variables for each practice. Recall that this index increases with an increasing decentralization of the organizational structure between 1993 and 1995. The results con rm those reported in Table 4. The index shows signi cant negative e ects on the total employment growth rate as well as on the employment growth rate of skilled workers. These lower employment growth rates are mainly driven by a signi cantly higher job destruction and separation rate in both cases. A higher decentralization also increases the job destruction and separation rates for professionals and engineers. Their job ow rate, however, is not signi cantly a ected by the index. The index does not have signi cant e ects on the job ow rate of unskilled workers. However, it signi cantly decreases the job creation rate and increases the job destruction rate of this group of workers. Tables 6 and 7 reports the results when removing all observed and unobserved time-invariant establishment xed e ects by taking rst di erences using information form the period from 1992 to 1993. In most cases, the e ects of organizational and technological change are estimated less precisely. The overall picture, however, does not change when taking xed establishment e ects into account. In particular, skilled workers are negatively a ected by organizational changes through higher job destruction and separation rates. When using our index for the degree of decentralization, unskilled workers appear to be a ected negatively by organizational change as well. This negative e ect could again be mainly explained with higher job destruction and separation rates. Di erent to the results reported in Tables 4 and 5, however, the introduction of self-managed teams and the index of decentralization have a signi cant positive e ect on the churning rates in the speci cation for all workers as well as for unskilled workers. After controlling for establishment xed-e ects, main investments in IT have only signi cant e ects on the churning 20 rates for professionals and engineers. 6. Summary Using a linked employer-employee panel data set for Germany, this paper analyzes the e ects of technological and organizational changes on gross job and worker ows. Investigating gross job and worker ows in addition to net employment changes provides important insights into the speci c employment adjustment processes associated with technological and organizational changes. Our empirical results indicate that rms that introduce high performance work practices show signi cantly lower net employment growth rates. We nd some support for skill-biased organizational change. Establishments that changed their organizational structure have significantly lower net employment growth rates for unskilled and particularly skilled workers. These negative employment e ects can be explained mainly with a relative increase in job destruction and separation rates. Employment patterns of professionals and engineers, however, are not a ected signi cantly by organizational changes. After controlling for establishment xed-e ects, our indicators for technological change do not a ect gross job and worker ows signi cantly. If anything, new information technologies seem to increase churning rates among professionals and engineers. This result, however, might be explained by our vague indicator for technological change. 21 References Abowd, J., P. Corbell, and F. Kramarz (1999): \The Entry and Exit of Workers and the Growth of Employment: An Analysis of French Establishments," Review of Economics and Statistics, 81(2), 170-187. Aghion, Philippe, and P. Howitt (1992): \A Model of Growth through Creative Destruction,"Econometrica, 60, 323-351. Aghion, Philippe, and P. Howitt (1999): Endogenous Growth Theory, Cambridge, MA: MIT Press. Alb k, K., and B. S rensen (1998): \Worker Flows and Job Flows in Danish Manufacturing," Economic Journal, 108, 1750-1771. Anderson, P. and B. 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Thoenig (2000): \Creative Destruction and Firm Organization Choice" Quarterly Journal of Economics, 115(4), 1201-1237. 24 Table 1: Technological and Organizational Change, 1993-1995 (in %) All Establishments Manufacturing Non-Manufacturing Reduction of Hierarchy Levels Transfer of Responsibilities Introduction of Self-Managed Team Investments in IT Main Investments in IT Observations 27.20 41.92 30.65 81.38 26.82 1,305 37.37 46.94 39.46 82.36 19.13 669 16.51 36.64 21.38 80.35 34.91 636 25 Table 2: Mean Job and Worker Flows per 100 Workers by Employment Growth Categories, 1995-1996 JFiet Zet JFR JCiet Zet JCR JDiet Zet JDR Hiet Zet HR Siet Zet SR Ciet Zet CR ES in 1995 Firms with increasing employment (N=421): All Workers 7.567 7.567 Unskilled Workers 5.775 8.306 ( 2.805) ( 3.129) Skilled Workers 6.850 8.466 ( 3.204) ( 3.558) Professionals and Engineers 3.918 8.584 ( 1.558) ( 1.868) Firms with decreasing employment (N=824): All Workers -11.861 Unskilled Workers -12.957 0.955 ( -5.040) (0.180) Skilled Workers -9.496 1.189 ( -3.750) (0.297) Professionals and Engineers -12.272 2.396 ( -3.071) (0.219) Firms with stable employment (N=60): All Workers Unskilled Workers -5.448 (-0.693) Skilled Workers 1.474 ( 1.008) Professionals and Engineers -5.128 (-0.315) 2.530 (0.324) 1.617 (0.354) 4.666 (0.309) 11.861 13.912 ( 5.220) 10.685 ( 4.047) 14.668 ( 3.291) 20.075 19.767 ( 8.046) 18.784 ( 8.060) 17.054 ( 3.969) 9.888 9.056 ( 3.396) 10.595 ( 3.710) 10.492 ( 2.783) 12.508 13.992 ( 5.241) 11.934 ( 4.856) 13.136 ( 2.410) 21.749 22.013 ( 8.436) 20.090 ( 7.460) 22.764 ( 5.854) 23.040 22.923 0.397 ( 9.834) 20.635 0.408 ( 9.004) 16.940 0.195 ( 4.202) 18.384 16.202 0.402 ( 6.431) 18.810 0.369 ( 6.827) 16.192 0.229 ( 5.127) 19.349 17.668 0.391 ( 8.001) 18.655 0.398 ( 7.579) 9.875 0.211 ( 3.770) 11.972 11.972 2.279 7.727 11.113 16.561 (0.459) ( 1.152) ( 4.459) ( 5.152) 4.057 2.583 13.385 11.910 (1.351) ( 0.343) ( 5.140) ( 4.133) 3.777 8.905 8.715 13.843 (0.487) ( 0.802) ( 2.372) ( 2.687) Notes: Observations: 1,305. JFR: Job ow rate JCR: Job creation rate JDR: Job destruction rate HR: Hiring rate SR: Separation rate CR: Churning rate ES: Employment share. 26 Table 3: Mean Job and Worker Flows per 100 Workers by skill group and Organizational and Technological Change, 1995-1996 JFiet Zet JFR JCiet Zet JCR JDiet Zet JDR Hiet Zet HR Siet Zet SR Ciet Zet CR ES in 1995 All rms (N=1,305): All Workers Unskilled Workers Skilled Workers Professionals and Engineers -5.048 2.441 7.489 13.270 -6.569 3.387 9.956 12.606 (-2.309) (1.144) ( 3.454) ( 4.945) -3.718 3.669 7.387 13.365 (-1.288) (1.397) ( 2.685) ( 5.179) -6.721 4.456 11.176 12.527 (-1.451) (0.763) ( 2.214) ( 3.146) 11.631 10.718 ( 4.433) 11.869 ( 4.531) 12.421 ( 2.667) 13.005 12.112 ( 4.874) 13.607 ( 5.042) 12.628 ( 3.090) 12.258 11.312 ( 4.864) 12.974 ( 4.760) 12.401 ( 2.634) 14.467 12.805 ( 4.002) 14.571 ( 6.521) 13.378 ( 3.944) 18.318 19.175 ( 7.254) 17.083 ( 6.467) 19.248 ( 4.597) 19.403 20.983 ( 8.251) 19.075 ( 7.119) 20.081 ( 4.033) 19.804 20.212 ( 7.655) 19.246 ( 7.138) 20.318 ( 5.011) 16.928 16.893 ( 7.146) 15.800 ( 5.846) 16.848 ( 3.936) 19.985 22.641 ( 6.218) 18.281 ( 7.902) 22.267 ( 5.865) 19.931 18.438 0.400 ( 7.601) 19.392 0.383 ( 7.564) 16.143 0.217 ( 4.766) 18.061 17.207 0.425 ( 7.214) 18.903 0.375 ( 7.293) 15.480 0.200 ( 3.554) 19.821 18.214 0.408 ( 7.564) 20.356 0.372 ( 7.617) 16.801 0.220 ( 4.640) 19.493 18.254 0.428 ( 7.977) 19.796 0.365 ( 7.289) 16.705 0.207 ( 4.227) 21.709 19.392 0.305 ( 6.460) 20.614 0.438 ( 9.174) 17.554 0.257 ( 6.075) Firms that reduced number of hierarchy levels (N=355): All Workers -7.772 1.891 9.663 Unskilled Workers -10.265 2.114 12.380 ( -3.818)(0.826) ( 4.644) Skilled Workers -7.206 2.417 9.624 ( -2.589)(0.884) ( 3.473) Professionals and Engineers -7.661 4.681 12.341 ( -1.365)(0.890) ( 2.256) Firms that transferred responsibilities (N=547): All Workers -6.799 2.200 Unskilled Workers -8.100 3.005 (-2.781) (1.092) Skilled Workers -5.639 3.429 (-2.096) (1.234) Professionals and Engineers -7.689 4.228 (-1.922) (0.770) 8.999 11.105 ( 3.873) 9.067 ( 3.330) 11.917 ( 2.691) Firms that introduced self-managed teams (N=400): All Workers -4.670 1.807 6.477 Unskilled Workers -5.581 2.185 7.766 (-2.281) (0.876) ( 3.157) Skilled Workers -2.826 3.076 5.901 (-1.086) (1.115) ( 2.201) Professionals and Engineers -4.448 4.048 8.496 (-1.302) (0.520) ( 1.823) Firms with main investments in IT (N=350): All Workers -5.518 2.620 Unskilled Workers -9.836 3.109 (-2.215)( 0.773) Skilled Workers -3.711 4.264 (-1.382)( 1.933) Professionals and Engineers -8.890 4.601 (-1.921)( 0.906) Notes: See notes to Table 2. 8.138 12.945 ( 2.988) 7.974 ( 3.315) 13.490 ( 2.827) 27 Table 4: Organizational Change, Technological Change and Job and Worker Turnover: Tobit Estimations JFR Panel A: All Workers: Reduction of Hierarchy Levels Transfer of Responsibilities Self-Managed Teams Investments in IT Main Investments in IT Main + Interactive E ects JCR -1.459 (1.399) -0.350 (1.240) 0.099 (1.303) 0.336 (1.470) 0.136 (1.291) 0.472 (1.602) JDR 4.727** (1.984) 2.921 (1.789) -3.127* (1.852) -2.672 (2.131) 1.927 (1.906) -0.745 (2.384) 6.418** (2.810) 3.230 (2.567) -4.497* (2.659) -4.372 (3.067) 5.325* (2.743) 0.952 (3.431) 6.811** (2.670) 4.312* (2.425) -4.698* (2.533) -4.165 (2.897) 3.157 (2.581) -1.008 (3.221) HR 0.419 (0.745) -0.080 (0.668) 0.053 (0.695) 0.457 (0.795) 0.345 (0.707) 0.802 (0.883) SR 3.047** (1.375) 3.176** (1.233) -2.505* (1.284) -2.767* (1.468) 2.888** (1.305) 0.121 (1.629) CR 0.073 (0.807) -0.214 (0.722) 0.820 (0.752) -0.330 (0.860) 1.457* (0.765) 1.127 (0.955) Panel B: Unskilled Workers: Reduction of Hierarchy Levels -3.930* -3.269 (2.091) (2.185) Transfer of Responsibilities -2.199 -0.796 (1.874) (1.892) Self-Managed Teams 3.231* -1.489 (1.952) (1.993) Investments in IT 4.650** 0.476 (2.232) (2.236) Main Investments in IT -6.679*** -2.002 (1.985) (1.991) Main + Interactive E ects -2.030* -1.527 (2.475) (2.478) Panel C: Skilled Workers: Reduction of Hierarchy Levels -3.991** -2.761* (1.773) (1.560) Transfer of Responsibilities -3.776** 0.690 (1.589) (1.376) Self-Managed Teams 3.619** 0.279 (1.656) (1.431) Investments in IT 3.969** 1.224 (1.892) (1.651) Main Investments in IT -1.584 0.432 (1.683) (1.445) Main + Interactive E ects 2.386 1.655 (2.099) (1.821) -2.650* (1.535) -3.260** (1.376) 2.569* (1.433) 3.287** (1.638) -2.462* (1.457) 0.826 (1.182) -0.745 3.721* -0.536 (1.117) (1.966) (1.384) -0.007 1.794 -0.600 (0.998) (1.767) (1.239) -0.586 -3.948** 0.515 (1.039) (1.837) (1.288) 1.050 -3.777* 0.758 (1.195) (2.107) (1.484) -1.312 5.763*** 0.981 (1.061) (1.874) (1.317) -0.262 1.986 1.215 (1.333) (2.345) (1.818) -0.519 3.364** 0.003 (0.936) (1.647) (1.060) 0.963 4.989*** 1.688* (0.838) (1.479) (0.950) 0.324 -3.444** 0.104 (0.872) (1.539) (0.988) 1.445 -2.688 1.016 (1.003) (1.768) (1.139) 0.898 2.472 0.985 (0.888) (1.569) (1.008) 2.343** -0.216 1.602 (1.113) (1.966) (1.322) 28 Table 4: continued Organizational Change, Technological Change and Job and Worker Turnover: Tobit Estimations JFR Panel D: Professionals and Engineers: Reduction of Hierarchy Levels -3.413 (2.477) Transfer of Responsibilities -2.821 (2.220) Self-Managed Teams 3.190 (2.312) Investments in IT 3.098 (2.644) Main Investments in IT -2.305 (2.351) Main + Interactive E ects 0.793 (2.932) JCR 1.361 (2.551) -1.178 (2.318) 0.670 (2.404) 3.163 (2.792) -0.245 (2.442) 2.918 (3.075) JDR 9.895** (3.921) 3.316 (3.541) -4.285 (3.680) -4.144 (4.260) 3.973 (3.760) -0.171 (4.741) HR 2.195 (1.440) -0.265 (1.301) 1.216 (1.344) 3.123** (1.578) 0.289 (1.378) 3.412* (1.751) SR 6.201** (2.603) 3.157 (2.358) -1.816 (2.436) -0.154 (2.844) 2.835 (2.495) 2.680 (3.153) CR 0.134 (1.740) 0.756 (1.576) 2.389 (1.619) 4.455** (1.931) 0.642 (1.667) 5.096** (2.142) Notes: Observations: 1,305. JFR: Job ow rate JCR: Job creation rate JDR: Job destruction rate HR: Hiring rate SR: Separation rate CR: Churning rate. *: Signi cant at the 90% con dence level. **: Signi cant at the 95% con dence level. ***: Signi cant at the 99% con dence level. Regressions include the log of employment of the respective groups in 1995, the share of unskilled workers, the share of skilled workers, the share of females, the share of foreigners, the share of part-time workers, the median age of the employees in the establishment, two dummy variables indicating the development of an establishment's revenues between 1994 and 1995, two dummy variables indicating the expected development of the revenues from 1996 to 1997, the change in the share of exports on total revenues between 1994 and 1995, a variable indicating whether the establishment uses state-of-the-art technology, 8 industry and 7 regional dummies. 29 Table 5: Index of Decentralization and Job and Worker Turnover: Tobit Estimations JFR Panel A: All Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects Panel B: Unskilled Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects Panel C: Skilled Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects JCR -0.585 (0.589) 0.336 (1.467) 0.160 (1.289) 0.496 (1.600) JDR 1.738** (0.849) -2.539 (2.140) 1.841 (1.915) -0.698 (2.392) HR 0.120 (0.316) 0.451 (0.795) 0.337 (0.707) 0.788 (0.882) SR 1.500** (0.586) -2.627* (1.473) 2.801** (1.310) 0.173 (1.635) CR 0.199 (0.342) -0.357 (0.860) 1.468* (0.765) 1.111 (0.955) -1.385** (0.654) 3.139* (1.642) -2.381 (1.461) 0.758 (1.821) -1.149 -1.847** 2.030* (0.890) (0.907) (1.216) 4.526** 0.514 -4.172 (2.235) (2.234) (3.078) -6.560*** -1.980 5.079* (1.989) (1.990) (2.753) -2.034 -1.466 0.908 (2.479) (2.475) (3.444) -0.491 (0.657) 1.263 (1.651) 0.501 (1.444) 1.764 (1.820) 0.187 (1.092) 3.076 (2.790) -0.243 (2.442) 2.834 (3.074) 2.555** (1.149) -3.921 (2.913) 3.035 (2.596) -0.855 (3.238) 3.226* (1.666) -3.939 (4.276) 3.760 (3.772) -0.179 (4.757) -0.433 0.683 -0.256 (0.474) (0.838) (0.587) 1.068 -3.645* 0.733 (1.194) (2.113) (1.484) -1.306 5.631*** 0.994 (1.060) (1.879) (1.317) -0.237 1.986 1.727 (1.332) (2.352) (1.657) 0.334 2.050*** 0.733 (0.397) (0.704) (0.449) 1.469 -2.465 1.064 (1.003) (1.777) (1.138) 0.919 2.375 0.996 (0.888) (1.577) (1.007) 2.388** -0.089 2.060* (1.112) (1.976) (1.263) 0.998 (0.611) 3.072* (1.578) 0.256 (1.378) 3.328* (1.750) 2.750** (1.107) -0.054 (2.849) 2.676 (2.500) 2.622 (3.158) 1.128 (0.736) 4.437** (1.930) 0.691 (1.666) 5.128** (2.140) -1.697** (0.757) 3.787** (1.899) -1.463 (1.690) 2.324 (2.107) Panel D: Professionals and Engineers: Index of Decentralization -1.252 (1.054) Investments in IT 2.953 (2.646) Main Investments in IT -2.198 (2.354) Main + Interactive E ects 0.755 (2.935) Notes: See notes to Table 4. 30 Table 6: Organizational Change, Technological Change and Job and Worker Turnover: First Di erences JFR Panel A: All Workers: Reduction of Hierarchy Levels Transfer of Responsibilities Self-Managed Teams Investments in IT Main Investments in IT Main + Interactive E ects JCR 0.240 (0.627) -0.385 (0.463) -0.581 (0.497) 0.023 (0.634) -0.393 (0.505) -0.371 (0.633) JDR 2.532 (1.912) 2.694* (1.597) -1.218 (1.481) 0.798 (1.963) 2.460* (1.487) 3.259 (2.252) HR 0.645 (0.831) -0.281 (0.670) 0.266 (0.672) -0.394 (0.837) 0.079 (0.733) -0.316 (0.933) SR 2.937 (1.836) 2.797* (1.528) -0.371 (1.414) 0.381 (1.929) 2.932** (1.459) 3.314 (2.208) CR 1.253 (0.896) -0.455 (0.799) 1.935** (0.774) -0.796 (1.037) 1.243 (0.836) 0.448 (1.181) Panel B: Unskilled Workers: Reduction of Hierarchy Levels -3.544 -0.536 3.008 -0.344 3.199 0.383 (2.439) (0.759) (2.192) (1.074) (2.132) (1.384) Transfer of Responsibilities -2.555 0.222 2.777 0.476 3.031 0.508 (2.209) (0.738) (1.928) (1.012) (1.957) (1.390) Self-Managed Teams 0.678 -0.972 -1.650 0.884 0.206 3.712*** (2.038) (0.739) (1.743) (0.959) (1.720) (1.189) Investments in IT 1.464 0.808 -0.657 0.766 -0.699 -0.084 (2.765) (1.097) (2.388) (1.334) (2.463) (2.032) Main Investments in IT -6.154** -1.019 5.135** -1.702 4.452** -1.366 (2.466) (0.803) (2.072) (1.217) (2.113) (1.699) Main + Interactive E ects -4.690 -0.211 4.478 -0.936 3.754 -1.450 (3.327) (1.198) (2.859) (1.605) (2.945) (2.498) Panel C: Skilled Workers: Reduction of Hierarchy Levels -4.813** -1.405** 3.408* -0.920 3.893** 0.971 (2.238) (0.705) (1.953) (0.935) (1.933) (1.163) Transfer of Responsibilities -3.437* -0.231 3.206* 0.106 3.543** 0.674 (2.067) (0.693) (1.767) (0.924) (1.750) (1.087) Self-Managed Teams 1.512 -0.461 -1.972 -0.814 -2.326 -0.707 (1.813) (0.639) (1.569) (0.817) (1.533) (0.997) Investments in IT 2.323 1.159 -1.164 0.843 -1.480 -0.632 (2.656) (0.853) (2.370) (1.119) (2.451) (1.551) Main Investments in IT -2.570 -0.594 1.976 0.002 2.571 1.191 (1.836) (0.721) (1.548) (0.952) (1.575) (1.215) Main + Interactive E ects -0.247 0.565 0.812 0.845 1.092 0.559 (2.945) (0.925) (2.637) (1.272) (2.744) (1.821) -2.292 (2.088) -3.078* (1.725) 0.637 (1.624) -0.775 (2.141) -2.854* (1.641) -3.629 (2.431) 31 Table 6: continued Organizational Change, Technological Change and Job and Worker Turnover: First Di erences JFR Panel D: Professionals and Engineers: Reduction of Hierarchy Levels -2.006 (2.704) Transfer of Responsibilities -3.322 (2.410) Self-Managed Teams 2.078 (2.309) Investments in IT 2.098 (3.676) Main Investments in IT -3.060 (2.668) Main + Interactive E ects -0.962 (4.075) JCR 1.417 (1.087) -0.051 (0.794) -0.274 (0.899) -0.202 (1.264) -0.101 (0.944) -0.303 (1.352) JDR 3.423 (2.245) 3.271 (2.115) -2.353 (1.956) -2.300 (3.197) 2.959 (2.306) 0.659 (3.611) HR 2.683** (1.330) 0.239 (1.067) -0.109 (1.180) 1.717 (1.805) 0.461 (1.248) 2.178 (1.915) SR 4.690** (2.221) 3.561 (2.171) -2.188 (2.003) -0.381 (3.320) 3.522 (2.393) 3.140 (3.748) CR 2.532 (1.587) 0.580 (1.546) 0.330 (1.558) 3.838 (2.585) 1.126 (1.581) 4.963* (2.665) Notes: Observations: 1,305. JFR: Job ow rate JCR: Job creation rate JDR: Job destruction rate HR: Hiring rate SR: Separation rate CR: Churning rate. *: Signi cant at the 90% con dence level. **: Signi cant at the 95% con dence level. ***: Signi cant at the 99% con dence level. Regressions include the log of employment of the respective groups, the share of unskilled workers, the share of skilled workers, the share of females, the share of foreigners, the share of part-time workers, the median age of the employees in the establishment, two dummy variables indicating the development of an establishment's revenues, two dummy variables indicating the expected development of the revenues, the change in the share of exports on total revenues, a variable indicating whether the establishment uses state-of-the-art technology. All variables are measured in rst di erences. 32 Table 7: Index of Decentralization and Job and Worker Turnover: First Di erences JFR Panel A: All Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects Panel B: Unskilled Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects Panel C: Skilled Workers: Index of Decentralization Investments in IT Main Investments in IT Main + Interactive E ects JCR -0.268 (0.269) 0.034 (0.633) -0.406 (0.505) -0.372 (0.633) -0.408 (0.324) 0.818 (1.096) -0.999 (0.806) -0.181 (1.201) JDR 1.511** (0.658) 0.856 (1.962) 2.481* (1.485) 3.338 (2.249) 1.558* (0.813) -0.585 (2.385) 5.151** (2.070) 4.565 (2.856) HR SR CR -1.779** (0.741) -0.822 (2.140) -2.887* (1.638) -3.709 (2.427) -1.966** (0.945) 1.403 (2.762) -6.149** (2.462) -4.746 (3.323) 0.186 1.966*** 0.868** (0.349) (0.648) (0.379) -0.391 0.431 -0.813 (0.835) (1.928) (1.034) 0.057 2.944** 1.199 (0.729) (1.457) (0.830) -0.334 3.375 0.386 (0.922) (2.206) (1.177) 0.371 2.337*** 1.557** (0.463) (0.819) (0.626) 0.748 -0.655 -0.138 (1.333) (2.460) (2.029) -1.687 4.463** -1.376 (1.212) (2.109) (1.687) -0.938 3.808 -1.514 (1.604) (2.942) (2.493) -2.461*** -0.706** 1.755** -0.528 1.933*** 0.356 (0.795) (0.315) (0.683) (0.398) (0.702) (0.523) 2.230 1.149 -1.081 0.846 -1.385 -0.607 (2.653) (0.852) (2.366) (1.119) (2.449) (1.553) -2.564 -0.569 1.995 0.026 2.591 1.191 (1.835) (0.718) (1.550) (0.948) (1.579) (1.210) -0.334 0.580 0.914 0.872 1.206 0.584 (2.933) (0.936) (2.625) (1.271) (2.735) (1.819) Panel D: Professionals and Engineers: Index of Decentralization -1.307 0.354 1.661* 0.940 2.247** 1.173 (1.183) (0.498) (0.958) (0.647) (0.969) (0.717) Investments in IT 2.031 -0.180 -2.211 1.752 -0.279 3.865 (3.673) (1.264) (3.193) (1.805) (3.320) (2.581) Main Investments in IT -3.111 -0.130 2.981 0.414 3.525 1.088 (2.663) (0.943) (2.305) (1.247) (2.394) (1.573) Main + Interactive E ects -1.080 -0.311 0.770 2.166 3.246 4.952* (4.071) (1.353) (3.607) (1.918) (3.752) (2.666) Notes: See notes to Table 6. 33 Appendix Table 1: Variable Description and Descriptive Statistics Variable Description 1992/1993 Mean S.D. 1995/1996 Mean S.D. 34 JF R JF RU JF RS JF RH JCR JCRU JCRS JCRH JDR JDRU JDRS JDRH HR HRU HRS HRH SR SRU SRS SRH CR CRU CRS CRH Reduction of Hierarchy Levels Transfer of Responsibilities Self-Managed Teams Investments in IT Main Investments in IT Job ow rate of all workers (in %) -9.020 15.288 -5.048 21.456 Job ow rate of unskilled workers (in %) -11.580 20.948 -6.569 29.129 Job ow rate of skilled workers (in %) -7.268 20.349 -3.718 24.737 Job ow rate of professionals and engineers (in %) -7.060 26.541 -6.721 33.882 Job creation rate of all workers (in %) 1.357 4.661 2.441 7.475 Job creation rate of unskilled workers (in %) 1.967 7.802 3.387 10.620 Job creation rate of skilled workers (in %) 2.855 9.752 3.669 9.894 Job creation rate of professionals and engineers (in %) 3.250 10.262 4.456 12.879 Job destruction rate of all workers (in %) 10.377 13.558 7.489 19.181 Job destruction rate of unskilled workers (in %) 13.547 18.017 9.956 25.850 Job destruction rate of skilled workers (in %) 10.123 16.158 7.387 21.443 Job destruction rate of professionals and engineers (in %) 10.309 23.066 11.176 29.706 Hiring rate of all workers (in %) 13.597 9.608 13.270 11.204 Hiring of unskilled workers (in %) 12.741 14.315 12.606 14.251 Hiring of skilled workers (in %) 14.619 13.430 13.365 12.760 Hiring of professionals and engineers (in %) 12.995 15.315 12.527 16.520 Separation rate of all workers (in %) 22.617 14.078 18.318 19.465 Separation of unskilled workers (in %) 24.321 19.339 19.175 25.948 Separation of skilled workers (in %) 21.887 17.166 17.083 21.979 Separation of professionals and engineers (in %) 20.054 24.675 19.248 30.197 Churning rate of all workers (in %) 22.993 13.605 19.931 12.494 Churning of unskilled workers (in %) 21.547 21.282 18.438 17.277 Churning of skilled workers (in %) 23.527 17.489 19.392 13.962 Churning of professionals and engineers (in %) 19.490 22.445 16.143 19.076 Dummy variable that equals 1 if establishment reduced 0.272 0.445 0.272 0.445 number of hierarchy levels between 1993 and 1995, 0 otherwise. Dummy variable that equals 1 if establishment transfered 0.419 0.494 0.419 0.494 responsibilities to lower hierarchy levels between 1993 and 1995, 0 otherwise. Dummy variable that equals 1 if establishment introduced 0.307 0.461 0.307 0.461 self-managed teams between 1993 and 1995, 0 otherwise. Dummy variable that equals 1 if establishment invested 0.268 0.443 0.268 0.443 in IT between 1993 and 1995, 0 otherwise. Dummy variable that equals 1 if investments in IT are 0.814 0.389 0.814 0.389 single biggest investment between 1993 and 1995, 0 otherwise Appendix Table 1 continued: Variable Description and Descriptive Statistics Variable Description 1992/1993 Mean S.D. 1995/1996 Mean S.D. 5.827 1.578 5.719 1.553 0.413 0.247 39.968 24.763 0.380 0.217 38.317 21.684 37.752 26.610 37.031 26.419 8.676 9.801 8.956 9.865 37.359 4.861 38.452 4.402 15.114 14.869 15.152 15.613 0.555 0.497 0.507 0.500 0.209 0.407 0.212 0.409 0.507 0.500 1.117 1.507 0.212 0.409 0.947 1.566 11.256 20.232 14.369 22.552 4.027 0.771 3.892 0.754 log(Employment) Employment Share of Unskilled Workers Employment Share of Skilled Workers Share of Females Share of Foreigners Median Age of Employees Share of Part-Time Workers Revenues increased Revenues decreased Expected Revenues increase 35 Expected Revenues decrease Share of Export State-of-the-Art Technology Notes: Observations: 1,305. Logarithm of total establishment employment in 1992/1995 Share of unskilled workers in 1992/1995 Share of skilled workers in 1992/1995 Share of females in 1992/1995 Share if foreigners in 1992/1995 Median age of employees in 1992/1995 Share of part-time workers in 1992/1995 Dummy variable that equals 1 if revenue increased during 1991-1992 or 1994-1995, respectively, 0 otherwise. Dummy variable that equals 1 if revenue decreased during 1991-1992 or 1994-1995, respectively, 0 otherwise. Dummy variable that equals 1 if establishment expects an increasing revenue during 1993-1994 or 1996-1997, respectively, 0 otherwise. Dummy variable that equals 1 if establishment expects a decreasing revenue during 1993-1994 or 1996-1997, respectively, 0 otherwise. Share of exports on total revenues in 1991-1992/1994-1995 Categorical variable indicating whether the establishment uses newest technology compared to other establishment in the industry. Appendix Table 2 (not intended for publication): Organizational Change, Technological Change and Job Turnover: Tobit Estimates log 36 JFR Reduction of Hierarchy Levels -2.650* (1.535) Transfer of Responsibilities -3.260** (1.376) Introduction of Self-Managed 2.569* Teams (1.433) Investments in IT 3.287** (1.638) Main Investments in IT -2.462* (1.457) (Employment) -1.210** (0.476) Employment Share of 0.097** Unskilled Workers (0.043) Employment Share of 0.086* Skilled Workers (0.049) Share of Females -0.039 (0.038) Share of Foreigners -0.049 (0.069) Median Age of Employees -0.436*** (0.140) Share of Part-Time Workers 0.049 (0.054) Revenues increased 1.719 (1.411) Revenues decreased -2.808 (1.710) Expected Revenues increase 1.868* (0.974) Expected Revenues decrease -1.385 (0.947) Share of Export 0.083** (0.033) State-of-the-Art Technology 0.000 (0.788) All Workers JCR -1.459 (1.399) -0.350 (1.240) 0.099 (1.303) 0.336 (1.470) 0.136 (1.291) -1.990*** (0.426) 0.038 (0.037) 0.070* (0.042) -0.020 (0.033) -0.034 (0.063) -0.577*** (0.123) 0.101** (0.045) 2.488** (1.266) -4.456*** (1.656) 1.831** (0.889) -1.438* (0.855) 0.084*** (0.029) 0.108 (0.712) JDR 4.727** (1.984) 2.921 (1.789) -3.127* (1.852) -2.672 (2.131) 1.927 (1.906) 1.663*** (0.627) -0.148** (0.058) -0.120* (0.066) 0.047 (0.049) 0.146* (0.088) 0.572*** (0.185) -0.011 (0.073) -3.959** (1.837) 4.304** (2.178) -1.735 (1.263) 1.275 (1.230) -0.109** (0.043) -0.457 (1.022) Unskilled Workers JFR JCR JDR -3.930* -3.269 6.418** (2.091) (2.185) (2.810) -2.199 -0.796 3.230 (1.874) (1.892) (2.567) 3.231* -1.489 -4.497* (1.952) (1.993) (2.659) 4.650** 0.476 -4.372 (2.232) (2.236) (3.067) -6.679*** -2.002 5.325* (1.985) (1.991) (2.743) -1.164* -1.837*** 2.203** (0.648) (0.661) (0.902) 0.236*** 0.048 -0.273*** (0.059) (0.059) (0.082) 0.200*** 0.103 -0.211** (0.066) (0.066) (0.094) -0.041 -0.015 0.065 (0.051) (0.051) (0.072) -0.024 0.048 0.096 (0.094) (0.095) (0.127) -0.429** -0.780*** 0.714*** (0.190) (0.193) (0.268) 0.119 0.068 -0.182* (0.074) (0.072) (0.106) -0.373 0.970 -1.800 (1.922) (1.940) (2.646) -4.311* -2.776 6.917** (2.329) (2.450) (3.141) 0.126 -0.248 -0.382 (1.327) (1.332) (1.825) -0.320 -0.368 0.358 (1.290) (1.295) (1.770) 0.109** 0.090** -0.132** (0.045) (0.046) (0.061) -0.857 -0.690 0.318 (1.074) (1.081) (1.475) Skilled Workers JFR JCR JDR -3.991** -2.761* 6.811** (1.773) (1.560) (2.670) -3.776** 0.690 4.312* (1.589) (1.376) (2.425) 3.619** 0.279 -4.698* (1.656) (1.431) (2.533) 3.969** 1.224 -4.165 (1.892) (1.651) (2.897) -1.584 0.432 3.157 (1.683) (1.445) (2.581) -1.089** -1.739*** 2.393*** (0.550) (0.477) (0.863) 0.161*** 0.056 -0.244*** (0.050) (0.043) (0.080) 0.060 -0.044 -0.038 (0.056) (0.048) (0.089) -0.101** -0.053 0.128* (0.043) (0.038) (0.068) -0.214*** -0.030 0.307** (0.079) (0.069) (0.121) -0.045 -0.433*** 0.191 (0.161) (0.140) (0.251) 0.088 0.151*** -0.080 (0.063) (0.052) (0.102) 1.257 1.588 -4.985** (1.630) (1.400) (2.509) -3.830* -5.875*** 7.028** (1.975) (1.819) (2.937) 1.168 1.747* -1.439 (1.125) (0.973) (1.737) -1.450 -1.355 2.254 (1.094) (0.942) (1.691) 0.102*** 0.084** -0.172*** (0.038) (0.033) (0.058) -0.487 0.389 0.411 (0.910) (0.787) (1.397) Professionals and Engineers JFR JCR JDR -3.413 1.361 9.895** (2.477) (2.551) (3.921) -2.821 -1.178 3.316 (2.220) (2.318) (3.541) 3.190 0.670 -4.285 (2.312) (2.404) (3.680) 3.098 3.163 -4.144 (2.644) (2.792) (4.260) -2.305 -0.245 3.973 (2.351) (2.442) (3.760) 0.492 -1.164 3.432*** (0.768) (0.799) (1.265) 0.087 0.151** -0.214* (0.070) (0.071) (0.113) 0.123 0.229*** -0.207 (0.079) (0.080) (0.129) -0.003 0.053 0.059 (0.061) (0.062) (0.098) 0.009 0.189* 0.060 (0.111) (0.111) (0.182) -0.328 -0.593** 0.634* (0.225) (0.230) (0.371) 0.073 0.227*** 0.016 (0.088) (0.085) (0.145) 0.912 -1.165 -3.649 (2.277) (2.322) (3.651) -3.551 -10.556*** 5.119 (2.758) (3.006) (4.369) 3.029* 3.666** -4.770* (1.571) (1.655) (2.494) -1.925 -2.595 3.310 (1.527) (1.594) (2.430) 0.011 0.079 -0.029 (0.053) (0.053) (0.085) -0.796 -0.098 0.195 (1.272) (1.353) (2.009) Notes: See notes to Table 4. Appendix Table 3 (not intended for publication): Decentralization, Technological Change and Job Turnover: Tobit Estimates Index of Decentralization Investments in IT Main Investments in IT log (Employment) 37 Employment Share of Unskilled Workers Employment Share of Skilled Workers Share of Females Share of Foreigners Median Age of Employees Share of Part-Time Workers Revenues increased Revenues decreased Expected Revenues increase Expected Revenues decrease Share of Export State-of-the-Art Technology JFR -1.385** (0.654) 3.139* (1.642) -2.381 (1.461) -1.146** (0.475) 0.105** (0.043) 0.095* (0.049) -0.038 (0.038) -0.044 (0.069) -0.447*** (0.139) 0.051 (0.055) 1.748 (1.415) -2.900* (1.714) 1.732* (0.974) -1.278 (0.947) 0.083** (0.033) 0.213 (0.787) All Workers JCR -0.585 (0.589) 0.336 (1.467) 0.160 (1.289) -1.994*** (0.423) 0.040 (0.037) 0.070* (0.042) -0.021 (0.033) -0.033 (0.063) -0.584*** (0.122) 0.101** (0.045) 2.484** (1.265) -4.479*** (1.654) 1.830** (0.885) -1.443* (0.851) 0.083*** (0.029) 0.137 (0.709) JDR 1.738** (0.849) -2.539 (2.140) 1.841 (1.915) 1.649*** (0.627) -0.161*** (0.058) -0.134** (0.066) 0.050 (0.050) 0.139 (0.089) 0.608*** (0.185) -0.016 (0.074) -3.980** (1.845) 4.469** (2.187) -1.650 (1.265) 1.232 (1.232) -0.109** (0.043) -0.723 (1.022) Unskilled Workers Skilled Workers JFR JCR JDR JFR JCR JDR -1.149 -1.847** 2.030* -1.697** -0.491 2.555** (0.890) (0.907) (1.216) (0.757) (0.657) (1.149) 4.526** 0.514 -4.172 3.787** 1.263 -3.921 (2.235) (2.234) (3.078) (1.899) (1.651) (2.913) -6.560*** -1.980 5.079* -1.463 0.501 3.035 (1.989) (1.990) (2.753) (1.690) (1.444) (2.596) -1.139* -1.882*** 2.190** -1.022* -1.790*** 2.342*** (0.646) (0.656) (0.901) (0.549) (0.475) (0.864) 0.246*** 0.050 -0.289*** 0.173*** 0.059 -0.263*** (0.059) (0.059) (0.083) (0.050) (0.043) (0.080) 0.210*** 0.104 -0.225** 0.071 -0.042 -0.056 (0.066) (0.066) (0.094) (0.056) (0.048) (0.089) -0.043 -0.016 0.069 -0.101** -0.056 0.130* (0.051) (0.051) (0.072) (0.044) (0.038) (0.068) -0.017 0.050 0.083 -0.207*** -0.029 0.295** (0.094) (0.094) (0.127) (0.080) (0.069) (0.121) -0.455** -0.794*** 0.764*** -0.066 -0.454*** 0.247 (0.190) (0.193) (0.267) (0.161) (0.140) (0.251) 0.122* 0.068 -0.186* 0.091 0.151*** -0.086 (0.074) (0.072) (0.106) (0.063) (0.053) (0.103) -0.371 0.961 -1.776 1.284 1.548 -4.982** (1.927) (1.939) (2.656) (1.637) (1.399) (2.524) -4.451* -2.828 7.172** -3.970** -5.969*** 7.214** (2.334) (2.448) (3.153) (1.983) (1.819) (2.955) 0.038 -0.200 -0.314 1.012 1.796* -1.364 (1.326) (1.327) (1.827) (1.127) (0.969) (1.742) -0.268 -0.420 0.352 -1.334 -1.416 2.255 (1.289) (1.290) (1.772) (1.095) (0.938) (1.696) 0.108** 0.089* -0.130** 0.101*** 0.081** -0.173*** (0.045) (0.046) (0.061) (0.038) (0.033) (0.058) -0.622 -0.676 -0.024 -0.202 0.429 0.046 (1.072) (1.077) (1.475) (0.911) (0.783) (1.400) Professionals and Engineers JFR JCR JDR -1.252 0.187 3.226* (1.054) (1.092) (1.666) 2.953 3.076 -3.939 (2.646) (2.790) (4.276) -2.198 -0.243 3.760 (2.354) (2.442) (3.772) 0.540 -1.116 3.460*** (0.765) (0.796) (1.264) 0.097 0.151** -0.237** (0.070) (0.071) (0.113) 0.133* 0.230*** -0.230* (0.079) (0.080) (0.129) -0.003 0.055 0.067 (0.061) (0.062) (0.099) 0.015 0.189* 0.045 (0.111) (0.111) (0.183) -0.348 -0.581** 0.709* (0.224) (0.229) (0.371) 0.075 0.227*** 0.005 (0.088) (0.085) (0.146) 0.929 -1.136 -3.621 (2.280) (2.324) (3.665) -3.674 -10.542*** 5.467 (2.762) (3.008) (4.384) 2.910* 3.588** -4.719* (1.569) (1.651) (2.496) -1.840 -2.512 3.325 (1.525) (1.590) (2.433) 0.010 0.080 -0.026 (0.053) (0.053) (0.086) -0.557 -0.067 -0.161 (1.268) (1.348) (2.009) Notes: See notes to Table 4. Appendix Table 4 (not intended for publication): Organizational Change, Technological Change and Worker Turnover: Tobit Estimates log 38 HR Reduction of Hierarchy Levels 0.419 (0.745) Transfer of Responsibilities -0.080 (0.668) Introduction of Self-Managed 0.053 Teams (0.695) Investments in IT 0.457 (0.795) Main Investments in IT 0.345 (0.707) (Employment) -0.976*** (0.231) Employment Share of -0.001 Unskilled Workers (0.021) Employment Share of 0.033 Skilled Workers (0.024) Share of Females 0.027 (0.018) Share of Foreigners 0.121*** (0.033) Median Age of Employees -0.568*** (0.068) Share of Part-Time Workers 0.119*** (0.026) Revenues increased 0.348 (0.685) Revenues decreased -1.141 (0.830) Expected Revenues increase 0.849* (0.473) Expected Revenues decrease -0.709 (0.459) Share of Export 0.006 (0.016) State-of-the-Art Technology -0.401 (0.382) All Workers SR 3.047** (1.375) 3.176** (1.233) -2.505* (1.284) -2.767* (1.468) 2.888** (1.305) 0.305 (0.428) -0.098** (0.039) -0.053 (0.044) 0.068** (0.034) 0.165*** (0.062) -0.132 (0.125) 0.064 (0.049) -1.321 (1.265) 1.719 (1.533) -1.054 (0.872) 0.744 (0.848) -0.081*** (0.029) -0.407 (0.706) CR 0.073 (0.807) -0.214 (0.722) 0.820 (0.752) -0.330 (0.860) 1.457* (0.765) 0.376 (0.251) -0.002 (0.023) 0.010 (0.026) 0.068*** (0.020) 0.171*** (0.036) -0.706*** (0.074) 0.102*** (0.029) 0.246 (0.741) -0.191 (0.898) 0.559 (0.511) -0.539 (0.497) -0.036** (0.017) -0.571 (0.414) Unskilled Workers HR SR CR -0.745 3.721* -0.536 (1.117) (1.966) (1.384) -0.007 1.794 -0.600 (0.998) (1.767) (1.239) -0.586 -3.948** 0.515 (1.039) (1.837) (1.288) 1.050 -3.777* 0.758 (1.195) (2.107) (1.484) -1.312 5.763*** 0.981 (1.061) (1.874) (1.317) -0.534 0.997 1.196*** (0.350) (0.619) (0.437) 0.071** -0.168*** 0.152*** (0.032) (0.056) (0.040) 0.082** -0.134** 0.072 (0.036) (0.064) (0.045) 0.014 0.055 0.030 (0.028) (0.049) (0.034) 0.139*** 0.167* 0.208*** (0.050) (0.088) (0.062) -0.484*** -0.023 -0.516*** (0.103) (0.181) (0.128) 0.097** -0.036 0.134*** (0.040) (0.071) (0.050) 0.317 0.857 1.508 (1.027) (1.815) (1.275) -0.458 4.376** -0.053 (1.246) (2.196) (1.546) 0.608 0.704 1.825** (0.707) (1.251) (0.878) -1.013 -0.757 -1.868** (0.687) (1.216) (0.853) 0.007 -0.117*** -0.049* (0.024) (0.042) (0.030) -0.774 0.075 -0.736 (0.574) (1.013) (0.713) Skilled Workers HR SR CR -0.519 3.364** 0.003 (0.936) (1.647) (1.060) 0.963 4.989*** 1.688* (0.838) (1.479) (0.950) 0.324 -3.444** 0.104 (0.872) (1.539) (0.988) 1.445 -2.688 1.016 (1.003) (1.768) (1.139) 0.898 2.472 0.985 (0.888) (1.569) (1.008) -0.665** 0.903* 1.164*** (0.293) (0.519) (0.334) 0.063** -0.104** 0.074** (0.027) (0.047) (0.030) 0.063** 0.028 0.172*** (0.030) (0.053) (0.034) -0.001 0.108*** 0.063** (0.023) (0.041) (0.026) 0.033 0.257*** 0.091* (0.042) (0.074) (0.048) -0.443*** -0.438*** -0.657*** (0.086) (0.151) (0.097) 0.119*** 0.005 0.028 (0.033) (0.060) (0.038) 0.278 -1.006 0.434 (0.862) (1.522) (0.978) -1.158 2.811 0.679 (1.045) (1.844) (1.187) 1.139* 0.010 0.872 (0.594) (1.050) (0.674) -1.056* 0.412 -1.081* (0.578) (1.020) (0.655) 0.019 -0.090** -0.022 (0.020) (0.035) (0.023) -0.400 -0.080 -1.045* (0.481) (0.850) (0.546) Professionals and Engineers HR SR CR 2.195 6.201** 0.134 (1.440) (2.603) (1.740) -0.265 3.157 0.756 (1.301) (2.358) (1.576) 1.216 -1.816 2.389 (1.344) (2.436) (1.619) 3.123** -0.154 4.455** (1.578) (2.844) (1.931) 0.289 2.835 0.642 (1.378) (2.495) (1.667) 1.701*** 2.376*** 4.677*** (0.463) (0.835) (0.572) -0.060 -0.220*** -0.282*** (0.041) (0.074) (0.049) 0.026 -0.193** -0.227*** (0.046) (0.084) (0.056) 0.076** 0.120* 0.156*** (0.036) (0.065) (0.044) 0.112* 0.095 -0.010 (0.066) (0.120) (0.080) -0.364*** -0.006 -0.320* (0.135) (0.245) (0.167) 0.171*** 0.077 0.001 (0.052) (0.094) (0.064) -1.121 -2.005 -1.197 (1.331) (2.417) (1.613) -4.602*** -0.044 -2.780 (1.636) (2.949) (1.987) 0.293 -3.322** -1.713 (0.920) (1.663) (1.110) 0.400 2.778* 1.880* (0.894) (1.616) (1.080) -0.020 -0.027 -0.058 (0.031) (0.056) (0.037) -0.516 0.423 -0.090 (0.750) (1.350) (0.909) Notes: See notes to Table 4. Appendix Table 5 (not intended for publication): Decentralization, Technological Change and Worker Turnover: Tobit Estimates Index of Decentralization Investments in IT Main Investments in IT log (Employment) 39 Employment Share of Unskilled Workers Employment Share of Skilled Workers Share of Females Share of Foreigners Median Age of Employees Share of Part-Time Workers Revenues increased Revenues decreased Expected Revenues increase Expected Revenues decrease Share of Export State-of-the-Art Technology HR 0.120 (0.316) 0.451 (0.795) 0.337 (0.707) -0.968*** (0.230) -0.001 (0.021) 0.033 (0.024) 0.028 (0.018) 0.120*** (0.033) -0.565*** (0.068) 0.119*** (0.026) 0.354 (0.685) -1.132 (0.830) 0.838* (0.471) -0.697 (0.458) 0.006 (0.016) -0.404 (0.381) All Workers SR 1.500** (0.586) -2.627* (1.473) 2.801** (1.310) 0.251 (0.427) -0.107*** (0.039) -0.061 (0.044) 0.068** (0.034) 0.160*** (0.062) -0.118 (0.125) 0.062 (0.049) -1.342 (1.270) 1.819 (1.539) -0.931 (0.873) 0.650 (0.849) -0.081*** (0.030) -0.622 (0.706) CR 0.199 (0.342) -0.357 (0.860) 1.468* (0.765) 0.390 (0.250) -0.001 (0.023) 0.011 (0.026) 0.068*** (0.020) 0.171*** (0.036) -0.707*** (0.073) 0.103*** (0.029) 0.252 (0.741) -0.205 (0.898) 0.532 (0.510) -0.516 (0.495) -0.036** (0.017) -0.535 (0.412) Unskilled Workers HR SR CR -0.433 0.683 -0.256 (0.474) (0.838) (0.587) 1.068 -3.645* 0.733 (1.194) (2.113) (1.484) -1.306 5.631*** 0.994 (1.060) (1.879) (1.317) -0.551 0.978 1.208*** (0.348) (0.617) (0.434) 0.070** -0.180*** 0.154*** (0.032) (0.056) (0.040) 0.081** -0.145** 0.074 (0.036) (0.064) (0.045) 0.013 0.056 0.030 (0.028) (0.049) (0.034) 0.139*** 0.160* 0.209*** (0.050) (0.088) (0.062) -0.488*** 0.005 -0.518*** (0.103) (0.181) (0.128) 0.097** -0.039 0.134*** (0.040) (0.071) (0.050) 0.307 0.862 1.513 (1.027) (1.821) (1.275) -0.463 4.520** -0.071 (1.246) (2.203) (1.546) 0.633 0.797 1.798** (0.705) (1.251) (0.875) -1.037 -0.811 -1.848** (0.685) (1.216) (0.851) 0.007 -0.115*** -0.049* (0.024) (0.042) (0.030) -0.786 -0.176 -0.694 (0.572) (1.012) (0.710) Skilled Workers HR SR CR 0.334 2.050*** 0.733 (0.397) (0.704) (0.449) 1.469 -2.465 1.064 (1.003) (1.777) (1.138) 0.919 2.375 0.996 (0.888) (1.577) (1.007) -0.695** 0.797 1.121*** (0.291) (0.519) (0.332) 0.063** -0.116** 0.073** (0.027) (0.047) (0.030) 0.063** 0.016 0.170*** (0.030) (0.053) (0.034) -0.002 0.105** 0.061** (0.023) (0.041) (0.026) 0.034 0.251*** 0.091* (0.042) (0.075) (0.048) -0.452*** -0.427*** -0.665*** (0.085) (0.151) (0.097) 0.119*** 0.002 0.028 (0.033) (0.060) (0.038) 0.260 -1.043 0.410 (0.862) (1.530) (0.978) -1.182 2.930 0.668 (1.045) (1.854) (1.187) 1.177** 0.219 0.934 (0.593) (1.052) (0.673) -1.096* 0.240 -1.142* (0.576) (1.023) (0.653) 0.018 -0.090** -0.023 (0.020) (0.035) (0.023) -0.401 -0.373 -1.078** (0.479) (0.851) (0.544) Professionals and Engineers HR SR CR 0.998 2.750** 1.128 (0.611) (1.107) (0.736) 3.072* -0.054 4.437** (1.578) (2.849) (1.930) 0.256 2.676 0.691 (1.378) (2.500) (1.666) 1.753*** 2.384*** 4.677*** (0.461) (0.833) (0.569) -0.060 -0.232*** -0.279*** (0.041) (0.074) (0.049) 0.027 -0.203** -0.224*** (0.046) (0.084) (0.056) 0.078** 0.122* 0.155*** (0.036) (0.065) (0.044) 0.111* 0.086 -0.007 (0.066) (0.120) (0.080) -0.351*** 0.030 -0.330** (0.134) (0.244) (0.166) 0.171*** 0.074 0.002 (0.052) (0.094) (0.064) -1.093 -1.958 -1.209 (1.331) (2.422) (1.613) -4.572*** 0.136 -2.831 (1.636) (2.955) (1.986) 0.221 -3.256* -1.743 (0.917) (1.662) (1.107) 0.474 2.750* 1.898* (0.891) (1.615) (1.077) -0.019 -0.025 -0.059 (0.031) (0.056) (0.037) -0.496 0.188 -0.009 (0.747) (1.348) (0.905) Notes: See notes to Table 4. Appendix Table 6 (not intended for publication): Organizational Change, Technological Change and Job Turnover: First Di erences log 40 JFR Reduction of Hierarchy Levels -2.292 (2.088) Transfer of Responsibilities -3.078* (1.725) Introduction of Self-Managed 0.637 Teams (1.624) Investments in IT -0.775 (2.141) Main Investments in IT -2.854* (1.641) (Employment) -9.748 (6.695) Employment Share of -0.347 Unskilled Workers (0.425) Employment Share of -0.133 Skilled Workers (0.279) Share of Females 0.007 (0.244) Share of Foreigners 0.281 (0.285) Median Age of Employees 0.654 (0.427) Share of Part-Time Workers -0.366 (0.279) Revenues increased 2.826** (1.192) Revenues decreased -1.961 (1.496) Expected Revenues increase 2.122** (0.951) Expected Revenues decrease -1.196 (0.870) Share of Export 0.047 (0.045) State-of-the-Art Technology 0.014 (0.807) Constant 3.962* (2.028) 2 0.06 Notes: See notes to Table 6. R All Workers JCR JDR 0.240 2.532 (0.627) (1.912) -0.385 2.694* (0.463) (1.597) -0.581 -1.218 (0.497) (1.481) 0.023 0.798 (0.634) (1.963) -0.393 2.460* (0.505) (1.487) -3.305* 6.442 (1.947) (5.926) -0.063 0.284 (0.092) (0.389) -0.064 0.069 (0.097) (0.248) 0.097 0.090 (0.097) (0.194) 0.132 -0.149 (0.107) (0.251) 0.082 -0.572 (0.117) (0.397) -0.056 0.310 (0.097) (0.242) 0.281 -2.545** (0.429) (1.055) -0.289 1.673 (0.523) (1.331) 0.650** -1.472* (0.256) (0.877) -0.401 0.794 (0.260) (0.797) 0.012 -0.035 (0.014) (0.041) -0.031 -0.044 (0.236) (0.722) 0.726 -3.236* (0.593) (1.839) 0.03 0.05 Unskilled Workers JFR JCR JDR -3.544 -0.536 3.008 (2.439) (0.759) (2.192) -2.555 0.222 2.777 (2.209) (0.738) (1.928) 0.678 -0.972 -1.650 (2.038) (0.739) (1.743) 1.464 0.808 -0.657 (2.765) (1.097) (2.388) -6.154** -1.019 5.135** (2.466) (0.803) (2.072) -7.356 -2.890 4.466 (6.932) (1.879) (6.231) -0.978* -0.442*** 0.536 (0.529) (0.136) (0.497) 0.273 -0.180 -0.453 (0.518) (0.132) (0.480) -0.430 0.181 0.611** (0.359) (0.164) (0.275) 0.441 0.296** -0.146 (0.353) (0.148) (0.287) 0.565 0.140 -0.424 (0.558) (0.195) (0.490) 0.226 0.092 -0.133 (0.333) (0.114) (0.296) 2.788 -0.077 -2.866** (1.752) (0.668) (1.450) -3.252* -0.778 2.474 (1.907) (0.704) (1.623) 0.355 -0.040 -0.396 (1.218) (0.409) (1.069) -0.138 -0.129 0.009 (1.124) (0.415) (0.967) 0.070 0.023 -0.047 (0.053) (0.019) (0.048) -1.011 0.126 1.137 (1.084) (0.486) (0.863) 3.214 0.392 -2.822 (2.858) (1.235) (2.389) 0.07 0.04 0.06 Skilled Workers JFR JCR JDR -4.813** -1.405** 3.408* (2.238) (0.705) (1.953) -3.437* -0.231 3.206* (2.067) (0.693) (1.767) 1.512 -0.461 -1.972 (1.813) (0.639) (1.569) 2.323 1.159 -1.164 (2.656) (0.853) (2.370) -2.570 -0.594 1.976 (1.836) (0.721) (1.548) -12.953* -6.321** 6.631 (7.174) (2.539) (5.645) 0.018 -0.034 -0.052 (0.499) (0.158) (0.392) -0.928** -0.702*** 0.226 (0.402) (0.175) (0.300) 0.011 -0.056 -0.067 (0.284) (0.112) (0.222) 0.148 -0.168 -0.316 (0.421) (0.149) (0.360) 0.367 -0.166 -0.533 (0.512) (0.194) (0.436) -0.174 0.044 0.218 (0.321) (0.126) (0.244) 1.560 0.194 -1.367 (1.363) (0.478) (1.198) -1.837 -0.820 1.017 (1.746) (0.593) (1.511) 0.504 0.235 -0.268 (1.052) (0.391) (0.902) -0.444 0.146 0.590 (0.983) (0.361) (0.843) 0.049 0.013 -0.036 (0.048) (0.018) (0.041) -0.957 -0.506 0.450 (0.976) (0.382) (0.793) 3.119 0.092 -3.027 (2.563) (0.865) (2.231) 0.06 0.13 0.03 Professionals and Engineers JFR JCR JDR -2.006 1.417 3.423 (2.704) (1.087) (2.245) -3.322 -0.051 3.271 (2.410) (0.794) (2.115) 2.078 -0.274 -2.353 (2.309) (0.899) (1.956) 2.098 -0.202 -2.300 (3.676) (1.264) (3.197) -3.060 -0.101 2.959 (2.668) (0.944) (2.306) -16.685*** -6.518*** 10.167** (5.390) (2.132) (4.607) 1.375*** 0.681*** -0.694** (0.405) (0.178) (0.348) 1.088** 0.623*** -0.465 (0.442) (0.191) (0.386) 0.565* 0.356** -0.208 (0.322) (0.162) (0.246) 0.531 0.489** -0.042 (0.503) (0.246) (0.399) -0.414 -0.236 0.178 (0.612) (0.250) (0.535) -0.162 0.049 0.210 (0.285) (0.129) (0.238) 0.818 -0.350 -1.168 (1.967) (0.830) (1.605) -2.484 -1.409 1.074 (2.755) (0.937) (2.341) 0.494 -0.506 -0.999 (1.395) (0.540) (1.204) 0.988 0.876 -0.112 (1.353) (0.560) (1.151) 0.028 -0.035* -0.062 (0.056) (0.019) (0.048) 2.176 0.120 -2.057* (1.434) (0.582) (1.164) 0.441 1.413 0.972 (3.712) (1.237) (3.260) 0.04 0.07 0.03 Appendix Table 7 (not intended for publication): Decentralization, Technological Change and Job Turnover: First Di erences Index of Decentralization Investments in IT Main Investments in IT log (Employment) Employment Share of Unskilled Workers Employment Share of Skilled Workers Share of Females 41 Share of Foreigners Median Age of Employees Share of Part-Time Workers Revenues increased Revenues decreased Expected Revenues increase Expected Revenues decrease Share of Export State-of-the-Art Technology Constant R 2 JFR -1.779** (0.741) -0.822 (2.140) -2.887* (1.638) -9.663 (6.552) -0.345 (0.423) -0.129 (0.278) 0.001 (0.243) 0.272 (0.285) 0.647 (0.426) -0.364 (0.278) 2.892** (1.187) -1.977 (1.493) 2.056** (0.956) -1.151 (0.875) 0.050 (0.045) 0.033 (0.806) 2.320 (2.171) 0.06 All Workers JCR -0.268 (0.269) 0.034 (0.633) -0.406 (0.505) -3.421* (1.918) -0.061 (0.092) -0.064 (0.097) 0.095 (0.097) 0.131 (0.107) 0.083 (0.118) -0.056 (0.097) 0.290 (0.429) -0.287 (0.521) 0.659*** (0.254) -0.406 (0.260) 0.013 (0.014) -0.032 (0.235) 0.430 (0.652) 0.03 JDR 1.511** (0.658) 0.856 (1.962) 2.481* (1.485) 6.243 (5.792) 0.284 (0.386) 0.065 (0.246) 0.094 (0.194) -0.141 (0.251) -0.564 (0.395) 0.308 (0.240) -2.601** (1.053) 1.690 (1.328) -1.397 (0.883) 0.745 (0.801) -0.038 (0.041) -0.065 (0.722) -1.890 (1.972) 0.05 JDR 1.755** (0.683) -1.081 (2.366) 1.995 (1.550) 6.297 (5.501) -0.051 (0.388) 0.221 (0.298) -0.064 (0.222) -0.306 (0.361) -0.523 (0.436) 0.214 (0.242) -1.433 (1.200) 1.041 (1.507) -0.166 (0.905) 0.523 (0.844) -0.039 (0.041) 0.422 (0.796) -1.503 (2.309) 0.02 Unskilled Workers JFR JCR JDR -1.966** -0.408 1.558* (0.945) (0.324) (0.813) 1.403 0.818 -0.585 (2.762) (1.096) (2.385) -6.149** -0.999 5.151** (2.462) (0.806) (2.070) -7.017 -2.845 4.172 (6.752) (1.844) (6.072) -0.981* -0.444*** 0.537 (0.526) (0.136) (0.493) 0.275 -0.181 -0.457 (0.516) (0.131) (0.477) -0.430 0.184 0.614** (0.357) (0.165) (0.273) 0.437 0.300** -0.137 (0.353) (0.148) (0.288) 0.558 0.142 -0.416 (0.556) (0.195) (0.489) 0.228 0.092 -0.137 (0.331) (0.114) (0.294) 2.813 -0.108 -2.921** (1.753) (0.664) (1.453) -3.268* -0.774 2.494 (1.904) (0.704) (1.619) 0.286 -0.022 -0.307 (1.218) (0.409) (1.069) -0.093 -0.143 -0.049 (1.125) (0.415) (0.968) 0.072 0.022 -0.050 (0.053) (0.018) (0.048) -0.993 0.120 1.113 (1.083) (0.486) (0.863) 1.495 0.027 -1.468 (2.844) (1.155) (2.426) 0.06 0.04 0.06 Skilled Workers JFR JCR -2.461*** -0.706** (0.795) (0.315) 2.230 1.149 (2.653) (0.852) -2.564 -0.569 (1.835) (0.718) -12.450* -6.153** (6.975) (2.486) 0.014 -0.037 (0.494) (0.157) -0.924** -0.703*** (0.401) (0.175) 0.011 -0.053 (0.283) (0.112) 0.141 -0.165 (0.423) (0.149) 0.357 -0.166 (0.510) (0.194) -0.170 0.044 (0.318) (0.125) 1.600 0.168 (1.365) (0.477) -1.862 -0.821 (1.742) (0.593) 0.397 0.232 (1.059) (0.392) -0.377 0.146 (0.988) (0.364) 0.051 0.012 (0.048) (0.018) -0.929 -0.506 (0.978) (0.382) 0.996 -0.506 (2.609) (0.852) 0.06 0.13 Professionals and Engineers JFR JCR JDR -1.307 0.354 1.661* (1.183) (0.498) (0.958) 2.031 -0.180 -2.211 (3.673) (1.264) (3.193) -3.111 -0.130 2.981 (2.663) (0.943) (2.305) -16.578*** -6.765*** 9.812** (5.308) (2.113) (4.538) 1.378*** 0.685*** -0.693** (0.404) (0.177) (0.348) 1.095** 0.624*** -0.471 (0.441) (0.191) (0.385) 0.557* 0.352** -0.204 (0.319) (0.161) (0.244) 0.517 0.487** -0.031 (0.502) (0.246) (0.399) -0.424 -0.235 0.188 (0.612) (0.250) (0.535) -0.158 0.048 0.206 (0.284) (0.129) (0.237) 0.917 -0.324 -1.241 (1.955) (0.829) (1.600) -2.506 -1.406 1.100 (2.755) (0.934) (2.342) 0.397 -0.491 -0.888 (1.397) (0.536) (1.211) 1.054 0.869 -0.185 (1.356) (0.558) (1.157) 0.032 -0.034* -0.066 (0.056) (0.019) (0.048) 2.204 0.117 -2.087* (1.436) (0.581) (1.167) -0.750 1.650 2.400 (3.612) (1.147) (3.205) 0.04 0.07 0.02 Notes: See notes to Table 6. Appendix Table 8 (not intended for publication): Organizational Change, Technological Change and Worker Turnover: First Di erences log 42 HR Reduction of Hierarchy Levels 0.645 (0.831) Transfer of Responsibilities -0.281 (0.670) Introduction of Self-Managed 0.266 Teams (0.672) Investments in IT -0.394 (0.837) Main Investments in IT 0.079 (0.733) (Employment) -7.038*** (2.530) Employment Share of -0.375** Unskilled Workers (0.163) Employment Share of -0.533*** Skilled Workers (0.202) Share of Females 0.159 (0.143) Share of Foreigners 0.172 (0.161) Median Age of Employees -0.233 (0.189) Share of Part-Time Workers -0.016 (0.110) Revenues increased 1.060* (0.564) Revenues decreased -0.807 (0.706) Expected Revenues increase 0.544 (0.373) Expected Revenues decrease -0.413 (0.376) Share of Export 0.015 (0.016) State-of-the-Art Technology 0.172 (0.374) Constant -1.025 (0.827) 2 0.09 Notes: See notes to Table 6. R All Workers SR 2.937 (1.836) 2.797* (1.528) -0.371 (1.414) 0.381 (1.929) 2.932** (1.459) 2.710 (5.658) -0.028 (0.389) -0.400 (0.271) 0.152 (0.191) -0.109 (0.252) -0.887** (0.398) 0.350 (0.240) -1.765* (1.068) 1.155 (1.286) -1.578* (0.850) 0.782 (0.769) -0.032 (0.040) 0.158 (0.717) -4.986*** (1.811) 0.05 CR 1.253 (0.896) -0.455 (0.799) 1.935** (0.774) -0.796 (1.037) 1.243 (0.836) -5.462*** (1.858) -0.553*** (0.172) -0.643*** (0.211) 0.043 (0.144) 0.007 (0.197) -0.680*** (0.236) 0.032 (0.098) 1.327** (0.617) -0.614 (0.775) 0.034 (0.431) -0.335 (0.418) 0.008 (0.016) 0.504 (0.485) -3.535*** (1.048) 0.09 Unskilled Workers HR SR CR -0.344 3.199 0.383 (1.074) (2.132) (1.384) 0.476 3.031 0.508 (1.012) (1.957) (1.390) 0.884 0.206 3.712*** (0.959) (1.720) (1.189) 0.766 -0.699 -0.084 (1.334) (2.463) (2.032) -1.702 4.452** -1.366 (1.217) (2.113) (1.699) -6.962** 0.393 -8.146** (2.751) (5.473) (3.326) -0.835*** 0.144 -0.785*** (0.191) (0.483) (0.267) -0.529** -0.802 -0.699** (0.210) (0.503) (0.314) 0.239 0.669** 0.115 (0.187) (0.282) (0.221) 0.173 -0.268 -0.245 (0.243) (0.344) (0.389) -0.191 -0.755 -0.662 (0.270) (0.500) (0.411) 0.329** 0.103 0.473** (0.153) (0.289) (0.221) 0.975 -1.814 2.104* (0.844) (1.492) (1.102) -1.583* 1.669 -1.609 (0.959) (1.607) (1.265) 0.386 0.030 0.852 (0.556) (1.078) (0.762) -0.610 -0.472 -0.962 (0.543) (0.975) (0.742) 0.030 -0.040 0.013 (0.023) (0.044) (0.023) -0.262 0.749 -0.776 (0.616) (0.897) (0.799) -2.137 -5.350** -5.057** (1.397) (2.484) (2.200) 0.08 0.06 0.07 Skilled Workers HR SR CR -0.920 3.893** 0.971 (0.935) (1.933) (1.163) 0.106 3.543** 0.674 (0.924) (1.750) (1.087) -0.814 -2.326 -0.707 (0.817) (1.533) (0.997) 0.843 -1.480 -0.632 (1.119) (2.451) (1.551) 0.002 2.571 1.191 (0.952) (1.575) (1.215) -10.628*** 2.325 -8.612*** (3.003) (6.039) (2.778) -0.157 -0.174 -0.244 (0.190) (0.430) (0.221) -1.019*** -0.091 -0.634*** (0.245) (0.319) (0.235) 0.119 0.108 0.350 (0.207) (0.276) (0.350) -0.067 -0.215 0.202 (0.207) (0.379) (0.292) -0.694** -1.061** -1.056** (0.287) (0.476) (0.419) 0.001 0.175 -0.085 (0.147) (0.268) (0.164) 0.962 -0.598 1.537* (0.681) (1.266) (0.905) -0.290 1.548 1.061 (0.847) (1.516) (1.097) 0.001 -0.503 -0.469 (0.520) (0.894) (0.593) -0.116 0.328 -0.524 (0.491) (0.836) (0.585) 0.021 -0.027 0.017 (0.020) (0.041) (0.022) -0.110 0.846 0.792 (0.526) (0.822) (0.749) -1.392 -4.511* -2.968 (1.215) (2.366) (1.805) 0.14 0.03 0.07 Professionals and Engineers HR SR CR 2.683** 4.690** 2.532 (1.330) (2.221) (1.587) 0.239 3.561 0.580 (1.067) (2.171) (1.546) -0.109 -2.188 0.330 (1.180) (2.003) (1.558) 1.717 -0.381 3.838 (1.805) (3.320) (2.585) 0.461 3.522 1.126 (1.248) (2.393) (1.581) -6.520** 10.165** -0.004 (2.787) (4.501) (3.493) 0.464** -0.912** -0.436* (0.214) (0.354) (0.257) 0.476** -0.613 -0.296 (0.225) (0.390) (0.304) 0.400* -0.164 0.087 (0.236) (0.267) (0.280) 0.314 -0.217 -0.350 (0.271) (0.440) (0.390) -0.276 0.138 -0.079 (0.338) (0.554) (0.459) 0.018 0.180 -0.060 (0.147) (0.246) (0.172) -0.165 -0.983 0.370 (1.075) (1.691) (1.480) -1.421 1.062 -0.024 (1.304) (2.436) (1.595) -0.858 -1.352 -0.705 (0.706) (1.251) (0.902) 1.391* 0.403 1.030 (0.733) (1.202) (0.872) -0.031 -0.058 0.008 (0.025) (0.046) (0.029) 0.336 -1.841 0.431 (0.798) (1.202) (1.033) -2.756 -3.196 -8.337*** (1.791) (3.422) (2.656) 0.04 0.03 0.02 Appendix Table 9 (not intended for publication): Decentralization, Technological Change and Worker Turnover: First Di erences Index of Decentralization Investments in IT Main Investments in IT log (Employment) 43 Employment Share of Unskilled Workers Employment Share of Skilled Workers Share of Females Share of Foreigners Median Age of Employees Share of Part-Time Workers Revenues increased Revenues decreased Expected Revenues increase Expected Revenues decrease Share of Export State-of-the-Art Technology Constant R 2 HR 0.186 (0.349) -0.391 (0.835) 0.057 (0.729) -7.152*** (2.489) -0.373** (0.163) -0.532*** (0.202) 0.156 (0.143) 0.169 (0.161) -0.233 (0.189) -0.016 (0.110) 1.086* (0.561) -0.808 (0.704) 0.540 (0.372) -0.409 (0.376) 0.016 (0.016) 0.174 (0.373) -0.894 (0.867) 0.09 All Workers SR 1.966*** (0.648) 0.431 (1.928) 2.944** (1.457) 2.512 (5.530) -0.028 (0.386) -0.403 (0.269) 0.154 (0.191) -0.102 (0.252) -0.881** (0.397) 0.347 (0.239) -1.806* (1.066) 1.169 (1.283) -1.516* (0.853) 0.742 (0.771) -0.034 (0.040) 0.141 (0.717) -3.214* (1.931) 0.05 CR 0.868** (0.379) -0.813 (1.034) 1.199 (0.830) -5.582*** (1.829) -0.549*** (0.172) -0.640*** (0.211) 0.036 (0.144) -0.001 (0.198) -0.684*** (0.236) 0.033 (0.098) 1.392** (0.618) -0.622 (0.775) -0.002 (0.432) -0.309 (0.419) 0.011 (0.016) 0.516 (0.486) -2.768*** (1.002) 0.09 Unskilled Workers HR SR CR 0.371 2.337*** 1.557** (0.463) (0.819) (0.626) 0.748 -0.655 -0.138 (1.333) (2.460) (2.029) -1.687 4.463** -1.376 (1.212) (2.109) (1.687) -6.801** 0.215 -7.913** (2.687) (5.351) (3.247) -0.836*** 0.144 -0.786*** (0.191) (0.479) (0.268) -0.530** -0.805 -0.696** (0.211) (0.500) (0.316) 0.241 0.671** 0.113 (0.187) (0.280) (0.222) 0.174 -0.262 -0.251 (0.242) (0.345) (0.389) -0.192 -0.750 -0.668 (0.270) (0.499) (0.411) 0.329** 0.101 0.475** (0.152) (0.288) (0.221) 0.964 -1.849 2.144* (0.839) (1.497) (1.097) -1.586* 1.682 -1.625 (0.958) (1.604) (1.264) 0.371 0.085 0.786 (0.555) (1.075) (0.758) -0.602 -0.508 -0.918 (0.544) (0.973) (0.742) 0.030 -0.042 0.015 (0.023) (0.044) (0.024) -0.259 0.734 -0.758 (0.616) (0.896) (0.802) -1.727 -3.222 -3.508* (1.330) (2.490) (2.040) 0.08 0.06 0.06 Skilled Workers HR SR CR -0.528 1.933*** 0.356 (0.398) (0.702) (0.523) 0.846 -1.385 -0.607 (1.119) (2.449) (1.553) 0.026 2.591 1.191 (0.948) (1.579) (1.210) -10.524*** 1.926 -8.742*** (2.953) (5.874) (2.729) -0.159 -0.173 -0.243 (0.190) (0.425) (0.220) -1.021*** -0.097 -0.635*** (0.245) (0.317) (0.235) 0.122 0.111 0.350 (0.207) (0.276) (0.349) -0.063 -0.204 0.204 (0.207) (0.381) (0.292) -0.692** -1.050** -1.054** (0.287) (0.476) (0.419) 0.001 0.170 -0.087 (0.147) (0.266) (0.164) 0.930 -0.671 1.524* (0.679) (1.266) (0.902) -0.287 1.575 1.068 (0.845) (1.510) (1.095) 0.012 -0.385 -0.439 (0.522) (0.898) (0.593) -0.126 0.251 -0.543 (0.493) (0.837) (0.585) 0.020 -0.031 0.016 (0.020) (0.041) (0.022) -0.114 0.814 0.784 (0.526) (0.826) (0.749) -1.847 -2.844 -2.682 (1.211) (2.433) (1.774) 0.14 0.02 0.07 Professionals and Engineers HR SR CR 0.940 2.247** 1.173 (0.647) (0.969) (0.717) 1.752 -0.279 3.865 (1.805) (3.320) (2.581) 0.414 3.525 1.088 (1.247) (2.394) (1.573) -6.927** 9.651** -0.323 (2.737) (4.424) (3.426) 0.469** -0.909** -0.432* (0.213) (0.353) (0.256) 0.477** -0.618 -0.295 (0.225) (0.389) (0.304) 0.394* -0.163 0.082 (0.236) (0.266) (0.280) 0.310 -0.207 -0.353 (0.270) (0.439) (0.391) -0.274 0.149 -0.078 (0.339) (0.554) (0.459) 0.017 0.175 -0.061 (0.147) (0.245) (0.172) -0.121 -1.038 0.405 (1.070) (1.688) (1.472) -1.416 1.090 -0.020 (1.303) (2.438) (1.595) -0.834 -1.231 -0.687 (0.702) (1.255) (0.900) 1.380* 0.326 1.022 (0.730) (1.205) (0.870) -0.029 -0.061 0.009 (0.024) (0.045) (0.029) 0.331 -1.873 0.428 (0.795) (1.204) (1.028) -2.029 -1.278 -7.358*** (1.718) (3.338) (2.612) 0.04 0.03 0.02 Notes: See notes to Table 6. IZA Discussion Papers No. 556 557 Author(s) S. E. Black E. Brainerd G. C. Giannelli C. Braschi T. Bauer G. Epstein I. N. Gang B. R. Chiswick T. J. Hatton J. W. Budd J. Konings M. J. Slaughter W. J. Carrington P. R. Mueser K. R. Troske J. T. Addison W. S. Siebert T. Dunne L. Foster J. Haltiwanger K. R. Troske J. D. Brown J. S. Earle H. L. van Kranenburg F. C. Palm G. A. Pfann R. Hujer M. Caliendo D. Radi H. Lehmann K. Phillips J. Wadsworth H. O. Duleep D. J. Dowhan J. Haltiwanger M. Vodopivec T. K. Bauer S. Bender Title Importing Equality? The Impact of Globalization on Gender Discrimination Reducing Hours of Work: Does Overtime Act as a Brake Upon Employment Growth? An Analysis by Gender for the Case of Italy Enclaves, Language and the Location Choice of Migrants International Migration and the Integration of Labor Markets Wages and International Rent Sharing in Multinational Firms The Impact of Welfare Reform on Leaver Characteristics, Employment and Recidivism Changes in Collective Bargaining in the U.K. Wage and Productivity Dispersion in U.S. Manufacturing: The Role of Computer Investment The Reallocation of Workers and Jobs in Russian Industry: New Evidence on Measures and Determinants Survival in a Concentrating Industry: The Case of Daily Newspapers in the Netherlands Skill Biased Technological and Organizational Change: Estimating a Mixed Simultaneous Equation Model Using the IAB Establishment Panel The Incidence and Cost of Job Loss in a Transition Economy: Displaced Workers in Estonia, 1989-1999 Revisiting the Family Investment Model with Longitudinal Data: The Earnings Growth of Immigrant and U.S.-Born Women Worker Flows, Job Flows and Firm Wage Policies: An Analysis of Slovenia Technological Change, Organizational Change, and Job Turnover Area 1 5 Date 08/02 08/02 558 1 08/02 559 560 2 2 08/02 08/02 561 3 08/02 562 563 3 5 08/02 08/02 564 4 09/02 565 3 09/02 566 5 09/02 567 4 09/02 568 1 09/02 569 570 4 1 09/02 09/02 An updated list of IZA Discussion Papers is available on the center`s homepage www.iza.org. ...
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This note was uploaded on 01/31/2012 for the course POL 2107 taught by Professor Bourgault during the Spring '08 term at University of Ottawa.

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