The effects of the labor market environment on the costs to fill a vacancy: establishment-level evidence on search, adaptation and disruption costs

Transcription

1 The effects of the labor market environment on the costs to fill a vacancy: establishment-level evidence on search, adaptation and disruption costs Samuel Muehlemann a,b,c Mirjam Strupler Leiser a a University of Bern, Switzerland b University of California, Berkeley, United States c IZA Bonn, Germany January 28, 2014 PRELIMINARY VERSION Abstract This paper provides new empirical evidence on the magnitude of a firm s costs to fill a vacancy in Switzerland, and how these costs are associated with a labor market tightness. In 2009, average costs to fill a vacancy for a skilled worker in Switzerland amount about 16 weeks of wage payments. The main components of hiring costs are training expenditures and initially low productivity of new hires (53 percent), disruption costs (26 percent) and search costs (21 percent). We further find a significant association of hiring costs and the within-industry vacancy-unemployment (V/U) ratio for small firms, in the cross-section and over time. A one standard deviation increase in the V/U growth rate is associated with a 11 percent increase in average hiring costs for small firms. Moreover, exploiting the introduction of the Agreement on the Free Movement of Persons between Switzerland and the European Union as a natural experiment that facilitates a firm s access to the international labor market, we find a significant decrease in search and adaptation costs in occupations with a high importance of recruiting foreign skilled workers. JEL Classification: J32, J63, M53 Keywords: Hiring costs, search costs, adaptation costs, disruption costs, vacancyunemployment ratio, free movement of persons agreement This study is based on three administrative surveys from the years 2000, 2004, and The first survey was financed by the Commission for Technology and Innovation, and the second and the third survey by the Swiss Federal Office for Professional Education and Technology (OPET), both with the assistance of the Swiss Federal Statistical Office. This research has partly been funded by the Swiss State Secretariat for Education, Research and Innovation (SERI) through its Leading House on Economics of Education: Firm Behavior and Training Policies. We are grateful to participants at the Workshop on Labor Adjustment Costs 2012 (University of Bern) and the International Conference in Marbach for helpful comments. samuel.muehlemann@vwi.unibe.ch.

2 1 Introduction To fill a vacancy, a firm incurs direct costs for searching and interviewing suitable candidates and subsequent training activities, as well as indirect costs related to an initially lower productivity of new hires and disruption of the firm s production process. While the costs to fill a vacancy primarily differ by a firm s skill requirements, such costs may also depend on labor market tightness. Thus if skilled labor is scarce, a firm may have to increase its search effort to find a suitable job candidate, or accept a lower match quality at a given level of search effort. However, hiring lower quality workers may prolong the adaptation period, i.e., the time it takes for a new hire to become fully productive, require additional formal training, or increase disruption costs due to an increased need of informal instruction by co-workers. This assessment uses Swiss administrative establishment-level survey data for 2000, 2004 and 2009 with detailed information about a firm s costs to fill a vacancy. In addition, we match administrative vacancy and unemployment data at the industry level to the data, to test how changes in the labor market tightness affect a firm s hiring costs. Finally, we exploit the introduction of the Agreement on the Free Movement of Persons (AFMP) between Switzerland and the European Union as a natural experiment that facilitates a firm s access to the international labor market. We find significant effects of labor market tightness on hiring costs. First, both the level and changes in the vacancy-unemployment (V/U) ratios are negatively related to hiring costs in the cross-section and over time. A one standard deviation increase in the V/U growth rate is associated with a 11 percent increase in hiring costs for small firms. Second, we find that hiring costs in occupations where firms frequently hire foreign skilled workers were significantly higher before than after the introduction of the AFMP, while we find no effects for other occupations. However, the effects of labor market tightness are only statistically significant for small establishments with fewer than 50 employees. We also find evidence for a convex structure of search costs, i.e., increasing marginal search costs for additional hires. Again, those effects are more pronounced for small firms, but even for large firms we find statistically significant effects of the per-period number of hires 1

3 on search costs. The remainder of this article is organized as follows: Section 2 provides an overview of the relevant literature. Section 3 describes the data for our analysis. Section 4 discusses the estimation strategy. Section 5 contains the empirical analysis of the effect of labor market tightness on hiring costs. Section 6 concludes. 2 Relevant Literature The size and shape of labor adjustment costs play an important role in theoretical search models of the labor market (as surveyed in Eckstein and van den Berg, 2007; Rogerson et al., 2005; Rogerson and Shimer, 2011; Yashiv, 2007). However, there is still a lack of empirical evidence to justify the assumptions for such models. While search models often focus on a firm s and a worker s costs to find each other, i.e., the required search effort for firms to advertise a vacancy and the effort of an individual worker to find that vacancy, a firm s total costs to fill a vacancy also includes training costs and indirect costs related to initially lower productivity of new hires and costs that arise when new hires disrupt the work of other employees in the firm. Thus from this point on, we refer to search costs as those costs that arise until a successful match is accomplished, and we refer to hiring costs as the total costs to fill a vacancy, including those costs that arise after a new hire signs the contract with a firm Labor market tightness and hiring costs Recently, Davis et al. (2012) discuss the importance of the recruitment intensity to explain key outcomes of the labor market. They find differences in a firm s recruitment intensity during and after the recent Great Recession. Davis et al. (2012) show that the performance of search and matching models can be greatly improved if firms cannot only adjust the number of vacancies, but also choose their recruitment intensity. However, they emphasize 1 Thus our definition of hiring costs is similar to Silva and Toledo (2009), although they also consider separation costs in their definition of postmatch labor turnover costs, a cost factor that we exclude in this paper due to the lack of empirical data. 2

4 a lack of direct empirical data on recruitment intensity (Davis et al., 2012, p. 588):...this paper points to an important role for recruiting intensity in the cyclical relationship among hires, vacancies, and unemployment. Data limitations, however, require an indirect approach to the measurement of recruiting intensity per vacancy. There is a need to develop data that support more direct measures. Thus they suggest that the standard search models need to be extended by a firm s recruitment intensity. Our first contribution is to empirically test whether a firm s recruitment intensity changes in response to labor market tightness (i.e., the within-industry vacancy-unemployment ratio). Rogerson and Shimer (2011) make a similar point (p.652): Unfortunately we are unaware of any time series showing the number of workers (or hours of work) devoted to recruiting, and so the choice of f [the functional form] is somewhat arbitrary. To calibrate their search model, they rely on estimates from Hagedorn and Manovskii (2008) and Silva and Toledo (2009). However, Hagedorn and Manovskii (2008) rely on crosssectional evidence from Barron et al. (1997) who analyze US firms between 1980 and While the evidence in Barron et al. (1997) points toward small search costs (about 11 percent of weekly pay), other studies provide evidence for much higher search costs (e.g., Blatter et al find average search costs in the magnitude of 369 percent of weekly pay for intermediate skill-level positions in Switzerland, Muehlemann and Pfeifer (2012) report a corresponding share of 277 percent for Germany). Moreover, hiring costs not only include search costs, but also costs for initial formal (and informal) training and indirect costs for lost productivity until a new hire reaches full productivity. Accounting for adaptation costs, average hiring costs to fill a vacancy are in the range of one quarter of yearly wage payments in Switzerland and Germany (Blatter et al. 2012, Muehlemann and Pfeifer 2012). 2 Silva and Toledo (2009) use existing survey information on postmatch labor turnover costs for the US (Barron et al., 1997, Bishop, 1996, Dolfin, 2006) that account for workers not initially being fully productive. They find that accounting for such costs substantially improves the performance of their calibrated model. However, to our knowledge there is currently no survey information about hiring costs that allows to 2 While Hagedorn and Manovskii (2008) allow for wage costs of recruitment personnel to fluctuate over the business cycle, they do not allow for changes in a firm s recruitment intensity (as in Davis et al. 2012). 3

5 identify the effects of changes in the labor market tightness (e.g., changes in the vacancyunemployment ratio) on a firm s hiring costs. However, Stadin (2012) finds that local labor market conditions in Sweden significantly affect the probability of a firm to fill a vacancy thereby also affecting hiring costs, as longer vacancy durations are associated with increased expenditures on job advertisements and unsuccessful (and costly) interviews with job applicants. 2.2 Economies or diseconomies of scale in recruitment Many macroeconomic models typically assume a specific form of labor adjustment costs in regard to the number of hires, so that models fit aggregate data (Yashiv, 2007). Again, there is still an ongoing debate about the shape of such adjustment costs (i.e., whether they are linear, piece-wise linear, convex, or non-convex). Observing firms hiring many workers at once is interpreted as there being economies of scale in recruitment, whereas the opposite implies diseconomies of scales. Much of the evidence on worker flows indicates that there are economies of scale in recruitment, as firms seem to group hirings. 3 More recently, Cooper and Willis (2009) highlights the importance of disruption costs, i.e., new hires disrupting a firm s production process during the adaptation period. They find that non-convex disruption costs at the firm level can best explain aggregate fluctuations. Besides investigating workers flows to indirectly infer hiring costs, there is a small, but growing literature that analyzes direct empirical evidence on hiring costs. Manning (2011) shows that a convex structure of hiring costs implies that a labor market is monopsonistic. Direct evidence on hiring costs points towards a convex cost structure in Germany (Muehlemann and Pfeifer 2012), Switzerland (Blatter et al. 2012), the UK (Manning 2006) and the US (Dube et al. 2010), and linear adjustment costs in France (Kramarz and Michaud 2010). Our contribution to this literature is to investigate individual cost components and test whether they exhibit different costs structures. 3 The early literature on the shape of labor adjustment costs based on observing worker flows is surveyed in Hamermesh and Pfann (1996). 4

6 3 Data 3.1 Survey design and data To analyze the influence of the labor market tightness on a firm s hiring costs, we use three waves (2000, 2004 and 2009) of administrative and representative Swiss establishment-level survey data that includes comprehensive information on firms hiring costs and strategies. All three surveys were carried out by the Centre for Research in Economics of Education at the University of Bern and the Swiss Federal Statistical Office. 4 The Federal Statistical office sent a paper-based questionnaire to a sample of selected firms. 5 The firm s management or the human resource department supplied information on hiring costs for a specific occupation, randomly chosen by the Statistical Office dependent on the relative importance of this occupation for the firm. The data therefore corresponds to occupations that require a vocational degree at the upper secondary level. However, vocational upper secondary education is the most common education in Switzerland and represents roughly two-thirds of the Swiss workforce. The pooled sample consists of 8,353 firms (2,360 in 2000, 2,118 in 2004 and 3,875 in 2009) that hired at least one worker in the three previous years of the survey. 6 Firms provided detailed information on their hiring activities, particularly about search costs (costs for job postings, costs for external placement agencies/headhunters), interview costs (time spent for interviews), adaptation costs (training costs, reduced productivity for new hires), and disruption costs. 7 Moreover, the data includes information on the availability of skilled workers, difficulties in hiring employees from abroad and the importance of hiring skilled labor from abroad. Furthermore, we matched industry-level vacancy-unemployment ratios averaged for the three-year-periods from the Swiss State Secretariat for Economic Affairs 4 The surveys originally were carried out to estimate firm s expenditure on vocational education and training in Switzerland. 5 To account for stratified sampling the results in this paper are weighted by sampling weights. For more details on the sample design and the calculation of weights see Renfer (2002); Potterat (2003, 2006, 2011) , 1999 and 2000 for the survey in 2000; 2002, 2003 and 2004 for the survey in 2004 and 2007, 2008 and 2009 for the survey in Disruption costs are available only in the 2009 survey. 5

7 (SECO) to our data. This information provides a measure for the availability of skilled labor on the labor market. 3.2 Calculation of hiring costs Comprehensive information on the components of hiring costs in our data allows us to compute hiring costs C i for each firm i for Hiring costs consist of three parts: search costs s i, adaptation costs a i and disruption costs d i. 8 Adaptation costs a i reflect a reduced productivity of a new hire during the adaptation period t, and disruption costs d i arise when workers within the firm are disrupted in their productive work because they introduce the new hires in the production process. Hiring costs are defined as: Search costs can be written as: C i = s i + a i + d i (1) s i = v i + J i c ai + e i (2) where v i are costs for posting a vacancy. J i denotes the number of applicants per vacancy that are invited for a job interview and c ai is the cost for a single interview (time spent for the interview multiplied with wage). Finally, e i are costs for external placement agencies or headhunters. Newly hired workers need some time to reach full productivity, therefore firms have to bear adaption costs. These costs can be written as: a i = d ai (1 p i )w i + d ti w i + c ti (3) where d ai represents the days the newly hired worker is less productive than an average skilled worker within the firm. p i is the productivity of the newly hired worker and w i denotes to the wage. Some firms train workers in external courses during the adaptation period. These courses produce direct training costs c ti and costs resulting from the absence 8 Unfortunately disruption costs, that amount for more than a quarter of a firm s hiring costs are only available in

8 of the workers from the workplace (d ti is the number of days the newly hired worker is absent because of external training). The third component of hiring costs are disruption costs d i that are associated with new hires disrupting workers within the firm during the adaptation period. Workers within the firm might be incorporated in the adaption process of the new hires, providing the newly hired workers with relevant information on the production process. Disruption costs can be written as: d i = i ti w i (4) where i ti represents the number of hours workers in the firm spend with informal training to new hires, and w i denotes the wage. Disruption costs are only available in the 2009 survey, thus when analyzing hiring costs across time, we can only investigate search and adaption costs. 3.3 Descriptive Statistics Hiring Costs This section provides descriptive statistics on hiring costs of Swiss firms in 2009 as well as information on the labor market tightness in the last decade. Table 1 shows that firms in Switzerland in 2009 bear average hiring costs of Swiss Francs (CHF) 9 with a considerable variation between firms. The maximum hiring costs are above CHF while for some firms minimum hiring costs are virtually zero. On average, 53 percent of hiring costs are adaptation costs that mainly arise because of the initially low productivity of a new hire. Search costs account for 21 percent of hiring costs and mainly consist of personnel costs for interviews and costs for job postings. The remaining 26 percent of hiring costs are caused by new hires disrupting the production process, as they require informal training from other workers so that the latter cannot carry out their regular tasks (on average about 100 hours per new hire) In 2009, 1 CHF was roughly equal to 1 USD. 10 Table A1 in the Appendix shows descriptive statistics on the components of search costs and adaptation costs in the 2000 and 2004 survey. When comparing surveys across time we use costs in prices

9 Table 1: Descriptive statistics 2009 Variable Mean Standard Dev. Number of new hires Number of skilled workers Costs for job postings (v i ) Number of interviewed applicants per vacancy Time for job interviews in hours Personnel costs for interviews (Jc a ) Costs for external advisors/headhunters (e i ) Search costs (s i ) Duration of adaptation period in days (d ai ) Average decline in productivity (1-p) (in %) Training courses in days (d ti ) Direct training costs (c t ) Weekly wage payments for skilled workers (w i ) Adaptation costs (a i ) Disruption time in hours (i ti ) Disruption costs (d i ) Hiring costs (C i ) Observations Note: all costs in Swiss francs (CHF) 8

10 3.3.2 Labor market environment We use the vacancy-unemployment (V/U) ratio as a measure of labor market tightness. Figure 1 reports the V/U ratio, the subjective difficulties in finding skilled labor and GDP growth. 11 In 2000, about 50 percent of the firms reported having difficulties in finding skilled workers on the external labor market. In 2004, however, the economic downturn after the recession in the beginning of the new millennium still affected the labor market, and firms faced less difficulties finding suitable skilled workers in our second observation period ( ). In 2009, Switzerland faced yet another an economic downturn as a result of the financial crisis. However, compared to other countries, the Swiss economy remained relatively strong, and the GDP growth in the previous years caused a rather tight labor market for the period , the last period during which we observe firms recruiting new employees. Figure 1: Availability of skilled labor on the labor market The question we assess in this paper is to which extent labor market tightness influences a firm s hiring costs, and whether there are heterogenous effects across hiring cost components. We answer this question first making use of the variation of the conditions on the labor market. Second, we make use of the agreement of free movement of persons, 11 GDP change compared to the previous year. Source: /00456/00458/index.html?lang=de 9

11 which facilitated the firm s access to the international labor market. 4 Estimation strategy We are interested in the association between changes in labor market tightness and hiring costs. Thus we analyze the association between the growth in the within-industry V/U ratio and a firm s observed hiring costs in a particular occupation. 12 As we observe a firm s hiring behavior over a three year period, we define the growth rate of the V/U ratio as (U s /V s ) t,t 1 = [(V s /U s ) t (V s /U s ) t 1 ]/(V s /U s ) t 1, where t corresponds to a three-year period and (V s /U s ) t corresponds to the average V/U ratio in period t and industry s. To infer the structure of hiring costs, we follow Manning (2011) and assume that a firm s total hiring costs C take the form C = H β. The advantage of such a specification is to allow for both economies and diseconomies of scale in recruitment. A value of β > 1 implies diseconomies of scale, whereas there are economies of scale if β < 1. In our estimations we add further control variables for firm size and wages, as the hiring technology may differ between small and large firms, and because high-wage firms may be more attractive for job-seekers. Marginal hiring costs are given by C H = βhβ 1. Our estimates are based on average hiring costs per vacancy, i.e., the ratio of total hiring costs and the number of hires H, C H = Hβ 1. Thus as noted in Manning (2011), C H = β C H, allowing us to identify β based on regressing average hiring costs per vacancy on the number of hires in the period of interest. Thus we estimate the following regression: ln C i = λ + α(u s /V s ) t,t 1 + (β 1) ln H i + X iθ + ε i (5) where α denotes to the effect of labor market tightness on hiring costs, β the effect of the number of hires in the preceding three years on total hiring costs. Moreover, X i 12 We also ran regressions using the level of the V/U ratio, and found significant results. However, as the level of vacancies and unemployment may be affected by other unobserved (structural) factors within industries, we focus our analysis on the growth rate of the V/U ratio. 10

12 includes firm characteristics, in particular, firm size, the number of skilled employees in the chosen occupation, wage of skilled workers, occupation and region as well as the year of observation. To account for heterogeneity at the firm level, we subsequently estimate a panel fixedeffects regression model for a non-random subset of firms that can be identified in 2004 and Thus we estimate a panel fixed-effects regression of the form: ln C it = δ + ζ(u s /V s ) t + X itϑ + η it. (6) Third, we estimate a panel with aggregated average hiring costs within sectors (s), using fixed-effects to account for heterogeneity at the sector level: ln C st = κ 0 + µ(u s /V s ) t + πw st + υ st (7) where w st is the average wage in sector s. 14 Finally, we estimate a pooled regression to identify the effect of the free movement of persons agreement between Switzerland and the European Union (AFMP) on a firm s hiring costs. As only a relatively small fraction of firms actually recruit foreign skilled workers, we investigate the effect in occupations where firms predominantly hire foreign skilled workers in 2000, i.e., before introduction of the AFMP: ln C it = α 0i + ρ 1 AF MP t + ρ 2 Occup i + ρ 3 (AF MP t Occup i ) + X itγ + ω it (8) As the AFMP was introduced in 2002, we compare the hiring costs between 2000 and the subsequent two periods (AF MP t ). 15 We first identify occupations in which firms predominantly assign a high importance to recruit foreign skilled workers in 2000 (Occup i ). 13 Even though attrition may be non-random, the survey population was such that every firm with more than 50 employees in 2004 and every firm with more than 50 employees in 2009 was included in the population of firms that received a questionnaire, whereas smaller firms were subject to a randomized sampling procedure across sectors that was carried out by the Swiss Federal Statistical Office, cf. Potterat (2006) for details. 14 Industries are weighted according to the number of firms within industry. 15 where AF MP t is zero before the introduction of the agreement and one in the two subsequent periods 11

13 Second, we compare hiring costs before and after the introduction of the AFMP in those occupations where firms are most likely to recruit foreign skilled workers, compared to all other occupations (AF MP t Occup i ). 5 Results The presentation of the results is structured as follows: First we present the estimates for the 2009 sample, using the most complete definition of hiring costs that also includes disruption costs, a cost component that was not included in the 2000 and 2004 survey. We provide separate results for total hiring, search, adaptation, and disruption costs, and also for individual cost parameters. Second, even though we use cross-sectional data, we are able to identify a non-random subsample of firms for more than one period. We thus provide panel estimates for search and adaptation costs. Third, we show results for changes in aggregate hiring costs within sectors and how they are affected by changing labor market conditions over time. Finally, we discuss the effects of the AFMP on hiring costs. 5.1 Hiring costs and the vacancy-unemployment rate As the hiring technology is likely to differ between small and large firms (e.g., large firms typically have a human resources department), we provide separate results for firms with more (less) than 50 employees. While a human resources department may be able to exploit economies of scale when hiring a large number of new hires in a given period, large firms may also be more attractive for job applicants, not only through offering higher pay, but also by providing more career opportunities compared to small firms. The results in Table 2 show the effects of the V/U growth rate from the period in relation to the period , and similarly we estimate separate effects for changes in the growth of unemployment and vacancies. 16 For small firms the effects for the V/U growth 16 We also performed regressions using the level of the V/U rate, and we find statistically significant effects. However, as a number of unobserved factors may be correlated with the level of vacancies and unemployment in a particular industry, we do not report these results. 12

14 rate are positive and statistically significant throughout the different model specifications. Similarly, we find a negative and significant effect for unemployment growth, and a positive effect for vacancy growth when we use each of those variables separately in a regression (models 4 and 5). In our preferred specification (model 5 and 10) we control for state-fixed effects (as unemployment benefits may differ across region) and wages. For small firms, we find that a one standard deviation increase in the V/U growth rate (which corresponds to 0.62) is associated with a 11 percent increase in the average costs to fill a vacancy. 17 For large firms with more than 50 employees, however, we find no statistically significant effects. 18 As the association between hiring costs and the labor market tightness may arise for a number of reasons, we also analyze the different subcomponents of hiring costs. Table 3 provides estimates for the components of search costs for small (model 1-4) and large (model 5-8) firms. For small firms, a one standard deviation increase in the growth rate of the V/U growth rate increases overall search costs by 10.5 percent (model 1). However, this effect can primarily be attributed to higher expenditures on advertisement costs (i.e., to fill a vacancy, a one standard deviation increase in the V/U growth rate is associated with a 26.4 percent increase in expenditures for job postings). The coefficient on interview time is close to zero and not statistically significant. 17 We also estimate this regression using an alternative variable for labor market tightness, a subjective indicator variable reporting whether a firm has difficulties to find suitable skilled labor. The effect size of that variable is 22 percent, results are available upon request. 18 We also estimated a model with an interaction term of skilled worker wage and the V/U growth rate. However, the coefficient on the interaction term is not statistically significant. Nonetheless, we find that an increase in the V/U growth rate is positively associated with the skilled worker wage, but only for small firms with less than 50 employees (Table A2). Thus while a tight labor market also puts an upward pressure on wages, our results suggest that a tight labor market, conditional on wages, leads to an increase in a firm s costs to fill a vacancy both for low-wage and high-wage firms. Consequently, the coefficient on wages in the hiring costs regressions does not have a strictly causal interpretation. 13

15 Table 2: Labor market environment and hiring costs Small firms (<50 employees) Large firms (50+ employees) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) lnh lnh lnh lnh lnh lnh lnh lnh lnh lnh Within-industry (V/U)t,t *** 0.238*** 0.171*** (0.0337) (0.0386) (0.0369) (0.0792) (0.0537) (0.0467) Within-industry Vt,t *** (0.0439) (0.0703) Within-industry Ut,t *** (0.129) (0.179) ln Number of hires (0.0321) (0.0330) (0.0325) (0.0316) (0.0467) (0.0443) (0.0443) (0.0396) ln Number of skilled employees *** *** *** ** (0.0320) (0.0319) (0.0325) (0.0317) (0.0465) (0.0427) (0.0456) (0.0395) ln wage (weekly) 1.225*** 1.449*** (0.117) (0.157) employees 0.158*** 0.143*** 0.157*** (0.0488) (0.0483) (0.0497) (0.0515) 100+ employees (0.0760) (0.0752) (0.0746) (0.0641) Constant 9.228*** 9.282*** 9.327*** 9.329*** *** 9.550*** 9.547*** 9.552*** (0.0331) (0.105) (0.107) (0.105) (0.837) (0.129) (0.176) (0.173) (0.175) (1.099) Observations 2,604 2,604 2,604 2,604 2,604 1,271 1,271 1,271 1,271 1,271 R Note: Robust standard errors in parentheses. * p<0.1, ** p<0.05 *** p<0.01. Models 1-5 for small firms and models 6-10 for large firms. Columns 2-5 and 7-10 controlled for 4 sectors, 26 regions and 14 occupations 14

16 For large firms, the effect of the V/U growth rate is not statistically significant (model 5, Table 3), although the point estimate remains positive. Nonetheless, we find a statistically significant effect of the V/U growth rate on average interview time (model 7), indicating that large firms spend more time to evaluate job applicants in times of a tight labor market. Similarly, large firms are more likely to make use of external placement agencies in times of a tight labor market, indicating the a firm is more likely to poach workers from other firms when they are otherwise not available (model 8). Moreover, we find that the number of per-period hires significantly increases search costs, both for small and large firms, primarily through higher costs for job postings and longer interview times (large firms only), i.e., search costs are convex (marginal costs increase in the number of hires). However, while large firms spend more on job advertisements, we find a negative association between firm size and interview time, indicating that large firms are able to conduct interviews more efficiently, conditional on the number of hires (Table 3, model 7). Thus a human resources department may indeed allow firms to exploit economies of scales because of a more efficient screening process. Table 4 shows estimations for the components of adaptation costs in small (model 1-4) and large (model 5-8) firms. For small firms a one standard deviation increase in the V/U growth rate is associated with a 13 percent increase in average adaptation costs (model 1). We find that a positive association between the V/U growth rate and the productivity loss (i.e., the adaptation period adjusted for daily loss in productivity between a new hire and an experienced skilled worker), as a one standard deviation increase in the V/U growth rate increases the productivity loss in small firms by 14 percent. These results suggest that small firms hire new employees of lower ability that require a longer adaptation period. While the duration of formal training courses is slightly lower (but only marginally significant at the 10 percent level), the costs for formal training are slightly higher but do not statistically depend on labor market tightness. A shorter training duration during boom periods could be expected when firms upgrade their employees skills during a recession, thus some of the initial training may be postponed so that new hires can be integrated sooner in the firm s production process. Concerning the number of hires per period in small firms, we find a negative association between hires and adaptation costs, mainly be- 15

17 cause of a shorter adaptation period and lower formal training expenditures. Conversely, we find that firms with a large number of skilled workers in the hiring occupation have a longer adaptation period. Thus the results show that distinguishing between firm size, the number of employees in the hiring occupation, and the number of hires is important, as we find evidence for opposing effects. Moreover, in small firms we find a positive association between wages and adaptation costs, mainly because high-wage firms show a longer adaptation period, longer formal training and higher costs for formal training. These results suggest that high-wage firms may have higher skill requirements compared to low-wage firms, even within a certain occupation. For large firms, we find no statistically significant association between labor market tightness and adaptation costs (Table 4, models 5-8). Similarly, concerning the number of hires, we find no effect on overall adaptation costs. However, as for small firms, wages are positively associated with adaptation time, formal training duration and formal training costs, indicating that high-wage firms have higher skill requirements, even when controlling for firm size. Table 5 provides estimations for the components of disruption costs for small (model 1-4) and large (model 5-8) firms. Disruption costs mainly depend on skilled worker pay, but for small firms also on the tightness of the labor market, as a one standard deviation increase in the V/U growth rate leads to a 12 percent increase in disruption costs (Table 5, model 2). Thus our findings suggest that even though small firms spend more on search costs when the labor market is tight, they recruit hires with a lower match quality, as suggested by increased adaptation and disruption costs. Finally, wages impact disruption costs in two ways: first, a firm s wage level is positively associated with the disruption time (model 4), and second, an hour of disruption time is valued at a higher price in high-wage firms, so that a 1 percent increase in the wage level is associated with a 1 percent increase in disruption costs for small firms (model 2), and a 1.35 percent increase in disruption costs for large firms (model 6). Moreover, disruption costs are non-convex in the number of hires, a result that is in line with with Cooper and Willis (2009). 16

18 Table 3: Labor market environment and search costs Small firms (<50 employees) Large firms (50+ employees) (1) (2) (3) (4) (5) (6) (7) (8) lns lnadver lnitime Ext. agency lns lnadver lnitime Ext. agency Within-industry (V/U)t,t *** 0.426*** ** 0.159** (0.0520) (0.142) (0.0453) (0.0219) (0.0939) (0.231) (0.0676) (0.0676) ln Number of hires 0.194*** 0.549*** *** 0.184*** 0.334* * * (0.0430) (0.126) (0.0366) (0.0131) (0.0653) (0.182) (0.0475) (0.0475) ln Number of skilled employees ** * * *** *** (0.0400) (0.122) (0.0367) (0.0138) (0.0647) (0.194) (0.0475) (0.0475) ln wage (weekly) 1.163*** ** 0.154*** 1.281*** *** 0.730*** (0.157) (0.591) (0.148) (0.0479) (0.226) (0.779) (0.178) (0.178) employees 0.372*** 0.692*** 0.195*** ** (0.0676) (0.262) (0.0579) (0.0230) 100+ employees ** (0.120) (0.315) (0.0814) (0.0814) Constant *** ** ** (1.120) (4.274) (1.049) (0.339) (1.596) (5.484) (1.263) (1.263) Observations 2,604 2,604 2,604 2,604 1,271 1,271 1,271 1,271 R Note: Robust standard errors in parentheses. * p<0.1, ** p<0.05 *** p<0.01. Models 1-4 for small firms and models 5-8 for large firms. All columns controlled for 4 sectors, 26 regions and 14 occupations 17

19 Table 4: Labor market environment and adaptation costs Small firms (<50 employees) Large firms (50+ employees) (1) (2) (3) (4) (5) (6) (7) (8) lna lnprloss TrDur TrCost lna lnprloss TrDur TrCost Within-industry (V/U)t,t *** 0.290*** * (0.0447) (0.0696) (0.222) (88.82) (0.0725) (0.103) (0.209) (126.5) ln Number of hires ** ** (0.0414) (0.0692) (0.133) (60.67) (0.0575) (0.0900) (0.198) (99.87) ln Number of skilled 0.113*** 0.116* * employees (0.0402) (0.0690) (0.256) (78.57) (0.0528) (0.0728) (0.245) (139.9) ln wage (weekly) 1.224*** * 538.8*** 1.654*** 0.623* 1.656** *** (0.147) (0.224) (0.634) (206.5) (0.228) (0.326) (0.797) (437.6) employees (0.0598) (0.0900) (0.199) (88.99) 100+ employees ** *** (0.0986) (0.141) (0.346) (187.0) Constant *** ** ** * *** (1.051) (1.575) (4.558) (1441.0) (1.609) (2.323) (5.565) (3035.0) Observations 2,604 2,604 2,604 2,604 1,271 1,271 1,271 1,271 R Note: Robust standard errors in parentheses. * p<0.1, ** p<0.05 *** p<0.01. Models 1-4 for small firms, models 5-8 for large firms. All columns controlled for 4 sectors, 26 regions and 14 occupations 18

20 Table 5: Labor market environment and disruption costs Small firms (<50 employees) Large firms (50+ employees) (1) (2) (3) (4) (5) (6) (7) (8) lnd lnd lntime lntime lnd lnd lntime lntime Within-industry (V/U)t,t (0.0535) (0.0630) (0.0425) (0.0545) (0.0739) (0.0701) (0.0660) (0.0682) ln Number of hires (0.0708) (0.0492) (0.0518) (0.0495) ln Number of skilled employees (0.0640) (0.0484) (0.0469) (0.0439) ln wage (weekly) (0.176) (0.147) (0.231) (0.211) 100+ employees (0.0800) (0.0761) Constant (0.0630) (1.242) (0.0481) (1.041) (0.0940) (1.658) (0.0858) (1.515) Observations 2,604 2,604 2,604 2,604 1,271 1,271 1,271 1,271 R Note: Robust standard errors in parentheses. * p<0.1, ** p<0.05 *** p<0.01. Models 1-4 for small firms, models 5-8 for large firms Columns 2, 4, 6 and 8 controlled for 4 sectors, 26 regions and 14 occupations 19

21 5.2 Panel analysis As a robustness check, we first present a fixed-effects panel regression for a non-random sample of firms that we identify in the 2004 and 2009 survey. Moreover, we provide a fixed-effects panel regression for average hiring costs across industries for the years 2000, 2004 and As we observe only search and adaptation costs but no disruption costs in 2000 and 2004, we can only analyze the former two components of hiring costs in a panel setting. The panel results in Tables 6 and 7 for firms surveyed in 2004 and 2009 confirm the positive association between the V/U rate and search costs for small firms found in the cross-section. In particular, we find that a small firm increases advertisement expenditures and is more likely to use external placement agencies to find skilled workers in periods of a tight labor market. However, while we found a positive association between labor market tightness and adaptation costs for small firms in the cross-section (mainly because of increased productivity losses), we find no statistically significant association in the panel analysis (model 4). Thus unobserved firm-specific effects may drive our results in the cross-section. However, other parameters such as training duration and training costs show similar results compared to the cross-sectional analysis. For large firms we find a negative association between the V/U ratio and the productivity loss associated with the adaptation period, a finding that may be due to a firm wanting to integrate new hires as quickly as possible in their production process and possibly postpone non-essential training activities. When comparing average costs across industries from 2000 to 2009, we find that the V/U ratio is positively associated with search costs, but not with adaptation costs (Table 8), a finding that is in line with the panel estimates above. The advantage of running industry-level regressions is to make use of our full data set for all survey periods, while accounting for industry-fixed effects and the wage level of skilled workers. Controlling for the average skilled worker wage, a one standard deviation increase in the V/U ratio is associated with a 9.5 percent increase in within-sector average search costs. 20

22 Table 6: Panel estimates (2004 and 2009): small firms with <50 employees (1) (2) (3) (4) (5) (6) lnadv lnitime Ext.agency lnprloss TrDuration TrCost Within-industry (V/U)t 1.255*** ** (0.330) (0.151) (0.0637) (0.107) (0.434) (230.6) ln wage (weekly, 2000 prices) 2.856** (1.155) (0.671) (0.341) (0.558) (1.845) (1015.3) Constant * (8.210) (4.808) (2.438) (4.041) (13.25) (7284.7) Observations R F Note: Fixed effects estimates. Clustered standard errors on establishment level in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01 Table 7: Panel estimates (2004 and 2009): large firms with 50+ employees (1) (2) (3) (4) (5) (6) lnadv lnitime Ext.agency lnprloss TrDuration TrCost Within-industry (V/U)t *** ** (0.159) (0.0845) (0.0420) (0.0630) (0.316) (162.2) ln wage (weekly, 2000 prices) (1.058) (0.433) (0.187) (0.760) (1.927) (605.2) Constant *** (7.625) (3.071) (1.340) (5.404) (13.81) (4370.0) Observations R F Note: Fixed effects estimates. Clustered standard errors on establishment level in parentheses * p < 0.10, ** p < 0.05, *** p <

23 Summing up, we find robust evidence that labor market tightness affects a firm s search costs across all estimation strategies, while we find mixed evidence regarding a firm s adaptation costs. Table 8: Panel estimates by sectors (2000, 2004, 2009) (1) (2) (3) (4) (5) (6) ln(s+a) ln(s+a) ln(s) ln(s) ln(a) ln(a) (V s /U s ) t (0.0240) (0.0266) (0.0382) (0.0332) (0.0298) (0.0350) ln(average wage in sector s) (0.641) (1.047) (0.535) Constant (0.0295) (4.543) (0.0470) (7.428) (0.0367) (3.788) Observations R F Note: Fixed effects estimates. Standard errors in parentheses. Weighted for industry size. p < 0.10, p < 0.05, p < Swiss-EU Agreement on the Free Movement of Persons (AFMP) Labor adjustment costs are an important (non-wage) component of total labor costs. Thus high labor adjustment costs increase a firm s costs for labor in the production for goods and services. This is particularly important for firms that compete on international markets (e.g., export industry), as higher product prices due to higher labor costs may lower sales abroad (while local firms may be able to increase product prices without suffering from a loss in sales). A firm may ultimately move production abroad when there are not sufficient qualified workers available at a given wage and search effort. The Agreement of the Free Movement of Persons (AFMP) between Switzerland and the EU that started in 2002, with the aim to facilitate the hiring process for foreign employees. The agreement made it significantly easier for residents of the EU to work in Switzerland (and vice versa) and also included the recognition of professional diplomas that were obtained in the EU. Thus the AFMP was particularly helpful for those firms in Switzerland that recruited foreign skilled workers, as their recruitment effort was expected to fall significantly, particularly 22

24 in regard to obtaining work permits. Thus, the AFMP serves as a natural experiment, as facilitating the hiring process should result in lower costs to fill a vacancy. However, if the introduction of the AFMP lead firms that previously did not hire from abroad to take advantage of the new legal regulations and consequently hire foreign employees, then the AFMP would not be suitable for our analysis. Previous studies showed that the AFMP had little to no effects on wages and employment for domestic workers (Gerfin and Kaiser, 2010; Sheldon and Cueni, 2011), thus we do not expect significant effects of the AFMP on hiring costs for domestic workers. However, Table 9 shows that the fraction of firms that had difficulties to obtain work permits to hire foreign skilled workers decreased substantially from more than 12 percent in 2000 to 4 percent in 2004, and 3 percent in Table 9: Descriptives: Hiring employees from abroad Mean Std. Err Mean Std. Err Mean Std. Err Difficulties in obtaining work permits Share of firms hiring abroad Observations 2,360 2,118 3,875 Nonetheless, in the same period the firms subjective importance of hiring foreign skilled workers remained unchanged. The share of firms reporting that hiring foreign skilled workers is important or very important averages 12 percent. Therefore, we expect that the introduction of the AFMP, at least during the first years, mainly facilitated the hiring process of those firms that already hired foreign skilled workers before the introduction of the AFMP. Thus, we would expect that hiring costs for foreign skilled workers decreased after the introduction of the AFMP, an effect that is most likely visible in firms that put a high importance on recruiting foreign skilled workers. Hiring foreign workers is predominantly important for export-oriented firms that employ skilled workers in technical occupations (engineering, IT) as well as firms in the construction sector (mason) or food industry (cooks). Table A3 shows that firms employing workers in those occupations were more likely to assign a high importance to recruiting 23

25 Table 10: Hiring costs before and after AFMP Small firms Large firms (1) (2) (3) (4) lns lna lns lna AFMP x Occupation recruited from abroad *** *** (0.128) (0.164) (0.142) (0.163) AFMP * (1.572) (2.855) (2.635) (3.049) Occupation recruited abroad in ** 0.399*** (0.105) (0.134) (0.0915) (0.127) Within-industry (V/U) t 0.104*** * 0.118*** (0.0225) (0.0511) (0.0399) (0.0610) AFMP x (V/U) t ** ** (0.0342) (0.0572) (0.0593) (0.0736) ln wage (weekly, 2000 prices) 1.573*** 1.015*** 1.838*** 1.527*** (0.168) (0.370) (0.289) (0.335) AFMP X ln weekly wage ** (0.222) (0.406) (0.356) (0.429) ln Number of skilled employees * 0.128** (0.0341) (0.0530) (0.0537) (0.0621) ln Number of hires 0.342*** *** * (0.0446) (0.0763) (0.0620) (0.0911) Constant *** ** (1.182) (2.588) (2.197) (2.398) Observations 5,154 5,154 3,199 3,199 R Note: Robust standard errors in parentheses. Additional controls: Canton, Canton x AFMP, Firm size, Firm size x AFMP. * p < 0.10, ** p < 0.05, *** p <

26 foreign skilled workers in 2000 compared to all other occupations (Coefficient Occupation recruited abroad in 2000 ). However, the firm s importance of hiring foreign skilled workers did not change significantly after the introduction of the AFMP, neither in those occupations where firms already hired foreign workers, nor in other occupations. As the hiring behavior of firms did not significantly change as a result of the AFMP, we can test whether the AFMP affected the costs to fill a vacancy in those occupations where firms place a higher importance of recruiting foreign skilled workers. Table 10 shows that search costs decreased significantly after the introduction of the AFMP in occupations firms place high importance to the recruitment of foreign workers compared to all other occupations, however, only for the subsample of small firms with less than 50 employees. Unfortunately, we do not have information about the exact fraction of foreign hires nor do we observe hiring costs separately for domestic and foreign hires. Thus large firms may still benefit from decreasing hiring costs for foreign hires, which, however, would only show up in average hiring costs if the fraction of foreign hires was sufficiently high. Interestingly, the effect of the V/U rate on search costs changed after the introduction of the AFMP. Thus while search costs in 2000 were significantly higher in those industries with a high V/U rate, the coefficient on the interaction term of AFMP (V/U) rate almost offsets the baseline effect, an indication that firms may have recruited a higher fraction of foreign skilled workers in response to a tight domestic labor market. 6 Conclusions In this paper we analyze the effect of the labor market tightness on a firm s costs to fill a vacancy. Using representative establishment-level data for Switzerland, we find that these costs amount on average to about 16 weeks of wage payments. While search costs only account for 21 percent of the costs to fill a vacancy, most of a firm s hiring expenses occur after the signing of a contract. Adaptation cost (i.e., training costs and initially low productivity of a new hire) account for 53 percent, whereas disruption costs (i.e., productivity loss that occurs because other workers cannot fulfill their regular tasks as they provide informal training to new hires) account for 26 percent of total hiring costs. 25