Social Networks, Job Search Methods and Reservation Wages: Evidence for Germany

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1 Social Networks, Job Search Methods and Reservation Wages: Evidence for Germany Marco Caliendo Ricarda Schmidl Arne Uhlendorff Working Paper February 1, 2010 Abstract In this paper we analyze the relationship between social networks and job search behavior of unemployed individuals. It is assumed that networks convey useful information in the job search process so that individuals with larger networks should experience a higher productivity of informal search. Hence, job search theory suggests that individuals with larger networks use informal search channels more often than others and substitute from formal search towards informal search. Also, due to the increase in search productivity it is likely that individuals set higher reservation wages. We investigate these relations in an empirical analysis, using the IZA Evaluation Dataset. This extensive data set contains information on unemployed individuals interviewed shortly after their entry into unemployment. Our findings confirm theory in that individuals with larger networks use informal search channels more often and substitute formal search intensity for informal search. We find that informal search is mainly considered a substitute for passive, less cost intensive search channels. The effect of networks on reservation wages seems not very pronounced for the network indicators used, however strong differences exist for individuals with heterogeneous educational attainment. In the second step of our analysis we relate these findings to labor market outcomes up to one year after entry into unemployment. Keywords: JEL: Job Search Behavior, Unemployment, Social Networks J64 We thank the German Research Foundation (DFG) for financial support of the project CA 829/1-1. The usual disclaimer applies. IZA/Bonn and IAB/Nuremberg, caliendo@iza.org. IZA/Bonn, schmidl@iza.org IZA/Bonn, DIW/Berlin, uhlendorff@uni-mannheim.de

2 1 Introduction Social Networks are an important source of information in the labor market and many workers find jobs through friends and relatives. Seminal studies by Rees (1966) and Granovetter (1995) show that a considerable part of the working population relies on personal contacts to obtain information about job offers. According to a recent study by Franzen and Hangartner (2006) around 44% of the workers in the U.S. and 34% of the workers in Germany have found their jobs through social networks 1. A common explanation for the extensive use of informal search channels is the idea that informal contacts convey superior information in terms of quality and reliability. For example, it is assumed that informal job contacts may reduce uncertainty about the job match quality and employers may consider referrals as more reliable than direct applications, see e.g. Montgomery (1991). In terms of labor market outcomes this mechanism may lead to higher wages and longer job tenure. However, the empirical evidence in the literature is rather mixed and the findings range from lower or no difference to higher wages for individuals who found their jobs via their social network, compare e.g. Ioannides and Datcher Loury (2004) or Mouw (2003) for extensive overviews. In this paper we provide direct evidence on the relationship between social contacts and job search behavior of unemployed individuals. In contrast to many previous studies focussing on realized search outcomes we directly link the social network of the unemployed to the choices they make in the job search process. If the assumption that networks convey relevant job-information holds, it is likely that well-connected individuals receive more job offers through their network than individuals with lower levels of social contacts. In turn, if networks do play a role in the job search process it is expected that individuals adjust their search behavior contingent on the network they possess. Our data allow us to observe the job search process of unemployed in detail, i.e, we observe the types of search channels they use, their intensity of search, as well as their reservation wage. In our analysis we link these variables to social networks measured as the number of close friends and the contact frequency to former colleagues. In the context of job search, several studies analyze the use of multiple search 1 These numbers are based on the International Social Survey Program (ISSP)

3 channels and its impact on labor market outcomes, see e.g. Holzer (1988), van den Berg and van der Klaauw (2006) or Weber and Mahringer (2008). Based on job search models with differential search channels these studies derive implications from changes in productivity or costs of search on job search behavior and corresponding labor market outcomes. Following this literature we distinguish between two different search channels, formal and informal search. Formal search is defined as search via newspaper ads, the internet, the public employment office, etc., while informal search refers to search via friends and relatives. We discuss potential effects of an exogenously determined network size on job search efforts and reservation wages within a theoretical framework which is closely related to the above mentioned studies. Our empirical analysis is based on a unique data set, the IZA Evaluation Data Set (see Caliendo et al., 2009, for details). This data set is based on around 17,000 individuals who had become unemployed between late 2007 and early The data provide detailed information about search behavior, reservation wages, social networks and different psychological traits including locus of control. The interviews were conducted around 6 weeks after entering unemployment. The fact that all individuals are interviewed at the same point in time during their unemployment spell reduces the problem of potential reverse causality, which is a typical concern of studies on the relationship between concepts like social networks or non-cognitive skills and labor market outcomes. 2 Another concern is that the size and the type of the network might be correlated with unobserved heterogeneity which additionally has an impact on the job search behavior. In order to control for this potential selection bias one would need a source of exogenous variation in the network size, which is not available in our case. However, since we have a rather informative set of observable characteristics including personality traits like openness and extraversion and previous labor market outcomes, exploring the relationship between networks and job search behavior conditional on observable characteristics seems to be a reasonable strategy. Our results show that search behavior is indeed influenced by the presence of social contacts. In particular, we find evidence that individuals with larger networks substitute informal search for formal search effort. This is especially the case 2 Alternatively one could model the interdependencies between net work formation and employment dynamics explicitly, see for example Bramoulle and Saint-Paul (2010). For this approach one needs panel data in order to explore individual variation over time. 2

4 for passive formal search methods, i.e., informational sources that generate rather unspecific types of job offers at low relative costs. In line with the predictions of the theoretical model we also find small positive effects of an increase in networks on reservation wages. Sensitivity Analysis indicates that the benefit of informal search varies with labor market status of individuals. Here, we find that networks are least important for individuals who search for part-time employment, and individuals with low levels of educational attainment. The highest benefit of social networks is found among high skilled individuals and those who search for full-time employment. Here, a high contact frequency to former colleagues is associated with a reduction of formal search by up to one third and an increase in reservation wage at about 2% to 6.5%. The outline of this paper is as follows. Section 2 presents the theoretical model, while Sections 3 describes the IZA Evaluation Data Set in more detail, specifies the sampling strategy for the estimation sample and motivates the choices of the network information used. In Section 4, we present our estimation strategy and the results, Section 5 concludes. 2 Theoretical Framework and Empirical Findings Many studies have shown that unemployed workers use multiple channels of job search and that the majority of unemployed workers make use of informal channels. In the standard job search model with endogenous job search effort unemployed individuals make use of one general search channel and choose an optimal search effort s and a reservation wage φ in order to maximize their utility (see e.g. Mortensen, 1986). The reservation wage defines the stopping rule and corresponds to the wage offer for which the present value of ongoing search equals the present value of accepting the wage offer, i.e. every wage offer above φ will be accepted. In the analysis of job search with multiple search channels it is usually assumed that the choice of a particular search channel and the channel specific search effort is determined by the relative efficiency of that channel in generating acceptable job offers. 3 An early example for a study on the determinants of the choice of search methods 3 For a theoretical equilibrium analysis on the effects of two different search channels on labor market outcomes see e.g. Mortensen and Vishwanath (1994). In their model they show that those workers with a higher probability of obtaining wage information through employed contacts earn more in equilibrium. 3

5 and its effectiveness is Holzer (1988). Using a sample of unemployed youth who are interviewed at different points in time during their unemployment spell his findings suggest that the main determinants of search channel use are the relative costs in terms of time spent on a particular channel for generating job offers and acceptances. Blau and Robins (1990) analyze the differences between job search outcomes for unemployed and employed individuals. They find differences in the job offer arrival and acceptance rates for different search channels. Both studies find evidence for informal search channels being the most efficient channels in terms of relative costs and benefits, respectively, and conclude that this might explain their wide-spread use. Weber and Mahringer (2008) more recently conducted a similar analysis based on a sample of unemployed workers in Austria. They find that the choice and the benefits of particular search channels vary by individual characteristics like education and sector of the previous job. However, none of these studies investigates correlations between network indicators and the choice of job search methods. An example for a study analyzing the impact of the social networks on job search channels and search outcomes is Wahba and Zenou (2005). They use population density as a proxy for the size of social networks and find based on cross-sectional data for Egypt that the probability to find a job through friends and relatives increases and is concave with population density. In a structural analysis on the differences of formal and informal search, Koning, van den Berg, and Ridder (1997) find no evidence for differences in the wage offer distributions between formal and informal search channels, but that there is an increased exit rate from unemployment for the use of informal channels compared to formal channels. However, they do not find any significant effect for a social network indicator reflecting the number of friends on the exit rate from unemployment to employment via informal channels. Based on a social experiment, van den Berg and van der Klaauw (2006) show in the context of active labor market policies that unemployed workers shift from informal search effort to formal effort if they are monitored on their formal search level. They find evidence that these one-sided monitoring activities may lead to inefficient substitution effects, especially for well qualified individuals. In summary, these studies indicate that the choices of specific search channels are indeed driven by cost-benefit considerations. Accordingly, if the hypothesis that social networks give access to additional information holds, it should be the case that individuals with higher levels of networks experience have a higher productivity of 4

6 their informal search channel and thus adjust their job search behavior. In the following we discuss the theoretical implications of the size of social networks on the individual choice of search channels, the corresponding search efforts and the reservation wage. Our model is closely related to the theoretical model of job search with endogenous search effort and two search channels by van den Berg and van der Klaauw (2006). We focus on two search channels, formal (f) and informal (n). An unemployed worker chooses optimal levels of formal search effort s f and informal search effort s n, the sum of both equals the overall search effort s, s = s f + s n. Each search channel has a channel specific job offer arrival rate λ i, i = f, n that is a function of the search effort devoted to it. We assume that the job offer arrival rate is strictly concave in search effort for both search channels. In our model the productivity of the informal search depends positively on the size of the network. by λ n0 (s n )f(n). n, δf(n) n The job offer arrival from informal search λ n (s, n) is given f(n) is an increasing function of the magnitude of the network > 0, which is multiplied with the baseline arrival rate which depends positively on search effort s n. Furthermore there is a cost c of search that increases with the search effort invested. We assume that c = c(s n, s f ) is convex in s n and s f. In addition to that we assume that δ 2 c/δ(s f )δ(s n ) > 0, which captures that formal and informal search are similar activities. The marginal costs for informal search are higher, the more time one invests in formal search, and the other way around. In each period of length dt, the individual receives a job offer with probability (λ f + λ n )dt. Each wage offer is characterized by a wage w, randomly drawn from the wage offer distribution F (w), which is the same for both search channels. If an individual receives an offer, he has to decide whether to accept the offer with wage w or to continue searching. If he accepts the offer, his utility will be equal to the present value V e (w) of working at wage w. His present value of continued search given his expectations of future job offers is V u. In order to maximize his utility the worker is therefore going to continue search until V e (w) V u. It can be shown that the individual is indifferent between searching and accepting if the wage offer w is equal to his reservation wage φ = ρv u, where ρ denotes the rate of discount. Hence, in each period the worker maximizes his current and expected utility by choosing an optimal amount of search effort in each search channel and the reservation wage 5

7 φ. The optimal reservation wage is given by: [ ] max φ = b c(s f, s n ) + (1/ρ)(λ f (s f ) + λ n (s n, n)) s n,s f (w φ)h(w)dw, (1) with b representing the amount of unemployment benefits. We are interested in the impact of an increase of the network size n on the optimal levels of the reservation wage φ and the search efforts s f and s n. Since we assume that the network size is exogenously determined and that it enters the optimization problem only via a change in the job arrival rate of the informal search channel, this model is very similar to the one discussed in van den Berg and van der Klaauw (2006). In their theoretical model, counseling by the caseworkers facilitates search along the formal channel. They are interested in the effects of a change in the amount of counseling on the job search behavior and show that under several reasonable assumptions an increase in the amount of counseling increases the reservation and the effort spent for formal search, while the unemployed reduce the effort for informal search. For the detailed proof see van den Berg and van der Klaauw (2006). We can directly adopt their theoretical results to our model. This implies that we expect a higher reservation wage for individuals with a larger network (δφ/δn > 0), a positive impact of the network size on informal search (δs n /δn > 0) and a negative impact on the effort spent for formal search (δs f /δn < 0). Intuitively, an increase in network size leads to an increase in the overall search productivity, which leads for a given amount of search effort to an increase in the value of search. The present value of unemployment increases, which implies an increase of the reservation wage. In order to optimally allocate the search effort, an increase in the productivity leads for a given amount of overall search effort to a redistribution from the effort spent on formal search to the effort spent for informal search. φ 3 Dataset, Search Behavior and Social Networks We are going to test the hypothesis of our model empirically, using observable characteristics of the individuals network as indicator for the efficiency of search via the informal search channel. The next section provides information of the Dataset used and explains the job search and network measures in more detail. 6

8 3.1 IZA-Evaluation Dataset The data we use in our empirical analysis are drawn from the IZA Evaluation Dataset that consists of an inflow sample into unemployment from June 2007 to May The dataset is based on two components, an administrative part that contains extensive information on past labor market experience, and a survey part. The key feature of the survey data is that individuals are interviewed shortly after they become unemployed. They are asked general questions about their socio-demographic background, their employment history, as well as a variety of non-standard questions about attitudes and expectations (see Caliendo et al., 2009, for details). The sampling of the data is restricted to individuals who are 17 to 54 years old, and who receive or are eligible to receive unemployment benefits under the German Social Code III. From the monthly unemployment inflows of approximately 206,000 individuals in the administrative records, a 9% random sample is drawn which constitutes the gross sample. Out of this gross sample each month a representative samples of approximately 1,450 individuals is interviewed, so that after one year 12 monthly cohorts are gathered. Altogether this amounts to a number of 17,396 realized interviews with an average time lag of six weeks between the unemployment registration and the interview. In the empirical analysis we estimate the effects of social networks on the search behavior of newly unemployed workers. We therefore restrict the sample to individuals who are still unemployed when interviewed and who are currently actively searching for employment. That is, we exclude individuals who have found a job already, who search for self-employment or who do not search for other reasons. We also exclude individuals who are below the age of 25 and who state that they are in parallel looking for an apprenticeship and employment. In order to get comparable individuals in terms of their network composition we further exclude individuals who state that they did not have colleagues in some earlier employment relationship. From this preliminary sample of about 9,383 individuals, compare Table (1), we further exclude the lowest and highest percentile of the reported hourly reservation wage and the search intensity as well as individuals with missing values for any key variables. This leaves us with a sample size of 7,922 individuals. Table (2) provides some descriptive statistics of the estimation sample used. The average unemployed in our sample is 36 years old and equally likely to be male or female. 68% of the unemployed live in West Germany with 5% not having the Ger- 7

9 man citizenship. Comparing these sample figures with official unemployment data in Germany, it can be seen that the sample selection process did not affect the representativeness of our sample (compare Bundesagentur für Arbeit (2007)). Regarding the education level, the majority of individuals have a medium level high school degree and 72% have completed at most some type of professional training. Before entering unemployment the majority of individuals was in regular employment (67%). Complementary to the standard socio-demographic questions, individuals were asked to answer questions regarding their locus of control, which is a generalized expectancy about internal versus external control of reinforcement (Rotter, 1966). Furthermore the data contain information on personality traits as measured by the Five Factor Model. Using factor analysis, the Five Factor Model identifies five different distinct personality dimensions based on self-reported personal characteristics 4. A large array of literature has shown that noncognitive skills and personality traits have predictive power in models on labor market outcomes, see for example Borghans, Duckworth, Heckman, and Weel (2008) for an overview. Therefore it is important to control for them in our empirical analysis later on. See Table (2) for the distribution of a selection of the Big Five items and and the locus of control. 3.2 Defining Social Networks For the purpose of our analysis we are interested in exogenously given networks that the individuals might employ in order to get relevant information in the labor market. In particular it is required that the network size or strength is not affected by the current unemployment spell. Generally, several endogeneity issues might arise that have to be considered when using network parameters in the job search equations. In the case of a dynamic endogenous selection process the network of the unemployed is affected by the unemployment spell or the unemployment duration. First of all, it might be the case that the network of relevant social contacts is diminished in the course of unemployment, as the change in circumstances leads to the dissolution of some ties. This implies a potential problem of reverse causality, as the unemployment spell causes a change in network size. As argued above, we expect 4 The five dimensions identified are often summarized under the acronym of O-C-E-A-N, representing, Openness, C onscientiousness, E xtraversion, Agreeableness and N euroticism. 8

10 that the set-up of the data prevents the selection of this type as individuals are all interviewed at a similar point in time relative to their entry into unemployment. Since interviews were conducted shortly after the beginning of the unemployment spell, we also expect that any effects on network composition are comparably small. Another type of dynamic endogeneity is characterized by individuals strategically increasing their social network in order to increase the probability of receiving informal job information, compare e.g. Galeotti and Merlino (2008). In terms of our model of job search, this would imply that the measure of informal search effort should additionally capture the effort devoted to the enlargement of the social network. However, as this is also linked to the magnitude of the network the individuals had before entering unemployment, it is difficult to disentangle the effects of the existing and the new network on the job search process. In order to avoid this problem, we therefore restrict our analysis to networks that had already been established before individuals entered unemployment and that were presumably not altered in the course of unemployment. In the context of job search, the most relevant information on networks contained in our data are the questions regarding the existence of friends and colleagues. Clearly these two groups of contacts are not conclusive in depicting the whole of the social network of individuals, and are thus only to be seen as a approximation. In the following we will focus on these two types of networks for two reasons. First, they are highly likely to convey potentially relevant job-information, which makes them relevant for our analysis. Second, we are able to extract information that is most likely not influenced by the entry into unemployment, which is important in order to avoid the above-mentioned endogeneity problems. In particular we will approximate the network of friends by the number of close friends as it is not probable that many close friendships have been built up or were destroyed in the short time interval between entry into unemployment and interview date. With respect to the information on colleagues, we use the contact frequency to colleagues before the individuals entered unemployment. As this refers to characteristics of the network that had been established before entry in unemployment it is also very likely to be unaltered after the unemployment spell. We aggregate the information to reflect the individual s degree of interaction with the respective social network and thus his potential access to valuable labor market information. For both measures, we use a three-level scale of the network character- 9

11 istics 5, differentiating between low, medium and high levels of the respective network indicator. 6 Table (4) presents descriptives of the scaled network information. It can be seen, that the average unemployed considers three to five individuals to belong to their circle of close friends. Regarding the information on former colleagues, the Table also shows that the average unemployed had a medium contact frequency with their colleagues, whereas 19% have had a highly frequent contact with their colleagues. In order to compare the relative importance of the respective network indicators, we create an additional variable that captures the eight different combinations of low, medium and high friends and colleague-scalings. This partition is insightful in that it provides evidence on the question on whether the respective network indicators are addible in their effects, or if there exists overlap between the two groups that might lead to a substitution of one network indicator for the other. Table (4) depicts the frequency distribution of the different combinations and shows that each cell contains sufficient observations for an informative investigation. 3.3 Search Behavior The key variables of our analysis are the determinants of individual job search behavior, represented in particular by the reservation wage, the choice of informal search channels and the search intensity of formal search. The survey question regarding the use of particular search channels is designed as multiple choice answer, with individuals choosing one or more different types of search channels that were used since their entry into unemployment. They were offered ten alternatives, including informal search via relatives, friends and other contacts. Compare Table (3) for an overview of the search channels proposed. It can be seen that contacting friends and acquaintances is one of the most commonly used methods when searching for employment, with 85% of individuals using it. Other, similarly important sources of information are job advertisement posts in newspapers and search via the internet. In order to measure search intensity devoted to formal search we use the number of formal search channels used, a method proposed by Holzer (1988). Table (3) shows that the unemployed use on average four formal search channels, with values ranging 5 We obtain the three-level scale by grouping together the middle values of a quartiledecomposition of the friend distribution, and the middle-values of the four-level scale of contactfrequency, respectively. 6 Sensitivity checks of the regression results indicate that the low-medium-high scaling of the network variable is not decisive for the results we obtain, it just serves the purpose of convenience. 10

12 from none other than informal sources and all other channels. When we are analyzing substitution effects between formal and informal search channels, it is likely that some sources of information are considered more as substitutes to informal channels than others. In order to identify the extent to which certain channels may be considered as substitutes by the unemployed, we make the additional distinction between active and passive formal search. We define active search methods as those that individuals would consult if they wanted to solicit specific pre-defined types of jobs, rather than reacting to job opportunities that come up at random. In particular we attribute posting advertisements in newspapers, the direct application at companies as well as the use of private agents without agency vouchers to active search measures, and all other formal channels as passive search. Table (3) shows that the average individual uses three passive measures, and only one active source of information. Table (5) provides a descriptive overview of the differences in unconditional job search behavior for the different network categories of friends and former colleagues. Without controlling for any personal characteristics it can already be seen, that the use of informal search channels and the expected success of search increase unambiguously with the extent of the network indicator. The most significant differences seem to persists between low and medium levels of friends and colleagues, an additional increase in networks size from medium to high does not seem to be correlated with any changes in job search behavior. The reservation wage seems to be highest for the medium levels of the network indicators, the same holds true for the search intensity invested in formal search channels. Hence, an initial assessment of the relationship between networks and job search behavior indicates that differences exist. The magnitude and direction of these differences however will be tested in the empirical analysis in the next section. 4 Estimation and Results 4.1 Empirical Strategy In order to assess the impact of social networks on the job search process, we integrate the coded network information in a structural regression models of the type: Y i = α X i + (δ 1jN 1ji + δ 2jN 2ji ) + µ Z i + ε i, (2) j=l,m,h 11

13 with Y i denoting the individual parameters of job search behavior. These are measured by the reservation wage, the use of informal sources of information and the number of formal search channels used, jointly and divided by active and passive search. The regressor vector X i includes relevant socio-demographic characteristics of the individual (e.g. age, sex, nationality and education), as well as extensive information of past labor market experience (e.g. the last wage obtained, measures for general labor market attachment and the type of employment held before becoming unemployed). N 1i and N 2i are low-medium-high scaled dummies, representing the extent to which the individuals is connected in terms of the respective network type. The network types considered are as depicted in the previous section, the number of friends, as well as former contact frequency to colleagues from previous spells of employment. Additionally, we include a set Z i of observable personality traits as captured by the psychological measure of internal locus of control and the Five Factor Modell 7. By controlling for the individuals personality as, e.g., the degree of extraversion, neuroticism, etc., we are able to remove potential bias of δ 1 and δ 2 arising from personality traits that simultaneously affect job search behavior and the network formation. In particular, if we assume that these factors affect labor market success and network formation in the same way, neglecting them leads to an upward bias of δ 1 and δ 2 and thus an overestimation of the effects of networks in the regressions for reservation wage. On the other hand, if individuals with a higher locus of control tend to search more intensely, as suggested by Caliendo, Cobb-Clark, and Uhlendorff (2009) while possessing a larger network of friends, we would also get upward biased coefficients in the regression of formal search. If our model correctly predicts a reduction of formal search however, omission of Z i would lead to an underestimation of the true effect of networks. Hence, by controlling for Z i we thus ensure that Cov(N i, ε i ) = 0. In order to assess the magnitude and correct sign of the potential bias we will in the following application conduct the regression with and without the Z i and compare the results. 4.2 Results Table (6) depicts the marginal effects of the least squares regression analysis, incorporating the low-medium-high scaled network indicators of friends and colleagues 7 Due to problems in the data collection process we are only able to observe 10 of 15 questions asked in the Five Factor questionnaire. We include all 10 questions. 12

14 simultaneously 8. Continuing the line of thought in the previous section, we start our analysis by assessing the bias arising from omitting the usually unobservable personality traits. The upper part of the table displays the results of the regressions conducted without the incorporation of personality traits - in the lower part they are included. Comparison of the respective coefficients in Column II shows that the inclusion of personality traits leads to a substantial decrease in the positive effects observed for the reservation wage. Most of the effects observed in the upper part of the table lose their significance and/or are reduced substantially. For the case of the search intensity devoted to formal search channels, compare Column III, we observe the opposite. Whereas the negative effects of networks on the search intensity devoted to formal channels seem rather small and insignificant in the upper part, they decrease further to significant levels when including individual measures of conscientiousness and the locus of control. Furthermore we find, that, in contrast to the high responsiveness of mentioned job search indicators, the use of informal search channels is not significantly affected by the change in specification. It seems that the decision to use informal search channels does not vary with individual personality traits, but is primarily driven by the magnitude of the network. Nonetheless, as we aim to analyze the job search behavior in more detail, this assessment underscores the problem of unobserved heterogeneity in the context of analyzing social network effects without any sources of exogenous variation. The strong responsiveness of the above results in the expected directions indicates, however, that by controlling for a rich set of individual personality traits we are able to control for important sources of the omitted variable bias in our analysis. [Insert Table (6) about here.] Column I of the lower part of Table (6) shows that an increase in the respective network indicator of friends and colleagues leads to an increase in informal search channel use of 4% on average. These findings confirm the relevance of the network indicators used in the analysis and show that there exists a significant positive relationship between the extent of the network, and hence it s productivity, and the use of informal search channels. However, the magnitude of the relationship seems not as pronounced as expected. The relatively small size of the coefficients suggests that even individuals with low levels of networks choose to consult their 8 We included all network indicators simultaneously, separate analyses did not change the results significantly. 13

15 social contacts in getting job-information, and that the prevalent use of informal search channels is not necessarily linked to the existence of large networks. Clearly, this finding is not transferable to the case of informal search channel use on the intensive margin, for which we do not have information in our data. Based on our theoretical predictions in Section 2 however, we are able to deduce further insights from inspecting the reservation wage and the intensity of search devoted to formal channels. So far, our theoretical model assumes that the use of the informal search methods is the only channel through which the network affects the search process. In consequence we would expect that the search behavior of individuals who do not use informal search channels is independent of their network size. In a first approach we therefore exclude 14% of the individuals in our sample who stated that they do not use informal sources of information. Further reference to this will be made in the sensitivity analysis in the next section. Theory predicts that a sufficiently productive network leads to a substitution effect from formal to informal channels and thereby to an increase in the reservation wage. Columns III to V of the lower part in Table (6) refer to the effects of networks on the intensive margin of formal search channels, measured by the number of search channels used. When considering the total sum of formal search channel use in Column III, the throughout negative coefficients indicate that an increase in network measures does indeed lead to the predicted substitution effect. As in the case of informal channels we observe that the effect is strictly increasing with the level of networks considered. However, the effects seem to be of only weak significance and can only be found for high number of friends and a high former contact frequency to colleagues. Splitting up formal search into active and passive formal search leads to an improvement in significance and shows that informal search channels are indeed perceived as substitutes for passive formal search channels. For high levels of the respective network indicators we observe a significant reduction of search effort by 10% and 12%, respectively. If our interpretation of a productivity increase holds we would expect that individuals also increase their reservation wages. Column II shows that we observe indeed a small increase in reservation wages for medium levels of the friends and colleague indicators by about 1%. The point estimates for high levels of contact frequency with colleagues are of similar magnitude but do not show to be significant. [Insert Table (7) about here.] 14

16 Table 7 depicts the coefficients of the regression of the job search choices on the network indicators obtained by interacting the different levels of the friends and colleagues indicator. This allows us to compare the effect of the two network indicators jointly and assess potential differences in importance of the respective groups. Again we focus our interpretation on coefficients in the model with personality traits in the lower part. Comparison of the upper and lower results reveals, however, that similar findings are obtained with respect to the omission of personality traits as in Table (6). Column I in Table (7) shows that the effects are amplified if we include the network indicators jointly. In particular it can be seen that compared to the reference level of a low number of friends and a low number of colleagues, the probability of using informal search channels increases by about 6% to 9% if either network is in the medium or high range. Furthermore, in terms of search intensity devoted to formal search channels, we observe strong and significant reductions of effort for high levels of colleagues, independent on the number of the individual s close friends. Compared to the separate analysis the effects are also much more pronounced, ranging between 15% and 30% reduction, approximately. Whereas we had not found any effects on the use of active search channels before, some of the levels of the index now show that informal search channels are also used as substitutes for active search channels. However, the effects are usually less strong than for passive channels. Furthermore we are able to identify small but significant effects of about 3% on the reservation wage for the case where the network indicators are both medium or both high. The observation that the effects are not unambiguously increasing or decreasing in the network intensity, e.g. we do not observe any effects on reservation wages for the medium-high and high-medium network levels, may be explained by the fact that we are only able to observe an approximation of the complete network. The rather consistent findings across all network measures indicate however, that the tenor of our analysis are unaffected by the shortcomings of our network representation. In the following section we are going to put the previous results under further investigation by systematic variation of the estimation sample used. In particular we analyze the effect of expanding the sample to individuals that do no use informal search channels, in order to assess the robustness of our model assumption that the use of informal search channels is the only way by which networks influence the job search process. Another point of interest centers around the question whether the importance of networks varies with the labor market status of individuals, e.g., with the type of 15

17 job searched and the educational attainment of the unemployed. 4.3 Sensitivity Analysis The regressions conducted in the previous section were based on the assumption that networks influence the job search process by increasing the productivity of informal channels. Hence, we excluded individuals that did not use informal channels. Unfortunately, however we are not able to identify the reasons that determined the decision not to use informal search channels. In particular, we do not know if individuals maximized the equation (1) with two search channels, choosing not to allocate any search effort to their informal channel because of the low productivity of their social network. Or, one might consider the case of a random selection where individuals, independently of their network size, maximize a model of job search with only formal channels. For either case of the search decision process one might consider the case where relevant job-information is nonetheless transmitted via the network, entailing an increase in search efficiency of the formal channel. In terms of the mechanics of a theoretical model of job search with only one channel of search this would imply an increase in search effort and the reservation wage. Tables (A.1) and (A.2) in the appendix show the corresponding regression results after the inclusion of individuals that do not use informal channels. It can be seen that the effect on networks on formal search intensity are diminished, indicating that the individuals added to the analysis indeed exert higher levels of formal search effort, all else being equal. However we find, that the magnitude of the effect of networks on the reservation wages are almost identical compared to the analysis with only individuals using informal channels. This implies that the former expect similar levels of search productivity without actually using informal search, suggesting that networks affect the job search process via other channels simultaneously. A differential use and importance of networks in the job search process might also be explained by differences in occupational characteristics of the individual. In particular, one might consider the case where individuals with higher levels of education face a higher degree of job specification rate, and are thus more likely to rely on their network of colleagues than their network of friends. Similarly, one might consider the argument of network formation patterns, where individuals tend to form relationships with others that are similar to themselves, compare McPerson, Smith-Lovin, and Cook (2001). For example, we would expect that individuals with 16

18 higher degrees of labor market attachment are more likely to have relations that also have a high rate of labor market attachment. In turn, one would expect that individuals searching for full-time employment rather than part-time employment use their network more intensely. Table (A.3) in the appendix depicts the regression results for different levels of educational attainment. We stratified by the highest level of educational attainment, creating three subgroups for individuals with no vocational training, at most internal or external professional training and having completed a technical college or university. Across these three strata, we find that the network effects are strongly heterogeneous. Several issues catch the eye. First of all, it can be noted that networks seem to play a minor role in the job search process of low skilled individuals. Column I indicates, that the informal search decision of individuals with low levels of education is strongly dependent on the number of close friends, indicating that these individuals only consider informal search if their network is sufficiently large. Column I shows, that a medium and high number of friends leads to a 10% increase for individuals with low education, compared to a 4% increase for individuals in the other education categories. Additionally, we do not find evidence that networks affect any of the other job search indicators in the expected way - on the contrary, we even observe a reduction of the reservation wage at about 7% for a high contact frequency with colleagues. For the case of medium levels of educational attainment, we find that the network of friends is more important in conveying job-information than the network of colleagues. In particular we observe a small increase in reservation wages for medium levels of friends, and a highly significant reduction of formal search channels for a high number of friends at about 14%. For unemployed with high levels of education, the network of colleagues is most important. Unemployed with high levels of professional contacts significantly increase their reservation wage by about 6.5%, while reducing their (passive) formal search effort by approx. 30%. Table A.4 in the appendix depicts the regression coefficients for job search behavior stratified by the type of employment individuals search. The questionnaire differentiates between individuals searching for fulltime employment, part-time employment, or both. The results are in line with our intuitive reasoning above, as individuals who search for full-time employment only, or both, part- and full-time employment, seem to benefit more from informational networks in the job search 17

19 process than individuals searching for part-time employment. Similar to the case of low skilled individuals this manifests itself in the fact that individuals searching for part-time employment use the informal search channel only, if the size of the network is sufficiently large. The importance of friends and colleagues does not seem to differ in this context. However, we find differences in importance for the other subgroups. In particular, it can be seen that it is mainly the colleagues that matter for individuals that search for full-time employment only. Here, we see that the formal search effort decreases by approx. 17%, while the reservation wage increases by 2%. For individuals that are indifferent between finding part- or full-time employment we find similar results in terms of the substitution effect and reservation wage, for the case of a medium number of friends. 5 Conclusions In this paper we analyze the influence of social networks on job search behavior of unemployed individuals. Using the extensive data collection on recently unemployed workers in Germany in the IZA Evaluation Dataset we are able to test some hypotheses derived from a theoretical model of job search with two distinct search channels, as proposed by van den Berg and van der Klaauw (2006). In particular we are interested in testing the effect on an exogenous increase in network size on the job search behavior of individuals. If the assumption that networks convey job-relevant information holds, we would expect that, all else equal, the relative efficiency of informal search increases for higher levels of the network. The extent of the individuals network is approximated by the number of close friends and the contact frequency of individuals with former colleagues before unemployment. By virtue of the timely data collection process, approx. six weeks after entry into unemployment, and the rich set of information on personality traits we are able to eliminate important sources of unobserved heterogeneity that usually cause concern in a cross-section analysis of networks and labor market outcomes. Our findings underscore the established importance of networks in the job search process. In particular, we find that individuals with larger networks substitute informal for formal sources of information. We also find that the substitution effect is strongest for formal search channels that are considered to generate job offers with rather unspecific job characteristics at lower costs. We also find evidence that larger networks lead to a statistical significant increase in reservation wages 18

20 at about 1%. The effect becomes larger however if we stratify regressions by the level of educational attainment and the type of job sought, approximating potential differences in network quality and labor market status. The strongest results are found for high skilled individuals and individuals with higher levels of labor market attachment. For these subgroups we find the largest substitution effect and the highest increase in reservation wage. In particular, for the case of high skilled unemployed, we find that an increase in contact frequency with colleagues reduces formal search by one-third and increase reservation wages by about 6%. Hence, our analysis confirms the wide-spread notion that social contacts constitute relevant sources of information in the job search process, but that the extent of the effect varies with individual and, most likely, network characteristics. Unfortunately, we are not able to control for qualitative characteristics, e.g., labor market status, of individuals in the networks directly. This drawback prevents further sharpening of the results, which would be of particular interest for the analysis of the role of close friends. The more pronounced effect of former professional contacts in the job search process suggests that the respective network is most relevant for individuals who are also more likely to have contacts with similar professional background. Clearly, further research is needed to validate our findings with an analysis of the subsequent labor market success of the unemployed. In particular, we would expect that individuals that experience an increased productivity of search also leave unemployment earlier than otherwise similar unemployed without a relevant contacts. Also, it should be the case that the observed increase in reservation wages is translated into higher working wages, irrespective of the successful search channel. 19

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