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Job search effectiveness for employed and unemployed college graduate youth in Taiwan
JOB SEARCH EFFECTIVENESS FOR EMPLOYED AND UNEMPLOYED COLLEGE GRADUATE YOUTH IN TAIWAN HWEI-LIN CHUANG
In this paper we examine the diverse search methods used by college graduate youth in Taiwan to determine the relative effectiveness of obtaining employment. By estimating equations for the probability of gaining new employment, the probability of receiving offers, and the probability of accepting offers received, we find that unemployed job seekers are more effective in their searches. They gain more new employment, receive more offers, and accept more offers. The differences in search choices between these two groups helps to explain some of these outcomes. These findings not only support the validity of search unemployment but also indicate that it is worthwhile for a college graduate to invest in a full-time job search as it is more effective for gaining new employment. JEL 01.5; 053
Following the pioneer work of Stigler (1962), the literature on the economics of job search began in 1970. These studies of job searches led to theories of individuals’ choices concerning the search process that included the methods to use, how much effort to devote to the search, and what criteria to use to decide when to stop searching and to accept offers. For instance, Lippman and McCall (1976) used constrained maximization to model the choice of acceptance criterion. Following a similar approach, Benhabib and Bull (1983) modeled the choice of search intensity. As the main purpose of the job search theory in its early development was to justify the unemployment phenomenon in the labor market. One basic assumption of the standard job search model is that an individual has to quit his/her to search; that is, job search can be conducted only while unemployed. This assumption implies that unemployed job search is more effective than employed search. Otherwise, as claimed by Clark and Summers (1979), nobody should ever decline a job offer if searching while employed is as effective as searching while unemployed. However, Mattila (1974)
Hwei-Lin Chuang . Department of Economics. National Tsing Hua University, No. 101. Sec. 2, Kuang Fu Rd., Hsinchu 30043, Taiwan. R.O.C.: e-mail:[email protected]. Journal
of Asian Economics, Vol. 6, No. 2, 1995. pp. 247-260.
Copyright 0 1995 by JAI Press, Inc.
ISSN: 1049-0078
All riehts of reoroduction in any form reserved.
247
248
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
found that at least 50-60 percent of people transferring employers experienced no unemployment. Hence job searches are commonly conducted during employment. Job search models have therefore been amended to allow consideration of the search by both employed and unemployed individuals (e.g., Black, 1980, 1981; Burdett, 1978). As a result of the development in job search theories, one important issue addressed by empirical work on this topic is the relative effectiveness of employed versus unemployed search. The answer to this question is critical to the validity of the theory of search unemployment. Research on this issue provides very conflicting evidence. Mattila (1969), Black (1980) and Blau and Robins (1990) suggested that employed search was more effective either because employed search generated offers of greater remuneration or produced a higher rate of job finding than unemployed search. Kahn & Low (1982) and Holzer (1987) presented evidence that unemployed job search was more effective in terms of collecting more offers, accepting more offers, and yielding greater expected remuneration. Following the development of job search theories in the 1970’s, empirical studies on job search using Taiwan’s data began in the late 1970’s. Wu’s (1980) study, the pioneer work on job search, focused on the quitting decision of employed workers. Lin and Hsu (1988) found that job-search methods were far more important than personal characteristics in determining the employment probability for college graduates just entering the labor market based on data drawn from the 1982 “College Graduate Youth’s Employment Status Survey”. Shih (1990) analyzed the job search behavior for employed and unemployed workers separately based on data from the 1987 “Manpower Utilization Survey”; his findings about the employed search are consistent with common theoretical predictions, but the finding that the reservation wage increased with the unemployment duration contradicts the common theoretical prediction and therefore further studies are worthwhile. Although empirical studies on job search based on Taiwan’s data have accumulated for more than 10 years, the relative effectiveness of employed versus unemployed search is rarely discussed in the literature. Here we follow Holzer’s approach to analyze the relative effectiveness of employed and unemployed searches for college graduate youth in Taiwan based on data drawn from the “College Graduate Youth’s Employment Status Survey”. Our work differs from that of Holzer in several ways. First, we utilized other data and analyzed a slightly different set of search choice variables. Second, we extended Holzer’s analysis by including both female and male youth. Third, we distinguished those who quit their jobs to search more effectively from those who were laid off and forced to search whereas Holzer treated equally these two groups by using only one dummy variable for job leavers. In general, like Holzer, we found that unemployed job seekers are more effective than employed job seekers in terms of gaining new employment, receiving offers, and accepting offers. However, contrary to Holzer, we found that employed searchers are
Job Search Esfectiveness for College Graduates
249
significantly more likely to generate job offers and find new employment than those who quit or were laid-off into unemployment when we distinguished these unemployed job seekers from the labor market entry unemployed job seekers. The remainder of this paper is organized as follows. Section I describes the current data set. The econometric specification and the estimation results are discussed in Section II. The final section summarizes the findings and concludes.
I. DATA The data to be used are drawn from the 1984 and 1985 “College Graduate Youth’s Employment Status Survey” sponsored by the National Youth Commission.’ These data are well suited for this analysis because the contents of this survey include the current status of each respondent, working experience, post-graduation job search information (including search methods used, search frequency, and the minimum accepted wage), job information (including how to find the current job, position, work hours, wages, and attitude toward current job) for employed youth, and personal data (including sex, birth date, marriage, level of education, level of parents’ education, and the minimum accepted wage as of g~duation) for each respondent. This survey, conducted in 1986, included a total sample of 12,189 males and females who graduated from colleges or universities in 1984 or 1985.2 We excluded those who were self-employed, worked for a family business with no pay, and those who graduated from normal colleges or universities that guaranteed employment after graduation,3 as these young men and women either would not conduct job searches or their search activities were different from other common college graduates. After these deletions, there were 5,711 male and female cases in this analysis. As Holzer (1987) stated, “[dfefining the employment status of searchers was somewhat difficult. Since an unemployed searcher who had accepted job offers might be listed as currently employed, current employment status could not be used alone to define status while searching.” Therefore, in this analysis, we define unemployed searchers as both those who are currently unemployed and those who accepted their current jobs some time after their graduation and have no intention of changing their current jobs.4 The latter were thus defined as these respondents did not conduct employed search so that the information about their search activities which was collected for the most recent ones as of the survey date, was referred to their unemployed search.5 Table 1 presents summary statistics on the search choice variables for employed and unemployed job seekers. The results show that the average unemployed job seeker uses more methods than does the employed searcher, and the difference between the two is statistically signi~cant. This result holds for both males and females. Females tend to use more methods than males no matter whether employed or unemployed. The fraction using every method indicates that newspapers are the most popular method
1.82 (0.98)
1.92
0.15 (0.36) 0.23 (0.42) 0.16 (0.36) 0.005 (0.007) 0.10 (0.29)
0.21 (0.41)
0.23 (0.42)
0.22 (0.41)
0.01 (0.11)
0.08 (0.27)
Civil-service
School Placement Offices
Government
Private Agencies
Other Methods
NT$ 15663.49 (6741.71) N.A.a
-1.23
-1.88’
1.9s**
4.21”*
0.18
4.05***
-1.06
0.93
2.80***
T-test
NT$ 11470.63 (3426.72)
NT$ 11216.99 (3622.22)
0.07 (0.25)
0.01 (0.11)
0.20 (0.40)
0.28 (0.45)
(0.46)
0.30
0.52 (0.50)
NT% 10761.12 (3589.08)
NT% 11063.55 (3321.18)
0.10 (0.30)
0.01 (0.11)
0.14 (0.34)
0.28 (0.45)
0.19 (0.39)
0.53 (0.50)
0.73 (0.44)
0.74
Emnloved
(0.44)
2.11 ( 1.02)
Unemnloved
Females
N.A.a
1.15
-3.56***
0.37
4.21**’
-0.47
6.92***
-0.42
0.35
NT$ 13527.7 1 (4559.88)
NT$ 13227.97 (486 1.02)
0.07 (0.26)
0.01 (0.11)
0.21 (0.41)
0.25 (0.43)
0.25 (0.43)
0.46 (0.50)
0.75 (0.43)
2.01 (1.01)
Unemoloved
Job Seekers
3.24*”
T-test
*: These sample means are weighted. As the computed standard errors on weighted means are generally incorrect, r-tests were omitted. *~significant at 10 percent level: *,;significant at five percent level; : significant at one percent level. N.A.: not applicable.
pmple sizes are 3012 for unemployed seekers and 2699 for employed seekers. Standard deviations are in parentheses.
NT$ 15317.75 (479 1.44)
Reservation Wages of Those with Offers
Note:
NT$ 15038.49 (5116.85)
Reservation Wages
Agency
NT$ 15268.99 (5171.16)
0.43 (0.49)
0.41 (0.49)
Friends/Relatives
Entrance Examination
0.76 (0.43)
(1.00)
Emnloved
Unemnloved
Males
Statistics of Search Choices for Employed and Unemployed
0.77 (0.42)
Fraction Using: Newspapers
Number of Methods Used
TABLE 1.
NT$ 13196.09 (6124.73)
NT$ 13279.23 (4869.40)
0.10 (0.30)
(0.09)
0.008
0.15 (0.35)
(0.4)
0.26
0.17 (0.37)
0.47 (0.50)
(0.44)
0.74
(1.00)
1.90
Emnioved
Total
N.A.a
-0.40
-3.81***
1.56
5.95”’
-0.20
7.78***
-1.04
0.90
4.25***
T-test
w
z?
ij
R
2
g
F
!z
g
251
Job Search Effectiveness for College Graduates
TABLE 2.
Statistics of Search Outcomes for Employed Males
and Unemployed
Job Seekers Total
Females
Unemployed
Employed
Unemployed
Employed
Unemployed
Employed
Fraction Gaining New Employment
0.68 (0.47)
0.42 (0.49)
0.61 (0.49)
0.45 (0.50)
0.65 (0.48)
0.44 (0.50)
Fraction Receiving Offers
0.89 (0.28)
0.79 (0.50)
0.86 (0.31)
0.76 (0.54)
0.87 (0.29)
0.77 (0.52)
Fraction Accepting Received Offers
0.78 (0.38)
0.58 (0.57)
0.73 (0.41)
0.55 (0.58)
0.76 (0.39)
0.56 (0.58)
Wages of Accepted Offers
17561.86 (4988.24)
17827.50 (5277.62)
13562.93 (4257.85)
12748.70 (4001.77)
15777.69 (5011.81)
15337.72 (5229.73)
used by both employed and unemployed job seekers and there is no significant difference in the use of newspapers between the two groups. Connections from friends and relatives constitute the second popular method. Again, there is no significant difference in the fraction using this method between the two groups. Unemployed searchers use the civil-service entrance examination significantly more commonly than employed searchers. This result is reasonable as preparation for this examination requires more time. Unemployed job seekers are also more likely to try to find jobs with the help of government agencies whereas employed job seekers have significantly more access to other methods. Finally, the reservation wages are smaller for the unemployed although the difference is not statistically significant. Hence, the common theoretical predictions that greater costs of search for unemployed persons cause them to exert greater effort in searching and to be more willing to accept job offers are confirmed by these data. Summary statistics on the outcome variables for employed and unemployed seekers appear in Table 2. The results show that a greater fraction of the unemployed receives offers and the fraction accepting an offer is substantially higher for unemployed than for employed job seekers. In particular, we found that employed seekers rejected almost half the offers they received whereas unemployed searchers rejected only about a quarter. Thus, the likelihood of gaining a new job was significantly higher for an unemployed seeker than for an employed job seeker on both counts. Taken together, the summary results of Tables 1 and 2 indicate the importance of considering choices of search effort and reservation wages when comparing search outcomes for the employed and the unemployed, as these choices and outcomes may be linked. The greater search effort and smaller reservation wages of the unemployed (Table 1) are theoretically consistent with their greater rates of finding employment (Table 2).
II.
ECONOMETRIC SPECIFICATION AND ESTIMATION RESULTS
We analyzed these issues more carefully according to Holzer (1987). As stated by Holzer, a common finding of the job search literature is that the probability of gaining
252
JOURNAL OF ASIAN ECONOMICS (6)2,1995
new employment within a certain period is the product of the probability of receiving an offer, and the probability that the wage offered is greater than the reservation wage.6 Based on this relationship, we can specify the empirical equations for the employment outcomes as Holzer did. However, we made modifications as the contents of our data are distinct from those of NLSY data that Holzer used. Specifically, our econometric specifications have the following form:
Po=Po(X,SM,UNEMP,Q,L)+E, PA=PA(wr/wo, UNEMP,Q,L)+q
(3)
where PE, PO,and PAreflect the probability of gaining new employment, receiving a job offer, and accepting an offer conditional on receiving it, respectively; SM indicates the search methods used (we considered seven methods); UNEMP is a dummy variable for unemployed job seekers; Q is a dummy variable for those who quit their jobs to become unemployed; L is a dummy variable for those who were laid-off and became unemployed;? X is a vector of variables affecting the offer and wage functions. Speci~cally, Xincludes education, subject of study, type of institution, gender, marital status, paternal education, financial responsibility, labor market experience, and urban residence. Some econometric issues must be addressed before we turn to our estimation results. The search choice variables are treated as exogenous here, thereby implying a recursive model of search choice formation rather than a simultaneous one. This is not an inappropriate assumption as the search outcomes are observed subsequent to the observation of search choices in the current data set.* As for the wage offer in the PA equation, as we observed wages for only those who accepted offers, we requited a proxy variable for those who failed to accept offers. We applied Heckman’s two-stage method to estimate a wage offer equation and then used the imputed wages for each observation in the sample to estimate the PAequation.g Equations (l)-(3) are estimated independently here by probit. We thereby ignore possible correlation of errors across employment equations, The wage variables in all equations appear in log form. Table 3 shows estimates of equation (1) for the probability of gaining new employment. The estimated results are presented with and without the job leaver dummy variables, as well as with and without search choice variables. The results show that unemployed job seekers are significantly more likely to gain new jobs than are employed job seekers, even after taking into account personal characteristics and search choices. However, the sum of the coefficients for unemployment and forjob leaver dummy variables is negative. This implies that those who were laid-off or quit were somewhat less likely to gain new jobs than were employed searchers..
Job Search Effectiveness for College Graduates
TABLE 3.
Equations
Van’able
253
for Probability
of Gaining New Employment
1
2
3
4
0.542*** (7.44) 0.075*** (1.96)
0.507*** (6.59)
0.613*** (8.88)
0.542*** (7.39)
0.191*** (4.62)
0.131*** (3.62)
0.238*** (6.10)
R
R
R
R
Law, Business, Medical & Engineering
0.023 (0.60)
0.023 (0.62)
0.172’** (4.31)
Others
R
0.169”’ (4.00) R
R
R
Public
0.088** (2.16)
0.101”’ (2.36)
0.099*** (2.58)
0.096” (2.37)
Private
R
R
R
R
Level of Education Graduate School University College Subject
School
Gender Male
-0.091** (-2.39)
Female
R
-0.034 (4.84) R
(Z:; R
0.012 (0.31) R
Marital Status Married
JNI93
-0.096
(-1.42)
(-1.43)
(-1.89)
(-2.09)
R
R
R
R
1984
0.258*** (6.88)
0.336”; (8.55)
0.174”’ (4.98)
0.261*** (7.08)
1985
R
R
R
R
Single or Divorced
-0.117’
-0.134
Labor Market Experiencea
Paternal Education Beyond High School High School
4.108*** (-2.10) R
Below High School
0.32 (0.58) R
-0.084’ (-1.73) R
0.057 (1.09) R
X).116*** (-2.76)
0.053 (1.12)
-0.157*** (-3.95)
0.023 (0.51)
High
-0.153*** (-3.37)
0.171*** (2.76)
X).147*** (-3.41)
0.179*** (3.07)
Median
X).255*‘* (-1.05)
0.085 (1.12)
-0.226”’ (-3.80)
0.112 (1.57)
Urbanization
Low
R
R
R
R
Financial Responsibility Presence
X).141*** (-3.56)
Absence In Reservation
R Wageb
_
-0.079* (-1.92) R -0.049*** (4.80)
-0.129”’ (-3.46) R -
XN61 (-1.57) R 4.038*** (-3.93) (continued)
254
JOURNAL OF ASIAN ECONOMICS
TABLE 3. Variable
Search Methods Newspapers
I
-0.308**’ (-6.73) -0.048 (-1.27) -0.354*** (-7.65) 0.268*** (6.05) -(X202*** (-4.05) -0.464*** (-2.46) 0.284***
Friends/Relatives Civil-service Entrance Examination School Placement Government Agency Private Agency Other Method
(continue) 2
-
-
3
-
(4.09) Unemployed Quit into Unemployment Laid-off into Unemployment Log L
0.947*** (24.62) -2.002*** (-26.40) -2.169*** (-11.68) -3223.22
(6)2,1995
I .092*** (26.58) -1.919*** (-24.45) -2.071*** (-10.75) -3081.57
0*471*** (14.10)
-373 1.63
4
-0.419*** (-9,633 -0.102*** (-2.85) -0.405*** (-9.35) 0.305*** (7.25) -0.250*‘* (-5.36) -O&4*** (-2.64) 0.286*** (4.27) 0.660*** (18.23)
-3510.45
No&s: EquationsestimatedusingProbit. Sample size is 5711. T-ratio is given in parentheses. a: This dummy variable is to indicate fhat those who graduated in 1984 had entered the labor market earlier than those who aduated in 1985. B : In monthly payment. * : Significant at the ten percent level; ** : Significant at the five percent level; *** : Significant at the one percent level (Z-&&d tests).
Of the search choice variables, newspapers, friends/relatives, the civil-service entrance examination, gove~ment, and private agencies show little help in finding new jobs for college graduate job seekers, but they are more likely to gain new employment through school placement and other methods. The unemployment effect remains signi~c~t even with search choice variables added to the equation. The result of the reservation wage variable has a correct sign that is consistent with the common prediction from job search theory. Those with smaller reservation wages are more likely to gain new employment. Tables 4 and 5 present estimates of equations (2) and (3), which decompose the probability of gaining new employment into the probability of receiving offers and of accepting them. ‘*The results reported in Table 4 indicate that unemployed job seekers receive more offers than the employed. However both those who were laid-off or who quit received no more offers than the employed although the difference was small compared to the difference in the probability of gaining new employment between
255
Job Search Effectiveness for College Gradtrates
TABLE 4.
Equations for Probability of Receiving Job Offers
Vurioble
2
I
3
4
Level of Education 0.212*** (2.03)
0.165 (1.53)
0.291*** (2.84)
0.222*** (2.10)
University
0.214*** (4.23)
0.227*** (4.41)
0.241*** (8.62)
0.260*** (7.85)
College
R.
R
R
R
Public
0.523*** (8.61)
0.485”’ (7.83)
0.508*” (8.62)
0.473*** (7.85)
Private
R
R
R
R
Law, Business, Medical & Enginee~ng
0.327*** (6.47)
0.316*** (6.13)
0.327*** (6.59)
Others
R
R
R
0.326’*’ (6.44) R
Male
0.087. (1.76)
0.093’ (1.85)
0.105** (2.18)
0.115** (2.34)
Female
R
R
R
R
Graduate
School
&hoof
Subject
Gender
Marital Status Married
-0.051 (-0.56)
-0.045 (-0.49)
-0.057 (4.64) R
-0.051 (4.56)
R
R
1984
0.301*** (5.93)
0.301”’ (5.87)
0.263*** (5.32)
0.269**’ (5.36)
1985
R
R
R
R
Single or Divorced
R
Labor Market Experiencea
Paternal Education Beyond High School High School Below High School
0.0002 ((O.OtJ3) R
-0.030 (-0.43)
-0.030 (-0.54)
-0.060 (-1.05)
0.020 (0.31) R
R
-0.051 (-0.93)
-0.002 (-0.03) R -0.069 (-1.23)
Urbanization High Median
0.273*** (4.90) -0.076 (-1.03)
Low
R
0.189*** (2.95) -0.144* (-1.82)
0.273*** (5.00) -0.064*** (-0.88)
R
R
0.231*** (3.70) -0.096 (-1.24) R
Financial Responsibility Presence
-0.074 (-1.47)
Absence
R
-0.070 (-1.37)
-0.068 (-1.36)
R
R
-0.057 (-1.14) R
Search Methods Newspapers
-
0.118*’ (2.14)
-
0.054 (1.01) (continued)
256
JOURNAL OF ASIAN ECONOMICS (6)2, 1995
TABLE 4.
(Continue)
1
Variable
2
Friends/Relatives Civil Service Entrance Extinction School Placement
4
3
0.027 (0.59)
-
-0.005 (-0.10)
-0.145** (-2.50)
-
-0.190.“: (-3.35)
-xX266*** (4.39)
-
-0.300*** (5.08)
-
-0.185*** (-2.93)
-
-X).226*** (-3.65)
Private Agency
-
-0.348* (-1.86)
-
-0.354’ (-1.88)
Others
-
0.136 (1.56)
-
0.1X?* (1.76)
0.365*** (7.84)
0.421**’ (8.61)
Govemment
Agency
Unemployed
0.671”’ (12.11)
Quit into Unemployment Laid-off into Unemplo~ent Log L
0.694**’ (12.18)
-0.889*** (-11.24)
-0.855*‘* (-10.59)
-1.077*** (-6.83)
-1.043*** (-6.57) -1782.49
-1803.91
-1879.34
-1849.38
Equations estimated using Probit. Sample size is 4326. T-ratio is given in parentheses. a: This dummy variable is to indicate that those who graduated in 1984 had entered the labor market earlier than those who graduated in 1985. : Significant at the 10 percent level; *4 : Significant at the five Percent level: *** : Significant at the one percent level (Zrailed tests).
TABLE 5. Equations for Probability of Accepting Offers Variable In (Relative Reservation
1 Wage)”
Unemployed Quit into Unemployment Laid-off into Unemployment Log L
-
2 1.065*** (12.34)
1.067*” (29.17) -2X05*** (-22.28)
1.252*** (30.54) -2x02*** (-2 1.73)
-2.084*** (-9.37)
-2.001*** (-8.90)
-2097.83
NOMS:Equations estimated using Probit. Sample size is 3884. T-ratio is given in parentheses. “,~II monthly payment. : significant at the one percent level.
-2019.31
4
3 0.643*** (22.14) -
1.128*** (13.62) 0.836*** (25.13) -
-
-
-2432.76
-2336.79
Job Search Effectiveness for College Graduates
25-l
these two groups. These relationships still hold even after taking into account search choices. The search choice variables have less significant effects on the probability of receiving offers than on the probability of gaining new employment. The results on acceptance of offers show that unemployed job seekers accepted significantly more offers than did employed job seekers. As in Table 3 and 4, job leavers accepted fewer offers than the other unemployed and also less than employed job seekers. However, the ratio of reservation wages to offered wages has a significantly positive effect on job acceptance. This result is contrary to the indication from most job search models that the acceptance or rejection of offers is caused exclusively by comparisons of wage offers and reservation wages. Thus, a negative association between the relative reservation wage and the probability of accepting offers is expected. Our finding of a positive effect of the relative reservation wage implies that the acceptance or rejection of offers may not be simply determined by the comparisons of wage offers and reservation wages; other factors may be hidden in the reservation wage variable requiring further investigation. Another possible explanation of this result is that the wage offer variables in this analysis are estimated rather than observed. In sum, the results of Tables 3-5 confirm many predictions made above. In particular, the unemployed received and accepted more job offers than did the employed. These two factors yielded a greater rate of gaining new employment for the unemployed than for the employed. However, when we distinguished job leavers from those who entered the labor market from unemployment, we found that those who are laid-off or who quit their jobs to search receive and accept fewer offers than not only the previously unemployed but also the employed job seekers.
III.
CONCLUSION
The relative effectiveness of employed versus unemployed search is an important issue because the validity of the theory of search unemployment rests implicitly on the notion that unemployed search is more effective than employed search. We have argued that the greater costs of search for unemployed than for employed job seekers is expected to lead the former to invest more effort in search and to have smaller reservation wages relative to offered wages. These predictions are supported by empirical evidence on young college graduate job seekers in Taiwan. Our data show that unemployed job seekers used more search methods and their relative reservation wages were smaller. Moreover, these differences in search choices help to explain differences in search outcomes that we also observed between the two groups. Specifically, the extensive search methods used by the unemployed explain partially the greater probability of their receiving offers, and their smaller reservation wages explain part of their relatively greater rate of job finding. All these results indicate that the theory of search unemployment is valid as the data show that unemployed search is more effective than
258
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
employed search in terms of generating more job offers, accepting more offers received, and therefore gaining more new employment. These findings also suggest that it is worthwhile for a college graduate to invest in full-time job search. Thus, policy makers may not have to worry too much about the situation that there is a relatively higher than average unemployment rate among the college graduate labor force in Taiwan. Their unemployed search can be regarded as an investment activity rather than a waste of human resources. Acknowledgments.
I thank the National Science Council of Taiwan for financial support, Dr. Ching-hsi Chang, Dr. Ying-chuan Liu, and seminar participants at National Chengchi University and the 1994 Western Economic Association International Conference for helpful comments on earlier drafts of this paper, Dr. Huei-lin Wu for providing the data set, and Sonny Wei for research assistance. I am grateful to two anonymous referees for excellent suggestions.
NOTES 1. The purpose of this survey is to investigate the job search behavior and the employment status of college graduates when they first enter the labor market. 2. There were 15,672 males and females included in the original survey conducted in 1986. However, some of them were still in military service or in school during the survey period. These samples were excluded, and therefore only 12,189 cases were left in the final survey. 3. Students who enrolled in normal colleges or universities did not pay for their tuition and fees (the government paid for them) and therefore were required to accept jobs assigned by the government after graduation. 4. Among the unemployed searchers, there is a group of college graduate youth whose unemployed searches refer to their search activities right after graduation and therefore they may be termed as labor market entry unemployed searchers. This term was kindly provided by one of the referees. 5. This survey only collects information on job searches for the most recent search activity for each respondent. That is, for those who were unemployed and conducted search activities as of the survey date, the job search information referred to their most recent search. For those who were employed and had no intention to change their current jobs, the job search information referred to their unemployed search or employed search depending on the respondent’s employment situation prior to their current jobs. For those who were currently employed and conducted search activity, the search information referred to their employed search. 6. As stated in page 602 of Holzer (1987), “the probability of receiving a new job within a certain period is related to reservation wages and search effort in the following manner: PE = 71(&!?)[I - F (w’)], where PE is the probability of gaining employment, w’ is the reservation wage, SE is search effort, n is the probability of receiving an offer, and f(w’) is the density function of wage offers facing an individual.” As shown, the standard search theory implies that a comparison of the reservation and offered wages completely determines the acceptance decision. However, the statistics reported in Table 1 suggest that the employment status may also have influence on the acceptance probability, and therefore the employment status variables are also included in the PA equation. 7. There will be no perfect collinearity problem of including three dummy variables--LINEUP, Q, and Gin the estimation because there is a group of labor market entry unemployed searchers in the sample.
259
Job Search Effectiveness for College Graduates
8. Although the fact that outcomes are observed after search choices are made does not guarantee that the latter are exogenous, a simultaneous treatment would be less appropriate for the current data set. 9. This way to handle the problem of unobserved offered wages can be found in Connelly, DeGraff, and Levison (1994). Details of the estimation of the wage offer equation appear in the appendix. 10. Because of the imperfection of the questionnaire design in the survey, many respondents have missing values regarding the job offer questions. Therefore, the sample size in Table 4 is smaller than that in Table 3. The sample size in Table 5 is smaller than that in Table 4 since those who do not receive job offers are excluded in the estimation of the equations for probability of accepting offers.
APPENDIX This appendix describes the estimation of the wage offer equation. As we observed wages for only those who accepted offers, there is a potential problem of selectivity bias if we apply OLS to estimate the wage offer equation based on the sample with observed wages. Therefore, Heckman’s two-stage estimation approach is applied. The fist stage is a probit estimation of the acceptance of offer based on the sample of observations with offers. Then the selectivity bias-corrected regression is run using the sample of those observations with observed wages. The second stage estimation results are presented in Table A. As shown in Table A, the significant effect of the selectivity variable 1 indicates that selection bias is not negligible in this case.
TABLE
A.
Heckman’s Two Stage Estimates of the Wage Offer Equation
Variables
Coefficient
Constant
8.088***
Age Age Squared
0.074*** -O.o01**
t-Ratio
22.06 2.80 -2.33
Graduate School
0.429***
19.99
University
0.168***
13.21
Major
0.051”’
Public
0.098***
Male
0.172”’
13.74
Married
0.049”’
2.98
Work Experience
0.094***
9.66
Paternal Education Beyond HSa
0.014
Paternal Education Below HSa
4.90 9.69
1.os
-0.004
-0.37
High Urbanization
0.006
0.34
Median Urbanization
0.003 -0.071***
h Notes: Sample size is 3122. R’ = 0.503 “,;HS denotes high school. **/significant at the five percenr
: significant
level.
at the one percent level.
0.13 A.44
260
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
REFERENCES Benhabib, J., & Bull, C. (1983). Job search: The choice of intensity. JournalofPolitical Economy, 91(5), 141-164. Black, M. (1980). Pecuniary implications of on-the-job search and quit activity. Review ofEconomics and Statistics, 62(2), 222-229. -. (1981). An empirical test of the theory of on-the-job search. Journal of Human Resources, 16( 1). 129-l 40. Blau, D. M., & Robins, P. K. (1990). Job search outcomes for the employed and unemployed. Journal of Political Economy, 98(3), 637455. Burdett, K. (1978). A theory of employee job search and quit rates. American Economic Review, 68( 1), 212-220. Clark, K. B., & Summers, L. H. (1979). Labor market dynamics and unemployment: A reconsideration. Brookings Papers of Economic Activity, (I), 13-60. Holzer, H. J. (1987). Job search by employed and unemployed youth. Industrial and Labor Relations Review, 40,601-6 11. Kahn, L., & Low, S. (1982). The relative effects of employed and unemployed job search. Review of Economics and Statistics, 64(2), 234-241. Lin, C. C., & Hsu, L. S. (1988). College graduate youth and their job search behavior. Bulletin of the Institute of Ethnology, Academia Sinica, 58, 225-250. Lippman, S. A., & McCall, J. J. (1976). The economics of job search: A survey. Economic Inquiry, 14, 155-189. Mattila, J. P. (1969). Quit behavior in the labor market. American Statistical Association Proceedings, Economic Statistics Section, 697-701. Mattila, J. P. (1974). Job quitting and frictional unemployment. American Economic Review, 64,235-239. Stigler, G. J. (1962). Information in the labor market. Journal of Political Economy, 70, ‘M-105. Shih, G. T. (1990). An empirical study on the job search behavior in Taiwan’s labor market. M.A. thesis, Department of Economics, National Taiwan University. Wu, C. G. (1980). A study on workers’ quit rate in Kaoshiang export processing zone. Taiwan Economic Review, 9(2), 25-56.
Received
May 1994; Revised
February
1995
In this paper we examine the diverse search methods used by college graduate youth in Taiwan to determine the relative effectiveness of obtaining employment. By estimating equations for the probability of gaining new employment, the probability of receiving offers, and the probability of accepting offers received, we find that unemployed job seekers are more effective in their searches. They gain more new employment, receive more offers, and accept more offers. The differences in search choices between these two groups helps to explain some of these outcomes. These findings not only support the validity of search unemployment but also indicate that it is worthwhile for a college graduate to invest in a full-time job search as it is more effective for gaining new employment. JEL 01.5; 053
Following the pioneer work of Stigler (1962), the literature on the economics of job search began in 1970. These studies of job searches led to theories of individuals’ choices concerning the search process that included the methods to use, how much effort to devote to the search, and what criteria to use to decide when to stop searching and to accept offers. For instance, Lippman and McCall (1976) used constrained maximization to model the choice of acceptance criterion. Following a similar approach, Benhabib and Bull (1983) modeled the choice of search intensity. As the main purpose of the job search theory in its early development was to justify the unemployment phenomenon in the labor market. One basic assumption of the standard job search model is that an individual has to quit his/her to search; that is, job search can be conducted only while unemployed. This assumption implies that unemployed job search is more effective than employed search. Otherwise, as claimed by Clark and Summers (1979), nobody should ever decline a job offer if searching while employed is as effective as searching while unemployed. However, Mattila (1974)
Hwei-Lin Chuang . Department of Economics. National Tsing Hua University, No. 101. Sec. 2, Kuang Fu Rd., Hsinchu 30043, Taiwan. R.O.C.: e-mail:[email protected]. Journal
of Asian Economics, Vol. 6, No. 2, 1995. pp. 247-260.
Copyright 0 1995 by JAI Press, Inc.
ISSN: 1049-0078
All riehts of reoroduction in any form reserved.
247
248
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
found that at least 50-60 percent of people transferring employers experienced no unemployment. Hence job searches are commonly conducted during employment. Job search models have therefore been amended to allow consideration of the search by both employed and unemployed individuals (e.g., Black, 1980, 1981; Burdett, 1978). As a result of the development in job search theories, one important issue addressed by empirical work on this topic is the relative effectiveness of employed versus unemployed search. The answer to this question is critical to the validity of the theory of search unemployment. Research on this issue provides very conflicting evidence. Mattila (1969), Black (1980) and Blau and Robins (1990) suggested that employed search was more effective either because employed search generated offers of greater remuneration or produced a higher rate of job finding than unemployed search. Kahn & Low (1982) and Holzer (1987) presented evidence that unemployed job search was more effective in terms of collecting more offers, accepting more offers, and yielding greater expected remuneration. Following the development of job search theories in the 1970’s, empirical studies on job search using Taiwan’s data began in the late 1970’s. Wu’s (1980) study, the pioneer work on job search, focused on the quitting decision of employed workers. Lin and Hsu (1988) found that job-search methods were far more important than personal characteristics in determining the employment probability for college graduates just entering the labor market based on data drawn from the 1982 “College Graduate Youth’s Employment Status Survey”. Shih (1990) analyzed the job search behavior for employed and unemployed workers separately based on data from the 1987 “Manpower Utilization Survey”; his findings about the employed search are consistent with common theoretical predictions, but the finding that the reservation wage increased with the unemployment duration contradicts the common theoretical prediction and therefore further studies are worthwhile. Although empirical studies on job search based on Taiwan’s data have accumulated for more than 10 years, the relative effectiveness of employed versus unemployed search is rarely discussed in the literature. Here we follow Holzer’s approach to analyze the relative effectiveness of employed and unemployed searches for college graduate youth in Taiwan based on data drawn from the “College Graduate Youth’s Employment Status Survey”. Our work differs from that of Holzer in several ways. First, we utilized other data and analyzed a slightly different set of search choice variables. Second, we extended Holzer’s analysis by including both female and male youth. Third, we distinguished those who quit their jobs to search more effectively from those who were laid off and forced to search whereas Holzer treated equally these two groups by using only one dummy variable for job leavers. In general, like Holzer, we found that unemployed job seekers are more effective than employed job seekers in terms of gaining new employment, receiving offers, and accepting offers. However, contrary to Holzer, we found that employed searchers are
Job Search Esfectiveness for College Graduates
249
significantly more likely to generate job offers and find new employment than those who quit or were laid-off into unemployment when we distinguished these unemployed job seekers from the labor market entry unemployed job seekers. The remainder of this paper is organized as follows. Section I describes the current data set. The econometric specification and the estimation results are discussed in Section II. The final section summarizes the findings and concludes.
I. DATA The data to be used are drawn from the 1984 and 1985 “College Graduate Youth’s Employment Status Survey” sponsored by the National Youth Commission.’ These data are well suited for this analysis because the contents of this survey include the current status of each respondent, working experience, post-graduation job search information (including search methods used, search frequency, and the minimum accepted wage), job information (including how to find the current job, position, work hours, wages, and attitude toward current job) for employed youth, and personal data (including sex, birth date, marriage, level of education, level of parents’ education, and the minimum accepted wage as of g~duation) for each respondent. This survey, conducted in 1986, included a total sample of 12,189 males and females who graduated from colleges or universities in 1984 or 1985.2 We excluded those who were self-employed, worked for a family business with no pay, and those who graduated from normal colleges or universities that guaranteed employment after graduation,3 as these young men and women either would not conduct job searches or their search activities were different from other common college graduates. After these deletions, there were 5,711 male and female cases in this analysis. As Holzer (1987) stated, “[dfefining the employment status of searchers was somewhat difficult. Since an unemployed searcher who had accepted job offers might be listed as currently employed, current employment status could not be used alone to define status while searching.” Therefore, in this analysis, we define unemployed searchers as both those who are currently unemployed and those who accepted their current jobs some time after their graduation and have no intention of changing their current jobs.4 The latter were thus defined as these respondents did not conduct employed search so that the information about their search activities which was collected for the most recent ones as of the survey date, was referred to their unemployed search.5 Table 1 presents summary statistics on the search choice variables for employed and unemployed job seekers. The results show that the average unemployed job seeker uses more methods than does the employed searcher, and the difference between the two is statistically signi~cant. This result holds for both males and females. Females tend to use more methods than males no matter whether employed or unemployed. The fraction using every method indicates that newspapers are the most popular method
1.82 (0.98)
1.92
0.15 (0.36) 0.23 (0.42) 0.16 (0.36) 0.005 (0.007) 0.10 (0.29)
0.21 (0.41)
0.23 (0.42)
0.22 (0.41)
0.01 (0.11)
0.08 (0.27)
Civil-service
School Placement Offices
Government
Private Agencies
Other Methods
NT$ 15663.49 (6741.71) N.A.a
-1.23
-1.88’
1.9s**
4.21”*
0.18
4.05***
-1.06
0.93
2.80***
T-test
NT$ 11470.63 (3426.72)
NT$ 11216.99 (3622.22)
0.07 (0.25)
0.01 (0.11)
0.20 (0.40)
0.28 (0.45)
(0.46)
0.30
0.52 (0.50)
NT% 10761.12 (3589.08)
NT% 11063.55 (3321.18)
0.10 (0.30)
0.01 (0.11)
0.14 (0.34)
0.28 (0.45)
0.19 (0.39)
0.53 (0.50)
0.73 (0.44)
0.74
Emnloved
(0.44)
2.11 ( 1.02)
Unemnloved
Females
N.A.a
1.15
-3.56***
0.37
4.21**’
-0.47
6.92***
-0.42
0.35
NT$ 13527.7 1 (4559.88)
NT$ 13227.97 (486 1.02)
0.07 (0.26)
0.01 (0.11)
0.21 (0.41)
0.25 (0.43)
0.25 (0.43)
0.46 (0.50)
0.75 (0.43)
2.01 (1.01)
Unemoloved
Job Seekers
3.24*”
T-test
*: These sample means are weighted. As the computed standard errors on weighted means are generally incorrect, r-tests were omitted. *~significant at 10 percent level: *,;significant at five percent level; : significant at one percent level. N.A.: not applicable.
pmple sizes are 3012 for unemployed seekers and 2699 for employed seekers. Standard deviations are in parentheses.
NT$ 15317.75 (479 1.44)
Reservation Wages of Those with Offers
Note:
NT$ 15038.49 (5116.85)
Reservation Wages
Agency
NT$ 15268.99 (5171.16)
0.43 (0.49)
0.41 (0.49)
Friends/Relatives
Entrance Examination
0.76 (0.43)
(1.00)
Emnloved
Unemnloved
Males
Statistics of Search Choices for Employed and Unemployed
0.77 (0.42)
Fraction Using: Newspapers
Number of Methods Used
TABLE 1.
NT$ 13196.09 (6124.73)
NT$ 13279.23 (4869.40)
0.10 (0.30)
(0.09)
0.008
0.15 (0.35)
(0.4)
0.26
0.17 (0.37)
0.47 (0.50)
(0.44)
0.74
(1.00)
1.90
Emnioved
Total
N.A.a
-0.40
-3.81***
1.56
5.95”’
-0.20
7.78***
-1.04
0.90
4.25***
T-test
w
z?
ij
R
2
g
F
!z
g
251
Job Search Effectiveness for College Graduates
TABLE 2.
Statistics of Search Outcomes for Employed Males
and Unemployed
Job Seekers Total
Females
Unemployed
Employed
Unemployed
Employed
Unemployed
Employed
Fraction Gaining New Employment
0.68 (0.47)
0.42 (0.49)
0.61 (0.49)
0.45 (0.50)
0.65 (0.48)
0.44 (0.50)
Fraction Receiving Offers
0.89 (0.28)
0.79 (0.50)
0.86 (0.31)
0.76 (0.54)
0.87 (0.29)
0.77 (0.52)
Fraction Accepting Received Offers
0.78 (0.38)
0.58 (0.57)
0.73 (0.41)
0.55 (0.58)
0.76 (0.39)
0.56 (0.58)
Wages of Accepted Offers
17561.86 (4988.24)
17827.50 (5277.62)
13562.93 (4257.85)
12748.70 (4001.77)
15777.69 (5011.81)
15337.72 (5229.73)
used by both employed and unemployed job seekers and there is no significant difference in the use of newspapers between the two groups. Connections from friends and relatives constitute the second popular method. Again, there is no significant difference in the fraction using this method between the two groups. Unemployed searchers use the civil-service entrance examination significantly more commonly than employed searchers. This result is reasonable as preparation for this examination requires more time. Unemployed job seekers are also more likely to try to find jobs with the help of government agencies whereas employed job seekers have significantly more access to other methods. Finally, the reservation wages are smaller for the unemployed although the difference is not statistically significant. Hence, the common theoretical predictions that greater costs of search for unemployed persons cause them to exert greater effort in searching and to be more willing to accept job offers are confirmed by these data. Summary statistics on the outcome variables for employed and unemployed seekers appear in Table 2. The results show that a greater fraction of the unemployed receives offers and the fraction accepting an offer is substantially higher for unemployed than for employed job seekers. In particular, we found that employed seekers rejected almost half the offers they received whereas unemployed searchers rejected only about a quarter. Thus, the likelihood of gaining a new job was significantly higher for an unemployed seeker than for an employed job seeker on both counts. Taken together, the summary results of Tables 1 and 2 indicate the importance of considering choices of search effort and reservation wages when comparing search outcomes for the employed and the unemployed, as these choices and outcomes may be linked. The greater search effort and smaller reservation wages of the unemployed (Table 1) are theoretically consistent with their greater rates of finding employment (Table 2).
II.
ECONOMETRIC SPECIFICATION AND ESTIMATION RESULTS
We analyzed these issues more carefully according to Holzer (1987). As stated by Holzer, a common finding of the job search literature is that the probability of gaining
252
JOURNAL OF ASIAN ECONOMICS (6)2,1995
new employment within a certain period is the product of the probability of receiving an offer, and the probability that the wage offered is greater than the reservation wage.6 Based on this relationship, we can specify the empirical equations for the employment outcomes as Holzer did. However, we made modifications as the contents of our data are distinct from those of NLSY data that Holzer used. Specifically, our econometric specifications have the following form:
Po=Po(X,SM,UNEMP,Q,L)+E, PA=PA(wr/wo, UNEMP,Q,L)+q
(3)
where PE, PO,and PAreflect the probability of gaining new employment, receiving a job offer, and accepting an offer conditional on receiving it, respectively; SM indicates the search methods used (we considered seven methods); UNEMP is a dummy variable for unemployed job seekers; Q is a dummy variable for those who quit their jobs to become unemployed; L is a dummy variable for those who were laid-off and became unemployed;? X is a vector of variables affecting the offer and wage functions. Speci~cally, Xincludes education, subject of study, type of institution, gender, marital status, paternal education, financial responsibility, labor market experience, and urban residence. Some econometric issues must be addressed before we turn to our estimation results. The search choice variables are treated as exogenous here, thereby implying a recursive model of search choice formation rather than a simultaneous one. This is not an inappropriate assumption as the search outcomes are observed subsequent to the observation of search choices in the current data set.* As for the wage offer in the PA equation, as we observed wages for only those who accepted offers, we requited a proxy variable for those who failed to accept offers. We applied Heckman’s two-stage method to estimate a wage offer equation and then used the imputed wages for each observation in the sample to estimate the PAequation.g Equations (l)-(3) are estimated independently here by probit. We thereby ignore possible correlation of errors across employment equations, The wage variables in all equations appear in log form. Table 3 shows estimates of equation (1) for the probability of gaining new employment. The estimated results are presented with and without the job leaver dummy variables, as well as with and without search choice variables. The results show that unemployed job seekers are significantly more likely to gain new jobs than are employed job seekers, even after taking into account personal characteristics and search choices. However, the sum of the coefficients for unemployment and forjob leaver dummy variables is negative. This implies that those who were laid-off or quit were somewhat less likely to gain new jobs than were employed searchers..
Job Search Effectiveness for College Graduates
TABLE 3.
Equations
Van’able
253
for Probability
of Gaining New Employment
1
2
3
4
0.542*** (7.44) 0.075*** (1.96)
0.507*** (6.59)
0.613*** (8.88)
0.542*** (7.39)
0.191*** (4.62)
0.131*** (3.62)
0.238*** (6.10)
R
R
R
R
Law, Business, Medical & Engineering
0.023 (0.60)
0.023 (0.62)
0.172’** (4.31)
Others
R
0.169”’ (4.00) R
R
R
Public
0.088** (2.16)
0.101”’ (2.36)
0.099*** (2.58)
0.096” (2.37)
Private
R
R
R
R
Level of Education Graduate School University College Subject
School
Gender Male
-0.091** (-2.39)
Female
R
-0.034 (4.84) R
(Z:; R
0.012 (0.31) R
Marital Status Married
JNI93
-0.096
(-1.42)
(-1.43)
(-1.89)
(-2.09)
R
R
R
R
1984
0.258*** (6.88)
0.336”; (8.55)
0.174”’ (4.98)
0.261*** (7.08)
1985
R
R
R
R
Single or Divorced
-0.117’
-0.134
Labor Market Experiencea
Paternal Education Beyond High School High School
4.108*** (-2.10) R
Below High School
0.32 (0.58) R
-0.084’ (-1.73) R
0.057 (1.09) R
X).116*** (-2.76)
0.053 (1.12)
-0.157*** (-3.95)
0.023 (0.51)
High
-0.153*** (-3.37)
0.171*** (2.76)
X).147*** (-3.41)
0.179*** (3.07)
Median
X).255*‘* (-1.05)
0.085 (1.12)
-0.226”’ (-3.80)
0.112 (1.57)
Urbanization
Low
R
R
R
R
Financial Responsibility Presence
X).141*** (-3.56)
Absence In Reservation
R Wageb
_
-0.079* (-1.92) R -0.049*** (4.80)
-0.129”’ (-3.46) R -
XN61 (-1.57) R 4.038*** (-3.93) (continued)
254
JOURNAL OF ASIAN ECONOMICS
TABLE 3. Variable
Search Methods Newspapers
I
-0.308**’ (-6.73) -0.048 (-1.27) -0.354*** (-7.65) 0.268*** (6.05) -(X202*** (-4.05) -0.464*** (-2.46) 0.284***
Friends/Relatives Civil-service Entrance Examination School Placement Government Agency Private Agency Other Method
(continue) 2
-
-
3
-
(4.09) Unemployed Quit into Unemployment Laid-off into Unemployment Log L
0.947*** (24.62) -2.002*** (-26.40) -2.169*** (-11.68) -3223.22
(6)2,1995
I .092*** (26.58) -1.919*** (-24.45) -2.071*** (-10.75) -3081.57
0*471*** (14.10)
-373 1.63
4
-0.419*** (-9,633 -0.102*** (-2.85) -0.405*** (-9.35) 0.305*** (7.25) -0.250*‘* (-5.36) -O&4*** (-2.64) 0.286*** (4.27) 0.660*** (18.23)
-3510.45
No&s: EquationsestimatedusingProbit. Sample size is 5711. T-ratio is given in parentheses. a: This dummy variable is to indicate fhat those who graduated in 1984 had entered the labor market earlier than those who aduated in 1985. B : In monthly payment. * : Significant at the ten percent level; ** : Significant at the five percent level; *** : Significant at the one percent level (Z-&&d tests).
Of the search choice variables, newspapers, friends/relatives, the civil-service entrance examination, gove~ment, and private agencies show little help in finding new jobs for college graduate job seekers, but they are more likely to gain new employment through school placement and other methods. The unemployment effect remains signi~c~t even with search choice variables added to the equation. The result of the reservation wage variable has a correct sign that is consistent with the common prediction from job search theory. Those with smaller reservation wages are more likely to gain new employment. Tables 4 and 5 present estimates of equations (2) and (3), which decompose the probability of gaining new employment into the probability of receiving offers and of accepting them. ‘*The results reported in Table 4 indicate that unemployed job seekers receive more offers than the employed. However both those who were laid-off or who quit received no more offers than the employed although the difference was small compared to the difference in the probability of gaining new employment between
255
Job Search Effectiveness for College Gradtrates
TABLE 4.
Equations for Probability of Receiving Job Offers
Vurioble
2
I
3
4
Level of Education 0.212*** (2.03)
0.165 (1.53)
0.291*** (2.84)
0.222*** (2.10)
University
0.214*** (4.23)
0.227*** (4.41)
0.241*** (8.62)
0.260*** (7.85)
College
R.
R
R
R
Public
0.523*** (8.61)
0.485”’ (7.83)
0.508*” (8.62)
0.473*** (7.85)
Private
R
R
R
R
Law, Business, Medical & Enginee~ng
0.327*** (6.47)
0.316*** (6.13)
0.327*** (6.59)
Others
R
R
R
0.326’*’ (6.44) R
Male
0.087. (1.76)
0.093’ (1.85)
0.105** (2.18)
0.115** (2.34)
Female
R
R
R
R
Graduate
School
&hoof
Subject
Gender
Marital Status Married
-0.051 (-0.56)
-0.045 (-0.49)
-0.057 (4.64) R
-0.051 (4.56)
R
R
1984
0.301*** (5.93)
0.301”’ (5.87)
0.263*** (5.32)
0.269**’ (5.36)
1985
R
R
R
R
Single or Divorced
R
Labor Market Experiencea
Paternal Education Beyond High School High School Below High School
0.0002 ((O.OtJ3) R
-0.030 (-0.43)
-0.030 (-0.54)
-0.060 (-1.05)
0.020 (0.31) R
R
-0.051 (-0.93)
-0.002 (-0.03) R -0.069 (-1.23)
Urbanization High Median
0.273*** (4.90) -0.076 (-1.03)
Low
R
0.189*** (2.95) -0.144* (-1.82)
0.273*** (5.00) -0.064*** (-0.88)
R
R
0.231*** (3.70) -0.096 (-1.24) R
Financial Responsibility Presence
-0.074 (-1.47)
Absence
R
-0.070 (-1.37)
-0.068 (-1.36)
R
R
-0.057 (-1.14) R
Search Methods Newspapers
-
0.118*’ (2.14)
-
0.054 (1.01) (continued)
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JOURNAL OF ASIAN ECONOMICS (6)2, 1995
TABLE 4.
(Continue)
1
Variable
2
Friends/Relatives Civil Service Entrance Extinction School Placement
4
3
0.027 (0.59)
-
-0.005 (-0.10)
-0.145** (-2.50)
-
-0.190.“: (-3.35)
-xX266*** (4.39)
-
-0.300*** (5.08)
-
-0.185*** (-2.93)
-
-X).226*** (-3.65)
Private Agency
-
-0.348* (-1.86)
-
-0.354’ (-1.88)
Others
-
0.136 (1.56)
-
0.1X?* (1.76)
0.365*** (7.84)
0.421**’ (8.61)
Govemment
Agency
Unemployed
0.671”’ (12.11)
Quit into Unemployment Laid-off into Unemplo~ent Log L
0.694**’ (12.18)
-0.889*** (-11.24)
-0.855*‘* (-10.59)
-1.077*** (-6.83)
-1.043*** (-6.57) -1782.49
-1803.91
-1879.34
-1849.38
Equations estimated using Probit. Sample size is 4326. T-ratio is given in parentheses. a: This dummy variable is to indicate that those who graduated in 1984 had entered the labor market earlier than those who graduated in 1985. : Significant at the 10 percent level; *4 : Significant at the five Percent level: *** : Significant at the one percent level (Zrailed tests).
TABLE 5. Equations for Probability of Accepting Offers Variable In (Relative Reservation
1 Wage)”
Unemployed Quit into Unemployment Laid-off into Unemployment Log L
-
2 1.065*** (12.34)
1.067*” (29.17) -2X05*** (-22.28)
1.252*** (30.54) -2x02*** (-2 1.73)
-2.084*** (-9.37)
-2.001*** (-8.90)
-2097.83
NOMS:Equations estimated using Probit. Sample size is 3884. T-ratio is given in parentheses. “,~II monthly payment. : significant at the one percent level.
-2019.31
4
3 0.643*** (22.14) -
1.128*** (13.62) 0.836*** (25.13) -
-
-
-2432.76
-2336.79
Job Search Effectiveness for College Graduates
25-l
these two groups. These relationships still hold even after taking into account search choices. The search choice variables have less significant effects on the probability of receiving offers than on the probability of gaining new employment. The results on acceptance of offers show that unemployed job seekers accepted significantly more offers than did employed job seekers. As in Table 3 and 4, job leavers accepted fewer offers than the other unemployed and also less than employed job seekers. However, the ratio of reservation wages to offered wages has a significantly positive effect on job acceptance. This result is contrary to the indication from most job search models that the acceptance or rejection of offers is caused exclusively by comparisons of wage offers and reservation wages. Thus, a negative association between the relative reservation wage and the probability of accepting offers is expected. Our finding of a positive effect of the relative reservation wage implies that the acceptance or rejection of offers may not be simply determined by the comparisons of wage offers and reservation wages; other factors may be hidden in the reservation wage variable requiring further investigation. Another possible explanation of this result is that the wage offer variables in this analysis are estimated rather than observed. In sum, the results of Tables 3-5 confirm many predictions made above. In particular, the unemployed received and accepted more job offers than did the employed. These two factors yielded a greater rate of gaining new employment for the unemployed than for the employed. However, when we distinguished job leavers from those who entered the labor market from unemployment, we found that those who are laid-off or who quit their jobs to search receive and accept fewer offers than not only the previously unemployed but also the employed job seekers.
III.
CONCLUSION
The relative effectiveness of employed versus unemployed search is an important issue because the validity of the theory of search unemployment rests implicitly on the notion that unemployed search is more effective than employed search. We have argued that the greater costs of search for unemployed than for employed job seekers is expected to lead the former to invest more effort in search and to have smaller reservation wages relative to offered wages. These predictions are supported by empirical evidence on young college graduate job seekers in Taiwan. Our data show that unemployed job seekers used more search methods and their relative reservation wages were smaller. Moreover, these differences in search choices help to explain differences in search outcomes that we also observed between the two groups. Specifically, the extensive search methods used by the unemployed explain partially the greater probability of their receiving offers, and their smaller reservation wages explain part of their relatively greater rate of job finding. All these results indicate that the theory of search unemployment is valid as the data show that unemployed search is more effective than
258
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
employed search in terms of generating more job offers, accepting more offers received, and therefore gaining more new employment. These findings also suggest that it is worthwhile for a college graduate to invest in full-time job search. Thus, policy makers may not have to worry too much about the situation that there is a relatively higher than average unemployment rate among the college graduate labor force in Taiwan. Their unemployed search can be regarded as an investment activity rather than a waste of human resources. Acknowledgments.
I thank the National Science Council of Taiwan for financial support, Dr. Ching-hsi Chang, Dr. Ying-chuan Liu, and seminar participants at National Chengchi University and the 1994 Western Economic Association International Conference for helpful comments on earlier drafts of this paper, Dr. Huei-lin Wu for providing the data set, and Sonny Wei for research assistance. I am grateful to two anonymous referees for excellent suggestions.
NOTES 1. The purpose of this survey is to investigate the job search behavior and the employment status of college graduates when they first enter the labor market. 2. There were 15,672 males and females included in the original survey conducted in 1986. However, some of them were still in military service or in school during the survey period. These samples were excluded, and therefore only 12,189 cases were left in the final survey. 3. Students who enrolled in normal colleges or universities did not pay for their tuition and fees (the government paid for them) and therefore were required to accept jobs assigned by the government after graduation. 4. Among the unemployed searchers, there is a group of college graduate youth whose unemployed searches refer to their search activities right after graduation and therefore they may be termed as labor market entry unemployed searchers. This term was kindly provided by one of the referees. 5. This survey only collects information on job searches for the most recent search activity for each respondent. That is, for those who were unemployed and conducted search activities as of the survey date, the job search information referred to their most recent search. For those who were employed and had no intention to change their current jobs, the job search information referred to their unemployed search or employed search depending on the respondent’s employment situation prior to their current jobs. For those who were currently employed and conducted search activity, the search information referred to their employed search. 6. As stated in page 602 of Holzer (1987), “the probability of receiving a new job within a certain period is related to reservation wages and search effort in the following manner: PE = 71(&!?)[I - F (w’)], where PE is the probability of gaining employment, w’ is the reservation wage, SE is search effort, n is the probability of receiving an offer, and f(w’) is the density function of wage offers facing an individual.” As shown, the standard search theory implies that a comparison of the reservation and offered wages completely determines the acceptance decision. However, the statistics reported in Table 1 suggest that the employment status may also have influence on the acceptance probability, and therefore the employment status variables are also included in the PA equation. 7. There will be no perfect collinearity problem of including three dummy variables--LINEUP, Q, and Gin the estimation because there is a group of labor market entry unemployed searchers in the sample.
259
Job Search Effectiveness for College Graduates
8. Although the fact that outcomes are observed after search choices are made does not guarantee that the latter are exogenous, a simultaneous treatment would be less appropriate for the current data set. 9. This way to handle the problem of unobserved offered wages can be found in Connelly, DeGraff, and Levison (1994). Details of the estimation of the wage offer equation appear in the appendix. 10. Because of the imperfection of the questionnaire design in the survey, many respondents have missing values regarding the job offer questions. Therefore, the sample size in Table 4 is smaller than that in Table 3. The sample size in Table 5 is smaller than that in Table 4 since those who do not receive job offers are excluded in the estimation of the equations for probability of accepting offers.
APPENDIX This appendix describes the estimation of the wage offer equation. As we observed wages for only those who accepted offers, there is a potential problem of selectivity bias if we apply OLS to estimate the wage offer equation based on the sample with observed wages. Therefore, Heckman’s two-stage estimation approach is applied. The fist stage is a probit estimation of the acceptance of offer based on the sample of observations with offers. Then the selectivity bias-corrected regression is run using the sample of those observations with observed wages. The second stage estimation results are presented in Table A. As shown in Table A, the significant effect of the selectivity variable 1 indicates that selection bias is not negligible in this case.
TABLE
A.
Heckman’s Two Stage Estimates of the Wage Offer Equation
Variables
Coefficient
Constant
8.088***
Age Age Squared
0.074*** -O.o01**
t-Ratio
22.06 2.80 -2.33
Graduate School
0.429***
19.99
University
0.168***
13.21
Major
0.051”’
Public
0.098***
Male
0.172”’
13.74
Married
0.049”’
2.98
Work Experience
0.094***
9.66
Paternal Education Beyond HSa
0.014
Paternal Education Below HSa
4.90 9.69
1.os
-0.004
-0.37
High Urbanization
0.006
0.34
Median Urbanization
0.003 -0.071***
h Notes: Sample size is 3122. R’ = 0.503 “,;HS denotes high school. **/significant at the five percenr
: significant
level.
at the one percent level.
0.13 A.44
260
JOURNAL OF ASIAN ECONOMICS
(6)2,1995
REFERENCES Benhabib, J., & Bull, C. (1983). Job search: The choice of intensity. JournalofPolitical Economy, 91(5), 141-164. Black, M. (1980). Pecuniary implications of on-the-job search and quit activity. Review ofEconomics and Statistics, 62(2), 222-229. -. (1981). An empirical test of the theory of on-the-job search. Journal of Human Resources, 16( 1). 129-l 40. Blau, D. M., & Robins, P. K. (1990). Job search outcomes for the employed and unemployed. Journal of Political Economy, 98(3), 637455. Burdett, K. (1978). A theory of employee job search and quit rates. American Economic Review, 68( 1), 212-220. Clark, K. B., & Summers, L. H. (1979). Labor market dynamics and unemployment: A reconsideration. Brookings Papers of Economic Activity, (I), 13-60. Holzer, H. J. (1987). Job search by employed and unemployed youth. Industrial and Labor Relations Review, 40,601-6 11. Kahn, L., & Low, S. (1982). The relative effects of employed and unemployed job search. Review of Economics and Statistics, 64(2), 234-241. Lin, C. C., & Hsu, L. S. (1988). College graduate youth and their job search behavior. Bulletin of the Institute of Ethnology, Academia Sinica, 58, 225-250. Lippman, S. A., & McCall, J. J. (1976). The economics of job search: A survey. Economic Inquiry, 14, 155-189. Mattila, J. P. (1969). Quit behavior in the labor market. American Statistical Association Proceedings, Economic Statistics Section, 697-701. Mattila, J. P. (1974). Job quitting and frictional unemployment. American Economic Review, 64,235-239. Stigler, G. J. (1962). Information in the labor market. Journal of Political Economy, 70, ‘M-105. Shih, G. T. (1990). An empirical study on the job search behavior in Taiwan’s labor market. M.A. thesis, Department of Economics, National Taiwan University. Wu, C. G. (1980). A study on workers’ quit rate in Kaoshiang export processing zone. Taiwan Economic Review, 9(2), 25-56.
Received
May 1994; Revised
February
1995