the cost of corruption in higher education4 the hierarchy in price and prestige normally includes...

The Cost Of Corruption in Higher Education

Conference on the Economics Of Education Institute for the Study of Economics Of Education

Dijon, France June, 2006

Draft: do not cite without permission of the authors

Stephen P. Heyneman (Vanderbilt University), Kathryn Hart Anderson (Vanderbilt University), Nazym Nuraliyeva (International Kazakh-Turkish University)

[email protected]

[email protected]

Executive Summary Since the collapse of the Soviet Union, there has been a general increase in corruption, affecting many economic sectors. We review the evidence and the economic models pertaining to corruption and apply them in the field of education. The paper defines how corruption occurs in education and draws a link between corruption and educational quality. The paper explains how the quality of higher education affects economic productivity, and makes a case to suggest that a university characterized by corrupt practices has sacrificed that quality. The cost of corruption in higher education is analogous to reducing the economic productivity of a university due to a reduction in its quality. We estimate that the rates of return to corrupt universities would be reduced by anywhere between 2% and 15%. The paper displays the frequency of corruption as reported by students in six countries and suggests that corruption is higher in courses of study with more labor market demand and in universities which adhere to local, rather than international, sources of professional conduct. As to effective interventions we would recommend regular surveys of students such as those reported here. In one country, with surveys at two points in time, the decline in corruption was significant, suggesting when the possibility of exposure and professional embarrassment is real, the propensity to engage in corruption declines. This decline is, however, not uniform. The subject areas where corruption did not decline remain those in high demand, particularly economics and business.

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Introduction: Corruption in the Transition Corruption was symptomatic of business and government interactions in Russia and other countries of the former Soviet Union before and during the economic transition of the 1990s. Corruption is difficult to quantify, but the perception of corruption is quantifiable. Nations can even be arranged along a hierarchy of the degree to which they are perceived as being corrupt, for instance in their business practices or in the administration of public responsibilities. The world map below gives a picture of corruption in business based on the Transparency International Corruption Perception Index for 2005.1 The darker the red in the map below, the more corrupt the country at least from the perspective of those doing business within the country. The former USSR region including Central Asia and the Caucasus are among the most corrupt countries in the world in 2005. Figure 1. Corruption perceptions world map.

Source: Transparency International, 2005.

1 The web address for the map and other information about the Corruption Perceptions Index is: www.transparency.org/policy_research/surveys_indices/cpi/2005.

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Shleifer and Vishny (1993) characterize corruption in Russia and other countries in the former Soviet Union as a principal-agent model in which officials serve as agents for the government in the sale of public goods and services. The agent has property rights over the goods that private consumers to purchase and firms need to use to conduct business. During the era of the party-state, where corruption existed it was centralized and enforced through the mechanism of the political party. As they put it, “…bribes were channeled through local Communist Party offices. Any agreed-upon pattern of corruption would be penalized by the party bureaucracy, so few deviations occurred. Once the bribe was paid, the buyer got full property rights over the set of government goods that he bought.” (Shleifer and Vishny, 1993, p. 605) If consumers and firms needed government goods and services from several different agents, the penchant for corrupt agents to act independently through different Ministries and levels of government in their own self-interest was minimized through the coordination at the Party level. Total economic output was lower than in the absence of corruption but higher than if the actions of individual corrupt agents were independent of the actions of other officials. Total rents collected by agents acting in concert were higher than if corrupt agents acted alone.

During the transition period of the 1990s, centralized, coordinated rent-taking by

the government began to break down. “Sellers of complementary government goods … act independently. Different ministries, agencies, and levels of local government all set their own bribes independently in an attempt to maximize their own revenue, rather than the combined revenue of all the bribe collectors.” (Shleifer and Vishny, 1993, p. 605) The central government weakened and was unable to control the behavior of independent agents, the level of overall corruption probably was higher2, inefficiency inherent in rent-seeking activity within government increased, and output decreased. However, over time as markets opened to global competition and the private sector expanded, more private competitors to government suppliers entered the local markets. If the level of corruption was lower among the new suppliers, consumers and firms could obtain more goods and services that they needed at lower prices. The level of bribes in the aggregate under this scenario, and output and the quality of goods and services increases due to competition for government products. The transition from an administered economy and centralized government to a more open and competitive environment is strongly correlated with transition in rent-seeking within the public sector.

2 Data on the transition of corruption are spotty, but the institutional development during the 1990s is consistent with the predictions from Shleifer and Vishny’s (1993) theory of corruption.

Education and Corruption Anecdotal evidence would suggest that the level of education corruption in the

USSR was lower than in other sectors. The ‘fairness’ of the system, particularly to children of proletarian origins and to minorities, was manifest as a philosophy. However, the education sector is not immune from the influences of corruption, and where it existed, the pattern was likely to have fit in many respects the profile described above. The government would have provided the product to the public [students, suppliers] at a price. The collection of rents would have been coordinated and extracted from students and other buyers of educational products.

What we observe today, however, is that bribes may be obtained in eight different ways within the educational system (Figure 2). In the case of procurement and accreditation, the buyer is the educational institution and the seller of the bribe is the government, usually the ministry of education. In the case of obtaining illegal entrance to specialized programs, having grades raised on the grounds of an illegal payment, or paying illegally for normal educational services (housing, library use, and administrative procedures)3, the buyer is the student and the seller is either a faculty member or the administration. The agents vary but can be broadly classified as teachers, rectors and other administrators, and the Ministry of Education.

3 Students are sometimes required to show their teacher that they have bought the textbook authored by the teacher (rather than using a borrowed book) from a store before they are allowed to take the final examination. Post-graduate students may be asked for a bribe before a member of the dissertation committee will agree to sign off on their doctoral thesis.

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Figure 2. Types of corruption in education by buyer and seller.

BUYERS SELLERS

RECTORS STUDENTS SUPPLIERS

MINISTRY OF EDUCATION

Accreditation Procurement

RECTOR Entrance Examinations

OTHER ADMINISTRATION

Library ServicesHousing Services

FACULTY Entrance Examinations Exam Grades Class Grades Book Sales

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During the economic transition, the central authority in education breaks down and the various agents no longer act in concert. Decentralization and privatization does not reduce bribe-taking, but may significantly increase it. The increase is particularly rapid if international competition from private education providers is restricted. The quality of education is likely to deteriorate during this phase because individual rent-seeking behavior by teachers, administrators, and local and Ministry officials increases and is not coordinated in any way. Competition in the education sector did increase in the transition period. Local private providers of educational goods and services entered the market, and this sometimes included foreign providers. The new suppliers provided education both in the local language or a foreign language. The owners were local, foreign selling a local product, or foreign selling a ‘branded product’.4 The question is whether corruption may vary with this new competition.

From the perspective of social development, corruption in education can be worse than corruption in the police, customs service other forms of corruption because it contains immoral in addition to illegal elements. Much of education corruption is classified under the term ‘professional misconduct’. Professional misconduct is behavior which breaks the code of conduct normally pertaining to the university professorate (Braxton and Bayer, 1999). But ‘corruption’ contains elements beyond the professional behavior. It may include corruption on the part of institutions. Educational institutions which pay a bribe to be accredited for instance (Heyneman, 2004a) may turn out graduates whose skills and professional levels could be a danger to the public. Other educational institutions which commit fraud cheat the public both because they collect an illegal rent, but also because they commit a crime in the very same institution which is established in order to select future leaders on a fair and impartial basis ( Noah and Eckstein, 2001).

Corruption can be efficiency-improving in instances in which prices (tuition, fees,

wages) are distorted by regulation or lags in application.5 However the social benefits from corruption are less likely to be observed in education because corruption affects all the other social goals for making the education investment. (Bardhan, 1997) As a term, corruption is used because of the public good nature of education and education’s role in affecting social cohesion (Heyneman, 2002/3). Because education serves as a way of modeling good behavior for children or young adults, allowing an education system to become corrupt may be more costly than allowing corruption in the customs service or 4 The hierarchy in price and prestige normally includes four categories of institutions: (i) local institutions (public or private) which supply a business degree in the local language; (ii) local institutions which supply a business degree in an international language; (iii) international institutions with unknown names which supply a business degree in an international language, and (iv) an international institutions with a well-known ‘brand name’ which supplies a business degree in an international language. 5Ahlin and Bose (2006) demonstrate that partially honest bureaucrats who bribery is efficiency-improving in a static framework contribute to economic inefficiency when corruption is modeled as a dynamic process and consumers have to reapply continuously for permits and licenses.

the policy. By design, one function of education is to purposefully teach the young how to behave in the future. If the education system is corrupt, one can expect future citizens to be corrupt as well. This clearly must have a cost.

Efficiency also fails within an educational institution if corrupt officials are

affected by nonpecuniary factors such as favoritism towards one’s ethnic, regional, or religious group. In this case, university officials admit unqualified students and faculty, and education becomes a high price, low quality good. Instead of increasing the competition within the university, bribery limits competition and reduces quality. (Bardhan, 1997) The causes of corruption are varied. (See Bardhan (1997) for a review of the economic literature on the causes and consequences of corruption.) Some have argued that corruption is cultural; seriousness varies in treatment from one culture to another, We do not accept the notion that corruption should be treated as a cultural phenomenon, for several reasons. No nation or local community takes pride in having a high level of corruption, hence giving the stigma of corruption face validity. In fact, the opposite is quite common: nations may protest if identified with a high level of corruption. The economic benefits of higher education quality Monetary returns associated with different levels of education attainment is the most common method to gauge economic impact (Giliches and Mason, 1972). But educational quality varies significantly from one part of the world to another (Heyneman, 2004b), and it is axiomatic that to rely on quantity may be economically misleading (Behrman and Birdsall, 1983). Yet finding valid and reliable measures of higher education quality can be difficult (James et. Al., 1989). Nevertheless, progress has been made in terms of hammering out common definitions (Solman, 1975; Welch, 1966), and exploring the relationship between earnings, educational quality and individual ability (Solman and Wachtel, 1975; Kingston and Smart, 1990; Giliches and Mason, 1972; Dale and Krueger, 1999; Brewer, Eide, and Ehrenberg, 1999). Because it is difficult to directly measure college quality, it has been common to utilize proxy measure. These have included college prestige and selectivity (Kingston and Lewis, 1990; Mueller, 1988; Kingston and Smart, 1990; Kingston an Lewis, 1990; Brewer, Eide, and Ehrenberg, 1999; Stayer, 2002); type or purpose (Solman and Wachtel, 1975); and one’s individual course of study (Rumberger and Thomas, 1993; Link, 1973). While most studies have found that the higher quality is associated with higher salaries, some have wondered whether the effect on earnings is though the use of college as a screening device (Psacharopoulos, 1974; McGuinniess, 2003a), or a result of natural ability rather than college quality (Griliches and Mason, 1972; Hause, 1971; 1972). Whichever proxy has been chosen, college quality has generally been found to be positively associated with lifetime earnings (McGuinness, 2003b; Hilmer, 2002; Wales, 1973; Strayer, 2002). In one study, the rate of return to investment in college varied from

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a low of 2.5% to a high of 15.6% depending on the measure of college quality (Ono, 2004, p. 612). Corruption and Higher Education 1. Incidence of corruption In Russia and the 14 other countries within the party state of the USSR, corruption was centralized, enforced and monitored effectively. (Shleifer and Vishny, 1993) With the breakup of the USSR and decentralization, ministries and local governments operated more independently than under the planned economy. The central government’s enforcement mechanisms weakened, and rent-seeking activity could not be effectively coordinated as effectively as under central planning. The result at least in the earliest years of independence was an increase in overall corruption and inefficiency at many levels of government and administration, and the education sector was not immune from these forces. (Schleifer and Vishny, 1993; Shleifer and Treisman, 2005) Ministry officials demanded bribes for accreditation and procurement. Administrators demanded bribes for admission, housing, book rental, grades, exams, and transcripts. Teachers demanded bribes for admission, grades and exams, and book purchases. If a college or university acquires a reputation for having its faculty or administrators accept bribes for entry, grades, or graduation, the power of the university in the labor market is adversely affected. In domestic labor markets, particularly those with many state run enterprises, the risk is less because the choice of graduates will be fewer. But in the private sector and particularly with companies which draw from international labor markets, the effect on a university for a reputation of corruption may be more serious. But how common is the perception of corruption? And how different is the perception of corruption from the actual experience of corruption? We present data from a series of surveys in six countries that were designed to measure and evaluate the incidence of corruption in education. Surveys from Serbia, Croatia, Bulgaria, and Moldova were sponsored by the Open Society Institute regional office in Budapest in 2003. Random samples of university students were asked about corruption in admissions, grading, and housing, and discrimination and their attitudes towards corruption. A large number of these questions were identical in all four surveys, but in Serbia in particular additional questions were included to better identify the corrupt agents and buyers within universities. We also examine more limited information from two countries in Central Asia – Kazakhstan and the Kyrgyz Republic. The Kazakhstan data are from one foreign-managed university and are the teaching evaluation records for all faculty in 2001/2002 and 2004/2005. Only five questions were asked on these evaluations and only one focused on bribery. The second source of information is from surveys of higher education institutions in the Kyrgyz Republic conducted by the Eberts Fund. We do not

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have the individual evaluations from these institutions, however, and rely on tabulations from public reports on corruption within these institutions.6 In the Youth Society for Peace and Development of the Balkans project on Corruption in Higher Education, students at universities in each country surveyed randomly selected samples of students at institutions throughout their countries on their experiences with and attitudes towards corruption in education. We report summary statistics from this project for four countries: Bulgaria, Serbia, Croatia, and Moldova. The sample sizes for these four surveys are given in Table 1a below. In all four countries, significant corruption is evident in admissions and for grades. The incidence of corruption is highest on most dimensions in Serbia. These data are summarized in Table 1a.

6 None of the surveys collected information on bribery where the buyer was the institution. We therefore have no information on corruption in accreditation or procurement.

Table 1a. Incidence of corruption in universities in Bulgaria, Croatia, Moldova, and Serbia (percent). Bulgaria Croatia Moldova Serbia Never heard of illegal methods of admission 21 40 21 16 Thought there was bypassing of the official selection process 37 35 38 45 Percent of faculty who would illegally change admission test scores 33 28a 36a 36 Percent of students using some illegal method of admission 18 18 40 5-20 Percent buying admission exam 9 3 --- 6 Percent who knew of bribery for a grade or an exam among their faculty 60 62 80 66 Percent who said they would offer a bribe to receive a certain grade 17 15 31 20 Percent who said they had ever paid for an exam or grade 7 0.5 28 4 aQuestion is: “Possibilities for admission test scores to be illegally changed.”

Only 16-21 percent of students in Bulgaria, Moldova, and Serbia and 40 percent

in Croatia had never heard about illegal methods of admission (bribes to mediators, professors, or administrators); 35-45 percent thought that the official selection process could be bypassed, and 28-36 percent thought that admission test scores could be changed with bribes. On average the students surveyed thought that about 18-20 percent of students of students in Bulgaria, Croatia, and Serbia and 40 percent in Moldova had used some illegal method of admission, and 6-9 percent admitted to buying the admission exam. Bribery was higher for grades than for admission. Over 60 percent of these students had heard about that some faculty could be bribed for a grade or an exam; 80 percent of students in Moldova knew of bribery for a grade among the faculty. Over 17 percent said they would offer a bribe for a grade, and four-seven percent admitted to bribery for a grade. In Moldova, these percentages are much higher; 31 percent of students would offer a bribe for a grade, and 28 percent said they had paid for a grade.

Many of the students in all four countries had a sort of fatalistic sense about corruption. Few students would report cheating if they observed it, most would cheat if they could get away with it, and few would feel badly about it. These attitudes are summarized in Table 1b.

Nevertheless, even in circumstances in which cheating is the ‘norm’, there

appears to be a significant percentage of students and faculty (11-14 percent) who ‘resist’ the temptation and who consider corrupt behavior to be ‘unacceptable’.

Resisters exist even in circumstances in which corruption is common. What

should be done with those who are caught? Thirty-four percent of the students in Bulgaria thought that they should be expelled; 36 percent of students in Serbia approved of a severe penalty such as expulsion, legal prosecution, jail and public humiliation. However, 90% of the students did not know the penalty for faculty who are caught accepting a bribe, and 87-90 percent of them did not know the penalty for students who cheat (Posliyski and Vatev, nd.).

Table 1b. How Students in Bulgaria, Croatia, Moldova, and Serbia Feel about Cheating. Percent Answering Yes to the Question Bulgaria Croatia Moldova Serbia Would you feel bad after cheating on an examination? 20 25 35 22 If you would be in a situation to cheat without getting

caught, would you cheat? 60 76 67 69 Have you heard about cheating on exams in your university? 77 73 59 79 Table 1c. Bulgarian and Serbian Students Who Cite Cheating as Being Unacceptable Percent Who Answer Unacceptable Bulgaria Croatia Moldova Serbia What is your opinion of students who do not allow their tests to be copied? 20 25 35 22 What is your opinion about copying at the examinations? 21 11 23 13

In study of students at local universities in Kyrgyzstan, the majority of students described their universities as being ‘bribable’. These statistics are given in Table 1d. Table 1d. Higher Education Bribery in Kyrgyzstan: Percent of University Students Describing their University as Bribable Kyrgyz Technical University 68.0 Kyrgyz Agrarian University 67.5 National State University 64.9 Bishkek State University 62.0 Medicine Academy 59.6 Kyrgyz State University of Construction and Architecture 59.0 Kyrgyz Slavonic University (Russian) 51.0 International University in Kyrgyzstan 49.5 Kyrgyz State Physical Culture and Sport Academy 34.3 Source: Ebert Fund. http://akipress.org/news/26369 (in Russian) The degree of corruption in a university located in Central Asia managed by foreigners in accordance with international standards of professional conduct might be expected to have significantly less corruption than in state universities.7 This prediction is supported with the data from the Kyrgyz Republic in Table 1d. Only 5.1% of the students at the American University of Central Asia, for instance, report that their university is ‘bribable’. In other universities, the incidence of bribery was 50-70 percent. (Ebert Fund, March 2, 2006)

Students at the Shymkent Institute of the International Kazak-Turkish University evaluated their professors in the academic year 2001/2002 and again in 2004/2005. Students in 2001/2002 were asked if teachers were willing to take gifts and other payments and if the course was professional.8 There was no warning that the question on bribery would be included on the evaluation. In the 2004/2005 survey of students the bribery question was anticipated and the question was changed so that bribery could be separately identified from giving gifts without requiring a favor from the instructor. The revised question was: “Did the teacher demand gifts or bribes from you?” The percentage of students reporting that the faculty accepted gifts averaged seven percent in 2001; in 2004/2005, 4.3 percent of students reported that their instructors demanded a gift or bribe. There was a significant decline in the percentage of students reporting gift-taking or bribery among faculty after instructors knew that this behavior would be reported, but the decline could be attributable to the redefinition. The Kazak-Turkish University, like the American University of Central Asia, is unique and likely has a lower incidence of

7 A foreign university must adhere to two sources of rules and regulations: from the country where they are situated and in their home country. 8 The professional quality of the course and the instructor was defined in terms of the quality of lectures and seminars, respect from students, and objectivity in evaluation of a student’s progress. The average score of the four professional quality questions was the instructor’s rating on professional skill.

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bribery than state institutions because of the application of Turkish standards of professional conduct to the behavior of faculty and administrators. 2. Who is more likely to accept bribes? Within higher education institutions, there a wide variation in corruption departments and fields. This is evident in the data from the Kazak-Turkish University in 2001/2002 and 2004/2005 which is presented in Table 2a below. In 2001/2002 gift-taking was highest among chemistry, world history, Kazakh literature and language, political science, and economics faculties. 16.8 percent of students in the organic and physical chemistry courses and 8.1 percent of students in economics courses reported gift-taking by faculty. The incidence of bribery or gift-taking declined over the period in all departments except for English language, Economics and Management, Graphics, and Law. The increase in gift-taking in economics for example was from eight to 10 percent, and the increase in law was from 5-4 to 12.8 percent. In contrast, gift-taking among physical and organic chemistry and world history professors fell to about two percent. In English and Law, the professional rating of teaching fell slightly as bribery increased; there was no change in the professional rating of economics instruction over the period. In general the courses of study most likely to be bribable seem to be those in highest demand—law, economics, finance, and criminology – where the competition to enter is greater, the fees and tuitions are larger and where the stakes for graduating are higher. This pattern is consistent with theoretical predictions and empirical evidence from other regions. The probability that an instructor demands or accepts a gift or bribe increases as the difference between the instructor’s opportunity wage (value in the global market) and university compensation widens. If bribery cannot easily be detected or the sanctions for revealed corruption are weak, the probability of bribe-taking is even higher. (Becker and Stigler, 1974; Rose-Ackerman, 1975; Shleifer and Vishny, 1993; Sosa, 2004; van Rijckeghem and Weber, 2001)

The same pattern is observed in Bulgaria and Serbia. Figure 2.1 below is reprinted from the report on corruption in Bulgarian universities and shows by faculty the percentage of students who had bought a textbook as a condition of passing an exam. The incidence of this form of corruption is highest in the medical subjects – general medicine (58 percent) and dentistry (54 percent). This is followed by chemistry (50 percent) and law, history, sociology/political science, economics, and engineering/electronics (40-50 percent).

Table 2a. Proportion of Students Claming they had been asked for a Bribe by departments in the Kazak-Turkish University, 2001 and 2005.

2005

№ Departments 2004-2005%

taking a bribe

Rank on bribe-taking

Percent Taking a

Bribe 2001

Professional Rating 2005

Professional Rating 2001

Professional Rank 2005

1 Turkish language and literature 0 1 4.93 12 Design 0 2 8.96 4.49 4.44 133 Physics 1.04 3 5.63 4.57 4.40 74 Russian language 1.31 4 4.91 4.47 4.61 155 Imitative (fine) arts 1.69 5 8.44 4.47 4.49 146 Information system 1.75 6 5.09 4.33 4.26 327 Programming and computer 1.76 7 4.32 338 Organic and physical chemistry 2.1 8 16.84 4.5 4.08 109 World history 2.34 9 14.88 4.46 4.25 16

10 Center of linguistic 2.4 10 3.1 4.41 4.55 2211 Pedagogic and psychology 2.44 11 4.36 3012 Study of Turkic 2.49 12 7.1 4.57 4.3 613 Clothing design 2.58 13 4.36 4.38 4.46 2714 World literature 2.62 14 5.25 4.35 4.53 3115 History of Kazakhstan 2.71 15 4.02 4.44 4.45 1916 Kazakh literature 2.8 16 10.82 4.56 4.46 817 Mechanics 2.96 17 4.62 4.5 4.25 1218 Physical culture 3.05 18 7.85 4.44 4.46 1819 Kazakh language 3.12 19 9.22 4.44 4.33 1720 Music and singing 3.44 20 5.26 4.76 4.46 221 General and non-organic chemistry 3.69 21 10.1 4.4 4.26 2322 High mathematic 3.76 22 6.9 4.5 4.37 11

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22 Choreography 6.56 23 4.31 2023 Religion 3.77 24 4.41 2524 Foreign language 3.78 25 5.68 4.39 4.47 2625 Ecology 3.83 26 0 4.37 4.46 426 Sport 4.46 27 4.6 927 Political science 5.02 28 9.52 4.55 4.46 2828 Biology 5.2 29 5.93 4.36 4.35 3929 ENGLISH LANGUAGE 5.85 30 3.91 4.17 4.32 3530 Accountant and audit 5.9 31 4.3 2931 German language 6.43 32 4.36 3433 Economic theory 7.21 33 4.37 2434 Anatomy and physiology 7.36 34 4.28 3635 Graphics 7.78 35 6.9 4.68 4.52 336 Philosophy 8.64 36 4.17 3837 Crime and civic law 9.49 37 4.59 538 Finance and credit 10.04 38 4.06 4039 ECONOMICS AND MANAGEMENT 10.09 39 8.11 4.4 4.44 2140 lAW STUDY 12.84 40 5.4 4.19 4.39 37

Source: Shymkent Institute Sociology Survey. Shymkent Kazakhstan, 2006

Figure 2.1. Percentage of students who bought a textbook as a condition of passing an exam, by faculty in Bulgaria, 2003.

Source: Posliyski and Vatev, 2003.

The survey of students in Serbia contained more detailed information on bribery by faculty. Among the 1303 students in the sample, the largest representation is in the Faculty of Medical Science, the Faculty of Economics, and the Faculty of Law. The distribution of students by faculty is given in Appendix Table A.1. Appendix Tables A.2-A.7 report cross-tabulations of the incidence of corruption by faculty. Table 2b below summarizes some of the information reported in these tables for these three faculties in comparison to the total faculty. Students in these departments were more likely to pay other students or faculty to take an exam, to pay a bribe or buy a textbook for a grade, enroll illegally or experience corruption among administrators than within the university as a whole. The pattern of corruption in the table is further support, in a descriptive way, for the predictions from the economic theory of corruption.

Table 2b. Corruption by faculty, Serbia 2003. Frequently or very Frequently Never Reported Reported (1) Students paying other student to take an exam Economics 45.5 3.5 Medical Science 44.2 3.4 Law 40.5 1.6 Total 30.5 6.2 (2) Students paying professors to take an exam Economics 12.5 13.0 Medical Science 4.9 22.8 Law 9.7 15.7 Total 8.5 16.9 (3) Students bribing faculty for a grade Economics 29.5 8.5 Medical Science 26.9 6.2 Law 20.5 11.9 Total 19.0 11.8 (4) Students must buy textbook in order to pass Economics 29.5 8.5 Medical Science 24.9 9.0 Law 28.1 8.6 Total 25.1 13.0 (5) Corruption within the administration Economics 25.5 6.0 Medical Science 16.5 6.2 Law 33.4 4.9 Total 21.4 6.1 (6) Illegal enrolment Economics 24.5 5.5 Medical Science 23.5 7.6 Law 29.2 3.8 Total 23.0 7.4

Corruption and Higher Education Quality

Economic growth in countries of the former Soviet Union was largely affected by the difficulties of transitioning from a command to a market-kind of economy driven by prices and profits. There is evidence that the increase in corruption contributed to the economic difficulties in the region and reduced growth and capital investment. (Kaufman, Kraay, and Zoido-Lobaton (1999); Campos (2000)) But, the causality between corruption and growth is not clear. In a cross-national study of economic growth, investment, and corruption, Mauro (1995) estimates that a one standard deviation increase in corruption (as measured by the Transparency International Corruption Perceptions Index) reduced investment by about three percent overall. Because the fixed cost of public investment increases with corruption, entry of new products and technologies is stifled and long-run economic performance is negatively affected. Economic growth in the long run was negatively affected but in a nonlinear pattern. Corruption channeled resources from public investment into private consumption of government officials including university administrators and staff. During the early investment period and as countries transition out of central planning, economic growth created a “dual-track system” in which some prices were administered and other prices were determined in the market. This offered new opportunities for corruption including bribes, kickbacks, and “crony capitalism.” (Bardhan, 1997, page 1329) In the long run, however, corruption generally fell with growth as the wages of public officials approached market wages, and the profitability of private enterprise increased. With growth, the cost of corruption in terms of long opportunities to earn income increased. Mocan (2004) estimated a simultaneous equations model of corruption and growth based on Treisman’s theoretical macroeconomic model. Corruption is determined by the legal environment, cultural norms, and economic development; economic development is determined by institutional and human capital characteristics of the country, cultural norms, and the legal environment, and corruption. Corruption is measured with the corruption indices from Transparency International Corruption Perceptions Index, the World Bank, Business International, and the International Crime Victims’ Survey ; economic development is growth. He finds a connection between wealth and corruption, but when he controls for the quality of institutions within countries, he finds no impact of corruption on economic growth. His result is in contrast to much of the literature cited in Bardhan (1997).9 Corruption in specific sectors of the economy is also likely to affect performance in that sector and in the economy as a whole. Under central planning, consumers had few alternatives to products produced by the state. If corruption was common but centralized in state enterprises, the only alternative to purchasing goods from these firms was to not buy the good at all. The average quality of the good and the variance in quality were lower than would be expected in a market-based economy. With transition, alternative 9 A study by Gupta, Davoodi, and Tiongson (2002) breaks down growth into sectors and examines the effect of corruption on the provision of education and health services in the economy. They find a significant decline in these services with the increase in corruption.

firms entered the market, and the variance is quality increased across firms. There was more risk associated with buying a product from any enterprise, but the average quality of the product was likely to increase. In this more competitive environment, corruption may signal to consumers that the product is of low quality relative to non-corrupt firms. If over time consumer demand increases in non-corrupt firms relative to corrupt firms, then corruption should erode and the variance in product quality narrow. The higher education sector in the former Soviet Union fits this profile. Under central planning higher education was confined to state universities under the control of Ministries of Education. The variance in quality was small, and rationing within the system was not based on prices but on the preferences of state officials. With transition, the higher education sector expanded; private universities, often supported by foreign organizations, entered the market including the American University of Central Asia in Bishkek and the Kazak-Turkish University in Shymkent. The increase in the supply of higher education institutions in the last 10-15 years led to an increase in the variance in the quality of education.

Education potentially serves two functions in the labor market. First, it is an investment in human capital and develops labor productivity. In this case, we expect to find that each additional year of higher education, for example, increases wage earnings because the student acquires new knowledge that is transferable to employment. The student and society both gain from the private investment in higher education. Second, completion of education can signal to employers that the student is of high ability and has great potential to be a productive employee. Only the most able students are able to complete higher education because the costs of completion (time, money, and effort) are lower than for other students. Higher education may not directly increase the productivity of labor, but it does help employers sort out the most productive from other more costly workers. If education signals ability in the labor market, individual investors gain from investments in education, but the benefits to society are small.

Corruption affects the private and social return to education investment through both of these paths. If students purchase grades, for example, students have less incentive to learn. Advancement is less correlated with knowledge and the acquisition of skill than with wealth and the ability to pay for achievement. The private and social returns to higher education are degraded. The signaling function of education is also reduced if there is significant corruption among faculty and administrators. Completion of education cannot be closely linked to the ability of students if entry into programs and high grades are for sale. The employer does not know whether the student completed the program and did well because she was a high ability, low cost student or because she paid for her grades. The variance in ability of students completing a corrupt program is higher than for students who do not complete a corrupt program. Even if an individual student from a relatively corrupt institution is honest and of high ability, the signaling value of the degree is reduced. An employer with a choice of candidates reduces the risk of hiring an unproductive employee by avoiding graduates of corrupt institutions and programs and hiring only students from institutions with a reputation for honesty. For this employer to hire a student from a corrupt program, the student would have to accept a

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significantly lower salary and prove their economic value to the employer through on-the-job experience.

Corruption in undergraduate institutions affects the probability that a student can

obtain a graduate degree. Graduate schools, particularly in western universities, discount applicants from institutions in which corruption is perceived as common. Applicants from corrupt programs are less likely to be selected because grades and test scores do not represent their ability to do graduate level work.

If employers know the level of corruption within higher education institutions and across programs within these institutions, then we expect employment and earnings to be positively affected by attending a university with a low level of corruption among its faculty and staff. The productivity and signaling functions are illustrated through a standard earnings functions given in (1) below:

itititititit ZXDSWW εββββ +++++= 43210 )ln()ln( . (1) The logarithm of earnings (W) of employee i at time t is a function of the years of education (S), completion of degree (D), market experience (X), and other observable characteristics (Z) of i that affect employment and wage decisions. β1 is the annual rate of return to each year of investment in education; β2 is the sheepskin or signaling effect of education completion. Both β1 and β2 are affected by corruption (C) within the education institution attended by i. The more corrupt the institution, the lower the human capital and signaling values of degrees from the institution, and β1 and β2 are reduced. If education has less value in the labor market if is obtained through corruption, then employers may place a higher weight on other non-educational productivity-related characteristics of workers such as previous work experience, health, and marital status in their employment decisions. The returns to experience (measured through β3) and other characteristics (β4) may increase in the presence of corruption. In general: βj = f(C) , j=1,…,4,

0,0 4321 >∂∂

∂∂

<∂∂

∂∂

Cand

Cand

Cand

Cββββ if X and Z increase the earnings of employee i.

This model is similar to the education quality models of Link (1973) and others.

With information on individual earnings, completion of education, and corruption in education institutions, (1) can be estimated with linear regression and inclusion of interactions between the quantity and quality (corruption) of education.

)2()()()()()ln(

44

332211

ititit

ititititit

eCZcZbCXcXbCDcDbSCcSbaW

+++++++++=

where a, bj and cj (j=1,2,3,4) are estimated regression coefficients. The return to years of education in the absence of corruption is b1 (>0), and the presence of corruption lowers

22

this return to b1 + c1C if c1 < 0 and C is positive. The signaling value of education completion is given by b2, and corruption lowers this value by c2C if c2 < 0. If employers put more weight on X and Z in the presence of corruption (c3 and c4 > 0), then the impacts of X and Z on the log wage increase to b3 + c3C and b4 + c4C.

Equations (1) and (2) assume that the level of corruption is exogenous to the wage and not affected by the unobserved characteristics of workers such as their inherent honesty or ability. This is not likely to be the case for several reasons. Those students who are willing to pay a bribe are more likely to be selected from the lower tail of the ability distribution and have other sources of income, possibly obtained through illegal transactions or corruption in the market. Professors who accept bribes are also not randomly selected from the population of professors but are more likely to be drawn from fields which are in high demand, pay a low salary relative to their value in the outside market, and are from the lower tail of the teaching ability distribution. If a professor graduates highly productive students, this signals her productivity to the private sector and can lead to additional income through contracts and grants. The professors who are of lower ability and have low value in the outside market are more likely to demand bribes to compensate them for their lack of skill. In this case, regression estimation of (2) produces biased estimates of returns to education with and without corruption. We can minimize this bias with instrumental variables estimation or with panel data methods.

Our first attempt to determine the impact of corruption on the value of education ignores the endogeneity problem and examines the level of university corruption based on the teaching evaluation data in Kyrgyzstan and Kazakhstan. We assume that the corruption weight on the return to years of education and the signaling value of completion of degree are equal to the proportion of the faculty who accepted gifts or bribes. We then adjust the estimated returns found in the literature for the level of corruption. If b1 and c1 are equal to b1 and b2 and c2 are equal to b2, then the return to years of schooling is (1-b1)(C) and the sheepskin effect is (1-b2)(C) in the presence of corruption and b1 and b2 in the absence of corruption.

The literature on the returns to education in the East European and Eurasian region is small in comparison to the literature in OECD countries and other middle income countries. The first usable, unbiased worker level data were acquired after the breakup of the former Soviet Union. Anderson (2006) summarizes the literature on returns to education in this region during the post-Soviet period. Her table is reprinted in Appendix Table A.9. Returns to education in Russia range from .03 to .10 and are slightly higher for women than men. Returns in Eastern and Central Europe range from .02 to .05, and in all countries in the region returns increased over time. Studies that looked at completion of degrees and not years of schooling find, in general, no significant return to secondary education over primary and a large positive return to college over primary or secondary. For Central Asia, Anderson and Pomfret (2003) estimate positive returns of 17-20 percent for higher education or about three percent per year of college; these returns are lower than estimates for Central Europe, the Baltics, and Russia. University education increased earnings by 60-80 percent in the Czech Republic and 100

23

percent in Hungary and by 70-76 percent in Estonia over basic education. The annual return to college completion was about 10 percent in Russia.10

We assume that the teaching evaluation scores in Kazakhstan and the Kyrgyz Republic measure the extent of corruption in universities in this region. These corruption scores range from 4.3 percent in the Kazakh-Turkish University in Kazakhstan to 68 percent at the Kyrgyz Technical University. We combine these ratings with the estimated returns to education found in Anderson and Pomfret (2003) to measure the value of education in markets with low and high levels of university corruption. If a student of average productivity with a university degree from Kazakhstan or the Kyrgyz Republic graduated from a university with low corruption (4.3 percent, for example), the gain in the Central Asian labor market from obtaining a college diploma would fall from .17-.20 to .163-.192. If this same student graduated from a university with high corruption (68 percent, for example), the signaling value of the degree would fall to .054-.064. If the productivity from the years of study within these institutions were also degraded by corruption, the value of higher education in the Central Asian labor market would fall even more.

Nations would have to reduce the social returns to their investments in education in proportion to the level of perceived domestic corruption.11 Using Ono’s results, the returns to higher education would have to be reduced by a minimum of 2.5% and a maximum of 15% if the quality of the university was downgraded due to corruption.

10Fleisher, Sabirianova, and Wang (2005) review the literature on the returns to education in Russian, Central and Eastern Europe, and China using meta-analysis. They link these returns to economic reform. They find that returns to education increased as reform was adopted in these countries. Specifically, privatization and deregulation positively affected the value of education in these countries. This evidence is consistent with the literature on corruption in education. Privatization of education increased and regulation from the Ministry level declined although slowly. A one standard deviation increase in the speed of reforms is associated with a .5 percentage point improvement in the return to education. This is additional but indirect evidence that competition can benefit university graduates in the region. Competition is associated with diminution of corruption. (Shleifer and Vishny, 1993) 11 A university system may suffer from the perception of corruption independently from the level of actual corruption. Perception, however, determines the level of discount necessary. Hence, the burden of proof (through regular and transparent evaluations, open accounts, and public codes of conduct) is on the university to demonstrate that it is not corrupt.

24

Summary This paper has reviewed the evidence to date on corruption in higher education and has attempted to estimate its costs. Like other illegal and unprofessional activities, the prevalence and distribution of education corruption is difficult to estimate. Although educational corruption existed under the Soviet Union, we hypothesize that it was modest by comparison to the level today. The quantity has increased because decentralized decision-making makes actors more difficult to control, because of the proliferation of university owners and purposes, because of the inexperience with enforcing professional norms without traditional sanctions. Moreover, private education and tuition-based public education have been new, and there is little experience in managing the expectations of fee-paying students.12 The paper illustrates the extent of higher education corruption by citing student surveys in six countries – Kyrgyzstan, Kazakhstan, Croatia, Moldova, Serbia and Bulgaria. These surveys suggest that corruption varies in accordance with the market demand of the subject of study, with higher frequencies of corruption found in the subjects in highest demand. Also, corruption is more likely to be found in local universities with local professional codes of conduct, and less likely to be found in universities accredited in Europe or North America. By adapting a model used originally to estimate the contribution of higher education quality, we hypothesize that the cost to a student who attends a university characterized by a high level of corruption would be the equivalent of sacrificing the economic impact of higher education quality. We estimate that the economic rates of return to public investment in education would have to be reduced from between 2 and 15 % as a result of the sacrifice in quality due to academic corruption. As to effective interventions we would recommend regular surveys of students such as those reported here.13 In one country, with surveys at two points in time, the decline in corruption was significant, suggesting when the possibility of exposure and professional embarrassment is real, the propensity to engage in corruption declines. This decline is, however, not uniform. The subject areas where corruption did not decline remain those in high demand, particularly economics and business.

12 Where professional integrity is not based on tradition, ‘private’ university may imply that all educational products are for sale. Codes of conduct and legal agreements spelling out the rights and obligations of students and faculty are only now beginning to appear. 13 A complete list of interventions to lower the incidence of education corruption can be found in Heyneman (2004a).

25

Bibliography Ahlin, Christopher and Bose, Pataki. 2006 “The pitfalls of a partially honest bureaucracy: Bribery, inefficiency and bureaucratic delay.” Forthcoming, Journal of Development Economics. Anderson, Kathryn. 2006. “The importance of social investments for economic growth and governance in transitioning states: a survey of recent evidence.” Report prepared for United States Agency for International Development through Aguirre International. Anderson, Kathryn and Pomfret, Richard. 2003. Consequences of Creating a Market Economy: Evidence from Household Surveys from Central Asia. Cheltenham, UK: Edward Elgar Press. Bardhan, Pranad. 1997 “Corruption and development: a review of issues,” Journal of Economic Literature 35(September), pp. 1320-1346. Becker, Gary S. and Stigler, George J. 1974 “Law enforcement, malfeasance, and compensation of enforcers,” Journal of Legal Studies 3, pp. 1-19. Behrman, Jere R. and Birdsall, Nancy. 1983 “The quality of schooling: Quantity alone is misleading,” American Economic Review 73 (December), pp. 928 – 46. Brewer, Dominic J., Eide, Eric R. And Ehrenberg, Ronald G. 1999 “Does it pay to attend an elite private college? Cross-Cohort Evidence on the Effects of College Type on earnings,” Journal of Human Resources Vol. 34 (Winter),pp. 104 – 23. Campos, N. 2000 “Context is Everything: Measuring Institutional Change in Transition Economies,” World Bank Policy Research Working Paper 2269. Washington, DC: The World Bank. Fleisher, Belton M., Sabirianova, Klara and Wang, Xiaojun. 1995 “Returns to skill and the speed of reforms: Evidence from Central and Eastern Europe, China and Russia,” Journal of Comparative Economics 33(1), pp. 351-370. Gould, David J. and Amaro-Reyes, José A. 1983 “The effects of corruption on administrative performance,” World Bank Working Paper No. 580. Washington, DC: The World Bank. Griliches, Zvi and Mason, William M. 1972 “Education, Income and Ability,” Journal of Political Economy Vol. 80 (May/June, Part 2), pp. S74 – S103. Gupta, Ganjeev, Davoodi Hamid, and Tiongson, Erwin. 2002 “Corruption and provision of health care and education services.” In, George T. Abed and Sanjeev Gupta (eds.), Governance, Corruption and Economic Performance. Washington, DC: The International Monetary Fund.

Hause, John C. 1971 “Ability and Schooling as Determinents of Lifetime earnings or If you’re So Smart, why aren’t you Rich?” American Economic Review Vol. 61 (May), pp. 289 – 98. ------------------. 1972 “Earnings Profile: Ability and Schooling,” Journal of Political Economy Vol. 80 (May-June), pp. 108 – 38. Heyneman, S.P. 2002/3 “Defining the influence of education on social cohesion,” International Journal of Educational Policy, Research and Practice Vol. 3 (Winter), pp. 73 – 97. -------------------- 2003 “Education and Misconduct.” In, James Guthrie (ed.) Encyclopedia of Education. New York: Maxmillan Publishers, Vol. 5, pp. 1659 – 68. -------------------- 2004b “International Education Quality,” Economics of Education Review Vol. 23 (August), pp. 441 – 52. ----------------------- 2004a “Education and Corruption,” International Journal of Education Development Vol. 24 (6), pp. 638 – 48. ---------------------- 2005 “Organizations and Social Cohesion,” Peabody Journal of Education Vol. 80 (4), pp. 1 – 8. Hilmer, Michael J. 2002 “Human Capital Attainment, University Quality, and Entry-Level Wages for College Transfer Students,” Southern Economic Journal Vol. 69 (October), pp. 547 – 69. James, Estelle, Alsalam, Nabeel, Conaty, Joseph C. and Duc-Le To 1989 “College quality and future earnings: Where should you send your child to college?” The American Economic Review Vol. 79 (2), pp. 247 – 52. Johnson, Simon, Kaufman, Daniel and Zoido-Lobatόn, Pablo. 1998 “Regulatory discretion and the unofficial economy,” American Economic Review 88 (May), pp. 387-392. Kingson, Paul William and Lewis, Lionel S. 1990 “Introduction: Studying Elite Schools in America.” In,Paul William Kingston and Lionel S. Lewis (eds.) The High Status Track: Studies of Elite Schools and Stratification, Pp. xi – xxxiv. Albany: State University of New York Press. Kingston, Paul William and Smart, John C. 1990 “The economic payoff of prestigious colleges.” In,Paul William Kingston and Lionel S. Lewis (eds.)The High-Status Track: Studies of Elite Schools and Stratification, Pp. 147 – 74. Albany: State University of New York Press.

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Link, Charles R 1973 The Quantity and Quality of Education and their influence on earnings: the case of chemical engineers,” The Review of Economics and Statistics Vol. 55 (May), pp. 241 – 47. Mauro, Paulo. 1995. Corruption and growth. Quarterly Journal of Economics 110 (August), pp. 681-712. McGuinness, Seamus. 2003a “Graduate Overeducation as a sheepskin effect: evidence from Northern Ireland,” Applied Economics Vol. 35 (March 20), pp. 597 – 608. ------------------------ 2003b “University quality and labour market outcomes,” Applied Economics Vol. 35 (December 15), pp. 1943 – 55. Mocan, Naci. 2004 “What determines corruption? International evidence from micro data,” National Bureau of Economic Research Working Paper No. 10460. Cambridge, MA: NBER. Mueller, Ralph O. 1988 “The Impact of college selectivity on income for men and women,” Research in Higher Education, Vol. 29 (October), pp. 175 -91. Noah, Harold J. and Eckstein, Max A. 2001 Fraud and Education: the worm in the apple. Lanham (Maryland): Towman and Littlefield Publishers. Ono, Hiroshi, 2004 “College Quality and Earnings in the Japanese Labor Market,” Industrial Relations Vol. 43 (July), pp. 595 – 617. Psacharopoulos, George 1974 “College quality as a screening device,” Journal of Human Resources Vol. 9 (Fall), pp. 556 – 8. Posliyski, S. and Vatev, V. n.d. “Survey Report: Corruption in Higher Education” Sofia, Bulgaria: Anti-Corruption Student Network in South Eastern Europe. Mimeographed. Rose-Ackerman, Susan. 1975 “The economics of corruption,” Journal of Public Economics 4 (February), pp. 187-203. Rumberger, Russell W. and Thomas, Scott L. 1993 “The economic returns to college, major, quality, and performance: a Multilevel analysis of recent graduates,” Economics of Education Review Vol. 12 (March), pp. 1 – 19. Shleifer, Andrei and Treisman, Daniel. 2005 “A normal country: Russia after Communism,” Journal of Economic Perspectives 19(Winter), pp. 151-174. Shleifer, Andrei and Vishny, Robert W. 1993 “Corruption,” Quarterly Journal of Economics 108(August), pp. 599-617.

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Solmon, Lewis C. 1975 “The definition of college quality and its impact on earnings,” Explorations in Economic Research Vol. 2, pp. 537 – 87. Solmon, Lewis C. and Wachtel, Paul. 1975 “The effect on income of type of college attended,” Sociology of Education Vol. 48 (Winter), pp. 75 – 90. Sosa, Luis A. 2004 “Wages and other determinants of corruption,” Review of Development Economics 8(4), pp. 597-605. Stayer, Wayne 2002 “The Returns to School Quality: College Choice and Earnings,” Journal of Labor Economics Vol. 20 (3), pp. 475-503 van Rijckeghem, Caroline and Weber, Beatrice. 2001 “Bureaucratic corruption and the rate of temptation: do wages in the civil service affect corruption and by how much?” Journal of Development Economics 65(2), pp. 307-331. Wales, Terence J. 1973 “The Effect of College Quality on Earnings from the NBE Thornkike Data,” Journal of Human Resources Vol. 8 (Summer), pp. 306 – 17. Welch, Finis. 1966 “Measurement of the quality of schooling,” American Economic Review Vol. 56 (June), pp. 379 – 92.

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Appendix A Table A.1. Faculty representation within the sample of students in Serbian universities.

30

Table A.2. Incidence of illegal enrolment in courses by faculty, Serbia 2003.

31

Table A.3. Corruption within the administration of the faculty, Serbia 2003.

32

Table A.4. Incidence of bribery for an exam by faculty, Serbia 2003.

33

Table A.5. Incidence of bribery for a grade by faculty in Serbia, 2003.

34

Table A.6. Illegal enrolment by faculty, Serbia 2003.

35

Table A.7. Percent requiring students to buy their textbook in order to pass, Serbia 2003.

36

37

Table A.8. Incidence of students paying other students to take an exam for them, Serbia 2003.

Table A.9. Summary of estimates of rates of return to education. Research Years

Studied EarninMeasure

Countries Years of education

Completed secondary

Vocational Courses

Vocational: Firm

Technical/ professional

University Post- Graduate

Russia, Ukraine Brainerd, 1998

1991 1993 1994

Monthly earnings (Ln)

Russia: 1991 1994

M F .03 .05 .07 .10

M F -.10 -10 NS -.12

M F NS NS NS NS

M F NS .14 NS .25

Obloblin, 1999

1994-1996

Monthly wages + bonuses + benefits (Ln)

Russia

M F NS NS

M F NS NS

M F NS .15

M F .11 .32

Brainerd, 2000

1984 1992


Russia 1984 1992

.03 .05 .06 .10

Reilly, 2000 1992

1996 Monthly & hourly earnings (Ln)

Russia 1992 1996

M .19 NS (primary)

M NS NS

M F. .32 .21

Clark, 2003 1994-98 Monthly

wage (Ln) Russia 1994/95

1998 State Private

8 .09 .12 .17

.005-.006 .01-.007

.02-.08 -.05-(-.03)

.06-.07 .08

.09-.11 .10

-.07-(-.06) -.14-(-.13)

Brainerd, 2000

1984 1992


Ukraine 1984 1992

.06 .07 .09 .10

gs

State Private

.0

Table A.9. Summary of estimates of rates of return to education, continued.

Ganguli and Terrell, 2005

1986-2003

Net Contractual Monthly Salary (Ln)

Ukraine:

M F NS NS

.

NS NS

NS .15

.21 NS

Baltic States Kroncke and Smith, 1999

1989 1994


Estonia 1989 1994

Es Ru .02 NS .05 .05

Orazem and Vodopivec, 2000

1989 1994

Estonia: 1989 1994

M F .17 .09 .40 .40

M F .12 NS .27 .19

M F .21 .25 .70 .76

Hazans, Eamets, Earle, 2003

1999, 2000


Estonia Latvia Lithuania

.08 ..05 .07

.28 .21 .35

Eastern Europe: Jones and Simon, 2005

1989- 1992

Monthly wage + bonus (Ln)

Bulgaria: 1989/90 1991/92

.02 .04

Brainerd, 2000

1984, 1992


Bulgaria 1984 1992

.05 .06 .04 .07

Paternostro and Sahn, 1999

Gross hourly wage (Ln)

Romania, Rural Urban

M F .11 ..34 .09 .13

M F .28 .59 .24 .23

M F .43 .87 .44 .58

39


Andren, Earle, Sapatoru, 2004

1950-2000

Net monthly earnings, primary job (Ln)

Romania: 1950 1994-2000: Old ed. New ed.

.03 .06-.09 .08-.09

Lokshin and Jovanovic, 2003

1995-2000

Hourly gross wage, main job (Ln)

Yugoslavia State Private

M F -.45 -.40 -.27 -.49

M F -.47 -.56 NS -.54 (primary)

M F -.24 -.23 NS NS

Estimates relative to university education

Central Europe: Chase, 1998 1984

1993 Monthly Earnings (Ln)

Czech Republic: 1984 1993

M F .02 .04 .05 .06

.03 .03 .06 .07

.08 .13 .10 .28

.15 .16 .23 .27

.26 .36 .48 .45

.48 .49 .48 .48

Brainerd,2000 1984,

1992 Monthly earnings (Ln)

Czech Republic 1984 1992

M F .04 .07 .06 .08

Pailhe, 2000

1992 Monthly wage (Ln)

Czech Republic

.03 .03

Juragda, 1999 1998 Hourly wage Czech

Republic Public Private

.12 .12

.49 .39

.72 .72

.89 .85

40


Münich, Svejnar, Terrell, 2005b (JCE)

1989- 2002

Hourly earnings (Ln)

Czech Republic: 1989: 1996: State Private Sm. Private 2002: State Private Sm. private

.04 p.07 .06 .07 .08 .07 .07 .07 .06

.10 .37 .35 .41 .34 .36 .39 .30 .37

.067 .156 .196 NS .20 .124 .206 .NS .184

.20 .38 .46 .32 .39 .32 .43 .24 .25

.37 .65 .62 .80 .78 .61 .65 .70 .61

Münich, Svejnar, Terrell, 2005a

1991- 1996

Hourly earnings (Ln)

Czech Republic 1989-90 1991-96 State Private De Novo

.03 .06 .055 .065 .061

.14 .35 .40 NS NS

(3 years) .078 .11 NS .16 NS

.13 .29 .32 .33 .25

.28 .54 .48 .67 .60

Brainerd,2000 1984,


Hungary 1984 1992

.04 .07 .09 .09

Pailhe, 2000


Hungary .04 .04

Joliffe and Campos, 2004

1986- 1998

Monthly base + other wage (Ln)

Hungary 1986 1998

M F

M F .24 .29 .53 .60

M F .19 .21 .31 .30

M F .32 .36 .59 .63

M F .69 .79 1.28 1.24

41


Brainerd,2000 1984,


Poland 1984 1992

.04 .06 .05 .08

Pailhe, 2000


Poland

.04 .04

Keane and Prasad, 2002

1985- 1996

Quarterly earnings (Ln)

Poland 1986 1992 1996

.18 .26 .34

.13 .12 .17

.37 .53 .68

Chase, 1998 1984


Slovakia: 1984 1993

.03 .04 .05 .05

.02 .13 .06 .10

NS .17 .26 .25

.09 .22 .19 .24

.25 .44 .42 .50

.56 .50 .53 .45

Brainerd,2000 1984,


Slovak Republic 1984 1992

.04 .07 .06 .09

Pailhe, 2000


Slovakia

.02 .04

Juragda, 1999 1998 Hourly wage Slovak

Republic Public Private

.20 .09

.47 .25

.83 .63

.97 .83


1987 1991

Slovenia: 1987 1991

M F .32 ..37 .41 .47

M F .16 .16 .20 .18

M F .72 .77 .94 .94

42



1984 1992

Slovenia: 1984 1992

M F .32 .37 .41 .47

M F .16 .16 .20 .18

M F .72 .77 .95 .94

Central Asia Anderson and Pomfret, 2003

1993-1997


Kyrgyz Republic: 1993 1997

M F NS NS NS NS

M F NS NS NS NS

M F .19 .21 .20 .17

Germany Hunt, 2002 1990-

1994 Monthly base wage (Ln)

East Germany 1990 1994

(general schooling) .-.42 -.39

-.23 -.19

Comparison category

.16 .13

43

the cost of corruption in higher education4 the hierarchy in price and prestige normally includes...

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