Disparities between Arabs and Jews in school resources and student achievement in Israel

Economic Development and Cultural Change

Volumn 47, Issue 1, 1998, Pages 174-192

  Lavy, Victor ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 7044286366     PISSN: 00130079     EISSN: None     Source Type: Journal    
DOI: 10.1086/452391     Document Type: Article

References (41)

1. Eric Hanushek, "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature 23 (1986): 1141-77, and "The Impact of Differential Expenditures on School Performance," Educational Researcher 18, no. 4 (1989): 45-51.
2. Eric Hanushek, "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature 23 (1986): 1141-77, and "The Impact of Differential Expenditures on School Performance," Educational Researcher 18, no. 4 (1989): 45-51.
3. Eric Hanushek, "Money Might Matter Somewhere: A Response to Hedges, Laine, and Greenwald," Educational Researcher 23 (4): 5-8, and "Interpreting Recent Research on Schooling in Developing Countries" (University of Rochester, Rochester, N.Y., mimeographed, 1994); Eric Hanushek, Steven G. Rivkin, and Lori L. Taylor, "Aggregation and Estimated Effects of School Resources," Working Paper no. 397 (Rochester Center for Economic Research, University of Rochester, Rochester, N.Y., 1995).
4. Eric Hanushek, "Money Might Matter Somewhere: A Response to Hedges, Laine, and Greenwald," Educational Researcher 23 (4): 5-8, and "Interpreting Recent Research on Schooling in Developing Countries" (University of Rochester, Rochester, N.Y., mimeographed, 1994); Eric Hanushek, Steven G. Rivkin, and Lori L. Taylor, "Aggregation and Estimated Effects of School Resources," Working Paper no. 397 (Rochester Center for Economic Research, University of Rochester, Rochester, N.Y., 1995).
5. Eric Hanushek, "Money Might Matter Somewhere: A Response to Hedges, Laine, and Greenwald," Educational Researcher 23 (4): 5-8, and "Interpreting Recent Research on Schooling in Developing Countries" (University of Rochester, Rochester, N.Y., mimeographed, 1994); Eric Hanushek, Steven G. Rivkin, and Lori L. Taylor, "Aggregation and Estimated Effects of School Resources," Working Paper no. 397 (Rochester Center for Economic Research, University of Rochester, Rochester, N.Y., 1995).
6. See, e.g., William Sander, "Expenditures and Student Achievement in Illinois," Journal of Public Economics 52 (1993): 403-16; Larry V. Hedges, Richard D. Laine, and Rob Greenwald, "Does Money Matter? A Meta-Analysis of Studies of the Effects of Differential School Inputs on Student Outcomes," Educational Researcher 23, no. 3, (April 1994): 5-14.
7. See, e.g., William Sander, "Expenditures and Student Achievement in Illinois," Journal of Public Economics 52 (1993): 403-16; Larry V. Hedges, Richard D. Laine, and Rob Greenwald, "Does Money Matter? A Meta-Analysis of Studies of the Effects of Differential School Inputs on Student Outcomes," Educational Researcher 23, no. 3, (April 1994): 5-14.
8. The 1991 arithmetic tests included 45 questions for the fourth grade and 48 questions for the fifth grade. The reading comprehension test included 57 questions for the fourth grade and 60 questions for the fifth grade. Each test included a subtest of 15 questions as a criterion-referenced test for very basic knowledge and was defined as a basic skills test. Failure to answer three or more questions was recorded as a failure in the minimum competency tests. A norm test score was defined as the percentage of correct answers from a set of questions that included several items from the basic test and all the questions from number 16 to the end of the test. More details on the design and implementation of the tests, as well as on their results, are provided in reports published by the National Educational Testing Center, the Van Leer Jerusalem Institute, in October 1991 and October 1992.
9. It should be noted however, that results in the Arab sector are based on formal schools only; about 6% of all students in the elementary school system are in the nonformal system. Furthermore, the share of students in special education schools is larger among Jews than Arabs. The inclusion of Arab students in regular schools who should, in fact, be in special schools and the exclusion from data of Arab students from the nonformal schools make a simple comparison to the Jewish sector inappropriate.
10. This is the main endogenously allocated input, distributed to schools in the Jewish system as a function of the percentage of underprivileged students in the school. This variable, computed as a weighted average of parental education, family size, and country of origin, is not available for Arab schools and is therefore not used as a criterion for resource allocation.
11. For more evidence on this group, see also R. Klinov, "Arab-Jewish Disparities in Local Government Budgets," (Hebrew University, Department of Economics, 1989, mimeographed), and Allocation of Public Resources to Education (Jerusalem: Center for Social Policy Studies in Israel, 1991); Institute for the Study of Education Systems, Trends in the Education Budget in the Eighties in Israel (Jerusalem: Institute for the Study of Education Systems, 1993).
12. For more evidence on this group, see also R. Klinov, "Arab-Jewish Disparities in Local Government Budgets," (Hebrew University, Department of Economics, 1989, mimeographed), and Allocation of Public Resources to Education (Jerusalem: Center for Social Policy Studies in Israel, 1991); Institute for the Study of Education Systems, Trends in the Education Budget in the Eighties in Israel (Jerusalem: Institute for the Study of Education Systems, 1993).
13. For more evidence on this group, see also R. Klinov, "Arab-Jewish Disparities in Local Government Budgets," (Hebrew University, Department of Economics, 1989, mimeographed), and Allocation of Public Resources to Education (Jerusalem: Center for Social Policy Studies in Israel, 1991); Institute for the Study of Education Systems, Trends in the Education Budget in the Eighties in Israel (Jerusalem: Institute for the Study of Education Systems, 1993).
14. See, e.g., Stewart C. Purkey and Marshall S. Smith, "Effective Schools: A Review," Elementary School Journal 83, no. 4 (1983): 427-52.
15. On the role of primary schools, see Bert Creemers, T. Peters, and David Reynolds, School Effectiveness and School Improvement (Amsterdam: Swets & Zeit, 1990); J. S. Coleman, et al., Equality of Educational Opportunity (Washington, D.C.: U.S. Department of Education, 1966); and R. J. Murnane, "Interpreting the Evidence on School Effectiveness," Teachers' College Record 83, no. 1 (1981): 19-35. On the contribution of physical and pedagogical inputs, see Hanushek, "Economics of Schooling."
16. On the role of primary schools, see Bert Creemers, T. Peters, and David Reynolds, School Effectiveness and School Improvement (Amsterdam: Swets & Zeit, 1990); J. S. Coleman, et al., Equality of Educational Opportunity (Washington, D.C.: U.S. Department of Education, 1966); and R. J. Murnane, "Interpreting the Evidence on School Effectiveness," Teachers' College Record 83, no. 1 (1981): 19-35. On the contribution of physical and pedagogical inputs, see Hanushek, "Economics of Schooling."
17. On the role of primary schools, see Bert Creemers, T. Peters, and David Reynolds, School Effectiveness and School Improvement (Amsterdam: Swets & Zeit, 1990); J. S. Coleman, et al., Equality of Educational Opportunity (Washington, D.C.: U.S. Department of Education, 1966); and R. J. Murnane, "Interpreting the Evidence on School Effectiveness," Teachers' College Record 83, no. 1 (1981): 19-35. On the contribution of physical and pedagogical inputs, see Hanushek, "Economics of Schooling."
18. On the role of primary schools, see Bert Creemers, T. Peters, and David Reynolds, School Effectiveness and School Improvement (Amsterdam: Swets & Zeit, 1990); J. S. Coleman, et al., Equality of Educational Opportunity (Washington, D.C.: U.S. Department of Education, 1966); and R. J. Murnane, "Interpreting the Evidence on School Effectiveness," Teachers' College Record 83, no. 1 (1981): 19-35. On the contribution of physical and pedagogical inputs, see Hanushek, "Economics of Schooling."
19. Ralph Harbison and Eric Hanushek, Educational Performance of the Poor: Lessons from Rural Northeast Brazil (New York: Oxford University Press, 1992); E. Valéz, E. Schiefelbein, and J. Valezuela, "Factors Affecting Achievement in Primary School," Human Resources Working Paper no. 2 (World Bank, Washington, D.C., 1993).
20. Ralph Harbison and Eric Hanushek, Educational Performance of the Poor: Lessons from Rural Northeast Brazil (New York: Oxford University Press, 1992); E. Valéz, E. Schiefelbein, and J. Valezuela, "Factors Affecting Achievement in Primary School," Human Resources Working Paper no. 2 (World Bank, Washington, D.C., 1993).
21. Hanushek, "Money Might Matter Somewhere" (n. 2 above), and "Interpreting Recent Research on Schooling" (n. 2 above).
22. Hanushek, "Money Might Matter Somewhere" (n. 2 above), and "Interpreting Recent Research on Schooling" (n. 2 above).
23. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
24. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
25. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
26. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
27. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
28. In a study of all primary schools in Israel, A. Minkevich, A. Davis, and D. Bashi (Educational Achievements in Primary Schools in Israel [Jerusalem: Magnum Press, 1980] [in Hebrew]) conclude that home background accounted for a larger share of the explained variance in a student's achievements than did school characteristics. The study focused mainly on student characteristics and less on detailed measures of school educational inputs. In S. Smilanski and L. Shfatia ("The Relationship between Integration, Class Level Variables and Achievements in First and Second Grade," Megamot 23, no. 4 [1977]: 79-87 [in Hebrew]), the authors examined the determinants of achievements of first and second graders and found that teacher characteristics, experience, and education did not add any explanatory power to the regressions. However, a study of primary schools in Tel Aviv found that teacher characteristics (age, experience, education, ethnic origin) had a major effect on student achievements. See Tel Aviv Municipality, Achievement, Students' Background, and Teachers' Characteristics in Primary Schools (Tel Aviv: Department for Research and Statistics, 1976) (in Hebrew). A great many other studies focused on the achievement gap between students from families originating from North Africa or the Middle East versus others (e.g., Israeli born or originating from Europe or North America). See, e.g., A. Yogev and D. Kfir, "Factors Affecting High School Schooling Choice," Megamot 27, no. 3 (1981): 139-53 (in Hebrew); A. Yogev and C. Ayalon, The Law of Free High School and Equality of Opportunities in High School Education (Tel Aviv: Sapir Institute, Tel Aviv University, 1985) (in Hebrew); and S. Svirski, Education in Israel (Tel Aviv: Brerot, 1990) (in Hebrew). All examined this issue, but none looked into the issue of the effect of school resources, school educational inputs, and student achievements.
29. Hanushek, "Economics of Schooling" (n. 1 above).
30. r-1 (last year's cognitive achievement) in equation (1) leads to a more appropriate specification of the "technology."
31. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
32. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
33. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
34. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
35. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
36. See, e.g., B. S. Barnow, C. G. Cain, and A. S. Goldberger, "Issues in the Analysis of Selectivity Bias," Evaluations Studies 5 (1980): 42-59; J. D. Angrist, G. W. Imbens, and D. B. Rubin, "Identification of Causal Effects Using Instrumental Variables," unpublished manuscript; A. S. Goldberger, "Structural Equation Methods in the Social Sciences," Econometrica 40 (1972): 979-1001; D. Rubin, "Assignment to a Treatment Group on the Basis of a Covariate," Journal of Educational Statistics 2 (1977): 1-26; C. F. Manski, "The Selection Problem," in Advances in Econometrics, ed. C. Sims (New York: Cambridge University Press, 1992), pp. 240-68; and J. Heckman and V. J. Hotz, "Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," Journal of the American Statistical Association 84, no. 408 (December 1989): 862-80.
37. Not included in the sample are schools belonging to the Jewish orthodox education system, because many of the variables in the analysis were missing for these schools.
38. The socioeconomic index is a weighted average of variables measuring the standard of living.
39. I also introduced these interactions in the third graders' reading-comprehension regressions and obtained similar results.
40. For example, students from schools in the Arab Christian community have test scores that are higher than the mean of the Jewish students.
41. These predictions should be interpreted with some caution because the standard errors of the predictions increase as we move away from the sample means.