Vilalta-Bufi 2018b - Revision history

Scipediacontent at 10:52, 11 July 2018

2018-07-11T10:52:23Z

Danielquer: Danielquer moved page Vilalta-Bufi 2018a to Vilalta-Bufi 2018b

2018-05-11T10:57:35Z

Danielquer moved page Vilalta-Bufi 2018a to Vilalta-Bufi 2018b

Scipediacontent at 10:44, 12 April 2018

2018-04-12T10:44:19Z

Scipediacontent at 10:42, 12 April 2018

2018-04-12T10:42:55Z

Scipediacontent at 10:39, 12 April 2018

2018-04-12T10:39:26Z

Scipediacontent at 10:33, 12 April 2018

2018-04-12T10:33:34Z

Scipediacontent at 10:29, 12 April 2018

2018-04-12T10:29:32Z

Scipediacontent at 10:26, 12 April 2018

2018-04-12T10:26:14Z

Montsevilalta at 17:53, 18 January 2018

2018-01-18T17:53:09Z

Montsevilalta at 17:49, 18 January 2018

2018-01-18T17:49:18Z

← Older revision		Revision as of 10:52, 11 July 2018
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	We study whether parental education affects the choice of tertiary education in Spain. We analyze two qualitative characteristics of the university studies: the length of the program and its academic prestige. We identify for which individuals parental background matters the most. For the choice of a long program, parental background changes the most likely outcome for students with low grades in the academic track and those with excellent grades in the vocational track. Regarding the prestige of the program, parental background matters the most for the worse performing boys and the girls with rather good grades in the academic track.		We study whether parental education affects the choice of tertiary education in Spain. We analyze two qualitative characteristics of the university studies: the length of the program and its academic prestige. We identify for which individuals parental background matters the most. For the choice of a long program, parental background changes the most likely outcome for students with low grades in the academic track and those with excellent grades in the vocational track. Regarding the prestige of the program, parental background matters the most for the worse performing boys and the girls with rather good grades in the academic track.
−
−	~~Keywords: tertiary education, intergenerational mobility, academic prestige, Spain, university program.~~
−
−	~~JEL codes: I24, I23.~~

	<br/>		<br/>

@@ Line 732: / Line 732: @@
 {| style="align: center; width: 100%;"
 |-
-| [[Image:Vilalta-Bufi_2018a_9087_figure3_1.png|center|295px]]
+| [[Image:Vilalta-Bufi_2018a_9087_figure3_1.png|center|300px]]
-| [[Image:Vilalta-Bufi_2018a_1704_figure3_2.png|center|289px]]
+| [[Image:Vilalta-Bufi_2018a_1704_figure3_2.png|center|300px]]
 |-
-| colspan="2" | [[Image:Vilalta-Bufi_2018a_3285_figure3_3.png|center|289px]]
+| colspan="2" | [[Image:Vilalta-Bufi_2018a_3285_figure3_3.png|center|300px]]
 |}

@@ Line 726: / Line 726: @@
 Figure 3 displays the predicted probabilities for those cases from the vocational track where EMI is satisfied. In contrast to the previous results, parental background changes the most likely outcome for those individuals with rather high average grade in secondary education when they studied vocational track. We observe that, in general, those males with ‘Very good’ average grade get to prestigious programs unless their father has no studies, in which case they get to low prestigious studies. For those males who obtained a ‘Good’ average grade in secondary education, only those with highly educated fathers will be slightly more likely to graduate from highly prestigious programs. In the case of females results show that those with ‘Excellent’ grade whose father has at most primary education will most likely study in a low prestige program, while those whose father has secondary or tertiary education will be more likely to study in a highly prestigious program.
 '''Figure 3.''' Plots of predicted probabilities for those from vocational track where EMI is satisfied.
-{|
+{| style="align: center; width: 100%;"
 |-
-| [[Image:Vilalta-Bufi_2018a-picture-Canvas 335.svg|center|295px]]
+| [[Image:Vilalta-Bufi_2018a_9087_figure3_1.png|center|295px]]
-| [[Image:Vilalta-Bufi_2018a-picture-Canvas 394.svg|center|289px]]
+| [[Image:Vilalta-Bufi_2018a_1704_figure3_2.png|center|289px]]
 |}
 <div class="center" style="width: auto; margin-left: auto; margin-right: auto;">

@@ Line 305: / Line 305: @@
 |}
 ''t'' statistics in parentheses <sup>*</sup> ''p'' < 0.1, <sup>**</sup> ''p'' < 0.05, <sup>***</sup> ''p'' < 0.01, McKelvey & Zavoina’s R<sup>2</sup> reported, cutoff points tested for not overlapping.
 '''Table 4.''' Predicted probabilities of attending an academically prestigious program (Academic track, ‘Licenciados’ sample).
@@ Line 515: / Line 513: @@
 '''Figure 2.''' Plots of predicted probabilities for those from academic track where EMI is satisfied.
+{| style="width: 100%;align: center;"
 {|
 |-
-| [[Image:Vilalta-Bufi_2018a-picture-Canvas 221.svg|center|274px]]
+| [[Image:Vilalta-Bufi_2018a_6593_figure2_1.png|center|274px]]
-| [[Image:Vilalta-Bufi_2018a-picture-Canvas 279.svg|center|285px]]
+| [[Image:Vilalta-Bufi_2018a_8292_figure2_2.png|center|285px]]
 |}
 Father’s education: 1-without studies, 2-primary education, 3-secondary education and 4-tertiary education.
@@ Line 527: / Line 523: @@
 Table 5 reports the predicted probabilities to study a prestigious program for those individuals who followed a vocational track. We observe that parental background changes the most likely outcome for males with average grades ‘Good’ and ‘Very good’ in the secondary education. In the case of females, the same happens when they have ‘Excellent’ grade in secondary education. Note, however, that females with lower grades who followed a secondary vocational education are not affected by father’s education in their chances for academically prestigious program. This can be an artifact of gender socialization roles apparently still existent in Spain.
 '''Table 5.''' Predicted probabilities of attending an academically prestigious program (vocational track, ‘Licenciados’ sample)

@@ Line 222: / Line 222: @@
 Results in Table 2 reveal that parental background influences the probability of studying a long program. However, we need to resort to predicted probabilities to confirm that this effect is strong enough to change the most likely outcome for particular individuals.
 '''Figure 1.''' Plot of predicted probabilities of studying a long program by parental background. Cases where EMI is satisfied.
+[[Image:Vilalta-Bufi_2018a_9914_figure1.png|center|286px]]
-[[Image:Vilalta-Bufi_2018a-picture-Canvas 62.svg|center|286px]]
-−
 a. Academic track in secondary education and average grade ''‘pass’''.
+[[Image:Vilalta-Bufi_2018a_9514_figure2.png|center|292px]]
-[[Image:Vilalta-Bufi_2018a-picture-Canvas 115.svg|center|292px]]
 b. Academic track in secondary education and average grade ‘''good''’.
+[[Image:Vilalta-Bufi_2018a_1504_figure3.png|center|294px]]
-[[Image:Vilalta-Bufi_2018a-picture-Canvas 168.svg|center|294px]]
-−
 c. Vocational track in secondary education and average grade ‘''excellent with honors''’.

← Older revision	Revision as of 10:57, 11 May 2018
(No difference)

← Older revision		Revision as of 10:29, 12 April 2018
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	We first study whether parental background influences the choice between long and short university program. Table 2 reports the logistic estimation coefficients of the probability of studying a long program. In model 1, we include father’s education level. Model 2 includes instead the highest level of education of the parents, while model 3 includes both the education level of father and mother. Apart from parental education, we control for gender, track of secondary education (vocational vs. academic) and ability (average grade in secondary education). All these variables have a significant effect on the choice of study program. Results are as expected. Females and students that followed the vocational track in secondary education are less likely to graduate from a long program, while higher ability and parental education increase chances of studying a long program.		We first study whether parental background influences the choice between long and short university program. Table 2 reports the logistic estimation coefficients of the probability of studying a long program. In model 1, we include father’s education level. Model 2 includes instead the highest level of education of the parents, while model 3 includes both the education level of father and mother. Apart from parental education, we control for gender, track of secondary education (vocational vs. academic) and ability (average grade in secondary education). All these variables have a significant effect on the choice of study program. Results are as expected. Females and students that followed the vocational track in secondary education are less likely to graduate from a long program, while higher ability and parental education increase chances of studying a long program.

−	~~==<br/>==~~

	'''Table 2.''' Table of coefficients for a logistic estimation. Dependent variable: Long program (1=long, 0=short).		'''Table 2.''' Table of coefficients for a logistic estimation. Dependent variable: Long program (1=long, 0=short).

@@ Line 88: / Line 88: @@
 |  colspan='2'  style="border-left: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|'Licenciatura' sample
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Variable
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Variable
 |  style="text-align: center;vertical-align: bottom;"|Mean
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Std. Dev.
@@ Line 96: / Line 96: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Std. Dev.
 |-
-|  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Long program
+|  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Long program
 |  style="border-top: 1pt solid black;text-align: center;vertical-align: bottom;"|0.601
 |  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.490
@@ Line 104: / Line 104: @@
 |  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.000
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Prestigious program
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Prestigious program
 |  style="text-align: center;vertical-align: bottom;"|2.014
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.828
@@ Line 112: / Line 112: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.825
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Father’s education level
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Father’s education level
 |  style="text-align: center;vertical-align: bottom;"|2.646
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.966
@@ Line 120: / Line 120: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.984
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Mother’s education level
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Mother’s education level
 |  style="text-align: center;vertical-align: bottom;"|2.444
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.885
@@ Line 128: / Line 128: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.905
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Highest parental education level
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Highest parental education level
 |  style="text-align: center;vertical-align: bottom;"|2.792
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.945
@@ Line 136: / Line 136: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.944
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Female
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Female
 |  style="text-align: center;vertical-align: bottom;"|0.645
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.479
@@ Line 144: / Line 144: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.480
 |-
-|  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Vocational track
+|  style="border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Vocational track
 |  style="text-align: center;vertical-align: bottom;"|0.086
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.280
@@ Line 152: / Line 152: @@
 |  style="border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.174
 |-
-|  style="border-bottom: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Grade in secondary education
+|  style="border-bottom: 1pt solid black;border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Grade in secondary education
 |  style="border-bottom: 1pt solid black;text-align: center;vertical-align: bottom;"|2.861
 |  style="border-bottom: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.926
@@ Line 160: / Line 160: @@
 |  style="border-bottom: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|0.963
 |-
-|  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|Number of observations
+|  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: left;vertical-align: bottom;"|Number of observations
 |  colspan='2'  style="border-top: 1pt solid black;border-right: 1pt solid black;text-align: center;vertical-align: bottom;"|3522
 |  colspan='2'  style="border-top: 1pt solid black;text-align: center;vertical-align: bottom;"|1406

@@ Line 261: / Line 261: @@
 '''Table 3.''' Table of coefficients for an ordered logistic estimation. Dependent variable: Academically prestigious program (three levels: low, medium, high prestige).
-{|
+{|class="wikitable"
 |-
 !        !! Short Prog !! Short Prog !! Short Prog !! Long Pr !! Long Pr !!Long Pr

@@ Line 261: / Line 261: @@
 '''Table 3.''' Table of coefficients for an ordered logistic estimation. Dependent variable: Academically prestigious program (three levels: low, medium, high prestige).
+{|
-	Short-program (diplomatura)	Long-program (licenciatura)
+|-
-	(1)	(2)	(3)	(1)	(2)	(3)
+!        !! Short Prog !! Short Prog !! Short Prog !! Long Pr !! Long Pr !!Long Pr
-Female	-0.89***	-0.89***	-0.897***	-0.472***	-0.48***	-0.47***
+|-
-	(-8.36)	(-8.37)	(-8.40)	(-5.52)	(-5.57)	(-5.52)
+|	||(1)||	(2)||	(3)||	(1)	||(2)||	(3)
-Vocational track	-0.200	-0.182	-0.183	-0.436*	-0.456**	-0.436*
+|-
-	(-1.45)	(-1.32)	(-1.32)	(-1.89)	(-1.98)	(-1.89)
+| Female	||-0.89***||	-0.89***||	-0.897***||	-0.472***||	-0.48***||	-0.47***
-Grade in secondary educ.	0.374***	0.372***	0.368***	0.340***	0.341***	0.340***
+|-
-	(5.94)	(5.90)	(5.83)	(7.69)	(7.70)	(7.67)
+| ||  	(-8.36)||	(-8.37)||	(-8.40)||	(-5.52)	||(-5.57)||	(-5.52)
-Father’s education	0.0434		-0.0150	0.142***		0.148***
+|-
-	(0.77)		(-0.21)	(3.41)		(2.79)
+|Vocational track	||-0.200	||-0.182	||-0.183	||-0.436*	||-0.456**||	-0.436*
-Highest parental education		0.0863			0.103**
+|-
-		(1.55)			(2.39)
+|	||(-1.45)	||(-1.32)||	(-1.32)	||(-1.89)	||(-1.98)	||(-1.89)
-Mother’s education			0.107			-0.0111
+|-
-			(1.39)			(-0.19)
+|Grade in secondary educ.	||0.374***	||0.372***	||0.368***||	0.340***||	0.341***||	0.340***
-Constant cut1	0.0905	0.204	0.172	0.136	0.0480	0.128
+|-
-	(0.39)	(0.88)	(0.72)	(0.76)	(0.26)	(0.69)
+| ||	(5.94)||	(5.90)	||(5.83)	||(7.69)	||(7.70)	||(7.67)
-Constant cut2	1.601***	1.716***	1.684***	1.468***	1.377***	1.460***
+|-
-	(6.84)	(7.24)	(6.96)	(8.01)	(7.34)	(7.75)
+|Father’s education	||0.0434||	||	-0.0150||	0.142***||	||	0.148***
-N	1406	1406	1406	2116	2116	2116
+|-
-AIC	2947.2	2945.4	2947.3	4496.6	4502.5	4498.5
+| ||	(0.77)||	||	(-0.21)	||(3.41)||	||	(2.79)
-BIC	2978.7	2976.9	2984.0	4530.5	4536.4	4538.1
+|-
-MZ R2	0.0758	0.0772	0.0773	0.0541	0.0513	0.0541
+|Highest parental education|| ||	0.0863||  ||  ||	0.103**||
-Brant χ2	1.812	1.613	2.110	5.840	6.427	6.593
+|-
-Brant p-val.	0.770	0.806	0.834	0.211	0.169	0.253
+|	||	||(1.55)||  ||	||	(2.39)	||
+|-
 ''t'' statistics in parentheses <sup>*</sup> ''p'' < 0.1, <sup>**</sup> ''p'' < 0.05, <sup>***</sup> ''p'' < 0.01, McKelvey & Zavoina’s R<sup>2</sup> reported, cutoff points tested for not overlapping.