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Constant 1.206 1 .07 As indicated above, the p-value for the coefficient is largely greater than 0.1. This suggests that the number of desired changes in hospitals does not affect the respondent’s intention to migrate. So, even if the respondent suggests many changes to be applied in hospitals, he might not be willing to migrate to another country, the current situation of hospitals does not push medical doctors to migrate. Actually, while filling the questionnaires many medical doctors stated that though the hard circumstances in the Moroccan health sector, they don’t think about migration to another country. 8. Migration conditions disturbing medical doctors and intention to migrate In the previous sections, the study investigated the reasons encouraging medical professionals to migrate. However, one question in the survey asked respondents about the migration conditions that might disturb them or even make them decide to not migrate. The questionnaire records (as shown in figure 11 in the appendix) indicate that the main migration conditions bothering respondents and that might limit respondents’ intention to migrate are equivalence test (56% of respondents), readmission into the host country (44%), partner and child terms (43%), and salaries (17%). It is expected that these factors have a negative effect on respondents’ intention to migrate. So, the higher the number of migration conditions disturbing medical professionals, the lower will be their intention to migrate. In order to test whether these factors are related to respondents’ intention to migrate, a logit regression is performed with the number of conditions mentioned by respondents as an independent variable and intention to migrate as a dependent variable. Results Table II.2.3.7: Logit regression Output (Number of migration conditions disturbing respondents VS Intention to migrate) Regression Output Coefficient df P-Value # of migration conditions disturbing respondents .679 1 0.003 Constant .216 1 .547 ! *%'!
These results suggest that the number of migration conditions disturbing respondents do not negatively affect their intention to migrate, as was expected. So, even if respondents do not agree with a high number of migration conditions, they always have an intention to migrate. This can also explain the fact these medical are still practicing in Morocco though they have intention to migrate. So, if these migration conditions are reduced or cancelled, the number of medical doctors migrating might increase even more. II.2.3.2 Discussion of results As stated earlier, the main objective of this study is to investigate the reasons leading to medical doctors’ migration in Morocco. This is accomplished through a survey of 117 Moroccan medical doctors working in public and private hospitals in different cities (Azrou, Meknes, Rabat, Tiflet, Khemisset, Casablanca and others). First, the paper investigates the potential effect of gender on respondents’ intention to migrate. Previous literature suggests that females have less intention to migrate males do (Piper, 2005). In order to statistically test the gender effect on respondents’ intention to migrate, a chi-square test is performed with intention to migrate (yes or no) and gender as two categorical variables. The results of the analysis reveal that gender has no significant statistical effect on respondents’ intention to migrate. Hence, males and females are alike with regard to intention to migrate and there might be other factors that can affect medical professionals’ intention to migrate. Another factor that might have a strong effect on medical doctors’ intention to migrate is age. Previous studies indicate that young people have generally more intention to migrate for many reasons, including superior well-being and strength, fewer responsibilities, and higher motivation to better jobs even outside home countries (Piper, 2005; Docquier, Bhargava, & Moullan, 2010). In order to test whether age affect medical professionals’ intention to migrate, a logit regression is performed with age as an independent variable and intention to migrate as a dependent variable. The results suggest that age is negatively related to respondents’ intention to migrate. In other words, younger medical doctors have more intention to migrate and work abroad. ! *%(!
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F E M I S E R E S E A R C H P R O G
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What Can Be Learnt from the New Eco
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AMGA: American Medical Group Associ
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USA: United State of America WB: Wo
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medical doctors are then free to en
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elate to quality research and educa
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This may concern also EU countries
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discussed both in theory and practi
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EU are then described and discussed
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specialties. This study shows that
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with this trade. Special arrangemen
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into the developed countries; where
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them as follow: Cross-border delive
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In this regard, the EU is suggestin
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Given the importance of health care
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Serbia. Low wages, poor working con
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• How does tertiary education wit
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Driouchi & Kadiri (2010) are promis
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annual living costs per student. Th
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Lithuania 4.12 4.15 4.01 4.03 3.97
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Egypt 67.57 68.86 70.17 71.52 72.89
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observed externally from developing
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Relative Wages : MIN MENA / By comp
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No future, Heavy workload, to save
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one-year qualification apprenticesh
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Other European Countries Austria 4
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one medical university and studies
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includes a three-year vocational tr
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has 18 medical universities and stu
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général du Gouvernement to gradua
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of Medical Science, Bachelor of Med
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Egypt Iran 29463 31445 32134 25990
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major policies and strategies relat
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The aim of this sub-part is to prov
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• What is the role of mobility of
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Commonwealth of Independent states
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Dodani and LaPorte (2005) suggest t
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In regards to the mobility of Europ
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The general conclusions of these th
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Specific factors Impact of HIV/AIDS
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Portugal X X Romania X X X Russian
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Germany Italy Spain Lithuania Slova
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Italy (2%) and Russia (4) in 2008 (
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theory assumes perfect transferabil
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The data available suggest potentia
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This chapter deals with the migrati
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networks and on the major channels
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assumed here that emigration decisi
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Increases (respectively decreases)
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Figure II.1.2: The shape of H as a
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The optimal emigration rate that ca
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Figure II.1.4: Effects of the Level
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empirical investigation focuses on
Page 107 and 108: Table II.1.3.1: Country annual tren
Page 109 and 110: Table II.1.3.2: Country annual tren
Page 111 and 112: ! ! C/D>)! 01::! 0103! 5881::7! E#%
Page 113 and 114: "#$%&'!()*)+!Eurostat Database Abou
Page 115 and 116: Using these parameter estimates, co
Page 117 and 118: different websites for different co
Page 119 and 120: the theoretical values of the relat
Page 121 and 122: p-value 0.33 0.03 t test 0.99 2.25
Page 123 and 124: The following set of graphs are the
Page 125 and 126: The countries with higher number of
Page 127 and 128: Turkey (m*=0.41, m**=0.77) Yemen (m
Page 129 and 130: periods but should be concerned abo
Page 131 and 132: health report “Comptes Nationaux
Page 133 and 134: In accordance with the health insur
Page 135 and 136: 95 adults >15 years old per 100000
Page 137 and 138: To achieve progress in the health s
Page 139 and 140: The external problems comprise (1)
Page 141 and 142: first four hospital universities ex
Page 143 and 144: monitoring trends and economic fact
Page 145 and 146: Other support staff 6300 2.11 2004
Page 147 and 148: areas, the case of doctors who reti
Page 149 and 150: areas of Morocco. It is computed ye
Page 151 and 152: political instability, economic dep
Page 153 and 154: 1. Gender VS Intention to Migrate A
Page 155 and 156: salaries differs according to the w
Page 157: Results The results are given below
Page 161 and 162: Finally, the questionnaire records
Page 163 and 164: The past decades have witnessed an
Page 165 and 166: changed the notion of space, where
Page 167 and 168: implications on health, Huynen et a
Page 169 and 170: Figure III.1.3: Social stratificati
Page 171 and 172: Lee et al., (2007) primarily focus
Page 173 and 174: However, Collins (203) does recogni
Page 175 and 176: America. In Africa, where there are
Page 177 and 178: physicians from Liberia practice in
Page 179 and 180: Figure III.1.7: Migrant care worker
Page 181 and 182: espectively. An interesting particu
Page 183 and 184: Table III.1.5: Supply of foreign (-
Page 185 and 186: Table III.1.6: Health care wages in
Page 187 and 188: Figure II.1.11: Factors affecting h
Page 189 and 190: Figure III.1.12: Factors contributi
Page 191 and 192: Table III.1.10: International Quali
Page 193 and 194: health as integral to wellbeing thr
Page 195 and 196: III.2.1 Need for A cooperative Fram
Page 197 and 198: graduate spends of certain number o
Page 199 and 200: III.2.2 Migration of Medical Doctor
Page 201 and 202: The convexity condition is simply a
Page 203 and 204: • A payoff vector (ai)i S is said
Page 205 and 206: III.2.2.2 Discussion and Public Pol
Page 207 and 208: Europe. Second, in the North Africa
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In the short run, the country of or
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great incentive for medical student
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system, and therefore to the rest o
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MENA countries could be moving to p
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of their medical school. The other
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Beine, M., Docquier, F. & Rapoport,
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German Medical Association.(2011).
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World Bank Database, 2007. World Ba
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http://gse.buffalo.edu/org/inthighe
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Berland, Y. (2002). Demographie des
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Gericke, C.A. (2006). Finance healt
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Salehi-Isfahani, D., Tunali, I., As
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Beine, M., Docquier, F. & Rapoport,
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Docquier, F., Lohest, O. & Marfouk,
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Labdelaoui, H. (2010). Les dimensio
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Stark, O. (1991), The Migration of
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WHO - World Health Organization (20
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Linacre, S. (2007). “Migration: p
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Challenging Inequities in Health: F
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Mullan, F. (2007). Doctors and Socc
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Vujicic M, Zurn P, Diallo K, Dal Po
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Collins, T. (2003). Globalization,
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Kana, M.A., (2009). From Brain Drai
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Sagoe, K. (2004). Using the Diaspor
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Sub-part II.1: Appendix I Appendice
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means that So if , then: > which is
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A, B,C>0 and , , Then Demo 5: Sign
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t test 3.21788138 1.86856175 3.1713
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Lithuania Years m Relative wage H/H
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Romania Years m Relative wage H/H0
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MENA Countries Risk Neutral Model C
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Tunisia Turkey 1993 0.1781 2.50 1.9
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Syria Tunisia Turkey Yemen Stand.de
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Morocco Syria Tunisia t-stat (theor
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Risk aversion model summary table C
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Table II-2-1.2: Projections of the
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Observations 5 Coefficients Erreur-
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Figure 4: Age distribution within r
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Figure 11: Migration conditions dis
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! "(&!
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! "((!
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! ")+!
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! ")"!
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