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! B.3. Risk aversion coefficients Estimates of the constant relative risk aversion (CRRA) coefficient appear to be varying throughout the economic literature but all estimations tend to be around 1. Chetty (2003) found that positive uncompensated wage elasticity can result in a CRRA coefficient below 1.25, while the labor supply literature indicates that CRRA coefficient is close to 1. Szpiro (1986) found that the degree of relative risk aversion (the inverse of the CRRA coefficient) is approximately 2 (meaning a CRRA of 0.5). Cicchetti and Dublin (1994) estimated the degree of relative risk aversion to be of 0.6 (equivalent to a CRRA of 1.66). Fullenkamp et al (2003) considered that significant variations exist in the degree of relative risk aversion (between 0.64 and 1.76) meaning a CRRA of 0.83. Hartley, Lanot and Walker (2005) tried to estimate the degree of risk aversion and the way it varies across individuals using data from a popular TV game-show. The major result of this analysis is that the constant relative risk aversion coefficient is 1. Halek and Eisenhower (2001) address the issue distinguishing between pure and speculative risks in order to understand risk aversion. Among their findings, they established that under both pure and speculative risks, individuals who already proved to be risk-takers by migrating across national borders are less risk averse compared with the native population. Also, unemployed people are more disposed to risk their current income for the possibility to double it (Haled and Eisenhower, 2001). Harrison, Lau and Rutström (2005) found that the Danish population exhibited constant risk aversion attitudes with coefficients around 0.45, 0.68 and 0.97. These attitudes are found to vary that with different socio-economic and demographic factors. ! B.4. Testing for the validity of the model As assumed above, medical doctors study medicine in their countries of origin but have to make decisions to emigrate by the end of their studies or later. The theoretical aggregate level of human capital that stays in the country is derived from the model with the introduction of the values of the parameter related to education and the values of and with the observed “m” for each country. These parameters have been discussed in the previous two sections. Different values of the relative risk aversion coefficient are used including the one related to risk neutrality. The calculations provide ! **'!
the theoretical values of the relative net human capital that are given by the theoretical model (the theoretical H/H0). The observed relative human capital is obtained from the database considering the lowest value of m as corresponding to H0 with H as related to the other values of the emigration rates (human capital is considered to be the variable Total number of physicians). This allows for the computation of the observed H/H0. Then we have performed of a t-test to compare the means of the theoretical and observed relative human capital in each country. If there is no evidence for rejecting the hypothesis of equality of means for theoretical and observed values then the model can be validated. B.4.a. ECE Countries The following tables introduce the results of comparisons between observed and theoretical relative human capital for each ECE country with available data. Firstly, we have computed the theoretical relative human capital under risk neutrality and by using the gamma estimated in previous tables for each country and a gamma equal with 0.25, a fixed value of productivity of education. These values are compared with the relative human capital observed. The detailed results could be found in Appendix 2. In Slovakia we have obtained that there is no evidence for rejecting the null hypothesis with a significance level of 0.05. Therefore the model could be validated under risk neutrality. For all other countries, the null hypothesis is rejected with the level of significance of 0.05. This means that the observed and the theoretical means are proved to be different. Therefore, the models cannot be validated under risk neutrality for Bulgaria, Czech Republic, Lithuania, Hungary, Poland and Romania (Table II.1.3.10). Afterward we have computed the theoretical relative human capital under three risk aversion hypotheses, with alpha 0.33, 0.5 and 0.75 and by using the gamma estimated before for each country. These values are compared with the relative human capital observed. The detailed results could be found in Appendix 2. In Bulgaria, Hungary, Poland, Romania and Slovakia there is no evidence for rejecting the null hypothesis with a significance level of 0.01 under risk aversion with alpha equal to 0.5. Therefore in Bulgaria, Hungary, Poland, Romania and Slovakia, the model could be validated under risk aversion with alpha equal with 0.5. In Czech Republic, Lithuania and Slovakia there is no evidence for rejecting the null hypothesis with a significance ! **(!
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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
Page 67 and 68: The aim of this sub-part is to prov
Page 69 and 70: • What is the role of mobility of
Page 71 and 72: Commonwealth of Independent states
Page 73 and 74: Dodani and LaPorte (2005) suggest t
Page 75 and 76: In regards to the mobility of Europ
Page 77 and 78: The general conclusions of these th
Page 79 and 80: Specific factors Impact of HIV/AIDS
Page 81 and 82: Portugal X X Romania X X X Russian
Page 83 and 84: Germany Italy Spain Lithuania Slova
Page 85 and 86: Italy (2%) and Russia (4) in 2008 (
Page 87 and 88: theory assumes perfect transferabil
Page 89 and 90: The data available suggest potentia
Page 91 and 92: This chapter deals with the migrati
Page 93 and 94: networks and on the major channels
Page 95 and 96: assumed here that emigration decisi
Page 97 and 98: Increases (respectively decreases)
Page 99 and 100: Figure II.1.2: The shape of H as a
Page 101 and 102: The optimal emigration rate that ca
Page 103 and 104: Figure II.1.4: Effects of the Level
Page 105 and 106: 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: different websites for different co
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 and 158: Results The results are given below
Page 159 and 160: These results suggest that the numb
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
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Figure III.1.3: Social stratificati
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Lee et al., (2007) primarily focus
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However, Collins (203) does recogni
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America. In Africa, where there are
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physicians from Liberia practice in
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Figure III.1.7: Migrant care worker
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espectively. An interesting particu
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Table III.1.5: Supply of foreign (-
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Table III.1.6: Health care wages in
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Figure II.1.11: Factors affecting h
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Figure III.1.12: Factors contributi
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Table III.1.10: International Quali
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health as integral to wellbeing thr
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III.2.1 Need for A cooperative Fram
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graduate spends of certain number o
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III.2.2 Migration of Medical Doctor
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The convexity condition is simply a
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• A payoff vector (ai)i S is said
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III.2.2.2 Discussion and Public Pol
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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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