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antidepressant use as an indicator of depression is connected with greater uncertainty than applying this method to other medical treatments, because the variation in mental health care treatments is greater. <strong>An</strong>d finally, the founding premise of a positive effect of MTX on employment can be questioned. In chapter 7 a further expansion of the analysis was considered, looking at an approximately continuous variable instead of a binary explanatory variable. The estimation was performed with an unobserved effects Tobit model and resulted in positive marginal effects that were large in magnitude compared to the results from chapter 6. Nonetheless, the effect on the variable of interest in the Tobit model was also insignificant, just like the results from chapter 6. It was stressed that the analysis in chapter 7 only was a preliminary attempt to include a continuous dependent variable and therefore the results from chapter 7 should be interpreted cautious. Taken as a whole, the results of the presented analysis do not point towards antidepressants having an effect on employment as found by Galarraga et al. (2006). However, as mentioned above the empirical problems present in the analysis necessitate further analysis both with respect to the supporting hypothesis and the possible endogeneity of the control variables. One option would be to link the dataset to Landspatientregistret, which is a national register containing information on all the diagnoses established in the Danish hospitals. This would provide data on the degree of depression, but would not be without problems, as people are often diagnosed by their general practitioner without getting in touch with a hospital. In addition, the conducted estimations could be scrutinized further, looking into for example the effect of interaction terms or using dummies for different dosages of antidepressants, in order to capture heterogeneous treatment effects. 69
References Agerbo, E., T. Eriksson, P.B. Mortensen and N. Westergård-Nielsen. 1998. Unemployment and mental disorders – an empirical analysis. Center for Labour Market and Social Research, Aarhus. Agosti, V., J.W. Stewart and F.M. Quitkin.1991. Life satisfaction and psychosocial functioning in chronic depression: effect of acute treatment with antidepressants. Journal of Affective Disorders. 23 (1991): 35-41. <strong>An</strong>dersen, T.M., H. Linderoth, V. Smith og N. Westergård-Nielsen. 2002. Beskrivende dansk økonomi. 1 st version, 1 st edition. HVB-Boghandelen v/ Handelshøjskolen, Århus. <strong>An</strong>derson, K.H. and R.V. Burkhauser. 1985. The Retirement-Health Nexus: A New Measure of an Old Puzzle. The Journal of Human Resources 20 (3): 315-330. Berndt, E., A. Bir, S.H. Busch, R.G. Frank and S.T. Normand. 2002. The medical treatment of depression, 1991-1996: productive inefficiency, expected outcome variations, and price indexes. Journal of Health Economics 21 (2002) 373-396. Cahuc, P. and A. Zylberberg. 2004. Labor Economics. The MIT Press, Cambridge, Massachusetts. Chevalier, A. and L. Feinstein. 2006. Sheepskin or Prozac: The Causal Effect of Education on Mental Health. IZA DP No.2231. Day Poulsen, H., P. Munk-Jørgensen and T.G. Bolwig. 2004. Psykiatri – en grundbog. Kbh.: Munksgaard Danmark. Drugs Information Online, www.drugs.com Duggan, M.G. and W.N. Evans. 2005. Estimating the Impact of Medical Innovation: A Case Study of HIV <strong>An</strong>tiretroviral Treatments. NBER Working Paper Series, WP 11109. Frank, R.G. and T.G. McGuire. 1999. Economics and Mental Health. NBER Working Paper Series, WP 7052. Galarraga, O., D.S. Salkever, J.A. Cook and S.J. Gange. 2006. <strong>An</strong> Instrumental Variable Evaluation of <strong>An</strong>tidepressant Use on Employment among HIV-Infected Women Using Highly-Active <strong>An</strong>tiretroviral Therapy in the United States: 1996-2004. NBER Working Paper Series, WP 12619. Gordis, L. 1979. Conceptual and Methodologic Problems in Measuring Patient Compliance. In Compliance in health care. Ed. R.B. Haynes, D.W. Taylor and D.L. Sackett. The John Hopkins University Press. Baltimore and London. Greener, M.J. and J.F. Guest. 2005. Do <strong>An</strong>tidepressants Reduce the Burden Imposed by Depression on Employers? CNS Drugs 2005; 19 (3): 253-264. Grossman, M. 1972. On the Concept of Health Capital and the Demand for Health. The Journal of Political Economy 80 (2): 223-255. Haan, P. and A. Uhlendorff. 2007. Intertemporal Labor Supply and Involuntary Unemployment. IZA DP No. 2888. Haynes, R.B. 1979.Determinants of Compliance: The Disease and the Mechanisms of Treatment. In Compliance in health care. Ed. R.B. Haynes, D.W. Taylor and D.L. Sackett. The John Hopkins University Press. Baltimore and London. Jehle, G.A. and P.J. Reny. 2001. Advanced microeconomic theory. Boston: Addison-Wesley. Johnston, J. and J. DiNardo. 1997. Econometric Methods. Fourth Edition. McGraw-Hill. Jorm, A.F. 2000. Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychological Medicine 30(2000): 11-22. Killingsworth, Mr. and J.J. Heckman. 1986. Female Labor Supply. In Handbook of Labor Economics, Volume I. Ed. O. Ashenfelter and R. Layard. Amsterdam: North-Holland. Marcotte, D.E., V. Wilcox-Gök, D.P. Redmon. 1999. Prevalence and Patterns of Major Depressive Disorder in the United States Labor Force. The Journal of Mental Health Policy and Economics 2(1999): 123-131. 70
Page 1 and 2:
Estimating the Impact of An
Page 3 and 4:
Abstract This thesis aims at analys
Page 5 and 6:
1 Introduction According to the Wor
Page 7 and 8:
consisting of lack of data on the d
Page 9 and 10:
experience symptoms of depression o
Page 11 and 12:
(SSRI’s), also called the new ant
Page 13 and 14:
heumatologists. But since descripti
Page 15 and 16:
H > 0 or a corner solution, H = 0 .
Page 17 and 18:
employers more reluctant to hire ne
Page 19 and 20:
One of the most cited models when a
Page 21 and 22: One of the factors greatly influenc
Page 23 and 24: Galarraga et al. (2006) have chosen
Page 25 and 26: channel runs through enhanced compl
Page 27 and 28: 3.2 The effect of antidepressants o
Page 29 and 30: of patients receiving appropriate c
Page 31 and 32: Inspired by Galarraga et al. (2006)
Page 33 and 34: are used by other patients groups,
Page 35 and 36: Consequently I am dealing with a se
Page 37 and 38: constructed, and will be explained
Page 39 and 40: As mentioned in chapter 1, one of t
Page 41 and 42: Number of observations 2364 252 211
Page 43 and 44: is perhaps not surprising, since th
Page 45 and 46: Figure 7 The distribution of the us
Page 47 and 48: Figure 9 depicts the defined daily
Page 49 and 50: where φ ( z) is the standard norma
Page 51 and 52: 5.3 The binary response model and p
Page 53 and 54: The log of equation [5.7] gives the
Page 55 and 56: antidepressant use are displayed in
Page 57 and 58: As established in chapter 4, the pa
Page 59 and 60: probit estimation, respectively. Ha
Page 61 and 62: estimation. And ag
Page 63 and 64: As can be seen from table 7 the ext
Page 65 and 66: mtx 0.0002 0.0003 0.0001 0.0002 wag
Page 67 and 68: probit estimation produces more sig
Page 69 and 70: health. As a consequence, further a
Page 71: 8 Conclusion The aim of this thesis
Page 75 and 76: Zimmerman, F. and W. Katon. 2005. S
Page 77 and 78: wage2 Dummy=1 if wage income up to
Page 79 and 80: data medold; set b.lmdb_pct10_2003;
Page 81 and 82: if Last.aar then output; /*output o
Page 83 and 84: KEEP AAR ALDER ANC02 ANC36 ANC79 AN
Page 85 and 86: set b.register; yr=0+aar; DROP aar;
Page 87 and 88: HIGHER='Middle-range and higher edu
Page 89 and 90: dayemp4='Between 8 months and 364 d
Page 91 and 92: data collect; merge test1 (in=a) te
Page 93 and 94: data test1; set b.finaldata1; proc
Page 95 and 96: antidep_lastyr=lag(AD_dummy); if (u
Page 97 and 98: Estimation results Probit yr 2003 -
Page 99 and 100: Probit estimates Number of obs = 58
Page 101 and 102: single | -.3439072 .0893125 -3.85 0
Page 103 and 104: (Assumption: . nested in A) Prob >
Page 105 and 106: . /*with proxy, generalised residua
Page 107 and 108: . . /*Panel probit same as Galarrag
Page 109 and 110: Iteration 7: log pseudolikelihood =
Page 111 and 112: -----------------------------------
Page 113 and 114: . . probit emp antidep mtx wageinc
Page 115 and 116: ho = 0.2 log likelihood = -681.4270
Page 117 and 118: ab79 | -.2830833 .3452789 -0.82 0.4
Page 119 and 120: -----------------------------------
Page 121 and 122: . predict ohat, resid . . probit em
Page 123 and 124:
y99 | -.1676129 .4540083 -0.37 0.71
Page 125 and 126:
ab02*| -.0132912 .01201 -1.11 0.269
Page 127 and 128:
. gen numerator=normdenxb*[ad_dummy
Page 129 and 130:
Iteration 2: log likelihood = -306.
Page 131 and 132:
. . probit emp antidep_last5yrs mtx
Page 133 and 134:
note: 0 failures and 14 successes c
Page 135 and 136:
y = Pr(emp) (predict) = .64904538 -
Page 137 and 138:
Probit yr 2003 - Table 9: . use /ak
Page 139 and 140:
higher | .0160771 .2154333 0.07 0.9
Page 141 and 142:
ieland1*| .2476048 .11071 2.24 0.02
Page 143 and 144:
Random-effects tobit regression Num
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