The Effect of Mental Distress on Income: Results from a Community Survey / Richard G. Frank, Paul J. Gertler.

By:

Frank, Richard G

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w2433.Publication details: Cambridge, Mass. National Bureau of Economic Research 1987.Description: 1 online resource: illustrations (black and white)Subject(s):

H - Public Economics

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Abstract: We employ a unique data set from a community based survey to assess the effect of mental distress on earnings. The main advantage of the data is that detailed measurements of mental health status were made on all subjects in the study. This means that our population-based measure of mental distress does not rely on a patient having had contact with the health care system and obtaining a diagnosis from a provider. The use of diagnosis-based measures may introduce measurement-error bias into the estimates. Our results show that the presence of mental distress reduces earnings by approximately 21% to 33%. To assess the magnitude of any measurement-error bias we present a estimates of models using measures of mental health both on a population-wide basis and on a diagnosis basis. The estimated impact of mental illness on earning is only 9% lower using the using the diagnosis-based measure. The conclusion drawn from this is that little bias is introduced by using the diagnosis-based measure.

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Working Paper	Biblioteca Digital	Colección NBER	nber w2433 (Browse shelf(Opens below))	Not For Loan

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November 1987.

We employ a unique data set from a community based survey to assess the effect of mental distress on earnings. The main advantage of the data is that detailed measurements of mental health status were made on all subjects in the study. This means that our population-based measure of mental distress does not rely on a patient having had contact with the health care system and obtaining a diagnosis from a provider. The use of diagnosis-based measures may introduce measurement-error bias into the estimates. Our results show that the presence of mental distress reduces earnings by approximately 21% to 33%. To assess the magnitude of any measurement-error bias we present a estimates of models using measures of mental health both on a population-wide basis and on a diagnosis basis. The estimated impact of mental illness on earning is only 9% lower using the using the diagnosis-based measure. The conclusion drawn from this is that little bias is introduced by using the diagnosis-based measure.