Depression Economics and Alcohol Consumption

Transcription

1 Depression Economics and Alcohol Consumption Barry Anderson 1 & Mirko Moro 2 University College Dublin Dublin, Ireland May 2008 Draft - comments appreciated PLEASE DO NOT QUOTE OR CITE WITHOUT PERMISSION Abstract Anecdotal evidence filtering through the mainstream media since the start of the current economic downturn has indicated that certain behaviours associated with alcohol consumption are changing such as home drinking versus visiting a cocktail bar which may lead to increased alcohol consumption. However, previous studies have found alcohol consumption rising with income, indicating that alcohol is a normal good. This contradiction provides the research question of whether alcohol is an inferior good or a normal good, or whether the consumption of different types of alcohol (i.e., beer, wine and spirits) rises or falls according to economic conditions. We use historic U.S. state level data on alcohol consumption for beer, wine and spirits, along with relevant macro data from the NBER to perform a panel data analysis. The results from this macro analysis are then compared to those from a micro study using happiness data obtained from the Urban Institute Ireland National Survey on Quality of Life. We find that there is a correlation between both economic and psychological depression and drinking behaviour. 1 Barry Anderson, School of Geography, Planning and Environmental Policy, University College Dublin, Urban Institute Ireland, UCD Richview, Clonskeagh Drive, Dublin 14, Ireland. Tel: +353 (0) , barry.anderson@ucd.ie. 2 Mirko Moro, School of Geography, Planning and Environmental Policy, University College Dublin, Planning Building, UCD Richview, Clonkseagh Drive, Dublin 14, Ireland. mirko.moro@ucd.ie. Tel: +353 (0) , 1

2 1. Introduction As the current economic recession continues and personal disposable income continues to fall, consumers are forced to make the most of their current situation. The Mature Enjoyment of Alcohol Society (MEAS) recently reported in the Irish Times 3 that a survey of year olds found young people anticipated spending less on alcohol in recession. According to MEAS this means increased home drinking, where the lack of regulation in terms of closing times and moderation in strength of drinks, services usually offered by bartenders, is a recipe for increased alcohol consumption. However, previous studies have found alcohol consumption rising with income, indicating that alcohol is a normal good. This contradiction provides the research question of whether alcohol is an inferior good or a normal good, or whether the consumption of different types of alcohol (i.e., beer, wine and spirits) rises or falls according to economic conditions. The National Bureau of Economic Research (NBER) characterizes recessions as a decline in economic activity spread across the whole economy lasting more than few months, normally identified by decline in real Gross Domestic Product, industrial production and wholesale-retail sales. During economic downturns a portion of the population experiences job losses and a deterioration of their disposable income, which translates into changes in the amount and mix of commodities consumed, among other things. The demand of normal goods will decrease, while the demand of inferior good will increase. Anecdotal evidence would suggest that when living conditions become harsh, some people may turn to alcohol to find some relief from worsening conditions. In economic terms, this implies alcohol is an inferior good. Some alcoholic beverages might be more suitable than others for different occasions such as relaxation, celebration or consolation; therefore we focus our analysis on the effects of economic recession on the consumption of different types of drinks, namely, spirits, wine and beer. The separate analysis of alcoholic beverages is helpful to analyse more deeply the characteristics of alcohol as an economic good. In fact, alcohol as a composite good may be simultaneously an inferior good and a normal good. As already stated, during economic 3 2

3 downturns people may demand more alcohol but this may be happening during prosperous economic times as well, i.e., when income rises people might enjoy more drinks. This asymmetry may be solved by analysing classes of beverages separately to verify which types of alcoholic drinks are inferior or normal. The macro analysis on the relationship of alcohol consumption and economic recessions will be followed by a microeconomic analysis as a sort of robustness check. The micro-founded psychological motives behind drinking in harsh times can be picked up by a regression of happiness (or unhappiness) and drinking behaviour. Since economic depression affects psychological depression, the hypothesis is that unhappy people may drink more, ceteris paribus. This is supported by recent data from Gallup-Healthways daily polls in US. Every day, one thousand people in the United States are asked a variety of questions related with their mood, happiness and mental stress that yields a Wellbeing Index that is declining sharply since January 2008 (Gallup-Healthways, 2009). However, data useful to study happiness and drinking behaviour in a more systematic way will be derived from self-reported happiness data of Irish people. The use of this type of data has been growing exponentially within economics in order to analyse the determinants of life satisfaction through asking respondents to answer questions concerning their subjective well being. The reminder of the paper is structured as follows. The next section explores the literature on economic conditions and drinking behaviour and elucidates the motivation behind the research questions and the contribution of this paper to the current literature. Section 3 gives details the on both the empirical strategy adopted and the data used in the paper. The micro and macro econometric analyses are more formally described in Section 4 together with the results. Section 5 concludes by summarising the main results, identifying the major limitations and depicting future research. 2. Background The direct investigation of the relationship among economic conditions, and recessions in particular, and alcohol consumption has not received considerable attention in the economic and social literature so far. In general economic and social research has been focussed on identifying the effect of prices and taxes on alcohol sales and in estimating income elasticities. Blake and 3

4 Nield (1997) and Nelson (1997) found that beer consumption is income inelastic in the long run in UK and USA, but with values very close to 1 (0.8 and 0.7 in UK and USA, respectively). The literature that attempts to analyse how macroeconomic conditions affect alcohol consumption concludes that alcohol is a procyclical good. During bad economic times the consumption tends to decrease, while during good economic times, alcohol consumption tends to increase. Ruhm (1995) was the first to investigate how economic conditions are related to alcohol consumption and highway vehicle fatalities using US aggregate macroeconomic data for 48 states over the period. Both drinking and vehicle mortality have been found to vary procyclically. Freeman (1999) using a different econometric model confirmed these findings. A parallel literature using microeconomic data usually corroborate the general finding that alcohol is indeed a normal good, although in few cases the claim is not as conclusive as when using macro data. Ettner (1997) analysed cross-sectional data and concluded that alcohol consumption and dependence are procyclical. Being unemployed (including not participating in the labor force) reduces both alcohol consumption and dependence symptoms. However, involuntary unemployment during bad economic times is associated with more drinking but less alcohol dependence. Dee (2001) uses repeated cross-sections from a US survey embracing the period from 1984 to 1995 concluding that while average drinking is indeed procyclical, bingedrinking is countercyclical: for example, an increase of 5 percentage points in the unemployment rate induces an 8% increase in the probability of binge drinking. However, Ruhm and Black (2002) using more waves of the same survey as Dee (2001), confirmed that alcohol consumption is a normal good and that this is true also for heavy drinkers, after weighing to account for differences in sampling probabilities and by controlling for more covariates. It therefore seems that the literature agree on the point that bad economic times should be associated with a decrease in alcohol consumption. These findings contrast with anecdotal evidence and with the psychological and sociological literature that predicts that during economic downturns alcohol consumption may rise to cope with stress (Brenner and Mooney, 1983; Winton et al., 1986; Pierce et al., 1994). If employment fulfils several complex psychological needs (e.g., helping defining goals and purposes, a defined time structure, contacts with other experiences), as suggested for example by Jahoda (1979), the stress related with using a job may lead to alcohol use as a sort of self medication. Evidence of this can be found in selfreported data where individuals report that alcohol is a way of dealing with problems related 4

5 with one s own job and/or personal financial issues (Kruger and Svensson, 2008). Several studies also revealed that in experimental settings stress may induce alcohol consumption in animals (Poherecky, 1991; NIAAA, 1996; Dee, 2001). More recently, economists have been looking at direct measurement of psychological well-being by using self-reported measures of mental health and well-being, such as self assessed health and happiness or life satisfaction data. For example, Poikolainen et al. (1996) found that compared with abstainers, moderate drinkers were, on average, more often in good health, and heavy drinkers were more often in poor or average health. Poikolainen and Vartiainen (1999) found similar results in the case of wine drinkers: compared with subjects who drank no wine, average or poor health was less frequent among both men and women who imbibed 1 4 drinks of wine, and more common among men who consumed 10 drinks of wine or liquor. Moderate wine drinking seems to be related to good self-rated health. In general, most studies show a J-shaped curve with positive self-reports of subjective mental health associated with moderate drinking but not heavier drinking (El- Guebaly, 2007). General life satisfaction questions have not been used extensively to investigate the problem so far. For example, Graham et al. (2004) found that drinking is positively correlated with happiness, but excessive drinking does not seem to be good for well-being. Using a survey conducted on college students, Murphy et al. (2005) found that the results differ among male and female, with alcohol use associated with lower general satisfaction and anticipated future satisfaction among women, while drinking among men showed a positive, curvilinear relation to social satisfaction. In the literature studying different aspects of the demand for alcohol, it is common to include indicators accounting for the macro-economic environment in some way. The most common control variable used to account for macro-economic conditions are unemployment rates. While there is no doubting the correlation between business cycles and unemployment rates in the long term, there are also demerits to using the employment rate when trying to understand the interaction between the business cycle and alcohol consumption. One is the obvious fact that in an economic downturn, people do not necessarily need lose their jobs in order to feel stress and diminished levels of happiness that could lead to increased levels of alcohol consumption, or a change in the type of alcohol consumed. Losses in savings from stock market declines or falls in perceived wealth due to declining house prices could also lead fully employed people to alter their alcohol consumption behavior. As such, we diverge for previous studies in our choice of 5

6 variables used to understand the effects of the macro-economic environment on various aspects of alcohol consumption. In our study we will use a different approach to analyse specifically the effect of recessions (and depression) on the aggregate consumption of alcohol and on specific alcoholic beverages, by distinguishing among beer, wine and spirits. Paul Krugman has positioned himself as the modern sage of depression economics with the release of his latest book, The Return of Depression Economics and the Crisis of While the debate around depression economics and their application to the current economic debacle goes back and forth arguing the virtues of different market interventions, Krugman s common response to conventional macro wisdom and its current usefulness is, When you're in a situation like this, is realizing that normal rules don't apply 4. Might it also be the case for the usefulness of certain aspects of established microeconomic theory in times of recession or depression? Conventional wisdom holds that in aggregate terms, alcohol in a normal economic good with positive price elasticity. However, when consumers are forced to maximize their utility under abnormal budget constraints, alcohol may serve as a rather cheap substitute for other forms entertainment of leisure spending while serving double duty as self medication. Is it possible that as personal budgets shrink and less money is spent on leisure, an increasing portion of one s personal budget will be spent on various forms of alcohol? Under economic conditions of prosperity and expansion, it is likely to assume not. But Krugman s various arguments for the inadequacy of conventional macroeconomic policy fixes to the current situation force us to also ask whether the normal rules for alcohol consumption hold true in time of economic distress. Our method and empirical strategy is delineated in the following sections. 3. Method and Data The commonly accepted definition of recession is two consecutive quarters of non-positive real economic growth. Alternatively, the National Bureau of Economic Research (NBER) does not define a recession in terms of two consecutive quarters of decline in real GDP. Rather, a recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial 4 6

7 production, and wholesale-retail sales. According to these criteria, the NBER has identified reference dates for the peaks and troughs in the business cycle and using these dates we construct a dummy variable which takes a value of 1 during periods of economic contraction (times from peak to trough) and value of 0 during periods of economic expansion (trough to peak). As our alcohol data is aggregated to annual measures, and the business cycle dates are indicated by the month, we are forced to make a qualitative decision where our recession dummy variable takes a value of 1 if more than half of the year falls under a period of economic contraction. Ideally, monthly alcohol data instead of annual would negate the requirement for this assumption, but we do not have that luxury. The relationship between alcohol consumption and economic recessions is analysed by using panel data analysis on how alcohol consumption has been affected during six recent economic downturns controlling for several other factors at state and national level. The macro analysis will be followed by a micro-econometric happiness function in which self-reported happiness is regressed on several individual characteristics and on their drinking behaviour using ordered response model. Drinking may increase or decrease in response to economic-related stress. With this in mind we analyse the relationship between individual mental stress (measured using subjective wellbeing) and drinking behaviour as self-reported by a representative sample of Irish adults (UII, 2001). A rapidly growing literature in economics is now using happiness surveys, where respondents are asked, inter alia, to evaluate their subjective well-being (SWB), to study the relationship and the determinants of quality of life. 5 The relationship in interesting in its own right as it investigates directly the correlation between a measure of mental stress (i.e., psychological depression) and drinking behaviour. However, in this case it will help in understanding the psychological underpinnings behind economic conditions and alcohol consumption and also to shed a light to the causal link between mental and macro economic depressions and drinking consumption. If for example our micro econometric analysis finds that SWB and drinking behaviour are negatively correlated and our macro econometric analysis finds that alcohol consumption increases during economic depressions, a possible conclusion might be that happiness or mood affects drinking behaviour and not the opposite. 5 For recent and comprehensive reviews of the happiness economics literature see Clark et al. (2008), Di Tella and MacCulloch (2006), Frey and Stutzer (2002). 7

8 2.1 Macroeconomic data Periods of economic recession U.S. have been defined using the NBER Business Cycle Expansions and Contractions database, while time series on alcohol consumption by states are from the US National Institute on Alcohol Abuse and Alcoholism (NIAAA) of the National Institutes of Health. The other macroeconomic data used as control variables are obtained mainly from the US Bureau of Economic Analysis. As can be seen in Table 1 below, there are 6 periods of economic contraction where we expect behaviours around alcohol consumption to diverge from periods of economic expansion. Table 1 about here The period of analysis for this study is dictated by the data on consumption of beer, wine and spirits by U.S state is available from Table 2 contains descriptive statistics for alcohol consumption by type disaggregated to the state level while Figure 1 displays the dynamics of per capita consumption over time for the United States. There are no surprises in the least (Utah) and most (Nevada) heavily consuming states given the socio-demographic, cultural and business profiles of those states. The District of Columbia has the highest levels of consumption for both wine and spirits but lags behind Nevada in total due to the magnitude of Nevada beer consumption. Table 2 about here While the volume of beer consumption is expectedly magnitudes larger than both wine and spirits, Figure 1 shows how the growth in beer consumption has been steady and increasing, This graph falls in line with the conventional wisdom that the beer industry is recession proof and also the empirical finding of Freeman (2001) that beer is mostly immune to economic cycles. Beer follows a different growth pattern than that of wine and also spirits where there have been both increases and decreases in levels of consumption in the last 35 years. while the business cycle and beer has been explored we feel it is important to also understand the relationship between the 8

9 macroeconomic environment and wine and spirits consumption since both are of higher alcohol content and may be used as a form of self medication in times of distress. Figure 1 about here We do not include alcohol price or tax variables as controls in the current analysis as Freeman (2000) finds that past increases in state excise taxes, controlling for income, have had very little permanent effect on alcohol consumption. We control for both the macro income of the state by creating real GDP per capita using nominal state GDP data and the national deflators to convert the nominal figures into 2000 US dollars. We also include the state average for personal income which also may be considered as a proxy for educational attainment -a common explanatory variable in alcohol demand studies- and also state population density which is associate with higher crime rates and potentially higher levels of anxiety for citizens of a state. 2.2 Microeconomic data Micro data on happiness and drinking behaviour are from the Urban Institute Ireland National Survey on Quality of Life conducted in 2001 where a representative sample of 1,500 men and women, aged 18 and over and living in Ireland were interviewed (see Appendix A for further information on the survey). The survey included a self-reported well-being indicator and several questions on alcohol consumption by each individual, along with other questions that allow us to control for expected important socio-demographic factors. The SWB is based on the answers to the following question (which was preceded by a range of questions regarding various aspects of the respondent s life): Thinking about the good and the bad things in your life, which of these answers best describes your life as a whole?. Respondents could choose a category on a scale of one to seven ( As bad as can be, very bad, bad, alright, good, very good, as good as can be ). A set of question on drinking behaviour was included in the survey. We will make use of two variables that we consider more relevant for our analysis: the self-reported average number of drinks per day and the self-reported number of days within a typical week in which the individual consume some alcohol. These two variables represent good proxies of alcohol consumption at individual level. 9

10 Our regressions include the following set of covariates. The age of the respondent, the gender (a dummy variables taking 1 if the respondent is female), a categorical variable representing the level of education attained (primary school, lower secondary, upper secondary, degree and postgraduate), a dummy variable indicating whether the respondent is unemployed and finally the log of self-reported gross household income. Because missing values on income represented 23.7 percent of those interviewed, these were imputed based on the respondent s sociodemographic characteristics including age, gender, marital status, education level, area inhabited and employment status. The original income variable was divided in 10 categories, so mid-points were used (as in Stutzer, 2004). The survey was carried out when Ireland was still using the Irish Pound, so we converted to Euros using the fixed rate of IR 1= Econometric analysis 3.1 Alcohol consumption and economic depression We estimate the following equations with volume of beer, wine, spirits and total ethanol as dependent variables in order to compare the effects of economic contraction of alcohol consumption: lnbeervol= β 1 (NBERcontract it ) + β 2 (lnrealgdp it ) + β 3 (lnreal_pcpersinc it ) + β 4 (lnpopdens it ) + µ i + ε it (1) lnwinevol it = β 1 (NBERcontract it ) + β 2 (lnrealgdp it ) + β 3 (lnreal_pcpersinc it ) + β 4 (lnpopdens it ) + µ i + ε it (2) lnspiritvol it = β 1 (NBERcontract it ) + β 2 (lnrealgdp it ) + β 3 (lnreal_pcpersinc it ) + β 4 (lnpopdens it ) + µ i + ε it (3) lntotaleth it = β 1 (NBERcontract it ) + β 2 (lnrealgdp it + β 3 (lnreal_pcpersinc it ) + β 4 (lnpopdens it )+ µ i + ε it (4) Where the dependent variables are the natural logarithms of volume beverage and ethanol consumption by state and year, NBERcontract is a dummy equal to 1 in times of recession, 10

11 lnrealgdp is real state GDP, lnreal_pcpersinc is per capita personal income, lnpopdens is state population density, µi is a state specific fixed effect and εit is the idiosyncratic error term. The four initial specifications are shown below in Table 3 and all variables are in natural logarithms except the dummy variable for economic contraction. Table 3 about here The signs and significance of population density and personal income on the volume of consumption of all three types of alcohol are significant and of the expected sign. Only in the beer equation is real GDP significant and also negative in sign indicating that beer is an inferior economic good. The NBER dummy for economic contraction is positive in all three equations for alcohol by type but is statistically significant at the 1% level for both beer and spirit consumption as well as for total ethanol volume consumed. This provides evidence that people may turn to alcohol, especially the cheaper (beer) and more potent (spirits) more in recessions than in prosperous times, also else being equal. 3.2 Alcohol consumption and psychological depression The econometric specifications used to investigate the relationship between SWB and drinking behaviour are based on the following: SWB i = β 1 + β 2 (alcohol consumption i ) + β 3 (controls i ) + ε i. (5) Different specifications of equation (5) are run using ordered probit regressions to keep the categorical nature of the data together with OLS. The first column of Table 4 shows the estimated parameters for an ordered probit in which alcohol consumption is measured using the self-reported average number of drinks per day and. The second column is the analogous OLS regression. The third and fourth column shows the estimation of an ordered probit and OLS regressions, respectively, in which alcohol consumption is measured using the self-reported average number of days in a typical week where alcohol intake happens. Table 4 about here 11

12 In every specification used the measure of alcohol consumption is negatively correlated to SWB and it is statistically significant at 1 percent level. There are no differences among OLS and ordered probit estimations. The parameters in the specification using the number of drinking days in a typical week are larger in absolute value. OLS estimations can be interpreted directly as marginal effects and shows that an additional drink negatively affects the self-reported happiness by 0.47 points on our 7 scale, while an additional drinking day lower the reported mental stress by 0.73 points. To help the interpretation of ordered probit parameters we compute probability changes as the number of drinks changes from its sample minimum value to its maximum (i.e., from 0 to 32). Table 5 shows discrete effects together 95% confidence intervals of probability changes computed using the delta method (Long and Freese, 2005). Table 5 about here The probability of reporting the highest levels of SWB ( good, very good, as good as can be ) decreases by 5, 40 and 14 percentage points, respectively, as the number of drinks per day changes from 0 to 32 (the maximum number of drinks per day in our sample). These probability changes are statistically significant. Consistent with this finding is the fact that an average individual will be more likely to self-report himself on the lower ladder of the SWB scale if he has to increase his consumption of alcohol from 0 to 32 drinks per day. Although, these latter results are not statistically significant for the lowest categories ( as bad as can be and very bad ). The second row shows the probability changes when increasing the drinking days from 1 to 7. The probability of reporting the two highest level of SWB ( very good, as good as can be ) decreases by 13 and 6 percentage points, respectively, when drinking days changes from 1 to 7 in a typical week. These probability changes are statistically significant. Interestingly, and in contrast with the previous results, the probability of reporting the SWB category good increases by 6 percentage points as the number of drinking days vary between 1 and 7. The probability of reporting SWB = bad increases by 2 percentage points while, the probability changes at the lowest levels of SWB are very small and not statistically significant. 12

13 4. Conclusion Both our macro and micro analysis suggest that there is a relationship between economic recession and increasing consumption of alcohol and that heavy drinking behaviour is unambiguously associated with unhappy feelings or dissatisfaction. While there is potentially a difficulty in distinguishing the causality in the relationship between alcohol consumption and happiness or subjective well-being, there is less reason to speculate that alcohol consumption leads to recession, as opposed to our preliminary findings that people consume more alcohol in times of economic difficulty. Our findings are preliminary and fit our intuition that contributed to the formulation of the research question. In the future, it will be useful to collect more detailed macro-economic data such as state unemployment levels to test the robustness of our findings. Data on alcohol price levels and also taxes by alcohol type may prove useful so long as there is sufficient variation across state and also over time. 13

14 References Brenner, M.H., Mooney, A. (1983). Unemployment and health in the context of economic change. Social Science Medicine 17 (16): Clark, A.E. Frijters, P. and Shields, M.A. (2008). Relative Income, Happiness and Utility: An Explanation for the Easterlin Paradox and Other Puzzles. Journal of Economic Literature 46: Dee, T. (2001) Alcohol abuse and economic conditions: Evidence from repeated crosssections of individual-level data, Health Economics, 10: Di Tella, R. and MacCulloch, R. (2006). Some Uses of Happiness Data in Economics. Journal of Economic Perspectives 20: El-Guebaly, N. (2007). Investigating the Association Between Moderate Drinking and Mental Health Annals of Epidemiology, 17 (5), S55-S62. Ettner, S.L. (1997). Measuring the human cost of a weak economy: does unemployment lead to alcohol abuse? Social Science Medicine 44 (2), Freeman, D.G. (2001). Beer and the Business cycle. Applied Economics Letters 8: Freeman, D.G. Alternative Panel Estimates of Alcohol Demand, Taxation, and the Business Cycle. Southern Economic Journal, 67 (2): Frey, B. and Stutzer, A. (2002). What Can Economists Lear from Happiness Research? Journal of Economic Literature 40: Gallup-Healthways (2009). Monthly US Well-being Report, February Graham, C., Eggers, A. and Sukhtankar, S. (2004). Does happiness pay?: An exploration based on panel data from Russia. Journal of Economic Behavior and Organization 55(3): Jahoda, M. (1979). The impact of unemployment in the 1930s and the 1970s. Bulletin of the British Psychological Society 32, Johansson, E., Böckerman, P., Prättälä, R. and Uutela, A. (2006). Alcohol-related mortality, drinking behavior, and business cycles: Are slumps really dry seasons?, European Journal of Health Economics, 7, Murphy, J.G., McDevitt-Murphy, M.E and Barnett, N.P. (2005) Drink and Be Merry? Gender, 14

15 Life Satisfaction and Alcohol Consumption Among College Students. Psychology of Addictive Behavior 19(2): Krüger, N. and Svensson, M. (2008). Good Times are Drinking Times: Empirical Evidence on Businness Cycles and Alcohol Sales in Sweden Applied Economics Letters Long, J.S. and Freese, J. (2005). Regression Models for Categorical Outcomes Using Stata. Second Edition. College Station, TX: Stata Press. NIAAA. (1996) Alcohol and Stress, National Institute of Health, US Department of Health and Human Services, Washington D.C. Pierce, R.S., Frone, M.R., Russell, M., Cooper, M.L. (1994). Relationship of financial strain and psychosocial resources to alcohol use and abuse: the mediating role of negative affect and drinking motives. Journal of Health and Social Behavior 35 (4), Poherecky, L. A. (1991) Stress and alcohol interaction: An update of human research, Alcoholism: Clinical and Experimental Research, 15. Poikolainen K., Vartiainen E., Korhonen H. J. (1996). Alcohol intake and subjective health. American Journal of Epidemiology 144: Poikolainen K, Vartiainen E. (1999). Wine and good subjective health. American Journal of Epidemiology 150: Ruhm, C. J. (1995) Economic conditions and alcohol problems, Journal of Health Economics 14: Ruhm, C. J. and Black, W. E. (2002) Does drinking really decrease in bad times?, Journal of Health Economics 21: Stutzer, A. (2004). The role of income aspirations in individual happiness. Journal of Economic Behavior & Organization 54: UII (2001). Urban Institute Ireland National Survey on Quality of Life. Dublin: Urban Institute Ireland. Winton, M., Heather, N., Robertson, I. (1986). Effects of unemployment on drinking behavior: a review of the relevant evidence. The International Journal of Addictions 21(12):

16 Table 1. NBER Business Cycle Reference dates Peak Trough Recession years December 1969(IV) November 1970 (IV) 1970 November 1973(IV) March 1975 (I) 1974 January 1980(I) July 1980 (III) 1980 July 1981(III) November 1982 (IV) 1981,1982 July 1990(III) March 1991(I) 1990 March 2001(I) November 2001 (IV) 2001 Source: NBER Table 2. Per capita ethanol consumption (gallons of ethanol) with states Per capita ethanol consumption (gallons) Beer Wine Spirits Total Mean Median 1.29 (MI) 0.28 (MT) 0.86 (MT) 2.50 (CT) Minimum 0.83 (UT) 0.10 (MS) 0.48 (UT) 1.45 (UT) Maximum 1.95 (NV) 0.88 (DC) 2.41 (DC) 4.90 (NV) St. dev Source: NIAAA Table 3. Results from initial estimations Volume of Alcohol Beer Wine Spirit Total NBERcontract (0.0061)** (0.0083)** (0.0055)** lnrealgdp (0.0405)* lnreal_pcpersinc (0.0442)** (0.0802)** (0.0603)** lnpopdens (0.0467)** (0.0848)** (0.0638)** (0.0423)** Constant (0.1742)** (0.3161)** (0.2377)** (0.1578)** Observations R-squared Standard errors in parentheses * significant at 5%; ** significant at 1% 16

17 Table 4. SWB regressions on self-reported drinking behaviour Variable (1) (2) (3) (4) Alcohol consumption -.057*** -.047*** -.086*** -.073*** (0.127) (.011) (-.030) (.025) Age (-.004) (.002) (.002) (.002) Female -.198*** -.158*** -.143* -.115* (.074) (.061) (.073) (.061) Unemployed -1.06*** -.970*** -.970*** -.900*** (.223) (.186) (.222) (.186) Primary School (.143) (.119) (.144) (.121) Lower Secondary (.123) (.103) (.123) (.079) Upper secondary (.095) (.079) (.944) (.067) Log income.373***.322***.386***.335*** (.079) (.659) (.080) (.066) Standard errors in parenthesis. ***,**,* implies statistical significance at 1, 5 and 10%. 17

18 Table 5. Probability changes after SWB ordered probit regressions As bad as can be Very bad Bad Alright Good Very good As good as can be When # of drinks changes from min to max (0 32) [-0.037, 0.111] [-0.030, 0.171] [0.051, 0.231] [0.310, 0.388] [-0.081, ] [-0.433, ] minimum to its maximum value. 95% confidence level in squared brackets, ** implies statistical significance at the [-0.174, ] When # of drinking days changes from [-0.002, 0.005] [-0.004, 0.016] [0.004, 0.036] [0.085, 0.134] [0.061, 0.068] [-0.145, ] [-0.103, ] min to max (1 7) Note: Probability changes as the alcohol consumption (in terms of number of drinks in a month and drinking days) changes from its 18

19 Figure 2. Growth in per capita consumption of U.S. by alcohol type (1970=1) Source: NIAAA 19

20 Appendix A. The Urban Institute Ireland National Survey on Quality of Life The Urban Institute Ireland National Survey on Quality of Life was conducted in 2001 where a representative sample of 1,500 men and women, aged 18 and over and living in Ireland where interviewed. Due to missing observations the final sample consists of approximately (depending on the model specification) 1,467 observations. The effective response rate is 66.6 percent. The margin of error using the entire sample is ± 2.5 percent at a 95 percent confidence level. The 2000 Register of Electors was used as the sampling frame. The register is inclusive of all individuals nominated on Electoral Registration forms returned in July The register is compiled on a Local Authority basis of which there are 34 in Ireland (for more information on local authority and electoral divisions see below). The sampling procedure adopted was a two stage proportionate random sampling procedure using probability proportionate to size (PPS). The rationale governing this choice of design was to ensure coverage of all 34 Irish Counties with proportionate representation of all county areas. In selecting potential respondents from each, a computerized random numbers procedure was again used to ensure that each elector listed had an equal chance of being selected. All interviews were conducted during the period 12 March 2001 to 25 May To test for non-response bias, four key variables from the sample (age, sex, marital status and economic activity) were compared with corresponding Irish census estimates. Given the broad representativeness of the sample, no corrective weighting procedures were applied to the data (see UII, 2001). 20