1. Investigating the Volume and Structure of Alcohol Consumption and their Impact on Life Expectancy in Russian Regions Tatiana Kossova, PhD in Economics, Elena Kossova, PhD in Mathematics, Maria Sheluntcova, PhD in Economics National Research University Higher School of Economics, 2015 www.hse.ru This paper is an output of a research project implemented as part of the Basic Research Program at the National Research University Higher School of Economics (HSE)

2. National Research University Higher School of Economics, 2015 Consumption of alcohol in Russian regions фото What macroeconomic factors influence alcohol consumption in Russian regions? The priority of the government policy is to reduce alcohol consumption The volume and structure of alcohol consumption continue to change

3. National Research University Higher School of Economics, 2015 Literature review фото Regional differences in alcohol consumption Paper of Bränström & Andréasson (2008) for Sweden; Benčević- Striehlet et al (2009) for Croatia; Ogwang & Cho (2009) for Canada, etc. Macroeconomic factors influence alcohol consumption Per capita income: paper of Chaix & Chauvin (2003) for France, Ogwang & Cho (2009) for Canada, etc. Unemployment: paper of Herzfeld et al (2014) for Russia, Ogwang & Cho (2009) for Canada, Schnuerer et al (2013) for Germany, etc. Urbanization: paper of Klein & Pittman (1993) for the US, Schnuerer et al (2013) for Germany, Herzfeld et al (2014) for Russia, etc.

4. National Research University Higher School of Economics, 2015 Alcohol consumption and life expectancy in Russia фото Life expectancy gap between Russia and Western countries remains substantial largely due to alcohol abuse in Russia ( Shkolnikov et al., 2013) At least 1/3 of all deaths in Russia are directly or indirectly associated with alcohol intake (Pridemore 2008; Popov 2009) Regions substantially differ from each other on the volume of alcohol consumption and life expectancy indicators What is the relationship between alcohol consumption and mortality from external causes as well as life expectancy in Russia?

6. National Research University Higher School of Economics, 2015 Per capita consumption of alcoholic beverages in 2008 - 2012 фото

7. National Research University Higher School of Economics, 2015 Model specification and data фото

8. National Research University Higher School of Economics, 2015 Macroeconomic factors фото Income per-capita (rubles) Per-capita consumption of electricity (thousands kWh) Provision with computers per 100 households Economic development and living standards Population size (thousands) Degree of urbanization (%) Degree of urbanization Unemployment rate (%) Gini coefficient Level of social tension

9. National Research University Higher School of Economics, 2015 Definitions of variables used in models фото SymbolVariableComments ln(alcohol)Logarithm of absolute alcohol consumption ln(vodka)Logarithm of vodka and liqueurs consumption* ln(beer)Logarithm of beer per-capita consumption* ln(wine)Logarithm of wine per-capita consumption* ln(cogn) Logarithm cognacs, brandy and brandy spirits per- capita consumption* * Sales of alcoholic beverages during the year in physical terms (in liters). Measurement in physical terms make it easier to compare alcohol consumption in different regions.

10. National Research University Higher School of Economics, 2015 Definitions of variables used in models фото SymbolVariableComments Urbanization_rate Ratio of urban population to total population in a particular region ln(income_min) Logarithm of annual population income divided by 12 (months) and by the Average annual population size normalized by the subsistence minimum in the region ln(energy_consumpti on) Logarithm of per capita consumption of electricity ln(computers) Logarithm of provision of computers per 100 households 1/populationReciprocal value of the population of the region Unemployment_rate Ratio of the unemployed to the labor force in a particular region Gini_coefficientGini coefficient estimated for a particular region

11. National Research University Higher School of Economics, 2015 Descriptive statistics фото VariableMeanStd.dev.MinMax Population size (thousands)1792.11694.248.611 918.1 Degree of urbanization (%)69.512.626.4100 Income per-capita (rubles)16 3986 568.65 51348 622 Per-capita consumption of electricity (thousands kWh) 75.21.2333.15 Provision of computers per 100 households 61.52018118 Gini coefficient0.40.030.330.54 Unemployment rate (%)7.62.90.821.7 Vodka and liqueurs*11.43.82.224.3 Beer*64.323.12.5149.9 Wine*7.12.61.414.8 Cognacs, brandy and brandy spirits*0.70.40.12.3 Champagne and sparkling wine*1.70.90.35.3

12. National Research University Higher School of Economics, 2015 Estimation results фото VARIABLESLn(vodka)Ln(beer)Ln(wine) Ln(income_min)-0.130 0.252** -0.191* (0.0941)(0.107) (0.112) Ln(energy_consumption) 0.288***0.580*** 0.271** (0.0833)(0.112) (0.117) Ln(computers) -0.126*** (0.0339) Urbanization_rate 0.0188*** 0.0604*** (0.00659) (0.00951) 1/population 0.380*** (0.0893) Unemployment_rate -0.00831 0.0207*** (0.00542) (0.00598) Unempl_rate *(year-2008) -0.00532*** -0.00427*** (0.000650) (0.000914) Gini_coefficient 2.375** (1.059) Constant -0.6853.604*** -2.721*** (0.613)(0.242) (0.732) Observations390 R-squared0.3140.1150.207

13. National Research University Higher School of Economics, 2015 Estimation results фото (2)(3)(2) (4) VARIABLESLn(vodka)Ln(beer)Ln(wine)Ln(champ)Ln(cogn) Ln(income_min) -0.191*0.227* (0.112)(0.126)(0.121) Ln(energy_consumption)0.318***0.603***0.271**0.499*** (0.0809)(0.113)(0.117)(0.109) Ln(computers)-0.134***-0.0793*** (0.0310)(0.0277) Urbanization_rate0.0199*** 0.0604***0.0310***0.0520*** (0.00643) (0.00951)(0.00875)(0.0103) 1/population0.403***-0.193 (0.0871)(0.118) Unemployment_rate -0.0118**0.0207***-0.0239*** (0.00525)(0.00598)(0.00636) Unempl_rate *(year-2008)-0.00326*** -0.00427***0.00206**0.00517*** (0.000795)(0.000914)(0.000872)(0.000979) Gini_coefficient1.885** -1.354 (0.788) (1.421) Constant-0.2653.671***-2.721***-2.393***-4.230*** (0.560)(0.242)(0.732)(0.822)(0.754) Observations390 R-squared0.3500.1150.2070.2550.413

14. National Research University Higher School of Economics, 2015 Life expectancy for men and women in Russia фото Data source is the Federal State Statistics Service of Russia

15. National Research University Higher School of Economics, 2015 Estimation results фото VARIABLESLn(death)Ln(life_men)Ln(life_women) Ln(alcohol) 0.334*** -0.0346*-0.0219* (0.101) (0.0198)(0.0116) Ln(income_min) -0.286*** 0.0348***0.0152** (0.0785) (0.0122)(0.00671) Ln(computers) 0.0204***0.0106*** (0.00457)(0.00284) Ln(meat) 0.0374** (0.0173) Ln(sugar) 0.0370** (0.0154) Ln(Unemployment_rate) 0.0345* -0.00346* (0.0204) (0.00184) Ln(Unemployment_rate*(year-2008)) -0.0199***0.00256***0.00171*** (0.00208)(0.000407)(0.000234) Gini_coefficient 2.215***-0.235**-0.144** (0.795)(0.117)(0.0677) Constant 3.836***3.874***4.350*** (0.309)(0.111)(0.0373) R-squared 0,570,750,78

16. National Research University Higher School of Economics, 2015 Conclusions on the volume & structure of alcohol consumption in Russia фото There is the general trend of reduction of alcohol consumption in Russia as a whole over 2008 - 2012 Vodka and beer are main alcoholic beverages consumed in Russia The North of the European part of Russia and the Far East that are characterized by problem drinking

17. National Research University Higher School of Economics, 2015 Conclusions on macroeconomic factors фото Regions’ welfare & alcohol consumption: positive correlation The unemployment rate affects the consumption of different types of alcoholic beverages in a different way Urbanization & alcohol consumption: positive correlation. Sparsely populated regions are characterized by higher alcohol consumption

18. National Research University Higher School of Economics, 2015 Conclusions on alcohol consumption & life expectancy in Russia фото We confirm positive relationship between alcohol consumption and mortality from external causes in Russian regions The average life expectancy, other things being equal, is lower in regions where alcohol consumption is high. This effect is stronger for men than for women