A METHODOLOGICAL MANUAL: POVERTY MEASUREMENT IN THE KYRGYZ REPUBLIC This manual has been prepared in cooperation with the National Statistic Committee of the Kyrgyz Republic and underlines national methodology for poverty measurement. The manual was prepared by Saida Ismailakhunova (Sr. Economist), Sasun Tsirunyan (Sr. Statistician, consultant), Larisa Praslova (Sr. statistician, consultant), and with inputs from Galina Samohleb (Chief specialist of the Households Survey Division, NSC). Abbreviations and acronyms Full name KIHS Kyrgyz Integrated households budget and labor force survey HHS Household survey NSCKR the National Statistical Committee of the Kyrgyz Republic CPI Consumer Price Index DGs durable goods 2 TABLE OF CONTENTS 1. INTRODUCTION ................................................................................................................. 5 2. GOALS AND OBJECTIVES ................................................................................................ 6 2.1 Background ................................................................................................................................. 6 2.2 Review of the KIHS in the Kyrgyz Republic ........................................................................... 7 3. COMPONENTS OF CONSUMPTION AGGREGATE .................................................... 8 3.1 Estimating Food Costs ............................................................................................................... 8 3.2 Purchased Non-Food and Services ........................................................................................... 8 3.3 Durables ...................................................................................................................................... 8 3.4 Utility Services:........................................................................................................................... 9 3.5 Regional; Price deflators (Price Index): ................................................................................... 9 4. CONSTRUCTING THE POVERTY LINE ....................................................................... 10 4.1 Constructing the Food Basket Composition .......................................................................... 10 4.2 Constructing the Food Basket Cost ........................................................................................ 13 4.3 Constructing the Non-Food Basket Cost ................................................................................ 13 4.4 Estimating the Poverty Line at the Oblast Level ................................................................... 14 4.5 Application and Re-Computation of the Poverty Line ......................................................... 15 5. POVERTY STATISTICS .................................................................................................... 15 5.1 Constructing the Population’s Poverty Level ........................................................................ 15 5.2. Poverty Gap Index .................................................................................................................. 16 5.3. Poverty Severity Index ............................................................................................................ 16 CONCLUSION ......................................................................................................................... 17 ANNEX А. SPSS Syntax Codes Used to Produce the Results .............................................. 19 `1 Prices.sps ..................................................................................................................................... 19 2 Durables.sps ................................................................................................................................. 25 3 Income & Expenditures.sps ........................................................................................................ 27 4 Poverty Line.sps .......................................................................................................................... 38 5 Poverty.sps ................................................................................................................................... 43 ANNEX B. STATA do files translated from original SPSS syntax .................................... 45 1 Prices.do ....................................................................................................................................... 45 2 Durables.do .................................................................................................................................. 53 3 Income & Expenditures.do ......................................................................................................... 56 4 Poverty Line.do............................................................................................................................ 68 5 Poverty.do .................................................................................................................................... 74 ANNEX C. The Guidelines for Constructing Consumption Aggregates ........................... 77 3 List of Tables Table 1. Regional price deflators (Las-Peyres Price Index) for 2014 ......................................................... 9 Table 2. Composition of the Poverty Line Food Basket ........................................................................... 11 Table 3. Poverty Line Food Basket in 2008 .............................................................................................. 13 Table 4. Poverty Line in 2008 ................................................................................................................... 14 Table 5. Example Of Poverty Status Estimation ....................................................................................... 16 Table 6. Population Poverty Indicators by Region in 2014 in percent ................................................... 16 4 1. INTRODUCTION Poverty is a complex social and economic phenomenon and the activities designed to overcome it can be rather multi-faceted and implemented at a level of the whole country, a region, a settlement or an individual family; they can be carried out by government agencies, local communities and others. It is evident, that the applied poverty scale measurement shall take into account the specifics of carried out activities, the analysis needs and resource available for this measurement. The measurement of poverty in the Kyrgyz Republic was launched in 1996 under the Poverty Monitoring Project based on direct sample household surveys with the methodological and financial support from the World Bank. The poverty measurement methodology applied by the National Statistical Committee of the Kyrgyz Republic is based on objective measurements of household expenditures according to the World Bank’s LSMS (Living Standard Measuring Surveys) standards. There are three key concepts in the global practice defining poverty: absolute, relative and subjective. The absolute poverty concept is based on establishing the minimum set of key requirements (the minimum subsistence level) and the size of resources required to satisfy these needs. In case of a relative approach to poverty definition, welfare measurements are not compared to minimum needs, but to the level of material security prevailing in one or other country. The subjective approach is defined by the level of income, which, according to experts, respondents or a researcher allows making ‘ends meet’. In the Kyrgyz Republic the poverty level is measured by using the absolute poverty level. This approach is widely used in the global scale and has been adopted by the Kyrgyz Republic based on the recommendation by the World Bank experts. Such an approach enables establishing individuals, who do not have a sufficient monetary and in-kind income to achieve the minimum consumption level. 5 2. GOALS AND OBJECTIVES The integrated household budget and labor force survey (KIHS) provides the key information base to study the population’s living standards at the micro-level; the household statistics is one of the sectors of social and economic statistics examining the living standards of the country’s population, and mainly its financial situation. The findings of household survey characterize levels of income, expenditures, personal consumption, changes in the structure of income and consumer spending by various population groups, enable to identify differences in these levels depending on the family composition, employment of its members; describe the role of various sources in income generation, allow depicting changes in consumer demand; characterize population’ differentiation by the level of income, expenditures, consumption, etc. These KIHS are widely used in economic estimations of gross domestic product, development of national accounts, computing the consumer price index, population’s real income; preparing the balance of production and use of agricultural products, etc. The objectives of the KIHS are: - obtaining complete and reliable economic and statistical information about the population’s living standards; - using the data for policy making with the aim of protecting various population groups; - monitoring indicators of the National Sustainable Development Strategy (NSDS/Millennium Development Goals (MDGs), SDG, food security; - wide usage of survey materials in various economic and statistical computations by ministries, agencies, research and international organizations. 2.1 Background The National Statistical Committee of the Kyrgyz Republic runs the sample household budget survey in Kyrgyzstan for a long time (since 1952). Household budget statistics is a part of examination of the living standards of various social and demographic population groups living in the territory of the republic. The survey is based on direct interviews with household members and additional records on income and expenditures maintained by the survey households. There was a new impetus in developing the household budget statistics after the republic gained its independence, when the centralized organization of these surveys had been discontinued. Household survey reforms had been linked to the survey on the Poverty Monitoring Component in 1995 under the Social Security Network in the Kyrgyz Republic Project designed and implemented with the support from the World Bank. As a result of reforms carried out in sample surveys design in 1997, the scope of households had been expanded from 1,100 to 2,000 and since 2000 – to 3,000 households (0.27% of total population). From 2002, the National Statistical Committee of the Kyrgyz Republic, with the technical support from the Oxford Policy Management Ltd. Company implements the program “Development of Statistics to Support CDF/NPRS Processes” financed by the UK Department for International Development (DfID). The project restricted the existing household budget survey and established a new integrated sample survey, which was transformed from the monthly survey of 3,000 households to the quarterly survey of 5,000 households (0.4% of total population) based on the updated questionnaire, which included key indicators from poverty and labor monitoring surveys. 6 The integrated household survey represents a new system of household interviews. In contrast to the previous survey, the KIHS has a significantly larger sample size, and it is conducted not monthly, but quarterly, and uses significantly modified questionnaires. Introduction of the KIHS allowed to significantly reduce the burden on respondents and to provide for a broader coverage of households, which live in remote and mountainous areas. 2.2 Review of the KIHS in the Kyrgyz Republic Staring from 2003 the sample covers seven regions: Batken, Jalal-Abad, Issyk-Kul, Naryn, Osh, Talas and Chui oblasts, as well as Bishkek city. In 2013, Osh city was separated into an individual stratum. As of today the sample allocation is as follows: 1. Bishkek city – 660 households 2. Osh city – 264 households 3. Batken – 528 households 4. Jalal-Abad – 660 households 5. Issyk-Kul –660 households 6. Naryn – 528 households 7. Osh – 528 households 8. Talas – 528 households 9. Chui – 660 households. The KIHS uses seven questionnaires, which are divided into three types according to the completion schedule. I. Daily questionnaires: A diary to keep records of expenditures by a household for food (questionnaire №3, to be filled out for 14 days) and the Ledger to record expenditures by a household for non-food (questionnaire №5, to be filled out for 3 months); II. Quarterly questionnaires: A diary of a household (questionnaire №1), Employment and Unemployment (questionnaire №4) and Household’s Income and Expenditures (questionnaire №6); III. Annual questionnaires: Social and Demographic Characteristics of Individuals in a Household (questionnaire №2) and Personal Possessions in a Household and Housing Conditions (questionnaire №7); Questionnaires include the following information: QUESTIONNAIRE №1 – Socio-demographic information; QUESTIONNAIRE №2 – Education, migration, health status and anthropometric measurements of all household members and an individual woman’s questionnaire; QUESTIONNAIRE №3 – Purchases of food, drinks and tobacco products, consumption of food, drinks and tobacco products and expenditures for meals outside the home; QUESTIONNAIRE №4 – Labor force survey; Information about the respondent, key job, additional job, searching for a job, economically inactive, engaged in production of goods at the household and income of household members; QUESTIONNAIRE №5 – Purchases of non-food (quantity, measuring unit, cost, for whom purchased, what it is made of, condition); QUESTIONNAIRE №6 – Housing and utilities expenditures, health expenditures, transport expenditures, expenditures for education and childcare, other expenditures, payments for services, a home farm and income. QUESTIONNAIRE №7 – Housing conditions, availability of durables, land and machinery. 7 3. COMPONENTS OF CONSUMPTION AGGREGATE The consumption aggregate is estimated based on KIHS datasets and is consistent with standard methods (Deaton, 1980; Deaton and Zaidi, 1999). (see Annex В) When constructing general and per-capita consumption, we should collect together data on all consumption expenditures by the population. They include: – Computing the cost of consumed food (questionnaire №3); – Purchasing non-food for personal use (questionnaire №6); – Payment for personal services (questionnaire №6); – Computing notional earnings from durables given depreciation (questionnaire №7). 3.1 Estimating Food Costs Food costs are estimated based on the data on consumption of food in a household (Questionnaire №3, Section 2) and expenditures of the household for meals outside the home (Questionnaire №3, Section 3). Purchased food: one takes into account expenditures by households to buy food intended for consumption. Meals consumed outside the home: one takes into account expenditures by households for meals purchased and consumed outside home during the time period under survey. Food consumed in the household taking into account all sources of income (Questionnaire №3, Section 2): computing the total costs of consumed food based on purchase prices (Questionnaire №3, Section 1). First of all, one should compute the average price of each crop cultivated and that of the products of animal origin using the prices of this populated area. If the prices were not available at a local level, then the prices for regions of the country were constructed. Further, these prices are used to compute the total cost of agricultural products consumed by the family during the year. 3.2 Purchased Non-Food and Services These include such goods as clothes, underwear, furniture, books, newspapers, personal care products, detergents, goods for house repairs, as well as services: transport, laundry, sauna and hairdressers’, health and education services. The total amount spent for each of these categories of non-food and services during the period under review is computed for each family separately. Construction materials, bathroom fixtures, computing and office equipment, electrical appliances, vehicles, furniture and jewelry items are not included into estimations to measure poverty indicators. 3.3 Durables Durable consumer goods. From the viewpoint of household’s welfare, an adequate indicator reflecting consumption of durable goods (DGs) is not expenditures for their purchase 8 during the period under review, but the cost of services the household receives from all DGs in its possession during the corresponding period. That is one has to estimate the residual value and the notional value of using these goods (depreciation) applying a regression model (see Annex А). 3.4 Utility Services: Data on monthly expenditures for heating, electricity, gas, coal, kerosene, firewood, other types of fuel, water supply, waste disposal, telephone, cleaning, etc. are used. All expenditures mentioned above are summed up to get the total family consumption for a year. 3.5 Regional; Price deflators (Price Index): To estimate poverty at the level of regions, a price index estimated from survey data for food is used, which takes into account regional differences in prices for food in urban and rural areas. To analyze poverty, the nominal consumption of a household is adjusted for a Las- Peyres price index, which takes into account regional differences in prices for food in urban and rural areas. The consumer price index (CPI) in the Kyrgyz Republic is estimated based on the prices recorded in all spheres of trade in oblast centers and large cities. Taking into account that the official CPI does not reflect the price differential for rural areas, a decision was made to develop a price index at a level of urban/rural regions based on the survey data. The price index was estimated based only on food prices. A ratio of the average regional price to the average republican price for urban and rural areas is estimated for each type of product consumed by all households. The aggregated average values of ratios are normalized to the republican value. Normalization is considered as a ratio of the average price for each region to the average republican price. The table below presents the normalized food price index for urban/rural regions, where the average republican value during the period under review was regarded as 1.000. Table 1. Regional price deflators (Las-Peyres Price Index) for 2014 Kyrgyz Republic 1.000 Batken oblast, urban area 1.038 Batken oblast, rural area 1.009 Jalal-Abad oblast, urban area 1.035 Jalal-Abad oblast, rural area 1.025 Issyk-Kul oblast, urban area 0.954 Issyk-Kul oblast, rural area 0.946 Naryn oblast, urban area 0.988 Naryn oblast, rural area 0.970 Osh oblast, urban area 1.032 Osh oblast, rural area 1.004 Talas oblast, urban area 0.994 Talas oblast, rural area 0.956 9 Chui oblast, urban area 0.997 Chui oblast, rural area 0.978 Bishkek city 1.012 Osh city 1.063 Nominal food consumption by a household was adjusted for the price index using the following formula: Adjusted cost of food = Cost of food / Las-Peyres price index. Total adjusted consumption by a household was determined based on the following formula: Total consumption = Adjusted consumption of food + Nominal consumption of non-food, services and notional value of DGs. The key indicator of a household’s welfare is the total average per capita consumption given the size of a household. It should be mentioned that no temporal deflation was used because the households were surveyed during 12 months . 4. CONSTRUCTING THE POVERTY LINE 4.1 Constructing the Food Basket Composition Food is the essential need of any person. Food is computed in kind and in terms of cost, as well as its caloric value. Computation takes into account the consumed food obtained from different sources: purchased, received in exchange for work or as gift, produced at a home farm. The food basket is formulated in four stages: I. Formulation of a basket of actual in-kind consumption. For this purpose all consumed food is modified into one reference standard. The total consumption of each type of product is estimated. II. Actual consumption is estimated in terms of cost. The purchased consumed food is estimated based on the purchase price. To estimate the cost of food received in exchange for work or as gift, and home-produced food, the average weighted prices at a household level are used. If the prices for a certain product are not available at a household level, then the prices of the next level are used: village, aiyl okmotu, rayon, oblast (urban/rural) and republic (urban/rural). III. Actual consumption is estimated in terms of food’s caloric value using the following formula: TKh =  (FOODi*Kkali), where TKh – total consumption of calories by a household FOODi – the volume of i-th food, kg 10 Kkali – caloric value i-th food, kcal/kg IV. The total consumption of each product is computed based on three parameters: in- kind, cost, caloric value in the country as a whole and by decile group computed by level of consumption expenditures. The level of household’s welfare influences the quality, quantity and diversity of consumed food. The minimal set of basic products for a poverty line food basket is determined based on the actual food consumption by population with low income (3-5 decile groups of consumption per-capita). The considered target group represents 30 percent of population with an income below the average and does not include 20 percent of population with the lowest income. The poverty line food basket includes a set of food products, the cumulative cost share of which is 97 percent of the total cost of the total food basket of the target group. The basket includes food with the largest cost share, excluding liquors. In 2008 the food basket included 85 out 230 products in the composition of the food basket of the target group. Table 2. Composition of the Poverty Line Food Basket (III, IV, V deciles) № Name of product Quantity, kg Cost, soms Product’s Cumulative share in share total cost 1 Wheat flour 76,981.89 1871,119.99 17.08 17.1 2 Beef, veal and yak meat 6,582.66 1,028,593.24 9.39 26.5 3 Mutton 3,269.80 560,680.08 5.12 31.6 4 Potato 39,574.82 486,232.20 4.44 36.0 5 Hulled rice 9,101.22 429,400.66 3.92 39.9 6 Raw cow’s milk 23,054.00 370,775.72 3.38 43.3 7 Curdled milk and ayran, sour milk 8,135.41 337,628.36 3.08 46.4 8 Lump sugar sugar, sugar 9,682.06 308,122.51 2.81 49.2 9 Non-refined cotton seed oil 3,597.40 279,523.83 2.55 51.8 10 Jam 3,670.51 257,135.83 2.35 54.1 11 Apples 8,470.00 253,452.65 2.31 56.4 12 White wheat bread and black wheat 6,976.08 230,172.38 2.10 58.5 bread 13 Refined cotton seed oil 2,255.45 202,747.20 1.85 60.4 14 Butter 942.51 174,157.28 1.59 62.0 15 Sweet cookies 2,359.43 171,916.97 1.57 63.5 16 Eggs 31,981.30 167,151.58 1.53 65.1 17 Onion 12,092.92 164,099.07 1.50 66.6 18 Pasta 4,394.10 157,089.44 1.43 68.0 19 Refined sunflower oil 1,651.40 157,079.34 1.43 69.4 20 Black tea 619.29 146,866.03 1.34 70.8 21 Cooking carrot 10,785.30 142,545.53 1.30 72.1 22 Frozen chicken legs 1,271.09 124,255.14 1.13 73.2 23 Hedonic products, elbow macaroni 3,393.80 123,970.64 1.13 74.3 24 Noodles 3,112.53 116,024.35 1.06 75.4 25 “Maksym-Shoro” drink 6,860.80 109,177.20 1.00 76.4 26 Watermelons 9,415.50 100,900.56 0.92 77.3 27 Non-refined sunflower oil 1,279.70 99,677.47 0.91 78.2 28 Chocolate sweets 628.91 96,429.57 0.88 79.1 29 Flatbread 2,717.70 95,073.79 0.87 80.0 30 Other canned vegetables with acetic 1,751.10 93,558.00 0.85 80.8 11 № Name of product Quantity, kg Cost, soms Product’s Cumulative share in share total cost acid, assorted 31 Vermicelli 2436.30 88,999.03 0.81 81.6 32 Tomatoes 6124.00 81,441.25 0.74 82.4 33 Canned fruits and berries (home-made 864.10 79,328.09 0.72 83.1 compot) 34 Baking active yeast 308.19 56,895.78 0.52 83.6 35 Red and white cabbage 3,752.20 56,714.23 0.52 84.1 36 Cream 449.35 55,382.89 0.51 84.6 37 Caramel with fillings of fruit, berries, 665.89 55,334.89 0.50 85.1 fruit and berries and jelly 38 Buckwheat 1,412.75 52,226.64 0.48 85.6 39 By-products 851.74 49,115.30 0.45 86.1 40 Cucumbers 3,472.00 47,900.66 0.44 86.5 41 Goat meat 334.50 46,366.75 0.42 86.9 42 Tomato puree, tomato paste 670.76 44,347.03 0.40 87.3 43 Gingerbread 633.20 42,928.43 0.39 87.7 44 Fresh grapes 1,111.50 42,908.21 0.39 88.1 45 Salt 4,187.59 42,842.58 0.39 88.5 46 Margarine and similar products 350.16 38,156.82 0.35 88.9 47 Hens and chickens 294.26 37,105.69 0.34 89.2 48 Fruit and vegetable juices 856.40 36,695.69 0.33 89.5 49 Semi-smoked sausages 230.39 35,734.14 0.33 89.9 50 Boiled sausage products, frankfurters, 254.54 33,551.52 0.31 90.2 small sausages 51 Ice cream 317.77 31,858.03 0.29 90.5 52 Apricots 1,155.70 31,748.40 0.29 90.7 53 Cakes 193.70 30,519.76 0.28 91.0 54 Hard candy caramel 344.89 30,313.86 0.28 91.3 55 Fresh fish or frozen fish 292.17 29,541.46 0.27 91.6 56 Water, including mineral and 1,588.70 28,105.76 0.26 91.8 carbonated, with the addition of sugar and or sweeteners (Fanta, lemonade) 57 Canned cucumbers with vinegar or 418.60 26,516.67 0.24 92.1 acetic acid 58 Melons 2,015.80 25,816.92 0.24 92.3 59 Melted butter 156.76 2,5220.59 0.23 92.5 60 Lamb fat and beef fat 211.96 24,825.22 0.23 92.8 61 Walnuts 357.66 24,683.68 0.23 93.0 62 Noodles (lagman) 650.55 24,613.42 0.22 93.2 63 Natural honey 155.12 24,602.71 0.22 93.4 64 Pork 148.90 24,582.84 0.22 93.7 65 Salted and pickled cucumbers 340.40 22,200.02 0.20 93.9 66 Canned tomatoes with vinegar or acetic 346.50 21,442.45 0.20 94.1 acid 67 Radish 1,501.80 20,846.82 0.19 94.2 68 Horse meat 127.40 20,710.38 0.19 94.4 69 Dried apricots 226.00 20,476.27 0.19 94.6 70 Fresh bell pepper 1,248.96 20,155.12 0.18 94.8 71 Peas 618.95 19,457.66 0.18 95.0 72 Waffles 269.65 19,192.18 0.18 95.2 73 Kefir 517.50 18,662.56 0.17 95.3 74 Dry baking yeast 91.18 17,624.28 0.16 95.5 75 Sour-cream 251.36 17,295.37 0.16 95.6 76 Pears 431.50 16,602.34 0.15 95.8 77 Low-fat curd 122.40 16,534.33 0.15 96.0 12 № Name of product Quantity, kg Cost, soms Product’s Cumulative share in share total cost 78 Mayonnaise 184.85 16,268.63 0.15 96.1 79 Black and red ground pepper 110.48 16,243.73 0.15 96.2 80 Pickled cabbage 237.50 16,111.04 0.15 96.4 81 Pumpkin 768.43 13,804.24 0.13 96.5 82 Unsweetened mineral and carbonated 1,058.10 13,691.20 0.12 96.6 water 83 Dumplings 143.05 12,327.92 0.11 96.8 84 Beans 330.60 11,012.85 0.10 96.9 85 Green tea 55.03 10,966.05 0.10 97.0 4.2 Constructing the Food Basket Cost Once the set of products in the poverty line food basket is determined, one shall compute its cost to achieve the level of dietary energy consumption of 2,100 kcal per capita per day. For this purpose the quantity of actually consumed food is converted into calories by multiplying by the caloric value of each specific food product to estimate the total calories and the share of each food product in total calories. The cost of one calorie in each food is calculated in the constructed poverty line food basket. The food basket cost is adjusted to 2,100 kcal according to the formula of proportional equalization: 85 Cost of 2100 kcal =  Dk i =1 i * 2100 * St i , where Dki - the share of calories of i-th product; Sti - the cost of one calorie of i-th product. Table 3. Poverty Line Food Basket in 2008 Yearly costs, Calories by Share of Share of Monthly costs, soms group, cost in the calories in the soms kcal/day basket basket Food basket 975.84 11,710.10 2,100.0 1.000 1.000 Bread and bakery products 311.58 3,738.90 1,239.8 0.319 0.590 Milk and dairy products 84.53 1,014.37 93.6 0.087 0.045 Meat and meat products 162.24 1,946.80 93.5 0.166 0.045 Fish and fish products 1.91 22.95 0.4 0.002 0.000 Oil, margarine and other fats 75.07 900.84 258.2 0.077 0.123 Eggs 15.12 181.38 10.0 0.015 0.005 Potatoes 44.16 529.88 80.5 0.045 0.038 Vegetables and melons 96.26 1,155.16 65.8 0.099 0.031 Fruits and berries 45.01 540.15 38.9 0.046 0.019 Sugar and confectionery products 102.43 1,229.18 201.1 0.105 0.096 Tea, coffee, cocoa 14.24 170.92 5.3 0.015 0.003 Soft drinks 7.65 91.74 7.7 0.008 0.004 Other food 15.65 187.83 5.1 0.016 0.002 4.3 Constructing the Non-Food Basket Cost To construct the general poverty line the cost of the most essential non-food products and services is added to the cost of the food basket. 13 As for non-food and services, to avoid arbitrary judgments about the minimum needs for clothes, housing and transport services, an approach is used, which is based on household survey data. We considered 75 percent of the population (1, 2, and 3 quartiles by welfare level) as a target group, who have the cost of food consumption 30 percent higher than the food poverty line. Taking into account that the consumption of food by these basic families is close to the physiological minimum, it can be assumed that all non-food costs of such households are the most essential. The share of food consumption in the target group was 63.9%, consumption of non-food and services – 36.1%. Thus, General poverty line = Cost of food + Cost of non-food and services, where: The cost of food poverty line = 975.84 soms (63.9%) The cost of non-food and services = 551.08 soms (36.1%) The general poverty line = 975.84 +551.08 = 1526.92 soms per capita per month The poverty line is estimated based on the average cost of per capita consumption In 2011 the reference population for estimation of food poverty line was changed from deciles 3-5 to deciles 2-5. The reference population for estimation of the share of food in the poverty line was updated as well. The population consuming food within the interval of food poverty line +- 10 percent was adopted in the methodology in line with international best practices. 4.4 Estimating the Poverty Line at the Oblast Level To estimate the poverty line at the oblast level, the price deflator for food is used, which takes into account regional differences in prices for food in urban and rural areas. The index is estimated based on the household survey data. The ratio of the average regional price to the average republican price in urban and rural areas is computed for each product. Aggregated average values of ratios are normalized to the republican value. The computed price index for food has a dual application. The application of the price index to the cost of actual food consumption at the household level enables using the republican poverty line to assess the population’s poverty level. The application of the price index to the republican extreme poverty level enables measuring the general and extreme poverty lines at the level of regions for publication purposes. Table 4. Poverty Line in 2008 Poverty line, soms Region Price index Extreme General Kyrgyz Republic 1.000 975.84 1,526.92 Batken oblast – urban settlements 1.002 977.31 1,528.38 Batken oblast – rural area 0.970 946.39 1,497.47 Jalal-Abad oblast – urban settlements 1.009 985.06 1,536.14 Jalal-Abad oblast – rural area 0.984 960.43 1,511.51 Issyk-Kul oblast – urban settlements 1.011 986.54 1,537.61 Issyk-Kul oblast – rural area 0.994 969.76 1,520.84 Naryn oblast – urban settlements 1.022 996.98 1,548.05 Naryn oblast – rural area 1.020 995.28 1,546.36 14 Osh oblast – urban settlements 0.999 975.03 1,526.11 Osh oblast – rural area 0.991 967.45 1,518.52 Talas oblast – urban settlements 0.967 943.93 1,495.01 Talas oblast – rural area 0.952 929.24 1,480.32 Chui oblast – urban settlements 1.010 985.57 1,536.65 Chui oblast – rural area 0.996 972.38 1,523.45 Bishkek city 1.072 1,046.28 1,597.35 It should be mentioned that both methods of applying the price index are very close but not identical in measuring the poverty level. The reason is that the only food component of consumption was deflated regionally while non - component was not. The poverty was measures using a single national poverty line and deflated consumption aggregate of households. The table above is for presentation of approximate poverty lines on regional level using regionally adjusted national poverty line . The price deflators are computed annually. 4.5 Application and Re-Computation of the Poverty Line The poverty line is used for annual measurement of the population’s poverty line in the Kyrgyz Republic. The poverty line is computed at least every five years and is adjusted for inflation in subsequent years. The poverty line is indexed by the value of the average annual consumer price index for food and non-food, and services. In case the average annual inflation rate exceeds 10 percent, the poverty line will be re-computed. The poverty line is computed by the National Statistical Committee of the Kyrgyz Republic and is published annually in statistics digests. 5. POVERTY STATISTICS There are three different poverty metrics used in the analysis, which were proposed by Foster, Greer and Thorbecke in 1984. These indicators provide additional understanding of the population’s living standards. 5.1 Constructing the Population’s Poverty Level The key poverty metric is the headcount index (the poverty level in the country), which is defined as the proportion of the population with the consumption volume below the general poverty line. The poverty level is constructed based on the following formula: q H= , n where H – the promotion of poor population q – the number of poor population n – the total population Based on the results in Table 5, one can say that the households with codes 520, 896, 1319, 2450 and 2535 are referred to the category of poor, of which households 1319 and 2535 are very poor. All members of the households referred to the category of poor are counted as poor. 15 Table 5. Example Of Poverty Status Estimation Total expenditures Extreme A sign of being A sign of being Household code Poverty line per person a year poverty line poor very poor 213 16,115.40 7,005.63 4,218.50 0 0 415 17,781.26 7,005.63 4,218.50 0 0 520 4,440.46 7,005.63 4,218.50 1 0 896 5,633.16 7,005.63 4,218.50 1 0 1319 4,059.05 7,005.63 4,218.50 1 1 2105 14,784.79 7,005.63 4,218.50 0 0 2450 5,864.73 7,005.63 4,218.50 1 0 2535 3,802.65 7,005.63 4,218.50 1 1 2689 16,337.40 7,005.63 4,218.50 0 0 5.2. Poverty Gap Index The poverty gap index (income deficit or consumption deficit) is a percentage metric of the distance between the poverty line and the actual level of consumption by poor population, and shows those expenditures, which are needed to bring each household to the poverty line. The poverty gap, can be computed as follows: 1 ( zi − y i ) P1 =  z n i Q i . 5.3. Poverty Severity Index The poverty severity index is a metric proposed by Forester, Greer and Thorbecke (Р2), which shows the average weighted deviation of the poor population’s income from the poverty line value. averages the squares of the poverty gaps relative to the poverty line. The poverty severity metric is expressed by the following formula: 1 (z − y ) 2 P2 =  i 2 i n iQ zi . Table 6. Population Poverty Indicators by Region in 2014 in percent Poverty level Poverty Gap Poverty severity villag villag villag total town e total town e total town e Kyrgyz Republic 30.6 26.9 32.6 5.4 5.0 5.6 1.4 1.4 1.4 Batken oblast 40.7 24.6 47.5 8.9 6.0 10.1 2.6 1.8 3.0 Jalal-Abad oblast 46.4 54.2 43.3 8.2 10.9 7.1 2.1 3.0 1.8 Issyk-Kul oblast 26.0 15.9 30.0 3.7 2.8 4.1 0.8 0.7 0.8 Naryn oblast 30.6 26.4 31.2 5.9 6.6 5.8 1.7 2.4 1.6 Osh oblast 31.7 45.8 30.6 4.8 10.6 4.3 1.0 3.4 0.8 Talas oblast 19.0 10.7 20.4 2.6 1.2 2.8 0.5 0.2 0.5 16 Chui oblast 21.6 18.6 22.2 4.9 3.5 5.2 1.7 1.2 1.8 Bishkek city 17.6 17.6 2.4 2.4 0.5 0.5 Osh city 33.4 33.4 6.6 6.6 1.9 1.9 CONCLUSION The NSC’s methodology is aligned with international standards for poverty measurement and is based on scientific approaches with wide application of mathematical methods; it also allows obtaining objectives measurements of poverty indicators, which do not depend on subjective opinions of poor or non-poor citizens. It allows to relatively accurately measure the degree of households’ welfare and the population’s poverty level. 17 REFERENCES 1. Kudabaev Z. I., Ibragimova Sh. M. Economic Growth and Poverty Reduction in Kyrgyzstan. Issues of Statistics. Moscow. 4/2003. 2. Nanak Kakwani. Volume 18 No.2. Asian Development Review. 2000, pp. 74-84. 3. Martin Ravallion. Comparative Poverty Measurements, Working Paper №88 R, Statistical Study on Population’s Living Standards, 1999. 4. Deaton, Angus. The Measurement of Welfare. Theory and Practical Guidelines. Living Standard Measurement Study, Working Paper No. 7, World Bank, 1980. 5. “Living Standards” Compendium, 2014. 6. Resolution of the Government of the Kyrgyz Republic «”On Approval of the Methodology for Poverty Line Measurement”, 2009. 18 ANNEX А. SPSS Syntax Codes Used to Produce the Results `1 Prices.sps Computing the consumption aggregate to measure the poverty level Computing the consumption aggregate used for poverty level metrics includes several steps: 1. Estimating food consumed by a household during the year. 2. Computing household’s expenditures for non-food and services. 1. А) To estimate the foods consumed by the households during the year (Questionnaire №3, Section 2) it is necessary to compute the price of each food from Questionnaire №3, Section 1. The Reference Book on Food (GSKP.SAV – variable Ltr_kg) has the rates of conversion to one measuring unit (liters to kilograms), i.e. such food, as dairy products, vegetable preserves, etc. purchased in liters, shall be converted to kilograms, as well as grams to kilograms and milliliters to liters. ** 1 PRICES ************************************************. CD 'C:\Users\Sasun\Work\Kyrgyz\2021'. CD "D:\_WORK\Kyrgyz2021". **** estimation of personal consumption in KG from section 1 Form 3. GET FILE='DATA\f3_01.sav'. RENAME VARIABLES (code =c3 ). sort cases by c3 (a) . MATCH FILES /FILE=* /TABLE= 'out\GSKP_prod.sav' /BY c3. EXECUTE . IF (f3r1q6 = 3 & ltr_kg <> 1) f3r1q5 = f3r1q5 * ltr_kg. IF (f3r1q6 = 1 | f3r1q6 = 3 | f3r1q6 = 4) cons_kg = f3r1q5 . IF (f3r1q6 = 2 ) cons_kg = f3r1q5/ 1000 . IF ( f3r1q6 = 5) cons_kg = f3r1q5/ 1000 * ltr_kg . EXECUTE . COMPUTE price_f = f3r1q7 / cons_kg. VARIABLE LABELS price_f 'price per product unit’. SORT CASES BY hh_code (A) . MATCH FILES /FILE=* /TABLE='DATA\Basic.sav' /BY hh_code. SAVE OUTFILE='Out\Price.sav' /COMPRESSED. *************************************************. В) Some food consumed by a household have been grown in a home farm or received as a payment for work. To compute these products, one has 19 to compute prices at various territorial levels – from the settlement where the household lives to the republican level. ************** Estimation of median prices *******************. GET FILE='Out\Price.sav'. EXECUTE . *COMPUTE w = expfact* cons_kg . *COMPUTE w = expfact. weight by expfact. *weight by w. AGGREGATE /OUTFILE='Out\price_obl_reg.sav' /BREAK=kod_gr obl_reg /PROBL = MEDIAN (price_f ) / n1= NU. AGGREGATE /OUTFILE='Out\price_national.sav' /BREAK=kod_gr /PRnat = MEDIAN(price_f ) /sumpr= sum (f3r1q7)/ n1= NU. SORT CASES BY kod_gr (A). MATCH FILES /FILE=* /TABLE='Out\price_national.sav' /BY kod_gr. ******* deleting extreme values in prices ( unit values). DO IF (price_f < PRnat * 0.1 | price_f > PRnat * 10) . RECODE price_f (ELSE=SYSMIS) . END IF . EXECUTE . ******* checking missing values in price_f . DESCRIPTIVES VARIABLES=price_f /STATISTICS=MEAN SUM MIN MAX . ************ Estimation of prices on various levels **********. AGGREGATE /OUTFILE='Out\Price_punkt.sav' /BREAK=punkt kod_gr /pric_pu 'price in a settlement' = MEAN(price_f). AGGREGATE /OUTFILE='Out\Price_raion.sav' /BREAK=raion kod_gr /pric_ra 'price in the rayon' =MEAN(price_f). AGGREGATE /OUTFILE='Out\Price_kenesh.sav' /BREAK=kenesh kod_gr /pric_ke 'price in a kenesh' = MEAN(price_f). 20 AGGREGATE /OUTFILE='Out\Price_obl.sav' /BREAK=oblast kod_gr /pric_o 'price in oblast' = MEAN(price_f). AGGREGATE /OUTFILE='Out\Price_reg.sav' /BREAK=region kod_gr /pric_r 'price in the region' = MEAN(price_f). AGGREGATE /OUTFILE='Out\Price_for_r2.sav' /BREAK=hh_code kod_gr /pric_hh 'price for a household' = MEAN(price_f). SAVE OUTFILE='Out\Price.sav' /COMPRESSED. *************************************************. С) The next step is to compute the price index at the stratum level (region/town, village). It is required to equalize the regions in relation to the poverty line, as it is computed only at the republican level. ************ calculation of index. match files /FILE='Out\price_obl_reg.sav' /table='Out\price_national.sav' /by kod_gr . EXECUTE. COMPUTE pi = probl / prnat . WEIGHT BY sumpr. SAVE OUTFILE='Out\sumprw.sav' /COMPRESSED. AGGREGATE /OUTFILE='Out\CPI.tmp' /BREAK=obl_reg /pindex = MEAN(pi). GET FILE='Out\CPI.tmp'. COMPUTE one2 = 1 . AGGREGATE /OUTFILE='Out\Norm_CPI.tmp' /BREAK=one2 /meanpi = MEAN(pindex). MATCH FILES /FILE=* /TABLE='Out\Norm_CPI.tmp' /BY one2. EXECUTE. COMPUTE CPI = pindex / meanpi . EXECUTE . 21 formats cpi(f8.5). DESCRIPTIVES VARIABLES=cpi /STATISTICS=MEAN . SAVE OUTFILE='Out\CPI.sav' /COMPRESSED. *************************************************. D) The final stage is to compute the consumed foods. For this purpose Section 2 of Form 3 is linked to all files, where the prices have been computed for various levels of territory where the households live. All food products are computed using one measuring unit (grams in kilograms, milliliters in liters) beforehand. ********** Estimation of consumption from section 2 of diary *******. GET FILE='DATA\F3_02.sav'. RENAME VARIABLES (code =c3 ). sort cases by c3 (a) . MATCH FILES /FILE=* /TABLE='out\GSKP_prod.sav' /BY c3. EXECUTE . sort cases by c3 (a) . IF (f3r2q5 = 3 & ltr_kg <> 1) f3r2q4 = f3r2q4 * ltr_kg. IF (f3r2q5 = 1 | f3r2q5 = 3 | f3r2q5 = 4) cons_kg = f3r2q4. IF (f3r2q5 = 2 ) cons_kg = f3r2q4/ 1000. IF ( f3r2q5 = 5) cons_kg = f3r2q4/ 1000 * ltr_kg. VARIABLE LABELS cons_kg 'quantity of products' . SORT CASES BY hh_code (A) kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\Price_for_r2.sav' /BY hh_code kod_gr. SAVE OUTFILE='Out\F320_litr_kg1.sav' /COMPRESSED. GET FILE='Out\F320_litr_kg1.sav'. SORT CASES BY hh_code (A) . MATCH FILES /FILE=* /TABLE='DATA\Basic.sav' /BY hh_code. SORT CASES BY punkt (A) kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\Price_punkt.sav' /BY punkt kod_gr . SORT CASES BY raion (A) kod_gr (A) . 22 MATCH FILES /FILE=* /TABLE='Out\Price_raion.sav' /BY raion kod_gr . SORT CASES BY kenesh (A) kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\Price_kenesh.sav' /BY kenesh kod_gr . SORT CASES BY kod_gr (A) obl_reg (A). MATCH FILES /FILE=* /TABLE='Out\price_obl_reg.sav' /BY kod_gr obl_reg . SORT CASES BY oblast (A) kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\Price_obl.sav' /BY oblast kod_gr . SORT CASES BY region (A) kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\Price_reg.sav' /BY region kod_gr . SORT CASES BY kod_gr (A) . MATCH FILES /FILE=* /TABLE='Out\price_national.sav' /BY kod_gr . SAVE OUTFILE='Out\Price_2r.sav' /COMPRESSED. *********************************. If there is no price for some product at the household level, then it is replaced with the price at the territory level starting with the settlement where this households lives. *********************************. RECODE pric_pu pric_ra pric_ke pric_o pric_r probl prnat (0=SYSMIS). EXECUTE . IF (SYSMIS(pric_hh )) pric_hh = pric_pu . IF (SYSMIS(pric_hh )) pric_hh = pric_ke . IF (SYSMIS(pric_hh )) pric_hh = pric_ra . IF (SYSMIS(pric_hh )) pric_hh = probl . IF (SYSMIS(pric_hh )) pric_hh = pric_o . IF (SYSMIS(pric_hh )) pric_hh = pric_r . IF (SYSMIS(pric_hh )) pric_hh = prnat . COMPUTE cons_2r = cons_kg * pric_hh . VARIABLE LABELS cons_2r 'Consumption in monetary terms from Section2'. SAVE OUTFILE='Out\Price_2r.sav' /COMPRESSED. AGGREGATE /OUTFILE='Out\Cons_2r.sav' /BREAK=hh_code 23 /cons_2r = SUM(cons_2r). ** As food consumption data are collected based on the diary for 14 days, the obtained consumption shall be increased by coefficient 6.5 (number of days in a quarter / 14). GET FILE='DATA\basic.sav'. MATCH FILES /FILE=* /TABLE='Out\Cons_2r.sav' /BY hh_code. RECODE cons_2r (SYSMIS=0) . COMPUTE fcons = cons_2r * 6.52. SAVE OUTFILE='Out\t_food.sav' /keep hh_code fcons /COMPRESSED. ******** For estimation of expenditures for consumption ********. GET FILE='Out\Price.sav'. DO IF (kateg = 28). Compute alcol = f3r1q7 * 6.52. ELSE IF (kateg = 29) . Compute tabaco = f3r1q7 * 6.52. ELSE. Compute othfood = f3r1q7 * 6.52. END IF . RECODE alcol tabaco othfood (SYSMIS=0) . EXECUTE . sort cases by hh_code. SAVE OUTFILE='Out\food_1r.sav' /keep hh_code alcol tabaco othfood /COMPRESSED. 2. The computation of the aggregate consumption expenditures by a household for non-food and services includes: A) Notional income from durables B) Household’s expenditures for meals outside the home C) Household’s expenditures for non-food and services D) Household’s income, except for income from the home farm. A). To compute the notional income from durables, one shall use Section 2 of Questionnaire №7 of the households survey. The methodology of computation is based on the good’s depreciation value using the logistic regression equation depending on the cost of the good and the year of manufacturing/purchase. 24 2 Durables.sps ** 2 DURABLES ************************************************. ******* Estimation of flow from owned durable goods ******. CD 'C:\Users\Sasun\Work\Kyrgyz\2021'. CD "D:\_WORK\Kyrgyz2021". GET FILE='DATA\f7_02.sav'. RENAME VARIABLES (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5= c1 c2 c3 c4 c5). COMPUTE lprice = LN(c5) . SELECT IF(c3 >= 2005). REGRESSION /DEPENDENT lprice /METHOD=ENTER c3 /SAVE PRED /OUTFILE=COVB('OUT\Coef.TMP') . get file = 'OUT\Coef.TMP'. SELECT IF(rowtype_ = 'EST'). COMPUTE one = 1 . SAVE OUTFILE = 'OUT\C.TMP' . **********************************. GET FILE='DATA\f7_02.sav'. RENAME VARIABLES (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5= c1 c2 c3 c4 c5). COMPUTE lprice = LN(c5) . SORT CASES BY c1 . SPLIT FILE SEPARATE BY c1 . REGRESSION /DEPENDENT lprice /METHOD=ENTER c3 /SAVE PRED /OUTFILE=COVB('OUT\Coef_g.TMP') . get file = 'OUT\Coef_g.TMP'. SELECT IF(rowtype_ = 'SIG' ). sort cases by c1. rename variable c3 = c3_sig. SAVE OUTFILE = 'OUT\SIG.TMP' /KEEP C1 c3_sig . get file = 'OUT\Coef_g.TMP'. SELECT IF(rowtype_ = 'EST' ). sort cases by c1. rename variable c3 = c3_est. 25 SAVE OUTFILE = 'OUT\EST.TMP' /KEEP C1 c3_est . MATCH FILES /FILE=* /TABLE='OUT\SIG.TMP' /BY c1. COMPUTE one = 1 . MATCH FILES /FILE=* /TABLE='OUT\C.TMP' /BY one. rename variable c3 = c3_all. SAVE OUTFILE = 'OUT\Znach.TMP' /KEEP c1 c3_est c3_sig c3_all . get file 'OUT\Znach.TMP'. COMPUTE a_rate = EXP(c3_est)-1 . if (c3_sig > 0.05) a_rate = EXP(c3_all)-1 . SAVE OUTFILE = 'OUT\A_rate_Durable.TMP'. GET FILE='DATA\f7_02.sav'. RENAME VARIABLES (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5= c1 c2 c3 c4 c5). sort cases by c1. MATCH FILES /FILE=* /TABLE='OUT\A_rate_Durable.TMP' /BY c1. EXECUTE. COMPUTE durable = c5 * a_rate . IF (durable < 0) durable = 0. if (c4=2020) price_new_dur=c5 . EXEC. means durable price_new_dur a_rate / cells mean min max. AGGREGATE OUTFILE='OUT\Durable.sav' /BREAK=hh_code /durable 'Durable goods'=SUM(durable) /price_new_dur 'The price of new durable good purchased in current year'=SUM(price_new_dur). GET FILE='OUT\Durable.sav'. 26 3 Income & Expenditures.sps ** 3 INCOME & EXPENDITURES ****************************************. CD 'C:\Users\Sasun\Work\Kyrgyz\2021'. CD "D:\_WORK\Kyrgyz2021". **1 ************* Expenditures for meals outside the home ******. B) To determine household’s expenditures for meals outside the home, one shall use Section 3 of Questionnaire №3 – the diary for 14 days. GET FILE='DATA\F3_03.sav'. weight off. COMPUTE teat_out = f3r3q12*6.52. AGGREGATE /OUTFILE='OUT\eat_out.sav' /BREAK=hh_code /eat_out 'Meals outside the home'= SUM(Teat_out) . **2 ********** Expenditures for non-food ******************. С) To determine household’s expenditures for non-food and services, one shall use Questionnaire №6 – quarterly. Expenditures for non-food from Section 1 of the Questionnaire Form №6 are aggregated by the good’s code and the household’s code and then are transposed to the intermediate file. GET FILE='DATA\F6_01.sav'. AGGREGATE /OUTFILE=* /BREAK=hh_code f6r1_id /xnf ‘Expenditures for non-food’ = SUM(f6r1) . CASESTOVARS /ID = hh_code /INDEX = f6r1_id /GROUPBY = VARIABLE /separator ''. variable labels xnf1 'Fabrics' /xnf2 'Clothes' /xnf3 'Shoes' /xnf4 'Items for recreation, occupation and entertainment' /xnf5 'Gasoline' /xnf6 'Construction materials and bathroom fixtures' /xnf7 'Computing and office equipment' /xnf8 'TV and radio equipment' /xnf9 'Electric household appliances' /xnf10 'Vehicles' /xnf11 'Furniture' /xnf12 'Small wares' /xnf13 'Jewelry' 27 /xnf14 'Household articles' /xnf15 'Detergents and cleaning agents, household chemistry products' /xnf16 'Perfumes and cosmetics' /xnf17 'Personal care items' /xnf18 'Cooking utensils and household goods' /xnf19 'Other non-food items'. SAVE OUTFILE='TEMPS\xnf.tmp' /COMPRESSED. **3 ************* Expenditures for healthcare ***************. Expenditures for healthcare from Section 3 of Questionnaire №6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\f6_03.sav'. IF any(f6r3_id, 301,302,601,604,801,802,803) xh1 = f6r3 . IF any(f6r3_id, 303,304,341,305,306,307,308,309) xh2 = f6r3 . IF any(f6r3_id, 602,603,605,606,607,608,611,612,613) xh3 = f6r3 . EXECUTE . weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code /xh1 = SUM(xh1) /xh2 = SUM(xh2) /xh3 = SUM(xh3). variable labels xh1 'Medicines and consumables' / xh2 'Expenditures for out-patient care' / xh3 'Expenditures for in-patient care'. SAVE OUTFILE='TEMPS\xh.tmp' /COMPRESSED. **4_5 ******* Expenditures for education **********. Expenditures for education from Section 5 of Questionnaire №6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\F6_052.sav'. *IF any(f6r52_id,1,2,3,4,41,5) xe1 = f6r52 . weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code /xe1 = SUM(f6r52) . variable labels xe1 'Pre-school education'. SAVE OUTFILE='TEMPS\xe1.tmp' /COMPRESSED. GET FILE='DATA\F6_054.sav'. weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code 28 /xe3 = SUM(f6r54C3) /xe31 = SUM(f6r54C31) /xe6 = SUM(f6r54C6) /xe7 = SUM(f6r54C7) /xe8 = SUM(f6r54C8) /xe9 = SUM(f6r54C9) /xe10 = SUM(f6r54C10) /xe11 = SUM(f6r54C11). variable labels xe3 'payment for education' / xe31 'textbooks' / xe6 'library' / xe7 'tutors' / xe8 'transport' / xe9 'repairs' / xe10 'non-official payments' / xe11 'other expenditures'. SAVE OUTFILE='TEMPS\xe.tmp' /COMPRESSED. ***6_7 ******** Expenditures for housing and utility ************. Expenditures for housing and utility services from Section 2, question 1.1 and question 12 in form 6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\F6_0211.sav'. weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code /xu13 = SUM(f6r2q1C4) . variable labels xu13 'Expenditures for Fuel'. SAVE OUTFILE='TEMPS\xu1.tmp' /COMPRESSED. GET FILE='DATA\F6_02.sav'. IF f6r2q12_id=1 xu1 = f6r2q12C6 . IF f6r2q12_id=2 xu2 = f6r2q12C6 . IF f6r2q12_id=3 xu3 = f6r2q12C6 . IF f6r2q12_id=4 xu4 = f6r2q12C6 . IF f6r2q12_id=5 xu5 = f6r2q12C6 . IF any(f6r2q12_id,6,8) xu6 = f6r2q12C6 . IF f6r2q12_id=9 xu9 = f6r2q12C6 . IF any(f6r2q12_id, 7,10,11,12,13) xu10 = f6r2q12C6 . IF f6r2q12_id=14 xu14 = f6r2q12C6 . EXECUTE . weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code /xu1 = SUM(xu1) /xu2 = SUM(xu2) /xu3 = SUM(xu3) /xu4 = SUM(xu4) /xu5 = SUM(xu5) /xu6 = SUM(xu6) /xu9 = SUM(xu9) /xu10 = SUM(xu10) 29 /xu14 = SUM(xu14). variable labels xu1 'Payment for floor space' / xu2 'Centralized heating' / xu3 'Centralized gas supply' / xu4 'Electricity' / xu5 'Hot water' / xu6 'Cold water, sewage' / xu9 'Waste collection' / xu10 'Other services' / xu14 'Housing rent'. RECODE xu1 xu14 (SYSMIS=0). EXECUTE. SAVE OUTFILE='TEMPS\xu.tmp' /COMPRESSED. **8 ******** Expenditures for transport ************. Expenditures for transport from Section 4 in form 6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\F6_04.sav'. *COMPUTE xu11 = SUM(q2r1, q2r2, q2r3, q2r4, q2r5, q2r6, q2r7) . *EXECUTE . AGGREGATE /OUTFILE='TEMPS\xu11.tmp' /BREAK=hh_code /xu11 'Expenditures for transport’ = SUM(f6r4). **9 ******** Other expenditures ************. Other expenditures (taxes, alimony, assistance to relatives, purchase of real estate, grain, bank deposits, loans, etc.) from Section 6 in form 6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\F6_06.sav'. IF any(f6r6_id,1501,1701,1901,2101,2301,3501) xtax = f6r6 . *COMPUTE xtax = SUM( q15,q17,q19,q21,q23,q35) . *COMPUTE xtax = SUM( q15,q17) . IF f6r6_id=2701 xalim = f6r6 . *COMPUTE xalim = q27 . IF f6r6_id=2901 xhelp = f6r6 . *COMPUTE xhelp = q29 . IF any(f6r6_id,601, 602, 603,604,605,2501,3101,3301) xother = f6r6 . *COMPUTE xother = SUM( q6r1, q6r2, q6r3, q6r4, q6r4_1, q6r4_2, q6r4_3, q6r5,q25,q31,q33). *COMPUTE xother = SUM( q6r1, q6r2, q6r3, q6r4, q6r4_1, q6r4_2, q6r4_3, q6r5,q25,q31). IF any(f6r6_id,201,202,203,204) xbuild = f6r6 . *COMPUTE xbuild = SUM(q2r1,q2r2,q2r3,q2r4) . EXECUTE . AGGREGATE /OUTFILE='TEMPS\Other.tmp' /BREAK=hh_code 30 /xtax = SUM(xtax) /xother= SUM(xother) /xalim = SUM(xalim) /xbuild = SUM(xbuild) /xhelp = SUM(xhelp). **10 ******** Expenditures for services ************. Expenditures for services from Section 6, question 6.1 in form 6 are aggregated by the household code and recorded in the intermediate file. GET FILE='DATA\f6_61.sav'. *COMPUTE xserv = c3_4_5 . AGGREGATE /OUTFILE='TEMPS\xserv.tmp' /BREAK=hh_code /xserv = SUM(f6r61). **11_12 ********* Expenditures on personal farm ************. GET FILE='DATA\F6_07.sav'. *COMPUTE xa1 = SUM( q3r4,q3r5) . IF any(f6r7_id,3004,3005) xa1 = f6r7 . *COMPUTE xa2= SUM( q3r7,q3r8) . IF any(f6r7_id,3007,3008) xa2 = f6r7 . *COMPUTE xa3 = SUM(q3r1,q3r2,q3r3,q3r6,q3r9,q3r10,q3r11,q3r12,q3r13, q3r13_1,q3r14) . IF any(f6r7_id,3001,3002,3003,3006,3009,3010,3011,3012,3013,3131,3014) xa3 = f6r7 . EXECUTE . weight off. AGGREGATE /OUTFILE='TEMPS\xac.tmp' /BREAK=hh_code /xa1 'Expenditures on seeds and fertilizers' =SUM(xa1) /xa2 'Taxes for private household plots crop production' =SUM(xa2) /xa3 'Production services private household plots crop production' = SUM(xa3). GET FILE='DATA\F6_07.sav'. *COMPUTE xa5= SUM( q14r1,q14r11) . IF any(f6r7_id,14001,14011) xa5 = f6r7 . *COMPUTE xa7 = SUM( q14r2,q14r3,q14r5,q14r6,q14r7,q14r8,q14r9,q14r111, q14r112,q14r113,q14r12). IF any(f6r7_id,14002,14003,14005,14006,14007,14008,14009,14111,14112, 14113,14012) xa7 = f6r7 . EXECUTE . weight off. AGGREGATE /OUTFILE='TEMPS\xal2.tmp' /BREAK=hh_code 31 /xa5 'Purchase of feed and pharmaceuticals' = SUM(xa5) /xa7 'Production services household animal husbandry' = SUM(xa7). GET FILE='DATA\F6_713.sav'. *COMPUTE xa4 = f6r7q13A6. weight off. AGGREGATE /OUTFILE='TEMPS\xal1.tmp' /BREAK=hh_code /xa4 'Purchase or livestock, poultry' = SUM(f6r7q13A6). **13 ************** INCOME *******************************. D) Income of the household, except for income from the home farm, from Section 8 in form 6 is aggregated by the household code and recorded in the intermediate file by income items. GET FILE='DATA\F6_08.sav'. RENAME VARIABLES (f6r8_id f6r8=c1 c2_3_4). do if (c1 = '1' or c1 = '2' or c1 = '3' or c1 = '3.1'). compute y1 = c2_3_4 . else if (c1 = '4'). compute y3 = c2_3_4 . else if (c1 = '5'). compute y5 = c2_3_4 . else if (c1 = '6' ). compute y2 = c2_3_4 . else if (c1 = '7'). compute y41 = c2_3_4 . else if (c1 = '8'). compute y42 = c2_3_4 . else if (c1 = '9'). compute y46 = c2_3_4 . else if (c1 = '10' or c1 = '12.1'). compute y43 = c2_3_4 . else if (c1 = '11' or c1 = '12.2' or c1 = '12.3'). compute y44 = c2_3_4 . else if (c1 = '13' ). compute y45 = c2_3_4 . else if (c1 = '14' ). compute y46 = c2_3_4 . else if (c1 >= '15' and c1 <= '22' or c1 = '21.1' or c1 = '15.1' ). compute y10 = c2_3_4 . else if (c1 >= '23' and c1 <= '26' or c1 = '25.1' ). compute y6 = c2_3_4 . else if (c1 = '27' ). compute y7 = c2_3_4 . else if (c1 >= '28' and c1 <= '30' or c1 = '32' ). compute y9 = c2_3_4 . else if (c1 = '31' ). compute y8 = c2_3_4 . else if (c1 = '33' ). compute y11 = c2_3_4 . else if (c1 >= '34' and c1 <= '37' ). compute y12 = c2_3_4 . else if (c1 = '41' ). compute y13 = c2_3_4 . end if. 32 EXECUTE. weight off. AGGREGATE /OUTFILE=* /BREAK=hh_code /y1 = SUM(y1) /y2 = SUM(y2) /y3 = SUM(y3) /y41 = SUM(y41) /y42 = SUM(y42) /y43 = SUM(y43) /y44 = SUM(y44) /y45 = SUM(y45) /y46 = SUM(y46) /y5 = SUM(y5) /y6 = SUM(y6) /y7 = SUM(y7) /y8 = SUM(y8) /y9 = SUM(y9) /y10 = SUM(y10) /y11 = SUM(y11) /y12 = SUM(y12) /y13 = SUM(y13) . VARIABLE LABELS y1 'Wage' / y2 'Pension' / y3 'Educational allowance' / y41 'Social insurance benefit' / y42 'Monthly social benefit' / y43 'Lump-sum benefit' / y44 'Single monthly benefit to poor families and citizens' / y45 'Unemployment benefit' / y46 'Other benefits' / y5 'Alimony' / y6 'Income from leasing property or real estate' / y7 'Dividends from shares and other securities' / y8 'Income from sales of personal property or household effects' / y9 'Income from sales of real estate ' / y10 'A subsidy or financial assistance from the local government' / y11 'Financial assistance from relatives or acquaintances' / y12 'Savings' / y13 'Other'. SAVE OUTFILE='TEMPS\y.tmp' /COMPRESSED. **14 ****************** Expenditures for food *************. Е) Expenditures for food from the file generated when computing prices from Form 3 are aggregated by household code and food code, and then transposed to the intermediate file. GET FILE='OUT\Price_2r.sav'. COMPUTE fcons = cons_2r . SELECT IF(expfact > 0). AGGREGATE /OUTFILE='TEMPS\cons1.tmp' /BREAK=hh_code kateg /fcons14 = SUM(fcons). GET FILE='TEMPS\cons1.tmp'. RECODE kateg (1 thru 5=1) (6 thru 10=2) (11 thru 17=3) (30 thru 32=4) (18 thru 29=Copy) INTO KATEG12 . RECODE KATEG12 (1=1) (2=2) (3 thru 4=3) (18=4) (19=5) (20=6) (21=7) (22=8) (23=9) (24=10) (25=11) (26=12) (27=13) (28=14) (29=15). EXECUTE . 33 compute xf = fcons14 * 6.52. *** 4 quarters 14 days in each **. AGGREGATE /OUTFILE='TEMPS\tfood.tmp' /BREAK=hh_code /xf = SUM(xf). AGGREGATE /OUTFILE=* /BREAK=hh_code kateg12 /xf = SUM(xf). ********** - > restructure *******. SELECT IF(kateg12 > 0). FORMATS kateg12(f3.0). SORT CASES BY hh_code kateg12 . CASESTOVARS /ID = hh_code /INDEX = kateg12 /GROUPBY = VARIABLE /separator ''. variable labels xf1 'Bread and bread products' /xf2 'Milk and dairy products' /xf3 'Meat and meat products' /xf4 'Fish and fish products' /xf5 'Oil, margarine and other fats' /xf6 'Eggs' /xf7 'Potato' /xf8 'Vegetables and melons' /xf9 'Fruit and berries' /xf10 'Sugar' /xf11 'Tea, coffee, cocoa' /xf12 'Non-alcoholic drinks' /xf13 'Other food' /xf14 'Alcoholic drinks' /xf15 'Tobacco'. SAVE OUTFILE='TEMPS\xf.tmp' /COMPRESSED. ******************************************************************. ******* Merging all generated intermediate files in one ********. match files /file 'TEMPS\xf.tmp' /file 'TEMPS\xnf.tmp' /file 'TEMPS\xh.tmp' /file 'TEMPS\xe.tmp' /file 'TEMPS\xe1.tmp' /file 'TEMPS\xu1.tmp' /file 'TEMPS\xu.tmp' /file 'TEMPS\xu11.tmp' /file 'TEMPS\xac.tmp' /file 'TEMPS\xal1.tmp' /file 'TEMPS\xal2.tmp' 34 /file 'OUT\eat_out.sav' /rename (eat_out = xeout) /file 'TEMPS\Other.tmp' /file 'TEMPS\xserv.tmp' /file 'OUT\durable.sav' /rename (durable = cdur) /file 'DATA\Basic.sav' /file 'TEMPS\y.tmp' /by hh_code. EXECUTE. VARIABLE LABELS xserv 'Payment for services' /xtax 'Taxes, dues, inspection' /xother 'Other savings_spending' /xalim 'Alimony payment' /xbuild 'Purchase property' /xhelp 'Help relatives_friends'. ************** Computation of total indicators *********. Compute xf = SUM(xf1, xf2, xf3, xf4, xf5, xf6, xf7, xf8, xf9, xf10, xf11, xf12, xf13, xf14, xf15). VARIABLE LABELS xf 'Expenditures for food' . Compute xnf = SUM(xnf1 , xnf2, xnf3, xnf4, xnf5, xnf6, xnf7, xnf8, xnf9, xnf10, xnf11, xnf12, xnf13, xnf14, xnf15, xnf16, xnf17, xnf18, xnf19). VARIABLE LABELS xnf 'Expenditures for non-food'. Compute xh = SUM(xh1, xh2, xh3). Compute xe = SUM(xe1, xe3, xe31, xe6, xe7, xe8, xe9, xe10, xe11). Compute xu = SUM(xu1, xu2, xu3, xu4, xu5, xu6, xu9, xu10, xu11, xu13). Compute xa = SUM(xa1, xa3, xa4, xa5, xa7). VARIABLE LABELS xh 'Expenditures for healthcare’ /xe 'Expenditures for на education' /xu 'Expenditures for utilities' /xa 'Expenditures for private household plot and farm' . **** Expenditures for food, including meals outside the home . COMPUTE cf = SUM(xf, xeout) . **** Expenditures for Non-food, except for the following items: -Construction materials, bathroom fixtures -Computing and office equipment -Electric household appliances -Vehicles -Furniture -Jewelry, which are not included in computations to determine poverty indicators. COMPUTE cnf = SUM(xnf1,xnf2,xnf3,xnf4,xnf5,xnf12,xnf14, xnf15,xnf16,xnf17,xnf18,xnf19) . 35 **** Total expenditures for services. COMPUTE cserv = SUM(xu,xh,xe,xother,xserv) . **** Total expenditures. COMPUTE totx = SUM(cf,cnf,cserv,cdur,xa,xtax,xalim,xhelp) . **** Total consumption expenditures, including notional income from durable goods. RECODE price_new_dur (sysmis =0). COMPUTE totc = SUM(cf,cnf,cserv,cdur) - price_new_dur. if totc<0 totc = sum (totc, price_new_dur). EXECUTE. ****** Total income. Compute toty = SUM( y1, y2, y3, y41, y42, y43, y44, y45, y46, y5, y6, y7, y8, y9, y10, y11, y12,y13). variable labels totx 'Total expenditures /totc 'Total consumption (consumer expenditures plus consumption of own produced goods)' /toty 'Total income (form 6, section 8)' . ***** Computation of general indicators per capita. COMPUTE pccy = toty / hsize. COMPUTE pcc = totc / hsize. COMPUTE pccx = totx / hsize. COMPUTE pccf = cf / hsize. variable labels cf 'Exependitures on food' /cnf 'Expenditures on non-food items' /cserv 'Expenditures on services' /pcc 'Consumption per capita daily' /pccx 'Expenditures per capita daily' /pccf 'Food consumption per capita daily' /pccy 'Income per capita daily'. *For World Bank DB. COMPUTE pccnf = cnf / hsize. COMPUTE pccdur = cdur / hsize. COMPUTE pccserv = cserv / hsize. variable labels pccserv 'Consumption expenditures on services per capita daily' /pccnf 'Consumption expenditures on non-food items per capita daily' /pccdur 'Consumption of Durable goods per capita daily'. variable labels hh_code 'Household ID' /hsize 'Household size' /Region 'North-South' /obl_reg 'Oblast+location' /stratum '1-urban,2-rural' /kv 'Quarter'. EXECUTE. 36 ******** Computation of quintiles, deciles and quartiles on consumption expenditures. *means pcc / cells mean. weight by weight. rank pcc /ntiles (10) into decilc. rank pcc /ntiles (5) into quintilc. rank pcc /ntiles (4) into quartilc. rank pccx /ntiles (10) into decilx. rank pccx /ntiles (5) into quintilx. rank pccx /ntiles (4) into quartilx. *rank pcc_mes /ntiles (5) into quintmesx. freq quartilc quintilc decilc. recode all (SYSMIS = 0). weight off. SELECT IF(expfact > 0). EXECUTE . SAVE OUTFILE='OUT\exp_inc.sav' /COMPRESSED. SAVE OUTFILE='OUT\quintilc.sav' /KEEP hh_code quintilc /COMPRESSED. 37 4 Poverty Line.sps ** POVERTY LINE ************************************************. Constructing the Poverty Line Constructing the Food Basket Composition Food is the essential need of a man. Food is computed in kind and in terms of cost, as well as its caloric value. Computation takes into account the consumed food obtained from different sources: purchased, received in exchange for work or as gift, produced at a home farm. The total consumption of each product is computed based on three parameters: in-kind, cost, caloric value in the country as a whole and by decile group computed by level of consumption expenditures. ********************* Base for BASKET ***************************. CD 'C:\Users\Sasun\Work\Kyrgyz\2021'. CD "D:\_WORK\Kyrgyz2021". GET FILE='OUT\Price_2r.sav' / keep hh_code C3 KATEG Kkal CONS_KG CONS_2R PRNAT expfact / REN ( C3 CONS_KG CONS_2R = code q v ) . SELECT IF(expfact > 0). ************DROP Alcohol, tobacco etc . select if ( KATEG <> 28 and KATEG <> 29 and KATEG <> 35). EXECUTE. ************ Food grops . RECODE kateg (1 thru 5=1) (6 thru 10=2) (11 thru 17=3) (30 thru 32=4) (18 thru 27=Copy) INTO KATEG12 . RECODE KATEG12 (1=1) (2=2) (3 thru 4=3) (18=4) (19=5) (20=6) (21=7) (22=8) (23=9) (24=10) (25=11) (26=12) (27=13) . VALUE LABELS KATEG12 1 "Bread and bakery foods" 2 "Milk and dairy produce" 3 "Meat and meat foods" 4 "Fish and fish foods" 5 "Vegetable oil, margarine and other fats" 6 "Eggs" 7 "Potatoes" 8 "Vegetables, melons and gourds" 9 "Fruits and berries" 10 "Sugar" 11 "Tea, coffee, cacao" 12 "Non-alcoholic beverages" 13 "Other food products". EXECUTE. 38 freq kateg12. sort cases by hh_code code. AGGREGATE /OUTFILE= * /BREAK=hh_code code /food_gr=first(KATEG12)/ Kkal=first(Kkal)/ q =sum(q) / v =sum (v) /price=mean(PRNAT). match files / file * / table 'OUT\exp_inc.sav' / by hh_code. EXECUTE. ******************************. *** 56days and Daily Calories (for 4 quarters /56) . COMPUTE cal = q * Kkal . EXECUTE. VARIABLE LABELS code "Food code" / food_gr "Food group" / Kkal "Calories of 1 kg" / q "Quantity" / v "Value" / cal "Calories of consumption" / price "Nationality prices" . SAVE OUTFILE 'OUT\Base_for_Basket.sav' / KEEP hh_code code food_gr Kkal q v cal price b002 oblast expfact weight hsize decilc . ******************************. The minimal set of basic food products for a poverty line food basket is determined based on the actual food consumpton of so called reference population (2-5 decile of per capita consumption). The considered target group represents 40 percent of population with an income below the average and does not include poorest 10 percent of population with the lowest consumption per capita. Liquors and tobacco are excluded from the food basket. get file 'OUT\Base_for_Basket.sav'. freq decilc. *** SELECT decilec. SELECT IF(decilc>=2 and decilc<= 5). EXECUTE. weight by expfact. freq decilc. 39 AGGREGATE OUTFILE * / break Code / quantity = sum(q) / totv = sum (V) / cal = sum (cal) /price Kkal food_gr = first ( price Kkal food_gr). COMPUTE xx=1. AGGREGATE OUTFILE * mode addvar / break xx/ totalv = sum (totv). COMPUTE valshare = totv / totalv*100. EXECUTE. tables /ftotal t 'total' /observ valshare /table FOOD_GR by valshare /stat sum ('%' ). sort cases by valshare (d). COMPUTE cumvsh = valshare. if not sysmis ( lag (cumvsh) ) cumvsh =cumvsh +lag (cumvsh). sort cases by cumvsh. ***** The poverty line food basket includes a list of food products, the cumulative cost share of which is 97 percent of the total cost of the total food basket of the reference population. *N 85. *Select if cumvsh<=90.0. Select if cumvsh<=97.0. *Select if cumvsh<=98.0. *Select if cumvsh<=99.0. EXECUTE. ******************************************. COMPUTE xx=1. AGGREGATE OUTFILE * mode addvar / break xx / totalcal = sum(cal). COMPUTE calreq=2100. *comp calreq=2230. COMPUTE c2100 =totalcal/calreq. COMPUTE q2100 =quantity/c2100 . COMPUTE val2100 = q2100 * price. COMPUTE cc2100=Q2100 * Kkal. EXECUTE. VARIABLE LABELS cc2100 'calories in 2100 basket' / q2100 'quantities in 2100 Kcal basket' / val2100 'Cost in 2100 Kcal Basket'. EXECUTE. tables /ftotal t /observ cc2100 val2100 /table FOOD_GR +t by cc2100 +val2100 /stat spct ( 'share' ) 40 /table FOOD_GR > Code +t by cc2100 +val2100 /stat spct ( 'share' ). sort cases by Code. SAVE outf 'OUT\Basket2.sav' / KEEP CODE price q2100 cc2100 val2100 . string code1 (A12). COMPUTE CODE1= code. SAVE TRANSLATE OUTFILE= 'OUT\food_basket2100_ALL_97perc.xls' /TYPE=XLS/VERSION=8 /MAP /REPLACE /KEEP CODE1 CODE price q2100 cc2100 val2100 /FIELDNAMES /CELLS=LABELS. agg outf 'OUT\foodline.sav' /break = xx / fld "Food line day 2100 KCAL/day estimated with mean prices " = sum(val2100) / N 'number of products in the 2100 Kcal / day basket' = N. get file 'OUT\foodline.sav'. tables /table fld + N /stat count. **************************. get file 'OUT\exp_inc.sav' . COMPUTE xx=1. ***In this version New Food line (fld) created based 100% and 2230ccal. match files / file * / table 'OUT\foodline.sav' / by xx. EXECUTE. sort cases by obl_reg. MATCH FILES /FILE=* /TABLE='OUT\CPI.sav' /BY obl_reg. COMPUTE pccddc = pccf /(kv * 30.42)/CPI+(pcc-pccf)/(kv * 30.42). EXECUTE. COMPUTE pcfoodd = xf / (KV* 365/12) / hsize. COMPUTE fshare1 = xf / totc. *cOMP FLD =66. COMPUTE xxx1 = fld - 0.10 * fld. COMPUTE xxx2 = fld + 0.10 * fld. *comp weightc = totc * weight. 41 *comp weightc = totc * expfact. weight by WEIGHT . *weight by expfact. COMPUTE usl =(pcfoodd >xxx1 and pcfoodd b002 BY cf [SUM] + cnf [SUM] + cserv [SUM] + totc [SUM] /CATEGORIES VARIABLES=oblast ORDER=A KEY=VALUE EMPTY=INCLUDE /CATEGORIES VARIABLES=b002 ORDER=A KEY=VALUE EMPTY=INCLUDE TOTAL=YES POSITION=BEFORE. WEIGHT BY weight . MEANS cpsc fpsc pline_dc f_linec BY oblast BY B002/CELLS MEAN COUNT. ******* Poverty depth and severity. IF (cpsc = 100) pgc = (pline_dc -pccddc ) / pline_dc . RECODE pgc (SYSMIS=0) . COMPUTE p2c = pgc ** 2 . IF (fpsc = 100) fpgc = (f_linec-pccddc ) / f_linec . RECODE fpgc (SYSMIS=0) . COMPUTE fp2c = fpgc ** 2 . Variable labels pgc 'Poverty depth – consumption'. Variable labels p2c 'Poverty severity - consumption'. Variable labels fpgc 'Extreme poverty depth - consumption'. Variable labels fp2c 'Extreme poverty severity – consumption '. SAVE OUTFILE='POVERTY.sav' /COMPRESSED. 44 ANNEX B. STATA do files translated from original SPSS syntax 1 Prices.do ** 1 PRICES ************************************************. set more off set mem 5000M clear capture log close global path "D:\_WORK\Kyrgyz2021\" *global path "C:\Users\Sasun\Work\Kyrgyz\2021" global data "${path}\data" global do "${path}\do" global log "${path}\log" cd "${path}" *log using "OUTPUT_1", text replace ********* estimation of personal consumption in KG from section 1 Form 3 ******** use DATA\f3_01 , clear rename code c3 sort c3 merge m:m c3 using "OUT\GSKP_prod" tab1 _merge ,miss keep if (_merge == 3) drop _m* rename (*), lower replace f3r1q5 = f3r1q5 * ltr_kg if (f3r1q6 == 3 & ltr_kg != 1) gen cons_kg = f3r1q5 if (f3r1q6 == 1 | f3r1q6 == 3 | f3r1q6 == 4) replace cons_kg = f3r1q5/ 1000 if (f3r1q6 == 2 ) replace cons_kg = f3r1q5/ 1000 * ltr_kg if (f3r1q6 == 5) gen price_f = f3r1q7 / cons_kg 45 lab var price_f "цена за единицу продукции" sort hh_code merge m:m hh_code using "DATA\basic" tab1 _merge ,miss keep if (_merge == 3) drop _m* rename (*), lower save "OUT\Price", replace ************** Estimation of median prices ******************* use "OUT\Price" , clear *gen w = expfact *gen w = expfact * cons_kg preserve collapse (median)probl=price_f (count)n1=hh_code [aw=expfact], by (kod_gr obl_reg ) save "OUT\price_obl_reg" , replace restore preserve collapse (median)prnat=price_f (sum)sumpr=f3r1q7 (count)n1=hh_code [iw=expfact], by (kod_gr) save "OUT\price_national" , replace restore sort kod_gr merge m:m kod_gr using "OUT\price_national" tab1 _merge ,miss keep if (_merge == 3) drop _m* ******** deleting extreme values in prices ( unit values) replace price_f=. if (price_f < prnat * 0.1 | price_f > prnat * 10) ******* checking missing values in price_f 46 tab1 price_f if price_f==. , miss tabstat price_f [aw=expfact], statistics( min max mean sum) ************** Estimation of prices on various levels ***************** preserve collapse (mean)pric_pu=price_f [iw=expfact], by (punkt kod_gr) lab var pric_pu "price in a settlement" save "OUT\price_punkt" , replace restore preserve collapse (mean)pric_ra=price_f [iw=expfact], by (raion kod_gr) lab var pric_ra "price in the rayon" save "OUT\price_raion" , replace restore preserve collapse (mean)pric_ke=price_f [iw=expfact], by (kenesh kod_gr) lab var pric_ke "price in in a kenesh" save "OUT\price_kenesh" , replace restore preserve collapse (mean)pric_o=price_f [iw=expfact], by (oblast kod_gr) lab var pric_o "price in oblast" save "OUT\price_obl" , replace restore preserve collapse (mean)pric_r=price_f [iw=expfact], by (region kod_gr) lab var pric_r "price in the region" save "OUT\price_reg" , replace restore preserve collapse (mean)pric_hh=price_f [iw=expfact], by (hh_code kod_gr) 47 lab var pric_hh "price for a household" save "OUT\price_for_r2" , replace restore save "OUT\Price" , replace ************ calculation of index use "OUT\Price_obl_reg" , clear merge m:m kod_gr using "OUT\price_national" tab1 _merge ,miss keep if (_merge == 3) drop _m* gen pi = probl / prnat save "OUT\sumprw" , replace collapse (mean)pindex=pi [iw=sumpr], by (obl_reg) save "OUT\cpi_temp" , replace gen one2 = 1 preserve collapse (mean)meanpi=pindex , by (one2) save "OUT\norm_cpi_temp" , replace restore merge m:m one2 using "OUT\norm_cpi_temp" tab1 _merge ,miss keep if (_merge == 3) drop _m* gen cpi = pindex / meanpi format cpi %8.5f sum cpi 48 save "OUT\CPI" , replace ************* estimation of consumption from section 2 of diary ************* use "DATA\F3_02" , clear rename code c3 sort c3 merge m:m c3 using "OUT\GSKP_prod" tab1 _merge ,miss keep if (_merge == 3) drop _m* rename (*), lower replace f3r2q4 = f3r2q4 * ltr_kg if (f3r2q5 == 3 & ltr_kg !=1) gen cons_kg = f3r2q4 if (f3r2q5 == 1 | f3r2q5 == 3 | f3r2q5 == 4) replace cons_kg = f3r2q4/ 1000 if (f3r2q5 == 2 ) replace cons_kg = f3r2q4/ 1000 * ltr_kg if (f3r2q5 == 5) lab var cons_kg "quantity of products" sort hh_code kod_gr merge m:m hh_code kod_gr using "OUT\Price_for_r2" tab1 _merge ,miss keep if (_merge != 2) drop _m* rename (*), lower save "OUT\F320_litr_kg1", replace *********************** use "OUT\F320_litr_kg1" , clear sort hh_code merge m:m hh_code using "DATA\Basic" tab1 _merge ,miss 49 keep if (_merge != 2) drop _m* rename (*), lower sort punkt kod_gr merge m:m punkt kod_gr using "OUT\Price_punkt" tab1 _merge ,miss keep if (_merge != 2) drop _m* sort raion kod_gr merge m:m raion kod_gr using "OUT\Price_raion" tab1 _merge ,miss keep if (_merge != 2) drop _m* sort kenesh kod_gr merge m:m kenesh kod_gr using "OUT\Price_kenesh" tab1 _merge ,miss keep if (_merge != 2) drop _m* sort obl_reg kod_gr merge m:m obl_reg kod_gr using "OUT\Price_obl_reg" tab1 _merge ,miss keep if (_merge != 2) drop _m* sort oblast kod_gr merge m:m oblast kod_gr using "OUT\Price_obl" tab1 _merge ,miss keep if (_merge != 2) drop _m* sort region kod_gr merge m:m region kod_gr using "OUT\Price_reg" tab1 _merge ,miss 50 keep if (_merge != 2) drop _m* sort kod_gr merge m:m kod_gr using "OUT\price_national" tab1 _merge ,miss keep if (_merge != 2) drop _m* recode pric_pu pric_ra pric_ke pric_o pric_r probl prnat (0=.) replace pric_hh = pric_pu if pric_hh==. replace pric_hh = pric_ke if pric_hh==. replace pric_hh = pric_ra if pric_hh==. replace pric_hh = probl if pric_hh==. replace pric_hh = pric_o if pric_hh==. replace pric_hh = pric_r if pric_hh==. replace pric_hh = prnat if pric_hh==. gen cons_2r = cons_kg * pric_hh lab var cons_2r "Consumption in monetary terms from Section 2" save "OUT\Price_2r", replace collapse (sum)cons_2r=cons_2r , by (hh_code) save "OUT\Cons_2r" , replace use "DATA\basic" , clear rename (*), lower merge m:m hh_code using "OUT\Cons_2r" tab1 _merge ,miss keep if (_merge != 2) drop _m* recode cons_2r (.=0) gen fcons = cons_2r * 6.52 51 keep hh_code fcons save "OUT\t_food" , replace *********** for estimation of expenditures for consumption ********** use "OUT\Price" , clear gen alcol = f3r1q7 * 6.52 if kateg == 28 gen tabaco = f3r1q7 * 6.52 if kateg == 29 gen othfood = f3r1q7 * 6.52 if (kateg != 28 & kateg != 29) recode alcol tabaco othfood (.=0) keep hh_code alcol tabaco othfood sort hh_code save "OUT\food_1r" , replace *log close 52 2 Durables.do ** 2 DURABLES ************************************************. set more off set mem 5000M clear capture log close global path "D:\_WORK\Kyrgyz2021\" *global path "C:\Users\Sasun\Work\Kyrgyz\2021" global data "${path}\data" global do "${path}\do" global log "${path}\log" cd "${path}" *log using "OUTPUT_2", text replace ****** Estimation of flow from owned durable goods ****** use "DATA\f7_02" , clear rename (*), lower rename (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5) (c1 c2 c3 c4 c5) gen lprice = ln(c5) keep if (c3 >= 2005) regress lprice c3 matrix list r(table) gen CONST_all = r(table)[1,2] gen c3_all = r(table)[1,1] gen one =1 keep c3_all one keep if _n==1 53 save C.tmp , replace use C.tmp ************** use "DATA\f7_02" , clear rename (*), lower rename (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5) (c1 c2 c3 c4 c5) levelsof c1 display `r(levels)' foreach i in `r(levels)' { preserve keep if c1==`i' gen lprice = ln(c5) regress lprice c3 matrix list r(table) gen c3_sig = r(table)[4,1] gen c3_est = r(table)[1,1] keep c1 c3_sig c3_est keep if _n==1 capture append using coef_g.tmp save coef_g.tmp , replace restore } use coef_g.tmp , clear gen one=1 sort c1 merge m:m one using C.tmp tab1 _merge ,miss keep if (_merge == 3) drop _m* one save Znach.tmp , replace 54 erase coef_g.tmp ********************** use Znach.tmp , clear gen a_rate = exp(c3_est)-1 replace a_rate = exp(c3_all)-1 if (c3_sig > 0.05 & c3_sig!=. ) save "A_rate_Durable.tmp" , replace use "DATA\f7_02" , clear rename (*), lower rename (f7r2q1 f7r2q2 f7r2q3 f7r2q4 f7r2q5) (c1 c2 c3 c4 c5) sort c1 merge m:m c1 using "A_rate_Durable.tmp" tab1 _merge ,miss keep if (_merge == 3) drop _m* gen durable = c5 * a_rate replace durable = 0 if durable<0 gen price_new_dur = c5 if c4==2020 sum durable price_new_dur a_rate collapse (sum) durable price_new_dur , by(hh_code) lab var durable "Durable goods" lab var price_new_dur "The price of new durable good purchased in current year" recode price_new_dur (0=.) save "OUT\Durable" , replace *log close 55 3 Income & Expenditures.do ** 3 INCOME & EXPENDITURES **************************************. set more off set mem 5000M clear capture log close global path "D:\_WORK\Kyrgyz2021\" *global path "C:\Users\Sasun\Work\Kyrgyz\2021" global data "${path}\data" global do "${path}\do" global log "${path}\log" cd "${path}" *log using "OUTPUT_3", text replace **1 ************* Expenditures for meals outside the home ****** use DATA\F3_03 , clear rename (*), lower gen teat_out = f3r3q12*6.52 collapse (sum) eat_out = teat_out , by(hh_code) label var eat_out "Meals outside the home" save "OUT\eat_out" , replace **2 ********** Expenditures for non-food ****************** use DATA\F6_01 , clear rename (*), lower collapse (sum) xnf = f6r1 , by(hh_code f6r1_id) label var xnf "Expenditures for non-food" reshape wide xnf, i(hh_code) j(f6r1_id) 56 label variable xnf1 "Fabrics" label variable xnf2 "Clothes" label variable xnf3 "Shoes" label variable xnf4 "Items for recreation, occupation and entertainment" label variable xnf5 "Gasoline" label variable xnf6 "Construction materials and bathroom fixtures" label variable xnf7 "Computing and office equipment" label variable xnf8 "TV and radio equipment" label variable xnf9 "Electric household appliances" label variable xnf10 "Vehicles" label variable xnf11 "Furniture" label variable xnf12 "Small wares" label variable xnf13 "Jewelry" label variable xnf14 "Household articles" label variable xnf15 "Detergents and cleaning agents, household chemistry products" label variable xnf16 "Perfumes and cosmetics" label variable xnf17 "Personal care items" label variable xnf18 "Cooking utensils and household goods" label variable xnf19 "Other non-food items" save xnf.tmp , replace **3 ************* Expenditures for healthcare *************** use DATA\f6_03,replace rename (*), lower generate xh1 = f6r3 if inlist(f6r3_id, 301,302,601,604,801,802,803) generate xh2 = f6r3 if inlist(f6r3_id, 303,304,341,305,306,307,308,309) generate xh3 = f6r3 if inlist(f6r3_id, 602,603,605,606,607,608,611,612,613) collapse (sum) xh1 xh2 xh3 , by(hh_code) label var xh1 "Medicines and consumables" label var xh2 "Expenditures for out-patient care" label var xh3 "Expenditures for in-patient care" save xh.tmp , replace 57 **4_5 ******* Expenditures for education ********** use "DATA\F6_052" , clear rename (*), lower *gen xe1 = f6r52 if inlist(f6r52_id,1,2,3,4,41,5) collapse (sum) xe1 =f6r52 , by(hh_code) label variable xe1 "Pre-school education" save xe1.tmp,replace ************** use "DATA\F6_054" , clear rename (*), lower collapse (sum) xe3 = f6r54c3 (sum) xe31 = f6r54c31 (sum) xe6 = f6r54c6 (sum) xe7 = f6r54c7 /// (sum) xe8 = f6r54c8 (sum) xe9 = f6r54c9 (sum) xe10 = f6r54c10 (sum) xe11 = f6r54c11 , by(hh_code) label variable xe3 "payment for education" label variable xe31 "textbooks" label variable xe6 "library" label variable xe7 "tutors" label variable xe8 "transport" label variable xe9 "repairs" label variable xe10 "non-official payments" label variable xe11 "other expenditures" save xe.tmp,replace ***6_7 ******** Expenditures for housing and utility ************ use "DATA\F6_0211" , clear rename (*), lower 58 collapse (sum) xu13 = f6r2q1c4 , by(hh_code) label variable xu13 "Expenditures for Fuel" save xu1.tmp,replace ************ use DATA\f6_02 , clear rename (*), lower generate xu1 = f6r2q12c6 if f6r2q12_id==1 generate xu2 = f6r2q12c6 if f6r2q12_id==2 generate xu3 = f6r2q12c6 if f6r2q12_id==3 generate xu4 = f6r2q12c6 if f6r2q12_id==4 generate xu5 = f6r2q12c6 if f6r2q12_id==5 generate xu6 = f6r2q12c6 if f6r2q12_id==6 replace xu6 = f6r2q12c6 if inlist(f6r2q12_id,6,8) generate xu9 = f6r2q12c6 if f6r2q12_id==9 generate xu10 = f6r2q12c6 if inlist(f6r2q12_id, 7,10,11,12,13) generate xu14 = f6r2q12c6 if f6r2q12_id==14 collapse (sum) xu1 xu2 xu3 xu4 xu5 xu6 xu9 xu10 xu14 , by(hh_code) label variable xu1 "Payment for floor space" label variable xu2 "Centralized heating" label variable xu3 "Centralized gas supply" label variable xu4 "Electricity" label variable xu5 "Hot water" label variable xu6 "Cold water, sewage" label variable xu9 "Waste collection" label variable xu10 "Other services" label variable xu14 "Housing rent" recode xu1-xu14 (.=0) save xu.tmp,replace 59 **8 ******** Expenditures for transport ************ use DATA\f6_04, clear rename (*), lower collapse (sum) xu11 = f6r4 , by(hh_code) label variable xu11 "Expenditures for transport" save xu11.tmp , replace **9 ******** Other expenditures ************ use DATA\f6_06, clear rename (*), lower generate xtax = f6r6 if inlist(f6r6_id,1501,1701,1901,2101,2301,3501) generate xalim = f6r6 if f6r6_id==2701 generate xhelp = f6r6 if f6r6_id==2901 generate xother = f6r6 if inlist(f6r6_id,601, 602, 603,604,605,2501,3101,3301) generate xbuild = f6r6 if inlist(f6r6_id,201,202,203,204) collapse (sum) xtax xother xalim xbuild xhelp , by(hh_code) save other.tmp, replace **10 ******** Expenditures for services ************ use DATA\f6_61, clear rename (*), lower collapse (sum) xserv=f6r61 , by(hh_code) save xserv.tmp,replace **11_12 ********* Expenditures on personal farm ************ use DATA\f6_07, clear rename (*), lower 60 generate xa1 = f6r7 if inlist(f6r7_id,3004,3005) generate xa2 = f6r7 if inlist(f6r7_id,3007,3008) generate xa3 = f6r7 if inlist (f6r7_id,3001,3002,3003,3006,3009,3010,3011,3012,3013,3131, 3014) collapse (sum) xa1 xa2 xa3 , by (hh_code) label variable xa1 "Expenditures on seeds and fertilizers" label variable xa2 "Taxes for private household plots crop production" label variable xa3 "Production services private household plots crop production" save xac.tmp,replace ************* use DATA\f6_07, clear rename (*), lower generate xa5 = f6r7 if inlist(f6r7_id,14001,14011) generate xa7 = f6r7 if inlist(f6r7_id,14002,14003,14005,14006,14007,14008,14009,14111,14112,14113,14012) collapse (sum) xa5 xa7 , by(hh_code) label variable xa5 "Purchase of feed and pharmaceuticals" label variable xa7 "Production services household animal husbandry" save xal2.tmp,replace ************** use DATA\f6_713, clear rename (*), lower collapse (sum) xa4 =f6r7q13a6 , by(hh_code) label variable xa4 "Purchase or livestock, poultry" save xal1.tmp,replace **13 ****************** INCOME ******************************* 61 use DATA\f6_08, clear rename (*), lower rename (f6r8_id f6r8 ) (c1 c2_3_4) generate y1 = c2_3_4 if inlist(c1, "1" , "2" , "3" , "3.1") generate y3 = c2_3_4 if c1 == "4" generate y5 = c2_3_4 if c1 == "5" generate y2 = c2_3_4 if c1 == "6" generate y41 = c2_3_4 if c1 == "7" generate y42 = c2_3_4 if c1 == "8" generate y46 = c2_3_4 if c1 == "9" generate y43 = c2_3_4 if c1 == "10" | c1 == "12.1" generate y44 = c2_3_4 if c1 == "11" | c1 == "12.2" | c1 == "12.3" generate y45 = c2_3_4 if c1 == "13" replace y46 = c2_3_4 if c1 == "14" generate y10 = c2_3_4 if c1 >= "15" & c1 <= "22" | c1 == "21.1" | c1 == "15.1" generate y6 = c2_3_4 if c1 >= "23" & c1 <= "26" | c1== "25.1" generate y7 = c2_3_4 if c1 == "27" generate y9 = c2_3_4 if c1 >= "28" & c1 <= "30" | c1 == "32" generate y8 = c2_3_4 if c1 == "31" generate y11 = c2_3_4 if c1 == "33" generate y12 = c2_3_4 if c1 >= "34" & c1 <= "37" generate y13 = c2_3_4 if c1 == "41" collapse (sum) y1 y2 y3 y41 y42 y43 y44 y45 y46 y5 y6 y7 y8 y9 y10 y11 y12 y13 , by (hh_code) label variable y1 "Wage" label variable y2 "Pension" label variable y3 "Educational allowance" label variable y41 "Social insurance benefit" label variable y42 "Monthly social benefit" label variable y43 "Lump-sum benefit" label variable y44 "Single monthly benefit to poor families and citizens" label variable y45 "Unemployment benefit" label variable y46 "Other benefits" label variable y5 "Alimony" 62 label variable y6 "Income from leasing property or real estate" label variable y7 "Dividends from shares and other securities" label variable y8 "Income from sales of personal property or household effects" label variable y9 "Income from sales of real estate" label variable y10 "A subsidy or financial assistance from the local government" label variable y11 "Financial assistance from relatives or acquaintances" label variable y12 "Savings" label variable y13 "Other" save y.tmp,replace **14 ****************** Expenditures for food ************* use "OUT\Price_2r",clear generate fcons = cons_2r keep if expfact > 0 collapse (sum) fcons14 = fcons, by(hh_code kateg) save cons1.tmp,replace ********************************************************* use cons1.tmp,clear recode kateg (1/5=1) (6/10=2) (11/17=3) (30/32=4) , gen(kateg12) copyrest recode kateg12 (1=1) (2=2) (3 4=3) (18=4) (19=5) (20=6) (21=7) (22=8) (23=9) /// (24=10) (25=11) (26=12) (27=13) (28=14) (29=15) generate xf = fcons14 * 6.52 *** 4 quarters 14 days in each ** preserve collapse (sum) xf , by(hh_code) 63 save tfood.tmp,replace restore collapse (sum) xf , by(hh_code kateg12) ******************* - > restructure ******* keep if (kateg12 > 0) format kateg12 %3.0f sort hh_code kateg12 reshape wide xf , i(hh_code) j(kateg12) label variable xf1 "Bread and bread products" label variable xf2 "Milk and dairy products" label variable xf3 "Meat and meat products" label variable xf4 "Fish and fish products" label variable xf5 "Oil, margarine and other fats" label variable xf6 "Eggs" label variable xf7 "Potato" label variable xf8 "Vegetables and melons" label variable xf9 "Fruit and berries" label variable xf10 "Sugar" label variable xf11 "Tea, coffee, cocoa" label variable xf12 "Non-alcoholic drinks" label variable xf13 "Other food" label variable xf14 "Alcoholic drinks" label variable xf15 "Tobacco" save xf.tmp,replace ****************************************************************** ************* Merging all generated intermediate files in one ************* use DATA\basic,clear rename (*), lower 64 merge 1:1 hh_code using xf.tmp ,nogenerate merge 1:1 hh_code using xnf.tmp ,nogenerate merge 1:1 hh_code using xh.tmp ,nogenerate merge 1:1 hh_code using xe.tmp ,nogenerate merge 1:1 hh_code using xe1.tmp ,nogenerate merge 1:1 hh_code using xu1.tmp ,nogenerate merge 1:1 hh_code using xu.tmp ,nogenerate merge 1:1 hh_code using xu11.tmp ,nogenerate merge 1:1 hh_code using xac.tmp ,nogenerate merge 1:1 hh_code using xal1.tmp ,nogenerate merge 1:1 hh_code using xal2.tmp ,nogenerate merge 1:1 hh_code using out\eat_out ,nogenerate merge 1:1 hh_code using other.tmp ,nogenerate merge 1:1 hh_code using xserv.tmp ,nogenerate merge 1:1 hh_code using out\durable ,nogenerate merge 1:1 hh_code using y.tmp ,nogenerate rename (eat_out durable ) (xeout cdur) label variable xserv "Payment for services'" label variable xtax "Taxes, dues, inspection" label variable xother "Other savings_spending" label variable xalim "Alimony payment" label variable xbuild "Purchase property" label variable xhelp "Help relatives_friends" egen xf = rsum(xf1 xf2 xf3 xf4 xf5 xf6 xf7 xf8 xf9 xf10 xf11 xf12 xf13 xf14 xf15) egen xnf = rsum(xnf1 xnf2 xnf3 xnf4 xnf5 xnf6 xnf7 xnf8 xnf9 xnf10 xnf11 xnf12 xnf13 xnf14 xnf15 xnf16 xnf17 xnf18 xnf19) label variable xf "Expenditures for food" label variable xnf "Expenditures for non-food" egen xh = rsum(xh1 xh2 xh3) egen xe = rsum(xe1 xe3 xe31 xe6 xe7 xe8 xe9 xe10 xe11) egen xu = rsum(xu1 xu2 xu3 xu4 xu5 xu6 xu9 xu10 xu11 xu13) egen xa = rsum(xa1 xa3 xa4 xa5 xa7) 65 label variable xh "Expenditures for healthcare" label variable xe "Expenditures for на education" label variable xu "Expenditures for utilities" label variable xa "Expenditures for private household plot and farm" egen cf = rsum(xf xeout) egen cnf = rsum(xnf1 xnf2 xnf3 xnf4 xnf5 xnf12 xnf14 xnf15 xnf16 xnf17 xnf18 xnf19) egen cserv = rsum(xu xh xe xother xserv) egen totx = rsum(cf cnf cserv cdur xa xtax xalim xhelp) recode price_new_dur (. =0) egen totc = rsum(cf cnf cserv cdur) replace totc = totc - price_new_dur replace totc = totc+price_new_dur if totc<0 egen toty = rsum( y1 y2 y3 y41 y42 y43 y44 y45 y46 y5 y6 y7 y8 y9 y10 y11 y12 y13) label variable totx "Total expenditures" label variable totc "Total consumption (consumer expenditures plus consumption of own produced goods)" label variable toty "Total income (form 6, section 8)" generate pccy = toty / hsize generate pcc = totc / hsize generate pccx = totx / hsize generate pccf = cf / hsize label variable cf "Exependitures on food" label variable cnf "Exependitures on non-food" label variable cserv "Expenditures on services" label variable pcc "Consumption per capita daily" label variable pccx "Expenditures per capita daily" label variable pccf "Food consumption per capita daily" label variable pccy "Income per capita daily" *For WB 66 generate pccnf = cnf / hsize generate pccdur = cdur / hsize generate pccserv = cserv / hsize label variable pccserv "Consumption expenditures on services per capita daily" label variable pccnf "Consumption expenditures on non-food items per capita daily" label variable pccdur "Consumption of Durable goods per capita daily" label variable hh_code "Household ID" label variable hsize "Household size" label variable region "North-South" label variable obl_reg "Oblast+location" label variable stratum "1-urban,2-rural" label variable kv "Quarter" ******** Computation of quintiles, deciles and quartiles on consumption expenditures *sum pcc xtile decilc =pcc [aw=weight] ,nq(10) xtile quintilc=pcc [aw=weight] ,nq(5) xtile quartilc=pcc [aw=weight] ,nq(4) xtile decilхc =pccx [aw=weight] ,nq(10) xtile quintilx=pccx [aw=weight] ,nq(5) xtile quartilx=pccx [aw=weight] ,nq(4) tab1 quartilc quintilc decilc [aw=weight] , miss recode * (. = 0) keep if (expfact > 0 ) save "OUT\exp_inc",replace keep hh_code quintilc save "OUT\quintilc",replace *log close 67 4 Poverty Line.do ** POVERTY LINE ************************************************. set more off set mem 5000M clear capture log close global path "D:\_WORK\Kyrgyz2021\" *global path "C:\Users\Sasun\Work\Kyrgyz\2021" global data "${path}\data" global do "${path}\do" global log "${path}\log" cd "${path}" *log using "OUTPUT_4", text replace ********************* Base for BASKET *************************** use "OUT\Price_2r" , clear keep hh_code c3 kateg kkal cons_kg cons_2r prnat expfact rename ( c3 cons_kg cons_2r ) ( code q v ) keep if expfact > 0 ************ DROP alcool, tobacco etc keep if ( kateg !=28 & kateg != 29 & kateg != 35) ************ Food grops recode kateg (1/5=1) (6/10=2) (11/17=3) (30/32=4) , gen(kateg12) copyrest recode kateg12 (1=1)(2=2)(3 4=3)(18=4)(19=5)(20=6)(21=7)(22=8)(23=9)(24=10)(25=11)(26=12)(27=13) label define kateg12 /// 1 "Bread and bakery foods" 2 "Milk and dairy produce" 3 "Meat and meat foods" 4 "Fish and fish foods" /// 5 "Vegetable oil, margarine and other fats" 6 "Eggs" 7 "Potatoes" 8 "Vegetables, melons and gourds" /// 68 9 "Fruits and berries" 10 "Sugar" 11 "Tea, coffee, cacao" 12 "Non-alcoholic beverages" 13 "Other food products" lab val kateg12 kateg12 tab1 kateg12 sort hh_code code collapse (first)food_gr=kateg12 (first)kkal (sum) q v (mean)price= prnat, by (hh_code code) merge m:m hh_code using "OUT\exp_inc" tab1 _merge ,miss keep if (_merge == 3) drop _m* label define food_gr /// 1 "Bread and bakery foods" 2 "Milk and dairy produce" 3 "Meat and meat foods" 4 "Fish and fish foods" /// 5 "Vegetable oil, margarine and other fats" 6 "Eggs" 7 "Potatoes" 8 "Vegetables, melons and gourds" /// 9 "Fruits and berries" 10 "Sugar" 11 "Tea, coffee, cacao" 12 "Non-alcoholic beverages" 13 "Other food products" lab val food_gr food_gr tab1 food_gr ************************** 56 days and Daily Calories (for 4 quarters /56) gen cal = q * kkal lab var code "Food code" lab var food_gr "Food group" lab var kkal "Calories of 1 kg" lab var q "Quantity" lab var v "Value" lab var cal "Calories of consumption" lab var price "Nationality prices" keep hh_code code food_gr kkal q v cal price b002 oblast expfact weight hsize decilc order hh_code code food_gr kkal q v cal price b002 oblast expfact weight hsize decilc save "OUT\Base_for_Basket" , replace 69 ********************************************************************** use "OUT\Base_for_Basket" , clear tab1 decilc *** SELECT decilec keep if (decilc>=2 & decilc<= 5) tab1 decilc [iw=expfact] collapse (sum)quantity=q (sum)totv = v (sum)cal (first) price kkal food_gr expfact [iw=expfact] , by (code) egen totalv=sum(totv) gen valshare = totv / totalv*100 recode valshare (0=.) label value food_gr food_gr table food_gr , contents(sum valshare ) format(%8.2f) gsort -valshare gen cumvsh = sum(valshare) sort cumvsh *keep if cumvsh<=90.0 keep if cumvsh<=97.0 *keep if cumvsh<=98.0 *keep if cumvsh<=99.0 ****************************************** egen totalcal=sum(cal) gen calreq=2100 *gen calreq=2230 gen c2100 =totalcal/calreq 70 gen q2100 =quantity/c2100 gen val2100 = q2100 * price gen cc2100=q2100 * kkal lab var cc2100 "calories in 2100 basket" lab var q2100 "quantities in 2100 Kcal basket" lab var val2100 "Cost in 2100 Kcal Basket" egen totvsh=sum(val2100) gen cc2100sh = cc2100 / calreq*100 gen val2100sh = val2100 / totvsh*100 tabstat cc2100sh val2100sh , by (food_gr) stat(sum) format(%8.1f) tabstat cc2100sh val2100sh , by (code) stat(sum) format(%8.1f) sort code keep code price q2100 cc2100 val2100 save "OUT\Basket2" , replace gen code1 = code export excel code1 code price q2100 cc2100 val2100 /// using "OUT\Basket2" , sheet ("basket2100") sheetreplace firstrow(variables) save "OUT\food_basket2100_ALL_97perc_bySTATA.xls" , replace **************************** FOODLINE collapse (sum)fld=val2100 (count)n=val2100 lab var fld "Food line day 2100 KCAL/day estimated with mean prices " lab var n "Number of products in the 2100 Kcal / day basket" format fld %8.2f gen xx=1 save "OUT\foodline.dta", replace tab1 fld n 71 *get file 'E:\Comp\Budget and monitoring\2013\Poverty\Basket.sav' . ************************** use "OUT\exp_inc" , clear gen xx=1 ***In this version New Food line (fld) created based 100% and 2230 Kcal merge m:m xx using "OUT\foodline" tab1 _merge ,miss drop _m* sort obl_reg merge m:m obl_reg using "OUT\CPI" tab1 _merge ,miss drop _m* gen pccddc = pccf /(kv * 30.42)/cpi+(pcc-pccf)/(kv * 30.42) gen pcfoodd = xf / (kv * 365/12) / hsize gen fshare1 = xf / totc *gen fld =66 gen xxx1 = fld - 0.10 * fld gen xxx2 = fld + 0.10 * fld *gen weightc = totc * weight *gen weightc = totc * expfact gen usl=1 if (pcfoodd >xxx1 & pcfoodd