Recession and Inequalities – local findings

1. Recession and Inequalities – local findings Gergely Fábián – Péter Takács CONTENTS 1. Background and significance of the study 2. Recession, employment and economic activity 3. Incomes, income distribution, inequality 4. Social support system, social problems and benefit 5. Local measureof the quality of life - The FT Index Summary Local Organization of Social Services in Hungary Crises – Reactions – Changes Conference and Book launch 2012.11.15. Debrecen, DAB

2. 1. Background and significance of the study • In 2008, the Bureau of Social Affairs of Municipal Government of Nyíregyháza Mayor’s Office and • the Department of Applied Social Sciences of the University of Debrecen, Faculty of Health • launched a series of research studies to examine the citizens’ living conditions and to present • and analyze the changes over time.This survey is based on national and international examples • and utilizes the methodologyof household panel survey. The household panel survey collects • information on householdsin towns and their characteristics - changes are studied in the same • sample over time using the same questionnaires. • The household panel survey has used this standardized methodology both in the European Union • and Hungary: • European Community Household Panel (ECHP) - ran from 1994 to 2001 - was based on • a standardized questionnaire - interviewed the same sample population - 60,500 households – • topics including income, poverty, economic activity, and health. A renewal in the series of • surveys became necessary since much of the original survey population was lost to attrition • (moving out, death, other mobility problems). The original plans interviewing was stopped in • 2001. Statistics in Income and Living Conditions (EU-SILC) – continuation –under new title. • The EU-SILC basically provides two types of data: • cross-sectional (referring to a period of time or a point in time) and - longitudinal data (studying changes of the individuals in the sample followed over time at • annual intervals for 4 consecutive years). • TÁRKI’s survey Hungarian Household Panel (HHP)(later Household Monitor)- with same • methodology. • Nyíregyháza Household Panel (NHP) survey was based on national and international surveys. • It uses the questionnaires of ECHP, EU-SILC and HHP - therefore, local information • is comparable to that of Hungary as well as to other countries.

3. Methods The final version of the questionnaire grouped the questions into comprehensive sections: - Characteristics of the households (household composition, housing, income, etc.); - Economy activities (employment characteristics); - Health (health condition, long-term diseases); - Social relationships (family and personal relationships, extensity, intensity); - Elderly people (65 years of age and above); - Support systems – social problems (characteristics of natural and built-out social safety networks, allowances, opinion about the system of allowances and social care); - The Bureau of Social Affairs (clients’ opinion); - Biography (personal data about of the respondents). In selecting a sample, the methodology of HHP was used. Adults over 18 with permanent address in Nyíregyháza were placed into the sample pool. The sample populationwas chosen in a randomized way from the database of the Central Office for Public Administration and Electronic Public Service. In the first round, a database of 2000 persons was chosen. Later a database of 400 persons was added to provide the investigators with extra addresses to supplement the original sample if someone was unwilling to answer the questions. The representativeness was tested on the gender variable. All together 1848 usable questionnaires were collected to be analyzed (4866 persons - 4% of the total population of Nyíregyháza - such a large local population has not been studied before). The first wave was in 2008, while the second in 2010.

4. Sample - weighting The representative sample may be varied, since the investigators, just like in any other panel research, were instructed that the person most versed in household matters and most likely to be able to answer the questions should be asked first, then followed by the questionnaires asking information about persons. In a significant part of the households women answered to questions about the household. Table One Table One: Characteristics of the sample Similarly to any database the confounding factors may be corrected with weighting by to match the original incidence. Table Two Table Two: Characteristics of the sample – weighting Information on households is shown on the basis of the unweightedprimary database, since the respondent’s personal characteristics cannot be regarded as relevant information. The unit of analysis is not the person but the household itself. However, information on the individuals is taken from the weighted database.

5. 2. Results - Recession, employment and economic activity Chart One: Employment rate (%) (National and international data source: KSH, 2011a) The recent economic recession has greatly affected manufacturing which has led to a decrease in employment. When asked ‘Are you working at the moment?’ 54.9percent of the respondents gave a positive answer in 2008 whereas 54.5 percent in 2010. The employment rate is quite similar to the national one with its 54.5 percent among the 15-64 age group.The rate measured in the Nyíregyháza region exceeds the rate in the neighbouring Northern Great Plain Region (Észak-Alföldi Régió) and Szabolcs-Szatmár-Bereg County. The region had 44 percent, while 49.9 percent in 2008 and in the County it was 42.2 percent.The above mentioned rates lag behind the EU27 average which is 63.7 percent. However, a decrease in employment has been seen in the EU as well since 2008, when this rate was some 66 percent. Hungary and Nyíregyháza are lagging behind with some 9.2 percent.

6. Chart Two: The rate of employment of the citizens by gender, 2008-2010 (%) (Source: our own data) As for men and women a significant difference can be seen in employment in both periods, though a decrease is shown in the case of men. For womenhardly any changes can be seen, while among mensome decrease can be seen which also reflects the national tendencies. In the third quarter of 2010 the rate for women in Hungary was 51 percent, for men it was 61.2 percent. In the same period of 2008 the rate for women was also 51 percent while for men it was 63.9 percent, some 3 percent decrease has occurred. It can be explained, both locally and nationally, by the impact of economic recession on industry leading to a great number of laid off; and the loss of jobs affecting losing men in the first round. The difference in employment between men and women is rather significant. Losing jobs also happened in towns, though the number of laid off people and the rate of lagged behind other regions.

7. Chart Three: The number of laid off people between March and October 2008 (Source: GKI 2010) This map shows the business sphere in regions of high economic activity suffered the biggest fallin Hungary. Large export-oriented manufacturing factories and their suppliers, set up within the last 10-15 years in the Northern-Western part of Trans-Danubia, found themselves in a critical situation. Naturally, it does not mean that towns of the north-east region, Debrecen or Nyíregyháza, were not affected by difficulties, but to a lesser extent and the rate of unemployment is still much lower than in other regions of the country.

8. Chart Four: The rate of unemployment in the Nyíregyháza small region, 2010, (%) (Source: National Employment Service, 2011) The increase in unemployment in the small region shows the impact of economic recession, since the rate increased between 2008 and 2009 and has stayed steady since then. Chart Five: The rate of unemployment of small regions in Szabolcs-Szatmár-Bereg County, 2010, (%) It can be concluded that the employment situation of Nyíregyháza region became worse, the rate of unemployment has increased (from 6-7 percent to 9-10 percent), though comparing it to other regions the situation is still better. (Source: National Employment Service 2011)

9. Chart Six: The distribution of job holders of different sectors in the town, 2008-2010 (%) (Source: Own data) Due to the recession some inner transformation of employment is also visible. The loss of jobs in industry was compensated by the slight increase in agriculture and services, even though it slowed down still did not decrease the number and rate of unemployed people, however, the impact of the loss was buffered for a while. Chart Seven: Employment rate with regard to education, Nyíregyháza, 2008-2010 (%) Naturally, with regard to education significant differences can be seen and from earlier studies it widely accepted that the more educated you are the more favourableyour employability. As a matter of fact, some inner transformation can be seen in this field, too. Source: Own data

10. Employment rate and the education – reasons and consequences These changes follow the national tendencies, since according to the Hungarian Central Statistical Office (KSH) the number of employed people with college degree has decreased nationally, while there is an increase among university degree holders. The rate of employment for those with the lowest education lags behind all other groups. As a matter of concern for those who have completed only 8 grades of primary school or less is quite problematic, as it is written in the KHS report: “One explanation of the very low employment rate in Hungary in comparison with the EU is the extremely bad employment situation of people with low education. Only 27.2 percent of people with completed primary education were employed in Hungary in 2008, while the EU27 average was as high as 48.1 percent. Some 63.3 percent of the 15-64 age-group with secondary professional educational attainment worked in 2008 which lags behind the EU27 average with about 8 percent (71.3). Although the employment rate of people with higher educational attainment (79.5 percent) is closer to EU average, Hungary is the next to last in rank.” (KSH, 2011b). About 10% of those employed in Nyíregyháza (2008), apart from the wage or salary from their main job, had extra earnings from a second job. This rate rose to 13.4 percent in 2010. Though the difference is statistically not significant, it is worth focussing on this data since (having known the data above might not be surprising) the number of men with a second job exceeds that of women. It also can be regarded as a ‘trait of the educated ones’ because it is typical to those having higher educational attainment. The number of those with extra earnings (as well as opportunities) is extremely low among people with low educational attainment who, being unqualified, are often crowded out of this secondary job market.

11. 3. Results - Incomes, income distribution, inequality This survey, like other panel research studies, examined the characteristics and distribution of the net household disposable income, but has no information on the gross income or the ‘relation’ of gross and net incomes. In 2008, the average net household income in Nyíregyháza was 177.000 HUF, the medianincome 160.000, while in 2010 it was 184.000 HUF and the median remained steady. Though there is a slight growth in the monthly net household income, the steadiness of median already indicates the impact of the crisis, namely the ‘frozen’ wages or salaries. The increase could not keep up with the inflation, thus a decrease in real income was about 7 percent. The changes in income both in Hungary and Nyíregyházashow some income polarization. The proportion of poor and upper level groups increased at the expense of the middle class. A 2 percentage point rise in poverty was typical. In this sense one cannot talk about exclusive impoverishment but rather a growth of income inequalities which resulted in growing impoverishment of certain social classes, and weakening of the middle class, while the upper level group saw income gains; thus the social polarization. We can see it in next two slides.

12. Empirical estimate rates of income categories Hungary 2007-2009, % We study the middle class The categories: wealthy, upper-middle class, middle class, lower-middle class, poor This chart shows data for two years (2007 and 2009) in Hungary. We can see the elimination/depletion of the middle-class. The relative share of rich and poor is increasing. This means polarization in the population in the country. We can see it by GINI index too. upper-middle class lower-middle class poor wealthy - 5,0 1,0 2,0 0,0 2,0 Chart Eight Source: Hungary: 2007, 2009, TÁRKI

13. Empirical estimate rates of income categories Nyíregyháza, 2008-2010,% middle class We can observe the same in Nyíregyháza In 2008 and 2010. Remark/Note: Here we can see that Nyíregyháza have similar trends to the country. We can see the elimination / depletion of middle-class. The relative share of rich and poor is increasing. We believe that this is partly due to economic crisis. lower-middle class upper-middle class poor wealthy 0,8 1,3 - 3,7 - 0,4 2,0 Chart Nine Source: our survey

14. 4. Social support system, social problems and benefit Chart Ten: Whose help the citizens can count on when solving their problems – positive answers, 2008-2010 (%) (Source: Own Data) Having known and analyzed some impacts of the crisis, the question arises whose support the citizens can count on when solving their problems. Data and viewpoints concerning the natural support systems, social services, and social benefits was obtained by asking the question of whose help they can count on when solving their social problems. Data has shown that citizens having social problems typically count on the help of family members, followed by friends, acquaintances, then the elements of formal social safety nets, such as the municipality, certain social services, and the amount of this help cannot beneglected. Only a small number of people stated that no help was available.

15. The general opinion about social benefits - 2008 We applied the main component analysis; 4 factors were separated which, at the same time, made for 64.2 percent of the proportion explained. The first factor groups questions around what is labelled pro-benefits. Benefits are seen as a necessary form of support which could be given more frequently. Respondents who answer positively to this set of questions support benefits and totally refuse benefits to be stopped. The second factor relates to “swindlers taking undue advantage of the system”. Respondents who answer positively to this set of questions that not only people in need get benefit support but too many individuals apply for benefits who are not in need and are cheating the system and should be stopped. The third factor related to the position that benefits should be provided “in kind” and not in cash benefits. Respondents who answer positively to these questions, prefer that support be provided in kind and not in cash money. The fourth factor formed a grouping of statements that only those who are really in need reveal their correct financial situation and that real need should be provided. Then cash money could be given in larger amounts but only rarely.

16. The general opinion about social benefits - 2010 Having known the general changes over time, the citizens’ changes in preferences in two years’ time was also worth examining. The 2010 analysis was also carried out with main component analysis, 4 factors were separated which made for 64.2 % of the variance explained. It is quite probable that due to the economic and financial crises (laid off people, rise in unemployment, being in debts, people with mortgage, decrease in income, etc.) opinions went through apparent changes in the last two years. The most important and significant changes are the disappearance of two factors: the presence of swindlers and preference of benefit in-kind. As a matter of fact, these factors did not really disappear, they still exist but to a more modest extent. Basically all factors are in favour of the social benefit system, and “being in need and entitled to benefits” was more often emphasized. Opinions became restructured and more generalized which resulted in almost invisible differences regarding the acceptation or rejection of a factor by a certain economic or social class.

17. 5. Local measure of the qualityof life The FT Index Σ „The term quality of life is used to evaluate the general well-being of individuals and societies.” - wikipedia We present our local quality of life index: Index Fábián-Takács – FT index Questions of the quality of lifehavebeen focusedon developed societies at the end ofthe twentieth century. The basic idea is: The main objective of the whole society should be to increase the human quality of life, constantly. These require examination instruments and methods.So we can increase the objectivity of the researches.We can classifyquality of life indicatorsin the following ways. A, Objective and Subjective indicators. Per capita GDP (Gross domestic product); Life expectancy; Healthy Life Years; Personal satisfaction with the quality of life, with the health, with the economic status; etc. B, Profession-specific approach. Main areas where the studies startedareeconomics, sociology, psychology, health sciences, etc. Complex indicators were formed from these indicators. Indicators that we developed are complex indicators, based on mainly sociology. http://myviewsdrift.blogspot.com/2010/04/quality-of-life.html http://www.maps-inc.org/events/international-symposium-on-human-rights-and-quality-of-life-of-the-portuguese-speaking-communities-in-the-united-states-of-america-and-canada/

18. Methods We started the development of our local quality of life indicator in 2010.Our base was a research Nyíregyháza Household Panel (NHP) survey - the above mentioned. We developed two models. I. The first model is a simple aggregate model.2008. 1. model: QLI_1. & 2010. 2. model: QLI_2. This is the summary of the involved variables. The main results of this model is to develop and fix a variable-set– 23 questions. We used this variable-set in the second model. II. The second model was based on the Rahman-model (see quality of life literature). The Rahman-model uses eight groups of questions. Our 23 questions can be classified in seven Rahman-categories. We used principal component analysis (PCA) to establish the weight of the groups. We develop complex indicators(QLI_1, …, QLI_4 = FT Indexes) with weighted sum. 2008. 3. model: QLI_3. & 2010. 4. model: QLI_4. Remarks:The difference of the calculated weights are very smallin the two years. We present the four models and some results in the following slides – Contents: 2008. 1. model: QLI_1. - QLI_1. – ‘sub-area’ - QLI_1. – ‘rich’ - QLI_1. – ‘employment’ - QLI_1. – ‘language’ - QLI_1. – ‘car’ 2010. 2. model: QLI_2. – wrong way 2008. 3. model: QLI_3. - QLI_3. – ‘sub-area’ 2010. 4. model: QLI_4. - QLI_4. – ‘sub-area’ QLI_3 and QLI_4. – ‘sub-area’ - QLI_3. and QLI_4. – ‘rich’ - QLI_3. and QLI_4. – ‘education’ - QLI_3. and QLI_4. – ‘employment’ - QLI_3. and QLI_4. – ‘religion’

19. The research steps were the following: -selection of 30 questions -re-encoding - increasing human values represent increasing points -creating descriptive statistics -exclude four variables - many missing answers -Factor Analysis - exclude three variables - very different from the group -index calculation: summation – QLI_SUM_1 or QLI_1 We can see the descriptive statistics of the index on the right. We can see the histogram of the index on the left. The distribution of the QLI_1 variable is not a normal distribution Kolmogorov-Smirnov test p=0.000 and Saphiro-Wilk test p=0.000. The distribution is stretched to the right so we can understand the lack of normality. Now comes further investigations in relation to this index. 2008. 1. model: QLI_1model summary Chart Eleven

20. QLI_1. – ‘sub-area’ We can divide Nyíregyháza for 14 sub-area. We investigated the average of the variable QLI_1 in these sub-areas. The Kruskal-Wallis test does not require the normality of the variables. The Kruskal-Wallis test indicates a detectable difference(p=0.022). The Kruskal-Wallis test uses rank numbers: The first is „Sóstó” – rich area of Nyíregyháza. The last is „Huszártelep” – poor area of Nyíregyháza. Chart Twelve

21. QLI_1. – ‘rich’ We examined the perception of individual and family rich and the distribution of the QLI_1 index. The results are shown in this slide. We see, "the growing assessment of economic status" involves "increasing quality of life". The results of the statistical analysis are the following: A, ANOVA (Analysis of Variance) – no difference – p=0.279 B, Kruskal-Wallis test – difference – p=0.000 Analysis B, is the correct analysis due to lack of normality. The categories: wealthy, upper-middle class, middle class, lower-middle class, poor Chart Thirteen

22. QLI_1. – ‘employment’ We investigate the employment classification in the same way. The results are shown in this slide. The results of the statistical analysis are the following: A, ANOVA (Analysis of Variance) – no difference – p=0.547 B, Kruskal-Wallis test – difference – p=0.011 Analysis B, is the correct analysis due to lack of normality. The „disability pensioners” show the lowest quality of life. The highest part is the „dependents, supported by family” Chart Fourteen

23. QLI_1. – ‘language’ We investigate the „language knowledge” the same way. Those who speak foreign languageshas a higher quality of life. OR The high quality of life allows the language learning ‘Which came first: the chicken or the egg?’ t-test: p=0.025 Mann-Whitney-test: p=0.000 Chart Fifteen

24. QLI_1. – ‘car’ We investigate the question „Do you have a car?” the same way. Those who have a car have a higher quality of life. t-test: p=0.006 Mann-Whitney-test: p=0.000 Chart Sixteen

25. 2010. 2. model: QLI_2model summary We develop a similar model to the 2010 data. The histogram of QLI_2 index is on the slide. Since the reduction in number of elements was too large we have not continued this way for the analysis We developed a new model – the Principal Component Analysis (PCA) based model. Ø Chart Seventeen

26. 2008. 3. model: QLI_3model summary We explained the steps of model development previously. so here we discuss the descriptive statistics of model (QLI_3 or FT Index). We can seethe descriptive statistics and the histogram of the index in the slide. The number of cases was 1675. The average quality of life is 6.09. The distribution of the QLI_3 variable is a normal distribution. Kolmogorov-Smirnov test p=0.200 and Saphiro-Wilk test p=0.253 We can see the familiar bell-shaped curve in the diagram.The results of this model are more accurate. Chart Eighteen

27. QLI_3. – ‘sub-area’ We investigated the average of the variable QLI_3 in Nyíregyháza’ sub-areas. We used analysis of variance (ANOVA) to compare the averages. The analysis shows that the averages differ p=0.001 By the post-hoc analysis, Huszártelep has a significantly lower quality of life index. 2008. QLI_1 Chart Nineteen

28. 2010. 4. model: QLI_4model summary The PCA-based model in 2010 has good properties, just like in 2008. The distribution of the QLI_4 variable is close to normal distribution. Kolmogorov-Smirnov test: p=0.161 and Saphiro-Wilk test: p=0.023. The number of missing cases has grown highly. This is a warning sign concerning the following sampling. We will take care of sampling in 2012. Chart Twenty

29. QLI_4. – ‘sub-area’ We investigated the average of the variable QLI_4 in Nyíregyháza’ sub-areas. We used analysis of variance (ANOVA) to compare the averages. The analysis shows that the averages differ p=0.037 By the post-hoc analysis, Huszártelep has a significantly lower quality of life index, again. Chart Twenty One

30. QLI_3 and QLI_4. – ‘sub-area’ We can see the second (PCA-based) model (QLI_3, QLI_4) on the same slide: We can observe an increase of quality of life (standardized) in four parts of the city (from 14). The greatest reduction isin the following areas: Jósaváros II., Huszártelep, Bokortanyák, Újtelekiszőlő. We also examine the underlying causes. but We think we should pay attention to internal migration, in addition the economic crisis. Chart Twenty Two

31. QLI_3. and QLI_4. – ‘rich’ We compared the distribution of the perception of Individual and family rich in the two years. The quality of life of the poor (-0.19) and the rich (-0.2) is decreased. The middle class has not changed fundamentally. Quality of life in upper-middle class has increased. The categories: wealthy, upper-middle class, middle class, lower-middle class, poor Chart Twenty Three

32. QLI_3. and QLI_4. – ‘education’ We investigated the relationship between „education” and „quality of life”. We see, "the growing of personal education" involves "increasing quality of life". We can observe small changes in the city: The quality of life those have completed secondary education has grown. grammar school university college vocational school elementary school Chart Twenty Four

33. QLI_3. and QLI_4. – ‘employment’ We examine theemployment classification inthe same way. Here we can see even greater changes. We can see significant reduction in quality of life in many layers. employee own business on maternity leave social benefits, transfers disability pension unemployment Chart Twenty Five

34. QLI_3. and QLI_4. – ‘religion’ This figure presents the relationship "relation to religion" and "quality of life„. Change in two years is very high. The religious people's quality of life has increased. We are researching the causes ... the other believesateist ? uncertainty in religion religious people Chart Twenty Six

35. Summary The impact of financial crises can unquestionably be measured even locally, in Nyíregyháza. During the examined period, the number of unemployed people grew.During the second part of the study the rate did not change, so the situation did not get worse and kind of stagnation could be observed. Those who had lost their jobs before were still between jobs. Men apparently were affected to a larger extent. The difference between the number of employedmen and womenis still significant in Nyíregyháza. However, regarding employment and unemployment, the situation is still much morefavourable than in othersmall regions of Szabolcs-Szatmár-Bereg County. In addition, the government’s and local government’s restrictive measures resulted in a decrease in the number of people working in the public service. The impact of financial crisis on the citizens’ income has been rather unfavourable. Frozen income became a usual phenomenon, real income decreased by as much as 7 percent. The officially measured poverty ratein Nyíregyháza is almost 14 percent, which is two points higher than it was in 2008. All indices show a rise in income inequality, therefore not only impoverishment but income polarization can also be observed, which means that two tendencies exist parallel; impoverishment on the one hand and improvement of the well-off. Polarization involves a declining standard of living for the middle-class, so as a result the winners of the process have moved upwards while the losers have moved downwards. On the basis of TARKI research, it is also worth mentioning that Nyíregyháza has followed the national tendencies. Due to these changes the social benefit system has been restructured. Though the number of clients turning for help to the Social Bureau has not increased, more cash benefits were allocated than benefit in-kind. In line with it the respondents’ opinion about on the system of social benefit has apparently changed. The rationale for the formerly polarized opinions decreased, and less people objected to the necessity of social benefits, though opinions on the method of benefit provision diverted. On the other hand, people’s trust in official services, local government and other services has increased, in addition more of them share the viewpoint that services are able to help people in need. The current studies demonstrate the utility of the new FT quality of life index.

36. This was the Recession and Inequalities – local findings - in Nyíregyháza, in 2008-2010 ever since We have a lot of new research questions and We have somesmall answers. Thank you for your attention!