Monday, November 25, 2019

Attitudes towards the new banking regulations

The share of the public with loans from formal financial institutions doubled from 2011 to 2016 according to World Bank Group’s analysis based on Integrated Household Survey in Georgia. The July 2019 CRRC/NDI survey data suggests that about half of the population has a loan. To address perceived over-indebtedness, on 1 January, 2019 the National Bank of Georgia introduced new regulations, restricting lending without more extensive analysis of a consumer’s solvency. The analysis includes looking at an individual’s income, expenses and total obligations, and determination of debtors’ capacity to service their loans without significant financial difficulties.

But, what does the public think about the new regulations?

Almost half of the population approves of the new regulations, a third disapproves, and the remainder are uncertain or did not respond to the question. Considering that the Georgian Dream introduced the regulation it is unsurprising that Georgian Dream supporters have a more favorable view of the legislation than people who identify with the United National Movement (UNM). People who identify with liberal parties or support no party at all are less likely to approve of the new regulations compared to GD supporters. Apart from party support there are no significant differences between different social and demographic groups. Nor is there any significant difference in approval between people who have and do not have loans.

Although every second person in Georgia has a loan, the data suggests that having a loan is not associated with approval of the new regulations. However, support for different parties is. Those who identify with UNM, liberal parties or no party are less likely to approve the regulations compared to ruling party’s supporters.

Note: This blog post is based on a binary logistic regression analysis. The analysis includes having a loan or not, age group, settlement type, education level, party support, and employment status. The party support variable is coded as follows. The category “No party” consists of individuals that responded none or don’t know when asked which party was closest to them. The liberal group consists of New Rights, Bakradze-Ugulava - European Georgia, the Republican Party, the Free Democrats, the New Political Center – Girchi, the Movement State for the People, Political Platform - New Georgia, European Democrats, and Development Movement. The other grouping consists of the Alliance of Patriots of Georgia, Free Georgia, Democratic Movement – United Georgia, Left Alliance, Industry will save Georgia/Industrialists, the Georgian Conservative Party, the Georgian Labor Party, the Unity of Georgian Traditionalists, Tamaz Mechiauri for United Georgia, and Georgian Troupe. The data this blog post is based on is available here. The replication code for the above analysis is available here.

Monday, November 18, 2019

Knowledge of visa-free requirements falls since launch of scheme

Georgian citizens have been able to travel visa free within the Schengen zone for approaching three years, the result of several years of complex dialogue and policy reform. Despite the elapsed time, and a major EU-funded public information campaign, the results of the 2019 Survey on Knowledge of and Attitudes towards the European Union in Georgia (EU Survey) suggest that public knowledge of requirements for visa free travel have fallen since the scheme launched. Similarly, the same period has seen a large rise in the number of Georgian citizens being denied entry to EU countries, with Eurostat reporting over four thousand such cases in 2018 alone, up over a third since 2017.

For a Georgian citizen to enter the Schengen zone under the visa-free regime, the following documents are required:

  • A biometric passport;
  • Proof of financial means to cover expenses;
  • A return ticket;
  • Proof of address during stay (for example a hotel reservation).
Additionally, stays may not exceed 90 days in any 180-day period, and visitors under the visa free regime are not allowed to work.

In both the 2017 and 2019 waves of the EU survey, respondents were asked about their knowledge of requirements for documentation, length of stay, and right to work. The data suggest a marked decline in areas of knowledge asked about aside from the requirement for a biometric passport and the duration of stay. Falls were seen in awareness of the need for proof of address during the stay, proof of financial means to cover expenses, and a return ticket. In addition, there was a steep decline in knowledge of whether or not one can work during a stay.

To better understand who is more and less aware of the above requirements, a simple additive index describing an individual’s overall understanding of the EU requirements outlined above was developed. Correct responses to the above questions are counted as one point, resulting in knowledge scale from 0-6, with a score of zero representing no correct responses and six representing fully correct responses. Overall, across both waves, less than one percent of respondents answered all six questions correctly, with 13% answering none correctly. The average score on the index decreased from 2.6 in 2017 to 2.2 in 2019.

Scores on the index in 2019 are associated with the sex, age, ethnicity, employment status, education level, and internet use. After accounting for other factors, there is no significant differences in awareness between people living in Tbilisi, other urban areas, and rural areas. Younger people, men, people with tertiary education or higher, ethnic Georgians, the employed, and regular internet users are more likely to have better knowledge of the requirements for visa free travel on average, all else equal. By far the largest observed difference was for ethnic minorities, who are predicted to score one point lower on the knowledge index than ethnic Georgians.

This pattern is reflected in minorities reporting lower levels of awareness across all questions asked, except travel insurance. For example, 56% of ethnic minority respondents knew about the need for a biometric passport compared to 81% of Georgians survey – a 35 percentage point difference. Similarly large differences between Georgian and minority respondents were observed in correct responses relating to the right to work and financial requirements for entry, with minority respondents as a group respectively scoring 17 and 14 percentage points lower than their ethnic Georgian counterparts.

Although ethnic minorities are consistently less aware of visa free regulations, the overall decline in awareness appears to be driven by a fall among ethnic Georgian respondents. Between 2017 and 2019, there is a rise along some dimensions of knowledge of the requirements reported by ethnic minority groups. However correct responses from ethnic Georgian respondents have fallen in three of the six domains asked about.

While knowledge is lower among ethnic minorities, their knowledge has increased between waves of the survey along some dimensions. In contrast, awareness of the rules of visa free travel have been on the decline among the ethnic Georgian population.

With the available data, it is not possible to identify the source of the higher baseline (2017) scores for ethnic Georgian respondents vis-à-vis ethnic minorities, nor the driving factors behind their divergent changes over the past two years. This noted, this pattern would be consistent with the hypothesis that previous information campaigns may have been more effective in reaching ethnic Georgians than minority groups, and that public awareness has slipped as this issue has fallen from national headlines.

Substantial numbers of Georgian citizens have been denied entry to the EU since the introduction of visa-free travel, a process which generates significant financial costs and personal distress for the individuals concerned. In this context, it is concerning that the Georgian public’s knowledge of requirements for visa-free travel to Schengen zone countries has fallen since 2017 – suggesting a need for renewed messaging around the details of the scheme.

Furthermore, whilst there are some differences between knowledge across many demographic categories, ethnic minority groups display substantially lower knowledge than any other group. As such, for any renewed information campaign to be effective, it should take concrete steps to ensure the inclusion of ethnic minority groups.

Note: The data presented in the above blog post is available here. Replication code for the regression analysis is available here.

Monday, November 11, 2019

Government employees assess the work of the government better than the general public

The outlook in Georgia continues to be increasingly pessimistic, with more people reporting that the country is heading in the wrong direction. Similarly, performance assessments of government institutions have been on the decline in recent years. As recent CRRC analyses have highlighted, party identification, attitudes towards individual politicians, ethnicity, and Georgian language proficiency among ethnic minorities are associated with attitudes towards government. Analysis of the July 2019 CRRC and NDI survey suggests that working for the state is also associated with performance assessments. However, government employees in poor households and those in Tbilisi rate government performance significantly worse.

On the survey, 32% of respondents reported the government was performing well. In contrast, 60% said it was performing poorly. The remaining respondents stated either that they don’t know or refused to answer how they thought the government was doing.  On the survey about one in ten (12%) respondents said they work for a public agency or government, which is equivalent to one third of the respondents on the survey that reported having a job (33%). While 30% of people who do not work for government responded to the survey question saying the government was working well, 44% of state employees reported it was working well. Aside from state employees, people with tertiary education were more positive about government performance than people without, and people in the capital were less positive than in other settlements.

The significantly higher performance assessment among government employees remains after controlling for age, settlement type, wealth, sex, employment status, and education level. After adjusting for the previously noted characteristics, state employees are 14 percentage points more likely to report the government’s performance is positive compared to those without a job and 13 percentage points more likely than those with a job outside government. Similarly, the differences with education and settlement type remained after controlling for other factors. Other variables included in the analysis did not show significant associations with assessments of state performance.

However, digging deeper into the data to look at differences among different groups of government employees suggests that some government employees are more approving than others. Government employees that are in wealthier households (and presumably also earning larger amounts of money), are significantly more likely to have a positive attitude towards state performance: there is an 8% chance that the poorest government employees think government performance is positive compared with a 68% chance among the best off government employees. By comparison, performance assessments do not vary with wealth for those outside state employment.

Attitudes among government employees also vary based on what type of settlement they live in. In Tbilisi, government employees are most critical of the government, while in other urban and rural areas, they are significantly more likely to report they are positive about government performance. By comparison, the differences are much smaller between settlement types for individuals that are not employed or work outside of government.

While on average, people working for the government are more likely to think performance is better, government employees in Tbilisi and living in poor households are significantly less positive about government performance compared with both other government employees and the general public.

Note: The above analysis is based on two logistic regression analyses. The first contains sex (male, female), state employment (state employee, employed elsewhere, not working), wealth (number of assets owned), education level (secondary or less, vocational, or tertiary), age, and settlement type as independent variables. The dependent variable was positive (Very well, well) versus negative (Poorly, Very poorly) responses to the question, “Please tell me, how would you rate the performance of the current government?” The second analysis included the interaction of employment status with wealth as well as with settlement type. The data used in the above analysis is available here. The replication code for the above analysis is available here.

Monday, November 04, 2019

Drugs for desert? Biggest monthly household expenses in Georgia

The economy remains the main concern for people in Georgia. Together with the consumer price index and USD-GEL exchange rate rising, average household expenditures also have increased over the last couple of years. Meanwhile, according to recent data only 10% of the population has any savings. Although household expenditures have increased, what are people spending money on? The most recent CRRC-NDI survey from summer 2019 asked questions about household expenditures which provide a sense about what people spend money on in Georgia as well as who spends more on different categories of goods and services.

Most of the families in Georgia spend everything they earn. When asked about the largest monthly household expenses, everyday necessities came out on top, while leisure related expenditures were named by only a few. Food and utilities were named twice as frequently as any other expense. While this might not be a surprise, it is noteworthy that expenses on medicine came third, with more than one in three naming it as one of their largest monthly household expenses. Interestingly enough, some people, though a negligible number, still name travel, exercise, and entertainment related expenditures as the largest.

Note: Respondents were allowed to name up to three categories.

To understand how household expenditures vary between different demographic groups regression models were constructed. They included sex (male, female), age group (18-34, 35-54, 55 and +), settlement type (capital, large urban, small urban, rural), ethnic enclave status (primarily Georgian settlements, primarily minority settlements) and an additive index of ownership of different items, a common proxy for wealth.

When looking at the most common household expenses, food and utilities are on top regardless of people’s gender, age, the type of settlement they live in, or their economic situation. Nevertheless, the regression model showed that several demographic variables are useful in predicting who is more likely to have certain kinds of expenditures. For example, people who live in the capital  are less likely to name loans/installments/mortgages as their largest monthly expenditure compared to people in small urban and rural areas. People over 55 and people with lower economic standing are much less likely to name this expenditure as well, compared to people who are younger and people with higher economic standing. Also, minority settlements are less likely to name loans compared to Georgian settlements.

Similarly, there are some small differences in terms of education costs as well. People who are over 55 and men are slightly less likely to name education related expenditures compared to younger people and women. In households with higher economic standing, education related expenses are more likely to be mentioned among the largest monthly household expenditures.

One of the most interesting issues to look at is spending on medicine. It is third highest on the list, which is telling: a third of the population is spending as much or more medicine as food. There are also some interesting differences between various groups associated with medicine related expenses. People living in small urban and rural areas are more likely to name medicine among their top expenditures than those who live in the capital. Also, minority settlements are slightly less likely to mention medicine in their expenditures, than people from Georgian settlements. Similarly, younger people are one third as likely to name medicine, compared to people who are 56 or older. An additive index of ownership of household items shows that Georgians who own fewer things are more likely to say medicine is one of the top monthly expenditures in their household compared to people who own more. Differences between richer and poorer people hold even, when looking at people in different age groups. In all age groups people with higher economic standing name medicine less frequently than poorer people. Thus, older people and people with worse economic situations are more likely to name medicine as among their largest monthly expenditures. Interestingly, the same pattern is not present with medical care spending as opposed to spending on medication.

The data show that in all demographic groups in Georgia subsistence related expenses occupy the main position in household expenditures. Food, utilities, and medicine are the top expenditure categories for young and old, well-off and poor, men and women, and people in cities and rural areas. Though, there are of course some differences in expenditures between some demographic groups as well. Older people are less likely to have loans or education related expenses. Economically better off people are more likely to name these among their top expenditures. Moreover, older people and people with worse economic situations are more likely to name medicine related expenses, than younger people and those with better economic situation. Importantly, economic situation remains important even when controlling for age: better-off people are less likely to name medicine related expenses than the poor no matter their age.

Note: This blog post is based on logistic regression analyses. The dependent variable was a dummy variable for mentioning food, cost of utilities, medicine, medical care, or loans as the largest monthly household expense versus not naming this expense.  The independent variables included sex, age group, settlement type, ethnic enclave status, and an additive index of ownership of household items. The data used in the above analysis is available here. The replication code can be found here.