How many Tetri are in a Lari? The importance of municipal statistics for good governance

[Note: This post was co-published with Eurasianet and authored by Koba Turmanidze, CRRC-Georgia's Director.] 

The government of Georgia committed itself to collect and publish policy-relevant data in a timely manner under the Open Government Partnership. Yet while most ministries and state agencies are happy to provide national-level statistics, they often fail to break them down to the municipal level. 

As a result, if you think about it in monetary terms, the current system means that officials do not know how many tetri are in a lari. 

Reliable municipal statistics can contribute to good governance in several important ways. First, municipal-level data can let citizens assess the quality of state services they receive compared to other municipalities, or to the national average. Second, municipal-level data can help policy makers improve the targeting of programs, and therefore, spend public money more efficiently. Third, it can help both government and citizens evaluate the successes and failures of municipal governance.

The following scenarios highlight the benefits of comprehensive data on a local level: 

Imagine you want to move from one town to another for a better job. You consider moving with your spouse and a child of school age. However, your spouse does not want to move, arguing that your town has much better public schools than the new one. In such cases, it would help if you could look at municipal-level education data to see if schools in the two towns are similar or different in terms of the student-teacher ratio, exam scores, the success rate on national examinations, etc. 

Imagine you are a civil servant and are working with an investor to build a new factory in a municipality. You want the factory to be built in the municipality where its social impact will be highest. To persuade the investor, you use municipal statistics to demonstrate that the municipality of your choice has high unemployment, yet its labor force is younger and better trained than in comparable municipalities. 

Imagine you are an analyst in a think tank and your task is to advise the government on whether to extend a poverty reduction program or not. The government claims the program helped to reduce poverty by two percentage points nationwide, but you have reasons to suspect that the reduction happened in certain settlements, whereas in others the program had a negligible impact. You look at relevant data on the program and poverty statistics, and conclude that the program’s effect across municipalities was truly unequal. Importantly, it made no difference in the most economically deprived communities. Therefore, you advise the government to redesign the program to improve its impact on the communities with the highest poverty rates, before pouring more money into it. 

Unfortunately, we can only imagine the above. These three scenarios remain purely hypothetical, since, in Georgia, reliable municipal data is rarely available on education, employment and poverty. 

CRRC-Georgia’s repeated interactions with a multitude of state agencies over the past three years have uncovered at least three problems regarding municipal data. First, when municipal data of potentially good quality exists, it is often not processed and made available to the public. Second, if municipal data is accessible, its quality is often questionable. Third, municipal data often does not exist at all, since the responsible agency does not recognize its value, or is unable to collect it due to lack of relevant training. 

Below are three concrete cases that correspond to these three problems: 

Case 1: Until recently, the National Assessment and Examination Center (NAEC) maintained detailed and high-quality data on the results of the Unified National Exams (UNE) for many years. The data allowed one to see which municipality’s and even school’s students were most successful in the exams. Such data was not proactively shared on the Center’s website, but was available upon request. The situation changed when the Center introduced electronic applicant registration in 2011. Under the new system, an applicant’s place of residence and school was no longer recorded. However, the Center could still identify the municipality based on an applicant’s ID number. 

For the 2015 UNE results, NAEC processed the data this way and made the data file available on its website. However, when CRRC-Georgia requested the same data for 2016, the Center turned the request down, arguing it no longer processed data per municipality, and would not do so for our sake. As a result, it is no longer possible to analyze municipal- or school-level performance and map it as we did in this blog post. At the time, this map drew attention to large differences in educational attainment countrywide, including an important fact – that Unified National Exam scores in Upper Ajara were among the worst in the country. In part in response to this fact, AGL, a Norwegian company building a hydro-electric dam in upper Ajara created a tutoring program for students in the region to help them prepare for the exams. If the NAEC withholds such data, it will hinder the ability of interested parties to spot trends and develop remedial policies.

Case 2: The Social Service Agency (SSA) is a leading organization in the country in terms of providing access to comprehensive data on poverty and targeted social assistance at the national and municipal levels. Among other statistics, the Agency reports monthly data on applicants and recipients of social aid. The 2014 census data, however, casts some doubt on whether the SSA poverty statistics are trustworthy. 

The scale of mismatch between the agency’s data and the 2014 census results is evident from the chart below. Using Geostat’s population estimates, the agency calculates the share of the population registered for targeted social assistance in each municipality. The census was conducted in November 2014, so it is possible to re-calculate the share of those registered for targeted social assistance based on the census data and compare it with the agency’s estimates. 

Let’s take the extreme case of Lentekhi. The agency reported that 44 percent of the population applied for targeted social assistance. When the census data is used, the finding is that 89 percent of Lentekhi residents registered for social assistance. Thus, the SSA estimate was 45 percentage points lower than the actual percentage. The chart below plots the differences between the shares of the population registered for targeted social assistance, as calculated and reported by the SSA on the one hand, and updated calculations based on the 2014 census data on the other, for each municipality in November 2014. Overall, the agency underestimated the share of applicants by 14 percentage points, on average. However, publicly available data has yet to be adjusted based on the 2014 census.    

Case 3: In a number of cases municipal statistics do not exist. Measuring the scale of economic activity (level of employment by employment sector, total value added, etc.) in every municipality would require large-scale surveys that are both time-consuming and expensive. Geostat’s periodic Integrated Household Survey cannot provide this information, due to the cost that such a large sample size would entail. 

However, the Revenue Service (RS) under the Ministry of Finance of Georgia could help solve this challenge. Based on taxpayers’ IDs, the agency can provide information about the number of taxpayers, be it individuals or organizations, and amount of taxes collected in each municipality. This information would serve as a good proxy of economic activity by municipality. However, as the RS told CRRC-Georgia, it can only break the data down for regions. Officials claimed that breaking the data down further was not possible. 

Undoubtedly, the collection and analysis of municipal data requires additional resources. However, the three concrete cases highlighted above show that a little increase in awareness regarding municipal data could go a long way toward promoting better municipal governance in important ways. Investors could have clearer insight into the best investment destinations, for one. Civil society groups would also have better ways to assess the successes and failures of government actions. Citizens likewise would have a better idea of where their place of residence stands compared to other parts of the country, or the national average. Government could have better tools to ensure equal access to services in the country, or to achieve efficiencies in the provision of services. 

All of this is possible. Unfortunately, it is not reality. And as a result, the government doesn’t know how many tetri are in a lari.

Why the civil service? The civil service as seen by civil servants in Georgia

The civil service plays an important role in the development of a country. Thus the competence and motivation of civil servants matter. An online survey of civil servants conducted by CRRC-Georgia for NATO-PDP in December 2015 – January 2016 was one of the first attempts in Georgia to study civil servants’ perceptions of and attitudes towards their job. This blog post provides a brief overview of some of the findings, focusing on reported reasons for choosing to work in the civil service, the advantages and problems civil servants see with their jobs, as well as general assessments of civil servants’ motivation to work.

Slightly over a half of civil servants (56%) reported that the main reason they chose their job was an interest in working in the public sector. Forty-five percent hoped to improve their professional skills. The third most frequently named reason was a hope to improve the situation in their field. Importantly, a rather small share of civil servants (18%) reported a “stable job” as a reason for choosing to work in the civil service, and only 2% named an “attractive salary”.

About half of civil servants named the opportunity to contribute to the development of the country as the main advantage of working in the civil service. The opportunity to acquire new professional skills was the second most frequent answer, while the opportunity to make new connections, work one’s way up within the organization, and work with competent colleagues were named rarely.

Civil servants most frequently assessed the motivation to work of those in the civil service as average (50%). Positive assessments, though, are much more frequent than negative ones (36% vs 15%).

Note: To a certain extent, in response to most of the questions in this survey, civil servants tended to pick answers that can be considered socially desirable. Hence, social desirability bias is likely to have affected other responses as well, including assessments of other civil servants’ motivation to work. In order to avoid this bias in the case of this question, a very general wording was used: “How would you assess civil servants’ motivation to work?” This question measures civil servants’ reported perceptions of their colleagues’ motivation. To a certain extent, social desirability bias likely still influenced responses. However, this influence should be less than if the question had been asked about the respondent herself. 

Should the 50% of “average” assessments be considered a problem? Probably. The state invests financial resources in the improvement of civil servants’ professional skills, and the country, overall, is interested in a high productivity of their work. Undoubtedly, motivation encourages productivity. Thus, higher motivation will also lead to a more efficient use of public resources.

While trying to increase civil servants’ motivation in Georgia, it is important to consider the problems they face. The most frequently named problem is a lack of professionally competent civil servants. A fear of losing one’s job and poor infrastructure come in second and third, followed by a fair number of other problems.

Addressing these problems may improve civil servants’ motivation to work. As a result, the country would benefit from higher productivity among civil servants.

Proposed Reform Could Tilt Electoral Field Toward Incumbents

Irakli Kobakhidze, Speaker of Georgian Parliament, recently outlined proposed constitutional changes. Among them is a switch to a fully proportional electoral system, which civil society groups have long argued for. But this possible switch could tamp down on political competition.

This pending reform would produce two major changes besides the nixing of the first-past-the-post component: the first would re-allocate votes for parties that fail to clear the 5-percent electoral threshold (the percentage needed for a party to gain representation in parliament) to the leading party; the second, which is ironic coming from a party that came to power as a coalition, would prohibit parties from forming electoral coalitions. Taken together, some experts have cautioned that the proposed rules-changes could tilt the electoral playing field in favor of the incumbents, and thus would mark a setback for civil society.

In order to test the claim that the proposed reforms could skew democratic development in Georgia, and how the changes might affect future elections, the Caucasus Research Resource Centers calculated how seats would have been distributed among parties in the past three legislative elections.

The CRRC model looks at three variants, including the mixed system that Georgia currently uses, one which distributes seats through a coalition of a party-list vote, and first-past-the-post races. The CRRC model also applies the criteria that the parliament speaker proposed March 21, under which there is only the proportional, party-list vote, along with the re-allocation rule that gives the leading party the votes received by parties that fail to clear the 5-percent hurdle. In addition, the CRRC model shows how MP seats would be distributed on the basis of a proportional-vote system only with a 5 percent threshold, but without the re-allocation provision.

The CRRC model shows that in the 2008 and 2016 elections, during which there was only one strong party in the country, the incumbent party would have ended up with roughly the same number of seats under the current mixed system and the proportional-only system with the re-allocation rule. The incumbents would lose a significant number of seats, yet still retain a safe majority, under the system of proportional voting without re-allocation.

There would seem to be a genuine danger that the proposed rules changes would give the incumbents a decided advantage in a race in which two parties are otherwise evenly matched.

The 2012 election underscores this point. That race, which matched the Georgian Dream against United National Movement (UNM), was close and intense. When the results are run through the CRRC model, the parliament would have almost the same seat allocation under a fully proportional system as under the current mixed system. However, if the votes for parties that didn’t clear the 5-percent hurdle were re-allocated as Speaker Kobakhidze suggested, it would favor the winner, when compared to a proportional system without the re-allocation rule.

While the proportional system Georgian Dream proposes might appear to mark an improvement over the current system in some cases, under circumstances where there is a high level of political fragmentation, such as is currently the case, the changes would provide a significant boost to incumbent authority.

To highlight this phenomenon, a detailed look at the 1995 Georgian parliamentary elections is useful. In the 1995 vote, over 50 parties vied for seats in the legislature and 62 percent of ballots were cast for parties that didn’t clear the 5-percent hurdle, and thus were ineligible for representation in parliament. Had the electoral system in 1995 been the one that the Georgian Dream is currently advocating, rather than 107 seats, the Citizens Union of Georgia would have won 187 seats in what was a 235-member legislature.

The Georgian Dream, which came to office as an electoral coalition, is also proposing a ban on electoral coalitions. This rule in combination with wasted votes being allocated to the winner is likely to further benefit incumbents.

Each party would either have to run independently, or form a new political party to run together in elections. In practice, this rule obstructs electoral consolidation, which often promotes the formation of stable parliaments in a genuinely pluralistic system. If implemented in its current form, it is likely the new rule would increase the number of seats in parliament awarded to the party with the largest share of the vote.

Even without this change, Georgia’s political parties have already been fragmenting in recent years. The Georgian Dream was once a six-party coalition, but now consists of a single large party (the Georgian Dream) and two minor parties (the Conservatives and the Social Democrats). The remaining parties that formed the original coalition are now independent. Meanwhile, the United National Movement (UNM) has broken up into a number of parties, starting with the 2012-2016 parliament, when UNM members split to form Girchi and New Georgia, and more recently, when a majority of the party’s MPs broke off to establish the Movement for Freedom - European Georgia.

Another matter of potential concern is the question of dark money in the electoral system. It’s possible that incumbents, acting through shadowy intermediaries, could potentially provide assistance to small parties in order to draw votes away from potential competitors. This strategy has already been part of political competition in Georgia. When the UNM controlled parliament, for example, the Christian Democrat party was effectively a satellite party. This strategy may have also been at play in some of the splits from the United National Movement. Both Girchi and New Georgia, after splitting off from the UNM, were able to immediately open up a large number of offices throughout the country. It remains unclear where the money came from to afford such a significant expense.

The proposed electoral reforms could face opposition from civil society, and President Giorgi Margvelashvili could veto them. However, the Georgian Dream holds a constitutional majority in Georgian parliament, meaning it could overturn a veto, as MPs did in response to past vetoes.

For Georgia’s democratic political system to become stronger, the consolidation of parties, not further fragmentation, is needed. The proposed changes to the electoral system are unlikely to encourage consolidation, and instead seem to provide lots of incentives to encourage the continued fragmentation of the political landscape. At best, the proposed changes are two steps forward and one step back. At worst, they could squash political competition in Georgia.

To view the data used in this article, click here.

[Note: This post was originally published on Liberali in Georgian and on Eurasianet in English. Dustin Gilbreath is a Policy Analyst at CRRC-Georgia. David Sichinava is a Senior Policy Analyst at CRRC-Georgia.]

Safer transport options for passengers: Recommendations

In the previous blog posts in this series (see here, here, here, and here), we reported the design and results of a randomized control trial on minibus safety in Georgia. In this blog post, we provide recommendations for the Government of Georgia based on the results of the experiment. First, we recommend that the Government:

• Create an anonymous minibus monitoring program

Telling minibus drivers that they are being monitored for safe driving and may be punished for safety-violations may lead to safer, less distracted driving. The results of the experiment suggest such a program would likely be effective. This suggests that the government has an opportunity to implement a small program, which could have an important impact on making minibus driving safer and reduce the number of accidents related to dangerous driving. If the government does in fact implement such a program, we recommend that the program:

• Fine unsafe minibus drivers

While our experiment could not test the impact of a potential fine for unsafe driving, the behavioral economics literature suggests that individuals are roughly twice as likely to avoid losses as they are to seek out gains. Given that losses have stronger effects, this is also likely to ensure that there actually is an overall effect of the program. Importantly, this may offset costs associated with the program.

• Publicize the program in the lead up to implementation

Minibus drivers should be made aware of the program. If they do not know that they could be monitored, the program will be slower to encourage safe driving.

• Select routes for monitoring randomly on a daily basis

This would help prevent drivers from driving artificially safely in order to avoid a fine on a trip when they believe a monitor to be present based on prior information.

• Use few monitors, and change them regularly

The success of such a monitoring program relies on monitors being able to maintain their anonymity. In a country like Georgia, with a small population and dense social networks, maintaining monitor anonymity will be challenging. Hence, the government should consider drawing monitors from one of the civil service agencies with a relatively large staff. The Ministry of Internal Affairs Patrol Police Department would likely be an ideal institution given that patrol police officers are already aware of road safety legislation, and there are a sufficiently large number of officers who could participate in the program on a rolling basis.

The above recommendations are likely to help improve the safety of marshutka driving in Georgia. With less distracted and dangerous driving on Georgia’s roads, the high level of accidents, injuries, and fatalities on roadways are likely to decline. Ultimately, such a policy is likely to lead to safer transport options for passengers.

Safer transport options for passengers: Immediate, lasting, and contagion effects

As the last two blog posts in this series have described, CRRC-Georgia carried out a randomized control trial on minibus safety. This post reports the results of the experiment, and specifically whether there were immediate effects of being monitored, lasting effects on drivers which were monitored, and whether drivers who were not aware that they were being monitored ended up driving safer as a result of contagion effects i.e. drivers talking to each other about the monitoring. Overall, the results suggest that a small minibus monitoring program is likely to decrease dangerous driving behaviors in Georgia.

Did active knowledge that an individual was being monitored matter? To find out, we compare the control group from the first wave with the treatment group observations from the second wave. The statistical analysis suggests that drivers made 1.4 fewer calls per trip, smoked 1.5 fewer cigarettes, made 2.2 fewer illegal passes, and 2 fewer aggressive maneuvers on average. Overall, in the group that was directly aware that it was being monitored, there were 7.2 fewer incidents on average per trip. Other measures such as speed and seat belt non-use did not decline or increase in a statistically significant manner.

Based on these statistics we can conclude that direct knowledge of being monitored lead to fewer distracted and other dangerous driving behaviors. However, did these effects last? To understand whether direct knowledge of being monitored and that one would again be monitored had a lasting effect, we compare the results of the drivers who knew they were being monitored to roughly two weeks later when they did not know they were being monitored. In this case, a lasting effect is present if there was a statistically significant decline in a behavior in the first round of monitoring, and no significant change in the second round of monitoring.

Data analysis suggests that drivers who knew they would be monitored maintained lower levels of smoking, telephone conversations, illegal passing, aggressive maneuvers, and number of incidents overall. However, it is important to note that the drivers did drive less safely than they did when they were aware of being monitored. The differences between waves are however not statistically significant, suggesting that drivers did in fact drive safer roughly two weeks after being aware that they were being observed and would be again.

When it comes to contagion, the results of the statistical tests uniformly show no significant change except for in speed. Given that this is one in ten tests and that there was no significant effect from the first wave of monitoring on speed, we suspect that this test may have been found to be significant based on chance or other extraneous factors.

The table below presents the average treatment effect on the treated for each indicator with Abadie Imbens standard errors in parenthesis. On the line following the indicator name, 95% confidence intervals are provided. One star indicates that the estimate has less than a one in twenty chance of being due to chance alone. Two stars indicates that the estimate has less than a one in one hundred chance of being due to chance alone, and three stars indicates that the estimate has less than a one in one thousand chance of being due to chance alone. No stars indicates no significant difference.

Based on the above statistics we can conclude that direct knowledge of being monitored led to fewer distracted and other dangerous driving behaviors. However, the combination of the lack of significant contagion effect in combination with the increased but not significant increase between treatment groups suggests that a comparison of descriptive statistics is important to gain a sense of whether there was a lasting effect. The table below shows the average of each indicator given above in each group of the experiment.

The average indicator for the third wave of treatment and control group observations are quite similar. The similarity between means suggests one of two things. First, there may have been a small contagion effect since the levels are lower than in the first round control as well as a lasting effect that was not statistically significant. Supporting this conclusion is that both second wave means are lower than the mean in the first observation of the control group. The second possibility, however, is a lack of lasting effect and that an external factor caused the lowering of indicators during the third wave of observation.

Overall, the results of the experiment suggest that direct knowledge of being observed lowers the number of dangerous and distracted driving behaviors by a significant amount. This experience may have a lasting effect on drivers. What does this mean for the policy we proposed in the previous post, and what can the government do based on this information? In the next post, we provide recommendations for the government based on the information presented in this post.

Safer transport options for passengers: A Nudge on Marshutka Safety

Within the auspices of the Safer Transit Options for Passenger’s project, CRRC-Georgia carried out a randomized control trial, attempting to test whether a small policy change could make a large difference to minibus driving safety in Georgia. What was that small change, and how did we measure whether it might matter? This blog post provides an overview of both the policy to be tested and how we measured whether it could work.

The policy

A potentially simple way of decreasing distracted and other dangerous driving practices among minibus drivers is to use anonymous monitoring combined with penalties for dangerous driving. Under such a policy, the government would hire a small number of monitors to ride on randomly selected minibuses throughout the country without informing the drivers. After the ride, the monitor would report on any serious road safety violation as well as the number of distracted driving activities and safety violations carried out. If the driver committed serious traffic violations fines could be given out.

This policy would encourage safe driving and discourage dangerous driving. Moreover, it would require a relatively limited amount of funds from the government. Assuming that only 10 monitors are engaged in the program and they work 200 days a year, they could easily make up to 4000 trips, covering the majority, if not every, minibus route in the country. By randomly assigning monitors to different routes, minibus drivers would not be able to predict whether they are or would be monitored on any given trip. Hence, with the credible risk of being fined, drivers would likely drive safer.

Testing the theory

While the above policy, in theory, is quite sound, practice and theory often diverge. Hence, in order to test whether the policy would in fact be effective, CRRC-Georgia carried out a randomized control trial, which tested whether the knowledge that drivers might be monitored for safe driving and drivers could receive an award might improve their driving in late 2016.

Randomized control trials are a research design that comes from medical research. When doctors are attempting to understand whether a new medicine is effective, they randomly assign whether a patient gets the new drug or a placebo. Randomization is used to try to eliminate whether confounding factors that may make the medicine (in)effective for different individuals are distributed equally between the groups that receive the medicine and the placebo. Following this logic, for the STOP experiment, we randomly assigned minibus drivers to either a treatment or control group.

While in medicine, a treatment is, well a medical treatment, in our case information and action functioned as treatments. Minibus drivers that were assigned to the treatment group were told that they were being observed on a number of driving safety measures, and that the safest drivers would be awarded a gas voucher.  Importantly, as an NGO, we could not make a credible claim about the issuance of fines. Hence, we were unable to fully test the effectiveness of the proposed policy above. Notably, we would expect the issuance of fines for unsafe driving to be a stronger incentive for individuals to drive safer, because people are usually more averse to losses than prone to seeking gains, a phenomenon psychologists refer to as loss aversion.

Between September 20th and October 20th, CRRC-Georgia interviewers observed 360 minibus trips in three waves of observation. In the first wave of observation, minibus routes which had been randomly selected were observed without telling the driver that they were being monitored. This group forms the study’s control group. In the second wave of observation, routes assigned to the treatment group were observed. In the third wave of observation, observers returned to both the control and treatment minibuses for anonymous observation.

Minibus drivers in the treatment group who drive along similar routes were informed that:

1. Their trip would be monitored for safety along a number of dimensions;
2. A monitor would return in the coming weeks and monitor their driving as well as other drivers again without telling them;
3. If they were found to be among the safest drivers, they would be rewarded with a petrol voucher.

Over the course of the trip, monitors in all three waves recorded how many times drivers:

1. Smoked;
2. Text messaged;
3. Had telephone conversations;
4. Did not wear a seat belt;
5. Passed in areas it was not legal to do so;
6. Made other aggressive driving maneuvers;
7. Behaved aggressively towards passengers;
8. Behaved aggressively towards non-passengers.

Monitors also recorded stop and travel time, whether additional seats were added to the bus, whether passengers stood during the ride as well as a number of characteristics about the state of the minibus. Following the trip, the average speed of travel was calculated.

The above research design allows for a number of comparisons. First, by comparing the first wave control group to the second wave treatment group, we can test how the direct knowledge that one is being observed for safe driving effects driver safety. Second, by comparing the second wave treatment group to the third wave treatment group, we are able to tell whether the knowledge that one might be monitored again in the near future would have some lasting effect. Third, by comparing drivers in the first wave control group to drivers in the third wave control group, we can tell whether there was a contagion effect from the experiment i.e., whether the treated drivers talked to the non-treated drivers about the monitoring and they in turn also became safer drivers.

To test for the above types of effects, we used multivariate matching with genetic weights and calculations of average treatment on the treated (ATT). For readers interested in these methods, please see here. Using these methods, we calculate both the size of an effect and the probability that it emerged by chance alone.

In the next post in this series, which will appear tomorrow, we report the results of the experiment.

Safer transport options for passengers: Distracted and dangerous driving among minibuses

Over the course of this week, CRRC-Georgia will publish the results of a randomized control trial on minibus safety. While the introduction post to this series highlighted that Georgia’s roadways are dangerous, just how dangerous minibus drivers are has largely been left undescribed. As part of the Safer Transport Options for Passengers project, CRRC-Georgia collected data on dangerous and distracted driving practices on minibuses. This blog post reports descriptive statistics about distracted and dangerous driving from drivers unaware that they were being monitored.

While estimates do not exist for Georgia for how many accidents are caused by distracted and other dangerous driving practices, they are very likely contribute to the high fatality rates on the roads in Georgia. When it comes to distracted driving alone, studies from other contexts suggest that a distracted driver’s chances of being in an accident are four times higher. Cell phone use is associated with increased incidence of accidents among both novice and experienced drivers. Importantly, commercial vehicle drivers are no exception, with increased risk of accident associated with distracted driving among commercial drivers.

Overall, among minibus drivers unaware of being monitored, 96% engaged in some form of poor driving behavior, with illegal passes being the most common, followed by making telephone calls, and other aggressive driving maneuvers. Notably, few drivers were observed text messaging while driving. While we cannot claim that the data presented here is representative, for technical reasons, it is highly suggestive of the high prevalence of dangerous and distracted driving practices among minibuses on Georgia’s roadways.

The graph below presents the average number of times a driver engaged in a dangerous driving behavior as well as the maximum value for each indicator. Although the minimum value was 0 for each indicator, the high values for the maximums suggest that some drivers are particularly prone to dangerous driving, with as many as 62 dangerous events observed in a single trip.

The above statistics suggest that distracted and dangerous driving are common problems among minibus drivers in Georgia. In order to help ameliorate the situation, CRRC-Georgia tested whether a simple minibus monitoring policy would decrease the prevalence of dangerous and distracted driving. In subsequent posts in this series, we report the results of the randomized control trial, which suggest that such a program would in fact be effective.