The literature on corruption measurement practices show a gradual shift from the use of global aggregated, expert generated, primarily perception based corruption measures to the increasing use of national/local level, disaggregated, and based on the experience of the victims of corruption. This shift has come, as NORAD study report (2011) mentions, “the battlefield where this war (against corruption) is lost or won remains national”. Corruption may be a global problem but fights against it are waged at the national and local level.
Unfortunately, unlike in other countries where state and non-state agencies are actively engaged in measuring corruption on a regular basis, we do not have such a system in practice. With the availability of donor support, some surveys have been done in the past, but in the absence of regular monitoring and reporting, their use and impact is limited. When it comes to measuring corruption, we have so far relied on global aggregated measures published by the multi-lateral agencies like the World Bank or international anti-corruption agencies like the Transparency International. Our perceptions on corruption are primarily based on media reporting on corruption scandals. Policy makers also tend to assume corruption to be a known problem, therefore, you do not need organizing expensive surveys and studies. In the absence of hard data, anti-corruption policies and programs become nothing more than a wishful thinking.
Since 1998/99, in its annual report, CIAA has been publishing district-level and regional level corruption complaints lodged at District Administration Office (DAO) and Regional Administration Office (RAO). The data base can be used to understand corruption patterns and trends in corruption situation at the local level. However, due care must be made in interpreting the data. Simply by looking at the numbers of complaints lodged one cannot truly measure the extent of corruption at the local level. An increase in corruption complaints may simply be due to increase in people’s awareness of corruption problem; it could also be due to efficiency or access to the administration. A district with high economic activities (big allocation of budgets) will tend to have higher level of corruption compared to districts with low economic activities (small allocation of budgets). However, in the absence of any information, the reported figures on corruption complaint can be fairly used as a proxy measure of corruption at the local level. Another issue that is worth mentioning here is that, simply looking at the numbers (or frequencies) does not reflect the intensity of the problem. A district having a single reporting of corruption running over billions of rupees cannot be equated another district having reporting on hundreds of cases of petty corruption. The number of corruption complaints does not capture these issues. Keeping these caveats in mind, still some inferences can be made out of the available data.
Besides, corruption complaints at the centre, CIAA annual reports provide a data set of complaints lodged at 75 DAOs and five RAOs by (1) corruption complaints and (2) improper conduct. The data set also includes complaints resolved, forwarded to CIAA for its action and complaints pending for settlement. The data set is available from 1998/99 to 2010/11 covering a period of 13 years. For our analysis we ignore here regional level data. We also ignore the difference between corruption and improper conduct and merge them together to represent a total data set for corruption complaints. Please refer to Annex 1 for the data compilation.
Trends in corruption reporting
Graph 1 presents the total number of complaints lodged at 75 DAOs in Nepal for 13 years from 1998 to 2010. A couple of interesting observations can be made from the graph. First, the number of complaints peaked in 2005. This was the time when King Gyanendra usurped state power. Since anti-corruption was one of the agenda of the regime, there is a surge in corruption reporting at the district level. Corruption reporting also increased in 2002 when CIAA was very much in the limelight after the enactment of the new anti-corruption law. Second, corruption reporting dipped down immediately after people’s movement in 2006. This must be due to people’s lack of trust with DAOs in taking action against corruption complaints. Third, corruption complaints at DAO are increasing after reaching a lowest point in 2007. The increase is commensurate with media reporting of increase in local level corruption with the introduction of all party mechanism to manage local bodies.
High and Low Corruption Reporting Districts
If 75 districts are to be ranked based on total number of corruption complaints lodged at DAOs, the ten top-most corruption reporting districts turn out to be (1) Bara, (2) Lalitpur (3) Dhanusa, (4) Saptari, (5) Mohatari, (6) Parsa (7) Siraha, (8) Rupendehi (9) Banke and (10) Kathmandu. It is interesting to note that saving Lalitpur and Kathmandu, all eight districts are in southern Terai plains. Our President is drawn from Dhanusa district. If one goes down to the list of top twenty, more districts from Terai plains pop up on the list. This essentially implies corruption to be a serious problem in Terai plains compared to districts in the Hills and in the Mountains. Refer to Graph 2. There can be many underlying factors like easy access, more economic activity, and high awareness or even could be due to higher level of corruption in Terai. Actually, our interest is in the last factor.
At the bottom of the list one finds districts like (1) Manang, (2) Bajhang, (3) Mustang, (4) Pyuthan, (5) Rolpa, (6) Taplejung, (7) Makawanpur, (8) Okhaldhunga, (9) Bhojpur and (10) Dadheldhura. Except Makawanpur, all of the districts are either in Hills or in Mountains. The economic activities may be low in these districts impacting on low incidence of corruption. This must have impacted on the low reporting of corruption.
When district wise corruption complaints were juxtaposed with district-wise socio-economic development composite index used by Poverty Alleviation Fund, the correlation was found to be positive but statistically not significant. This is to imply that a district’s standing on socio-economic development has no relation with corruption reporting situation. Districts with high or low on socio-economic development index could have equally high or low reporting of corruption. Corruption seems to have thrived both in rich and poor districts in Nepal with the exception of Terai districts.
Regularity of Corruption Reporting
In terms of regularity of corruption reporting, that is, the districts which have reported corruption complaints throughout thirteen years (1998-2010), there are only five districts on the list. These included:
(4) Chitwan and
Three of these districts, namely, Mohattari, Dhanusa and Rupandehi also turn up as the most corruption reporting districts of Nepal. Factors like awareness and incidence of corruption must have influenced corruption reporting.