Poverty alleviation is at the heart of our development philosophy. This has probably been the over-riding theme in all our Five Year Plans beginning from the '60s. Although poverty, per se, is difficult to define, many definitions have burgeoned of late – those living on less than $1/$2 a day (World Bank), those not having access to services/amenities (Amartya Sen), those not able to meet a specific nutritional food intake, vulnerable segments of the society, those without a voice, those without any power, etc. However, the fact of the matter is that poverty exists in our country despite its multidimensional facets.
According to the Poverty Analysis Report -2007 (National Statistical Bureau and Department of Planning), the Total Poverty Line (TPL) has been computed at Nu. 1,096.94 per person per month. Accordingly, any household or person under the TPL is classified as living in poverty. As per this report, 23.2% of our population (with a margin of error of 1.5% and a confidence level of 95%) live in poverty (Quite a stark revelation - this means that about one in every four Bhutanese lives in poverty). This figure was 31.7% in 2004 (based on Poverty Analysis Report -2004). Although we are showing signs of improvement on this front, we still have a long way to go to eradicate it altogether.
The question that immediately pops to one’s mind is how to eradicate/alleviate poverty? What are the factors that account for this? Will constructing more roads alleviate it? Will a national electrification project help? Will an open economic policy help? I was mulling over this and so I did a multiple regression analysis to at least better understand this esoteric subject. I’ve extracted most of the data from the Poverty Analysis Report – 2007, the Annual Information Bulletin of the Ministry of Works and Human Settlement and the Bhutan Living Standard Survey – 2007. Incidence of poverty (for the various Dzongkhags in %) was taken as the dependent variable and three variables (total road length in km in each Dzongkhag, the total literacy rate in each Dzongkhag and the % of electrified households in each Dzongkhag) were taken as the independent variables.
The result of the regression analysis shows that of the three independent variables, there is a direct inverse co-relation between literacy rate and poverty (i.e. higher the literacy rate, lower is the incidence of poverty). The other two variables (electrification and roads) do not have any impact at all on poverty (at least statistically).
The R square of the model is about 29% with a significant F value of 0.0165. Accordingly, this model is quite sound at least mathematically. To see the EXCEL sheet, click on this link - http://d01.megashares.com/dl/a02de26/Poverty corelation analysis.xlsx. The model hinges on the veracity of the data as it could be a GIGO (Garbage in, Garbage out) phenomenon so we need to be quite cautious before we jump to any conclusions.
However, the model just goes to bolster our tacit understanding that education plays a key role in the development process. Let us therefore earnestly promote education and literacy so that Bhutan is poverty free, if not in the near future, at least in the long run.
Hi Sunil,
ReplyDeletenice to go through your blog. Am glade to see a serious and analytical citizen in Bhutan.
Anyways coming to your study on poverty alleviation, I would suggest you to go through the several reports on MDGs (millennium Development Goals) by the UNDP. It is said that access to affordable energy services plays key role in poverty alleviation.
I find something wrong in the value of R square and the F value. Your R square value is very very low. For that matter in econometrics, adjusted R squared is preferred over R squared. As you said it depends on the data, but it also depends on the regression functional forms (equation) you choose.
I appreciate your personal interest.