We have all probably heard the old adage “Earthquakes don’t kill people, buildings do”. Recent temblors in Haiti and earlier in China have tragically demonstrated the truth of this. Out-of-date building codes and regulations, poor enforcement and badly-planned urbanization have all greatly increased the risk of urban disasters all over the developing world.
|Despite the careless mistake, this letter represents to me individual concern translated into action. (Click for a larger view)|
|Malaysia's New Economic Model proposes a number of strategic reforms.|
The objective of the NEM is for Malaysia to join the ranks of the high-income economies, but not at all costs. The growth process needs to be both inclusive and sustainable. Inclusive growth enables the benefits to be broadly shared across all communities. Sustainable growth augments the wealth of current generations in a way that does not come at the expense of future generations.
In the last blog we saw that most resettlers are broadly satisfied with the resettlement process and are positive and optimistic about their lives as a whole. But…how do they feel about their lives in comparison to the very different world they lived in before relocation? What are the changes they value or regret?
The respondents were asked directly how they felt about life now compared with life before resettlement. The overwhelming majority think that life has got much better, and that the vulnerable households are even more likely to feel this way than the non-vulnerable—no vulnerable households felt that life had got worse.
In last week’s blog I showed that, when we examine consumption—a commonly used measure of household welfare—the resettled households appear to be doing relatively well, and much better than before resettlement. But economic circumstances are just one small part of what really matters to households. In order to get closer to a broader picture of “well-being”, I’m going to present some evidence of how these households themselves view their lives overall and how they feel about the changes going on around them. I hope that this will provide new insights to the question of “how are the resettled people doing overall?”
|On the Nakai plateau, a large proportion of income is non-monetary. If we fail to account for this income, we grossly underestimate the living standards of most households. (WB photo)|
China’s massive stimulus spending has raised widespread concerns about local government finances. Local governments have ramped up infrastructure spending since late 2008, while they are also under pressure to spend more on health, education, and social security, for which they are in large part responsible. With monetary conditions likely to become tighter this year and land revenues possibly slowing down or even declining, local government finances may become strained.
At the heart of the concerns are local government investment platforms. These are state-owned-enterprise (SOE)-type entities set up to finance infrastructure construction and urban development—sometimes also called Urban Development and Construction Companies. Set up in part to circumvent rules prohibiting local governments from borrowing, their investment activities are mainly financed by land sale revenue and bank financing, often using as collateral land requisitioned from local residents.
There’s an extensive literature on dam resettlement, and according to much of this, the track record on rebuilding sustainable livelihoods is not great. For those interested, an excellent starting point is “The Future of Large Dams” by Ted Scudder. Ted has spent 50 years or so studying dams and resettlement, and has been on Nam Theun 2’s (NT2) external Panel of Experts since the early days of project preparation.
The broad reasons behind poor results in dam-related resettlement are intuitive: dams often require the resettlement of entire communities (rather than, for example, the resettlement of specific households to make way for a road), and dams may also significantly impact on existing livelihood opportunities, by, for example, flooding agricultural areas.