What is the link between Globalization and Poverty?

In my previous post, I noted that the narrator of the Globalization is Good documentary claimed that there was a strong correlation between how globalized a country is and poverty. Specifically, those countries that are globalized are likely to have less poverty. How does this claim stand up to empirical scrutiny? Well, one answer comes from the National Bureau of Economic Research (NBER) in Cambridge, Massachusetts.

“The evidence strongly suggests that export growth and incoming foreign investment have reduced poverty everywhere from Mexico to India to Poland. Yet at the same time currency crises can cripple the poor.”

Does globalization, as its advocates maintain, help spread the wealth? Or, as its critics charge, does globalization hurt the poor? In a new book titled Globalization and Poverty, edited by NBER Research Associate Ann Harrison, 15 economists consider these and other questions. In Globalization and Poverty (NBER Working Paper No. 12347), Harrison summarizes many of the findings in the book. Her central conclusion is that the poor will indeed benefit from globalization if the appropriate complementary policies and institutions are in place.

Harrison first notes that most of the evidence on the links between globalization and poverty is indirect. To be sure, as developing countries have become increasingly integrated into the world trading system over the past 20 years, world poverty rates have steadily fallen. Yet little evidence exists to show a clear-cut cause-and-effect relationship between these two phenomena.

Many of the studies in Globalization and Poverty in fact suggest that globalization has been associated with rising inequality, and that the poor do not always share in the gains from trade. Other themes emerge from the book. One is that the poor in countries with an abundance of unskilled labor do not always gain from trade reform. Another is that the poor are more likely to share in the gains from globalization when workers enjoy maximum mobility, especially from contracting economic sectors into expanding sectors (India and Colombia). Gains likewise arise when poor farmers have access to credit and technical know-how (Zambia), when poor farmers have such social safety nets as income support (Mexico) and when food aid is well targeted (Ethiopia).

The evidence strongly suggests that export growth and incoming foreign investment have reduced poverty everywhere from Mexico to India to Poland. Yet at the same time currency crises can cripple the poor. In Indonesia, poverty rates increased by at least 50 percent after the 1997 currency crisis in that country, and the poor in Mexico have yet to recover from the pummeling of the peso in 1995.

Without doubt, Harrison asserts, globalization produces both winners and losers among the poor. In Mexico, for example, small and medium corn growers saw their incomes halved in the 1990s, while larger corn growers prospered. In other countries, poor workers in exporting sectors or in sectors with foreign investment gained from trade and investment reforms, while poverty rates increased in previously protected areas that were exposed to import competition. Even within a country, a trade reform may hurt rural agricultural producers and benefit rural or urban consumers of those farmers’ products.

The relationship between globalization and poverty is complex, Harrison acknowledges, yet she says that a number of persuasive conclusions may be drawn from the studies in Globalization and Poverty. One conclusion is that the relationship depends not just on trade or financial globalization but on the interaction of globalization with the rest of the economic environment: investments in human capital and infrastructure, promotion of credit and technical assistance to farmers, worthy institutions and governance, and macroeconomic stability, including flexible exchange rates. The existence of such conditions, Harrison writes, is emerging as a critical theme for multilateral institutions like the World Bank.

Kenya, ethnic diversity, and fractionalization scores

Had you taken my Introduction to Comparative Politics class in the fall of 2007, you would have been faced with writing a paper in response to this:

There is much debate regarding the determinants of, and obstacles to, democratization. Are states that rely on natural resources for a large share of their GDP less likely to become and remain democratic? Does ethnic diversity present an obstacle to the democratization and democratic consolidation of a regime? Your term paper will answer one of these two questions either in the affirmative or the negative.

In addition to making the theoretical argument, students were asked to use Iraq and one other state to illustrate and support their argument(s). A few students chose to write on Kenya. I hope they go back and read their papers in light of the current situation in that multi-ethnic state.

Is Kenya ethnically diverse? How can we measure ethnic (or religious, or linguistic) diversity? There is a formula called the fractionalization index, which essentially gives us an idea of how diverse a state is. You can find a table–in Appendix A (which I have excerpted here) of over 100 states around the world with their corresponding fractionalization scores (in three categories), in this National Bureau of Economic Research (NBER) paper by Alesina et al. here The higher the value the higher the level of diversity. Notice the relatively low diversity of states like Poland and Norway and the high amount of diversity of almost all African states. Which is the best way to measure “diversity”? Ethnically? Linguistically? By religion?


Country
Date (Ethnicity Data)
Ethnic
Language
Religion
Afghanistan
1995
0.7693
0.6141
0.2717
Canada
1991
0.7124
0.5772
0.6958
China
1990
0.1538
0.1327
0.6643
Croatia
1991
0.3690
0.0763
0.4447
Kenya
2001
0.8588
0.8860
0.7765
Malawi
1998
0.6744
0.6023
0.8192
Mozambique
1983
0.6932
0.8125
0.6759
Nigeria
1983
0.8505
0.8503
0.7421
Norway
1998
0.0586
0.0673
0.2048
Portugal
1998
0.0468
0.0198
0.1438
USA
2000
0.4901
0.2514
0.8241