Please note, due to essential maintenance online transactions will not be possible between 02:30 and 04:00 BST, on Tuesday 17th September 2019 (22:30-00:00 EDT, 17 Sep, 2019). We apologise for any inconvenience.
To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Globalization has been one of the biggest driving forces of the last half century. There has been substantial disagreement about the impact that increased international integration has on income inequality. Though most agree that globalization positively affects economic output, it is no surprise that it leads to relative winners and losers within nations. The question that remains is where in the income distribution are these relative gains and losses occurring? We offer a broader picture of globalization's effects on inequality by using a dynamic compositional approach to test the impact of globalization and relative factor endowments on the composition of income. Using data from four countries, we model the effects of globalization on quantiles of the income distribution. Our findings suggest that globalization has substantial (and divergent) effects across income strata, and that these effects differ across nations based on relative factor endowments.
Across a broad range of fields in political science, there are many theoretically interesting dependent variables that can be characterized as compositions. We build on recent work that has developed strategies for modeling variation in such variables over time by extending them to models of time series cross-sectional data. We discuss how researchers can incorporate the influence of contextual variables and spatial relationships into such models. To demonstrate the utility of our proposed strategies, we present a methodological illustration using an analysis of budgetary expenditures in the US states.
Email your librarian or administrator to recommend adding this to your organisation's collection.