This means you need to argue why the initial shares are exogenous. They walk through a couple of simple examples to illustrate this in a two-industry or single time-period case, before proving for the general case. is to show that the Bartik instruments are numerically equivalent to using the initial shares (interacted with time fixed effects when multiple periods are used) as instruments in a weighted GMM estimation – the shifts only provide the weights and affect the instrument relevance, but not the endogeneity. 397 different industries and multiple time periods in the trade example).Ī first result in Goldsmith-Pinkham et al. But this becomes a bit harder to see and do with the Bartik instrument, since it is this weighted average of many different shifts (e.g. Typically, when someone presents an instrumental variable, they spend a lot of time motivating and defending the exclusion restriction. The predicted inflow of migrants into a destination is then a weighted average of the national inflow rates from each country (“the shift”), with weights depending on the initial distribution of immigrants (“the shares”). Where here the z are the lagged or “initial” distribution of the share of immigrants from source country j in location l, and m is the normalized change in immigration from country j into the U.S. local labor market) on the change in native wages in that location:Ĭhange in log native wages (l,t) = a + b*Immigration(l,t) + e(l,t)Īnd again we are concerned that immigration is endogenous, and the Bartik instrument is then In the immigration literature, a similar example is to look at the impact of immigration flows into location l (e.g. That is, the predicted exposure of a location to Chinese imports is a weighted average of how much China is exporting in general of different products (the “shift”), with weights that come from the initial industry composition in a location (the “shares”). Where the z now are lagged (“initial”) shares of employment in location l in industry k, and g high-incomeis growth of imports from China to other high-income countries. The Bartik instrument used by Autor et al. The usual concern here is then that import exposure is not exogenous, but may be correlated with other characteristics of a location that also affect manufacturing employment. Where the z are the start of the period shares of employment in location l in each industry k, and g US is a normalized measure of growth in imports from China to the U.S.
cities (locations denoted by l):Ĭhange in Manufacturing Employment Rate (l,t) = a + b*Import Exposure (l,t) + e(l,t) Let’s illustrate this first with a trade example, and then a migration example.Ī key question in trade has been the impact of Chinese imports on manufacturing employment in U.S. What is the Bartik or Shift-Share Instrument? (2018) look under the hood of this instrument, and provide econometric and economic reasons to re-consider how it has been used.
Two recent papers by Goldsmith-Pinkham et al. Few literatures rely so heavily on a single instrument or variants thereof”, going on to list 60 publications in the last decade alone. (2018) noting that “it is difficult to overstate the importance of this instrument for research on immigration. Development economists tend to see these instruments used most in the trade and migration literatures, with Jaeger et al. While it has been said that “ friends don’t let friends use IV”, one exception has been the Bartik or shift-share instrument.
0 kommentar(er)
