**Table 7. Absolute convergence in location premia before and after sorting by municipality type (contd.)**

||**Urban**<br>**Rural**||**Urban**|**Rural**|
|---|---|---|---|---|
|**Panel F.**|**Chile**||||
||Annual location premium growth<br>2000/03-2015/17(before sorting)||Annual location pre<br>2015/17|mium growth 2000/03-<br>(after sorting)|
|γ0<br>b|-0.0172***<br>-0.0260***<br>(0.00144)<br>(0.00238)|γ0<br>ab|-0.0140***<br>(0.00202)|-0.0215***<br>(0.00282)|
|Obs.|<br> <br>201<br>98||<br>201|<br>98|
|R<sup>2</sup>|0418<br>0553||0193|0378|
|**Panel G.**|.<br>.<br>**Dominican Republic**||.|.|
||Annual location premium growth<br>2000/02-2014/16(before sorting)||Annual location pre<br>2014/16|mium growth 2000/02-<br>(after sorting)|
|γ0<br>b|-0.0317***<br>-0.0434***<br>(0.00499)<br>(0.00646)|γ0<br>ab|-0.0349***<br>(0.00564)|-0.0451***<br>(0.00553)|
|Obs.|<br> <br>51<br>64||<br>51|<br>64|
|R<sup>2</sup>|0.452<br>0.421||0.438|0.517|
|**Panel I.**|**Honduras**||||
||Annual location premium growth<br>2004/06-2017/19(before sorting)||Annual location pre<br>2017/19|mium growth 2004/06-<br>(after sorting)|
|γ0<br>b|-0.0400***<br>-0.0341***|γ0<br>ab|-0.0556***|-0.0421***|
||(0.00963)<br>(0.00370)||(0.0106)|(0.00387)|
|Obs.|<br> <br>33<br>210||<br>33|<br>210|
|R<sup>2</sup>|0.357<br>0.291||0.470|0.363|
|**PanelJ. C**|**osta Rica**||||
||Annual location premium growth<br>2001/03-2008/09(before sorting)||Annual location pre<br>2008/09|mium growth 2001/03-<br>(after sorting)|
|γ0<br>b|-0.00904<br>-0.0245***|γ0<br>ab|-0.0421***|-0.0218**|
||(0.0107)<br>(0.00886)||(0.0129)|(0.0102)|
|Obs.<br>|30<br>49<br>||30<br>|49<br>|
|R<sup>2</sup><br>|0.025<br>0.140<br>||0.276<br>|0.088<br><br>|
|Source: D’A<br>initial locati<br>characteristi<br>sorting, esti<br>characteristi<br>characteristi<br>all periods.<br>periods. In<br>metropolita<br>surveys.|oust, Galdo, and Ianchovichina (2022). Note:<br>on premium before sorting. These are the es<br>cs but are net of survey-year fixed effects as<br>mated with model (2.1). These are the estimate<br>cs (age, age squared, gender, human capita<br>cs) and are also net of survey-year fixed effect<br>In the case of Brazil, census data is used for<br>the case of Colombia, we use official aggre<br>n municipalities. For the rest of the countri|The resu<br>timated<br>in mode<br>d locatio<br>l, marita<br>s. In the<br>the perio<br>gates of<br>es, the a|lts are estimated based o<br>location premiums with<br>l (2.2).γ0<br>abrefers to the<br>n premiums controlling f<br>l status, household de<br>case of Mexico, the analy<br>d 2000-2010, while hous<br>value-added data and o<br>nalysis is based on SED|n model (2.3).γ0<br>brefers to the<br>out controlling for household<br>initial location premium after<br>or sorting based on household<br>mographics, and employment<br>sis is based on census data for<br>ehold data is used in all other<br>nly include one category for<br>LAC harmonized household|

Convergence occurred at different speeds across different types of localities (Table 7). In Mexico, convergence was fastest across metropolitan municipalities and slowest across large rural municipalities. In Brazil, convergence in labor productivity premia (i.e. location premia _before_ sorting) was fastest across the large urban and metropolitan municipalities, while convergence in place 26